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[ "<title>Background</title>", "<p>Carcinoid tumours (CTs) are the most common neoplasm of the appendix [##REF##9510314##1##,##REF##10080850##2##]. The overall incidence of carcinoid tumours has been estimated to 1 to 2 cases per 1000 appendectomies in surgical specimens [##REF##1157019##3##]. CTs are discovered usually during the course of another procedure. In children the tumour is usually smaller than 2 cm in diameter [##REF##8495322##4##]. A carcinoid tumour of the appendix may cause pain in lower abdominal quadrant, similar to the pain of acute appendicitis. The diagnosis should be confirmed histologically.</p>", "<p>In our case a carcinoid tumour in the tip of the appendix presented as acute appendicitis. It was the only appendiceal tumour throughout a total of 1540 appendicectomies, performed during the last eighteen years.</p>" ]

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[ "<title>Discussion</title>", "<p>Carcinoid tumours of the appendix are relatively uncommon neoplasms. Although are considered rare pathology in children, these are the most frequent tumours of the gastrointestinal tract in childhood and adolescence [##REF##2262861##5##]. They are usually benign neoplasm and the uncommon occurrence of metastasis is related to the primary tumour size and depth [##REF##3696178##6##].</p>", "<p>The reported incidence of appendiceal carcinoids in several studies ranges from 0.08 to 0.7% in surgical specimens [##REF##2262861##5##, ####REF##3696178##6##, ##REF##6690264##7##, ##REF##11215778##8####11215778##8##]. Willox in 1964 suggested that 0.2–0.5% of surgically removed appendices in children contained CT [##REF##14117766##9##]. Doede et al [##REF##11215778##8##] and D' Aloe et al [##REF##11452407##10##] estimated that CTs of the appendix occur in 1:100,000 to 169:100,000 children, respectively. These data illustrate the rarity of CT and explain the low rate of suspicion of this disease [##UREF##0##11##]. The tumour is more common in white females with a mean age of 12 to 13 years [##REF##11527175##12##,##REF##12297915##13##]. Some authors have been reported CT in children 3 years of age.</p>", "<p>The clinical presentation of the appendiceal carcinoids is similar to that of acute appendicitis, but in some cases the disease is incidentally found during surgery performed for another diagnosis or problem. Recurrent episodes of abdominal pain were reported in many cases may indicate partial obstruction of the appendiceal lumen by a tumour [##REF##11527175##12##]. In two reported cases the patients presented with clinical signs of peritonitis without previous episodes of acute abdominal pain [##REF##11527175##12##]. Symptoms of the carcinoid syndrome as flushing, diarrhoea, cardiac disease have been rarely reported and usually associated with liver or retroperitoneal metastases [##REF##11215778##8##,##REF##14166209##14##]. In these cases an increased urine excretion of 5-HIAA has been documented and in monitoring disease progression [##REF##11215778##8##,##REF##14166209##14##]. Our patient had no symptoms related to carcinoid syndrome, neither metastatic spreads nor 5-HIAA increased excretion. The majority of carcinoid tumours are discovered during the histological examination of the surgical specimen incidentally and rarely suspected before this examination [##UREF##1##15##].</p>", "<p>At present, the site and the size rather than the depth, are used for the assessment of the tumour [##REF##8495322##4##]. In the 75% of cases the tumour is localized at the apex of the appendix, in 20% and 5% affect the mid portion and the base respectively [##REF##12297915##13##]. The tumour's median diameter is 6 mm [##REF##8495322##4##,##REF##12297915##13##]. In our case the diameter of the tumour was 1 cm. Generally, carcinoid tumours located at the tip of the appendix and measuring less than 10 mm usually are mimicking the clinical presentation of acute appendicitis, while tumours measuring more than 20 mm and located at the base of the appendix may present with clinical signs of peritonitis [##REF##11527175##12##,##UREF##2##16##]. The prognosis is directly related to the tumour's size. If the tumour is smaller than 2 cm and has perforated the serosa, the treatment of choice is appendectomy, whatever the location. Other reports suggest that neoplasms with these characteristics do not tend to relapse. Tumours measuring 2 cm or more in diameter may have widespread metastases upon detection. The invasive properties of these tumours are well-known, but the presence of lymph node metastases is reported in only 4% to 5% of paediatric cases. The prognosis is excellent [##REF##11527175##12##]. It should be mentioned that carcinoid is not infrequently associated with MEN1 and loss of 11q, sometimes independently of the MEN1 gene (11q13), suggesting loss of MEN1 or another tumour suppressor gene is responsible for the condition. However, this is usually isolated to foregut carcinoids [##REF##11979373##17##].</p>", "<p>Metastasis of an appendiceal carcinoid is very rare in children probably because most reported tumours in this age group are small and less aggressive. In this case the tumour extended thought the entire diameter of the appendix and involved all layers of the wall to the overlying serosa surface without distant metastasis.</p>", "<p>The treatment of the carcinoid tumours in the appendix depends to the size and the site of the tumour. Tumours smaller than 2 cm can be adequately treated by appendectomy, while right hemicolectomy is recommended for pediatric patients with appendiceal carcinoid tumours larger than 2 cm, especially when the mesoapendix is involved or in cases with residual tumours at the margin of resection [##REF##11452407##10##]. Our patient had an appendiceal carcinoid tumour of 1 cm in size, respectively with tumour free-margin in all specimens; simple appendectomy was considered the adequate treatment for this patient.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, CTs are the most common tumours of the appendix. In children, they occur more commonly in white females with a mean age of 13 years. The clinical presentation of the CT is similar to acute appendicitis, but the CT can be an incidental finding during surgical procedures other than appendicectomy. CT was diagnosed on histological examination of the removed appendix. The site and the size of the tumours rather than the depth, are used for the assessment of the CT. Localized disease has an excellent prognosis. Patients with metastatic CT fare poorly. Single appendicectomy is considered the appropriate treatment, while right colectomy is indicated in tumour larger than 2 cm. We report a case of an appendiceal CT in a 13 year old girl with diameter 1 cm which was treated with isolated appendectomy. The patient is disease free of ten years follow-up. Clinical awareness and early diagnosis of CT of the appendix may significantly decrease morbidity and mortality.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Carcinoids are the most common tumours of the appendix. These tumours show prevalence in white children. The clinical presentation of the appendiceal carcinoids is similar to that of acute appendicitis, although in many cases the tumour is diagnosed incidentally during an operation. The diagnosis should be confirmed histologically. The prognosis in patients with local disease is excellent. In small lesions isolated appendicectomy is considered as the most appropriate treatment, while in larger lesions right colectomy should be performed. We report a case of a carcinoid tumour in the tip of the appendix of a thirteen year old girl which was diagnosed intraoperatively. The patient received isolated appendicectomy due to the small size of the lesion. Ten years after the operation there is no evidence of recurrence or metastases, and the patient is considered free of disease.</p>" ]

[ "<title>Case presentation</title>", "<p>A 13-years-old female patient presented complaining for abdominal pain in right lower quadrant (RLQ), nausea and decreased appetite the last two days. Physical examination revealed a healthy looking female with a mildly elevated temperature 38°C, blood pressure 110/80 mmHg and pulse rate 95/min. The patient showed no sings of acute abdomen suggestive of acute appendicitis, as direct and rebound tenderness in the RLQ. Rectal examination revealed a mild tenderness in the RLQ, but no blood or palpable masses were observed. Hematocrite was 40%, white blood cells 13700/mm with neutrophil prevalence 87%, platelets 175000/mm, erythrocytes sedimentation rate 55 mm/h, while the rest blood analysis was normal. Abdominal ultrasound revealed appendiceal inflammation with transverse appendix diameter to be 9 cm. The patient was operated for acute appendicitis. The appendix found inflamed with distension of the tip, which was palpated as a solid, moderately hard, elastic and yellowish mass with diameter 1 cm.(Figure ##FIG##0##1##) No local or regional enlarged lymph nodes were found. The histological examination revealed a typical CT of the appendix and tumour-free margin in all specimens. We used haematoxylin-eosin as staining method. The tumour was consisted of small homogenic neoplasmatic cells that were arranged in islet formation and infiltrated few areas of the muscular layer. The mitotic activity was insignificant. There was a coexisting acute appendicitis and periappendicitis. (Figure ##FIG##1##2##)</p>", "<p>5-hydroxyindoleacetic acid (5-HIAA) which was measured postoperatively was normal at 3,2 mg/24 h. The patient's postoperative course was uncomplicated and she was discharged the 4^thday. Ten years later the patient is free of local or metastatic disease.</p>", "<title>Abbreviations</title>", "<p>CTs: Carcinoid tumours; CT: Carcinoid tumour; cm: centimeters; RLQ: right lower quadrant; mm: millimeter; mm/h: millimeters per hour; °C: Celcious degrees; min: minutes; 5-HIAA: 5-hydroxyindoleacetic acid; mg: milligrams.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>EC participated in the patients treatment, had the concept of the case report and contributed in the first draft, NP participated in the first draft and in the revisions, MC participated in the diagnosis of the case and in the presentation of its pathology, GF contributed in writing the paper, SR contributed in writing the paper, and DF participated in patient;s treatment, co-wrote the first draft and performed all the revisions.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Intraoperatively we defined a solid, moderately hard, elastic and yellowish mass on the appendix tip, with diameter 1,0 cm.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>The fatty tissue of the appendiceal mesenterium is invaded by cancer cells.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1757-1626-1-136-1\"/>", "<graphic xlink:href=\"1757-1626-1-136-2\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Intussusception of the appendix is a rare type of intussusception with an incidence less than 0.01% [##UREF##0##1##]. It is usually mimicking acute or chronic abdominal entities and is usually presented as cecal mass. The diagnosis is difficult to be achieved preoperatively. Appendiceal plastron is not an unusual complication of acute appendicitis in children [##REF##10569505##2##]. Appendiceal plastron presented as intussusception has not been presented previously in the literature.</p>" ]

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[ "<title>Discussion</title>", "<p>The most common cause of acute abdomen in children is <italic>acute appendicitis </italic>(AA), which presents diagnostic problems and followed by severe complications. Non-typical symptoms include diarrhoeas similar to those in acute gastroenteritis. Atypical presentation of a pelvic acute appendicitis complicates the paediatric patients with high frequency [##UREF##1##3##,##REF##8085457##4##].</p>", "<p>In our case the initial administration of broad spectrum antibiotics may contribute in the delayed diagnosis. The right abdominal lower quadrant pain on palpation, the low-grade fever (38°C) and the localized tenderness to percussion were the most important clinical signs suggested appendicitis.</p>", "<p><italic>Chronic intussusception (CI) </italic>is another pathological entity of children that is difficult to diagnose. The CI may last more than 14 days and followed by persistent abdominal pain [##REF##8085457##4##, ####REF##2765835##5##, ##UREF##2##6####2##6##]. Non-typical presentation may occur in the non-ischemic type of CI which results in a delayed diagnosis. Generally intussusception presents no such typical picture as the acute type of intussusception, with a long history less severe symptoms, like diarrhoea [##REF##9853236##7##,##REF##1479505##8##]. Also there are infrequent attacks of abdominal pain, sporadic vomiting and no, or small changes in defecation [##REF##18137841##9##, ####REF##1267872##10##, ##UREF##3##11####3##11##]. Weight loss and abdominal mass assume diagnostic significance [##REF##9853236##7##]. Approximately 3% of all reported acute CI cases occur in infants and about 10% in those over one year of age [##UREF##3##11##]. The barium enema is usually unsuccessful in hydrostatic reduction and surgery reduction is necessary[##UREF##2##6##,##REF##9853236##7##,##REF##1267872##10##,##UREF##3##11##].</p>" ]

[ "<title>Conclusion</title>", "<p>The role of imaging exams (US and CT) in the diagnosis of AA in children may be crucial especially in complicated and obscure cases. In equivocal cases of right lower quadrant pain, these exams may contribute to an earlier diagnosis of AA reducing the rate of unnecessary appendicectomies [##REF##12635978##12##,##UREF##4##13##]. However, risk groups of children who would benefit most from imaging studies have not been established [##UREF##5##14##].</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>We report an unusual case of an 11-year-old Greek girl with complicated acute appendicitis. The pelvic plastron that had been formatted secondary to appendix perforation was mimicking appendiceal intussusception in the preoperative ultrasound and computed tomography images. Although acute complicated appendicitis and appendiceal intussusception may represent possible causes of acute abdomen no similar cases have reported in the literature.</p>" ]

[ "<title>Case Presentation</title>", "<p>An 11-year-old Greek girl presented in the emergency department complaining for intermittent pain in the lower abdomen, as well as for intermittent fever especially during the nights. The symptoms had been presented 14 days ago. The patient had been examined by a doctor who had administrated in an outpatient basis clarithromycin (tabl. 250 mg, 1 × 2, for 5 days) in combination with amoxycillin plus clavulanic acid (tabl. 500 mg, 1 × 3, for three days) because of the possibility of a streptococcal angina infection. At her admission the patient presented lower abdominal pain, fever (T = 37, 5°C) and brownish colour semi diarrhoeic mucous defecations. For six days the patient was treated conservatively, but she did not improve. On the contrary she remained febrile, with diffuse abdominal pain, tenderness and sensibility in press of the right ilium fossa. From the laboratory and imaging exams X-ray chest, urine and stool cultures were normal, and leucosytosis was the only finding WBC: 18,200/μl (Granulocytes: 80, 3%).</p>", "<p>The ultrasound of the right lower abdominal quadrant demonstrated in transverse incisions a target lesion with multiple hypoechoid and hyperechoid rings. Longitudinal imagination shows heterogeneous tubular mass, suggesting intussusception of the appendix into the cecum, with a small amount of fluid. There was not clear evidence of the appendix. (Figure ##FIG##0##1##)</p>", "<p>The CT scan with per os administrated contrast suggested cecal intussusception. The main finding was the remaining of the contrast liquid in cecum, the oedema of the cecal wall as well as the misty outline of the mesenteric fat and the lied intestinal loops that suggested peri-appendiceal inflammation. (Figure ##FIG##1##2##)</p>", "<p>The preoperative findings suggested possible appendiceal intussusception and the patient was operated. We used a right sided Pfannenstiel incision. After entering the abdomen an appendiceal pelvic plastron was revealed, while the appendix was not intussuscepted. Because of appendix inflammation, an appendicectomy without burial of the appendix stump was performed. Postoperatively a combination of wide spectrum antibiotics administrated for five days, and the patient discharged at the sixth postoperative day, without presenting any complications.</p>", "<title>Abbreviations</title>", "<p>mg: milligrams; T: temperature; °C: Celcious degrees; WBC: white blood cells; CT: computed tomography; AA: acute appendicitis; CI: chronic intussusception; US: ultrasound</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>All authors <italic>(EC, AS, CP, MP, GF, DF, SR, NP) </italic>contributed equally to the patient's therapy, writing the present case report and approving it.</p>", "<title>Consent section</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>US of the lower right abdomen suggesting intussusception of the appendix. A small quantity of fluid can be noticed.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>In the CT scan remaining of the contrast liquid in cecum as well as oedema of the cecal wall were observed suggested peri-appendiceal inflammation.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1757-1626-1-135-1\"/>", "<graphic xlink:href=\"1757-1626-1-135-2\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Calcification of thoracic aorta is very common in old people, especially ones with hypertension. This can sometime be visible on plain chest radiograph. Thoracic computed tomography (CT) can be used for risk stratification for coronary artery disease, and amount of calcium correlates strongly with the prognosis [##REF##18371491##1##].</p>" ]

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[ "<title>Discussion</title>", "<p>The relationship between aortic calcification and coronary atherosclerosis remains contentious. One study has shown a strong relationship between extra-coronary plaque in the aorta and coronary artery disease [##REF##9399716##2##]. <italic>Bogalusa Heart Study </italic>showed that the severity of asymptomatic coronary and thoracic aortic plaques increase with age and number of cardiovascular risk factors. This study showed strong relationship between aortic plaque formation and smoking [##REF##9614255##3##]. Our patient had extensive history of smoking in the past. Calcium deposition is one of the many processes involved in the atherosclerotic plaque formation, and hence the radio-opaque appearance. This is a complex disease process, and may begin early in childhood [##REF##8479518##4##,##REF##2243430##5##]. Two landmark autopsy studies on soldier's have also proven the fact that the young adults can have advanced coronary artery disease and evidence of aortic plaques [##UREF##0##6##,##REF##5108403##7##].</p>", "<p>Patients with severe aortic calcification may need further investigations based on their cardiac risk factors. If a physician is encountered with chest radiography and CT scan findings shown in these images which were requested for a different issue, further work up must be sought out at the discharge based on individual risk factor profile, and treatment should be individualized.</p>", "<p>Figure ##FIG##1##2## in our report display classic calcified aortic wall. This appears like 'solar eclipse'. In solar eclipse, the rim of sun is usually visible. The center is visually blocked by the orbiting moon. The appearance in the accompanying CT is exactly similar. The clear area depends on the thickness of the aortic wall. We propose that this appearance can potentially be called as 'solar eclipse sign', which essentially indicates circumferential calcification of the aortic wall.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Calcification of thoracic aorta is very common in old people, especially ones with hypertension. This can sometime be visible on plain chest radiograph.</p>", "<title>Case Presentation</title>", "<p>We present a case of a male patient who had extensive deposition of calcium in the thoracic aorta.</p>", "<title>Conclusion</title>", "<p>The relationship between aortic calcification and coronary atherosclerosis remains contentious. Computed tomography of the thorax can display this calcification which appears like 'solar eclipse'.</p>" ]

[ "<title>Case presentation</title>", "<p>A 79 year old male with 60 pack year smoking history, emphysema, and hypertension presented with dyspnea and cough. He denied any history of diagnosed coronary artery disease or peripheral artery disease. Chest radiography revealed emphysematous changes (figure ##FIG##0##1##), along with a coincidental finding of severely calcified thoracic aorta. Computed tomography confirmed these findings (figure ##FIG##1##2##). It further revealed infected bullae. He was treated with antibiotics, and was discharged with a plan for outpatient cardiac workup.</p>", "<p>Patient was not inclined to further pursue in-patient workup on this issue due to other co-morbid conditions. Unfortunately, he was lost to follow up after his discharge from the hospital.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>Both authors contributed equally in collecting patient data, chart review, and editing medical images. Both authors read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>An informed consent was obtained from the patient for publication of this case report and accompanying images in <italic>cases journal</italic>. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank patient for giving us consent for the publication of the case report and accompanying radiologic images. We are thankful to the Radiology team for their willingness to provide input on discussion of case and other related information for the publication of this case report. Our special thanks to Dr Hegde for reviewing the manuscript and providing valuable input.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Chest radiograph displaying extensive calcification of the aorta.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Computed tomography of the chest showing extensive calcification of ascending and descending aorta.</bold> This classically looks like a 'solar eclipse'.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1757-1626-1-133-1\"/>", "<graphic xlink:href=\"1757-1626-1-133-2\"/>" ]

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{ "acronym": [], "definition": [] }

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[ "<title>Discussion</title>", "<p>Hydatid cyst disease is a zoonotic disease caused by the larval stage of Echinococcus granulosus (dog tapeworm), E. multilocularis, or E. vogeli [##REF##15462811##1##]. This disease occurs when humans ingest the hexacanth embryos of the dog tape worm. Infestation by hydatid disease in humans most commonly occurs in the liver (55–70%) followed by the lung (18–35%); the two organs can be affected simultaneously in about 5–13% of cases [##UREF##0##2##].</p>", "<p>Peritoneal hydatidosis is almost always secondary to hepatic disease, although some unusual cases of primary peritoneal hydatidosis have been described. The overall frequency of peritoneal disease in cases of abdominal echinococcus is approximately 13%. Peritoneal involvement is usually undetected unless cysts are large enough to cause symptoms. Most of the cases of peritoneal hydatid disease are secondary to previous surgery for liver hydatidosis. In present case blunt abdominal injury was the probable cause of dissemination. Systemic anaphylaxis is usually associated with cyst rupture and can be predicted by positivity of Casoni reaction.</p>", "<p>USG is the first line of screening for abdominal hydatidosis. USG is particularly useful for detection of cystic membrane, septa, and to look for hydatid sand. CT scan best demonstrates cyst wall calcification and cyst infection [##REF##2037004##3##]. Immunoelectrophoresis, enzyme-linked immunosorbent assay (ELISA), latex agglutination and indirect haemagglutination (IHA) test are being carried out for the diagnosis, screening and post-operative follow up for recurrence [##UREF##1##4##].</p>", "<p>The treatment of choice for localized hydatid cysts in liver or lungs is principally surgical while the therapy for disseminated peritoneal hydatidosis remains medical [##UREF##2##5##]. Therapy with albendazole or praziquantel remains the mainstay of medical therapy. After medical treatment, the hydatid cysts show gradual reduction in cyst size and number and the follow up is advisable with Ultrasonography or CT scan. In our case despite of sufficient medical treatment the cyst size and number did not reduced and hence surgery remained the final resort. Surgery can be performed with removal of the cyst after sterilizing the cyst with formalin or alcohol. However, pre- and post-operative 1-month courses of albendazole or 2 weeks of praziquantel should be considered in order to sterilize the cyst, decrease the chance of anaphylaxis, decrease the tension in the cyst wall and to reduce the recurrence rate post-operatively [##REF##16156971##6##]. Intra-operatively, the use of hypertonic saline or 0.5% silver nitrate solutions before opening the cavities tends to kill the daughter cysts and therefore prevent further spread or anaphylactic reaction.</p>", "<p>Anaphylctic shock occurs when there is prior sensitization. The present case might have been sensitized at the time of rupture of hepatic cyst when she sustained blunt abdominal trauma. Utmost care of preventing the contact of hydatid cyst contents with the body tissues during operation can not avoid the anaphylactic shock. The surgeon should be ready for this catastrophe while operating hydatid cyst especially with the suspicion of prior sensitization.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>A middle age lady presented with abdominal pain was diagnosed to have multiple peritoneal and hepatic hydatid cysts on CT scan. Retrospectively she was found to have suffered blunt abdominal trauma.</p>" ]

[ "<title>Case presentation</title>", "<p>A forty five year old lady presented with chronic dull aching pain with gradually increasing lump in the epigastric and pelvic region since 3 years. A well defined, firm mass of about 20 × 20 centimeters was palpable in epigastrium extending more on right hypochondrium, probably arising from left lobe of liver. A similar mass was palpable in the hypogastrium while multiple small nodular masses palpable in the right iliac fossa and lumbar region. Detailed inquest revealed a 5 year old incidence of blunt abdominal trauma, while working in her farm. The ultrasonography and CT scan (See Figure ##FIG##0##1##) showed multiple thin walled cysts of varying size involving left lobe of liver, peritoneal cavity, omentum and mesentery. Cysts showing internal septae and peripheral tiny calcific foci were also seen extending into pelvis around uterus, adnexae and retro-uterine cervical region, markedly compressing distal descending colon, sigmoid colon and rectum. Ileal loops were compressed and displaced superiorly. Serology for hydatid cyst disease was positive with ELISA test.</p>", "<p>Two courses of 4 weeks of Albendazole (15 mg/kg/day) were given with the interval of 1 month. The follow up after 1 month did not show any decrease in the size of the cysts and decision of laparotomy was taken. Peritoneal cavity was crammed with cysts ranging from 1 to 12 centimeters (See Figure ##FIG##1##2##). Omentum was studded with cysts (See Figure ##FIG##2##3##) which was incised and cysts were picked up (See Figure ##FIG##3##4##). A superficial cyst found in the left lobe of liver was opened with small incision and the hydatid fluid and daughter cysts were drained. After the excision of germinal membrane the cavity was masupialized. Later, the pelvic cavity was exposed and cysts adherent to adnexa, uterus, broad ligament, urinary bladder and rectum were removed. More than 250 cysts of different sizes were removed from the abdomen (See Figure ##FIG##4##5##). Patient died of anaphylactic shock within few hours of operation.</p>", "<title>Consent</title>", "<p>A written consent was taken from the patient and her father regarding the publishing of this article.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>All the authors read and approved the final manuscript. NJS did the surgery, RKS and NV assisted the surgery. PNM is the corresponding author of the article who drafted and finalized the manuscript.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>CT scan showing multiple thin walled cysts.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Peritoneal cavity crammed with cysts.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Omentum was studded with cysts.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Berry picking of cysts.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p>Cysts removed from peritoneum.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1757-1626-1-118-1\"/>", "<graphic xlink:href=\"1757-1626-1-118-2\"/>", "<graphic xlink:href=\"1757-1626-1-118-3\"/>", "<graphic xlink:href=\"1757-1626-1-118-4\"/>", "<graphic xlink:href=\"1757-1626-1-118-5\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Extra-osseous osteogenic sarcomas have been reported from the thyroid gland, kidney, bladder and soft tissues, but mammary osteogenic sarcomas constitute only a small group [##REF##17290347##1##]. Primary sarcomas of the breast are extremely rare and make up less than 0.1% of all malignant tumours of the breast [##REF##15187996##2##]. Fewer than 150 cases of primary osteosarcoma of breast have been reported in the medical literature in the last 50 years. When this tumour develops in the breast, it originates either from normal breast tissue <italic>de novo</italic>, or as metaplastic differentiation of a primary benign or malignant breast lesion. Secondary deposits from a primary bone sarcoma occur only rarely. Primary osteogenic breast cancer is usually considered a poor prognosis tumour, with high risk of disease recurrence and haematogeneous spread, most commonly to the lungs.</p>", "<p>We present the case of a 66 year old Caucasian woman who was diagnosed with an osteogenic sarcoma of the breast and has survived eight years from surgical resection. We have performed a thorough literature review and would like to use this case to highlight several details of this unusual tumour.</p>" ]

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[ "<title>Discussion</title>", "<p>Extra-skeletal sarcomas tend to occur in the over 50 year old age group [##REF##14659358##3##], which is in contrast to osteogenic sarcoma arising from bone which mainly occur in children and adolescents. Primary osteosarcomas of the breast are very rare and account for less than 0.1% of breast tumours [##REF##15187996##2##] and are often found in women with a mean age of 64 years [##REF##9706972##4##].</p>", "<p>The carcinogenesis of primary osteogenic sarcoma of the breast is not clear, but an origin from totipotent mesenchymal cells of the breast stroma or a transformation from a pre-existing breast lesion has been suggested. For example, the tumour may originate from either benign breast neoplasms, such as a long standing fibroadenoma or an intraductal papilloma; or a malignant breast lesion, such as a phyllodes tumour [##REF##8293949##5##]. To confirm the diagnosis of primary osteogenic sarcoma of the breast, the direct extension of an osteogenic sarcoma arising from the ribs or sternum should be excluded. Primary breast carcinoma with extensive osseous metaplasia must also be considered [##REF##15657524##6##].</p>", "<p>Preoperative diagnosis is unusual and most patients the correct histological diagnosis of only established after surgical resection[##REF##17156481##7##]. The mammographic appearances of these tumours are of a well circumscribed dense lesion within the breast tissue with focal or extensive coarse calcifications [##REF##17325062##8##]. The border may be regular or irregular. The mammographic appearances may be deceptively benign and may imitate a benign fibroadenoma in a third of cases [##REF##9706972##4##]. Fine needle aspiration cytology may not yield some clues to the diagnosis with features such as hypocellular or hypercellular smears with pleomorphic cells; scarce or abundant metachromatic amorphous material, suggestive of osteoid; osteoclast-like giant cells; and stromal fragments [##REF##17536552##9##].</p>", "<p>The main histological differential diagnosis in our case was metaplastic carcinoma [##REF##15187996##2##], however this was excluded because of negative epithelial markers on immunohistochemical staining. Metaplastic carcinoma is recognised either by the presence of carcinomatous compenent on H&amp;E staining or by cytokeratin immunoreactivity of the neoplastic spindle cells [##REF##15187996##2##]. Phyllodes tumour was not a differential diagnosis in our case, but would be it in any sarcoma with a predominantly fibroblastic component. However, our case had characteristic osteoid formation and osteoclastic giant cells and it is possible to say with conclusively that our case is an osteosarcoma (Figure ##FIG##0##1##).</p>", "<p>Surgical management of these tumours is either by wide local excision or mastectomy depending on the size of the tumour and remaining breast tissue. It is important to achieve a complete resection with negative resection margins, as margin status is a major factor for local disease recurrence. Axillary clearance is not necessary as these tumours do not spread via the lymphatic route. Adjuvant radiotherapy to the chest wall may reduced the risk of local recurrence [##REF##10661345##10##]. Although adjuvant chemotherapy with either doxorubicin, cisplatin or ifosfamide based regimes has increased the survival of primary bone sarcomas, there are no proven benefits to the use of these regimes in primary osteosarcoma of the breast.</p>", "<p>The long-term prognosis is uncertain due to the small number of cases reported in the medical literature. Silver et al reported a 5 year survival of 38% in a study of 50 patients with primary breast oestosarcoma [##REF##9706972##4##]. Twenty eight percent of patients developed local recurrence and 41% distant metastases. Haematogenous metastases most commonly occur to the lungs (80%), bone (20%), and liver (17%). Prognostic factors included tumour size, number of mitoses, presence of stromal atypia, histological subtype and resection margin involvement [##REF##9706972##4##].</p>", "<p>The learning points from our case are presented in Table ##TAB##0##1##.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Primary osteosarcoma of the breast is a rare malignant tumour. It is typically a poor prognosis tumour, which has some interesting features worthy of discussion. We report a case of primary osteosarcoma of the breast and summarise the previous medical literature to highlight several details of this unusual tumour.</p>", "<title>Case presentation</title>", "<p>A 66-year-old Caucasian lady presented with painless lump in her right breast. Mammography showed features of fibroadenoma with calcification and fine needle aspiration cytology was reported as showing malignant cells (C5). Wide local excision was performed and histological features were consistent with primary osteosarcoma with predominance of osteoclastic activity. Subsequent completion mastectomy was performed because of suspicion of incomplete excision. She remains disease free 8 years from her initial surgery.</p>" ]

[ "<title>Case presentation</title>", "<p>A 66-year-old Caucasian lady presented with a painless, enlarging lump in her right breast. There was no history of trauma, skin changes, nipple discharge, or any other breast lumps. She was otherwise asymptomatic with no symptoms of bone pain. There was no family history of breast cancer. She had a past medical history of severe chronic obstructive airways disease, previous fracture neck of femur and surgery for a hiatus hernia. There was no prior history of radiotherapy. Clinical examination revealed a non-tender hard lump in right upper quadrant with no palpable axillary lymph nodes. Mammography showed features of fibroadenoma with calcification. Fine needle aspiration cytology (FNAC) was positive for malignant cells (C5).</p>", "<p>Wide local excision of the breast lump was performed in August 1998. This was performed under local anaesthesia due to her poor respiratory function. Macroscopic examination of the excised specimen revealed it to be composed of a piece of fibrofatty tissue measuring 6 × 4 × 2 cm that weighed 33 grams. There was a 2 cm cystic mass containing a necrotic tumour. The tumour appeared to infiltrate the cyst wall and extended to within 3 mm from the nearest resection margin. Microscopically, an encapsulated tumour composed of spindle cells, osteoclastic giant cells and osteoblasts was found. The spindle cells contained plump nuclei with prominent nucleoli. The cytoplasm was pale to eosinophilic with indistinct cell border. The tumour showed high apoptotic activity that was mitotically active with 24 mitoses/10 high power field. The tumour demonstrated osteoclastic and osteoblastic activity with marked osteoid formation (Figure ##FIG##0##1##). Immunohistochemistry was performed and the tumour cells were positive for vimentin. MNF116 and CAM5.2 (which are broad spectrum cytokeratin epithelial markers) staining was negative proving this was a primary osteosarcoma rather than metaplastic breast sarcoma (Figure ##FIG##0##1##). The tumour was also negative for S100, desmin and smooth muscle actin. The tumour infiltrated the breast capsule and extended very close to the resection margins, therefore it was not possible to be certain that excision was complete and further excision was advised.</p>", "<p>Computer tomography of the thorax and abdomen showed no evidence of distant metastasis. The patient was optimised for general anaesthesia after consultation with a Consultant Respiratory Physician who managed to improve her respiratory function with medical therapy. Subsequent right sided mastectomy was performed under general anaesthesia in January 1999. As the spread of extraskeletal osteosarcoma is haematogenous rather via lymph, axillary lymphadenectomy was not perfomed. Histology of the mastectomy specimen showed no evidence of residual tumour involvement.</p>", "<p>She was followed up in the outpatient clinic every 6 months. In March 2001, a magnetic resonance imaging (MRI) scan of right axilla was performed for a clinical suspicion of an axillary lump, but this was found to be normal. She was last reviewed in the breast clinic in November 2006 and was found to have no clinical evidence of recurrent disease and was therefore discharged back to the care of her General Practitioner.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>SK wrote the draft of the manuscript and performed the literature search; EG helped performed the literature research and revised the manuscript; NS re-examined the surgical specimen, took the photomicrographs of the specimen and helped with revising histopathological aspects of the manuscript; SR performed the surgical procedure and revised the manuscript for intellectual content.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors thank the patient for allowing this case to be published.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>(a) Osteosarcoma (×4); (b) Giant cells with osteoid formation (×20); (c) Giant cells with osteoid formation (×20); (d) Negative immunohistochemical staining for CAM5.2 (×20); (e) Negative immunohistochemical staining for MNF116 (×20); (f) Positive immunohistochemical staining for vimentin (×20).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Learning points from this case report</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\"><bold>Learning points</bold></td></tr></thead><tbody><tr><td align=\"left\">1.</td><td align=\"left\">Primary breast sarcomas are rare tumours of the breast. They make up less than 0.1% of all breast tumours.</td></tr><tr><td align=\"left\">2.</td><td align=\"left\">Tumour development is either from normal breast tissue <italic>de novo</italic>, or as metaplastic differentiation of a primary benign or malignant breast lesion. Secondary deposits from a primary bone sarcoma occur only rarely, but need to be</td></tr><tr><td align=\"left\">3.</td><td align=\"left\">excluded clinically. Diagnosis is made by careful assessment of the histological specimen, together with immunohistochemical staining.</td></tr><tr><td align=\"left\">4.</td><td align=\"left\">Typically primary osteogenic breast cancer is usually considered a poor prognosis tumour, with high risk of disease recurrence and haematogeneous spread, most commonly to the lungs. Lymph node metastases do not occur.</td></tr></tbody></table></table-wrap>" ]

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[ "<graphic xlink:href=\"1757-1626-1-148-1\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>A 68 year-old woman, with multiple myeloma, was admitted with progressive, exertional dyspnea and dry cough, which started a few days before presentation. With exercise, her oxygen saturation fell to 85% on room air. Two weeks prior, she had developed diffuse erythematous skin lesions that spontaneously resolved. She denied fever, chills, rigors, night sweats, weight loss, hemoptysis, myalgias, arthralgias, chest pain, palpitations, orthopnea and paroxysmal nocturnal dyspnea. She had no sick contacts. Two months before, she began treatment with thalidomide 50 mg daily, which was titrated up to 200 mg daily over two weeks. She also received dexamethasone 40 mg for four consecutive days every four weeks. Her past medical history was significant for remote cancers: breast cancer, for which she underwent lumpectomy and radiation; malignant melanoma, which was resected and endometrial cancer, for which hysterectomy and pelvic radiation were performed. There was no previous history of atopy or asthma. On presentation, her medications included aspirin, iron, alendronate, calcium, multivitamin and thalidomide (200 mg daily). She was not on dexamethasone at the time of presentation, but had received her dosing the previous month. She had no drug allergies and never received trimethoprim-sulfamethoxazole prophylaxis. She had no pertinent hobbies, pets, travel history or occupational exposures. Her human immunodeficiency virus status was negative.</p>", "<p>On physical examination, she was in mild respiratory distress and on 2 liters of oxygen, her saturation was 96%. Vital signs and cardiac examination were normal. Respiratory examination revealed bibasilar crackles. There were no skin lesions, lymphadenopathy, joint swelling or erythema.</p>", "<p>On admission, her white blood cell count was 5.6 k/uL (neutrophils 84%, lymphocytes 7.1%, and eosinophils 3%) and her hemoglobin 10.2 g/dl. Her blood chemistries were normal. Computed tomography pulmonary angiography (CTPA) of the chest revealed no pulmonary embolism. There were patchy ground glass infiltrates bilaterally (Fig ##FIG##0##1a##). Transthoracic echocardiogram revealed normal systolic function and pulmonary pressures. Bronchoscopy was performed to obtain a bronchoalveolar lavage (BAL) specimen and transbronchial biopsies. Specimens from the right middle lobe were sent for cell count and differential, bacterial and fungal cultures, acid fast bacilli stains and cytology. There were 18% lymphocytes and 33% eosinophils on the differential cell count. There was no evidence of cytomegalovirus, bacteria, fungus or Pneumocystis jiroveci. Transbronchial biopsy specimens showed evidence of interstitial pneumonitis with histiocytic clusters suggestive of granulomas (Fig ##FIG##1##2##). There was no evidence of malignancy. No parasites were seen. These results supported a diagnosis of acute eosinophilic pneumonia.</p>", "<p>The thalidomide was discontinued and she was started on prednisone 40 mg orally daily. She was discharged to home, after three days in the hospital, with minimal dyspnea. At that time, she was saturating 98% on room air, at rest, with no significant desaturation on exercise. Within one week, she was no longer dyspneic. The patient remained symptom free after discontinuation of the steroids. Spirometry and diffusion capacity, one month later, were normal. Repeat CT evaluation showed complete radiographic resolution of the infiltrates (Fig ##FIG##2##3##).</p>" ]

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[ "<title>Discussion</title>", "<p>Thalidomide, originally a sedative-hypnotic drug, has been shown to have activity in the multimodality treatment of leprosy, hematologic malignancies and solid tumors, including prostate, ovarian, renal cell cancer and Kaposi's sarcoma[##REF##10564693##1##,##REF##15811905##2##], due to its antiangiogenic, immunomodulating and anticytokine properties. Angiogenesis, downregulation of tumor necrosis factor, interference with stromal cell/myeloma adhesive properties and stimulation of natural killer cells are thought to be the mechanisms by which it exerts its beneficial effects in multiple myeloma[##REF##14679133##3##].</p>", "<p>Serious pulmonary complications due to thalidomide use are not common. The most common pulmonary side-effect is non-specific dyspnea, reported in 4% to 54%[##REF##12409330##4##]. This frequently improves on cessation of the drug. Arterial and venous thromboses, namely, pulmonary embolism and deep vein thromboses, [##REF##15045155##5##, ####REF##18164975##6##, ##REF##11520815##7##, ##REF##12043695##8####12043695##8##] are the most serious pulmonary complications and their frequency appears to increase when combined with dexamethasone and other chemotherapeutic drugs [##REF##15197211##9##]. Interstitial pneumonia has been described in case reports in patients with ovarian cancer and multiple myeloma [##REF##18191185##10##, ####REF##15800335##11##, ##REF##12756431##12####12756431##12##]. However, none of these patients had significant eosinophilia in the BAL fluid. The case series of three patients with advanced prostate cancer who were treated with a combination of docetaxel and thalidomide, attributed the pulmonary toxicity to the primarily the doxacetal, to which severe interstitial pneumonias had been ascribed[##REF##12756431##12##].</p>", "<p>A case report in the Japanese literature, describes a patient with a severe interstitial pneumonia, rash and eosinophilia in the BAL specimen, who required mechanical ventilation. His pneumonia and rash initially responded to discontinuation of the thalidomide and a course of steroids. However, his course was subsequently complicated by methicillin resistant staphylococcus aureus (MRSA) septicemia and he demised [##REF##15510838##13##]. It is not clear from the information provided in the case that the eosinophilia was definitely due to the thalidomide and not an undiagnosed underlying process.</p>", "<p>Pleural effusions may occur [##REF##12372201##14##], with the hypersensitivity-type responses [##UREF##0##15##]. Hypersensitivity pneumonitis has been described with an FDA-approved thalidomide analog, lenalidomide[##REF##17494808##16##].</p>", "<p>There is one case report of a patient with multiple myeloma who developed dyspnea and ground glass infiltrates on thalidomide. The bronchoalveolar lavage contained 31% neutrophils, 40% lymphocytes, 20% eosinophils and 1% plasma cells. Transbronchial biopsy specimens revealed fibroblastic plugs in the alveolar spaces with surrounding interstitial inflammation, diagnostic of organizing pneumonia[##REF##17195429##17##].</p>", "<p>There are published case reports of patients who developed pulmonary hypertension seemingly due to thalidomide. One case reported described a man with multiple myeloma, who transiently developed severe pulmonary hypertension on thalidomide, which improved on discontinuation and worsened on a rechallenge with the drug[##REF##12670354##18##]. Another case reports a patient with multiple myeloma, who had significant dyspnea, was found to have severe pulmonary hyperstension and subsequently died. There were no other identifiable causes of her pulmonary hypertension on pathology and review of her history and laboratory results[##REF##12670354##18##,##REF##15755296##19##].</p>", "<p>To our knowledge, this is the first reported case, in the English literature, of an acute eosinophilic pneumonia, related to thalidomide. The degree of eosinophilia in the BAL fluid, in the absence of any historical, physical or laboratory data to support an alternative cause of eosinophilic pneumonia, strongly supports the diagnosis of an esoinophilic pneumonia. The absence of eosinophils on histology would have been supportive of this diagnosis, but is not required for the diagnosis of eosinophilic pneumonia. Her clinical improvement on discontinuation of the thalidomide suggests that the thalidomide was the most reasonable culprit. This is somewhat confounded by the simultaneous treatment with prednisone, as it can be argued that the patient responded to the steroid, as eosinophilic pneumonias characteristically do and not necessarily to discontinuation of the drug. Resumption of the thalidomide, with recrudescence of the dyspnea and pulmonary infiltrates, would confirm the diagnosis of thalidomide-induced interstitial pneumonia. However, this is not recommended.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, we present a case of eosinophilic pneumonia secondary to thalidomide. The patient's clinical course, radiographic and bronchoscopic findings strongly support a diagnosis of thalidomide-induced eosinophilic pneumonia, in the absence of any other positive historical and laboratory evidence. Physicians should be cognizant of this potential complication in patients receiving thalidomide who present with dyspnea and pulmonary infiltrates.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Thalidomide has regained value in the multimodality treatment of leprosy, multiple myeloma, prostate, ovarian and renal cancer. Complications related to arterial and venous complications are well described. However, pulmonary complications remain relatively uncommon. The most common pulmonary side-effect reported is non-specific dyspnea. We report a patient with multiple myeloma, who developed an eosinophilic pneumonia, shortly after starting thalidomide. She had complete resolution of her symptoms and pulmonary infiltrates on discontinuation of the drug and treatment with corticosteroids. Physicians should be cognizant of this potential complication in patients receiving thalidomide who present with dyspnea and pulmonary infiltrates.</p>" ]

[ "<title>Abbreviations</title>", "<p>BAL: Bronchoalveolar lavage; CT: Computed Tomography; Ig G: Immunoglobulin G; MRSA: Methicillin-Resistant Staphylococcus Aureus.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>LT managed the patient and analyzed and interpreted the patient data regarding the clinical course of the patient. RD managed the hematological disease and provided follow up. FC performed the pathological examination of the lung biopsy and discussed the features significant to this case. MA was a major contributor in managing the patient and writing the manuscript. All authors read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Thanks to Dr. Jeffrey Kanne for providing the photographs of the radiographs.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>High-resolution transverse CT image shows extensive patchy ground-glass opacity throughout both lungs.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>The lung pathology consists of a mild interstitial pneumonitis with scattered clusters of histiocytes within the alveolar space consistent with loosely-formed granulomas. </bold>(Hematoxylin and eosin, 100×).</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>High-resolution transverse CT image at the same levels as figure 1 shows resolution of ground-glass opacity.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1757-1626-1-143-1\"/>", "<graphic xlink:href=\"1757-1626-1-143-2\"/>", "<graphic xlink:href=\"1757-1626-1-143-3\"/>" ]

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[ "<title>Background</title>", "<p>Pulmonary hypertension (PH) is a disease characterized by a progressive rise in pulmonary artery pressure and pulmonary vascular resistance, ultimately resulting in right heart failure and death [##REF##8988890##1##]. Symptoms include breathlessness, fatigue, palpitations, ankle oedema, chest pain, and syncope. Treatments for PH range from oral endothelin receptor antagonists through to nebulised or continuous intravenous or sub-cutaneous infusions of prostaglandin or prostaglandin analogues [##REF##11473937##2##]. Many of these treatments are inconvenient or have significant adverse effects. For example, intravenous Prostacyclin [##REF##14720012##3##] is associated with diarrhoea, systemic flushing, headaches, jaw pain and hypotension. Current treatments for PH (with the exception of pulmonary endarterectomy for thromboembolic PH) do not cure the disease.</p>", "<p>The present aim of treatment is to lengthen survival time, to ameliorate symptoms and to improve quality of life (QoL). However, treatments for PH are expensive. For example, Epoprostenol costs up to £71,000 per patient per year in the UK [##UREF##0##4##]. Given this cost there is a need to determine the benefits of such treatment.</p>", "<p>Several countries have produced guidelines for the conduct of economic evaluations in health care including Canada [##UREF##1##5##], Australia [##UREF##2##6##] and the UK [##UREF##3##7##]. All guidelines indicate that the preferred methodology is cost utility analysis (CUA) whereby the benefits of health care interventions are measured according to quality adjusted life years (QALYs). In addition, there is general agreement that where possible a generic preference based measure of health status based on general population values should be used to calculate QALYs. Generic preference based measures of health status include the EQ-5D [##UREF##4##8##], the SF-6D [##REF##11939242##9##] and the HUI-3 [##REF##11802084##10##]. However, for some specific clinical conditions generic measures may be considered inappropriate due to their lack of sensitivity and relevance [##UREF##5##11##,##REF##10210235##12##]. Pulmonary hypertension represents such a condition. In addition, there is evidence that disease-specific utility measures are more responsive than generic ones [##REF##18274882##13##,##REF##17091359##14##].</p>", "<p>Until recently only generic health status measures were available for assessing the impact of PH from the patients' perspective. The Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) was developed as a PH-specific measure to fill this gap [##REF##16411035##15##]. It consists of three separate scales that are specific to PH; symptoms, functioning and QoL. The content of the measure was derived directly from PH patients and all scales have been shown to have good face and content validity, reliability, reproducibility and construct validity [##REF##16411035##15##]. Furthermore, all scales have been shown to fit the Rasch model indicating that they represent unidimensional scales [##REF##16411035##15##,##UREF##6##16##]. The analysis also shows how severe each item is in relation to the construct being measured. However, scores from such a measure cannot be used directly to undertake economic evaluations of treatments. First it is necessary to convert it into a preference based measure. The approach used in this paper has been developed in Sheffield and used in the construction of the SF-6D and King's Health Questionnaire [##REF##11939242##9##,##REF##17641139##17##].</p>", "<p>An advantage of converting a disease-specific measure is that the resulting utility values calculated will be specific to the condition in question. If the source measure was carefully developed then all the items will be relevant to the respondents' condition and no important issue will have been omitted.</p>", "<p>The purpose of the present paper is to describe the development and validation of a preference based measure from the CAMPHOR that would yield utility values for patients with PH and allow more accurate economic evaluations of PH treatments.</p>" ]

[ "<title>Methods</title>", "<title>Item selection</title>", "<p>As the ultimate purpose of the study was to calculate QALYs, it was decided to construct the preference based measure from the 25-item CAMPHOR QoL scale. Fewer items are included in a preference based measure as, otherwise, it would require an unmanageable number of valuations in order to determine the utility of all possible health states. Consequently, a simplified health state classification for CAMPHOR was developed based on a sample of six items. These six items were combined into four domains such that two domains had three levels and the other two domains had two levels. The items were selected by re-analysis of the responses of 201 patients to the CAMPHOR QoL scale. The following criteria were employed for item selection:</p>", "<p>• Percentage affirmation of item: Items that were affirmed by a very small or very large proportion of the sample were excluded.</p>", "<p>• Item severity as assessed by logit location in Rasch analysis: Items with extreme logit locations (derived from the Rasch analyses) were candidates for exclusion. However, it was the aim to include a reasonable spread of items in terms of the degree of severity they represented. The logit severity of the selected items ranged from -1.25 to 2.09.</p>", "<p>• Regression: Ordinal regression was employed using CAMPHOR QoL responses to predict a general health perception variable (response options 'Very good', 'Good', 'Fair', and 'Poor'). Items that significantly predicted this variable were candidates for inclusion in the utility exercise.</p>", "<p>• Content of item: In addition to the statistical methods listed above it was important to select items that covered a range of issues included in the CAMPHOR scale.</p>", "<title>Valuation survey</title>", "<p>The main valuation survey was undertaken using the time trade-off (TTO) technique where individuals are asked to undertake conventional TTO valuations for a sample of health states. The Measurement and Valuation of Health (MVH) group version of TTO [##UREF##7##18##] was used to allow comparison with the EQ-5D tariff.</p>", "<p>A representative sample of the adult general population was invited to participate in the study. Consenting adults were visited in their home for the TTO interview. A small pilot study (n = 15) was undertaken in advance of the main study to check that interviewees understood the task and were answering the questions as expected. The final sample size for this study was 249 individuals.</p>", "<p>At the start of each interview respondents were given a self-completed questionnaire containing the EQ-5D and the CAMPHOR health state classification to complete. Respondents were then asked to rank the CAMPHOR health states from best to worst in order to help familiarize them with the states. The main elicitation task involved the use of a visual prop designed by the MVH group for use in the UK valuation of the EQ-5D. For health states that a respondent regards as better than being dead, they are asked to imagine two scenarios: 1) live in a state for 10 years (t) and 2) a shorter period (x) in perfect health. The time in the shorter state is varied until respondents are unable to choose between these two scenarios, at which point the value of the state is given as x/t. For states respondents regard as worse than being dead, the choice is between 1) dying immediately and 2) spending a period of time (x) in the state followed by (10-x) years in perfect health. Respondents were initially taken through a hypothetical TTO exercise to help them understand the task. They were then asked to undertake a total of nine TTO tasks. Finally, the interview concluded with a series of socio-demographic questions.</p>", "<p>For states better than being dead, the value of the health state x/t is bounded by 1.0 for perfect health and zero for states as bad as being dead. For states worse than being dead, health state values were calculated using the formula -(10-x)/10 to ensure it is bounded by -1.0 [##REF##9366889##19##].</p>", "<title>Modeling health state values</title>", "<p>The data from the TTO interviews were analysed using two approaches based on aggregate and individual level modelling. First, ordinary least squares (OLS) were used to estimate a mean level model. The mean health state values were the dependent variable and the independent variables were a series of dummy explanatory variables representing each level of the CAMPHOR dimensions. The mean level model is defined as:</p>", "<p></p>", "<p>Where the dependent variable <italic>Yi </italic>is the mean TTO value for each health state and <bold><italic>x </italic></bold>is a vector of dummy explanatory variables (<italic>x∂λ</italic>) for each level <italic>λ </italic>of dimension <italic>∂ </italic>of the simplified CAMPHOR classification. For example, <italic>x</italic>₃₁denotes dimension <italic>∂ </italic>= 3 (dependence), level <italic>λ </italic>= 1 (I don't feel very dependent). For any given health state <italic>x∂λ </italic>will be defined as follows:</p>", "<p><italic>x∂λ </italic>= 1, if for this state dimension <italic>∂ </italic>is at level <italic>λ</italic></p>", "<p><italic>x∂λ </italic>= 0, if for this state, dimension <italic>∂ </italic>is not at level <italic>λ</italic></p>", "<p>There are six of these terms in total with level <italic>λ </italic>= 1 acting as a baseline for each dimension. Hence for a simple linear model, the intercept (or constant) represents state 1111 and summing the coefficients of the 'on' dummies derives the value for all other states. <italic>Є</italic>_{<italic>i </italic>}is the error term which is assumed to be independent with constant variance structure.</p>", "<p>Secondly, a random effects model was used based on individual observations. This model specification takes account of the repeated measurement aspect of the data where multiple responses are obtained from the same individual.</p>", "<p>The random effects model is defined as:</p>", "<p></p>", "<p>Where i = 1,2...n represent individual health state values and j = 1,2...m represents respondents. The dependent variable <italic>Yij </italic>is the value assigned to each health state (i) valued by respondent j, <bold><italic>x </italic></bold>is a vector of dummy explanatory variables (<italic>x∂λ</italic>) defined as previously and <italic>Є</italic>_{<italic>ij </italic>}is the error term which is subdivided as follows:</p>", "<p></p>", "<p>Where <italic>uj </italic>is respondent specific variation and <italic>eij </italic>is an error term for the <italic>i</italic>th health state valuation of the <italic>j</italic>th individual. This is assumed to be random across observations.</p>", "<title>Validation of the CAMPHOR preference based measure</title>", "<p>After the valuation exercise it was possible to use the resulting weights for the six items to calculate utility data for previously collected CAMPHOR responses. Data collected in a previous study [##REF##16411035##15##] were available to validate the new preference based measure (which is embedded in the CAMPHOR QoL scale). This study involved administering the CAMPHOR to 91 PH patients on two occasions, two weeks apart. In addition, the EQ-5D was administered on the second occasion. The following psychometric properties of the new measure were assessed; test-retest reliability (reproducibility) and construct validity (utility scores compared between perceived general health groups and between PH severity groups based on CAMPHOR symptom scores).</p>", "<p>Ethical approval was sought and gained for the validation survey.</p>" ]

[ "<title>Results</title>", "<p>Table ##TAB##0##1## includes details of items selected. The internal consistency for these six items was 0.72.</p>", "<title>Derivation of health state classification</title>", "<p>Four domains were captured using the six selected CAMPHOR items; social activities, travelling, dependence and communication. Two items each provided three levels for the social activities (I can join in activities with family and friends, I'm unable to join in activities with family and friends, I feel very isolated) and Travelling (Travelling distances is not a problem, Travelling distances is a problem, I am reluctant to leave the house) domains. One item each provided two levels for the Dependence (I don't feel very dependent and I feel very dependent) and Communication (I never find speaking too much of an effort and Sometimes it's too much effort to speak) domains. A full factorial design produced 36 health states for valuation. The health states were stratified into mild, moderate and severe classifications. A sample of health states defined by the CAMPHOR items can be seen in Table ##TAB##1##2##. The health states were chosen to reflect a range of possible health states defined by the classification rather than predominantly a 'good' or 'bad' selection of health states.</p>", "<title>Valuation survey</title>", "<p>Descriptive characteristics of the respondents included in the valuation survey are included in Table ##TAB##2##3##. It can be seen that a majority of respondents were female, married and had experience of serious illness in their own families. Over 60% of respondents had education beyond the minimum school leaving age with over 40% holding a degree or equivalent professional qualification.</p>", "<p>The health state values ranged from 0.770 to 0.156 and generally had fairly large standard deviations (ranging from 0.250 to 0.532).</p>", "<p>Table ##TAB##3##4## shows the results for the mean level and random effects main effects only models (models 1 and 2).</p>", "<p>For the mean level model, all of the coefficients had the expected negative sign and were statistically significant (p &lt; 0.01). The coefficient estimates also increased with absolute size as the level of each dimension worsened. The explanatory power of the mean level model was 0.936 which is very high indicating that the model is a good fit for the data. For the random effects model, the results were similar in that all the coefficients had the expected negative sign but differed from the mean level model as not all of the coefficients increased with absolute size as the level of each dimension worsened (namely the movement from level 2 to level 3 in social activities and the movement from level 2 to level 3 in travelling). In common with the mean level model, all of the coefficients were statistically significant (p &lt; 0.01). The explanatory power of the random effects model (0.373) was, however, somewhat lower than that of the mean level model which was not surprising given the much larger number of actual data points which this model is aiming to fit. The predictive ability of the two models was quite similar with both models resulting in a similar proportion of errors greater than 0.05 (35% for the mean level model and 38% for the random effects models, respectively) and both models resulting in two predictive errors greater than 0.10.</p>", "<p>In both mean and random effects models the predictions were unbiased (t-test) indicating that neither model systematically over or under estimated the observed mean value and the Ljung-Box (LB) statistics suggested that there was no evidence of auto-correlation in the prediction errors of both models, when the errors are ordered by actual mean health state valuation.</p>", "<p>As the upper anchor for the analyses was perfect health and not the best state as defined by the CAMPHOR utility scale, the predicted utility value for the latter was less than 1. This was necessary since, for the purpose of calculating QALYs, results must lie on a scale where '1' is full health and '0' represents death. The predicted values of state 1111 is the constant term, which had values of 0.962 and 0.961 in the mean and RE models, respectively.</p>", "<p>Table ##TAB##4##5## presents examples comparing the predicted values according to each model and the actual values for each health state.</p>", "<title>Validation of the preference based CAMPHOR scale</title>", "<p>A majority (87.8%) of the 91 participants in the CAMPHOR validation survey were in New York Heart Association (NYHA) classes II and III. The correlation between the CAMPHOR QoL scores and the CAMPHOR preference based scores was 0.86.</p>", "<title>Test-retest reliability</title>", "<p>After removal of cases where there were 7 days &lt; or &gt;21 days between administrations or where perceived health changed between administrations, the test-retest coefficient was 0.85. Tables ##TAB##5##6## and ##TAB##6##7## show how the preference weights are related to perceived general health and PH severity, respectively. In both cases Kruskal-Wallis tests showed that the differences in utility were statistically significant (p &lt; .001).</p>", "<p>Similar values were found for the mean preference weights obtained for the CAMPHOR and EQ-5D in NYHA Class II (Table ##TAB##7##8##). These values are also relatively similar to those found in a PH study that obtained utility values from the SF-6D [##REF##17258153##20##]. However, there were marked differences between these three measures for Class III patients with the CAMPHOR utility scores being substantially lower than those on the EQ-5D and SF-6D. The CAMPHOR-generated preference weights showed greater sensitivity in terms of differentiating between NYHA classes. To illustrate this; if patients were to improve from NYHA Class III to Class II the effect size (difference in mean score divided by standard deviation at baseline) would be 0.71–0.92 for the CAMPHOR measure – a large effect size – compared with 0.42 for the EQ-5D. A moderately sized correlation (0.60) was found between the values derived from the two measures.</p>" ]

[ "<title>Discussion</title>", "<p>The results from this study present a method for analysing existing and future data from clinical trials and other evidence sources where the CAMPHOR has been employed. Thus the CAMPHOR is now able to provide data on health state values in addition to PH-specific symptomatology, functioning and QoL. The methodology employed has produced preference data that can be applied within the framework of cost utility analysis in economic evaluation.</p>", "<p>The mean level (model 1) is broadly consistent with a priori expectations in terms of coefficient size and direction of preference in relation to worsening levels of each dimension. The predicted health state values from this model also broadly conform to the logical ordering of the simplified CAMPHOR classification. This is not the case for the random effects model (model 2) which fails to indicate the direction of preference expected in terms of worsening levels of the social and travelling dimensions.</p>", "<p>Hence, it is recommended that Model 1 (the aggregate mean level model) be used. This model is superior because it removes inconsistencies and because of its high performance in terms of explanatory power and predictive ability. The tariff can be applied by classifying individuals into particular health states on the basis of their responses to the CAMPHOR. For example, an individual who indicates that they can join in activities with family and friends, that travelling distances is a problem, that they feel very dependent, and sometimes find it too much of an effort to speak, would be classified in health state 1222. The corresponding value for that health state according to the recommended model is 0.465. All other health state classifications arising from the CAMPHOR can be valued using the same approach.</p>", "<p>The CAMPHOR preference-based measure exhibited high correlations with the CAMPHOR QoL scale. High test-retest values indicate that the new utility scale has excellent reproducibility while evidence of the scale's validity was found in its ability to discriminate effectively between patients who have differing levels of disease severity.</p>", "<p>The estimation of preference weights for disease-specific QoL instruments is relatively rare and some health economists have expressed scepticism about the value of such an exercise [##REF##11788974##21##]. However, the main argument for using disease-specific descriptive systems rests on the premise that they are far more likely to be sensitive to changes in the condition under consideration (supported by results from the present validation exercise) and are more relevant to the concerns of patients than generic measures [##REF##12797709##22##,##REF##9792568##23##]. The effect size results show that the disease-specific measure is better able to distinguish signal from noise than the generic measures. This has important implications for sample sizes in trials. While it is accepted that for use in economic evaluation it is the absolute difference and not the effect size that determines cost effectiveness, the standard deviation influences the degree of uncertainty in the probabilistic sensitivity analysis [##REF##15248937##24##].</p>", "<p>There may also be a concern that the values produced by a disease-specific measure will not be comparable to those produced by a generic measure. However, it can be contended that providing the descriptive system is valued on the same scale using the same variant of the same valuation technique, as was the case for the CAMPHOR and EQ-5D models, then the valuations should be comparable [##UREF##8##25##].</p>", "<p>The valuation exercise found that the best state defined by the CAMPHOR items was below 1. It is clear from this and other studies that individuals valuing the best health state (i.e. that with no health problems) are still judged to have impaired health status as reflected by a mean utility value lower than 1 [##REF##14516171##26##,##REF##11939242##27##]. It is interesting to note that in the development of the EQ-5D the state of perfect health was not valued and was assumed to be 1 [##REF##9366889##19##]. This anchoring meant that in the PH validation sample around 8% of patients had perfect health according to the EQ-5D. It is questionable whether any individuals with PH would consider themselves to have perfect health given the severe nature of the symptoms, the fact that the condition is often not diagnosed until late in its progression and the poor prognosis. Given these factors, it is possible that the CAMPHOR utility scale provides a more realistic estimate of utility in PH.</p>" ]

[ "<title>Conclusion</title>", "<p>This research has demonstrated that it is possible to estimate preference weights for a disease-specific measure relating to pulmonary hypertension. The results can be applied to any data set including the CAMPHOR and hence widen the evidence base for conducting economic evaluations of new pharmaceuticals and other health care interventions designed to improve QoL for patients living with this serious condition.</p>", "<p>The CAMPHOR preference-based measure has been shown to have very good psychometric properties. It has excellent reproducibility, good construct validity and superior sensitivity to the EQ-5D in this population.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Pulmonary Hypertension is a severe and incurable disease with poor prognosis. A suite of new disease-specific measures – the Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) – was recently developed for use in this condition. The purpose of this study was to develop and validate a preference based measure from the CAMPHOR that could be used in cost-utility analyses.</p>", "<title>Methods</title>", "<p>Items were selected that covered major issues covered by the CAMPHOR QoL scale (activities, travelling, dependence and communication). These were used to create 36 health states that were valued by 249 people representative of the UK adult population, using the time trade-off (TTO) technique. Data from the TTO interviews were analysed using both aggregate and individual level modelling. Finally, the original CAMPHOR validation data were used to validate the new preference based model.</p>", "<title>Results</title>", "<p>The predicted health state values ranged from 0.962 to 0.136. The mean level model selected for analyzing the data had good explanatory power (0.936), did not systematically over- or underestimate the observed mean health state values and showed no evidence of auto correlation in the prediction errors. The value of less than 1 reflects a background level of ill health in state 1111, as judged by the respondents. Scores derived from the new measure had excellent test-retest reliability (0.85) and construct validity. The CAMPHOR utility score appears better able to distinguish between WHO functional classes (II and III) than the EQ-5D and SF-6D.</p>", "<title>Conclusion</title>", "<p>The tariff derived in this study can be used to classify an individual into a health state based on their responses to the CAMPHOR. The results of this study widen the evidence base for conducting economic evaluations of interventions designed to improve QoL for patients with PH.</p>" ]

[ "<title>Competing interests</title>", "<p>The study was sponsored by Actelion pharmaceuticals. Actelion may use the utility values derived in the study for cost-utility analyses relating to pulmonary hypertension treatments that they produce. Stephen McKenna and David Meads work for Galen Research Ltd who have, in the past, received other research funding from Actelion. A license is required for the commercial use of the CAMPHOR.</p>", "<title>Authors' contributions</title>", "<p>SM designed and managed the study, identified the items for the valuation exercise and wrote the manuscript. JR designed and managed the valuation survey, conducted analysis and reported on the valuation exercise. *DM ran the analysis to identify items for the valuation exercise, analysed the validation data and contributed to the writing of the manuscript. JB designed and managed the valuation survey, analysed and reported on the valuation data and contributed to the writing of the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank Actelion Pharmaceuticals UK Ltd for supporting the present study.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Item selection details</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Item</bold></td><td align=\"left\"><bold>%</bold><break/><bold> affirmation</bold></td><td align=\"left\"><bold>Corrected</bold><break/><bold>item-total</bold><break/><bold> correlation</bold></td><td align=\"left\"><bold>Factor</bold><break/><bold> loading</bold></td><td align=\"left\"><bold>Rasch</bold><break/><bold> location</bold></td><td align=\"left\"><bold>Mean</bold><break/><bold> change</bold></td></tr></thead><tbody><tr><td align=\"left\">7</td><td align=\"left\">32.2</td><td align=\"left\">.49</td><td align=\"left\">.54</td><td align=\"left\">0.84</td><td align=\"left\">0.07</td></tr><tr><td align=\"left\">12</td><td align=\"left\">65.9</td><td align=\"left\">.54</td><td align=\"left\">.60</td><td align=\"left\">-1.25</td><td align=\"left\">0.07</td></tr><tr><td align=\"left\">13</td><td align=\"left\">14.4</td><td align=\"left\">.30</td><td align=\"left\">.33</td><td align=\"left\">2.09</td><td align=\"left\">0.16</td></tr><tr><td align=\"left\">15</td><td align=\"left\">38.9</td><td align=\"left\">.64</td><td align=\"left\">.69</td><td align=\"left\">0.42</td><td align=\"left\">0.10</td></tr><tr><td align=\"left\">24</td><td align=\"left\">19.3</td><td align=\"left\">.46</td><td align=\"left\">.50</td><td align=\"left\">1.88</td><td align=\"left\">0.09</td></tr><tr><td align=\"left\">25</td><td align=\"left\">60.9</td><td align=\"left\">.64</td><td align=\"left\">.69</td><td align=\"left\">-1.00</td><td align=\"left\">0.00</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Sample health states defined by CAMPHOR</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">I can join in activities with my family and friends</td></tr><tr><td align=\"left\">Travelling distances is not a problem</td></tr><tr><td align=\"left\">I feel very dependent</td></tr><tr><td align=\"left\">I never find speaking too much of an effort</td></tr><tr><td/></tr><tr><td align=\"left\">I can join in activities with my family and friends</td></tr><tr><td align=\"left\">Travelling distances is not a problem</td></tr><tr><td align=\"left\">I feel very dependent</td></tr><tr><td align=\"left\">Sometimes it's too much effort to speak</td></tr><tr><td/></tr><tr><td align=\"left\">I can join in activities with my family and friends</td></tr><tr><td align=\"left\">Travelling distances is a problem</td></tr><tr><td align=\"left\">I don't feel very dependent</td></tr><tr><td align=\"left\">I never find speaking too much of an effort</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Descriptive characteristics of respondents</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Characteristics</bold></td><td align=\"left\" colspan=\"2\"><bold>Respondents</bold></td></tr><tr><td/><td align=\"left\">N</td><td align=\"left\">%</td></tr></thead><tbody><tr><td align=\"left\"><bold>Age</bold></td><td/><td/></tr><tr><td align=\"right\">18–25</td><td align=\"left\">12</td><td align=\"left\">4.8</td></tr><tr><td align=\"right\">26 to 35</td><td align=\"left\">28</td><td align=\"left\">11.2</td></tr><tr><td align=\"right\">36 to 45</td><td align=\"left\">63</td><td align=\"left\">25.3</td></tr><tr><td align=\"right\">46 to 55</td><td align=\"left\">54</td><td align=\"left\">21.7</td></tr><tr><td align=\"right\">56 to 65</td><td align=\"left\">50</td><td align=\"left\">21.1</td></tr><tr><td align=\"right\">66+</td><td align=\"left\">42</td><td align=\"left\">16.9</td></tr><tr><td align=\"left\"><bold>Gender</bold></td><td/><td/></tr><tr><td align=\"right\">Male</td><td align=\"left\">96</td><td align=\"left\">38.6</td></tr><tr><td align=\"right\">Female</td><td align=\"left\">153</td><td align=\"left\">61.4</td></tr><tr><td align=\"left\"><bold>Relationship status</bold></td><td/><td/></tr><tr><td align=\"right\">Married/living with partner</td><td align=\"left\">192</td><td align=\"left\">77.1</td></tr><tr><td align=\"right\">Living alone</td><td align=\"left\">57</td><td align=\"left\">22.9</td></tr><tr><td align=\"left\"><bold>Personal experience of serious illness</bold></td><td/><td/></tr><tr><td align=\"right\">Yes</td><td align=\"left\">81</td><td align=\"left\">32.5</td></tr><tr><td align=\"right\">No</td><td align=\"left\">168</td><td align=\"left\">67.5</td></tr><tr><td align=\"left\"><bold>Experience of serious illness in family</bold></td><td/><td/></tr><tr><td align=\"right\">Yes</td><td align=\"left\">164</td><td align=\"left\">66.1</td></tr><tr><td align=\"right\">No</td><td align=\"left\">84</td><td align=\"left\">33.9</td></tr><tr><td align=\"left\"><bold>Experience of serious illness in caring for others</bold></td><td/><td/></tr><tr><td align=\"right\">Yes</td><td align=\"left\">119</td><td align=\"left\">48.0</td></tr><tr><td align=\"right\">No</td><td align=\"left\">129</td><td align=\"left\">52.0</td></tr><tr><td align=\"left\"><bold>Main activity</bold></td><td/><td/></tr><tr><td align=\"right\">Employed or self employed</td><td align=\"left\">140</td><td align=\"left\">56.2</td></tr><tr><td align=\"right\">Other</td><td align=\"left\">109</td><td align=\"left\">43.8</td></tr><tr><td align=\"left\"><bold>Education after minimum school leaving age</bold></td><td/><td/></tr><tr><td align=\"right\">Yes</td><td align=\"left\">151</td><td align=\"left\">60.6</td></tr><tr><td align=\"right\">No</td><td align=\"left\">98</td><td align=\"left\">39.4</td></tr><tr><td align=\"left\"><bold>Degree or equivalent professional qualification</bold></td><td/><td/></tr><tr><td align=\"right\">Yes</td><td align=\"left\">103</td><td align=\"left\">41.4</td></tr><tr><td align=\"right\">No</td><td align=\"left\">146</td><td align=\"left\">58.6</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Consistent Mean and Random effects model results</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\" colspan=\"3\"><bold><italic>Mean level – model 1</italic></bold></td><td align=\"left\" colspan=\"2\"><bold><italic>Random effects – model 2</italic></bold></td></tr></thead><tbody><tr><td align=\"left\">Disvalue</td><td align=\"left\">Coef. (95% CI)</td><td align=\"left\">P<break/> value</td><td align=\"left\">Coef. (95% CI)</td><td align=\"left\">P<break/> value</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">Lev2 social act.</td><td align=\"left\">-0.297 (-0.345 to -0.249)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">-0.307 (-0.337 to -0.276)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\">Lev3 social act.</td><td align=\"left\">-0.308 (-0.357 to -0.258)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">-0.304 (-0.334 to -0.274)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\">Lev2 travelling</td><td align=\"left\">-0.202 (-0.250 to -0.154)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">-0.207 (-0.240 to -0.174)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\">Lev3 travelling</td><td align=\"left\">-0.223 (-0.273 to -0.173)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">-0.205 (-0.235 to -0.175)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\">Lev2 dependence</td><td align=\"left\">-0.147 (-0.188 to -0.108)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">-0.156 (-0.181 to -0.131)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\">Lev2 speaking</td><td align=\"left\">-0.147 (-0.187 to -0.107)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">-0.141 (-0.166 to -0.116)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\">Constant</td><td align=\"left\">0.962 (0.905 to 1.020)</td><td align=\"left\">&lt;0.001</td><td align=\"left\">0.961 (0.907 to 1.015)</td><td align=\"left\">&lt;0.001</td></tr><tr><td align=\"left\"><italic>N</italic></td><td align=\"left\">34</td><td/><td align=\"left\">249</td><td/></tr><tr><td align=\"left\">Adjusted R²</td><td align=\"left\">0.936</td><td/><td align=\"left\">0.373</td><td/></tr><tr><td align=\"left\">Inconsistencies</td><td align=\"left\">0</td><td/><td align=\"left\">2</td><td/></tr><tr><td align=\"left\">Mean absolute error</td><td align=\"left\">0.041</td><td/><td align=\"left\">0.042</td><td/></tr><tr><td align=\"left\">No. &gt; 0.05</td><td align=\"left\">12 (35%)</td><td/><td align=\"left\">13(38%)</td><td/></tr><tr><td align=\"left\">No. &gt; 0.10</td><td align=\"left\">2 (6%)</td><td/><td align=\"left\">2 (6%)</td><td/></tr><tr><td align=\"left\"><italic>Mean error</italic></td><td align=\"left\">0.000</td><td/><td align=\"left\">0.004</td><td/></tr><tr><td align=\"left\">LB</td><td align=\"left\">8.582</td><td/><td align=\"left\">10.711</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Comparison of predicted and actual values for selected health state classifications: mean level (ML) and random effects (RE) models</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Health</bold><break/><bold> State</bold></td><td align=\"left\"><bold>Actual mean</bold></td><td align=\"left\"><bold>Estimated mean</bold><break/><bold> (ML) model</bold></td><td align=\"left\"><bold>Estimated mean</bold><break/><bold> (RE) model</bold></td></tr></thead><tbody><tr><td align=\"left\">1111</td><td align=\"left\">N/A</td><td align=\"left\">0.962</td><td align=\"left\">0.961</td></tr><tr><td align=\"left\">1211</td><td align=\"left\">0.770</td><td align=\"left\">0.760</td><td align=\"left\">0.754</td></tr><tr><td align=\"left\">2121</td><td align=\"left\">0.515</td><td align=\"left\">0.517</td><td align=\"left\">0.498</td></tr><tr><td align=\"left\">2312</td><td align=\"left\">0.272</td><td align=\"left\">0.295</td><td align=\"left\">0.308</td></tr><tr><td align=\"left\">3322</td><td align=\"left\">0.156</td><td align=\"left\">0.136</td><td align=\"left\">0.155</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>Association between preference weights and perceived general health</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Rating of general health</bold></td><td align=\"left\"><bold>N</bold></td><td align=\"left\"><bold>Utility</bold></td></tr></thead><tbody><tr><td align=\"left\">Very good/good</td><td align=\"left\">35</td><td align=\"left\">0.69</td></tr><tr><td align=\"left\">Fair</td><td align=\"left\">36</td><td align=\"left\">0.49</td></tr><tr><td align=\"left\">Poor</td><td align=\"left\">16</td><td align=\"left\">0.37</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T7\"><label>Table 7</label><caption><p>Association between preference weights and perceived severity of PH</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>PH symptom severity</bold></td><td align=\"left\"><bold>N</bold></td><td align=\"left\"><bold>Utility</bold></td></tr></thead><tbody><tr><td align=\"left\">Mild</td><td align=\"left\">18</td><td align=\"left\">0.90</td></tr><tr><td align=\"left\">Moderate</td><td align=\"left\">23</td><td align=\"left\">0.56</td></tr><tr><td align=\"left\">Quite severe</td><td align=\"left\">22</td><td align=\"left\">0.49</td></tr><tr><td align=\"left\">Very severe</td><td align=\"left\">23</td><td align=\"left\">0.31</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T8\"><label>Table 8</label><caption><p>Preference weights for NYHA Classes II and III</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Mean (SD) utility value</bold></td><td align=\"left\" colspan=\"2\"><bold>CAMPHOR</bold></td><td align=\"left\"><bold>EQ-5D</bold></td><td align=\"left\"><bold>SF-6D</bold></td></tr></thead><tbody><tr><td/><td align=\"left\">Time 1</td><td align=\"left\">Time 2</td><td/><td/></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">NYHA Class II</td><td align=\"left\">0.70 (0.24)</td><td align=\"left\">0.66 (0.29)</td><td align=\"left\">0.69 (0.24)</td><td align=\"left\">0.67 (0.10)</td></tr><tr><td align=\"left\">NYHA Class III</td><td align=\"left\">0.48 (0.24)</td><td align=\"left\">0.45 (0.24)</td><td align=\"left\">0.59 (0.24)</td><td align=\"left\">0.60 (0.10)</td></tr><tr><td align=\"left\">Difference</td><td align=\"left\">0.22</td><td align=\"left\">0.20</td><td align=\"left\">0.10</td><td align=\"left\">0.07</td></tr><tr><td align=\"left\">Effect size if patients move from Class III to Class II</td><td align=\"left\">0.92</td><td align=\"left\">0.71</td><td align=\"left\">0.42</td><td align=\"left\">0.70</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula id=\"bmcM1\"><label>(1)</label><italic>Yi </italic>= <italic>f</italic>(<italic>β</italic>'<bold>x</bold>_{<italic>ij</italic>}) + <italic>Є</italic>_{<italic>i</italic>}</disp-formula>", "<disp-formula id=\"bmcM2\"><label>(2)</label><italic>Yij </italic>= <italic>f</italic>(<italic>β</italic>'<bold><italic>x</italic></bold>_{<italic>ij</italic>}) + <italic>Є</italic>_{<italic>ij</italic>}</disp-formula>", "<disp-formula id=\"bmcM3\"><label>(3)</label><italic>Є</italic>_{<italic>ij </italic>}= <italic>u</italic>_{<italic>j </italic>}+ <italic>e</italic>_{<italic>ij</italic>}</disp-formula>" ]

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[ "<title>Background</title>", "<p>Chronic diseases such as infectious disease, cancer, and diabetes are among the most common and costly health problems. The therapy of chronic diseases often lasts for a long time, while the treatment effect may be questionable and yet the side effects may be serious. Hepatitis C virus (HCV) is one of the major causes of chronic hepatitis, cirrhosis, and hepatocellular carcinoma. The current recommended treatment for chronic HCV infection is the combination of pegylated alpha interferon (peginterferon) and the oral antiviral drug ribavirin given for 24 or 48 weeks, but the chance to induce a sustained response is only 54%–56%[##REF##12500189##1##]. Using interferon and ribavirin for a long time may cause serious side effects, such as fever, chills, body aches, headaches, myeloid disorders[##REF##11263440##2##] and neuropsychiatric symptoms[##REF##15468615##3##]. The patients with poor response should better give up such treatment in the early stage. However the underlying mechanisms for different responses are not fully understood and it is hard to foresee treatment effects by conventional methods.</p>", "<p>We analyzed a published time series microarray dataset of a virological research in which the effects of pegylated interferon and ribavirin on 33 African-American (AA) and 36 Caucasian American (CA) patients with chronic HCV infection were studied[##REF##17267482##4##]. We established a diagnostic model to predict the outcome of pegylated interferon and ribavirin therapy using time series microarray gene expression profiles for AA and CA patients separately.</p>", "<p>Although the focus here is on how HCV infected patients respond to pegylated interferon treatment, the model described is generally applicable to other chronic diseases undergoing long term treatment.</p>" ]

[ "<title>Methods</title>", "<title>Original time-series microarray data applied in our study</title>", "<p>The original time-series microarray data used in this work is from a study of Milton W. Taylor which was published on Journal of Virology last year[##REF##17267482##4##], and publicly available at GEO <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/geo\"/> under accession number GSE7123. The initial data set consists of the gene expression profiles of 33 African-American and 36 Caucasian American patients with chronic HCV genotype 1 infection on day 0 (pretreatment), and 1, 2, 7, 14, and 28 of pegylated interferon and ribavirin therapy. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells (PBMC) of the patients at each time point. For each patient the decrease of HCV RNA level was calculated by subtracting baseline level (before treatment) from the level on day 28. Good response was defined as a decrease of more than 1.4 log₁₀IU/ml of HCV RNA level; and poor response was defined as less than 1.4 log₁₀IU/ml decline from the base level. Only patients with all the gene expression data of 6 time points were involved in our analysis, including 30 Caucasian Americans (CA) of whom 17 were good responders and 13 were poor, 28 African-Americans (AA) of whom 19 were good responders and 9 were poor.</p>", "<title>Data preprocessing</title>", "<p>First, we normalized the data of total 348 microarrays using quantile method and log₂-trasformed them. Only probes that were present in at least 75% microarrays with log₂intensities greater than 7 were kept for further analysis. This resulted in a subset of approximately 13620 probesets representing 9100 different genes.</p>", "<title>Statistical analysis to identify differentially expressed genes</title>", "<p>To avoid bias that may be created by single feature-selecting statistical method, we constructed a voting method based on several methods including Student's t test[##UREF##0##5##], Wilcoxon test[##UREF##1##6##], empirical Bayes test (eBayes) [##REF##16646809##7##]and significance analysis of microarray(SAM)[##REF##11309499##8##] to identify differentially expressed genes. Only genes that passed three out of the four methods were regarded as differentially expressed. The selection criterion was set at a defined P value for all four statistical tests.</p>", "<title>Time-dependent diagnostic model</title>", "<p>The classifier used in our program at each time point was C4.5-a decision tree classification method [##UREF##2##9##]. With leave-one-out cross-validation, the model was trained and tested at each time point. The framework is illustrated in Figure ##FIG##0##1## and detailed as follows:</p>", "<title>Train the model</title>", "<p>Each patient in the training set was regarded as an instance and the class label for him was the outcome of the treatment. At each time point, differentially expressed genes between good and poor response group were identified using the voting method described above as the marker probe sets of this time point. At the first time point (time point 0, before treatment), the features were that day's gene expression values of the marker probe sets at that time point; at the following time point during the treatment, the features were the combination of that day's gene expression values of marker probe sets at that time point and features of previous time points. For example, the features at day 1 are the expression values of differentially expressed genes at day 1 and the expression values of differentially expressed genes at day 0.</p>", "<p>Every patient is assumed treatable until predicted as nontreatable with sufficient differentially expressed genes at that day. For each time point, if the number of differentially expressed genes was equal or greater than 5, the C4.5 classifier will be constructed at this time point; otherwise, differentially expressed gene number at this time point will be set as null and no C4.5 classifier will be trained at this time point. This check step helps to avoid false negative decision.</p>", "<title>Test the model</title>", "<p>At each time of leave-one-out cross-validation, we used the data of N-1 patients to build a model and then applied it on the one left patient to predict his treatment outcome. If a patient was predicted as treatable by every time point's classifier, this was a positive prediction. If the final outcome according to the HCV RNA level decline was good response for this patient, this was a true positive prediction; otherwise, it was a false positive prediction.</p>", "<p>If a patient was predicted as nontreatable by one of the six classifiers (day 0, 1, 2, 7, 14 and 28), this was a negative prediction. That means this patient should be eliminated from the treatment and the workflow of this patient will stop at that time point. If the real outcome was poor response for this patient, this was a true negative prediction; otherwise, this was a false negative prediction.</p>", "<p>The prediction accuracy Q of leave-one-out cross-validation was calculated as follows:</p>", "<p></p>", "<p>tp, tn, fp and fn stand for true positive, true negative, false positive and false negative, respectively. Detailed information about this model, including processed microarray data, R code and results, can be found in Additional file ##SUPPL##0##1## and file ##SUPPL##1##2##.</p>", "<title>Relevance and significance of candidate biomarkers</title>", "<p>To assess the biological relevance of the identified candidate biomarkers which were important for CA response prediction, we used PubGene to find relationships between these candidate biomarkers and IFN (Interferon)/HCV (Hepatitis C viruses). PubGene <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.pubgene.org/\"/> is a tool to carry out automated extraction of explicit and implicit biomedical knowledge from publicly available gene and text databases to create a gene-to-gene co-citation network by automated analysis of titles and abstracts in MEDLINE records[##REF##11326270##10##]. Moreover, GO and KEGG category enrichment analyses were applied to validate the functional and pathway relevance of selected candidate biomarkers.</p>" ]

[ "<title>Results</title>", "<title>Time-dependent diagnostic model</title>", "<p>The true power of time series microarray analysis does not come from the analysis of single time point, but rather, from the analysis of a series of time points to identify a biomarker chain. The main idea of our model is to fully utilize gene expression profiles before and during treatment to predict the final treatment outcome.</p>", "<p>The time-dependent diagnostic results of all patients, AA patients and CA patients are shown in Figure ##FIG##1##2##. It illustrates that true negative CA patients were all correctly detected on day 1 and true negative AA patients were mostly detected on day 1 and 7. The leave-one-out cross-validation results of all patients, AA patients and CA patients are given in Table ##TAB##0##1##. In the preliminary research, we found that the numbers of differentially expressed genes in all patients, AA patients and CA patients under the same cut-off P value were quite different. To balance the numbers of differentially expressed genes in different groups, P values given to identify differentially expressed genes in all patients, AA patients and CA patients were 0.00001, 0.001 and 0.0001, respectively.</p>", "<title>Simplified Time-dependent diagnostic model</title>", "<p>We have known that if only static gene expression profiles before treatment were used the prediction accuracy was rather low (data not shown). However from the above results, it occurred to us that the seemingly complicated models may actually be simplified to day 1 classifier – depending only on gene expression profiles of very early treatment time point. The leave-one-out cross-validation accuracy based on day 1 classifier (including day 0 and day 1 gene expression profiles) of CA patients could achieve 100%, the same as the result using data of all the time points. With AA patients, the accuracy dropped some, but still much better than if only using pre-treatment gene expression profile. The leave-one-out cross-validation results of all patients, AA patients and CA patients on day 1 are given in Table ##TAB##1##2##.</p>", "<title>Identification of candidate biomarkers of CA patients</title>", "<p>As stated above, CA patients of HCV infection are more sensitive to the therapy of interferon and ribavirin, and after one day treatment the outcome could be one hundred percent predicted. Using the feature selection methods described in Methods section, we identified 30 differentially expressed genes or probes on day one between 17 good response CA patients and 13 poor response CA patients as the candidate biomarkers relevant to interferon therapy response. They are EIF3S5, HSPA9, ABLIM1, RPL4 (201154_x_at), MARCKS, HTRA2, SH2B3, KIAA0999, LCK, C8orf70, TTLL1, CD86, TUFT1, KLRK1, PARP1, KPNB1, NT5C2, RPL4 (211710_x_at), MRPS27, AOF2, HSD17B8, RBMX, TNFSF10, SMARCA4, C14orf122, KIAA0748, PCID2, DNAPTP6, TLE2 and CYFIP2. Their detailed probe information are provided in Additional file ##SUPPL##2##3##.</p>", "<p>The time series expression profiles of two representative genes TNFSF10 (tumor necrosis factor (ligand) superfamily, member 10) and KLRK1 (killer cell lectin-like receptor subfamily K, member 1) are shown in Figure ##FIG##2##3##. In Figure ##FIG##2##3A##, at most of the time, the difference of TNFSF10 expression level between Good response CA and Poor response CA is much greater than the difference between Good response AA and Poor response AA. Moreover, the difference between Good response CA and Poor response CA increases with time, but the difference between Good response AA and Poor response AA decreases with time. In Figure ##FIG##2##3B##, the same phenomenon can be observed on day 1 and 7. Many other genes showed similar tendency at earlier time points. Maybe this partly explains why the treatment of CA patients can be more accurately predicted than AA patients. The dynamic expression graphics of all thirty genes are provided in Additional file ##SUPPL##3##4##.</p>", "<p>To further evaluate whether these expression signatures are associated with therapeutic outcome (good or poor response), we conducted clustering of CA patients using differentially expressed genes on day 1 between CA groups of good and poor outcome (Figure ##FIG##3##4C##), and compared it with the clustering result of all patients using differentially expressed genes on day 1 between all patients of good and poor outcome(Figure ##FIG##3##4A##), of AA patients using differentially expressed genes on day 1 between AA groups of good and poor outcome (Figure ##FIG##3##4B##).</p>", "<p>It can be seen that Figure ##FIG##3##4C## best clustered its patients. These thirty genes could classify the CA patients into good responders and poor responders very well. Therefore the simplified day 1 diagnostic model can clearly be applied to CA patients.</p>", "<title>Relevance and significance of candidate biomarkers</title>", "<p>The relationship between those candidate biomarkers and IFN (Interferon)/HCV (Hepatitis C viruses) were explored by using PubGene. The two literature networks are shown in Additional file ##SUPPL##4##5##, indicating six genes that have direct connections with both IFN and HCV. They are LCK (lymphocyte-specific protein tyrosine kinase), NT5C2 (5'-nucleotidase, cytosolic II), KLRK1 (killer cell lectin-like receptor subfamily K, member 1), CD86 (CD86 antigen (CD28 antigen ligand 2, B7-2 antigen)), PARP1 (poly (ADP-ribose) polymerase family, member 1) and TNFSF10 (tumor necrosis factor (ligand) superfamily, member 10). It has been reported that IFN-alpha can significantly enhance CD86 expression on dendritic cells from chronic hepatitis C patients[##REF##17501761##11##,##REF##17439521##12##]. The ligation of tumor necrosis factor receptor (TNFR1) can initiate apoptosis or programmed cell death which is part of interferon (IFN)-mediated anti-viral action[##REF##11222103##13##].</p>", "<p>GO category enrichment analysis results (see Additional file ##SUPPL##5##6##) show that many of these candidate biomarkers are involved in immunity, such as T cell differentiation and positive regulation of T cell activation, which are concerned with antivirus.</p>", "<p>The KEGG category enrichment analysis (see Additional file ##SUPPL##5##6##) illustrates that three candidate biomarkers (LCK, lymphocyte-specific protein tyrosine kinase; KLRK1, killer cell lectin-like receptor subfamily K, member 1; TNFSF10, tumor necrosis factor (ligand) superfamily, member 10) are components of the Natural killer cell mediated cytotoxicity pathway, which is important in antineoplastic, antivirus and immune regulation. It has been reported that impairment of natural killer cell activity is associated with chronic hepatitis C virus infection[##REF##12217606##14##].</p>" ]

[ "<title>Discussion</title>", "<p>It is evident that the prediction accuracy of CA patients is higher than AA patients. Constitutively different responses of black and white hepatitis C patients to pegylated interferon and ribavirin therapy had been reported[##REF##15880320##15##] before our study. It shows in our study as, markers that may be important for predicting response did not change as remarkably in AA patients as in CA patients. Our diagnostic model did not perform well on AA patients who did not demonstrate sufficient differentially expressed genes at early time points.</p>", "<p>Our results implied that if there is a sensitive change of gene expression profile at early treatment time points, the diagnostic model will be more sensitive and useful. This was confirmed by the simplified diagnostic model. With day 1 model CA patients with HCV infection who are more responsive to interferon and ribavirin therapy can already be predicted of their treatment outcome after 28 days. With less sensitive response the diagnostic model may need to be stretched to include profiles after longer time treatment, like in AA patients. Even with AA patients, profiles of early time points are sufficient for making reasonable predictions of outcome. This is good news for clinical and experimental workers. It means that the strategy of using early time-treatment gene expression profiling to predict outcome for potential long-term treatment is affordable and applicable.</p>", "<p>Microarray gene expression analysis has been proved valuable in numerous applications including disease classification, diagnosis, survival analysis, choice of therapy etc, but rarely for more complex clinical problems such as the dynamic prediction of treatment effects we addressed in this paper. We tried several methods including traditional statistical techniques and the latest computer-intensive techniques to predict the final treatment effects based on the static gene expression profiles before treatment and the prediction results were unacceptable. Dynamic prediction chains using time series gene expression profiles have been proved to make more successful prediction model. There were two outcome prediction studies based on 70-gene expression dataset generated by kinetic reverse-transcription PCR from 52 multiple sclerosis patients treated with rIFNβ[##REF##15630474##16##,##REF##17094268##17##]. They obtained good results but were limited to the 70 genes. Our model directly applied on large-scale microarray data, and may have found some novel biomarkers. Our results justify further biological studies to evaluate whether these candidate biomarkers could truly predict the effect of interferon and ribavirian therapy. Further investigations may shed light on the mechanisms of different responses between CA patients and AA patients of HCV infection to this kind of therapy.</p>" ]

[ "<title>Conclusion</title>", "<p>Our time-dependent diagnostic model suggests a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatics strategies may be used to improve treatment decisions for other chronic diseases. This may be an important strategy in future personalized medicine.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study.</p>", "<title>Methods</title>", "<p>In the published study, 33 African-American (AA) and 36 Caucasian American (CA) patients with chronic HCV genotype 1 infection received pegylated interferon and ribavirin therapy for 28 days. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells (PBMC) of all the patients on day 0 (pretreatment), 1, 2, 7, 14, and 28. According to the decrease of HCV RNA levels on day 28, two categories of responses were defined: good and poor. A voting method based on Student's t test, Wilcoxon test, empirical Bayes test and significance analysis of microarray was used to identify differentially expressed genes. A time-dependent diagnostic model based on C4.5 decision tree was constructed to predict the treatment outcome. This model not only utilized the gene expression profiles before the treatment, but also during the treatment. Leave-one-out cross validation was used to evaluate the performance of the model.</p>", "<title>Results</title>", "<p>The model could correctly predict all Caucasian American patients' treatment effects at very early time point. The prediction accuracy of African-American patients achieved 85.7%. In addition, thirty potential biomarkers which may play important roles in response to interferon and ribavirin were identified.</p>", "<title>Conclusion</title>", "<p>Our method provides a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatical strategies may be used to improve treatment decisions for other chronic diseases.</p>" ]

[ "<title>Authors' contributions</title>", "<p>TH and KT carried out the study. TH and LX wrote the manuscript. LX and YxL supervised the project. YS provided statistical suggestions, CcW contributed discussions. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank Editor Francesco Marincola for his responsible attitude and encouraging comments to our manuscript. We also would like to thank Dr. Hongyue Dai for his insightful comment. Funding for this research was provided by Shanghai Pujiang program 06PJ14073, National High-Tech R&amp;D Program (863): 2006AA02Z334, 2007AA02Z332, and National Basic Research Program of China 2006CB910700, 2004CB720103, 2004CB518606.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>The framework of time-dependent diagnostic model</bold>. \"nontreatable\" means the patient was predicted to have a poor response and should be eliminated from the treatment, \"treatable\" means the patient was predicted to have a good response and should keep the treatment.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>The leave-one-out cross-validation results of time-dependent diagnostic models based on all patients, AA patients and CA patients</bold>. On day one, most nontreatable patients could be detected correctly. \"T\" means true prediction; \"F\" means false prediction.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>The time series expression of two representative genes TNFSF10 (tumor necrosis factor (ligand) superfamily, member 10) and KLRK1 (killer cell lectin-like receptor subfamily K, member 1)</bold>. The horizontal axis depicts days that the treatment has lasted, the vertical axis stands for expression mean values with error bar. Different colour indicates different groups of patients.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Unsupervised two-way hierarchical clustering based on expression profiles of differentially expressed genes of all patients on day 1(A), AA patients on day 1(B), and CA patients on day 1(C). P values given to identify differentially expressed genes in all patients, AA patients and CA patients were 0.00001, 0.001 and 0.0001, respectively. The bar indicates the response status of patients.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>The Leave-one-out cross-validation results of all patients, AA patients and CA patients.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\">All patients</td><td align=\"center\" colspan=\"3\">AA patients</td><td align=\"center\" colspan=\"3\">CA patients</td></tr></thead><tbody><tr><td/><td/><td align=\"center\">Predicted<break/> Good</td><td align=\"center\">Predicted<break/> poor</td><td/><td align=\"center\">Predicted<break/> Good</td><td align=\"center\">Predicted<break/> poor</td><td/><td align=\"center\">Predicted<break/> Good</td><td align=\"center\">Predicted<break/> poor</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">2 × 2 Table</td><td align=\"center\">Actual<break/> Good</td><td align=\"center\">28</td><td align=\"center\">8</td><td align=\"center\">Actual<break/> Good</td><td align=\"center\">16</td><td align=\"center\">3</td><td align=\"center\">Actual<break/> Good</td><td align=\"center\">17</td><td align=\"center\">0</td></tr><tr><td/><td align=\"center\">Actual<break/> poor</td><td align=\"center\">8</td><td align=\"center\">14</td><td align=\"center\">Actual<break/> poor</td><td align=\"center\">1</td><td align=\"center\">8</td><td align=\"center\">Actual<break/> poor</td><td align=\"center\">0</td><td align=\"center\">13</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">Accuracy</td><td/><td align=\"center\">72.4%</td><td/><td/><td align=\"center\">85.7%</td><td/><td/><td align=\"center\">100%</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>The leave-one-out cross-validation results of all patients, AA patients and CA patients on day 1.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\">All patients</td><td align=\"center\" colspan=\"3\">AA patients</td><td align=\"center\" colspan=\"3\">CA patients</td></tr></thead><tbody><tr><td/><td/><td align=\"center\">Predicted<break/> Good</td><td align=\"center\">Predicted<break/> poor</td><td/><td align=\"center\">Predicted<break/> Good</td><td align=\"center\">Predicted<break/> poor</td><td/><td align=\"center\">Predicted<break/> Good</td><td align=\"center\">Predicted<break/> Poor</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">2 × 2 Table</td><td align=\"center\">Actual <break/>Good</td><td align=\"center\">28</td><td align=\"center\">8</td><td align=\"center\">Actual<break/> Good</td><td align=\"center\">16</td><td align=\"center\">3</td><td align=\"center\">Actual <break/>Good</td><td align=\"center\">17</td><td align=\"center\">0</td></tr><tr><td/><td align=\"center\">Actual<break/> poor</td><td align=\"center\">8</td><td align=\"center\">14</td><td align=\"center\">Actual<break/> poor</td><td align=\"center\">4</td><td align=\"center\">5</td><td align=\"center\">Actual <break/>poor</td><td align=\"center\">0</td><td align=\"center\">13</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">Accuracy</td><td/><td align=\"center\">72.4%</td><td/><td/><td align=\"center\">75%</td><td/><td/><td align=\"center\">100%</td><td/></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Processed microarray data, R code and results of time-dependent diagnostic model (part 1). Additional file ##SUPPL##0##1## and file ##SUPPL##1##2## should be downloaded together. R code is for the performance of model construction.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Processed microarray data, R code and results of time-dependent diagnostic model (part 2). Additional file ##SUPPL##0##1## and file ##SUPPL##1##2## should be downloaded together. R code is for the performance of model construction.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Detailed probe information of thirty candidate biomarkers. The probe information comes from the original microarray probe set.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>Dynamic expression graphics of thirty candidate biomarkers. For each of the thirty candidate biomarkers a graph of its expression levels in four groups of patients (good CA, poor CA, good AA, poor AA) at all time points is given.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p>Literature networks of thirty candidate biomarkers in relation to IFN (Interferon)/HCV (Hepatitis C viruses). The six genes that have direct connections with both IFN and HCV are framed with blue boxes.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S6\"><caption><title>Additional file 6</title><p>GO and KEGG category enrichment analyses of thirty candidate biomarkers. Thirty-seven enriched GO biological processes and ten GO molecular functions as well as one enriched KEGG pathway are shown (p &lt; 0.01).</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>* Good means good response, poor means poor response.</p></table-wrap-foot>", "<table-wrap-foot><p>* Good means good response, poor means poor response.</p></table-wrap-foot>" ]

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[ "<title>Background</title>", "<p>Drug eluting stent (DES) has dramatically reduced restenosis risks compared with bare metal stent (BMS) and conventional balloon angioplasty [##REF##14523139##1##, ####REF##14769686##2##, ##REF##16580520##3####16580520##3##]. Angiographic analysis found that the majority of DES restenosis were focal, localized, and bordered by segments with no angiographic evidence of neointima, while BMS restenosis tended to be diffuse or proliferative [##REF##12860901##4##,##REF##12719283##5##]. Thereby, DES has revolutionized revascularization therapy and is rapidly becoming the standard for percutaneous coronary intervention (PCI).</p>", "<p>Although the incidence of late stent thrombosis is very low, DES may increase the risk for late events, especially associated with discontinuation of dual anti-platelet therapy [##REF##17174201##6##,##REF##17145250##7##]. Considering that the patients are difficult in anti-platelet compliance and more drug cost, we have to ask whether all lesions need DES and what specific lesion types are independent of DES therapy. Factors known to increase the risks of in-stent restenosis include smaller vessel diameter, prior restenosis, length of stented vessel, and diabetes mellitus [##REF##10545431##8##,##REF##17010786##9##]. However, few of study reported that a simple de novo lesion, for example, lesion type A/B1[##REF##2969312##10##,##REF##2401060##11##] in the middle and large vessel was treated with single BMS vs single DES at short- and long-term follow-up.</p>", "<p>Thus we investigated the efficacy and safety of single BMS vs. single DES in nondiabetic patients with a simple de novo lesion in the middle and large vessel at 6-month, 1-year and 3-year follow-up in real world.</p>" ]

[ "<title>Methods</title>", "<title>Study population</title>", "<p>Demographic and procedural data were retrieved from a dedicated PCI database between Apr 2004 to Dec 2004 at Fu Wai hospital. Only a simple de novo lesion in single middle and large vessel, stent diameter ≥ 3.0 mm, stent length ≤ 18 mm were included. The unprotected left main disease ≥ 50% stenosis, left ventricular ejection fraction ≤ 30% and diabetic patients including definite diabetic patients, newly diagnosed patients and diet controlled patients were the major exclusion criteria. Finally, there were 150 patients in BMS group and 85 patients in DES group.</p>", "<title>Procedures and relevant medications</title>", "<p>All patients were pretreated with aspirin and either ticlopidine or clopidogrel. A 300 mg loading dose of clopidogrel was administered before the procedure if patients were not pretreated. During the procedure, a bolus dose of unfractionated heparin (100 U/kg) was administered after femoral or radial artery sheath insertion, with repeat bolus given as needed to maintain activated cloting time between 250 to 300 seconds. The administration of glycoprotein IIb/IIIa inhibitors Tirofiban was left to the operator's discretion. The operators were free to use the BMS or DES that they considered best. BMS included Coroflex Delta, Driver, Express 2, micro-Driver, Multi-Link Mini Vision, Multi-Link Vision, Multi-Link Zeta, Mustang and Tecnic Carbostent, DES included Cypher, Cypher Select, Firebird and Taxus Express 2.</p>", "<p>All patients kept on aspirin therapy (300 mg/day for 3 months and 100 mg/day in lifelong time). Ticlopidine (500 mg/day) or Clopidogrel (75 mg/day) was administered for 6 to 12 months after DES implantation or for 3 months in BMS group.</p>", "<title>Clinical definitions and follow-up</title>", "<p>The clinical data were reviewed to obtain from a computerized database by specialized personnel at the cardiovascular interventional center in Fu Wai hospital. Risk factors for coronary artery disease that were tabulated included diabetes mellitus (only if treated medically), hypertension (only if treated medically), and hyperlipidemia (only if treated medically or if serum cholesterol was 240 mg/dl), but in this study we excluded diabetic patients. The diagnosis of acute myocardial infarction (AMI) during hospitalization and follow-up was based on the presence of new Q wave on electrocardiogram and/or elevation of creatine kinase MB to at least three times the upper limit of the normal range [##REF##9672272##12##]. Simpsons method was used for LVEF measurement by the blind to two observers.</p>", "<p>Quantitative coronary angiography analysis was made using a validated, edge detection system (MED CON QCA software). Lesion length was defined as the distance from the proximal to the distal shoulder of the lesion. The degree of stenosis before and after angioplasty was measured after intracoronary injection of nitrates in the view showing the most severe stenosis, and expressed as the minimum lumen diameter and the linear percent lumen diameter reduction, using the average diameter of the nearest proximal and distal normal segments as the reference. In-segment restenosis was defined as diameter stenosis ≥ 50% within a previously stented segment (5 mm proximal and distal to stent) using follow-up angiograms. A blood flow rate of grade 1 or higher according to the classification of the Thrombolysis in Myocardial Infarction (TIMI) trial.</p>", "<p>Stent thrombosis was defined as occlusion of either vessel or thrombus within or adjacent to a previously successfully stented vessel from angiographic evidence or, in the absence of angiographic confirmation, either AMI in the distribution of the treated vessel or death not clearly attributable to other causes [##REF##14724301##13##]. In-stent thrombosis was categorized according to the timing of the event into: acute thrombosis (within 24 hours after the procedure), subacute thrombosis (from postprocedure 1 to 30 days), late thrombosis (&gt; 30 days and &lt; 1 year) and very late thrombosis (≥ 1 year). Target lesion revascularization (TLR) was defined as any symptom driven coronary artery bypass graft or repeat PCI for restenosis or closure of the target lesion. MACE included recurrent myocardial infarction (Re-MI), cardiac death and TLR. Data for patients who did not have MACE were censored either at 3 years or at the last known time of follow-up. Data for patients who died before 3-year follow-up were censored at the time of death.</p>", "<p>A patient's clinical status was assessed by outpatient interview or telephone conversation. All patients were asked to return for coronary angiography approximately six months after the procedure, or earlier if angina symptoms occurred. Telephone interviews or outpatient interview were repeated at twelve months and three years after the procedure. Relevant data were collected and entered into a computerized database by specialized personnel at the cardiovascular interventional center in Fu Wai hospital.</p>", "<title>Statistical analysis</title>", "<p>All statistical analyses were performed with SPSS for Windows (version 10.0, Chicago). Continuous variables were described as mean ± SD, and categorical variables were reported as percentages or proportions. The comparisons of continuous variables were performed with unpaired t-tests (normal distribution) and nonparametric Mann-Whitney U test (skew distribution). The analysis of categorical variables was performed with Fisher's exact test and Chi-square test. Kaplan-Meier time-to-event estimates was used for the primary events at 1-year and 3-year of follow-up, which were compared with the log-rank test between BMS group and DES group. All reported P values were two-sided, and a P value &lt; 0.05 was considered statistically significant.</p>" ]

[ "<title>Results</title>", "<p>Baseline clinical characteristics were shown in table ##TAB##0##1##. Compared to DES group, the patients in BMS group had lower hypercholesteremia rate (22.0% vs 38.8%, P = 0.006), but age, gender, other risk factors for coronary artery disease and left ventricular function were similar in the two groups (all P &gt; 0.05).</p>", "<p>During procedure and in-hospital, BMS group had higher proportion of TIMI grade 0 than DES group (12.0% vs 1.2%, P &lt; 0.05), but other variable including calcified lesion (%), lesion length (mm), stent diameter (mm), percentage of lumen stenosis (%), balloon predilatation (%), stent length (mm), post-dilatation (%), vessel dissection (%), postprocedural residual stenosis (%) and in-hospital outcomes did not significantly differ (all P &gt; 0.05) in table ##TAB##1##2##. Despite that BMS had higher acute thrombosis rate than DES (3.3% vs 0%, P = 0.162), these patients recovered reperfusion after thrombolysis and intra-aortic balloon pump therapy, there were not in-hospital TLR and death in BMS group.</p>", "<p>Repeat coronary angiography at 6-month follow-up showed similar acute and subacute thrombosis (%), late thrombosis (%), in-segment restenosis (%), TLR (%) and composite of cardiac death or Re-MI (%) in the two groups (all P &gt; 0.05) in table ##TAB##2##3##.</p>", "<p>The rates of lost to follow up at 3-year follow-up were 6.7% and 1.2% between BMS and DES group. The both groups had not significant differences in primary events including TLR (1.3% vs 1.2%, P = 1.00) and recurrent myocardial infarction (Re-MI) (0% vs 1.2%, P = 0.36) or cardiac death (0.7% vs 1.2%, P = 1.00) between 1- and 3-year, So were Re-MI (%), cardiac death (%), TLR (%) and MACE (%) at 1- and 3-year follow-up (all P &gt; 0.05) in table ##TAB##3##4##.</p>", "<p>The cumulative survival free of cardiac death in BMS group vs DES group was 100% vs 100% (Log rank P = 1.000) at 1-year and 98.67% vs 97.65% (Log rank P = 0.559) at 3-year follow-up (Fig. ##FIG##0##1##). Similarly, TLR-free cumulative survival between BMS group and DES group was 95.33% vs 95.29% (Log rank P = 0.978) at 1-year and 94.00% vs 94.12% (Log rank P = 0.984) at 3-year follow-up (Fig. ##FIG##1##2##). Noticeably, there was a trend towards a decrease of Re-MI-free cumulative survival in the DES group compared with the BMS group at 1-year (98.82% vs 100%, Log rank P = 0.183) and 3-year follow-up (97.65% vs 100%, Log rank P = 0.059) (Fig. ##FIG##2##3##).</p>" ]

[ "<title>Discussion</title>", "<p>This is the first study to investigate efficacy and safety of single BMS vs. single DES in nondiabetic patients with a simple de novo lesion in the middle and large vessel at 3-year follow-up in real world. The present study found that both DES group and BMS group had similar acute and subacute thrombosis (%), late thrombosis (%), in-segment restenosis (%), TLR (%), composite of cardiac death or Re-MI (%) at 6-month follow-up, so were Re-MI (%), cardiac death (%), TLR (%) and MACE (%) at 1- and 3-year follow-up in the two groups, furthermore, nonsignificant difference in the cardiac death-free and TLR-free cumulative survival rates except that there was a trend towards a decrease of Re-MI-free cumulative survival rate in DES group compared with BMS group at 1- and 3-year follow-up (all P &gt; 0.05).</p>", "<p>The previous study found that vessel diameter was an established predictor of angiographic outcome after catheter-based intervention, with a higher restenosis rate in smaller vessels [##REF##8087933##14##]. Thereby, at the time of these pilot studies, sirolimus-eluting stents were only available in a 3.0 mm or 3.5 mm diameter, limiting treatment to relatively large vessels, these sirolimus-eluting stents showed 0% restenosis at 4-month [##REF##11208675##15##], 6-month [##REF##11686669##16##], and 12-month [##REF##11673337##17##]. Later, a study demonstrated that the classic inverse relationship between vessel diameter and restenosis rate was seen in the BMS group but not in the sirolimus-eluting stent group [##REF##12370218##18##], and vessel sizes of 2.5 – 3.5 mm were allowed in the subsequent randomized study with the sirolimus-coated Bx velocity balloon-expandable stent in the treatment of patients with de novo native coronary artery lesions (RAVEL) trial, yet lesions still had to be covered with one stent [##REF##12050336##19##].</p>", "<p>Currently, based on a lot of studies, people began to believe that the restenosis at the site of stent implantation seen in 15–60% of patients was dependent on various confounding factors, such as the presence or absence of diabetes mellitus, the size of the targeted coronary artery, the length of the coronary lesion, and the degree of vessel patency achieved by the intervention [##REF##9728982##20##, ####REF##8837554##21##, ##REF##8822967##22##, ##REF##9362398##23##, ##REF##9581723##24##, ##REF##12900339##25####12900339##25##]. DES has been shown to reduce the risk of restenosis compared with BMS [##REF##14523139##1##,##REF##12050336##19##,##REF##12900339##25##,##REF##15491330##26##]. Despite that treatment of specific lesions types, especially in stent restenosis and distal stenosis of left main coronary, as well as diabetic patients, remains suboptimal with DES, whereas considering that DES practice including complex interventions is safe and associated with significant reductions in clinical driven repeat revascularization rates [##REF##17630659##27##]. Moreover, DES also can effectively treat in-stent restenosis and saphenous vein graft restenosis [##REF##16635600##28##, ####REF##16531619##29##, ##REF##17276188##30####17276188##30##], thus it appears to be the advent of transition from BMS to DES in routine PCI practice.</p>", "<p>However, we do not disregard an important problem of DES, that is, thrombosis. Especially subacute in-stent thrombosis could occur more frequently with DES than with BMS and a prolonged anti-platelet regimen is mandatory [##UREF##0##31##]. In spite of the use of anti-platelet agents, stent thrombosis occurs in approximately 1% of patients, with an increased likelihood of occurrence in high-risk patients or complex lesion subset of patients [##REF##17296827##32##,##REF##15078797##33##]. According to the previous report, triple anti-platelet therapy (aspirin + clopidogrel + cilostazol) seemed to be more effective in preventing thrombotic complications after stenting than dual anti-platelet agent [##REF##16286167##34##], but latterly a case report showed a patient with subacute stent thrombosis involving two different arteries simultaneously under the use of triple anti-platelet regimen [##UREF##0##31##]. Therefore, the promises of this potential panacea – DES, have been recently attenuated by the specter of late and very late stent thrombosis because of anti-platelet discontinuation [##REF##18180534##35##, ####REF##17998768##36##, ##REF##17174201##37##, ##REF##17296822##38####17296822##38##]. However, the large-scale clinical trials and pool analysis demonstrated that the beneficial effect of DES on reducing the need for new revascularization compared with BMS extends to 4 years without evidence of a worse safety profile including thrombosis [##REF##17562952##39##, ####REF##17662400##40##, ##REF##17296824##41##, ##REF##17296821##42####17296821##42##].</p>", "<p>In our study, the specific lesion was choiced in the nondiabetic patients, and both BMS group and DES group had similar post-procedural outcomes including balloon predilatation (%), stent length (mm), stent diameter (mm), post-dilatation (%), vessel dissection (%) and postprocedural residual stenosis (%), finally we found that the both groups had similar acute and subacute thrombosis (%), late thrombosis (%), in-segment restenosis (%), TLR(%), composite of cardiac death or Re-MI (%) at 6-month follow-up and Re-MI (%), cardiac death (%), TLR (%) as well as MACE (%) at 1- and 3-year follow-up, so were the cardiac death-free and TLR-free cumulative survival rate, however, there was a trend towards a decrease of Re-MI-free cumulative survival rate in the DES group compared with the BMS group at 1- and 3-year follow-up (all P &gt; 0.05), we presumed that the Re-MI might be associated with very late thrombosis. In view of less cost, short-term anti-platelet regimen, less thrombosis incidence, similar restenosis rate and TLR rate in BMS compared with DES, suggesting that BMS may has similar efficacy and superior safety compared with DES at 3-year follow up, thus the nondiabetic patients with a simple de novo lesion in the middle and large vessel seem to have other benefit from BMS instead of DES in real world.</p>", "<title>Limitation</title>", "<p>Firstly, we investigated the non-diabetic patients with specific lesion in real world, the design of this trial was not randomized controlled trial (RCT), thereby the patients in BMS group had lower hypercholesteremia rate (22.0% vs 38.8%, P = 0.006) than DES group in baseline clinical characteristics, thereafter it is necessary for the RCT trials' investigation. Secondly, this is a small population and single medical center of investigation, thus it needs the large-scale trials to validate these findings. Thirdly, this study did not present very late thrombosis data, though it was few of incidence, the very late thrombosis should be investigated in future trials.</p>" ]

[ "<title>Conclusion</title>", "<p>The single BMS has similar efficacy and safety to single DES in non-diabetic patients with a simple de novo lesion in the middle and large vessel at short- and long-term follow-up.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Objective</title>", "<p>This study was aimed to investigate the short- and long-term outcomes of percutaneous coronary intervention (PCI) between single bare metal stent (BMS) and single drug eluting stent (DES) in nondiabetic patients with a simple de novo lesion in the middle and large vessel.</p>", "<title>Methods</title>", "<p>Two hundred and thirty-five consecutive patients with a simple de novo lesion in the middle and large vessel were treated with BMS or DES in our hospital from Apr. 2004 to Dec. 2004.</p>", "<p>The inclusion criteria: a simple de novo lesion in the middle and large vessel, stent diameter ≥ 3.0 mm, stent length ≤ 18 mm, the exclusion criteria: diabetes mellitus, left main trunk disease and left ventricular ejection fraction ≤ 30%. Of them, there were 150 patients in BMS group and 85 patients in DES group, and the rates of lost to follow up were 6.7% and 1.2% respectively.</p>", "<title>Results</title>", "<p>BMS group had lower hypercholesteremia rate (22.0% vs 38.8%) and higher proportion of TIMI grade 0 (12% vs 1.2%) than DES group (all P &lt; 0.05), but both groups had similar stent length (16.16 ± 2.81 mm vs 16.06 ± 2.46 mm) and stent diameter (3.85 ± 3.07 mm vs 3.19 ± 0.24 mm) after procedure, in-segment restenosis rate (0% vs 1.2%) and target lesion revascularization (TLR, 2.0% vs 2.4%) at 6-month follow-up (all P &gt; 0.05). No difference was found in TLR (1.3% vs 1.2%, P = 1.00) and recurrent myocardial infarction (Re-MI) (0% vs 1.2%, P = 0.36), cardiac death (0.7% vs 1.2%, P = 1.00) between 1- and 3-year. So were TLR (6.0% vs 5.9%, P = 0.97), Re-MI (0% vs 2.4%, P = 0.06), cardiac death (2.0% vs 3.5%, P = 0.48) and major adverse cardiac events (MACE, 8.7% vs 10.6%, P = 0.63), cardiac death-free cumulative survival (98.7% vs 97.7%, P = 0.56), TLR-free cumulative survival (94.0% vs 94.1%, P = 0.98) and Re-MI-free cumulative survival (100% vs 97.7%, P = 0.06) at 3-year follow-up.</p>", "<title>Conclusion</title>", "<p>The single BMS has similar efficacy and safety to single DES in nondiabetic patients with a simple de novo lesion in the middle and large vessel at short- and long-term follow-up.</p>" ]

[ "<title>Authors' contributions</title>", "<p>JLC, SBQ, XWQ, MY, JC, YJW, HBL, JiQY, SJY, JJL, JD and RLG carried out the relevant PCI procedures, BX participated in the design of the study, collected and managed the relevant data, YJY conceived of the study, participated in its design and coordination, and revised this manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We are very grateful to the staff in the department of cardiology and catheterization laboratory, Fu Wai Hospital, Chinese Academy of Medical Sciences, who contributed to complete the present study,</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>The Cardiac death-free cumulative survival between BMS group and DES group at 1-year and 3-year followup.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>TLR-free cumulative survival between BMS group and DES group at 1-year and 3-year follow-up.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>The Re-MI-free cumulative survival between BMS group and DES group at 1-year and 3-year follow-up.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Baseline Clinical Characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Characteristics</td><td align=\"center\">BMS group<break/> (N = 150 Pts)</td><td align=\"center\">DES group<break/> (N = 85 Pts)</td><td align=\"center\">P value</td></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"center\">56.66 ± 11.72</td><td align=\"center\">58.26 ± 11.14</td><td align=\"center\">0.307</td></tr><tr><td align=\"left\">Male (%)</td><td align=\"center\">80.7</td><td align=\"center\">78.8</td><td align=\"center\">0.734</td></tr><tr><td align=\"left\">Hypercholesteremia (%)</td><td align=\"center\">22.0</td><td align=\"center\">38.8</td><td align=\"center\">0.006</td></tr><tr><td align=\"left\">Hypertension (%)</td><td align=\"center\">50.7</td><td align=\"center\">60.0</td><td align=\"center\">0.168</td></tr><tr><td align=\"left\">Family history of CAD (%)</td><td align=\"center\">3.3</td><td align=\"center\">3.5</td><td align=\"center\">0.937</td></tr><tr><td align=\"left\">Smoking (%)</td><td align=\"center\">37.3</td><td align=\"center\">38.8</td><td align=\"center\">0.821</td></tr><tr><td align=\"left\">Unstable angina history (%)</td><td align=\"center\">72.0</td><td align=\"center\">75.3</td><td align=\"center\">0.198</td></tr><tr><td align=\"left\">Acute myocardial infarction (%)</td><td align=\"center\">34.7</td><td align=\"center\">23.5</td><td align=\"center\">0.075</td></tr><tr><td align=\"left\">LVEF (%)</td><td align=\"center\">63.24 ± 23.23</td><td align=\"center\">68.43 ± 17.06</td><td align=\"center\">0.108</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Angiographic characteristics and in-hospital outcomes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Characteristics</td><td align=\"center\">BMS group<break/> (N = 150 Pts)</td><td align=\"center\">DES group<break/> (N = 85 Pts)</td><td align=\"center\">P value</td></tr></thead><tbody><tr><td align=\"left\">Calcified lesion (%)</td><td/><td/><td align=\"center\">0.282</td></tr><tr><td align=\"left\"> None</td><td align=\"center\">79.9</td><td align=\"center\">70.6</td><td/></tr><tr><td align=\"left\"> Slightness</td><td align=\"center\">15.4</td><td align=\"center\">18.8</td><td/></tr><tr><td align=\"left\"> Moderation</td><td align=\"center\">3.4</td><td align=\"center\">8.2</td><td/></tr><tr><td align=\"left\"> Severity</td><td align=\"center\">1.3</td><td align=\"center\">2.4</td><td/></tr><tr><td align=\"left\">Lesion length (mm)</td><td align=\"center\">12.60 ± 4.05</td><td align=\"center\">11.65 ± 3.09</td><td align=\"center\">0.062</td></tr><tr><td align=\"left\">Percentage of lumen stenosis (%)</td><td align=\"center\">87.82 ± 8.70</td><td align=\"center\">85.73 ± 8.48</td><td align=\"center\">0.075</td></tr><tr><td align=\"left\">TIMI grade</td><td/><td/><td align=\"center\">0.030</td></tr><tr><td align=\"left\"> 0</td><td align=\"center\">12.0</td><td align=\"center\">1.2</td><td/></tr><tr><td align=\"left\"> 1</td><td align=\"center\">3.3</td><td align=\"center\">2.4</td><td/></tr><tr><td align=\"left\"> 2</td><td align=\"center\">14.7</td><td align=\"center\">17.6</td><td/></tr><tr><td align=\"left\"> 3</td><td align=\"center\">70.0</td><td align=\"center\">78.8</td><td/></tr><tr><td align=\"left\">Balloon predilatation (%)</td><td align=\"center\">63.3</td><td align=\"center\">56.5</td><td align=\"center\">0.300</td></tr><tr><td align=\"left\">Stent length (mm)</td><td align=\"center\">16.16 ± 2.81</td><td align=\"center\">16.06 ± 2.46</td><td align=\"center\">0.782</td></tr><tr><td align=\"left\">Stent diameter (mm)</td><td align=\"center\">3.85 ± 3.07</td><td align=\"center\">3.19 ± 0.24</td><td align=\"center\">0.050</td></tr><tr><td align=\"left\">Post-dilatation (%)</td><td align=\"center\">15.4</td><td align=\"center\">25.6</td><td align=\"center\">0.060</td></tr><tr><td align=\"left\">Vessel dissection (%)</td><td align=\"center\">0</td><td align=\"center\">1.2</td><td align=\"center\">0.363</td></tr><tr><td align=\"left\">Acute thrombosis (%)</td><td align=\"center\">3.3</td><td align=\"center\">0</td><td align=\"center\">0.162</td></tr><tr><td align=\"left\">Postprocedural residual stenosis (%)</td><td align=\"center\">0.21 ± 1.15</td><td align=\"center\">0.29 ± 1.61</td><td align=\"center\">0.656</td></tr><tr><td align=\"left\">In-hospital TLR (%)</td><td align=\"center\">0</td><td align=\"center\">1.2</td><td align=\"center\">0.183</td></tr><tr><td align=\"left\">In-hospital cardiac death (%)</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">......</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>The procedural characteristics and 6-month outcomes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Characteristics</td><td align=\"center\">BMS group<break/> (N = 150 Pts)</td><td align=\"center\">DES group<break/> (N = 85 Pts)</td><td align=\"center\">P value</td></tr></thead><tbody><tr><td align=\"left\">Subacute thrombosis (%)</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">......</td></tr><tr><td align=\"left\">Late thrombosis (%)</td><td align=\"center\">0</td><td align=\"center\">2.4</td><td align=\"center\">0.129</td></tr><tr><td align=\"left\">In-segment restenosis (%)</td><td align=\"center\">0</td><td align=\"center\">1.2</td><td align=\"center\">0.258</td></tr><tr><td align=\"left\">Composite of cardiac death or Re-MI (%)</td><td align=\"center\">0</td><td align=\"center\">1.2</td><td align=\"center\">0.362</td></tr><tr><td align=\"left\">TLR (%)</td><td align=\"center\">2.0</td><td align=\"center\">2.4</td><td align=\"center\">1.000</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Clinical outcomes at 1-year and 3-year follow-up between DES group and BMS group</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Events</td><td align=\"center\" colspan=\"3\">1-year follow-up</td><td align=\"center\" colspan=\"3\">3-year follow-up</td><td align=\"center\" colspan=\"3\">Between 1-year and <break/>3-year follow-up</td></tr><tr><td/><td colspan=\"9\"><hr/></td></tr><tr><td/><td align=\"center\">BMS group<break/> (N = 150 Pts)</td><td align=\"center\">DES group<break/> (N = 85 Pts)</td><td align=\"center\">P</td><td align=\"center\">BMS group<break/> (N = 150 Pts)</td><td align=\"center\">DES group<break/> (N = 85 Pts)</td><td align=\"center\">P</td><td align=\"center\">BMS group<break/> (N = 150 Pts)</td><td align=\"center\">DES group <break/>(N = 85 Pts)</td><td align=\"center\">P</td></tr></thead><tbody><tr><td align=\"left\">Re-MI (%)</td><td align=\"center\">0</td><td align=\"center\">1.2</td><td align=\"center\">0.36</td><td align=\"center\">0</td><td align=\"center\">2.4</td><td align=\"center\">0.06</td><td align=\"center\">0</td><td align=\"center\">1.2</td><td align=\"center\">0.36</td></tr><tr><td align=\"left\">Cardiac death (%)</td><td align=\"center\">1.3</td><td align=\"center\">2.4</td><td align=\"center\">0.62</td><td align=\"center\">2.0</td><td align=\"center\">3.5</td><td align=\"center\">0.48</td><td align=\"center\">0.7</td><td align=\"center\">1.2</td><td align=\"center\">1.00</td></tr><tr><td align=\"left\">TLR (%)</td><td align=\"center\">4.7</td><td align=\"center\">4.7</td><td align=\"center\">1.00</td><td align=\"center\">6.0</td><td align=\"center\">5.9</td><td align=\"center\">0.97</td><td align=\"center\">1.3</td><td align=\"center\">1.2</td><td align=\"center\">1.00</td></tr><tr><td align=\"left\">MACE (%)</td><td align=\"center\">6.0</td><td align=\"center\">7.1</td><td align=\"center\">0.75</td><td align=\"center\">8.7</td><td align=\"center\">10.6</td><td align=\"center\">0.63</td><td align=\"center\">2.7</td><td align=\"center\">3.5</td><td align=\"center\">0.71</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Note: Pts, patients; CAD, coronary artery disease; LVEF, left ventricular ejection fraction.</p></table-wrap-foot>", "<table-wrap-foot><p>Note: Pts, patients; TLR, target lesion revascularization.</p></table-wrap-foot>", "<table-wrap-foot><p>Note: Pts, patients; Re-MI, recurrent myocardial infarction; TLR, target lesion revascularization.</p></table-wrap-foot>", "<table-wrap-foot><p>Note: Pts, patients; Re-MI, recurrent myocardial infarction; TLR, target lesion revascularization; MACE, major adverse cardiac events.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1479-5876-6-42-1\"/>", "<graphic xlink:href=\"1479-5876-6-42-2\"/>", "<graphic xlink:href=\"1479-5876-6-42-3\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Bovine Spongiform Encephalopathy (BSE) was first described in the UK in 1985 and became an epidemic that peaked with 37, 280 cases reported in 1992[##REF##14522859##1##]. BSE and other Transmissible Spongiform Encephalopathy (TSE) diseases are untreatable, uniformly fatal degenerative syndromes of the central nervous system (CNS). A post-mortem examination revealing characteristic deposits of an insoluble host encoded protein, astrocytosis and spongiosis is required for definitive diagnosis. The characteristic protein deposits are formed by the accumulation of misfolded isoforms of a host-encoded protein, PrP^c, or prion protein. The disease associated isoforms are derived from the host protein, PrP^c, by a posttranslational process and are often distinguished by their partial resistance to proteinase K digestion[##REF##6414721##2##]. The term PrP^dis used to denote the presence of abnormal accumulations or isoforms of PrP detected by any method without prejudice as to its biochemical properties, its infectivity, source or host range[##REF##17617870##3##].</p>", "<p>The new human variant of Creutzfeldt-Jakob Disease (vCJD) identified in 1996 is thought to have been caused by dietary exposure to BSE infected products[##REF##15449463##4##]. In contrast to typical cases of classical CJD, vCJD seems to affect predominantly young adults. Risk reduction measures implemented in response to BSE and the emergence of this new disease led to profound changes in the production and trade of agricultural goods. To minimize the risk of disease transmission to consumers specified risk materials (SRM), constituting tissues known to harbour high levels of infectivity such as the brain and spinal cord, have been removed from the food chain. In addition, the testing of risk animals and of all slaughtered animals above the age of thirty months for BSE is a requisite for access to many potential markets for beef products. The rapid tests currently approved for BSE monitoring in slaughtered cattle are all based on the detection of the disease related isoform of the prion protein, PrP^d, in brain tissue and consequently are only suitable for post-mortem diagnosis.</p>", "<p>A reliable ante-mortem test would provide an alternative to the routine culling of herds when a confirmed case of BSE is detected. More importantly, in instances such as assessing the health of breeding stock where post-mortem testing is not an option, there is a demand for ante-mortem tests based on a matrix or body fluid that would permit repeated sampling. The development of such assays, based on the detection of PrP^d, have been complicated by the extremely low amounts of PrP^dpresent in accessible tissues, or in body fluids such as cerebrospinal fluid (CSF), blood and urine [##REF##11423531##5##, ####REF##15310752##6##, ##REF##15031285##7##, ##REF##16824033##8####16824033##8##]. Furthermore, the demonstration that most infectivity is associated with protease sensitive forms of PrP^dalso calls into question the reliability of tests reliant on the association of prion infectivity with the presence of a proteinase K resistant fragment that is measured by Western blotting, enzyme-linked immunosorbent assay, or immunohistochemistry[##REF##14747574##9##].</p>", "<p>The advent of the protein misfolding cyclic amplification assay (PMCA), offered a possible solution to this problem[##REF##11459061##10##]. Indeed, the use of modified PMCA assays using relatively defined components has resulted in the detection of PrP^din the CSF, serum and urine of terminal stage hamsters. However, PMCA based methods require further investigation and validation before they are ready for routine use [##REF##17643109##11##, ####REF##16954698##12##, ##REF##17872544##13##, ##REF##18096717##14##, ##REF##17664944##15####17664944##15##]. Thus, the identification of alternative biomarkers in accessible tissues or body fluids applicable to the development of diagnostic tests remains a relevant approach.</p>", "<p>Urine, due to its ease of collection and comparatively less complex protein profile, is perhaps the ideal matrix for surveillance provided a sufficiently sensitive and specific alternative biomarker for disease can be identified. Previously, it was demonstrated that the presence of protease resistant light chain immunoglobulin in urine may constitute a surrogate marker for prion diseases[##REF##15310752##6##,##REF##15833355##16##]. Building on these results we have used two dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry analyses to demonstrate that the relative abundance of other proteins in the urine of BSE infected cattle and age matched controls change over the course of the disease. These analyses, performed on biological replicates, identified a single protein able to discriminate between control and infected cattle throughout the course of the disease as well as a subset of proteins able to accurately identify the collection date of the samples. The results indicate that biomarkers in urine may be useful in the diagnosis, prognosis and monitoring of disease progression of transmissible spongiform encephalopathy diseases (TSEs).</p>" ]

[ "<title>Methods</title>", "<title>Urine</title>", "<p>Urine was collected from 4 Simmental cross-breed calves that were orally infected with BSE and 4 age matched controls at 8 month intervals throughout the course of the disease. The calves were infected at 4 months of age. All cattle were scored every second month for clinical signs. BSE was confirmed by immunohistochemistry of the obex[##REF##17325380##17##]. Urine samples were frozen immediately after collection and stored at -80°C until processing. This generated 4 infected and 4 control biological replicates at each of the 6 time points. One sample from this set was not obtained resulting in 47 samples in total.</p>", "<p>Urine samples (80–90 mL) were thawed overnight at 4°C. Insoluble particles were removed by a pre-spin, 4°C at 415 g for 5 minutes. The soluble fraction was concentrated with a 5 K MWCO Centricon Plus-70 centrifugal filter unit (Millipore) in a swinging bucket rotor at 4°C and 3400 g for approximately 20 minutes or until volumes reached less than 4 mL. The urine was further concentrated with an Amicon 4 ml 5 K MWCO centrifugal filter unit (Millipore) at 4°C and 7000 g until volumes reached 200 μl.</p>", "<p>The concentrated urine samples were purified using a 2D Clean Up kit (GE Healthcare) according to the manufacturer's recommendations. The resulting protein pellets were resuspended in 100 μL of Rehydration Buffer (0.03 M Tris, 8 M Urea, 2 M Thiourea, 2% Chaps, pH 8.5). Samples were adjusted to pH8.5 with the addition of 1–5 μl of 0.05 M NaOH. The concentration of each sample was determined using a 2D Quant kit (GE Healthcare) according to the manufacturer's recommendations. The pooled internal standard was created by combining 100 μg of each sample.</p>", "<title>2D Gel Electrophoresis</title>", "<p>CyDye™ (GE Healthcare) minimal labeling was performed as per the manufacturer's recommendations (400 pmol: 50 μg) with the Cy2 label reserved for the pooled sample. The control and infected samples were labeled in a randomized manner with either Cy3 or Cy5. An equal volume of 2× Rehydration Buffer (0.03 M Tris, 8 M Urea, 2 M Thiourea, 2% Chaps, pH 8.5, 4 mg/ml Dithiothreitol (DTT), 1% IPG buffer pH 4–7) was added to a mixture comprised of 30 μg each of the labeled Pooled, Control and Infected samples. After a 10 minute incubation on ice approximately 400 μl of 1× Rehydration Buffer (0.03 M Tris, 8 M Urea, 2 M Thiourea, 2% Chaps, pH 8.5, 2 mg/ml DTT, 0.5% IPG buffer pH 4–7) and 5 μl of 1% Bromophenol blue (10 mM TrisCl pH 8.5) were added to bring the volume up to a total of 450 μl. The labelled samples were loaded onto a reswelling tray and overlaid with a 24 cm Immobiline DryStrip pH 4–7 (GE Healthcare) and DryStrip Cover Fluid and allowed to rehydrate overnight at room temperature. The strip was transferred to a Manifold filled with 108 mL of DryStrip Cover Fluid and placed on an Ettan IPGphor3 focusing apparatus that was programmed as follows: Step 30 V 8 hrs, Step 500 V 1 hr, Step 1000 V 1 hr, Grad 10000 V 3 hrs and Step 10000 V 3 hrs. A final focusing program: Grad 10000 V 0:20 hr and Step 10000 V until the volt hours reached a total of 55000 was added as required.</p>", "<p>Completed isoelectric focusing (IEF) runs were stored at -80°C until the second dimension was run. IEF strips were prepared for second dimension gels by incubating in two different Equilibration Buffer solutions (50 mM Tris-Cl pH8.8, 6 M Urea, 30% Glycerol, 2% SDS, 0.2% Bromophenol Blue, supplemented with either 65 mM DTT – 1^stincubation or 135 mM Iodoacetamide – 2^ndincubation) for 15 minutes each with gentle rocking.</p>", "<p>The prepared IEF strips were placed on 15–20% gradient gels between low fluorescent glass plates (NextGen Sciences). After sealing in place with a 1% agarose solution, the gels were placed in the Ettan DALT6 unit (GE Healthcare) and run at 2 W overnight and then at 100 W until a total of 3100 Vhr was reached.</p>", "<title>Data Acquisition and Analysis</title>", "<p>Two randomly selected samples labeled with Cy5 and Cy3 were co-resolved with a Cy2 labeled pooled internal standard on each of 24 gels. Gels were scanned within 24 hours of being run on a Molecular Dynamics Typhoon 9400. Gel images were cropped using Molecular Dynamics Image Quant 5.2 software.</p>", "<p>Upon visual inspection of the 24 gels, proteins on three gels were observed to not be well resolved. These three gels were immediately rerun using the same Cy2 labelled standard to obtain gel images suitable for analysis. Acquired gel images were first analyzed in the DeCyder™ Differential In-gel Analysis (DIA) module of the GE HealthCare DeCyder™ 2D Software version 6.5. The DIA generated identical spot feature detection patterns on all images derived from the same gel. This ensured that the internal standard and the sample spot features had identical spot boundaries. Quantification of spot features was achieved by normalizing spot feature volumes against the internal standard.</p>", "<p>The DIA files were imported into the Biological Variation Analysis (BVA) module to match spot feature migration patterns and normalize abundance values using the unique signal of each spot feature from the pooled internal standard. The standardized abundance was derived from the normalized spot volume, standardized against the intra gel standard. To obtain a normal distribution around zero the spot feature standardized log abundance values were used for inter-gel spot comparisons.</p>", "<p>Multivariate analysis was performed in the DeCyder™ Extended Data Analysis (EDA) module version 1.0. Marker selection and classifier creation were performed using partial least squares for the searching and ranking of spot features and K-nearest neighbor (KNN) to evaluate the spot feature set found.</p>", "<title>Protein Digest</title>", "<p>Spot features of interest were manually excised using a Gilson P1000 Pipetman from SYPRO Ruby stained preparative gels and stored in 1% acetic acid. The ART pipet tips were cut with a razor blade to increase the pore size. The gel slices were washed a total of five times; first with sterile water, secondly with 25 mM ammonium bicarbonate and finally three consecutive washes with 25 mM ammonium bicarbonate/50% acetonitrile solution with the last wash being an overnight incubation at 10°C. Gel slices were dehydrated with 100% acetonitrile before adding trypsin (Trypsin Gold, Promega) at 20 μg/ml (in 40 mM ammonium biocarbonate/10% acetonitrile solution) and incubated at 37°C overnight. Tryptic peptides were extracted from the gel slices by washing with 0.1% formic acid and then 0.1% formic acid/50% acetonitrile solutions. The tryptic peptide extracts were vacuum-dried and reconstituted with 10 μl of 5% acetonitrile and 0.1% formic acid.</p>", "<title>LC/MS/MS</title>", "<p>Nanoflow LC of tryptic peptide samples was performed with an Agilent 1100 nanoflow LC system equipped with a C₁₈pre-column (Zorbax 300SB-C18, 5 μm, 5 mm × 0.3 mm, Agilent) and a C₁₈analytical column (Zorbax 300SB-C18, 3.5 μm, 15 cm × 75 μm, Agilent). The aqueous mobile phase (solution A) contained 5% acetonitrile and 0.1% formic acid, and the organic mobile phase (solution B) contained 95% acetonitrile and 0.1% formic acid. Samples (5-μl injected) were loaded and washed on the pre-column for 5 minutes with solution A at 50 μl/min. Peptides were then eluted off the pre-column and through the analytical column with a 50 minute profile at 300 nl/min: 1 to 30% solution B over 30 min, 40% to 95% B over 5 minutes, 95% B over 5 minutes, and re-equilibrated for 10 minutes at initial conditions. Peptides were eluted directly into a QStar XL via a nanospray ion source (Applied Biosystems). The ion source was equipped with a 50-μm inner-diameter, fuse-silica needle with a 15-μm tip (PicoTip Emitter, New Objective). Data dependant acquisition was performed with a 10 second cycle: 1-second interval for acquiring intact peptide signal (MS), and three 3-second intervals for collision induced dissociation of the 3 most intense peptide signals in the initial 1-second interval (MS/MS). The MS <italic>m/z </italic>range was 350 to 1500, and the MS/MS <italic>m/z </italic>range was 70 to 2000. Collision energy was automatically determined by the data acquisition software (Analyst QS 1.1). MS/MS data were acquired for the entire LC run.</p>", "<title>Data analysis</title>", "<p>Mascot (version 2.2, Matrix Science) search engine was used to search the NCBI database with the MS/MS data. The search parameters were as follows: taxonomy was unrestricted, protein molecular weight was unrestricted, fixed modification was Carbamidomethyl (C), variable modification was Oxidation (M), peptide and fragment mass tolerance was ± 0.3 Da, and up to one missed cleavage was allowed. Individual ion scores &gt; 54 indicate identity or extensive homology (p &lt; 0.05).</p>" ]

[ "<title>Results</title>", "<title>Gel image acquisition</title>", "<p>Urine was collected from 4 Simmental cattle orally infected with BSE and 4 age matched controls at 8 month intervals over the first 40 months of the disease. This generated 4 infected and 4 control biological replicates at each of the 6 time points. An internal gel standard was created by pooling equivalent amounts of protein from each sample. In total 27 gels, each comprised of the internal standard and two biological samples, were run to obtain gel images suitable for analysis. Ultimately, 46 gel images representing 46 biological samples and 24 gel images of the internal standard were used for analyses (Table ##TAB##0##1##).</p>", "<p>The acquired gel images were analyzed using the DeCyder™ DIA and BVA software modules. Manual landmarking of 12 spot features across 24 gel images of the internal standard was performed in order to improve the accuracy of the gel-to-gel matching process. This resulted in the detection, quantification, and matching of 1329 master spot features across the 24 gels, all containing the same internal standard (Figure ##FIG##0##1##).</p>", "<title>PCA analyses</title>", "<p>Multivariate analyses of protein expression data derived from the BVA were performed using the DeCyder™ Extended Data Analysis Software (EDA). The gel images were first grouped such that the 6 samples from each individual animal formed a group. This resulted in 8 groups each representing one of 8 biological replicates. The data were filtered so that only the 36 spot features exhibiting statistically significant (ANOVA p &lt; 0.01) changes in abundance and present on all 46 gel images were considered in the following analyses.</p>", "<p>Principle component analysis (PCA) on this filtered data set was performed to identify the relative contributions of the inherent differences between individuals and disease state on the variance exhibited by the 8 biological replicates. The PCA analysis demonstrated that the cows generally segregated into infected and control groups indicating that the disease status of the animals was the primary factor affecting the differential abundance of urinary proteins (Figure ##FIG##1##2##). The exception was cow #54. At no time point did this animal cluster with the other infected animals and it further diverged from all other animals as the disease progressed.</p>", "<p>The reason for the atypical pattern demonstrated by this animal is not known, but it is interesting to note that it had an atypical phenotype as well. Cow #54 developed clinical signs, as determined by regular scoring for clinical signs (20 minutes/animal), between 40–46 months post infection (mpi), but then phenotypically recovered before reaching the terminal stage of the disease at 56 mpi. In contrast, cows #38 and #53 reached the terminal stage of the disease at 44 mpi and cow #40 at 48 mpi. The behaviour of cow #54 was atypical, not only with respect to the other three infected cattle considered in this study, but from the other 10 infected cows in the herd that were allowed to reach the terminal stage of the disease. For the purposes of this experiment all the data representing this animal were excluded from subsequent analyses. BSE infection was confirmed in all four cases by immunohistochemical analyses of the obex.</p>", "<p>The 40 remaining gel images were then grouped according to disease state and months post infection. Control and infected cows at each time point formed a group. This resulted in 10 groups each representing either the 3 remaining infected cows or the 4 control cows at a particular point in the experiment. Samples collected from these 7 cows prior to the start of the experiment formed an 11th group (normal). The data were again filtered revealing 56 spot features that exhibited statistically significant (ANOVA p &lt; 0.01) changes in abundance and were present on all 40 gel images for consideration in the following analyses.</p>", "<p>PCA analysis on this filtered data set was performed to identify the relative contributions of time and disease state on the variance observed (Figure ##FIG##2##3##). The cows again segregated into infected and control groups further indicating that the disease status of the animals was the primary cause of the differential abundance in urinary proteins observed. Nonetheless, within the infected group it was also observed that the individual time points clustered together and generally moved down and to the right as disease progressed. A somewhat similar, but less pronounced pattern was observed in the control samples. This indicates that time did factor into the differential abundance of urinary proteins observed. That time played a role in the urinary protein profile was reinforced by the observation that the animals at 0 mpi formed a distinct group (normal).</p>", "<p>PCA of the 56 spot features that exhibited statistically significant (ANOVA p &lt; 0.01) changes in abundance and were present on all 40 gels revealed 3 outliers representing either mismatched features or strongly differentially abundant features (Figure ##FIG##3##4A##). Visual inspections of all potential outliers were made in the corresponding BVA file containing the gel images. The 3 spot features clearly observed in the infected image were not visible in the control image of the gel (Figure ##FIG##3##4B##). Visualization of the shape of the peak representing spot feature 405 and those in the surrounding area demonstrated that the matches were legitimate (Figure ##FIG##3##4C##). The increase in abundance of 405 ranged from 17 to 77 fold over the course of the experiment. Graphical representation of the standardized log abundance obtained for the spot feature 405 demonstrated strong differential abundance of the spot feature throughout the experiment. Note the segregation of the control and infected biological replicates at each time point (Figure ##FIG##3##4D##).</p>", "<title>Classifier creation</title>", "<p>In order to determine whether the differences suggested by the PCA analyses were sufficient to discriminate control from infected animals the marker selection and classifier creation functions of the EDA module were used. Initially this was performed on the pooled data obtained from all control, infected and normal samples. The data, as before, were filtered so that only spot features exhibiting statistically significant (ANOVA p &lt; 0.01) changes in abundance and present on all 40 gel images were considered.</p>", "<p>The partial least squares method was used for the searching and ranking of spot features and K-nearest neighbor (KNN) was used to evaluate the set of biomarkers found. The use of 16 biomarkers and KNN classification demonstrated that the training data set could be classified with 83.3% ± 18.3 accuracy (Table ##TAB##1##2##). Removal of the confounding normal samples led to the identification of a single spot feature (405) that could discriminate between the remaining control and infected sample sets with 100% accuracy.</p>", "<p>In order to evaluate the information concerning disease progression contained in the urine samples the 14 gel images of the infected samples were considered separately. The data were filtered so that only the 25 spot features exhibiting statistically significant (ANOVA p &lt; 0.01) changes in abundance and present on all 14 gel images were considered. The classifier created using the 16 spot features identified by marker selection was able to classify the time post infection that the infected samples were collected with 85% ± 13.2 accuracy. The two misclassified samples were placed into the immediately proceeding time point (Table ##TAB##2##3##).</p>", "<p>In order to parse out those changes due to disease progression from those associated with aging a similar analysis was performed on the control samples. The classifier created using 16 of the spot features identified by marker selection was able to classify with 85% ± 19.1 accuracy the time post infection that the control samples were collected (Table ##TAB##3##4##). Two of the three misclassified samples were placed into the immediately proceeding time point.</p>", "<p>The 16 spot features used by the 3 classifiers are provided in Table ##TAB##4##5##. The rank assigned to the spot features denotes the relative contribution of each protein to the classification. The standardized abundance ratio of the top three ranked proteins in the disease progression classifier were plotted with respect to time post infection (Figure ##FIG##4##5##). The steady increase or decrease in abundance observed over the course of the experiment illustrated the utility of the relative abundance of the spot features in classifying the urine samples with respect to date post infection. Three of the spot features utilized to predict disease progression (597, 1022, 1041) were also used in disease class prediction indicating that these markers are disease specific. Another disease progression spot feature (710) also appeared among the control progression markers indicating that changes in the abundance of this spot feature were age related.</p>", "<title>LC/MS/MS analyses</title>", "<p>The 16 biomarkers making up the class prediction classifier (Figure ##FIG##0##1B##), designed to discriminate between control, infected and normal samples, were excised from a preparative gel and subjected to protein identification using mass spectrometry and database interrogation as described in Materials and Methods. MS analysis identified 5 unique proteins, not including redundancies likely due to post-translational modifications or proteolysis, and enabled proteins to be assigned to 13 of the 16 spot features. A summary of the results of this analysis are shown in Table ##TAB##5##6##. See Additional File ##SUPPL##0##1## for additional protein statistics.</p>", "<p>The 5 different proteins representing the 13 spot features were: clusterin, Ig Gamma-2 chain C region, similar to GCAP-11/uroguanylin, cystatin E/M, and cathelicidin1. Some of the redundancies appeared to be due to post-translational modifications that created charge-related isoforms that had different iso-electric points, but indistinguishable molecular masses. For example, 2 spot features identified as clusterin (393, 405), appeared to meet this criteria (Figure ##FIG##3##4B##). It is also interesting to note that the differential abundance of one of the isoforms is much more robust than the other (Figure ##FIG##3##4A##).</p>" ]

[ "<title>Discussion</title>", "<p>Recent advances in 2-dimensional gel electrophoresis technologies, namely the introduction of fluorescent dyes, which allow multiple samples to be co-separated and visualized on one 2-D gel, have increased the utility of this methodology for the discovery of robust protein biomarkers for disease [##REF##12548632##18##, ####REF##17185779##19##, ##REF##17366473##20####17366473##20##]. For example, power analysis for 2D-DIGE has demonstrated statistical power of &gt;0.8 for detecting 2-fold changes at p ≤ 0.01 with 4 biological replicates[##REF##16035117##21##]. In our experiment urine samples representing 4 control and 4 age matched infected cattle were run with an internal standard. The internal standard, created by pooling aliquots of all biological samples in the experiment, was run on all gels within the experiment thereby creating an intrinsic link across all gels. Normalization of the internal standard across gels allowed the ratio of relative abundance of the same protein to be compared directly, separating gel-to-gel variation from biological variation. Differences in protein abundance were then determined by comparing the ratio obtained from one fluorescent labelled sample directly with another.</p>", "<p>Changes in the amount of a given soluble protein in urine can result from a change in its concentration in the blood plasma, a change in the function of the glomerular filter, an alteration in the proximal tubule scavenging system or a change in local production and excretion[##REF##16837576##22##]. No proteinuria indicating a change in the glomerular filter was observed in response to BSE infection (Additional file ##SUPPL##1##2##). In addition, no significant difference (p &lt; 0.01) in the standardized log of abundance for cystatin was observed at any time point when compared to the corresponding control (Additional file ##SUPPL##2##3##). Cystatin is a low molecular weight cysteine proteinase inhibitor that is freely filtered by the renal glomeruli and reabsorbed in the proximal tubules. Consequently cystatin serves as an indicator of the health of the proximal tubule scavenging system[##REF##12135813##23##,##REF##15603510##24##]. The absence of change in cystatin abundance indicated that the proximal tubule scavenging system was unaffected by BSE infection. Together these results suggest that the differential abundances observed in response to BSE infection were likely due to changes in the protein concentration in the blood plasma or a disease associated alteration in local production.</p>", "<p>One of the identified classifier proteins that exhibited increased abundance in response to infection was immunoglobulin Gamma-2 chain C region. Increased immunoglobulin has previously been observed in the urine of scrapie infected hamsters and in one report it was speculated that this was the result of a nephritic syndrome [##REF##11423531##5##,##REF##15310752##6##,##REF##15833355##16##]. In contrast, the data presented suggests that the increased abundance of immunoglobulin in urine associated with BSE was probably due to a change in immunoglobulin concentration in the blood plasma. Nonetheless, the detection of differential abundance of another immunoglobulin protein in urine by an unbiased screen lends support to the suggestion that immunoglobulin light chain may constitute a surrogate marker for TSE diseases[##REF##15310752##6##,##REF##15833355##16##].</p>", "<p>In addition to immunoglobulin Gamma-2 chain C region and cystatin, the 3 other identified classifier proteins were well known urinary proteins. One was the antimicrobial peptide cathelicidin that is produced in the kidney by the epithelial cells that line the urinary tract. When exposed to bacteria the levels of cathelcidin mRNA are known to rapidly increase, however, even in the absence of microbes the epithelial surface of the urinary tract are continuously bathed with cathelicidin[##REF##16760999##25##,##REF##16751768##26##]. A second protein was the natriuretic peptide uroguanylin that is produced in the small intestine and kidney. In response to salt loading no increase in circulating uroguanylin is observed indicating that the natriuretic effect of uroguanylin is in part mediated by increased renal production that inhibits tubular resorption of ions from the glomerular filtrate[##REF##16819406##27##]. These characteristics suggested that the decreased abundance of both cathelicidin, observed after 24 mpi, and uroguanylin throughout the experiment were probably the result of decreased renal production and excretion. The precise cause of the decreased production and the possible effects of the altered abundance on prion pathobiology are not known.</p>", "<p>The third protein, identified as clusterin, was able to distinguish between infected animals and age matched controls with 100% accuracy throughout the experiment. Clusterin is a multifunctional glycoprotein with nearly ubiquitous tissue distribution[##REF##11906815##28##]. Increased abundance of clusterin in association with TSE diseases has been reported previously and has included increased expression in astrocytes as well as a significant accumulation in cerebrospinal fluid and blood plasma[##REF##11907798##29##]. Thus, increased amounts of circulating clusterin may have caused the increased clusterin abundance observed in the urine of the BSE infected animals. Despite the power of clusterin as a biomarker of BSE in this experiment, the increased clusterin abundance in CSF observed in models of other neurodegenerative diseases, such as Alzheimer's disease, and in response to a variety of renal insults raises doubts as to the specificity of clusterin per se as a biomarker of BSE in cattle [##REF##18288611##30##, ####REF##17455085##31##, ##REF##12427144##32##, ##REF##12457227##33##, ##REF##17929958##34####17929958##34##]. However, the specificity of the particular isoform of clusterin observed to best discriminate between BSE infected and control cattle remains to be seen.</p>", "<p>EDA analyses also demonstrated that the differential abundance of different subsets of proteins provided accurate measures of disease progression and aging. This was an unexpected result, but the ability to follow disease progression by monitoring the differential abundance of a subset of proteins has potential applications as a prognostic indicator or in the assessment of the therapeutic benefit of potential treatments. Furthermore, while markers of disease progression must be sensitive to changes in disease state and present in easily accessible tissues that permit repeated sampling, they do not require the same high disease specificity as diagnostic markers. The ultimate utility of these markers of disease progression will be determined by their identification and validation as well as their applicability to clinically relevant disease models. Significantly, the markers of disease progression demonstrated very little overlap with those identified as able to track age. This indicates that they were a measure of disease specific progression and that their identification may also provide insight into the pathology of these diseases.</p>", "<p>The results demonstrate that in principle it is possible to identify biomarkers of TSE disease by analyzing changes in the urine protein profile provoked by the disease. Extending the present study to larger numbers of cattle and to those of other strains will test the value of the biomarkers identified. Even more promising markers may have been missed due to the bias of 2D-DIGE to the identification of abundant proteins. This shortfall will be addressed in future studies by utilizing a variety of pre-fractionation methods.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The bovine spongiform encephalopathy (BSE) epidemic and the emergence of a new human variant of Creutzfeldt-Jakob Disease (vCJD) have led to profound changes in the production and trade of agricultural goods. The rapid tests currently approved for BSE monitoring in slaughtered cattle are all based on the detection of the disease related isoform of the prion protein, PrP^d, in brain tissue and consequently are only suitable for post-mortem diagnosis. Objectives: In instances such as assessing the health of breeding stock for export purposes where post-mortem testing is not an option, there is a demand for an ante-mortem test based on a matrix or body fluid that would permit easy access and repeated sampling. Urine and urine based analyses would meet these requirements.</p>", "<title>Results</title>", "<p>Two dimensional differential gel eletrophoresis (2D-DIGE) and mass spectrometry analyses were used to identify proteins exhibiting differential abundance in the urine of BSE infected cattle and age matched controls over the course of the disease. Multivariate analyses of protein expression data identified a single protein able to discriminate, with 100% accuracy, control from infected samples. In addition, a subset of proteins were able to predict with 85% ± 13.2 accuracy the time post infection that the samples were collected.</p>", "<title>Conclusion</title>", "<p>These results suggest that in principle it is possible to identify biomarkers in urine useful in the diagnosis, prognosis and monitoring of disease progression of transmissible spongiform encephalopathy diseases (TSEs).</p>" ]

[ "<title>Authors' contributions</title>", "<p>JDK, MG, SC, CG have made substantial contributions to conception and design of the experiment. SLRS, LL, MP, JL, UZ, MS performed the acquisition of data. JDK carried out the analysis and interpretation of data. JDK, SLRS, MP, LL, SC have been involved in drafting the manuscript or revising it critically for important intellectual content. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We would like to thank Michael Carpenter and Julie Boutillier for their advice and many helpful discussions. We would also like to thank Garrett Westmacott and Keding Cheng of the Proteomics Core Facility, Public Health Agency of Canada, for the Mass Spectrometry Analyses. This work was funded by the Alberta Prion Research Institute and the Public Health Agency of Canada.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Representative Cy2-labelled internal standard proteome gel image illustrating proteins resolved in the pH4-7 range</bold>. The gel image as loaded into the DIA module prior to spot detection (A). In panel B the 1329 spot features, including spots at the edges of the gel that were outside the pH range of the 1^stdimension separation, are each denoted by a green dot. The position of the 16 spot features used in the class prediction classifier have been marked with yellow and the associated master gel spot feature number assigned to the same spot features on all gels by the DeCyder BVA module are shown.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Principle component analysis of the 8 biological replicates</bold>. The samples obtained from individual infected and control cows clustered together indicating that disease is the factor that most influences the differential abundance observed in the urine samples. The time of the 6 sample collections from cow #54 are given to illustrate that the urine proteome of this animal diverged further from all the other animals as the disease progressed. This analysis was based on the 36 spot features exhibiting statistically significant (ANOVA p &lt; 0.01) changes in abundance and present on all 46 gel images. (PC1 = 36.3, PC2 = 15.2).</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Principle component analysis of different disease states followed throughout the disease progression</bold>. Ellipses have been drawn to illustrate the clustering of the 3 groups (BSE infected, control and normal). Within the infected group it can also be seen that the individual time points cluster together. A somewhat similar but less pronounced pattern is observed in the control samples. This analysis is based on the 56 spot features exhibiting statistically significant (ANOVA p &lt; 0.01) changes in abundance and present on all 40 gel images. (PC1 = 38.6, PC2 = 23.0).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Differentially abundant spot features</bold>. Principle component analysis of 56 spot features that exhibited statistically significant (ANOVA p &lt; 0.01) changes in abundance and were present on all 40 gels (A). The red rectangle on the gel image shows the region on the gels where the potential outliers were situated. Two magnified views of this region showing infected and control images (B). 3D images of spot feature 405 showing the 23.68 fold increase in abundance observed at 8 mpi (C). Graphical representation of the standardized log abundance data obtained for spot feature 405 (D).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Proteins that exhibited a steady increase or decrease in abundance throughout disease progression</bold>. The average standardized abundance ratios of the top three ranked proteins used in the disease progression classier (437, 1041, 1022) are shown. The consistent increase or decrease in abundance over the course of the experiment illustrates the utility of the relative abundance of these spot features in classifying the urine samples with respect to date post infection.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Sample loading and labelling matrix.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>group</bold></td><td align=\"center\"><bold>cow</bold></td><td align=\"center\"><bold>gel no.</bold></td><td align=\"center\"><bold>dye</bold></td><td align=\"center\"><bold>mpi</bold></td><td align=\"center\"><bold>group</bold></td><td align=\"center\"><bold>cow</bold></td><td align=\"center\"><bold>gel no.</bold></td><td align=\"center\"><bold>dye</bold></td><td align=\"center\"><bold>mpi</bold></td></tr></thead><tbody><tr><td align=\"left\">infected</td><td align=\"center\">38</td><td align=\"center\">na</td><td align=\"center\">na</td><td align=\"center\">0</td><td align=\"center\">control</td><td align=\"center\">67</td><td align=\"center\">23</td><td align=\"center\">Cy3</td><td align=\"center\">0</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">40</td><td align=\"center\">1</td><td align=\"center\">Cy5</td><td align=\"center\">0</td><td align=\"center\">control</td><td align=\"center\">69</td><td align=\"center\">22</td><td align=\"center\">Cy5</td><td align=\"center\">0</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">53</td><td align=\"center\">15</td><td align=\"center\">Cy3</td><td align=\"center\">0</td><td align=\"center\">control</td><td align=\"center\">72</td><td align=\"center\">11</td><td align=\"center\">Cy5</td><td align=\"center\">0</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">54</td><td align=\"center\">17</td><td align=\"center\">Cy5</td><td align=\"center\">0</td><td align=\"center\">control</td><td align=\"center\">73</td><td align=\"center\">13</td><td align=\"center\">Cy3</td><td align=\"center\">0</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"left\">infected</td><td align=\"center\">38</td><td align=\"center\">24</td><td align=\"center\">Cy3</td><td align=\"center\">8</td><td align=\"center\">control</td><td align=\"center\">67</td><td align=\"center\">1</td><td align=\"center\">Cy3</td><td align=\"center\">8</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">40</td><td align=\"center\">8</td><td align=\"center\">Cy3</td><td align=\"center\">8</td><td align=\"center\">control</td><td align=\"center\">69</td><td align=\"center\">3</td><td align=\"center\">Cy5</td><td align=\"center\">8</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">53</td><td align=\"center\">13</td><td align=\"center\">Cy5</td><td align=\"center\">8</td><td align=\"center\">control</td><td align=\"center\">72</td><td align=\"center\">23</td><td align=\"center\">Cy5</td><td align=\"center\">8</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">54</td><td align=\"center\">8</td><td align=\"center\">Cy5</td><td align=\"center\">8</td><td align=\"center\">control</td><td align=\"center\">73</td><td align=\"center\">9</td><td align=\"center\">Cy3</td><td align=\"center\">8</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"left\">infected</td><td align=\"center\">38</td><td align=\"center\">19</td><td align=\"center\">Cy5</td><td align=\"center\">16</td><td align=\"center\">control</td><td align=\"center\">67</td><td align=\"center\">24</td><td align=\"center\">Cy5</td><td align=\"center\">16</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">40</td><td align=\"center\">27</td><td align=\"center\">Cy3</td><td align=\"center\">16</td><td align=\"center\">control</td><td align=\"center\">69</td><td align=\"center\">14</td><td align=\"center\">Cy3</td><td align=\"center\">16</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">53</td><td align=\"center\">25</td><td align=\"center\">Cy3</td><td align=\"center\">16</td><td align=\"center\">control</td><td align=\"center\">72</td><td align=\"center\">16</td><td align=\"center\">Cy5</td><td align=\"center\">16</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">54</td><td align=\"center\">18</td><td align=\"center\">Cy3</td><td align=\"center\">16</td><td align=\"center\">control</td><td align=\"center\">73</td><td align=\"center\">6</td><td align=\"center\">Cy5</td><td align=\"center\">16</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"left\">infected</td><td align=\"center\">38</td><td align=\"center\">19</td><td align=\"center\">Cy3</td><td align=\"center\">24</td><td align=\"center\">control</td><td align=\"center\">67</td><td align=\"center\">15</td><td align=\"center\">Cy5</td><td align=\"center\">24</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">40</td><td align=\"center\">21</td><td align=\"center\">Cy3</td><td align=\"center\">24</td><td align=\"center\">control</td><td align=\"center\">69</td><td align=\"center\">17</td><td align=\"center\">Cy3</td><td align=\"center\">24</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">53</td><td align=\"center\">na</td><td align=\"center\">na</td><td align=\"center\">24</td><td align=\"center\">control</td><td align=\"center\">72</td><td align=\"center\">3</td><td align=\"center\">Cy3</td><td align=\"center\">24</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">54</td><td align=\"center\">26</td><td align=\"center\">Cy5</td><td align=\"center\">24</td><td align=\"center\">control</td><td align=\"center\">73</td><td align=\"center\">21</td><td align=\"center\">Cy5</td><td align=\"center\">24</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"left\">infected</td><td align=\"center\">38</td><td align=\"center\">10</td><td align=\"center\">Cy5</td><td align=\"center\">32</td><td align=\"center\">control</td><td align=\"center\">67</td><td align=\"center\">14</td><td align=\"center\">Cy5</td><td align=\"center\">32</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">40</td><td align=\"center\">12</td><td align=\"center\">Cy3</td><td align=\"center\">32</td><td align=\"center\">control</td><td align=\"center\">69</td><td align=\"center\">9</td><td align=\"center\">Cy5</td><td align=\"center\">32</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">53</td><td align=\"center\">25</td><td align=\"center\">Cy5</td><td align=\"center\">32</td><td align=\"center\">control</td><td align=\"center\">72</td><td align=\"center\">2</td><td align=\"center\">Cy5</td><td align=\"center\">32</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">54</td><td align=\"center\">6</td><td align=\"center\">Cy3</td><td align=\"center\">32</td><td align=\"center\">control</td><td align=\"center\">73</td><td align=\"center\">16</td><td align=\"center\">Cy3</td><td align=\"center\">32</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"left\">infected</td><td align=\"center\">38</td><td align=\"center\">10</td><td align=\"center\">Cy3</td><td align=\"center\">40</td><td align=\"center\">control</td><td align=\"center\">67</td><td align=\"center\">20</td><td align=\"center\">Cy3</td><td align=\"center\">40</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">40</td><td align=\"center\">11</td><td align=\"center\">Cy3</td><td align=\"center\">40</td><td align=\"center\">control</td><td align=\"center\">69</td><td align=\"center\">2</td><td align=\"center\">Cy3</td><td align=\"center\">40</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">53</td><td align=\"center\">18</td><td align=\"center\">Cy5</td><td align=\"center\">40</td><td align=\"center\">control</td><td align=\"center\">72</td><td align=\"center\">26</td><td align=\"center\">Cy3</td><td align=\"center\">40</td></tr><tr><td align=\"left\">infected</td><td align=\"center\">54</td><td align=\"center\">12</td><td align=\"center\">Cy5</td><td align=\"center\">40</td><td align=\"center\">control</td><td align=\"center\">73</td><td align=\"center\">27</td><td align=\"center\">Cy5</td><td align=\"center\">40</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Classification Matrix</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">83.33% ± 18.3</td><td align=\"center\" colspan=\"3\">Class Prediction</td></tr></thead><tbody><tr><td/><td align=\"right\">control</td><td align=\"right\">infected</td><td align=\"right\">normal</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">control</td><td align=\"right\"><bold>20</bold></td><td align=\"right\">0</td><td align=\"right\">3</td></tr><tr><td align=\"left\">infected</td><td align=\"right\">0</td><td align=\"right\"><bold>14</bold></td><td align=\"right\">0</td></tr><tr><td align=\"left\">normal</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>3</bold></td></tr><tr><td align=\"left\">no class</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">error</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">3</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Disease Progression Matrix</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">85% ± 13.2</td><td align=\"center\" colspan=\"5\">Infected Progression</td></tr></thead><tbody><tr><td/><td align=\"right\">08 mpi</td><td align=\"right\">16 mpi</td><td align=\"right\">24 mpi</td><td align=\"right\">32 mpi</td><td align=\"right\">40 mpi</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\">08 mpi</td><td align=\"right\"><bold>3</bold></td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">16 mpi</td><td align=\"right\">0</td><td align=\"right\"><bold>3</bold></td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">24 mpi</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>2</bold></td><td align=\"right\">2</td><td align=\"right\">0</td></tr><tr><td align=\"left\">32 mpi</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>1</bold></td><td align=\"right\">0</td></tr><tr><td align=\"left\">40 mpi</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>3</bold></td></tr><tr><td align=\"left\">no class</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">error</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">2</td><td align=\"right\">0</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Aging Matrix</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">85% ± 19.1</td><td align=\"center\" colspan=\"5\">Control Progression</td></tr></thead><tbody><tr><td/><td align=\"right\">08 mpi</td><td align=\"right\">16 mpi</td><td align=\"right\">24 mpi</td><td align=\"right\">32 mpi</td><td align=\"right\">40 mpi</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\">08 mpi</td><td align=\"right\"><bold>4</bold></td><td align=\"right\">1</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">16 mpi</td><td align=\"right\">0</td><td align=\"right\"><bold>3</bold></td><td align=\"right\">1</td><td align=\"right\">1</td><td align=\"right\">0</td></tr><tr><td align=\"left\">24 mpi</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>3</bold></td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">32 mpi</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>3</bold></td><td align=\"right\">0</td></tr><tr><td align=\"left\">40 mpi</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\"><bold>4</bold></td></tr><tr><td align=\"left\">no class</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td><td align=\"right\">0</td></tr><tr><td align=\"left\">error</td><td align=\"right\">0</td><td align=\"right\">1</td><td align=\"right\">1</td><td align=\"right\">1</td><td align=\"right\">0</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Biomarker sets used to create classifiers.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"2\">Control Progression</td><td align=\"center\" colspan=\"2\">Disease Progression</td><td align=\"center\" colspan=\"2\">Class Prediction</td></tr></thead><tbody><tr><td/><td align=\"right\">Spot #</td><td align=\"right\">Rank</td><td align=\"right\">Spot #</td><td align=\"right\">Rank</td><td align=\"right\">Spot #</td><td align=\"right\">Rank</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"right\">1</td><td align=\"right\">161</td><td align=\"right\">10</td><td align=\"right\">125</td><td align=\"right\">9</td><td align=\"right\"><bold>387</bold></td><td align=\"right\">2</td></tr><tr><td align=\"right\">2</td><td align=\"right\">168</td><td align=\"right\">8</td><td align=\"right\">127</td><td align=\"right\">6</td><td align=\"right\">393</td><td align=\"right\">3</td></tr><tr><td align=\"right\">3</td><td align=\"right\">395</td><td align=\"right\">2</td><td align=\"right\">239</td><td align=\"right\">4</td><td align=\"right\">405</td><td align=\"right\">1</td></tr><tr><td align=\"right\">4</td><td align=\"right\">473</td><td align=\"right\">6</td><td align=\"right\">297</td><td align=\"right\">10</td><td align=\"right\"><italic>597</italic></td><td align=\"right\">11</td></tr><tr><td align=\"right\">5</td><td align=\"right\">482</td><td align=\"right\">6</td><td align=\"right\">437</td><td align=\"right\">1</td><td align=\"right\">749</td><td align=\"right\">12</td></tr><tr><td align=\"right\">6</td><td align=\"right\">603</td><td align=\"right\">3</td><td align=\"right\"><italic>597</italic></td><td align=\"right\">5</td><td align=\"right\">896</td><td align=\"right\">10</td></tr><tr><td align=\"right\">7</td><td align=\"right\">608</td><td align=\"right\">5</td><td align=\"right\">626</td><td align=\"right\">6</td><td align=\"right\"><italic>1022</italic></td><td align=\"right\">8</td></tr><tr><td align=\"right\">8</td><td align=\"right\"><italic>710</italic></td><td align=\"right\">8</td><td align=\"right\"><italic>710</italic></td><td align=\"right\">11</td><td align=\"right\">1038</td><td align=\"right\">7</td></tr><tr><td align=\"right\">9</td><td align=\"right\">860</td><td align=\"right\">10</td><td align=\"right\">740</td><td align=\"right\">8</td><td align=\"right\"><bold>1041</bold></td><td align=\"right\">12</td></tr><tr><td align=\"right\">10</td><td align=\"right\">1006</td><td align=\"right\">10</td><td align=\"right\">841</td><td align=\"right\">9</td><td align=\"right\">1043</td><td align=\"right\">4</td></tr><tr><td align=\"right\">11</td><td align=\"right\">1007</td><td align=\"right\">4</td><td align=\"right\">911</td><td align=\"right\">7</td><td align=\"right\">1071</td><td align=\"right\">12</td></tr><tr><td align=\"right\">12</td><td align=\"right\">1101</td><td align=\"right\">7</td><td align=\"right\"><italic>1022</italic></td><td align=\"right\">3</td><td align=\"right\">1123</td><td align=\"right\">9</td></tr><tr><td align=\"right\">13</td><td align=\"right\">1127</td><td align=\"right\">9</td><td align=\"right\"><italic>1041</italic></td><td align=\"right\">2</td><td align=\"right\">1124</td><td align=\"right\">5</td></tr><tr><td align=\"right\">14</td><td align=\"right\">1200</td><td align=\"right\">1</td><td align=\"right\">1078</td><td align=\"right\">12</td><td align=\"right\"><bold>1150</bold></td><td align=\"right\">10</td></tr><tr><td align=\"right\">15</td><td align=\"right\">1278</td><td align=\"right\">4</td><td align=\"right\">1103</td><td align=\"right\">11</td><td align=\"right\">1198</td><td align=\"right\">8</td></tr><tr><td align=\"right\">16</td><td align=\"right\">1457</td><td align=\"right\">9</td><td align=\"right\">1318</td><td align=\"right\">10</td><td align=\"right\">1228</td><td align=\"right\">6</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>Thirteen of the 16 spot features included in the class prediction classifier were identified. The average ratios at each time point are given.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td align=\"center\" colspan=\"6\">Average Ratio (infected/control)</td></tr></thead><tbody><tr><td align=\"left\">Spot</td><td align=\"left\">Protein ID</td><td align=\"center\">0 mpi</td><td align=\"center\">8 mpi</td><td align=\"center\">16 mpi</td><td align=\"center\">24 mpi</td><td align=\"center\">32 mpi</td><td align=\"center\">40 mpi</td></tr><tr><td colspan=\"8\"><hr/></td></tr><tr><td align=\"left\">387</td><td/><td align=\"center\">2.04</td><td align=\"center\">12.35</td><td align=\"center\">10.91</td><td align=\"center\">7.63</td><td align=\"center\">2.46</td><td align=\"center\">8.70</td></tr><tr><td align=\"left\">393</td><td align=\"left\">clusterin (Bos Taurus)</td><td align=\"center\">2.44</td><td align=\"center\">11.36</td><td align=\"center\">9.17</td><td align=\"center\">5.23</td><td align=\"center\">10.12</td><td align=\"center\">6.76</td></tr><tr><td align=\"left\">405</td><td align=\"left\">clusterin (Bos Taurus)</td><td align=\"center\">4.05</td><td align=\"center\">23.68</td><td align=\"center\">77.54</td><td align=\"center\">17.00</td><td align=\"center\">54.36</td><td align=\"center\">33.80</td></tr><tr><td align=\"left\">597</td><td align=\"left\">Ig Gamma-2 chain C region (Bos taurus)</td><td align=\"center\">1.98</td><td align=\"center\">-1.4</td><td align=\"center\">3.58</td><td align=\"center\">2.35</td><td align=\"center\">3.03</td><td align=\"center\">4.93</td></tr><tr><td align=\"left\">749</td><td align=\"left\">simlar to GCAP-11/uroguanylin (Bos taurus)</td><td align=\"center\">-1.33</td><td align=\"center\">1.80</td><td align=\"center\">1.03</td><td align=\"center\">-1.23</td><td align=\"center\">1.03</td><td align=\"center\">1.15</td></tr><tr><td align=\"left\">896</td><td align=\"left\">cystatin E/M (Bos Taurus)</td><td align=\"center\">-1.15</td><td align=\"center\">1.13</td><td align=\"center\">-1.09</td><td align=\"center\">1.23</td><td align=\"center\">-1.33</td><td align=\"center\">1.10</td></tr><tr><td align=\"left\">1022</td><td align=\"left\">cathelicidin antimicrobial peptide (Bos Taurus)</td><td align=\"center\">-1.10</td><td align=\"center\">-1.12</td><td align=\"center\">-1.02</td><td align=\"center\">-2.54</td><td align=\"center\">-1.61</td><td align=\"center\">-1.91</td></tr><tr><td align=\"left\">1038</td><td align=\"left\">cathelicidin 1 (Bos Taurus)</td><td align=\"center\">-3.84</td><td align=\"center\">1.03</td><td align=\"center\">-1.91</td><td align=\"center\">-4.13</td><td align=\"center\">-2.46</td><td align=\"center\">-1.87</td></tr><tr><td align=\"left\">1041</td><td/><td align=\"center\">-1.10</td><td align=\"center\">-1.17</td><td align=\"center\">-1.14</td><td align=\"center\">-2.77</td><td align=\"center\">-1.80</td><td align=\"center\">-2.18</td></tr><tr><td align=\"left\">1043</td><td align=\"left\">cathelicidin 1 (Bos Taurus)</td><td align=\"center\">1.35</td><td align=\"center\">1.27</td><td align=\"center\">1.13</td><td align=\"center\">-2.99</td><td align=\"center\">-1.61</td><td align=\"center\">-1.60</td></tr><tr><td align=\"left\">1071</td><td align=\"left\">cathelicidin 1 (Bos Taurus)</td><td align=\"center\">1.23</td><td align=\"center\">-1.47</td><td align=\"center\">-1.20</td><td align=\"center\">-2.29</td><td align=\"center\">-1.76</td><td align=\"center\">-1.81</td></tr><tr><td align=\"left\">1123</td><td align=\"left\">simlar to GCAP-11/uroguanylin (Bos taurus)</td><td align=\"center\">1.35</td><td align=\"center\">-1.14</td><td align=\"center\">1.05</td><td align=\"center\">-2.98</td><td align=\"center\">-1.91</td><td align=\"center\">-2.51</td></tr><tr><td align=\"left\">1124</td><td align=\"left\">simlar to GCAP-11/uroguanylin (Bos taurus)</td><td align=\"center\">1.27</td><td align=\"center\">-3.52</td><td align=\"center\">-2.25</td><td align=\"center\">-3.19</td><td align=\"center\">-2.28</td><td align=\"center\">-2.55</td></tr><tr><td align=\"left\">1150</td><td/><td align=\"center\">1.38</td><td align=\"center\">-3.02</td><td align=\"center\">-1.66</td><td align=\"center\">-1.08</td><td align=\"center\">-5.36</td><td align=\"center\">1.01</td></tr><tr><td align=\"left\">1198</td><td align=\"left\">simlar to GCAP-11/uroguanylin (Bos taurus)</td><td align=\"center\">-1.34</td><td align=\"center\">-3.00</td><td align=\"center\">-1.49</td><td align=\"center\">-1.04</td><td align=\"center\">-4.16</td><td align=\"center\">-1.43</td></tr><tr><td align=\"left\">1228</td><td align=\"left\">simlar to GCAP-11/uroguanylin (Bos taurus)</td><td align=\"center\">-1.11</td><td align=\"center\">-5.84</td><td align=\"center\">-5.19</td><td align=\"center\">-6.95</td><td align=\"center\">-3.20</td><td align=\"center\">-3.98</td></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional File 1</title><p>Results of LC/MS/MS analyses and protein statistics. Thirteen of the 16 spot features included in the class prediction classifier were identified. For each identified protein the mascot score, the number of peptides, the % coverage and the corresponding NCBI identifier are provided. Individual ions scores &gt; 54 indicate identity or extensive homology (p &lt; 0.05). The average ratios at each time point are also given.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Statistical Analysis of Protein Concentration in the Urine Samples. Protein concentrations of urine are evaluated to determine if there was any difference amongst cows and whether or not the concentration changed throughout the course of the disease.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Statistical Analysis of Cystatin Abundance in Control and Infected Urine samples collected at each of the 5 time points. The relative cystatin abundances found in control and infected urine were compared.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>The disease state, cow identity and months post infection (mpi) identify the sample. Dyes and gels were randomly assigned to the 4 biological replicates of infected and control cows to minimize the influence of dye bias and gel to gel variation. The 2 infected samples marked NA were either not collected (cow 52, 24 mpi) or no suitable gel image was obtained (cow 38, 0 mpi)</p></table-wrap-foot>", "<table-wrap-foot><p>The classifier created was applied to the training set to assign gel maps with respect to disease state. The classification matrix shows an overview of the classification of the gel maps. Gels that were correctly classified are displayed in bold type. A classifier containing 16 biomarkers was used to discriminate between the 3 groups with 83.33% ± 18.3 accuracy. A single protein was able to discriminate between control and infected samples with 100% accuracy.</p></table-wrap-foot>", "<table-wrap-foot><p>The classifier created was applied to the training set to assign gel maps with respect to disease progression. The classification matrix shows an overview of the classification of the gel maps. Gels that were correctly classified are displayed in bold type. A classifier containing 16 biomarkers was used to discriminate between the 5 time points with 85% ± 13.2 accuracy. The two misclassified samples at 32 mpi were placed into the immediately proceeding sampling time.</p></table-wrap-foot>", "<table-wrap-foot><p>The classifier created was applied to the training set to assign gel maps with respect to sample collection time. The classification matrix shows an overview of the classification of the gel maps. Gels that were correctly classified are displayed in bold type. A classifier containing 16 biomarkers was used to discriminate between the 5 time points with 85% ± 19.2 accuracy. The misclassified samples at 16 and 24 mpi were placed into the immediately proceeding sampling times. The misclassified sample at 32 mpi was classified as 16 mpi.</p></table-wrap-foot>", "<table-wrap-foot><p>In this particular instance each classifier was composed of 16 biomarkers. Biomarkers that appear in more than one classifier are in italics. The three biomarkers in the class prediction set that were not identified by MS analysis (387,1041,1150) are in bold faced type.</p></table-wrap-foot>" ]

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[ "<title>Introduction</title>", "<p>Diabetic cardiomyopathy is known to develop in humans in the absence of coronary or hypertensive disease [##REF##16159978##1##]. The mechanism by which diabetic cardiomyopathy develops has been studied in literature using in vivo and ex vivo experiments [##REF##15294881##2##,##REF##17937784##3##]. It has been postulated that endothelial dysfunction, endomyocardial fibrosis, direct toxic effect of hyperglycemia on cardiomyocytes and autonomic neuropathy play an important role. Although recent studies have suggested abnormalities in coronary small vessels in humans [##REF##9285513##4##,##REF##8513969##5##], similar to dilated cardiomyopathy [##REF##3976520##6##,##REF##2306829##7##], and in spontaneously diabetic rats [##REF##2776149##8##], the association between vascular and myocardial disease in diabetes remains controversial.</p>", "<p>Myocardial contrast echocardiography (MCE) has been shown to be a useful tool to estimate the myocardial blood flow (MBF) at rest and during stress in dogs and humans [##REF##11382724##9##, ####REF##10600857##10##, ##REF##12618735##11##, ##REF##15734622##12##, ##REF##9490243##13####9490243##13##]. Echocardiography has been recently adapted to image hearts of rodents [##REF##18490338##14##] and MCE has shown a good correlation of MBF estimates with microspheres technique [##REF##12049959##15##].</p>", "<p>In order to better investigate the role of functional vessel abnormalities and its relationship with structural small vessel abnormalities, we sought to apply this new MCE method in a small animal model of Streptozotocin-induced diabetes, to determine the coronary vascular reserve compared to normal controls, combined with histopathology. Furthermore, we aimed to establish a relationship between these alterations and the cardiac function.</p>" ]

[ "<title>Methods</title>", "<title>Animals handling and study protocol</title>", "<p>A total of 40 adult male Wistar Unilever rats (Harlan, The Netherlands) (10 weeks-old, 328 ± 7 g) were studied.</p>", "<p>Diabetes mellitus was induced in 20 rats by a single intravenous injection of 45 mg/kg Streptozotocin (STZ) in a 0.1 mol/l citrate buffer solution. Three days after treatment with STZ, tail vein blood glucose samples were measured with Onetouch^Rglucometer (Johnson &amp; Johnson) to ensure induction of diabetes. During the entire study the animals were housed in stainless steel cages with sawdust bedding. They were kept at an average room temperature of 24°C, a relative humidity of 50% and a 12-hour day/night cycle. All rats had unlimited access to food and water during follow up.</p>", "<p>MCE was performed at 1 and 6 months, both at rest and after dipyridamole (DIP) infusion (20 mg/kg over 10 minutes). Blood pressure was measured with the advanced auto-inflate blood pressure monitor with infrared sensor and tail-cuff from Harvard Apparatus^®France. The rats were anesthetized with pentobarbital 50 mg/kg intraperitoneally and allowing spontaneous respiration.</p>", "<p>This study was approved by the Animal Research Committee at the Vrije Universiteit Brussel and conformed to the Institute for Laboratory Animal Research Guide for Care and Use of Laboratory Animals.</p>", "<title>Myocardial Contrast Echocardiography</title>", "<p>The anterior chest hair was removed with a shaver and the rats were positioned in left lateral decubitus on a wooden bench. Recordings were made under continuous ECG monitoring by fixing electrodes on the paws. A 24-gauge cannula was inserted into a tail vein for infusion. The commercially available contrast agent Sonovue^®(Bracco Diagnostics, Inc.) is an aqueous suspension of stabilized SF₆microbubbles. The size of these microbubbles is between 1 and 10 μm, and their number is between 2 and 5 × 10⁸per mL. The solution was prepared according to the manufacturer's instructions. Subsequently this solution was diluted twice by adding 5 ml of sodium chloride 0.9% (same carrier fluid). A continuous infusion of the diluted solution of Sonovue^®was given using a dedicated pump (Bracco, Italy) at a rate of 0.3–0.4 ml/min.</p>", "<p>We used a Vivid 7 (GE, VingMed, Horton, Norway) with a 10 MHz (10S) probe. High power intermittent images were recorded in a parasternal short axis view at a depth of 2 cm at the level of the papillary muscles. The transmit power was set at a maximum (0 dB), with a mechanical index of 0.8. Gain settings were optimized at the beginning of the study and subsequently held constant. The pulsing interval (PI) was gated to the ECG (end systole) and progressively increased from 1 to 20 (depending on the heart rate). Images were digitally stored and measurements were analysed offline by the cardiologist, using the EchoPAC software (GE Vingmed, version 3.1.3). Regions of interest were placed on the anterior myocardium with a constant size (height: 1 mm, wide: 3 mm). The myocardial ROIs were individually adjusted by hand to carefully avoid the right and LV cavities. Videointensity (VI) was measured in these ROI's. As shown in the Figure ##FIG##0##1##, PI versus background-substracted images VI plots were then generated, and they were fitted to the exponential function y = A(1-e^-βt), in which beta represents the rate of rise in signal intensity, which reflects microbubble velocity, and A is the peak plateau amplitude, which reflects the microvascular cross-sectional area or myocardial blood volume, as previously described [##REF##15597016##16##]. Regional differences in VI due to concentration of microbubbles in blood may occur and the same concentration may not be achievable both at rest and during stress even with continuous infusions. Moreover, significant heterogeneity of acoustic energy in different parts of the scan sector makes comparisons of backscatter signals from segments at the margins or lower depths difficult with those in the centre and attenuation also results in spurious decreases in myocardial VI. Therefore, we quantitatively estimated the relative blood volume rBV by the division of myocardial plateau video intensity A and the adjacent left ventricular intensity in the near wall cavity (ALV), as described previously [##REF##15734622##12##]. In accordance with Positron Emisson Tomography, at was set to 1.05 g·ml-1, and MBF was calculated with the following equation: MBF = rBV × β/ρT = (A-ALV) × β/ρT</p>", "<p>Finally, the vasodilator reserve for beta and rBV, MBF, were calculated as the ratio of hyperaemic to baseline values for these parameters.</p>", "<title>Echocardiographic measurements</title>", "<p>Grey scale images were recorded in a parasternal short axis view at a depth of 1.5 to 2 cm, using a linear 13 MHz probe (i13L), both at rest and after dypiridamole infusion. Left ventricular chamber diameter in end-systole (LVESD) and end-diastole (LVEDD), left ventricular anterior wall thickness in end-systole and end-diastole, and left ventricular posterior wall thickness in end-systole and end-diastole, as well as left ventricular fractional shortening (FS% = [(LVEDD – LVESD)/LVEDD] × 100), were determined from the M-mode tracings in a short axis view (average of three consecutive cycles) at the level of the papillary muscles.</p>", "<title>Histology</title>", "<p>At the end of the follow-up, all rats were killed with with 2 ml/kg sodium pentobarbital (CEVA, Brussels, Belgium) intravenously for histological studies. The hearts were immediately removed and fixed in 4% neutral buffered formalin for 2 hours. Three short-axis slices of myocardial tissue were obtained and embedded in paraffin. Heamatoxylin-eosin and Masson's trichrome staining were performed. Morphometry was performed by digital image analysis using a PC digital image camera (Digital Sight DS-5M, Nikon Corp, Japan) mounted on an Axiolab Zeiss light microscope (Carl Zeiss Corp, Germany) with a 10× objective (Acroplan, Zeiss). We used the NIH Image program (Image-J 1.35d, Nation Institutes of Health, Bethesda, USA). The program was calibrated with a graduated slide. Five randomly selected Masson's Trichrome microscopic images were used to evaluate the cardiomyocytes, interstitium and capillaries. The width of at least 10 left ventricle cardiomyocytes was measured in each section. Colour segmentation was applied to calculate the percentage of interstitial fibrosis. For the measurement of the capillary surface the histological photomicrographs were converted to 8-bit grey scale images. Subsequently, the threshold was adjusted until only the space between the cardiomyocytes was highlighted. This space was considered as a marker for capillary area. The percentage of black colored area was then measured. (Figure ##FIG##1##2##) Capillary diameters were measured manually. Microangiopathy involving arterioles, capillaries, and venules, and hyaline arteriosclerosis were also evaluated. An experienced pathologist performed the analyses blindly.</p>", "<title>Statistical analysis</title>", "<p>Data are expressed as mean ± SD. The unpaired Student's <italic>t </italic>test was used for continuous variables to assess differences between groups, whereas ordinal variables were analyzed with the chi-square test. A subset of 10 rats underwent MCE three days after the first examination in order to test the interstudy variability. Differences between the repeated measurements were evaluated by the paired Student's t-test. The coefficient of variability was expressed as the percentage difference for each pair of measurements as ((measurement observation 1 – measurement observation 2)/0.5 × (measurement observation 1+ measurement observation 2)) × 100 and expressed as mean ± SD. Another subset of 20 rats studies (10 rest and 10 stress) were analyzed by two independent observers, blinded for the results of each other, in order to test the interobserver variability. The interobserver variability in quantitative MCE was assessed by computing intraclass correlation coefficients using one-way ANOVA with a random factor and by calculating the limits of agreement between measurements made by use of Bland-Altman analysis [##REF##2868172##17##]. A value of p &lt; 0.05 was considered statistically significant. All statistical analyses were performed using SPSS (version 14.0) statistical software (SPSS Inc, Chicago, IL).</p>" ]

[ "<title>Results</title>", "<title>Clinical parameters</title>", "<p>Glucometry and gravimetric parameters are summarized in Table ##TAB##0##1##. After six months, animals treated with STZ had high glucose levels. Other symptoms frequently associated with diabetic state such as lower body weights, polyuria, polyphagia were observed in the diabetic rats. The heart mass decreased in the diabetic group but it was not significant compared to controls. The heart/body weight ratio significantly increased in the diabetic group.</p>", "<p>At the end of the follow-up there was no significant change in heart rate in the diabetic when compared to control rats nor in systolic blood pressure.</p>", "<title>Myocardial contrast echocardiography</title>", "<p>Simple pulsing sequence during MCE was feasible in rats and it could assess myocardial blood velocity and volume separately, and myocardial blood flow as the product of the two. As shown in Table ##TAB##1##2##, during hyperaemia the basic haemodynamic parameters did not differ significantly in both groups. The myocardial blood flow estimate by MCE was also similar in controls and diabetics at rest and during hyperaemia. Interestingly, the β slope was significantly less steep in the control group compared to diabetics, both at rest and during hyperaemia. Although relative blood volume was not different at baseline in both groups, the rBV had significantly increased with hyperaemia in the controls compared to diabetics. Table ##TAB##2##3## summarizes the changes in perfusion parameters and the myocardial perfusion reserve with hyperaemia. Although diabetics had a steeper β slope at rest and during hyperaemia, the change in β did not differ significantly between controls and diabetics. Conversely, changes in rBV were significantly more pronounced in the controls than in diabetics. As a result, the myocardial perfusion reserve was significantly higher in the control group.</p>", "<p>Finally, no side effects due to contrast were observed and there was no significant change of the heart rate before and after contrast infusion both at rest and during hyperaemia.</p>", "<title>Interobserver and interstudy variability</title>", "<p>Measurements were obtained in all rats. In the subset of 10 rats in which MCE was performed three days after the first examination in order to test the interstudy variability, differences between the repeated measurements were not statistically significant (p &gt; 0.05). Interobserver variability was acceptable: 13.2 ± 10.1% and 14.5 ± 4.5% for top A and slope β, respectively. Bland-Altman analysis showed a good agreement between observers for both rest and DIP studies, as shown in the Figure ##FIG##2##3##.</p>", "<title>Echocardiographic measurements</title>", "<p>Means and SD of the different anatomical parameters are given in Table ##TAB##3##4##. As can be derived from the M-Mode measurements, there was no difference between normal and diabetic rats after six months of follow-up both at rest and during DIP infusion, except for a decrease in inferior wall thickness at rest in diastole. When corrected for LV mass [##REF##2936235##18##], a significant increase in LVESD (6.13 ± 1.8 vs 3.98 ± 0.03 mm/g; p &lt; 0.001) and in LVEDD (13.98 ± 1.4 vs 5.12 ± 0.02 mm/g; p &lt; 0.001) was observed in the diabetic group compared to controls.</p>", "<title>Histology</title>", "<p>There was no difference regarding extra-cellular collagen deposits (trichrome staining) or endomyocardial necrosis (heamatoxilin-eosin staining) in myocardium of control and diabetic rats at the end of the follow up. The percentage of fibrosis was less than 1%, with no difference between the two groups at the end of the follow up. Mean capillary surface area (16.2 ± 1.7%, p = 0.01) and capillary diameter (11.9 ± 0.5 μm, p = 0.04) were significantly lower in the diabetic animals compared to the controls (11.0 ± 1.2% and 10.8 ± 0.3 μm, respectively). No microangiopathy involving arterioles, capillaries, venules, and hyaline arteriosclerosis was observed.</p>" ]

[ "<title>Discussion</title>", "<p>The study of cardiomyopathies in small animals may contribute to our understanding of the cardiac pathophysiology and to evaluate experimental treatment strategies. The present study shows that myocardial perfusion imaging with contrast echocardiography can successfully be applied for the non-invasive evaluation of cardiac perfusion at rest and under hyperaemia in STZ-induced diabetic rats. Our results suggest that after six months, diabetes induces a functional alteration of the myocardial microcirculation that may explain left ventricular systolic dysfunction. Our data further indicate that microcirculation is already altered at rest and that the major determinant for decreasing myocardial perfusion reserve during hyperaemia, is the lower capillary recruitment in the diabetic group. Finally, histopathology findings demonstrate a reduced density of myocardial capillaries, in the diabetic group that can only be unmasked with hyperaemia using MCE.</p>", "<title>Clinical parameters</title>", "<p>The STZ induced diabetic rats used in our experiments are reminiscent of a model of uncontrolled hyperglycemia due to the direct pancreatic beta cell destruction and resulting insulin deficiency [##UREF##0##19##]. Our glucometry and gravimetric values (Table ##TAB##0##1##) are in accord with other published values at similar time points [##REF##2477102##20##, ####REF##1928388##21##, ##REF##10634674##22####10634674##22##]. These STZ rats resembled more type 1 diabetes. The dose of STZ injected (45 mg/kg) was low in this study. However, it has been successfully applied in previous studies [##REF##17937784##3##,##REF##18490338##14##] and the impact on glucometry and gravimetric values was similar compared to the administration of a higher dose of STZ, leading to equivalent absolute insulin deficiency.</p>", "<title>Myocardial perfusion</title>", "<p>Microbubbles are excellent tracers of red blood cell kinetics. They are pure intravascular tracers. The method to quantify MBF is based on rapid destruction of these microbubbles by ultrasound, and subsequent assessment of the rate of replenishment into the myocardium within the ultrasound beam elevation. This method allows the assessment of the components of MBF: flow velocity and myocardial blood volume [##REF##9490243##13##]. In the presence of increased myocardial oxygen demand, there is arteriolar vasodilation, reducing the resistance at the arteriolar level, which enables a higher precapillary pressure, translating into increased red blood cell velocity across the capillary network, and opening dormant capillary networks in order to maintain mean trans-capillary pressure (recruitment), thus increasing the overall myocardial blood volume. Hence overall myocardial blood flow is increased.</p>", "<p>The present study has shown that quantitative MCE is a robust method to assess the myocardial blood flow in small animals at rest and during hyperemia. The measurements are feasible and repeatable over time and between observers. As expected from physiology and previous in vitro and in vivo studies [##REF##11382724##9##,##REF##10600857##10##,##REF##9490243##13##,##REF##7270706##23##,##REF##6480228##24##], we were able to show the increase of MBF with hyperemia in normal rats. Moreover, our data were consistent with previous experiments in small animals, validating MCE measurements using microspheres [##REF##12049959##15##].</p>", "<p>In our diabetic population, we could observe, at rest, a significant increase in β compared to controls. This suggests a decrease in arteriolar resistance and vasodilation of arterioles. Although this increase in red cell velocity at rest compared to controls persists under hyperaemia in the diabetics versus the controls, the change in β is not significantly different in diabetics compared to controls. This finding suggests the capacity of arterioles to further vasodilate, even in the diabetic group, in the absence of coronary artery lesions.</p>", "<p>Structural alterations of the small vessels in diabetes have been incriminated in the development of diabetic cardiomyopathy, although this remains controversial. A reduction in capillary density and a significantly greater thickening of the capillary basement membrane has been shown compared to control subject in humans [##REF##10642930##25##] and more recently in rodents [##REF##17148754##26##]. Because rBV represents essentially capillaries, one would therefore expect to find a decrease in A in the diabetic rats, which is not the case at rest. However, during hyperaemia, there is less increase of rBV in diabetic rats compared to normal rats, indicating a less important capillary recruitment in diabetics. This may reflect the absence of compensation to an increased pre-capillary pressure mediated by arteriolar vasodilatation, as shown by the increased red cell velocity at rest and during hyperaemia compared to controls. In our study, histopathology did confirm a significant reduction in capillary density, in accordance with the previous studies [##REF##10642930##25##,##REF##17148754##26##]. The increase in pre-capillary pressure induced by the arteriolar vasodilation and the decrease of capillary density may be compensated by a capillary recruitment at rest in the diabetic group resulting in no significant change of rBV. We can hypothesize that hyperaemia is required to unmask the decrease of capillary density in diabetics, using MCE. As a net result, myocardial perfusion reserve is altered and may lead to relative ischemia. Similarly, a reduction of myocardial blood flow and significant increase in total coronary resistance during hyperaemia and consequent impairment of coronary flow reserve have been reported in type I young adult diabetic patients with no or minimal microvascular complications and without any evidence of coronary heart disease [##REF##9519721##27##]. Reduced myocardial flow reserve may lower the threshold for myocardial ischemia, particularly when coronary stenoses are present. It has been proposed that diabetic cardiomyopathy is a consequence of repeated episodes of myocardial ischemia resulting from these functional abnormalities in small vessels during increased myocardial demand. As shown by Litwin and colleagues, a real insulin-therapy that aims to normalize the glycemia, also corrects the cardiac abnormalities [##REF##2200804##28##]. An ongoing study investigates the effect of the correction of diabetes condition on the impairment of coronary circulation.</p>", "<title>Left ventricular function</title>", "<p>There remains controversy regarding diabetes-induced LV dysfunction, especially in type 1 diabetes, in the absence of documented coronary artery disease. Some authors have been able to detect early systolic LV dysfunction and dilatation of the left ventricle in STZ induced diabetic cardiomyopathy [##REF##12967586##29##,##REF##11510948##30##]. On the contrary, others were not able to demonstrate a remodelling and a significant alteration of the systolic function in a similar rat population [##REF##8864645##31##]. A recent study in patients with type 1 diabetes, even with the application of echocardiography, biochemical and morphologic techniques, failed to demonstrate that diabetes type 1 may actually precipitate myocardial dysfunction and no heart-specific, histological changes in the myocardium were found. However, as acknowledged by the authors of this latter study, all the patients were treated with intensive insulin therapy [##REF##17766928##32##].</p>", "<p>Standard measurements of LV wall thickness and systolic and diastolic LV diameters by M-mode have extensively been described in normal and diseased rat models [##REF##7743628##33##, ####REF##12911343##34##, ##REF##12958037##35##, ##REF##14752491##36####14752491##36##]. The ratio data such as fractional shortening and ejection fraction have been demonstrated to be similar in rat and human echocardiography [##REF##14752491##36##]. Comparable results were obtained in the present study. In literature anatomical M-Mode and bi-dimensional echocardiography have been able to detect early systolic LV dysfunction and dilatation of the left ventricle in STZ induced diabetic cardiomyopathy [##REF##10634674##22##,##REF##12967586##29##,##REF##10588232##37##, ####REF##11510948##38##, ##REF##16501301##39####16501301##39##]. We observed an increase in mean normalized EDV of the diabetic group compared to controls. Meanwhile the normalized ESV of the diabetic rats also increased compared to controls but in lower proportion. The significant increase of normalized EDV with diabetes in this study is in accordance with previous reports [##REF##10634674##22##,##REF##12967586##29##,##UREF##1##40##,##REF##10588232##41##]. However, in contrast to our findings, other authors have shown no significant change or even an decrease in this parameter [##REF##11790819##42##, ####REF##16595006##43##, ##REF##16501301##44####16501301##44##]. We also observed an increase in normalized ESV, suggesting a decrease in contractility, in accord with all previous studies [##REF##10634674##22##,##REF##12967586##29##,##UREF##1##40##,##REF##16595006##43##,##REF##16501301##44##]. The differences in LV volumes may be due to the method used to normalize the data or to theabsence of normalization to body weight in other studies. Allometric relations exist between cardiac and body size measurements. However, the correct method to use in rat is unknown. We normalized LV mass to bodyweight as applied in the previous studies using the same animal model [##REF##10634674##22##,##REF##10588232##41##]. In addition, these differences may reflect the difference in the strain of rats (Wistar Unilever, Wistar Kyoto, Sprague-Dawley), since this factor has been shown to clearly influence cardiomyopathy in the STZ model of diabetes [##REF##9217891##45##].</p>", "<title>Histopathology</title>", "<p>In the present study, no significant pathological changes were observed in diabetic rats, regarding extra-cellular collagen deposits, endomyocardial necrosis in myocardium, and no microangiopathy involving arterioles, capillaries, venules, and hyaline arteriosclerosis was present, at the end of the follow up. Conversely, in our study, histopathology did confirm a significant reduction in capillary density. These results are in accordance with previously published works [##REF##10642930##25##,##REF##17148754##26##]. The muscular fibers were thinner in the diabetic rats: 14.6 ± 3.1 μm in controls and 11.4 ± 2.8 μm in diabetics (P = 0.043). This last finding was also consistent with previously published work (23).</p>" ]

[ "<title>Conclusion</title>", "<p>Myocardial perfusion imaging with contrast echocardiography can successfully be applied for the non-invasive evaluation of cardiac perfusion at rest and under hyperaemia in STZ-induced diabetic rats. After six months, diabetes induces a functional alteration of the myocardial microcirculation and a left ventricular systolic dysfunction. Microcirculation is already altered at rest. The major determinant for decreasing myocardial perfusion reserve during hyperemia, is the lower capillary recruitment in the diabetic group. Histopathology findings demonstrate a reduced density of myocardial capillaries in the diabetic group that can only be unmasked with hyperaemia using MCE. These findings may offer new insights into the underlying mechanisms of diabetes cardiomyopathy.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>The role of structural and functional abnormalities of small vessels in diabetes cardiomyopathy remains unclear. Myocardial contrast echocardiography allows the quantification of myocardial blood flow at rest and during dipyridamole infusion. The aim of the study was to determine the myocardial blood flow reserve in normal rats compared with Streptozotocin-induced diabetic rats using contrast echocardiography.</p>", "<p>We prospectively studied 40 Wistar rats. Diabetes was induced by intravenous streptozotocin in 20 rats. All rats underwent baseline and stress (dipyridamole: 20 mg/kg) high power intermittent imaging in short axis view under anaesthesia baseline and after six months. Myocardial blood flow was determined and compared at rest and after dipyridamole in both populations. The myocardial blood flow reserve was calculated and compared in the 2 groups. Parameters of left ventricular function were determined from the M-mode tracings and histological examination was performed in all rats at the end of the study.</p>", "<p>At six months, myocardial blood flow reserve was significantly lower in diabetic rats compared to controls (3.09 ± 0.98 vs. 1.28 ± 0.67 ml min-1 g-1; p &lt; 0.05). There were also a significant decrease in left ventricular function and a decreased capillary surface area and diameter at histology in the diabetic group.</p>", "<p>In this animal study, diabetes induced a functional alteration of the coronary microcirculation, as demonstrated by contrast echocardiography, a decrease in capillary density and of the cardiac systolic function. These findings may offer new insights into the underlying mechanisms of diabetes cardiomyopathy.</p>" ]

[ "<title>Limitations</title>", "<p>Our STZ model resembled more type 1 diabetes and therefore, our results may not be applied to other forms of diabetes. Using M-Mode, we have only performed radial measurements of diameters and therefore volumes were calculated based on these measurements. However, it has been previously shown that M-mode echocardiographic measurements are representative of ventricular function and volumes measurements, compared to other imaging techniques [##REF##17937784##3##,##REF##16595006##43##]. No significant structural abnormalities were noted in the myocardium after 6 months. However, electron microscopic was not performed in the present study and previous studies using this method have repeatedly documented that diabetes is indeed associated with abnormalities in myocardial structure [##REF##3896897##46##]. This may partially explain the left ventricular dysfunction despite the absence of abnormal findings at histology in our study.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Steven Droogmans is Aspirant of the Research Foundation – Flanders (Belgium) (FWO).</p>", "<p>Tony Lahoutte is a Senior Clinical Investigator of the Research Foundation – Flanders (Belgium) (FWO).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Example of quantitative perfusion analysis. </bold>The rBV was quantitatively estimated by the division of myocardial plateau video intensity and the adjacent left ventricular intensity in the near wall cavity at rest and during hyperaemia (DIP).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Histological characteristics and analysis of the myocardium in the diabetic and control rats after 20 weeks.</bold> Top panel (A), Masson's trichrome staining showed no evidence of myocardial fibrosis in both groups. Cardiomyocytes were smaller in the diabetic animals (upper right). Lower panel (B), the histological photographs (A) were subsequently converted to 8-bit grey scale images (not shown) and an appropriate threshold was chosen in order to visualize the capillaries only (black and white images, B). The percentage capillary area and capillary diameters were lower in the diabetic rats compared to controls (lower right). Magnification at 400× (A and B), scale bar is 100 μm, *P &lt; 0.05.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Bland-Altman graphs for top (A) and slope (β) at rest and after dypiridamole in normal rats. </bold>All measurements are within 2 SD of their differences demonstrating the agreement between the two independent observers.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Glucometry and gravimetric data obtained at 6 months of diabetes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Glycemia (mg/dL)</bold></td><td align=\"center\"><bold>Body mass (g)</bold></td><td align=\"center\"><bold>Heart mass (mg)</bold></td><td align=\"center\"><bold>Heart to Body Mass ratio (mg/g)</bold></td></tr></thead><tbody><tr><td align=\"center\">Controls (n = 20)</td><td align=\"center\">95 ± 13</td><td align=\"center\">662 ± 49</td><td align=\"center\">1369 ± 222</td><td align=\"center\">2.1 ± 0.2</td></tr><tr><td align=\"center\">Diabetics (n = 20)</td><td align=\"center\">426 ± 54*</td><td align=\"center\">382 ± 34*</td><td align=\"center\">1182 ± 279</td><td align=\"center\">2.8 ± 0.3*</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Haemodynamic and perfusion data at baseline and during hyperaemia in controls and diabetics.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\">Baseline</td><td align=\"center\" colspan=\"3\">Hyperemia</td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"center\">Variable</td><td align=\"center\">Controls</td><td align=\"center\">Diabetics</td><td align=\"center\">p</td><td align=\"center\">Controls</td><td align=\"center\">Diabetics</td><td align=\"center\">p</td></tr></thead><tbody><tr><td align=\"left\">Heart rate, min^-1</td><td align=\"center\">318 ± 27</td><td align=\"center\">299 ± 33</td><td align=\"center\">NS</td><td align=\"center\">315 ± 29</td><td align=\"center\">316 ± 25</td><td align=\"center\">NS</td></tr><tr><td align=\"left\">SBP, mm Hg</td><td align=\"center\">131 ± 7</td><td align=\"center\">131 ± 13</td><td align=\"center\">NS</td><td align=\"center\">96 ± 3</td><td align=\"center\">100 ± 6</td><td align=\"center\">NS</td></tr><tr><td align=\"left\">RPP, min^-1mm Hg</td><td align=\"center\">41,342 ± 1,234</td><td align=\"center\">39,056 ± 1,324</td><td align=\"center\">NS</td><td align=\"center\">31,339 ± 1,567</td><td align=\"center\">31,561 ± 1,234</td><td align=\"center\">NS</td></tr><tr><td align=\"left\">MBF, ml·min ^-1·g ^-1</td><td align=\"center\">2.42 ± 0.823</td><td align=\"center\">3.75 ± 0.943</td><td align=\"center\">NS</td><td align=\"center\">5.81 ± 0.99</td><td align=\"center\">5.02 ± 0.76</td><td align=\"center\">NS</td></tr><tr><td align=\"left\">β, min^-1</td><td align=\"center\">23.3 ± 8.2</td><td align=\"center\">27.6 ± 9.1</td><td align=\"center\">†</td><td align=\"center\">32.3 ± 7.7</td><td align=\"center\">37.4 ± 9.9</td><td align=\"center\">†</td></tr><tr><td align=\"left\">rBV, ml·min ^-1</td><td align=\"center\">0.112 ± 0.045</td><td align=\"center\">0.120 ± 0.05</td><td align=\"center\">NS</td><td align=\"center\">0.191 ± 0.046</td><td align=\"center\">0.141 ± 0.043</td><td align=\"center\">*</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Changes in perfusion parameters and myocardial perfusion reserve with hyperaemia</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\">Changes with Hyperaemia</td></tr><tr><td/><td colspan=\"3\"><hr/></td></tr><tr><td align=\"center\">Variable</td><td align=\"center\">Controls</td><td align=\"center\">Diabetics</td><td align=\"center\">p</td></tr></thead><tbody><tr><td align=\"left\">MBF, ml·min^-1·g ^-1</td><td align=\"center\">3.09 ± 0.98</td><td align=\"center\">1.28 ± 0.67</td><td align=\"center\">†</td></tr><tr><td align=\"left\">β, min^-1</td><td align=\"center\">9.1 ± 1.2</td><td align=\"center\">9.5 ± 1.1</td><td align=\"center\">0.06</td></tr><tr><td align=\"left\">rBV, ml·ml^-1</td><td align=\"center\">0.073 ± 0.015</td><td align=\"center\">0.023 ± 0.009</td><td align=\"center\">*</td></tr><tr><td align=\"left\">MPR</td><td align=\"center\">2.39 ± 0.89</td><td align=\"center\">1.38 ± 0.43</td><td align=\"center\">†</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>M-Mode parameters of the LV (parasternal short-axis view) measured in normal (n = 20) and diabetic rats (n = 20) after six months at rest and after dypiridamole infusion (DIP).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Normal Rest</td><td align=\"center\">Diabetes Rest</td><td align=\"center\">Normal DIP</td><td align=\"center\">Diabetes DIP</td></tr></thead><tbody><tr><td align=\"left\">Anterior wall diastole (cm)</td><td align=\"center\">0.21 ± 0.04</td><td align=\"center\">0.19 ± 0.04</td><td align=\"center\">0.21 ± 0.02</td><td align=\"center\">0.19 ± 0.02</td></tr><tr><td align=\"left\">Inferior wall diastole (cm)</td><td align=\"center\">0.21 ± 0.03</td><td align=\"center\">0.14 ± 0.03*</td><td align=\"center\">0.2 ± 0.02</td><td align=\"center\">0.18 ± 0.02</td></tr><tr><td align=\"left\">Anterior wall thickening (%)</td><td align=\"center\">49 ± 17</td><td align=\"center\">47 ± 15</td><td align=\"center\">58 ± 16</td><td align=\"center\">56 ± 16</td></tr><tr><td align=\"left\">Inferior wall thickening (%)</td><td align=\"center\">48 ± 16</td><td align=\"center\">46 ± 14</td><td align=\"center\">48 ± 12</td><td align=\"center\">49 ± 17</td></tr><tr><td align=\"left\">LV enddiastolic diameter (cm)</td><td align=\"center\">0.83 ± 0.09</td><td align=\"center\">0.88 ± 0.05</td><td align=\"center\">0.81 ± 0.07</td><td align=\"center\">0.85 ± 0.05</td></tr><tr><td align=\"left\">LV endsystolic diameter (cm)</td><td align=\"center\">0.47 ± 0.08</td><td align=\"center\">0.52 ± 0.05</td><td align=\"center\">0.48 ± 0.06</td><td align=\"center\">0.51 ± 0.05</td></tr><tr><td align=\"left\">LV enddiastolic volume (ml)</td><td align=\"center\">1.24 ± 0.3</td><td align=\"center\">1.49 ± 0.2</td><td align=\"center\">1.12 ± 0.3</td><td align=\"center\">1.30 ± 0.22</td></tr><tr><td align=\"left\">LV endsystolic volume (ml)</td><td align=\"center\">0.29 ± 0.12</td><td align=\"center\">0.34 ± 0.08</td><td align=\"center\">0.24 ± 0.08</td><td align=\"center\">0.28 ± 0.06</td></tr><tr><td align=\"left\">Fractional shortening (%)</td><td align=\"center\">41.42 ± 4.40</td><td align=\"center\">41.19 ± 3.92</td><td align=\"center\">40.4 ± 2.94</td><td align=\"center\">40.47 ± 3.48</td></tr><tr><td align=\"left\">LV ejectionfraction (%)</td><td align=\"center\">75.22 ± 4.93</td><td align=\"center\">74.86 ± 4.21</td><td align=\"center\">78.69 ± 3.01</td><td align=\"center\">78.71 ± 3.41</td></tr><tr><td align=\"left\">Left ventricular mass (g)</td><td align=\"center\">1.35 ± 0.21</td><td align=\"center\">1.22 ± 0.28</td><td align=\"center\">1.34 ± 0.17</td><td align=\"center\">1.23 ± 0.22</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>*p &lt; 0.05</p></table-wrap-foot>", "<table-wrap-foot><p>Values are mean ± SD. *p = 0.0001; †p = 0.005.</p><p>MBF = myocardial blood flow; rBV = relative blood volume;</p><p>RPP = rate-pressure product; SBP = systolic blood pressure.</p></table-wrap-foot>", "<table-wrap-foot><p>Values are mean ± SD. *p = 0.0001;</p><p>†p = 0.005. MBF = myocardial blood flow; rBV = relative blood volume; MPR = myocardial perfusion reserve</p></table-wrap-foot>", "<table-wrap-foot><p>* indicates p &lt; 0.05</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1475-2840-7-26-1\"/>", "<graphic xlink:href=\"1475-2840-7-26-2\"/>", "<graphic xlink:href=\"1475-2840-7-26-3\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The progression of Type 2 diabetes is driven by progressive <italic>β</italic>-cell dysfunction and increased insulin resistance, which results in hypoglycaemia due to difficulty of achieving glycaemic control. Typically, lifestyle modifications such as diet and exercise fail to achieve and give way to the administration of oral hypoglycaemic agents (OHAs) in order to maintain glucose control. In addition to tolerability issues for patients, the inability of OHAs to stem the decline in <italic>β</italic>-cell function [##REF##10359389##1##] commonly lead to the introduction of exogenous basal insulin to maintain normoglycaemia [##REF##15013454##2##]. Traditionally regarded as a drastic measure in Type 2 diabetes, physicians are increasingly favouring earlier introduction of basal insulin to control hyperglycaemia and minimise the associated micro- and macrovascular complications of diabetes [##REF##17890232##3##,##REF##10938048##4##]. Whilst undoubtedly clinically effective, use of insulin regimens also carries some problems, namely:</p>", "<p>• an inability to control mealtime glucose excursion [##REF##11118018##5##],</p>", "<p>• increased risk of severe hypoglycaemia [##REF##12663593##6##,##REF##16870077##7##],</p>", "<p>• the need for complicated dose-titration [##UREF##0##8##], and</p>", "<p>• weight gain [##REF##15677776##9##].</p>", "<p>Hypoglycaemia of any severity has a profound effect on patients' quality of life [##REF##16870077##7##] and is regarded as the single greatest obstacle to achieving normoglycaemia [##REF##12089099##10##]. In addition to reduced quality of life, hypoglycaemia results in substantial direct medical cost and lost productivity [##REF##16689714##11##].</p>", "<p>Insulin glargine (Lantus™) is an analogue of human insulin with a prolonged duration of action and once-daily dosing. In Type 2 diabetes, the principal emergent benefit is significantly reduced risk of all forms of hypoglycaemia over Neutral Protamine Hagedorn (NPH) [##REF##15793205##12##]. However, initiation of insulin glargine still requires careful dose titration to an appropriate level over a period of time. This is essential for successful treatment of diabetes and the avoidance of hypoglycaemia [##UREF##1##13##]. However, recent trial evidence has suggested that insulin glargine could be introduced earlier to achieve glycaemic goals [##REF##16842477##14##] and a further study showed that adding insulin glargine to OHA therapy had a positive effect on treatment satisfaction and quality of life (QoL) without complaints related to hypoglycaemia [##REF##17490781##15##]. Insulin glargine is currently not recommended by the National Institute for Health and Clinical Excellence (NICE) for routine use for people with Type 2 diabetes, but can be considered for people with Type 2 diabetes who require assistance from a third party to administer their insulin injections, who have recurrent symptomatic hypoglycaemic episodes or who would otherwise need twice-daily basal insulin injections in combination with oral antidiabetic drugs. Using their own model (based on United Kingdom Prospective Diabetes Study (UKPDS) 68 [##REF##15517152##16##]), NICE concluded that human insulin analogues are the most cost-effective option and glargine was estimated to be cost-effective in Type 2 diabetes patients at increased risk of hypoglycaemia [##UREF##2##17##]; the NICE guidelines are due to be reviewed and republished in early 2009.</p>", "<p>The incretin mimetics are emerging as a significant new class of hypoglycaemic agents that regulate glucose homeostasis similarly to endogenous glucagon-like peptide-1 (GLP-1). Exenatide (Byetta™), the first such compound to be licensed by the European Medicine Agency (EMEA) [##UREF##3##18##], enhances glucose-dependent insulin secretion, regulates glucagon release, and delays gastric emptying thereby reducing hyperglycaemia in a similar manner to GLP-1. Unlike the short-lived GLP-1, exenatide resists metabolism by dipeptidyl peptidase-IV giving it a pharmacokinetic profile suitable for chronic administration [##UREF##4##19##]. Exenatide is recommended for use in the treatment of Type 2 diabetes in combination with metformin, and/or sulphonylureas in patients who have not achieved adequate glycaemic control on maximally tolerated doses of these oral therapies and is given twice daily by subcutaneous injection. Exenatide was approved by the Scottish Medicines Consortium (SMC) in June 2007, as an adjunct therapy to patients with Type 2 diabetes who, despite currently taking metformin and/or a sulphonylurea either singly or in combination, fail to achieve adequate glycaemic control [##UREF##5##20##]. Exenatide, however, is not currently recommended by NICE for routine use for people with Type 2 diabetes [##UREF##2##17##] and should only be considered for people with Type 2 diabetes, who have a body mass index (BMI) over 35 kg/m², specific problems arising from high weight, inadequate blood glucose control (glycosylated haemoglobin (HbA_1c) &gt;7.5 %), prescribed conventional oral therapy and where other high cost therapies would otherwise be commenced. Using their own model (based on UKPDS 68 [##REF##15517152##16##]), NICE estimated that exenatide was not cost-effective in any scenario [##UREF##2##17##] and, furthermore, exenatide has been linked with occurrences of acute pancreatitis [##UREF##6##21##].</p>", "<p>The only published head-to-head randomised controlled trial (RCT) [##REF##16230722##22##] of exenatide versus glargine, reported similar improvements in the overall glycaemic control in patients with Type 2 diabetes sub-optimally controlled with combination OHAs at maximal doses. For secondary endpoints, patients treated with exenatide experienced significantly fewer nocturnal hypoglycaemic events (0.9 vs. 2.4 events per patient per year; a 63% reduction), but higher incidence of daytime hypoglycaemia (6.6 vs. 3.9 events per patient per year; a 69% increase) and achieved significant weight loss from baseline (Δ -2.3 kg), whereas insulin glargine-treated subjects gained weight of a similar magnitude (Δ +1.8 kg) by the study endpoint. The principal drawback reported in exenatide treated patients was nausea (in 57.1% of subjects) and vomiting (in 17.4%), which led to withdrawal of almost 10% of exenatide-treated patients from the study protocol. This finding is consistent with evidence from other published phase 3 placebo-controlled trials [##UREF##7##23##]. By comparison, less than 1% of those exposed to insulin glargine withdrew due to adverse events. The most common adverse event reported with insulin glargine was nasopharyngitis (in 9.0%). Within this trial setting, however, the dosage of glargine was very low with an average of 25 international units (IU)/day. This does not reflect clinical practise, where the dosage is typically 42 IU/KG [##REF##17697063##24##]. A higher dose with glargine will lead to better glycaemic control, but also more weight gain and will have an effect on hypoglycaemic events [##REF##14578243##25##,##REF##17384341##26##]. Regarding patient reported outcomes, Boye and colleagues published the patient reported outcomes measured from the same head-to-head trial [##REF##16230722##22##] and showed no significant difference in improvement of health utility or quality of life [##REF##17034640##27##].</p>", "<p>The increasing global financial burden of chronic health conditions is fuelling a rising demand for value for money when introducing new health technologies. In line with many other countries, in the United Kingdom (UK), NICE currently accepts as cost-effective, \"those interventions with an incremental cost-effectiveness ratio of less than £20,000 per QALY (quality adjusted life year) and that there should be increasingly strong reasons for accepting as cost effective interventions with an incremental cost-effectiveness ratio of over £30,000 per QALY [##UREF##8##28##].\" A recently published study of Ray et al. [##REF##17355742##29##] showed exenatide to have a cost-effectiveness ratio of £22,420 vs. insulin glargine; however, a major limitation of this study was that it used an estimated UK cost of exenatide based on the US price. The study reported exenatide as dominant (less costly and more effective) when marketed at 20% of the US price in the UK. The study of Ray et al. used cohort details from the Heine trial [##REF##16230722##22##] that were then applied to a previously published cost effectiveness model [##REF##15324513##30##], the CORE Model.</p>", "<p>The objective of this analysis was to prospectively evaluate the cost-effectiveness of exenatide from a UK NHS perspective, using insulin glargine as a comparator and the current UK NHS price for exenatide and also applying the cohort profiles and published data from the Heine trial [##REF##16230722##22##]. The model, which has been previously published [##UREF##9##31##], used to evaluate the cost-effectiveness was a discrete event simulation (DES) model for patients with Type 2 diabetes using UKPDS-derived risk functions [##REF##15517152##16##] and a multivariate regression model for the utility associated with hypoglycaemia [##REF##16870077##7##].</p>" ]

[ "<title>Methods</title>", "<title>Modelling approach and model</title>", "<p>This evaluation was undertaken within the context of the UK National Health Service (NHS), and used the NHS as its perspective (payer's perspective). The method used was a cost-utility analysis (CUA) intended to determine the cost per quality adjusted life years gained (QALYs gained) comparing exenatide to insulin glargine as adjunct therapy to maximal doses of metformin and sulphonylurea in Type 2 diabetes.</p>", "<p>The modelling approach used was a discrete event simulation (DES) model of people with Type 2 diabetes using UKPDS-derived risk functions for development of vascular complications [##REF##15517152##16##] and a multivariate regression model for the utility decrement associated with hypoglycaemia [##REF##16870077##7##]. The details of the model and its validation have been published [##UREF##10##32##], but a brief description is given below.</p>", "<p>The model simulates a cohort of 1000 subjects over a 40-year time horizon. The specific events modelled were ischaemic heart disease (IHD), myocardial infarction (MI), congestive heart failure (CHD), stroke, blindness in one eye, end stage renal disease (ESRD) and amputation, in addition to diabetes-related and all-cause mortality; furthermore, the model additionally predicts severe, nocturnal, and symptomatic hypoglycaemic events. The results presented represent an average of one hundred first order Monte Carlo simulations. The baseline characteristics of the subjects from Heine trial [##REF##16230722##22##] (Table ##TAB##0##1##) were applied and are generally consistent with the profile of insulin-treated patients with Type 2 diabetes in the UK, as older and obese (Body Mass Index (BMI) greater than 30 kg/m²).</p>", "<p>The model first simulates treatment of the cohort with basal insulin glargine plus OHAs. At the beginning of each time period, checks were made for specific fatal or non-fatal events. The order in which these events occurred was randomised. If a fatal event occurred, all costs, life years and quality adjusted life years were accumulated and the simulation ended for that individual. The simulation then selects the next individual and the process begins again. Assuming a subject does not die in any specific year then following the 'check for events' stage, a simulated subject's disease state is updated and any appropriate decrement in health utility was then applied together with associated costs. The simulation time clock is then advanced and if the end of the simulation time horizon has been reached, the simulation ended for that individual and the process starts again with the next individual. Once all individuals had been simulated, the process ends and all summary statistics are calculated for that particular run of the model.</p>", "<p>The second run of the model for treatment with exenatide plus OHAs utilised exactly the same patient cohort data as the first run but applied the alternative treatment effects and costs (Table ##TAB##1##2##). After applying any differential effects to the patient data, the model was then re-initialised and run through in exactly the same manner as for the first run.</p>", "<title>Effectiveness</title>", "<p>Three significant endpoints emerged from the Heine trial [##REF##16230722##22##] which were included in the model as treatment effects. Overall, patients in the exenatide group had a higher rate of hypoglycaemic events then patients in the insulin glargine group (7.3 events/patient-year vs. 6.3 events/patient-year). Nocturnal hypoglycaemia was 63% lower in the exenatide group than the insulin glargine group (0.9 events/patient-year vs. 2.4 events/patient-year), but patients in the exenatide group had a 69% higher incidence of daytime hypoglycaemia than patients the insulin glargine group (6.6 events/patient-year vs. 3.9 events/patient-year). No differences in severe hypoglycaemia were recorded and therefore the model was run using previously published rates [##REF##12663593##6##].</p>", "<p>At the 26-week trial endpoint average patient weight was 4.1 kg lower in the exenatide group compared to the insulin glargine group. For each group, change in weight (kg) over time (weeks) had begun to plateau by the study endpoint, a pattern echoed by the long-term extension trials of exenatide [##UREF##7##23##]. Thus, this difference was conservatively applied as the maximum weight improvement for exenatide patients. Differential levels of HbA_1cwere not modelled as the trial showed no significant difference in glycaemic control between insulin glargine and exenatide.</p>", "<p>Finally, discontinuation rates due to adverse events (Δ 8.9% of intention-to-treat (ITT) patients) were modelled using three approaches: either completely ignored; exenatide-discontinuations removed from analysis; and exenatide discontinuations switched to insulin glargine.</p>", "<title>Estimates of financial costs</title>", "<p>The financial costs applied to the simulation model are detailed in Table ##TAB##2##3##, and summarised as follows. Costs of medical treatment were obtained from UK sources and were indexed to year 2007 with UK Treasury rates [##UREF##10##32##].</p>", "<p><bold>Treatment and comparator </bold>Insulin glargine cost was calculated on a per kilogram basis, costed at the current UK weighted average wholesale prices for Lantus across the different preparations [##UREF##11##33##] to reflect the UK market. A 0.28 IU/kg/day dose regimen was assumed for insulin glargine, based on the average daily requirement reported at the study endpoint [##REF##16230722##22##]. In common with the Heine trial protocol [##REF##16230722##22##], where daily glucose monitoring was not required for patients assigned to receive exenatide, the additional cost of one reagent tests strip and one lancet per day was applied. In each case, the weighted average cost was derived from the 2006 Department of Health (DOH) Prescription Cost Analysis [##UREF##12##34##]. As neither blood glucose testing meters nor finger-pricking devices are available on the NHS, they did not represent a cost to the health payer and were excluded from the analysis. The exenatide treatment cost was estimated using the UK market launch price [##UREF##13##35##]. 5 microgram twice daily (BD) was assumed for initiation for a month and after this a 10 microgram BD maintenance dose, this follows the NHS recommendations [##UREF##14##36##]. In both the insulin glargine and exenatide simulated cohorts the cost of metformin and gliclazide (representing 1^stline sulphonyureas) administered were modelled at their respective maximum daily dosages [##UREF##11##33##]. The model assumes these first line therapies are well tolerated to the maximum dose and patient management will typically involve titrating to the maximum daily dose and then subsequent therapy will be added to this and titrated appropriately.</p>", "<p><bold>Macrovascular event costs </bold>Macrovascular event costs are split into either fatal or non-fatal costs and were applied in the year in which the event occurred. Maintenance costs for those subjects surviving were applied in all subsequent years until either the end of the simulation time horizon or until the subject died.</p>", "<p><bold>Blindness (in one eye) </bold>Subjects were assumed to incur blindness in one eye only. The initial cost related to the event was assumed to be equal to zero, with subsequent maintenance costs applied annually thereafter from published data [##REF##12659641##37##].</p>", "<p><bold>Nephropathy </bold>Dialysis costs were annual weighted mean costs for peritoneal dialysis (£15,534; 71%) and haemodialysis (£33,516; 29%) [##REF##18174268##38##].</p>", "<p><bold>Peripheral vascular disease </bold>was modelled as the occurrence of an amputation and had a single cost associated with the event and a subsequent annual maintenance cost.</p>", "<p><bold>Severe hypoglycaemia </bold>costs are applied to severe hypoglycaemia events only and are based on the costs of hospitalised treatment reported in Tayside, UK. The Diabetes Control and Complications Trial (DCCT), estimated that 20% of all severe hypoglycaemic episodes result in a hospital intervention, either emergency room attendance or inpatient hospitalization. The most comprehensive data relating to treatment modality of severe hypoglycaemic episodes is reported by Leese et al. [##REF##12663593##6##], from their observational study of registered diabetics in Tayside, Scotland, UK. In this study, 34% of severe hypoglycaemia episodes were managed by an ambulance attendance, 46% by accident &amp; emergency (A&amp;E) consultation, and the remaining 20% were hospitalized as inpatients, representing 5% of all estimated severe hypoglycaemia (hospitalized or not) for this population. Over the 12-month study period, Leese et al report 244 episodes totalling £92,078 of healthcare resources, some £377.37 per episode. Given this represents only a fifth of all severe episodes [##REF##8366922##39##], the average known cost across all episodes in 1998 (year of Leese' data collection) is estimated to be £75.47. Indexed to 2007, the average cost of treating all DCCT-defined severe hypoglycaemia is £93.85.</p>", "<title>Health-related utility</title>", "<p>Utility estimates were taken from either the UKPDS study [##REF##15517152##16##], or generated via the Health Outcomes Data Repository (HODaR) database [##REF##16176496##40##,##REF##16307698##41##]. The utility decrements associated with each specified event have been specified previously [##UREF##9##31##] and are shown in Table ##TAB##3##4##. The model assumes that multiple diabetes related complications have an additive effect on utility; that is, the combined utility decrement for a person experiencing both an MI and stroke event would be the sum of the two individual utility values. The same utility decrement was applied in years subsequent to the year in which the event occurred. Utility associated with hypoglycaemia events is handled somewhat differently. Statistical models were developed that related the frequency and severity of hypoglycaemia to fear of hypoglycaemia, and subsequently to changes in health-related utility [##REF##16870077##7##]. The relationship between hypoglycaemia and utility was modelled using a two stage approach in which equations were derived describing the relationship between hypoglycaemia and the fear of hypoglycaemia (measured via the Hypoglycaemia Fear Score (HFS)). Subsequently the relationship between changes in HFS was related to health utility, measured using the EQ5D [##REF##10109801##42##]. The equations showed that the marginal effects of the occurrence of at least one severe hypoglycaemic episode was associated with a 5.881 change in HFS score and that unit changes in the natural log of the number of symptomatic events and the square root of the number of nocturnal events was associated with a 1.773 and 1.054 change in the HFS score respectively. Each unit increase in HFS was associated with a utility of decrement of 0.008 (for severe and symptomatic) and 0.007 for nocturnal hypoglycaemia. The disutility associated with the fear of hypoglycaemia is applied throughout each simulated year if a hypoglycaemic event occurs; if simulated patients do not experience an event then no disutility is applied. Hypoglycaemia is the only adverse event accommodated in the model; the analysis does not model complications such as acute pancreatitis and therefore is somewhat conservative with respect to glargine.</p>", "<p>Important differences exist between exenatide and glargine that may also affect quality of life; in particular, changes in weight and a different side effect profile. A number of studies have shown exenatide to be associated with weight reduction [##REF##15504997##43##,##REF##15855572##44##] whilst insulin is associated with weight gain [##REF##9614608##45##,##REF##15315867##46##]. Furthermore, exenatide has been shown to have more frequent gastrointestinal side effects. A number of studies have reported changes in utility associated with changes in weight (or more specifically, BMI). Importantly, these studies are cross-sectional in design and do not capture changes in utility associated with an individuals' experience of their own weight loss/gain and, therefore, the application of such utility gains may overstate the effects of weight change. This view is corroborated by results from a randomised trial comparing patient reported outcomes in 549 subjects randomised to either insulin glargine or exenatide. Despite expected differences in weight change, side effect profile and dosing frequency, insulin glargine patients exhibited a non-significant increase in EQ5D compared patients receiving exenatide (0.03 versus 0.02 utility gain, p = 0.35) [##REF##17034640##47##].</p>", "<p>The results presented here did not accommodate any utility changes associated with gastrointestinal side effects or weight change. Furthermore, consistent with longitudinal studies assessing health utility and insulin initiation, no utility decrement was applied to therapy type [##REF##10388978##48##].</p>", "<title>Other economic analysis details</title>", "<p>All prices are all adjusted to 2007 values (UK£) using the UK Treasury gross domestic product (GDP) deflator formula [##UREF##10##32##]. Where necessary, costs and benefits were discounted at 3.5% per year in accordance with current NICE guidance [##UREF##8##28##].</p>" ]

[ "<title>Results</title>", "<title>Number of end points forecast in each arm</title>", "<p>The model was designed to output the frequency (per 1,000 patients) in each of a range of pertinent vascular events and mortality that are listed in Table ##TAB##4##5## for the three main scenarios.</p>", "<title>Ignoring discontinuation rates</title>", "<p>In the first scenario where no exenatide treatment discontinuations was considered, there was an overall difference of 21,359 nocturnal episodes of hypoglycaemia, in favour of exenatide, but 38,808 more daytime episodes of hypoglycaemia for patients treated with exenatide. Overall 24.5 severe hypoglycaemic events were predicted for patients treated with exenatide. The biggest difference in vascular endpoints occurred for congestive heart failure (CHF), where use of exenatide results in 7.7 fewer events on average; this difference being driven by the improved BMI profile associated with exenatide.</p>", "<title>Removing patients discontinuing from the analysis</title>", "<p>With exenatide treatment discontinuations excluded from the analysis, the number of clinical endpoints predicted are fewer in the exenatide group (with the exception of daytime hypoglycaemic events); however, this observation is due to fewer patients available in the model to experience clinical endpoints.</p>", "<title>Switching patients discontinuing exenatide to insulin glargine</title>", "<p>Switching exenatide discontinuations to insulin glargine produces similar results to ignoring discontinuation rates altogether. The number of nocturnal hypoglycaemic events with exenatide reduces to 19,465 and the number of additional daytime hypoglycaemic events increases by 35,402. The number of expected CHF events avoided with exenatide is 6.87 when compared with insulin glargine. Under these conditions, mortality due to macrovascular events is still favourable to exenatide with 4.0 deaths avoided, but this scenario is the least positive result to exenatide compared with 4.7 macrovascular deaths saved in the baseline scenario and 43.0 macrovascular deaths saved when exenatide treatment failures are excluded.</p>", "<title>Total costs and QALYS forecast in each arm</title>", "<p>Applying the current UK price of exenatide, total treatment costs over the simulation period associated with exenatide use were significantly higher than for insulin glargine. Ignoring discontinuations rates resulted in the discounted total costs (per 1,000 patients) of £14,567,526 and £9,280,312 for exenatide and insulin glargine, respectively (Δ ≈ £5.3 M, Table ##TAB##4##5##). The total and difference in quality adjusted life years (QALYs) is also listed in Table ##TAB##4##5##; with 160 fewer QALYs associated with exenatide. Although there were fewer nocturnal hypoglycaemic events associated with exenatide, their contribution to improving quality of life was offset by higher daytime events and overall higher severe hypoglycaemic events when compared to insulin glargine. Using the current multivariate hypoglycaemia model each nocturnal hypoglycaemic event results in a 0.68% decrement in utility, whereas one severe hypoglycaemic event leads to a 4.40% utility decrement [##REF##16870077##7##].</p>", "<title>Incremental cost effectiveness ratios</title>", "<p>Under the no discontinuation scenario, the mean incremental cost effectiveness ratio (ICER) was-£29,149 per QALY gained, with insulin glargine being less costly and more effective than exenatide. Under the most conservative scenario of excluding exenatide failures, the dominance of insulin glargine persisted with a mean ICER of -£4,579 per QALY gained. The scenario where exenatide failures were switched to insulin glargine produced similar results with insulin glargine remaining cheaper and more effective than exenatide (mean ICER of -£29,657 per QALY gained).</p>", "<title>Sensitivity analysis</title>", "<p>As a sensitivity analysis, the input factors for the model were varied to reflect long term outcomes and clinical practice for glargine and exenatide. Open label extension of exenatide trials showed that the glycaemic control in the long term was similar to the effect shown in the Heine trial. However weight reduction was continuing up to a maximum of 5.3 kg over 3 years. There was no evidence of the rate of hypoglycaemic events in published the open label extensions [##REF##17379054##49##, ####REF##16776751##50##, ##REF##16776749##51####16776749##51##]. Glargine studies applying a more clinically relevant dosage scenario – on average a dose of 53 IU/day – showed that glycaemic control could be more improved than shown in the Heine trial; on average a further reduction of 0.65% in HbA_1c. On the other hand weight increased on average by 3.0 kg and nocturnal hypoglycaemic events increased on average to 3.55 events/patient-year and symptomatic events on average to 5.65 events/patient-year. Using the same hypoglycaemic rates for exenatide as reported in the Heine trial, the nocturnal hypoglycaemia rate would be 75% lower in the exenatide group than the insulin glargine group, and incidence of daytime hypoglycaemia would be 17% higher in the exenatide group than in the insulin glargine group. Applying this evidence of glycaemic control, weight control and dosage to the model showed that exenatide in comparison to glargine was still estimated to be more costly and a less effective option with a cost-effectiveness ratio of £6,365 (glargine dominant). Using the evidence of increased hypoglycaemic events when using a higher dosage of glargine the results were similar and exenatide in comparison to glargine was still estimated to be more costly and a less effective option with a cost-effectiveness ratio of £6,884 (glargine dominant). The complete results of the two sensitivity scenarios are shown in Table ##TAB##5##6##.</p>" ]

[ "<title>Discussion</title>", "<p>For this analysis, a previously published UK diabetes Type 2 model was used to evaluate the introduction of exenatide in patients with sub-optimally controlled Type 2 diabetes to the UK NHS. As a comparator, insulin glargine, a long-acting once daily human insulin analogue, was chosen. The results of the study reflect the long-term projection of the findings of the Heine trial [##REF##16230722##22##]. Using the baseline profiles and treatment effects outlined here the economic evaluation conducted found that insulin glargine dominated exenatide.</p>", "<p>A recently published study of Ray et al. [##REF##17355742##29##] evaluating the cost-effectiveness of exenatide vs. insulin glargine using the same input from the Heine trial [##REF##16230722##22##] showed different results to our findings. Ray et al. demonstrated that exenatide has a cost-effectiveness ratio of £22,420 vs. insulin glargine at an estimated 100% US price. Furthermore, it was estimated that exenatide is dominant (cost and QALY saving), when marketed at 20% of the US price in the UK. A cost-effectiveness ratio below the recommended £20,000/QALY [##UREF##8##28##] was achieved at 80% of the US price, which approximately equals the current UK market price. Using the same Heine trial data [##REF##16230722##22##] as utilised in this study, Ray et al. [##REF##17355742##29##] estimated that exenatide is a cost-effective treatment option in patients with sub-optimally controlled Type 2 diabetes in the UK. Ray et al. [##REF##17355742##29##] modelled their baseline scenario (100% US price) over a time horizon of 35 years and reported higher direct medical costs for exenatide and insulin glargine £29,401 and £19,489 per patient respectively) and higher QALYs (14.62 and 14.51 per patient respectively) than we derived in our analyses for exenatide and insulin glargine (cost: (£14,568 and £9,280 per patient respectively; QALYs: 7.68 and 7.86 per patient respectively) using a time horizon of 40 years. Both studies showed that lifetime medical costs are higher for patients with exenatide and insulin glargine and Ray et al.'s [##REF##17355742##29##] estimate was much higher over a shorter time period than ours.</p>", "<p>The main difference between the outcomes reported by Ray et al. [##REF##17355742##29##] and our own study were the QALY estimates with Ray et al. [##REF##17355742##29##] estimating a QALY gain for patients treated with exenatide, while our analysis showed a QALY gain for patients treated with insulin glargine. Reviewing the input factors for the model of Ray et al. [##REF##17355742##29##] showed that the authors used more evidence from the Heine trial [##REF##16230722##22##] in favour of exenatide than we used in our study. While there is clear evidence for a difference in hypoglycaemic events, weight loss and patients with nausea, there was no clear evidence of any significant difference in other factors favouring exenatide. Ray et al. [##REF##17355742##29##] included lower systolic blood pressure (SBP), lower total cholesterol (TC), lower low-density lipoprotein (LDL) and lower triglycerides in patients treated with exenatide. These risk factors are influential predictors of future diabetes-related complications and improvements reported in the Heine trial [##REF##16230722##22##] were non-significant. We did not see this as evidence for a significant treatment effect and therefore did not include these in our model. As outlined in the methods section, we did not include disutility associated with weight gain, gastrointestinal side effects or insulin initiation. The justification for this approach being the analysis of patient reported outcomes in a head to head comparison of exenatide and glargine. Furthermore, while cross sectional studies have demonstrated a disutility of insulin use compared to oral agents [##REF##15386666##52##], prospective longitudinal studies have shown that insulin therapy does not impact on quality of life [##REF##11182217##53##].</p>", "<p>The major drawback of the Heine trial [##REF##16230722##22##] was that the dosing of glargine did not reflect clinical practice. Within the trial design, the dosing of glargine was very low, with an average of 25 IU/day. A higher dose of glargine naturally leads to improved glycaemic control, but also more weight gain and, potentially, hypoglycaemic events. Our sensitivity analyses showed that applying long term data to the exenatide arm and a more clinically relevant dosing scenario for glargine produced results consistent with the base case findings.</p>", "<p>As with all modelling simulations, our economic evaluation has a number of strengths and weaknesses. The model can only be as reliable as the predictive algorithms and other data that were used in its construction. The model was based on contemporary data largely drawn from the same source – the United Kingdom Prospective Diabetes Study; however, the dependence of our findings on the UKPDS model is not without drawbacks. In particular, the UKPDS outcomes model does not completely capture the complexities of all diabetes related complications. For example, complications such as peripheral neuropathy, ulceration, gross proteinuria or proliferative retinopathy and macular oedema are handled crudely, primarily due to insufficient patient numbers experiencing these events in the UKPDS study. This is largely due to the inclusion criteria of the UKPDS study in which patients were newly diagnosed with Type 2 diabetes with no pre-existing cardiovascular complications. Type 2 diabetes, however, is primarily characterised by macrovascular complications and the equations published from this study represent a robust approach to describing the relationship between the major complications occurring in Type 2 diabetes and modifiable risk factors. No modelled economic evaluation can ever provide point estimates that are demonstrably precise; nevertheless, the fact that exenatide is significantly more costly than insulin glargine, but provides only marginal benefits with respect to BMI provides some degree of confidence that the conclusions presented here are reliable.</p>", "<p>This study strictly applied those statistically significant differences between exenatide and insulin glargine emergent reported by Heine et al [##REF##16230722##22##]. Although not necessarily an accurate prediction of the performance of exenatide in day-to-day practice, it is, nevertheless, consistent with NICE economic modelling guidance [##UREF##8##28##], and therefore appropriate. The study did not include utility estimates regarding weight changes and adverse events due to treatment. Published utility data related to weight changes are not well reported, but preliminary analyses of HODaR data [##REF##16176496##40##], including longitudinal weight and utility data suggested that utility changes start to become significant if a patient gains/loses a great amount of weight (&gt;5 kg) and it is dependent on the initial weight (the higher the BMI the more likely the patient benefit from weight loss). Certain other factors not reported by the Heine trial [##REF##16230722##22##] could also have had an impact on these outcomes. For example, what was the utility decrement associated with nausea and vomiting in the exenatide group? Did the significant weight loss among exenatide-treated subjects improve utility, in spite of gastro-intestinal symptoms, and was the weight loss a result of nausea, pancreatic and other gastro oesophageal problems? How did lipid profiles change as a result of weight loss experienced in the exenatide arm? At the time of writing, these data are not available in the public domain but, in their absence, it is reasonable to conservatively assume there were no significant differences between the groups otherwise they would presumably have been reported in the trial-related publication.</p>" ]

[ "<title>Conclusion</title>", "<p>This study could have a number of implications for policy makers. Given therapeutic equivalence of exenatide and insulin glargine concerning glycaemic control it is likely that a forthcoming NICE appraisal of exenatide possibly would apply the lower £20,000 threshold. This economic evaluation showed that glargine, when used in the treatment of Type 2 diabetes patients, was dominant in comparison to exenatide. Maintaining the current UK price difference between insulin glargine and exenatide, the recommendation of exenatide should be considered cautiously as a cost-effective alternative to insulin glargine for tertiary treatment of Type 2 diabetes given the evidence present for exenatide.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Objective</title>", "<p>Exenatide belongs to a new therapeutic class in the treatment of diabetes (incretin mimetics), allowing glucose-dependent glycaemic control in Type 2 diabetes. Randomised controlled trial data suggest that exenatide is as effective as insulin glargine at reducing HbA_1cin combination therapy with metformin and sulphonylureas; with reduced weight but higher incidence of adverse gastrointestinal events. The objective of this study is to evaluate the cost effectiveness of exenatide versus insulin glargine using RCT data and a previously published model of Type 2 diabetes disease progression that is based on the United Kingdom Prospective Diabetes Study; the perspective of the health-payer of the United Kingdom National Health Service.</p>", "<title>Methods</title>", "<p>The study used a discrete event simulation model designed to forecast the costs and health outcome of a cohort of 1,000 subjects aged over 40 years with sub-optimally-controlled Type 2 diabetes, following initiation of either exenatide, or insulin glargine, in addition to oral hypoglycaemic agents. Sensitivity analysis for a higher treatment discontinuation rate in exenatide patients was applied to the cohort in three different scenarios; (1) either ignored or (2) exenatide-failures excluded or (3) exenatide-failures switched to insulin glargine. Analyses were undertaken to evaluate the price sensitivity of exenatide in terms of relative cost effectiveness. Baseline cohort profiles and effectiveness data were taken from a published randomised controlled trial.</p>", "<title>Results</title>", "<p>The relative cost-effectiveness of exenatide and insulin glargine was tested under a variety of conditions, in which insulin glargine was dominant in all cases. Using the most conservative of assumptions, the cost-effectiveness ratio of exenatide vs. insulin glargine at the current UK NHS price was -£29,149/QALY (insulin glargine dominant) and thus exenatide is not cost-effective when compared with insulin glargine, at the current UK NHS price.</p>", "<title>Conclusion</title>", "<p>This study evaluated the relative cost effectiveness of insulin glargine versus exenatide in the management of Type 2 diabetes using a published model. Given no significant difference in glycaemic control and applying the additional effectiveness of exenatide over insulin glargine, with respect to weight loss, and using the current UK NHS prices, insulin glargine was found to be dominant over exenatide in all modelled scenarios. With current clinical evidence, exenatide does not appear to represent a cost-effective treatment option for patients with Type 2 diabetes when compared to insulin glargine.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>PMc conceived the study. AW and TT prepared the model. All authors contributed to the design of the protocol. AW drafted the manuscript. All authors have read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors acknowledge the assistance of Christopher Morgan and Andrea Longman for help in preparing the manuscript for submission.</p>", "<p>This study was funded by Sanofi-Aventis UK, the manufacturer of insulin glargine.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Baseline patient characteristics.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Variable</td><td align=\"center\">Type 2 diabetes</td></tr></thead><tbody><tr><td align=\"left\">Age (years)^†</td><td align=\"center\">59</td></tr><tr><td align=\"left\">Gender (% male)^†</td><td align=\"center\">56%</td></tr><tr><td align=\"left\">BMI (kg/m²)^†</td><td align=\"center\">31.9</td></tr><tr><td align=\"left\">Weight (kg)^†</td><td align=\"center\">89.8</td></tr><tr><td align=\"left\">Height (metres)^†</td><td align=\"center\">1.67</td></tr><tr><td align=\"left\">Ethnicity (% black)^†</td><td align=\"center\">1%</td></tr><tr><td align=\"left\">Total cholesterol (mmol/L)^‡</td><td align=\"center\">5.2</td></tr><tr><td align=\"left\">HDL cholesterol (mmol/L)^‡</td><td align=\"center\">1.04</td></tr><tr><td align=\"left\">Systolic blood pressure (mmHg)^‡</td><td align=\"center\">136</td></tr><tr><td align=\"left\">HbA_1c(%)^†</td><td align=\"center\">7.1</td></tr><tr><td align=\"left\">Peripheral vascular disease (%)^‡</td><td align=\"center\">30%</td></tr><tr><td align=\"left\">Smoking (%)^‡</td><td align=\"center\">0</td></tr><tr><td align=\"left\">Risk of severe hypoglycaemia*</td><td align=\"center\">0.462</td></tr><tr><td align=\"left\">Number of nocturnal hypos (year)^†</td><td align=\"center\">2.4</td></tr><tr><td align=\"left\">Number of symptomatic hypos (year)^†</td><td align=\"center\">6.8</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Treatment and comparator costs applied in the model.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Description</bold></td><td align=\"right\"><bold>Cost</bold></td><td align=\"right\"><bold>Source</bold></td></tr></thead><tbody><tr><td align=\"left\"><italic>Insulin glargine group</italic></td><td/><td/></tr><tr><td align=\"left\"> price per 1000 IUs</td><td align=\"right\">£26.00</td><td align=\"right\">BNF No. 55[##UREF##11##33##]</td></tr><tr><td align=\"left\"> Glucose test strip</td><td align=\"right\">£0.302</td><td align=\"right\">2006 DoH Prescription Cost Analysis[##UREF##12##34##]</td></tr><tr><td align=\"left\"> Lancet</td><td align=\"right\">£0.055</td><td align=\"right\">2006 DoH Prescription Cost Analysis[##UREF##12##34##]</td></tr><tr><td align=\"left\"><italic>Exenatide group</italic></td><td/><td/></tr><tr><td align=\"left\"> 10 ug BD, per 28 days</td><td align=\"right\">£68.24</td><td align=\"right\">BNF No. 55[##UREF##13##35##]</td></tr><tr><td align=\"left\"><italic>Both groups</italic></td><td/><td/></tr><tr><td align=\"left\"> Metformin per day<break/> (500 mg QDS)</td><td align=\"right\">£0.21</td><td align=\"right\">BNF No. 55[##UREF##11##33##]</td></tr><tr><td align=\"left\"> Gliclazide per day<break/> (320 mg per day)</td><td align=\"right\">£0.25</td><td align=\"right\">BNF No. 55[##UREF##11##33##]</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Event, Maintenance and therapy costs (indexed to £UK 2007)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Variable</bold></td><td align=\"right\"><bold>Cost</bold></td><td align=\"left\"><bold>Source</bold></td></tr></thead><tbody><tr><td align=\"left\">Ischaemic Heart Disease, fatal event</td><td align=\"right\">£0</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Ischaemic Heart Disease, Non-fatal event</td><td align=\"right\">£2,388</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Ischaemic Heart Disease, Maintenance</td><td align=\"right\">£601</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Myocardial Infarction, Fatal event</td><td align=\"right\">£1,404</td><td align=\"left\">UKPDS Study No 65†</td></tr><tr><td align=\"left\">Myocardial Infarction, Non-fatal event</td><td align=\"right\">£4,961</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Myocardial Infarction, Maintenance</td><td align=\"right\">£566</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Congestive Heart Failure, Fatal event</td><td align=\"right\">£0</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Congestive Heart Failure, Non fatal event</td><td align=\"right\">£2,707</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Congestive Heart Failure, Maintenance</td><td align=\"right\">£769</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Stroke, Fatal event</td><td align=\"right\">£4,124</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Stroke, Non-fatal event</td><td align=\"right\">£2,885</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Stroke, Maintenance</td><td align=\"right\">£304</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Blindness, Event</td><td align=\"right\">0</td><td align=\"left\">O'Brien et al. [##REF##12659641##37##]</td></tr><tr><td align=\"left\">Blindness, Maintenance</td><td align=\"right\">£1,013</td><td align=\"left\">O'Brien et al. [##REF##12659641##37##]</td></tr><tr><td align=\"left\">Dialysis, Event and Maintenance</td><td align=\"right\">£20,049</td><td align=\"left\">Baboolal et al. [##REF##18174268##38##]</td></tr><tr><td align=\"left\">Amputation, Fatal event</td><td align=\"right\">£10,311</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Amputation, Non-fatal event</td><td align=\"right\">£10,311</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Amputation, Maintenance</td><td align=\"right\">£366</td><td align=\"left\">UKPDS Study No.65†</td></tr><tr><td align=\"left\">Hypoglycaemia, Event</td><td align=\"right\">£93.85</td><td align=\"left\">Leese GP et al. [##REF##12663593##6##]; DCCT hypoglycaemia report*</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Clinical endpoints modelled and utility decrements applied</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Health state</bold></td><td align=\"right\"><bold>Utility</bold></td><td align=\"left\"><bold>Source</bold></td></tr></thead><tbody><tr><td align=\"left\">Ischaemic Heart Disease</td><td align=\"right\">-0.09</td><td align=\"left\">UKPDS Study No.68[##REF##15517152##16##]</td></tr><tr><td align=\"left\">Myocardial Infarction</td><td align=\"right\">-0.055</td><td align=\"left\">UKPDS Study No.68[##REF##15517152##16##]</td></tr><tr><td align=\"left\">Congestive Heart Failure</td><td align=\"right\">-0.108</td><td align=\"left\">UKPDS Study No.68[##REF##15517152##16##]</td></tr><tr><td align=\"left\">Stroke</td><td align=\"right\">-0.164</td><td align=\"left\">UKPDS Study No.68[##REF##15517152##16##]</td></tr><tr><td align=\"left\">Blindness in one eye</td><td align=\"right\">-0.074</td><td align=\"left\">UKPDS Study No.68[##REF##15517152##16##]</td></tr><tr><td align=\"left\">ESRD</td><td align=\"right\">-0.305</td><td align=\"left\">Lee et al. [##REF##10109801##42##]</td></tr><tr><td align=\"left\">Amputation</td><td align=\"right\">-0.28</td><td align=\"left\">UKPDS Study No.68[##REF##15517152##16##]</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>The forecast frequency of vascular endpoints and cost-effectiveness using insulin glargine or exenatide per 1,000 patients over 40 years under the three discontinuation scenarios.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\"><bold>No discontinuation</bold></td><td align=\"center\" colspan=\"3\"><bold>Failures excluded</bold></td><td align=\"center\" colspan=\"3\"><bold>Failures switched</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td/><td align=\"left\"><bold>Exenatide</bold></td><td align=\"left\"><bold>Glargine</bold></td><td align=\"left\"><bold>Δ</bold></td><td align=\"left\"><bold>Exenatide</bold></td><td align=\"left\"><bold>Glargine</bold></td><td align=\"left\"><bold>Δ</bold></td><td align=\"left\"><bold>Exenatide</bold></td><td align=\"left\"><bold>Glargine</bold></td><td align=\"left\"><bold>Δ</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Macrovascular</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Ischaemic Heart Disease</td><td align=\"left\">122.2</td><td align=\"left\">121.2</td><td align=\"left\"><italic>-1.06</italic></td><td align=\"left\">111.1</td><td align=\"left\">121.4</td><td align=\"left\"><italic>10.32</italic></td><td align=\"left\">121.8</td><td align=\"left\">121.4</td><td align=\"left\"><italic>-0.36</italic></td></tr><tr><td align=\"left\">Myocardial Infarction</td><td align=\"left\">387.4</td><td align=\"left\">388.2</td><td align=\"left\"><italic>0.82</italic></td><td align=\"left\">351.9</td><td align=\"left\">387.7</td><td align=\"left\"><italic>35.79</italic></td><td align=\"left\">386.1</td><td align=\"left\">387.7</td><td align=\"left\"><italic>1.61</italic></td></tr><tr><td align=\"left\">Congestive heart Failure</td><td align=\"left\">84.9</td><td align=\"left\">92.6</td><td align=\"left\"><italic>7.68</italic></td><td align=\"left\">77.7</td><td align=\"left\">92.3</td><td align=\"left\"><italic>14.59</italic></td><td align=\"left\">85.4</td><td align=\"left\">92.3</td><td align=\"left\"><italic>6.87</italic></td></tr><tr><td align=\"left\">Stroke</td><td align=\"left\">98.9</td><td align=\"left\">99.7</td><td align=\"left\"><italic>0.74</italic></td><td align=\"left\">90.1</td><td align=\"left\">98.3</td><td align=\"left\"><italic>8.19</italic></td><td align=\"left\">99.2</td><td align=\"left\">98.3</td><td align=\"left\"><italic>-0.89</italic></td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Microvascular</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Retinopathy</td><td align=\"left\">55.5</td><td align=\"left\">55.4</td><td align=\"left\"><italic>-0.03</italic></td><td align=\"left\">50.7</td><td align=\"left\">55.4</td><td align=\"left\"><italic>4.73</italic></td><td align=\"left\">55.3</td><td align=\"left\">55.4</td><td align=\"left\"><italic>0.11</italic></td></tr><tr><td align=\"left\">Nephropathy</td><td align=\"left\">14.1</td><td align=\"left\">13.8</td><td align=\"left\"><italic>-0.29</italic></td><td align=\"left\">12.7</td><td align=\"left\">14.1</td><td align=\"left\"><italic>1.41</italic></td><td align=\"left\">14.1</td><td align=\"left\">14.1</td><td align=\"left\"><italic>-0.01</italic></td></tr><tr><td align=\"left\">Neuropathy</td><td align=\"left\">12.9</td><td align=\"left\">12.9</td><td align=\"left\"><italic>0.04</italic></td><td align=\"left\">11.8</td><td align=\"left\">12.9</td><td align=\"left\"><italic>1.13</italic></td><td align=\"left\">13.1</td><td align=\"left\">12.9</td><td align=\"left\"><italic>-0.14</italic></td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Hypoglycaemia events</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Nocturnal</td><td align=\"left\">12901.2</td><td align=\"left\">34259.8</td><td align=\"left\"><italic>21358.6</italic></td><td align=\"left\">11754.3</td><td align=\"left\">34269.6</td><td align=\"left\"><italic>22515.3</italic></td><td align=\"left\">14804.9</td><td align=\"left\">34269.6</td><td align=\"left\"><italic>19464.7</italic></td></tr><tr><td align=\"left\">Symptomatic</td><td align=\"left\">94479.7</td><td align=\"left\">55672.2</td><td align=\"left\"><italic>-38807.5</italic></td><td align=\"left\">86080.9</td><td align=\"left\">55688.1</td><td align=\"left\"><italic>-30392.8</italic></td><td align=\"left\">91090.4</td><td align=\"left\">55688.1</td><td align=\"left\"><italic>-35402.3</italic></td></tr><tr><td align=\"left\">Severe</td><td align=\"left\">6622.0</td><td align=\"left\">6597.5</td><td align=\"left\"><italic>-24.5</italic></td><td align=\"left\">6036.2</td><td align=\"left\">6598.1</td><td align=\"left\"><italic>561.9</italic></td><td align=\"left\">6626.2</td><td align=\"left\">6598.1</td><td align=\"left\"><italic>-28.2</italic></td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Fatal</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Macrovascular</td><td align=\"left\">453.5</td><td align=\"left\">458.2</td><td align=\"left\"><italic>4.68</italic></td><td align=\"left\">412.8</td><td align=\"left\">457.3</td><td align=\"left\"><italic>44.53</italic></td><td align=\"left\">453.3</td><td align=\"left\">457.282</td><td align=\"left\"><italic>4.008</italic></td></tr><tr><td align=\"left\">Microvascular</td><td align=\"left\">12.7</td><td align=\"left\">12.7</td><td align=\"left\"><italic>-0.02</italic></td><td align=\"left\">11.6</td><td align=\"left\">12.8</td><td align=\"left\"><italic>1.18</italic></td><td align=\"left\">12.9</td><td align=\"left\">12.752</td><td align=\"left\"><italic>-0.154</italic></td></tr><tr><td align=\"left\">Other</td><td align=\"left\">532.8</td><td align=\"left\">528.1</td><td align=\"left\"><italic>-4.68</italic></td><td align=\"left\">486.0</td><td align=\"left\">529.0</td><td align=\"left\"><italic>42.99</italic></td><td align=\"left\">532.8</td><td align=\"left\">529.0</td><td align=\"left\"><italic>-3.845</italic></td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Cost effectiveness</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Discounted costs</td><td align=\"left\">£14,567,526</td><td align=\"left\">£9,280,312</td><td/><td align=\"left\">£13,255,912</td><td align=\"left\">£9,296,371</td><td/><td align=\"left\">£14,092,624</td><td align=\"left\">£9,296,371</td><td/></tr><tr><td align=\"left\">Discounted QALYS</td><td align=\"left\">7,683</td><td align=\"left\">7,864</td><td/><td align=\"left\">7,000</td><td align=\"left\">7,865</td><td/><td align=\"left\">7,703</td><td align=\"left\">7,865</td><td/></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\"><bold>ICER (£/QALY)</bold></td><td align=\"center\" colspan=\"3\"><bold>Dominant (-£29,149)</bold></td><td align=\"center\" colspan=\"3\"><bold>Dominant (-£4,579)</bold></td><td align=\"center\" colspan=\"3\"><bold>Dominant (-£29,657)</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>Sensitivity analysis for the forecast of frequency of vascular endpoints and cost-effectiveness using insulin glargine or exenatide per 1,000 patients over 40 years (no discontinuation scenario).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\"><bold>Long term scenario</bold><break/><bold> (without hypoglycaemia risk change)</bold></td><td align=\"center\" colspan=\"3\"><bold>Long term scenario</bold><break/><bold> (with hypoglycaemia risk change)</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td/><td align=\"left\"><bold>Exenatide</bold></td><td align=\"left\"><bold>Glargine</bold></td><td align=\"left\"><bold>Δ</bold></td><td align=\"left\"><bold>Exenatide</bold></td><td align=\"left\"><bold>Glargine</bold></td><td align=\"left\"><bold>Δ</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Macrovascular</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Ischaemic Heart Disease</td><td align=\"left\">122.1</td><td align=\"left\">115.2</td><td align=\"left\">-6.95</td><td align=\"left\">122.1</td><td align=\"left\">115.2</td><td align=\"left\">-6.95</td></tr><tr><td align=\"left\">Myocardial Infarction</td><td align=\"left\">387.2</td><td align=\"left\">367.1</td><td align=\"left\">-20.12</td><td align=\"left\">387.2</td><td align=\"left\">367.1</td><td align=\"left\">-20.12</td></tr><tr><td align=\"left\">Congestive heart Failure</td><td align=\"left\">78.2</td><td align=\"left\">87.2</td><td align=\"left\">9.07</td><td align=\"left\">78.2</td><td align=\"left\">87.2</td><td align=\"left\">9.07</td></tr><tr><td align=\"left\">Stroke</td><td align=\"left\">97.5</td><td align=\"left\">95.7</td><td align=\"left\">-1.86</td><td align=\"left\">97.5</td><td align=\"left\">95.7</td><td align=\"left\">-1.86</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Microvascular</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Retinopathy</td><td align=\"left\">55.8</td><td align=\"left\">49.2</td><td align=\"left\">-6.59</td><td align=\"left\">55.8</td><td align=\"left\">49.2</td><td align=\"left\">-6.59</td></tr><tr><td align=\"left\">Nephropathy</td><td align=\"left\">14.0</td><td align=\"left\">14.0</td><td align=\"left\">0.01</td><td align=\"left\">14.0</td><td align=\"left\">14.0</td><td align=\"left\">0.01</td></tr><tr><td align=\"left\">Neuropathy</td><td align=\"left\">13.1</td><td align=\"left\">10.1</td><td align=\"left\">-3.04</td><td align=\"left\">13.1</td><td align=\"left\">10.1</td><td align=\"left\">-3.04</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Hypoglycaemia</bold><break/><bold> events</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Nocturnal</td><td align=\"left\">12,749</td><td align=\"left\">35,113</td><td align=\"left\">22,364</td><td align=\"left\">12,742</td><td align=\"left\">51,939</td><td align=\"left\">39,197</td></tr><tr><td align=\"left\">Symptomatic</td><td align=\"left\">94,627</td><td align=\"left\">57,059</td><td align=\"left\">-37,568</td><td align=\"left\">94,907</td><td align=\"left\">82,663</td><td align=\"left\">-12,244</td></tr><tr><td align=\"left\">Severe</td><td align=\"left\">6,626.5</td><td align=\"left\">6,760.3</td><td align=\"left\">133.8</td><td align=\"left\">6,626.5</td><td align=\"left\">6,760.3</td><td align=\"left\">133.8</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Fatal</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Macrovascular</td><td align=\"left\">449</td><td align=\"left\">428.4</td><td align=\"left\">-20.5</td><td align=\"left\">449</td><td align=\"left\">428.4</td><td align=\"left\">-20.5</td></tr><tr><td align=\"left\">Microvascular</td><td align=\"left\">13.1</td><td align=\"left\">11.2</td><td align=\"left\">-1.91</td><td align=\"left\">13.1</td><td align=\"left\">11.2</td><td align=\"left\">-1.91</td></tr><tr><td align=\"left\">Other</td><td align=\"left\">536.8</td><td align=\"left\">559.4</td><td align=\"left\">22.59</td><td align=\"left\">536.8</td><td align=\"left\">559.4</td><td align=\"left\">22.59</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Cost effectiveness</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Discounted costs</td><td align=\"left\">£14,552,192</td><td align=\"left\">£12,505,945</td><td/><td align=\"left\">£14,552,192</td><td align=\"left\">£12,505,945</td><td/></tr><tr><td align=\"left\">Discounted QALYS</td><td align=\"left\">7,688</td><td align=\"left\">8,009</td><td/><td align=\"left\">7,687</td><td align=\"left\">7,984</td><td/></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\"><bold>ICER (£/QALY)</bold></td><td align=\"center\" colspan=\"3\"><bold>Dominant (-£6,365)</bold></td><td align=\"center\" colspan=\"3\"><bold>Dominant (-£6,884)</bold></td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>^†Data from Heine et al[##REF##16230722##22##], ^‡data from UKPDS baseline cohort[##REF##15517152##16##], * data from Leese et al[##REF##12663593##6##]</p></table-wrap-foot>", "<table-wrap-foot><p>† Data from: Clarke P, Gray A, Legood R, Briggs A, Holman R: <bold>The impact of diabetes-related complications on healthcare costs: results from the United Kingdom Prospective Diabetes Study (UKPDS Study No. 65). </bold><italic>Diabetic Medicine </italic>2003, <bold>20</bold>:442–450.</p><p>* Data from: The DCCT Research Group: <bold>Epidemiology of severe hypoglycemia in the diabetes control and complications trial</bold>. <italic>American Journal of Medicine </italic>1991, <bold>90</bold>:450–459.</p></table-wrap-foot>", "<table-wrap-foot><p>Note: the model takes an average of a series of runs in order for the resultant values to become stable. In taking this average non-integer values can be generated.</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Metal speciation is a primary control on metal mobility and bioavailability in the environment, and adsorption reactions can play a significant role in this process (e.g., [##UREF##0##1##]). Therefore, many researchers have worked to develop predictive models to describe metal adsorption for a wide range of systems. In studies of natural sediments and soils, empirical approaches based on partition coefficients (K_d) or semi-empirical Langmuir or Freundlich isotherms are often used to describe metal partitioning between solutions and solid substrates. However, because partition coefficients depend on solution and substrate composition, they cannot be extrapolated beyond the conditions for which they are measured (e.g., [##UREF##1##2##,##UREF##2##3##]). Furthermore, because partition coefficients do not include any consideration of mass balance, they can result in very misleading predictions regarding metal speciation and mobility [##UREF##1##2##]. The application of Langmuir or Freundlich isotherms is similarly hindered because these also depend on solution and substrate composition and do not account for the development of electrical charge at mineral surfaces, nor do they consider the structure of adsorbed species [##UREF##2##3##]. In contrast, thermodynamically-based surface complexation models (SCMs) include explicit descriptions of reaction stoichiometries and the development of electrical charge at the solid surface [##UREF##3##4##]. These models have a significant advantage over empirical or semi-empirical models because once calibrated, they should allow accurate prediction of metal speciation under varying solution compositions (e.g. in ionic strength, background electrolyte, competing ions, etc.), and thus should be useful in predicting metal speciation in a wide variety of systems.</p>", "<p>In spite of the significant potential advantages of surface complexation models (SCMs), widespread application of these models, especially to complex sediments and soils, has been lacking for a variety of reasons. Determining the mineralogy of the finest, and therefore highest surface area and presumably most reactive, constituents of soils and sediments is often difficult. Even when the bulk mineralogy is well characterized, deriving reactive surface areas to include in SCMs can be hampered by a lack of information regarding flow paths and the presence of coatings at solid surfaces (e.g., [##UREF##2##3##,##UREF##4##5##]). Furthermore, there is a lack of data for adsorption of many metals on substrates that are relevant for natural systems. Lastly, there is little information regarding the applicability of surface models parameterized using pure, single solid systems to more complex systems containing mixtures of solids (e.g. [##UREF##5##6##,##UREF##6##7##]). Overcoming these obstacles is crucial if existing surface complexation models are to become widely used and useful for understanding metal speciation in natural systems.</p>", "<p>Developing models which are better able to accurately predict the speciation of copper in the environment is important because, although ecosystems require trace quantities of copper to maintain physiological functions [##REF##12175030##8##], at higher concentrations copper is toxic to both plants and animals [##UREF##7##9##]. Furthermore, copper tends to bind strongly to organic and mineral substrates, potentially resulting in mobilization of competing metal ions. Concentrations of trace metals, including copper, have increased dramatically in many ecosystems worldwide due to anthropogenic activities, including dredging of river sediments [##UREF##8##10##, ####UREF##9##11##, ##REF##12469840##12##, ##REF##11837423##13####11837423##13##], application of pesticides and fungicides [##UREF##10##14##,##UREF##11##15##], and through mining and smelting operations. This has resulted in toxic levels of trace metals in many soils and sediments [##REF##12175030##8##,##UREF##7##9##,##UREF##12##16##], and a pressing need to develop accurate predictive models of Cu speciation in the environment.</p>", "<p>In order to better understand and quantify copper bioavailability and transport, copper adsorption has been extensively studied. However, Cu adsorption has been described using SCMs for a relatively small suite of single, pure minerals (e.g. Cu/goethite: [##REF##11871545##17##, ####UREF##13##18##, ##UREF##14##19##, ##UREF##15##20####15##20##]; Cu/hematite: [##UREF##16##21##]; Cu/gibbsite: [##UREF##17##22##]; Cu/kaolinite: [##UREF##18##23##, ####UREF##19##24##, ##REF##10469549##25##, ##REF##15589531##26##, ##UREF##20##27##, ##REF##16168423##28####16168423##28##]; Cu/hydrous manganese oxide: [##UREF##21##29##]; Cu/hydrous ferric oxide: [##UREF##3##4##]) and in even fewer studies in the presence of mixed mineral assemblages (e.g., [##UREF##5##6##]) or natural soils or sediments (e.g., [##UREF##22##30##,##UREF##23##31##]). Furthermore, many of the existing SCMs cannot be used to model adsorption of copper on mixtures of minerals, because the surface complexation parameters have been derived using different treatments of the electrical double layer (e.g. constant capacitance, double layer, triple layer models).</p>", "<p>The goal of this study is to develop internally-consistent descriptions of copper adsorption on hydrous ferric oxide and kaolinite at a variety of ionic strength and sorbate/sorbent ratios using a diffuse double layer model (DLM). Models for the individual solid systems are assessed using 95% confidence intervals of a goodness-of-fit parameter, V(Y). The performance of DLMs parameterized using single solid systems are assessed in mixture solid systems by quantitative comparison of measurements and predictions based on V(Y). The double layer model is chosen because of the extensive database of stability constants that has been derived for metal adsorption on hydrous ferric oxide [##UREF##3##4##] and hydrous manganese oxide [##UREF##21##29##]. Furthermore, the DLM approach requires fewer fit parameters than other SCMs (e.g. triple layer models) and yields stability constants that, at least in theory, do not vary with ionic strength (unlike those obtained using a constant capacitance model). These features make the DLM approach an attractive option for modeling adsorption on natural sediments and soils.</p>" ]

[ "<title>Experimental methods</title>", "<title>Materials</title>", "<p>All reagents used were ACS reagent or trace metal grade. DDI water was purified using a Barnstead E-pure (Model D4641) water system. Powdered kaolinite from Edgar, Florida was purchased from Ward's Scientific. X-ray diffraction indicates that the kaolinite is moderately well ordered with quartz and mica or smectite impurities, with perhaps 1–2% mica in the &lt; 1 μm size fraction (data courtesy of Ray Ferrell, Louisiana State University). Powdered low defect kaolinite from Washington County, GA, USA (KGa-1b) was obtained from the Clay Minerals Society Source Clays Repository. The most significant impurities in the KGa-1b kaolinite are ~1.64% TiO₂[##UREF##24##32##,##UREF##25##33##], 0.21% Fe₂O₃[##UREF##24##32##] and 231 ppm total organic carbon [##UREF##24##32##]. Kaolinite powder was dried at 90°C for 4 days, and then stored in a refrigerator until usage. No other precleaning was done. Hydrous ferric oxide (HFO) was synthesized based on procedures proposed by Schwertmann and Cornell [##UREF##26##34##]. Briefly, ~40 g of ferric nitrate was dissolved in ~500 mL of DDI water in a glass beaker. Concentrated trace metal grade NaOH was slowly titrated into the beaker under constant stirring as precipitate formed, until the mixture reached a pH of ~7.0. The mixture was kept at pH 7 for ~72 hours, then poured into a plastic tube, centrifuged, the supernatant decanted, and the remaining precipitate washed with DDI. The centrifuging and washing procedure was repeated ~5–6 times. The final washed precipitate was freeze-dried and the freeze-dried solid ground gently using a mortar and pestle to break up large aggregates.</p>", "<p>Specific surface areas for HFO and both types of kaolinite were determined at atmospheric pressure using a Quantachrome Nova Surface and Pore Analyzer Model 2200e. Replicate ~2 g samples of each solid were degassed for ~24 hrs and analyzed using 11-point N₂BET. A degassing temperature of ~80°C was used for the HFO and 25°C was used for both types of kaolinite. Measured specific surface areas were: 220 (HFO), 13.6 (KGa-1b kaolinite), and 25.7 (Ward's kaolinite) m²/g. Dzombak and Morel [##UREF##3##4##] argue that due to the presence of significant microporosity N₂BET underestimates the surface area available for sorbates on HFO, and therefore suggest that a specific surface area of 600 m²/g be adopted for modeling. This recommendation has been widely used in DLM descriptions of metal adsorption on HFO. To be consistent with these previous modeling efforts, this value is adopted here for all surface complexation models derived for Cu adsorption on HFO.</p>", "<title>Experimental approach</title>", "<p>Adsorption experiments were completed using continuously stirred batch reactors (500 mL), at room temperature and open to the atmosphere, containing dissolved Cu(II) and NaNO₃as the background electrolyte. Batch reactors were typically titrated first to an acidic initial pH (~2–4.5) using trace metal grade HNO₃. A 10 mL aliquot of this initial suspension of Cu and NaNO₃was removed for subsequent analysis of the initial Cu concentration. Next, the HFO, kaolinite or mixture of these solids was added to the well-stirred 500 mL batch reactor. This suspension was typically preequilibrated for 24 hours. The preequilibration procedure may result in some dissolution, especially of kaolinite at low pH. However, Landry et al. [##UREF##6##7##] demonstrate that preequilibration at acidic compared to circumneutral pH does not significantly influence Co adsorption on kaolinite under conditions similar to those used here. Thus, although some dissolution of the solids may have occurred during preequilibration, this should not significantly influence metal adsorption at the conditions used in this study. After 24 hours, the pH of the preequilibrated suspension was titrated upwards by additions of small volumes of 0.1 M NaOH sufficient to increase the pH by increments of 0.2 to 0.5. Several experiments were also completed in which the base titration was followed by an acid titration using 0.1 M HNO₃. The acid and base legs of these experiments exhibited no significant hysteresis, i.e. any hysteresis was less than the experimental uncertainty (see also below). After titrant addition and stabilization of the pH to within 0.05 pH log units per minute, which typically occurred in about 10 minutes, a 10 mL aliquot of the mixed suspension was pipetted into an acid-washed 15 mL plastic centrifuge vial. The 15 mL tubes, including the initial mineral-free control sample, were subsequently agitated with a benchtop shaker for 24 hrs, removed from the shaker and the pH measured again. The 24 hr period should be more than sufficient for the adsorption reaction to reach equilibrium (see below). In most experiments, each aliquot was then centrifuged and the supernatant filtered through a 0.2 μm syringe filter. However, several experiments were also completed to compare the effect of syringe-filtering to centrifugation only. No significant difference was observed between samples prepared by filtering and those prepared by centrifugation only. All supernatants were acidified using concentrated trace metal grade HNO₃, amended to 1000 ppb with an internal indium standard and analyzed for Cu using either a ThermoElectron PQ Excell ICP-MS or a Perkin Elmer Optima 2100DV ICP-OES with matrix-matched calibration standards. The amount of Cu adsorbed was calculated by the difference between Cu concentration in the analyzed supernatants and the initial Cu solution.</p>", "<p>To determine the adsorption kinetics and the reversibility of Cu adsorption, adsorption and desorption of Cu on kaolinite was tested as a function of time. Using a batch slurry of 2 g/L KGa kaolinite, 10^-5M Cu and 0.01 M NaNO₃, adsorption was initiated by titrating the slurry to a pH of 10.5. 98 ± 2% of the initial Cu was adsorbed by the kaolinite within 5 minutes (data not shown). Periodic sampling over the following 72 hours demonstrated that this Cu remained sorbed on the kaolinite surface. To test the reversibility of sorption, after the 72 hour period the slurry was titrated to pH 2.3. Within 10 minutes only 9 ± 4% of the Cu remained sorbed to the kaolinite and after 24 hours 100% of the Cu was recovered from the kaolinite. Under the conditions of the initial sorption experiment (pH 10.5, 10^-5M Cu, 0.01 M NaNO₃), tenorite is supersaturated and might precipitate. Although it is not possible to distinguish adsorption from surface precipitation in these macroscopic experiments, the rapid desorption of the Cu suggests that adsorption, rather than precipitation, occurs.</p>", "<title>Modeling approach</title>", "<p>Surface complexation stability constants for individual adsorption edge experiments were optimized using FITEQL4.0 [##UREF##27##35##]. Each optimization was completed for a specific reaction stoichiometry (see Table ##TAB##0##1## and discussion below) with activity corrections based on the Davies equation (see [##UREF##27##35##]) and including a stability constant of -7.29 for formation of CuOH⁺_(aq)from the JCHESS default thermodynamic database, which is based on the EQ3/6 database [##UREF##28##36##]. Due to their small influence (&lt; 2.5%) on calculated Cu speciation at the measured conditions, CO_2(g)and other aqueous Cu species were not included in the FITEQL input files. The optimization procedure was used to obtain best-fit stability constants for each edge obtained in a single experiment. In some cases, replicate experiments were completed. The resulting edges were fit individually, and were not aggregated in the modeling. Sets of edges were obtained on kaolinite and HFO to span a range of ionic strength and sorbate/sorbent ratios (see below). The median stability constant(s) derived for sorption onto each solid was input into the speciation code JCHESS, together with all reaction constituents, including CO_2(g). The resulting edges were calculated in JCHESS with activities based on the Debye-Huckel equation and using the default JCHESS thermodynamic database, which includes stability constants for formation of HNO_3(aq), HCO₃^-_(aq), CO_2(aq), CuOH⁺_(aq), CuO₂^-2_(aq), NaHCO₃^-_(aq), CuCO_3(aq), NaOH_(aq), NaCO₃^-_(aq), CuCO₃(OH)₂^-2_(aq)and Cu(CO₃)₂^-2_(aq). The calculated Cu adsorbed differed by &lt; 2.5% from those calculated using the more simplified FITEQL model, even for the highest ionic strength experiments. JCHESS was also used to assess saturation states of minerals and to complete speciation calculations for mixed solid assemblages, which is not possible using the FITEQL software. The default JCHESS thermodynamic database contains data for copper-bearing minerals including tenorite, malachite, azurite, and cuprite. No data is included for Cu(OH)_2(s). Calculations using the stability constant for formation of Cu(OH)_2(s)provided with the JCHESS MINTEQ database (log K = -8.64) indicate that for a given set of experimental conditions, tenorite saturates at lower pH then Cu(OH)_2(s).</p>", "<p>Adsorption edge data calculated with JCHESS were compared to the experimental data to assess goodness of fit V(Y) using the model proposed by Heinrich et al. [##UREF##29##37##]:</p>", "<p></p>", "<p>where Y is the difference between the calculated and measured concentration of metal remaining in solution for each data point, P; s_Yis the standard deviation; n_Pis the number of data points; n_Qis the number of components, Q, for which the concentration, C, and the total concentration, t, are known (n_Q= 1 for all edges in this study); and n_Ris the number or parameters being optimized. The standard deviation, s_Y, was assumed to be equal to 5% of the experimentally measured copper concentration in solution with a lower limit of 10 ppb (based on ICP OES errors and detection limits). Confidence intervals for V(Y) values were calculated according to the equation proposed by Heinrich et al. [##UREF##29##37##]:</p>", "<p></p>", "<p>where <italic>χ</italic>²_{<italic>p </italic>}is the quantile of the chi-square distribution with (n_Qxn_P-n_R) degrees of freedom with exceedence probability, <italic>p</italic>, and <italic>α </italic>= .05 (95% confidence interval). For a given set of adsorption edges, the simplest model yielding a statistically superior V(Y), i.e. the model with the lowest V(Y) having no overlap with the 95% confidence interval of the next best model, was accepted as the best model. The V(Y), together with the 95% confidence intervals, was also used to compare the fit of models calibrated for the single solids with those obtained for the mixed mineral systems.</p>" ]

[ "<title>Results and discussion</title>", "<title>Cu adsorption on hydrous ferric oxide (HFO)</title>", "<p>Cu adsorption on HFO was measured as a function of pH, ionic strength and sorbate/sorbent ratio (Fig. ##FIG##0##1##). For a given sorbate/sorbent ratio, there is little dependence of adsorption on ionic strength. Increasing the sorbate/sorbent ratio by an order of magnitude, from 10^-5M Cu to 10^-4M Cu on 2 g/L HFO, increases the pH of 50% adsorption (pH₅₀) from ~4.4 to ~4.7. Replicate experiments completed with 0.1 M NaNO₃and 10^-5M Cu are in reasonable agreement (Fig. ##FIG##0##1##, blue symbols). JCHESS calculations indicate that the only solid that may become supersaturated in this system is tenorite (CuO). In the absence of adsorption, saturation with respect to tenorite occurs at pH~6 and 6.5, for the 10^-4M and 10^-5M Cu experiments, respectively, which is well above the measured pH edges.</p>", "<p>Cu adsorption on HFO has been described by Dzombak and Morel [##UREF##3##4##] using a 2-site double layer surface complexation model (DLM) with the parameters shown in Tables ##TAB##0##1## and ##TAB##1##2##. Amphoteric strong and weak surface hydroxyl sites are included in the model, but Cu adsorption is assumed to occur as a monodentate complex only on the strong site, according to:</p>", "<p></p>", "<p>The resulting model curves are in very good agreement with the experimental data (Fig. ##FIG##0##1A##; V(Y) = 14.0). The Dzombak and Morel model adequately captures both the lack of ionic strength dependence and the shift in the edges with increased sorbate/sorbent ratio. In experiments with 10^-4M Cu, the relatively small number of strong sites (1.13·10^-4M) are nearly, but not entirely, saturated with sorbed Cu at high pH.</p>", "<p>An internally consistent set of single-site DLM parameters for the protonation and deprotonation of a wide variety of solids, including HFO and kaolinite, has been predicted by Sverjensky and Sahai [##UREF##30##38##] based on Born solvation theory. A goal of the current study is to develop robust DLM descriptions of cation adsorption on environmentally-relevant solids, while minimizing the number of fit parameters. Adsorption of Cu on kaolinite is described in this study (see discussion below) using a DLM based on the work of Sverjensky and Sahai [##UREF##30##38##]. A second goal of this study is to develop internally-consistent DLMs for Cu adsorption on both HFO and kaolinite. Therefore, the Cu adsorption edges for HFO were used to derive a best-fit stability constant using the site density, protonation and deprotonation values recommended by Sverjensky and Sahai [##UREF##30##38##] and assuming monodentate adsorption of Cu on the single site, according to:</p>", "<p></p>", "<p>The V(Y) value for the resulting model (V(Y) = 12.2), while slightly lower than that determined for the 2-site Dzombak and Morel [##UREF##3##4##] model, is not statistically superior (Table ##TAB##1##2##). Furthermore, the fits obtained with the single-site model, although statistically inseparable at the 95% confidence interval from those of the 2-site model, fail to capture the dependence of the adsorption edges on sorbate/sorbent ratio (Fig. ##FIG##0##1B##). In general, we recommend choosing the simplest model, with the least number of fitting parameters, when multiple models produce statistically inseparable results. However, the Dzombak and Morel [##UREF##3##4##] model has been carefully calibrated with a very large dataset (including many metals besides Cu), and this model is already in widespread use. Therefore, we apply both the Dzombak and Morel 2-site model and the simpler 1-site model developed in this study to predict Cu adsorption for systems containing both HFO and kaolinite (see discussion below).</p>", "<title>Cu adsorption on kaolinite</title>", "<p>Cu adsorption was measured on two types of kaolinite (KGa and Wards) as a function of ionic strength (0.001 to 0.1 M NaNO₃) and sorbate/sorbent ratio (10^-4to 10^-6M Cu on 2 or 5 g/L kaolinite). The pH₅₀decreases with smaller sorbate/sorbent ratios and typically increases with increasing ionic strength (Fig. ##FIG##1##2A, B##). This is in agreement with the results of prior studies of Cu adsorption on kaolinite (e.g., [##UREF##18##23##, ####UREF##19##24##, ##REF##10469549##25##, ##REF##15589531##26##, ##UREF##20##27##, ##REF##16168423##28####16168423##28##]). Replicate experiments (10^-5M Cu, 0.1 M NaNO₃in Fig. ##FIG##1##2A##; 10^-4M Cu, 0.01 M NaNO₃in Fig. ##FIG##1##2A##; 10^-5M Cu, 0.02 M NaNO₃in Fig. ##FIG##1##2B##) are generally in agreement, although one of the 10^-5M Cu, 0.02 M NaNO₃(Fig. ##FIG##1##2B##) does show higher adsorption then expected. Tenorite is predicted to be supersaturated in the absence of adsorption at pH ≥ 6 for 10^-4M Cu and ≥ 6.5 for 10^-5M Cu experiments. This is well above the 10^-5M Cu sorption edges, but could influence a portion of the 10^-4M Cu edges. However, as discussed above, rapid desorption of 10^-5M Cu from kaolinite after equilibration for 72 hours at pH 10.5 suggests that adsorption is the primary uptake mechanism.</p>", "<p>A number of surface complexation models have been proposed to describe Cu adsorption on kaolinite. Most of these follow the lead of Schindler et al. [##UREF##18##23##] and use a 2-site approach. Schindler et al. [##UREF##18##23##] derived a 2-site constant capacitance model (CCM) with the formation of an innersphere Cu surface complex on a variable charge site together with exchange of Cu⁺²for H⁺or Na⁺on a permanent charge, or ion exchange site. Schindler et al. [##UREF##18##23##] interpret the variable charge site as an aluminol site and suggest that the exchange site may either be due to isomorphous substitution giving rise to a small permanent structural charge on the kaolinite or may be due to the presence of a small amount of 2:1 interlayer clay impurity in the kaolinite specimen. Subsequent work by Ikhsan et al. [##REF##10469549##25##] used a similar modeling approach except that a bidentate complex was used to describe Cu adsorption on the variable charge site. Likewise, Heidmann et al. [##REF##15589531##26##] chose a 1-pK Stern model to describe Cu adsorption on variable charge edge sites of kaolinite with ion exchange sites used to describe adsorption at lower pH. An alternative approach for modeling Cu adsorption on kaolinite was proposed by Jung et al. [##UREF##19##24##], who used a triple layer surface complexation model assuming that Cu binds as an innersphere monodentate complex on an amphoteric aluminol site and as an outersphere monodentate complex on a deprotonatable silanol site. Similarly, Hizal and Apak [##REF##16168423##28##] assumed formation of monodentate Cu complexes on two variable charge sites, presumed to correspond to aluminol and silanol sites. Finally, Peacock and Sherman [##UREF##20##27##] used an extended constant capacitance model to describe Cu adsorption on kaolinite. Using EXAFS data as a guide, Peacock and Sherman [##UREF##20##27##] proposed a model with Cu sorption occurring at three sites, forming a bidentate, mononuclear innersphere complex with an aluminol edge site; a tridentate, binuclear complex with an aluminol edge site; and binding to an ion exchange site on the basal plane of the kaolinite.</p>", "<p>The goal of this study is to derive a simple, DLM description of Cu binding on kaolinite consistent with the DLM description of Cu binding on HFO that can be used to make predictions of Cu speciation in mixed solid systems. A variety of models were tested, including monodentate or bidentate binding of Cu to an amphoteric variable charge site in the presence or absence of an ion exchange site (see Table ##TAB##2##3##).</p>", "<p>Variable charge surface site densities can be estimated from crystallographic considerations, although this typically yields a range of values, depending on assumptions made regarding crystal morphology and the definition of a surface site (see discussion in [##UREF##31##39##]). For example, Koretsky et al. [##UREF##31##39##] estimated a range of 0 to 21.8 sites/nm²for kaolinite, based on crystallographic considerations. Due to this uncertainty, site densities are often treated as additional fit parameters in surface complexation models. Previous work demonstrates that surface complexation stability constants are dependent on the choice of site densities and that typically a wide range of site densities can provide a satisfactory fit to measured data (e.g., [##UREF##32##40##]). Therefore, in this study the variable charge surface site density is set equal to 10 sites/nm², as recommended by Sverjensky and Sahai [##UREF##30##38##]. For models with an additional ion exchange site, the ion exchange site density was calculated directly from the measured cation exchange capacity for KGA-1b reported by Bordon and Giese [##UREF##33##41##] (Table ##TAB##0##1##).</p>", "<p>Protonation and deprotonation stability constants are typically fit using measured potentiometric acid-base titrations for the mineral of interest. However, Sverjensky and Sahai [##UREF##30##38##] have developed a predictive scheme for estimating protonation and deprotonation stability constants for a wide variety of solids, based on Born solvation theory. There are several advantages to using their predicted constants. First, if their method produces satisfactory results, then development of the SCM is simplified, requiring fewer experimental measurements and fewer fit parameters. Secondly, their estimates are produced from analysis of many experimental datasets and therefore should be both robust and internally consistent. Finally, although perhaps difficult, a goal of this study is to develop a generally-applicable model of Cu adsorption on kaolinite, which is not specific to a particular specimen of kaolinite. Therefore, protonation and deprotonation stability constants for the variable charge site were taken from the predictions of Sverjensky and Sahai [##UREF##30##38##] (Table ##TAB##2##3##) and were not treated as fit parameters, in spite of the fact that doing so might produce a better model fit to the data.</p>", "<p>Fits were assessed by calculating the goodness-of-fit for the median stability constant(s) when applied to all of the measured edge data (n_p= 360). The lowest V(Y) is obtained for the simplest model tested: a single variable site model with formation of a monodentate Cu complex (Table ##TAB##1##2##; Fig. ##FIG##1##2##) according to:</p>", "<p></p>", "<p>This model produces a reasonable description of the pH edge dependence on ionic strength and sorbate/sorbent for both specimens of kaolinite although, especially for the Wards kaolinite, sorption is somewhat underestimated at low pH (&lt; 4.5). XAS and macroscopic isotherm data suggest the formation of a bidentate Cu complex on kaolinite [##REF##10469549##25##,##UREF##20##27##]. Modeling Cu adsorption on kaolinite using a simple single site model with a bidentate Cu complex, i.e.,</p>", "<p></p>", "<p>produces a slightly higher V(Y) compared to the simple monodentate model, although the fit is not statistically distinct at the 95% confidence interval (Table ##TAB##2##3##). However, visual inspection of the fits produced by the bidentate model suggests that the predicted edges are systematically steeper than the experimental data and also that the description of sorbate/sorbent dependence is poorer than for the monodentate model (Fig. ##FIG##2##3##).</p>", "<p>As described above, 2-site models have been used to describe Cu adsorption on kaolinite. Furthermore, two-site models are necessary to produce adequate descriptions of weaker ion sorption (e.g. Co and Cd) on kaolinite (e.g., [##UREF##6##7##,##REF##10469549##25##,##UREF##34##42##]). The eventual goal of the approach in this study is to develop a relatively simple surface complexation model that can be applied in natural systems containing mixtures of multiple solids and cations. Thus, a 2-site approach, even if it does not produce a statistically superior description of the experimental Cu data, may be necessary to describe metal adsorption in natural systems that contain mixtures of weakly and strongly sorbing ions. Therefore, the simple single variable charge site model was expanded to include a permanent charge, or ion exchange, site, which can bind Na⁺or Cu⁺²according to</p>", "<p></p>", "<p></p>", "<p>respectively (e.g. [##UREF##6##7##,##UREF##34##42##]). Although good fits, correctly describing the slightly elevated sorption at low pH, are obtained for individual edges by fitting for the three stability constants associated with reactions (5), (7) and (8), applying the median values to the full set of data results in a statistically poorer fit to the kaolinite data compared to the 1-site model (Table ##TAB##2##3##). Furthermore, for many experiments, FITEQL did not converge when stability constants for reactions (6), (7) and (8) were fit simultaneously. Landry et al. [##UREF##6##7##] found that a 2-site approach is necessary to adequately describe Co adsorption on kaolinite. Using an amphoteric variable charge site and an ion exchange site as shown above, Landry et al. [##UREF##6##7##] derived a stability constant of 2.5 for reaction (7). Using this value for the Na-H exchange stability constant and fitting for the stability constants associated with Cu binding on the ion exchange site and on the variable charge site (as either a bidentate or monodentate complex) still yields a statistically poorer fit to the data compared to the 1-site model (Table ##TAB##2##3##), producing overestimates of sorption at low ionic strength and sorbate/sorbent ratio and underestimates of sorption at high ionic strength and sorbate/sorbent ratio, particularly on KGa kaolinite (Fig. ##FIG##3##4##). The best model fit with the ion exchange included is obtained when Cu sorption to the ion exchange site (reaction 8) is excluded from the model (i.e. only reaction 7 is allowed) and Cu forms a bidentate site on the variable charge site (V(Y) = 33.8; Table ##TAB##2##3##; Fig. ##FIG##4##5##). The goodness-of-fit for this model is not statistically different from the 1-site bidentate model, although it is not as good as the 1-site monodentate model at the 95% confidence interval. Nonetheless, this model has the advantage that it is consistent with the 2-site models required to describe adsorption of weakly binding ions such as Cd⁺²or Co⁺²on kaolinite. It is also consistent with formation of a bidentate Cu species as inferred from isotherm data [##REF##10469549##25##] and XAS studies [##UREF##20##27##].</p>", "<p>Predictions from the two best models, i.e., the 1-site model (monodentate Cu adsorption on a variable charge site) and the 2-site model (ion exchange site that does not sorb Cu; variable charge site with bidentate adsorption of Cu) were compared to adsorption edge data obtained in previous studies [##UREF##19##24##,##REF##10469549##25##,##UREF##20##27##,##REF##16168423##28##]. For calculations with the 2-site model, the electrolyte was assumed to be NaNO₃, although two studies used KNO₃[##UREF##19##24##,##REF##10469549##25##] and one used NaClO₄[##REF##16168423##28##]. The 1-site monodentate model produced a V(Y) of 634 for all of the compiled data (n_p= 73), whereas the 2-site bidentate model resulted in a significantly better fit to the complete dataset (V(Y) = 281; Fig. ##FIG##5##6##). The adsorption edge reported by Ikhsan et al. [##REF##10469549##25##] is in reasonable agreement with predictions from the 1-site monodentate model derived independently in this study (Fig. ##FIG##5##6A##). The 2-site bidentate model yields a pH₅₀within ~0.3 of the measured pH₅₀, but the predicted edge is steeper than the data of Ikhsan et al. [##REF##10469549##25##]. Both models predict saturation of the surface at less than 100% for the conditions reported by Peacock and Sherman ([##UREF##20##27##]; Fig. ##FIG##5##6B##). The 2-site bidentate model produces a reasonable fit to both datasets reported by Jung et al. [##UREF##19##24##], while the 1-site monodentate model underestimates the amount of Cu adsorbed (Fig. ##FIG##5##6C##). The 1-site mondentate model is in slightly better agreement with the data of Hizal and Apak [##REF##16168423##28##] at high pH compared to the 2-site bidentate model, which produces a steeper edge, but both models underestimate adsorption compared to the data at lower pH (Fig. ##FIG##5##6D##).</p>", "<p>The general agreement between the predicted edges from the model derived here and data from four independent studies using different ionic strength, background electrolyte, sorbate/sorbent ratio and kaolinite specimens is encouraging. Discrepancies between model predictions and these experiments could be due to differences in experimental conditions, for example in the choice of background electrolyte (e.g., KNO₃or NaClO₄rather than NaNO₃). Another possibility is that the disagreement reflects differences in the purity, solid solution chemistry, defect structure or other characteristics of the kaolinite specimens. Differences in measured N₂-BET surface areas of the kaolinite specimens may also play a role in the model misfits. For example, Peacock and Sherman [##UREF##20##27##] report an N₂BET surface area of 12.2 m²/g for the Cornwall kaolinite used in their study. This, combined with the site density of 10 sites/nm²chosen here, results in saturation of the surface at ~80%, and underestimates the percentage of Cu adsorbed reported by Peacock and Sherman [##UREF##20##27##]. Increasing the surface area to 25.7 m²/g (as measured for the Wards sample in this study) results in much better agreement with the reported data (Fig. ##FIG##5##6B##). The significant dependence of derived stability constants on measured surface area and choice of site density is well known (e.g. [##UREF##32##40##,##UREF##35##43##]), and may prove to be particularly problematic in the application of surface complexation models to natural sediments, where reactive surface area is difficult to assess [##UREF##2##3##].</p>", "<title>Cu adsorption on mixture of kaolinite and hydrous ferric oxide</title>", "<p>Cu adsorption was measured on mixtures of HFO and kaolinite (both Wards and KGa) at a range of conditions, although most experiments were conducted in 0.01 M NaNO₃and using 10^-5M Cu. Total solid concentrations ranged from 4 g/L to 7.5 g/L and ratios of kaolinite to HFO ranged from 1:1 to 500:1. As might be expected, adsorption increases at a given pH, ionic strength and sorbate/sorbent ratio with increasing quantities of HFO (Fig. ##FIG##6##7##). Several experiments were conducted with base titration (closed symbols), followed by acid titration (open symbols), to test for hysteresis. Within the experimental uncertainty, no significant hysteresis was observed.</p>", "<p>Goodness-of-fit parameters for the mixed solid systems (n_p= 255) were assessed for various combinations of the single solid models discussed above (Table ##TAB##3##4##). The resulting V(Y) range from 12.6 to 58.2, with values typically intermediate between those obtained for the pure HFO and pure kaolinite systems. In the pure systems, the 1-site HFO model and the 1-site monodentate variable charge kaolinite model produced the lowest V(Y) values (12.2 and 23.3, respectively). Combining these two models yields V(Y) = 14.1 (Fig. ##FIG##6##7##). Although this is not the lowest V(Y) obtained by combining individual solid models, it is not statistically distinguishable from the lowest value of 12.6 (Fig. ##FIG##7##8##), obtained by combining the 1-site HFO model with the 2-site monodentate kaolinite model, without sorption of Cu on the ion exchange site, at the 95% confidence interval.</p>", "<p>Although combining the simplest models producing statistically indistinguishable V(Y) values for the individual systems is conceptually appealing, these models may not represent the best DLM descriptions of the systems. As discussed above, the 2-site HFO model of Dzombak and Morel [##UREF##3##4##] produces a visually better fit to the HFO data and has been calibrated for a greater breadth of data than the 1-site HFO model presented above. Combining the 1-site monodentate kaolinite model with the 2-site HFO model results in a V(Y) of 18.0 (Fig. ##FIG##8##9##). As can be seen in Figs. ##FIG##6##7## and ##FIG##8##9##, combining either HFO model with the 1-site monodentate kaolinite model produces a reasonable fit to the measured edges, although in both cases sorption is overestimated for experiments with the greatest kaolinite to HFO ratio. Use of the 2-site HFO model produces a better prediction of the dependence of sorption on sorbate/sorbent ratio (Figs. ##FIG##6##7A##, ##FIG##8##9A##; yellow data/lines).</p>", "<p>As discussed above, the 2-site kaolinite model with inclusion of an ion exchange site that does not significantly bind Cu may be preferable to the simpler 1-site model because of its potential for representing adsorption of weaker ions to kaolinite in mixed metal solutions. Combining the 1-site or 2-site HFO models with the 2-site bidentate kaolinite model produces V(Y) values of 15.9 and 13.6, respectively (Figs. ##FIG##9##10##, ##FIG##10##11##). The resulting edges are again somewhat steeper than the experimental data, but do adequately capture the dependence of the edges on kaolinite to HFO ratios.</p>", "<p>In all cases, surface complexation models calibrated for the single mineral systems do an adequate job of describing metal adsorption in the mixed solid systems. Goodness-of-fit parameters are intermediate between those obtained for the pure HFO and pure kaolinite systems. Discrepancies between model predictions and measured data are similar to those observed in the pure mineral systems. For example, edges that are too steep are produced from kaolinite models assuming bidentate adsorption of Cu in both the pure and mixed mineral systems. Similarly, the 2-site HFO model produces better descriptions of the dependence of Cu sorption on sorbate/sorbent ratio in both pure and mixed mineral systems. The relatively good fits (low V(Y)) obtained for predicted Cu sorption in mixed mineral systems suggest that the stability constants obtained for the pure mineral systems are reasonably robust, and even more importantly, that HFO-kaolinite interactions need not be explicitly included in the speciation model. In other words, a simple component additivity approach produces predictions for the mixed mineral systems that are as good as those for the calibrated pure mineral systems. However, it is important to point out that these experiments were conducted over a relatively brief temporal scale (days). It is possible that aging over months or years may produce surface coatings that physically or chemically block ion adsorption sites. This must be tested using further experimental work, together with adsorption studies on natural sediments and soils.</p>" ]

[ "<title>Results and discussion</title>", "<title>Cu adsorption on hydrous ferric oxide (HFO)</title>", "<p>Cu adsorption on HFO was measured as a function of pH, ionic strength and sorbate/sorbent ratio (Fig. ##FIG##0##1##). For a given sorbate/sorbent ratio, there is little dependence of adsorption on ionic strength. Increasing the sorbate/sorbent ratio by an order of magnitude, from 10^-5M Cu to 10^-4M Cu on 2 g/L HFO, increases the pH of 50% adsorption (pH₅₀) from ~4.4 to ~4.7. Replicate experiments completed with 0.1 M NaNO₃and 10^-5M Cu are in reasonable agreement (Fig. ##FIG##0##1##, blue symbols). JCHESS calculations indicate that the only solid that may become supersaturated in this system is tenorite (CuO). In the absence of adsorption, saturation with respect to tenorite occurs at pH~6 and 6.5, for the 10^-4M and 10^-5M Cu experiments, respectively, which is well above the measured pH edges.</p>", "<p>Cu adsorption on HFO has been described by Dzombak and Morel [##UREF##3##4##] using a 2-site double layer surface complexation model (DLM) with the parameters shown in Tables ##TAB##0##1## and ##TAB##1##2##. Amphoteric strong and weak surface hydroxyl sites are included in the model, but Cu adsorption is assumed to occur as a monodentate complex only on the strong site, according to:</p>", "<p></p>", "<p>The resulting model curves are in very good agreement with the experimental data (Fig. ##FIG##0##1A##; V(Y) = 14.0). The Dzombak and Morel model adequately captures both the lack of ionic strength dependence and the shift in the edges with increased sorbate/sorbent ratio. In experiments with 10^-4M Cu, the relatively small number of strong sites (1.13·10^-4M) are nearly, but not entirely, saturated with sorbed Cu at high pH.</p>", "<p>An internally consistent set of single-site DLM parameters for the protonation and deprotonation of a wide variety of solids, including HFO and kaolinite, has been predicted by Sverjensky and Sahai [##UREF##30##38##] based on Born solvation theory. A goal of the current study is to develop robust DLM descriptions of cation adsorption on environmentally-relevant solids, while minimizing the number of fit parameters. Adsorption of Cu on kaolinite is described in this study (see discussion below) using a DLM based on the work of Sverjensky and Sahai [##UREF##30##38##]. A second goal of this study is to develop internally-consistent DLMs for Cu adsorption on both HFO and kaolinite. Therefore, the Cu adsorption edges for HFO were used to derive a best-fit stability constant using the site density, protonation and deprotonation values recommended by Sverjensky and Sahai [##UREF##30##38##] and assuming monodentate adsorption of Cu on the single site, according to:</p>", "<p></p>", "<p>The V(Y) value for the resulting model (V(Y) = 12.2), while slightly lower than that determined for the 2-site Dzombak and Morel [##UREF##3##4##] model, is not statistically superior (Table ##TAB##1##2##). Furthermore, the fits obtained with the single-site model, although statistically inseparable at the 95% confidence interval from those of the 2-site model, fail to capture the dependence of the adsorption edges on sorbate/sorbent ratio (Fig. ##FIG##0##1B##). In general, we recommend choosing the simplest model, with the least number of fitting parameters, when multiple models produce statistically inseparable results. However, the Dzombak and Morel [##UREF##3##4##] model has been carefully calibrated with a very large dataset (including many metals besides Cu), and this model is already in widespread use. Therefore, we apply both the Dzombak and Morel 2-site model and the simpler 1-site model developed in this study to predict Cu adsorption for systems containing both HFO and kaolinite (see discussion below).</p>", "<title>Cu adsorption on kaolinite</title>", "<p>Cu adsorption was measured on two types of kaolinite (KGa and Wards) as a function of ionic strength (0.001 to 0.1 M NaNO₃) and sorbate/sorbent ratio (10^-4to 10^-6M Cu on 2 or 5 g/L kaolinite). The pH₅₀decreases with smaller sorbate/sorbent ratios and typically increases with increasing ionic strength (Fig. ##FIG##1##2A, B##). This is in agreement with the results of prior studies of Cu adsorption on kaolinite (e.g., [##UREF##18##23##, ####UREF##19##24##, ##REF##10469549##25##, ##REF##15589531##26##, ##UREF##20##27##, ##REF##16168423##28####16168423##28##]). Replicate experiments (10^-5M Cu, 0.1 M NaNO₃in Fig. ##FIG##1##2A##; 10^-4M Cu, 0.01 M NaNO₃in Fig. ##FIG##1##2A##; 10^-5M Cu, 0.02 M NaNO₃in Fig. ##FIG##1##2B##) are generally in agreement, although one of the 10^-5M Cu, 0.02 M NaNO₃(Fig. ##FIG##1##2B##) does show higher adsorption then expected. Tenorite is predicted to be supersaturated in the absence of adsorption at pH ≥ 6 for 10^-4M Cu and ≥ 6.5 for 10^-5M Cu experiments. This is well above the 10^-5M Cu sorption edges, but could influence a portion of the 10^-4M Cu edges. However, as discussed above, rapid desorption of 10^-5M Cu from kaolinite after equilibration for 72 hours at pH 10.5 suggests that adsorption is the primary uptake mechanism.</p>", "<p>A number of surface complexation models have been proposed to describe Cu adsorption on kaolinite. Most of these follow the lead of Schindler et al. [##UREF##18##23##] and use a 2-site approach. Schindler et al. [##UREF##18##23##] derived a 2-site constant capacitance model (CCM) with the formation of an innersphere Cu surface complex on a variable charge site together with exchange of Cu⁺²for H⁺or Na⁺on a permanent charge, or ion exchange site. Schindler et al. [##UREF##18##23##] interpret the variable charge site as an aluminol site and suggest that the exchange site may either be due to isomorphous substitution giving rise to a small permanent structural charge on the kaolinite or may be due to the presence of a small amount of 2:1 interlayer clay impurity in the kaolinite specimen. Subsequent work by Ikhsan et al. [##REF##10469549##25##] used a similar modeling approach except that a bidentate complex was used to describe Cu adsorption on the variable charge site. Likewise, Heidmann et al. [##REF##15589531##26##] chose a 1-pK Stern model to describe Cu adsorption on variable charge edge sites of kaolinite with ion exchange sites used to describe adsorption at lower pH. An alternative approach for modeling Cu adsorption on kaolinite was proposed by Jung et al. [##UREF##19##24##], who used a triple layer surface complexation model assuming that Cu binds as an innersphere monodentate complex on an amphoteric aluminol site and as an outersphere monodentate complex on a deprotonatable silanol site. Similarly, Hizal and Apak [##REF##16168423##28##] assumed formation of monodentate Cu complexes on two variable charge sites, presumed to correspond to aluminol and silanol sites. Finally, Peacock and Sherman [##UREF##20##27##] used an extended constant capacitance model to describe Cu adsorption on kaolinite. Using EXAFS data as a guide, Peacock and Sherman [##UREF##20##27##] proposed a model with Cu sorption occurring at three sites, forming a bidentate, mononuclear innersphere complex with an aluminol edge site; a tridentate, binuclear complex with an aluminol edge site; and binding to an ion exchange site on the basal plane of the kaolinite.</p>", "<p>The goal of this study is to derive a simple, DLM description of Cu binding on kaolinite consistent with the DLM description of Cu binding on HFO that can be used to make predictions of Cu speciation in mixed solid systems. A variety of models were tested, including monodentate or bidentate binding of Cu to an amphoteric variable charge site in the presence or absence of an ion exchange site (see Table ##TAB##2##3##).</p>", "<p>Variable charge surface site densities can be estimated from crystallographic considerations, although this typically yields a range of values, depending on assumptions made regarding crystal morphology and the definition of a surface site (see discussion in [##UREF##31##39##]). For example, Koretsky et al. [##UREF##31##39##] estimated a range of 0 to 21.8 sites/nm²for kaolinite, based on crystallographic considerations. Due to this uncertainty, site densities are often treated as additional fit parameters in surface complexation models. Previous work demonstrates that surface complexation stability constants are dependent on the choice of site densities and that typically a wide range of site densities can provide a satisfactory fit to measured data (e.g., [##UREF##32##40##]). Therefore, in this study the variable charge surface site density is set equal to 10 sites/nm², as recommended by Sverjensky and Sahai [##UREF##30##38##]. For models with an additional ion exchange site, the ion exchange site density was calculated directly from the measured cation exchange capacity for KGA-1b reported by Bordon and Giese [##UREF##33##41##] (Table ##TAB##0##1##).</p>", "<p>Protonation and deprotonation stability constants are typically fit using measured potentiometric acid-base titrations for the mineral of interest. However, Sverjensky and Sahai [##UREF##30##38##] have developed a predictive scheme for estimating protonation and deprotonation stability constants for a wide variety of solids, based on Born solvation theory. There are several advantages to using their predicted constants. First, if their method produces satisfactory results, then development of the SCM is simplified, requiring fewer experimental measurements and fewer fit parameters. Secondly, their estimates are produced from analysis of many experimental datasets and therefore should be both robust and internally consistent. Finally, although perhaps difficult, a goal of this study is to develop a generally-applicable model of Cu adsorption on kaolinite, which is not specific to a particular specimen of kaolinite. Therefore, protonation and deprotonation stability constants for the variable charge site were taken from the predictions of Sverjensky and Sahai [##UREF##30##38##] (Table ##TAB##2##3##) and were not treated as fit parameters, in spite of the fact that doing so might produce a better model fit to the data.</p>", "<p>Fits were assessed by calculating the goodness-of-fit for the median stability constant(s) when applied to all of the measured edge data (n_p= 360). The lowest V(Y) is obtained for the simplest model tested: a single variable site model with formation of a monodentate Cu complex (Table ##TAB##1##2##; Fig. ##FIG##1##2##) according to:</p>", "<p></p>", "<p>This model produces a reasonable description of the pH edge dependence on ionic strength and sorbate/sorbent for both specimens of kaolinite although, especially for the Wards kaolinite, sorption is somewhat underestimated at low pH (&lt; 4.5). XAS and macroscopic isotherm data suggest the formation of a bidentate Cu complex on kaolinite [##REF##10469549##25##,##UREF##20##27##]. Modeling Cu adsorption on kaolinite using a simple single site model with a bidentate Cu complex, i.e.,</p>", "<p></p>", "<p>produces a slightly higher V(Y) compared to the simple monodentate model, although the fit is not statistically distinct at the 95% confidence interval (Table ##TAB##2##3##). However, visual inspection of the fits produced by the bidentate model suggests that the predicted edges are systematically steeper than the experimental data and also that the description of sorbate/sorbent dependence is poorer than for the monodentate model (Fig. ##FIG##2##3##).</p>", "<p>As described above, 2-site models have been used to describe Cu adsorption on kaolinite. Furthermore, two-site models are necessary to produce adequate descriptions of weaker ion sorption (e.g. Co and Cd) on kaolinite (e.g., [##UREF##6##7##,##REF##10469549##25##,##UREF##34##42##]). The eventual goal of the approach in this study is to develop a relatively simple surface complexation model that can be applied in natural systems containing mixtures of multiple solids and cations. Thus, a 2-site approach, even if it does not produce a statistically superior description of the experimental Cu data, may be necessary to describe metal adsorption in natural systems that contain mixtures of weakly and strongly sorbing ions. Therefore, the simple single variable charge site model was expanded to include a permanent charge, or ion exchange, site, which can bind Na⁺or Cu⁺²according to</p>", "<p></p>", "<p></p>", "<p>respectively (e.g. [##UREF##6##7##,##UREF##34##42##]). Although good fits, correctly describing the slightly elevated sorption at low pH, are obtained for individual edges by fitting for the three stability constants associated with reactions (5), (7) and (8), applying the median values to the full set of data results in a statistically poorer fit to the kaolinite data compared to the 1-site model (Table ##TAB##2##3##). Furthermore, for many experiments, FITEQL did not converge when stability constants for reactions (6), (7) and (8) were fit simultaneously. Landry et al. [##UREF##6##7##] found that a 2-site approach is necessary to adequately describe Co adsorption on kaolinite. Using an amphoteric variable charge site and an ion exchange site as shown above, Landry et al. [##UREF##6##7##] derived a stability constant of 2.5 for reaction (7). Using this value for the Na-H exchange stability constant and fitting for the stability constants associated with Cu binding on the ion exchange site and on the variable charge site (as either a bidentate or monodentate complex) still yields a statistically poorer fit to the data compared to the 1-site model (Table ##TAB##2##3##), producing overestimates of sorption at low ionic strength and sorbate/sorbent ratio and underestimates of sorption at high ionic strength and sorbate/sorbent ratio, particularly on KGa kaolinite (Fig. ##FIG##3##4##). The best model fit with the ion exchange included is obtained when Cu sorption to the ion exchange site (reaction 8) is excluded from the model (i.e. only reaction 7 is allowed) and Cu forms a bidentate site on the variable charge site (V(Y) = 33.8; Table ##TAB##2##3##; Fig. ##FIG##4##5##). The goodness-of-fit for this model is not statistically different from the 1-site bidentate model, although it is not as good as the 1-site monodentate model at the 95% confidence interval. Nonetheless, this model has the advantage that it is consistent with the 2-site models required to describe adsorption of weakly binding ions such as Cd⁺²or Co⁺²on kaolinite. It is also consistent with formation of a bidentate Cu species as inferred from isotherm data [##REF##10469549##25##] and XAS studies [##UREF##20##27##].</p>", "<p>Predictions from the two best models, i.e., the 1-site model (monodentate Cu adsorption on a variable charge site) and the 2-site model (ion exchange site that does not sorb Cu; variable charge site with bidentate adsorption of Cu) were compared to adsorption edge data obtained in previous studies [##UREF##19##24##,##REF##10469549##25##,##UREF##20##27##,##REF##16168423##28##]. For calculations with the 2-site model, the electrolyte was assumed to be NaNO₃, although two studies used KNO₃[##UREF##19##24##,##REF##10469549##25##] and one used NaClO₄[##REF##16168423##28##]. The 1-site monodentate model produced a V(Y) of 634 for all of the compiled data (n_p= 73), whereas the 2-site bidentate model resulted in a significantly better fit to the complete dataset (V(Y) = 281; Fig. ##FIG##5##6##). The adsorption edge reported by Ikhsan et al. [##REF##10469549##25##] is in reasonable agreement with predictions from the 1-site monodentate model derived independently in this study (Fig. ##FIG##5##6A##). The 2-site bidentate model yields a pH₅₀within ~0.3 of the measured pH₅₀, but the predicted edge is steeper than the data of Ikhsan et al. [##REF##10469549##25##]. Both models predict saturation of the surface at less than 100% for the conditions reported by Peacock and Sherman ([##UREF##20##27##]; Fig. ##FIG##5##6B##). The 2-site bidentate model produces a reasonable fit to both datasets reported by Jung et al. [##UREF##19##24##], while the 1-site monodentate model underestimates the amount of Cu adsorbed (Fig. ##FIG##5##6C##). The 1-site mondentate model is in slightly better agreement with the data of Hizal and Apak [##REF##16168423##28##] at high pH compared to the 2-site bidentate model, which produces a steeper edge, but both models underestimate adsorption compared to the data at lower pH (Fig. ##FIG##5##6D##).</p>", "<p>The general agreement between the predicted edges from the model derived here and data from four independent studies using different ionic strength, background electrolyte, sorbate/sorbent ratio and kaolinite specimens is encouraging. Discrepancies between model predictions and these experiments could be due to differences in experimental conditions, for example in the choice of background electrolyte (e.g., KNO₃or NaClO₄rather than NaNO₃). Another possibility is that the disagreement reflects differences in the purity, solid solution chemistry, defect structure or other characteristics of the kaolinite specimens. Differences in measured N₂-BET surface areas of the kaolinite specimens may also play a role in the model misfits. For example, Peacock and Sherman [##UREF##20##27##] report an N₂BET surface area of 12.2 m²/g for the Cornwall kaolinite used in their study. This, combined with the site density of 10 sites/nm²chosen here, results in saturation of the surface at ~80%, and underestimates the percentage of Cu adsorbed reported by Peacock and Sherman [##UREF##20##27##]. Increasing the surface area to 25.7 m²/g (as measured for the Wards sample in this study) results in much better agreement with the reported data (Fig. ##FIG##5##6B##). The significant dependence of derived stability constants on measured surface area and choice of site density is well known (e.g. [##UREF##32##40##,##UREF##35##43##]), and may prove to be particularly problematic in the application of surface complexation models to natural sediments, where reactive surface area is difficult to assess [##UREF##2##3##].</p>", "<title>Cu adsorption on mixture of kaolinite and hydrous ferric oxide</title>", "<p>Cu adsorption was measured on mixtures of HFO and kaolinite (both Wards and KGa) at a range of conditions, although most experiments were conducted in 0.01 M NaNO₃and using 10^-5M Cu. Total solid concentrations ranged from 4 g/L to 7.5 g/L and ratios of kaolinite to HFO ranged from 1:1 to 500:1. As might be expected, adsorption increases at a given pH, ionic strength and sorbate/sorbent ratio with increasing quantities of HFO (Fig. ##FIG##6##7##). Several experiments were conducted with base titration (closed symbols), followed by acid titration (open symbols), to test for hysteresis. Within the experimental uncertainty, no significant hysteresis was observed.</p>", "<p>Goodness-of-fit parameters for the mixed solid systems (n_p= 255) were assessed for various combinations of the single solid models discussed above (Table ##TAB##3##4##). The resulting V(Y) range from 12.6 to 58.2, with values typically intermediate between those obtained for the pure HFO and pure kaolinite systems. In the pure systems, the 1-site HFO model and the 1-site monodentate variable charge kaolinite model produced the lowest V(Y) values (12.2 and 23.3, respectively). Combining these two models yields V(Y) = 14.1 (Fig. ##FIG##6##7##). Although this is not the lowest V(Y) obtained by combining individual solid models, it is not statistically distinguishable from the lowest value of 12.6 (Fig. ##FIG##7##8##), obtained by combining the 1-site HFO model with the 2-site monodentate kaolinite model, without sorption of Cu on the ion exchange site, at the 95% confidence interval.</p>", "<p>Although combining the simplest models producing statistically indistinguishable V(Y) values for the individual systems is conceptually appealing, these models may not represent the best DLM descriptions of the systems. As discussed above, the 2-site HFO model of Dzombak and Morel [##UREF##3##4##] produces a visually better fit to the HFO data and has been calibrated for a greater breadth of data than the 1-site HFO model presented above. Combining the 1-site monodentate kaolinite model with the 2-site HFO model results in a V(Y) of 18.0 (Fig. ##FIG##8##9##). As can be seen in Figs. ##FIG##6##7## and ##FIG##8##9##, combining either HFO model with the 1-site monodentate kaolinite model produces a reasonable fit to the measured edges, although in both cases sorption is overestimated for experiments with the greatest kaolinite to HFO ratio. Use of the 2-site HFO model produces a better prediction of the dependence of sorption on sorbate/sorbent ratio (Figs. ##FIG##6##7A##, ##FIG##8##9A##; yellow data/lines).</p>", "<p>As discussed above, the 2-site kaolinite model with inclusion of an ion exchange site that does not significantly bind Cu may be preferable to the simpler 1-site model because of its potential for representing adsorption of weaker ions to kaolinite in mixed metal solutions. Combining the 1-site or 2-site HFO models with the 2-site bidentate kaolinite model produces V(Y) values of 15.9 and 13.6, respectively (Figs. ##FIG##9##10##, ##FIG##10##11##). The resulting edges are again somewhat steeper than the experimental data, but do adequately capture the dependence of the edges on kaolinite to HFO ratios.</p>", "<p>In all cases, surface complexation models calibrated for the single mineral systems do an adequate job of describing metal adsorption in the mixed solid systems. Goodness-of-fit parameters are intermediate between those obtained for the pure HFO and pure kaolinite systems. Discrepancies between model predictions and measured data are similar to those observed in the pure mineral systems. For example, edges that are too steep are produced from kaolinite models assuming bidentate adsorption of Cu in both the pure and mixed mineral systems. Similarly, the 2-site HFO model produces better descriptions of the dependence of Cu sorption on sorbate/sorbent ratio in both pure and mixed mineral systems. The relatively good fits (low V(Y)) obtained for predicted Cu sorption in mixed mineral systems suggest that the stability constants obtained for the pure mineral systems are reasonably robust, and even more importantly, that HFO-kaolinite interactions need not be explicitly included in the speciation model. In other words, a simple component additivity approach produces predictions for the mixed mineral systems that are as good as those for the calibrated pure mineral systems. However, it is important to point out that these experiments were conducted over a relatively brief temporal scale (days). It is possible that aging over months or years may produce surface coatings that physically or chemically block ion adsorption sites. This must be tested using further experimental work, together with adsorption studies on natural sediments and soils.</p>" ]

[ "<title>Conclusion</title>", "<p>This study demonstrates that a simple diffuse layer surface complexation model produces reasonable descriptions of Cu adsorption on HFO and kaolinite over a range of pH, ionic strength, and sorbate/sorbent ratios. In particular, Cu adsorption on kaolinite can be adequately modeled using a very simple DLM with formation of a monodentate Cu complex on a single amphoteric variable-charge site. However, if this model approach is to be extended to natural systems, which contain many other cations, a 2-site approach may be required. Thus, a 2-site kaolinite model, including both a permanent charge and a variable charge site, is developed.</p>", "<p>Cu adsorption on mixtures of HFO and kaolinite is predicted reasonably well using a simple component additivity approach, with the DLM parameters derived for the pure mineral systems. Goodness-of-fit values derived for the predicted fits, together with visual inspection of the predictions, suggests that discrepancies between models and data for the mixed mineral systems are similar to those observed for the pure mineral systems. Thus, interactions between the kaolinite and the HFO, such as blocking of ion exchange or variable charge sites, can be neglected in the speciation calculations. However, it is important to note that all of the experiments in this study were conducted over short temporal scales, and that aging could produce coatings or other physical changes not apparent in the present study. Further experiments must be completed using longer timescales to assess the possible effects of aging on Cu speciation in mixed solid systems. Nonetheless, the results of this study are encouraging, suggesting that relatively simple models with few adjustable parameters may produce useful predictions of metal speciation in natural sediments and soils containing many solid components. However, it is also important to note that testing the component additivity approach for simple systems such as this is only a first step toward application of the component additivity approach to field settings. Even if mineral-mineral interactions can be ignored, methods must still be developed to assess reactive surface areas in field settings if the component additivity approach is to gain widespread use.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The application of surface complexation models (SCMs) to natural sediments and soils is hindered by a lack of consistent models and data for large suites of metals and minerals of interest. Furthermore, the surface complexation approach has mostly been developed and tested for single solid systems. Few studies have extended the SCM approach to systems containing multiple solids.</p>", "<title>Results</title>", "<p>Cu adsorption was measured on pure hydrous ferric oxide (HFO), pure kaolinite (from two sources) and in systems containing mixtures of HFO and kaolinite over a wide range of pH, ionic strength, sorbate/sorbent ratios and, for the mixed solid systems, using a range of kaolinite/HFO ratios. Cu adsorption data measured for the HFO and kaolinite systems was used to derive diffuse layer surface complexation models (DLMs) describing Cu adsorption. Cu adsorption on HFO is reasonably well described using a 1-site or 2-site DLM. Adsorption of Cu on kaolinite could be described using a simple 1-site DLM with formation of a monodentate Cu complex on a variable charge surface site. However, for consistency with models derived for weaker sorbing cations, a 2-site DLM with a variable charge and a permanent charge site was also developed.</p>", "<title>Conclusion</title>", "<p>Component additivity predictions of speciation in mixed mineral systems based on DLM parameters derived for the pure mineral systems were in good agreement with measured data. Discrepancies between the model predictions and measured data were similar to those observed for the calibrated pure mineral systems. The results suggest that quantifying specific interactions between HFO and kaolinite in speciation models may not be necessary. However, before the component additivity approach can be applied to natural sediments and soils, the effects of aging must be further studied and methods must be developed to estimate reactive surface areas of solid constituents in natural samples.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>All authors contributed to the design of the experiments and the modeling approach. TJL and MSS carried out all experiments. CMK conceived the study, participated in the design and coordination of all experiments and, together with TJL, drafted the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This study was supported by a grant from the National Science Foundation CAREER program (NSF-EAR 0348435). Dr. Ray Ferrell at Louisiana State University kindly provided XRD analyses for the kaolinite purchased from Ward's Scientific. Johnson Haas provided helpful comments on an initial draft of the paper. TJL, SD and CJL appreciate additional support from the Western Michigan University graduate and undergraduate research and creative activities funds. Helpful comments from the handling editor and two anonymous reviewers are also very much appreciated.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Cu adsorption as a function of pH on HFO</bold>. Solid concentration is 2 g/L. Lines indicate fits for (A) Dzombak and Morel [##UREF##3##4##] 2-site HFO model and (B) Sverjensky and Sahai [##UREF##30##38##] 1-site HFO model calculated using parameters shown in Tables 1 and 2. Replicate experiments (0.1 M NaNO₃and 10^-5M Cu) are distinguished by separate symbols.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Cu adsorption as a function of pH on kaolinite</bold>. Solid concentration is 2 g/L unless noted otherwise. Lines indicate fits for 1-site model with formation of a monodentate Cu complex on a variable charge site for (A) KGa and (B) Wards data. Model fits calculated using parameters shown in Tables 1 and 2. Replicate experiments (0.1 M NaNO₃and 10^-5M Cu; 0.1 M NaNO₃and 10^-4M Cu; 0.02 M NaNO₃and 10^-5M Cu;) are distinguished by separate symbols.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Cu adsorption as a function of pH on kaolinite</bold>. Solid concentration is 2 g/L unless noted otherwise. Lines indicate fits for 1-site model with formation of a bidentate Cu complex on a variable charge site for (A) KGa and (B) Wards data. Model fits calculated using parameters shown in Tables 1 and 2. Replicate experiments (0.1 M NaNO₃and 10^-5M Cu; 0.1 M NaNO₃and 10^-4M Cu; 0.02 M NaNO₃and 10^-5M Cu;) are distinguished by separate symbols.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Cu adsorption as a function of pH on kaolinite</bold>. Solid concentration is 2 g/L unless noted otherwise. Lines indicate fits for 2-site model with formation of a monodentate Cu complex on a variable charge site and Cu sorption on an ion exchange site site (A) KGa and (B) Wards data. Model fits calculated using parameters shown in Tables 1 and 2. Replicate experiments (0.1 M NaNO₃and 10^-5M Cu; 0.1 M NaNO₃and 10^-4M Cu; 0.02 M NaNO₃and 10^-5M Cu;) are distinguished by separate symbols.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Cu adsorption as a function of pH on kaolinite</bold>. Solid concentration is 2 g/L unless noted otherwise. Lines indicate fits for 2-site model with formation of a bidentate Cu complex on a variable charge site and an ion exchange site that that does not bind Cu for (A) KGa and (B) Wards data. Model fits calculated using parameters shown in Tables 1 and 2. Replicate experiments (0.1 M NaNO₃and 10^-5M Cu; 0.1 M NaNO₃and 10^-4M Cu; 0.02 M NaNO₃and 10^-5M Cu;) are distinguished by separate symbols.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Comparisons 1-site and 2-site kaolinite models with previously reported data</bold>. The 1-site model includes a monodentate Cu complex on a variable charge site. The 2-site model includes a bidentate cu complex on a variable charge site and an ion exchange site that does not bid Cu (parameters shown in Table 2). Data is from: (A) Ikhsan et al. [##REF##10469549##25##] for 0.005 M KNO₃, 10^-4M Cu, 6.8 g/L kaolinite with 14.73 m²/g surface area, (B) Peacock and Sherman [##UREF##20##27##] for 0.1 M NaNO₃, 3.93·10^-4M Cu, 3.33 g/L kaolinite with 12.2 m²/g, (C) Jung et al. [##UREF##19##24##] for 0.01 or 0.1 M KNO₃, 10^-4M Cu, 2.0 g/L kaolinite with 7.99 m²/g and (D) Hizal and Apak [##REF##16168423##28##] with 0.1 M NaClO₄, 1.57·10^-4M Cu, 50 g/L kaolinite with 26.68 m²/g (Clay II) or 17.8 m²/g (Clay III).</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p><bold>Predicted Cu adsorption as a function of pH on mixtures of kaolinite and HFO</bold>. Lines indicate fits using the Sverjensky and Sahai [##UREF##30##38##] 1-site HFO model and 1-site kaolinite model with formation of a monodentate Cu complex on a variable charge site. Model fits calculated using parameters shown in Tables 1, 2 and 3. Open and closed symbols indicate experiments with base titration (closed symbols) followed by acid titration (open symbols).</p></caption></fig>", "<fig position=\"float\" id=\"F8\"><label>Figure 8</label><caption><p><bold>Predicted Cu adsorption as a function of pH on mixtures of kaolinite and HFO</bold>. Lines indicate fits using the Sverjensky and Sahai [##UREF##30##38##] 1-site HFO model and 2-site kaolinite model with formation of a monodentate Cu complex on a variable charge site and no Cu adsorption on the ion exchange site. Model fits calculated using parameters shown in Tables 1, 2 and 3. Open and closed symbols indicate experiments with base titration (closed symbols) followed by acid titration (open symbols).</p></caption></fig>", "<fig position=\"float\" id=\"F9\"><label>Figure 9</label><caption><p><bold>Predicted Cu adsorption as a function of pH on mixtures of kaolinite and HFO</bold>. Lines indicate fits using the Dzombak and Morel [##UREF##3##4##] 2-site HFO model and the 1-site kaolinite model with formation of a monodentate Cu complex on a variable charge site. Model fits calculated using parameters shown in Tables 1, 2 and 3. Open and closed symbols indicate experiments with base titration (closed symbols) followed by acid titration (open symbols).</p></caption></fig>", "<fig position=\"float\" id=\"F10\"><label>Figure 10</label><caption><p><bold>Predicted Cu adsorption as a function of pH on mixtures of kaolinite and HFO</bold>. Lines indicate fits using the Sverjensky and Sahai [##UREF##30##38##] 1-site HFO model and the 2-site kaolinite model with formation of a bidentate Cu complex on a variable charge site and an ion exchange site that does not bind Cu. Model fits calculated using parameters shown in Tables 1, 2 and 3. Open and closed symbols indicate experiments with base titration (closed symbols) followed by acid titration (open symbols).</p></caption></fig>", "<fig position=\"float\" id=\"F11\"><label>Figure 11</label><caption><p><bold>Predicted Cu adsorption as a function of pH on mixtures of kaolinite and HFO</bold>. Lines indicate fits using the Dzombak and Morel [##UREF##3##4##] 2-site HFO model and the 2-site kaolinite model with formation of a bidentate Cu complex on a variable charge site and an ion exchange site that does not bind Cu. Model fits calculated using parameters shown in Tables 1, 2 and 3. Open and closed symbols indicate experiments with base titration (closed symbols) followed by acid titration (open symbols).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Surface areas, surface site types and site densities used in DLM calculations.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Solid</bold></td><td align=\"left\"><bold>Surface Area (m²/g)</bold></td><td align=\"left\"><bold>Site Types</bold></td><td align=\"left\"><bold>Site Density (μmol/m²)</bold></td></tr></thead><tbody><tr><td align=\"left\">HFO (2-site model)</td><td align=\"left\">600^[4]</td><td align=\"left\">&gt;Fe_(s)OH</td><td align=\"left\">0.094^[4]</td></tr><tr><td/><td/><td align=\"left\">&gt;Fe_(w)OH</td><td align=\"left\">3.74^[4]</td></tr><tr><td align=\"left\">HFO (1-site model)</td><td align=\"left\">600^[4]</td><td align=\"left\">&gt;FeOH</td><td align=\"left\">16.6^[38]</td></tr><tr><td align=\"left\">Kaolinite (KGa)</td><td align=\"left\">13.6 (this study)</td><td align=\"left\">&gt;SOH</td><td align=\"left\">16.6^[38]</td></tr><tr><td/><td/><td align=\"left\">X</td><td align=\"left\">2.2^a</td></tr><tr><td align=\"left\">Kaolinite (Wards)</td><td align=\"left\">25.7 (this study)</td><td align=\"left\">&gt;SOH</td><td align=\"left\">16.6^[38]</td></tr><tr><td/><td/><td align=\"left\">X</td><td align=\"left\">1.2^a</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Reaction stoichiometries and stability constants used in DLM calculations for HFO. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Reaction</bold></td><td align=\"left\"><bold>Log Stability Constant</bold></td><td align=\"left\"><bold>V(Y) (V(Y)_min, V(Y)_max)</bold></td></tr></thead><tbody><tr><td align=\"left\"><italic>HFO (2-site model):</italic></td><td/><td/></tr><tr><td align=\"left\">&gt;Fe_(s)OH + H⁺_(aq)= &gt;Fe_(s)OH₂⁺</td><td align=\"left\">7.29^[4]</td><td/></tr><tr><td align=\"left\">&gt;Fe_(w)OH+ H⁺_(aq)= &gt;Fe_(w)OH₂⁺</td><td align=\"left\">7.29^[4]</td><td/></tr><tr><td align=\"left\">&gt;Fe_(s)OH = &gt;Fe_(s)O^-+ H⁺_(aq)</td><td align=\"left\">-8.93^[4]</td><td/></tr><tr><td align=\"left\">&gt;Fe_(w)OH = &gt;Fe_(w)O^-+ H⁺_(aq)</td><td align=\"left\">-8.93^[4]</td><td align=\"left\">14.0</td></tr><tr><td align=\"left\">&gt;Fe_(s)OH + Cu⁺²_(aq)= &gt;Fe_(s)OCu⁺+ H⁺_(aq)</td><td align=\"left\">2.89^[4]</td><td align=\"left\">(10.9, 18.5)</td></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>HFO (1-site model):</italic></td><td/><td/></tr><tr><td align=\"left\">&gt;FeOH + H⁺_(aq)= &gt;FeOH₂⁺</td><td align=\"left\">7.5^[38]</td><td/></tr><tr><td align=\"left\">&gt;FeOH = &gt;FeO^-+ H⁺_(aq)</td><td align=\"left\">-10.2^[38]</td><td align=\"left\">12.2</td></tr><tr><td align=\"left\">&gt;FeOH + Cu⁺²_(aq)= &gt;FeOCu⁺+ H⁺_(aq)</td><td align=\"left\">0.98 (this study)</td><td align=\"left\">(9.5, 16.1)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Reaction stoichiometries and stability constants used in DLM calculations for kaolinite. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Reaction</bold></td><td align=\"left\"><bold>Log Stability Constant</bold></td><td align=\"left\"><bold>V(Y) (V_min(Y), V_max(Y))</bold></td></tr></thead><tbody><tr><td align=\"left\">&gt;KaoliniteOH + H⁺_(aq)= &gt;KaoliniteOH₂⁺</td><td align=\"left\">2.1^[38]</td><td/></tr><tr><td align=\"left\">&gt;KaoliniteOH = &gt;KaoliniteO^-+ H⁺_(aq)</td><td align=\"left\">-8.1^[38]</td><td/></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Monodentate variable charge site:</italic></td><td/><td align=\"left\">23.3</td></tr><tr><td align=\"left\">&gt;KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteOCu⁺+ H⁺_(aq)</td><td align=\"left\">-1.7 (this study)</td><td align=\"left\">(20.2, 27.1)</td></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Bidentate variable charge site:</italic></td><td/><td align=\"left\">28.5</td></tr><tr><td align=\"left\">2 &gt; KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteO₂Cu + 2H⁺_(aq)</td><td align=\"left\">-4.6 (this study)</td><td align=\"left\">(24.8, 33.2)</td></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Monodentate variable charge + ion exchange site (all log K's fit in this study):</italic></td><td/><td/></tr><tr><td align=\"left\">&gt;KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteOCu⁺+ H⁺_(aq)</td><td align=\"left\">-1.9 (this study)</td><td/></tr><tr><td align=\"left\">X(Na) + H⁺_(aq)= X(H) + Na⁺_(aq)</td><td align=\"left\">4.1 (this study)</td><td align=\"left\">44.9</td></tr><tr><td align=\"left\">2X(Na) + Cu⁺²_(aq)= X₂(Cu) + 2Na⁺_(aq)</td><td align=\"left\">0.72 (this study)</td><td align=\"left\">(38.9, 52.2)</td></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Monodentate variable charge + ion exchange site model (fixed Na-H exchange stability constant):</italic></td><td/><td/></tr><tr><td align=\"left\">&gt;KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteOCu⁺+ H⁺_(aq)</td><td align=\"left\">-2.3 (this study)</td><td/></tr><tr><td align=\"left\">X(Na) + H⁺_(aq)= X(H) + Na⁺_(aq)</td><td align=\"left\">4.3 (this study)</td><td align=\"left\">108</td></tr><tr><td align=\"left\">2X(Na) + Cu⁺²_(aq)= X₂(Cu) + 2Na⁺_(aq)</td><td align=\"left\">2.5^[7]</td><td align=\"left\">(93.6, 126)</td></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Bidentate variable charge + ion exchange site model (fixed Na-H exchange stability constant):</italic></td><td align=\"left\">-5.3 (this study)</td><td/></tr><tr><td align=\"left\">2&gt;KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteO₂Cu + 2H⁺_(aq)</td><td align=\"left\">4.6 (this study)</td><td align=\"left\">62.6</td></tr><tr><td align=\"left\">X(Na) + H⁺_(aq)= X(H) + Na⁺_(aq)</td><td align=\"left\">2.5^[7]</td><td align=\"left\">(54.4, 72.9)</td></tr><tr><td align=\"left\">2X(Na) + Cu⁺²_(aq)= X₂(Cu) + 2Na⁺_(aq)</td><td/><td/></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Monodentate variable charge + ion exchange site model, no Cu sorption on ion exchange site (fixed Na-H exchange stability constant):</italic></td><td align=\"left\">-1.8 (this study)<break/>2.5^[7]</td><td align=\"left\">190<break/>(165, 221)</td></tr><tr><td align=\"left\">&gt;KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteOCu⁺+ H⁺_(aq)</td><td/><td/></tr><tr><td align=\"left\">X(Na) + H⁺_(aq)= X(H) + Na⁺_(aq)</td><td/><td/></tr><tr><td/><td/><td/></tr><tr><td align=\"left\"><italic>Bidentate variable charge + ion exchange site model, no Cu sorption on ion exchange site (fixed Na-H exchange stability constant):</italic></td><td align=\"left\">-4.6 (this study)<break/>2.5^[7]</td><td align=\"left\">33.8<break/>(29.4, 39.3)</td></tr><tr><td align=\"left\">2 &gt; KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteO₂Cu + 2H⁺_(aq)</td><td/><td/></tr><tr><td align=\"left\">X(Na) + H⁺_(aq)= X(H) + Na⁺_(aq)</td><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Average goodness-of-fit parameters (V(Y)) and 95% confidence intervals of V(Y) for the fit of each model to all of the Cu on kaolinite + HFO adsorption edge data (n_p= 255). Exchange site models use reaction (7) stability constant of 2.5 from Landry et al. [##UREF##6##7##]</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Model HFO/Kaolinite</bold></td><td align=\"left\"><bold>V(Y) (V_min(Y), V_max(Y))</bold></td></tr></thead><tbody><tr><td align=\"left\"><italic>DM/MV</italic></td><td align=\"left\">18.0 (15.2, 21.6)</td></tr><tr><td align=\"left\"><italic>DM/BV</italic></td><td align=\"left\">13.6 (11.5, 16.3)</td></tr><tr><td align=\"left\"><italic>DM/MVE</italic></td><td align=\"left\">58.2 (49.3, 69.8)</td></tr><tr><td align=\"left\"><italic>DM/BVE</italic></td><td align=\"left\">27.0 (22.8, 32.3)</td></tr><tr><td align=\"left\"><italic>DM/MVE(noCu)</italic></td><td align=\"left\">21.6 (18.3, 25.9)</td></tr><tr><td align=\"left\"><bold><italic>DM/BVE(noCu)</italic></bold></td><td align=\"left\"><bold>13.6 (11.5, 16.3)</bold></td></tr><tr><td/><td/></tr><tr><td align=\"left\"><italic>SS/MV</italic></td><td align=\"left\">14.1 (12.0, 16.9)</td></tr><tr><td align=\"left\"><italic>SS/BV</italic></td><td align=\"left\">15.9 (13.5, 19.1)</td></tr><tr><td align=\"left\"><italic>SS/MVE</italic></td><td align=\"left\">19.2 (16.3, 23.1)</td></tr><tr><td align=\"left\"><italic>SS/BVE</italic></td><td align=\"left\">29.1 (24.6, 34.9)</td></tr><tr><td align=\"left\"><italic>SS/MVE(noCu)</italic></td><td align=\"left\">12.6 (10.7, 15.1)</td></tr><tr><td align=\"left\"><italic>SS/BVE(noCu)</italic></td><td align=\"left\">15.9 (13.5, 19.1)</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula id=\"bmcM1\"><label>(1)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1467-4866-9-9-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>V</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>Y</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>Q</mml:mi></mml:mrow></mml:munder><mml:mrow><mml:msup><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mi>Y</mml:mi><mml:mrow><mml:msub><mml:mi>s</mml:mi><mml:mi>Y</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:mstyle></mml:mrow><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>×</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>Q</mml:mi></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>R</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM2\"><label>(2)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\" name=\"1467-4866-9-9-i2\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mfrac><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mi>Q</mml:mi></mml:msub><mml:mo>×</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>P</mml:mi></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>R</mml:mi></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>∗</mml:mo><mml:mi>V</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>Y</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:msubsup><mml:mi>χ</mml:mi><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>α</mml:mi><mml:mo>/</mml:mo><mml:mn>2</mml:mn></mml:mrow><mml:mn>2</mml:mn></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>,</mml:mo><mml:mfrac><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mi>Q</mml:mi></mml:msub><mml:mo>×</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>P</mml:mi></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>R</mml:mi></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>∗</mml:mo><mml:mi>V</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>Y</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:msubsup><mml:mi>χ</mml:mi><mml:mrow><mml:mi>α</mml:mi><mml:mo>/</mml:mo><mml:mn>2</mml:mn></mml:mrow><mml:mn>2</mml:mn></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM3\"><label>(3)</label>&gt;Fe_(s)OH + Cu⁺²_(aq)= &gt;Fe_(s)OCu⁺+ H⁺_(aq).</disp-formula>", "<disp-formula id=\"bmcM4\"><label>(4)</label>&gt;FeOH + Cu⁺²_(aq)= &gt;FeOCu⁺+ H⁺_(aq).</disp-formula>", "<disp-formula id=\"bmcM5\"><label>(5)</label>&gt;KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteOCu⁺+ H⁺_(aq).</disp-formula>", "<disp-formula id=\"bmcM6\"><label>(6)</label>2 &gt; KaoliniteOH + Cu⁺²_(aq)= &gt;KaoliniteO₂Cu + 2H⁺_(aq),</disp-formula>", "<disp-formula id=\"bmcM7\"><label>(7)</label>X(Na) + H⁺_(aq)= X(H) + Na⁺_(aq)and</disp-formula>", "<disp-formula id=\"bmcM8\"><label>(8)</label>2X(Na) + Cu⁺²_(aq)= X₂(Cu) + 2Na⁺_(aq),</disp-formula>" ]

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[ "<table-wrap-foot><p>a. From CEC (3.0 meq/100 g) measured by Bordon and Giese [##UREF##33##41##] for kaolinite KGA-1b</p></table-wrap-foot>", "<table-wrap-foot><p>Average goodness-of-fit parameters (V(Y)) and 95% confidence intervals of V(Y) are for the fit of each model to all of the Cu on HFO adsorption edge data (n_p= 61).</p></table-wrap-foot>", "<table-wrap-foot><p>The same protonation/deprotonation constants for the variable charge site is used in all models. Average goodness-of-fit parameters (V(Y)) and 95% confidence intervals of V(Y) are for the fit of each model to all of the Cu on kaolinite adsorption edge data (n_p= 360).</p></table-wrap-foot>", "<table-wrap-foot><p>DM = 2-site HFO model from [##UREF##3##4##]</p><p>SS = 1-site HFO model</p><p>MV = 1-site monodentate variable charge kaolinite model</p><p>BV = 1-site bidentate variable charge kaolinite model</p><p>MVE = 2-site kaolinite model with monodentate variable charge and ion exchange site</p><p>MVB = 2-site kaolinite model with bidentate variable charge and ion exchange site</p><p>MVE(noCu) = 2-site kaolinite model with monodentate variable charge and ion exchange site (no Cu Sorption on exchange site)</p><p>MVBnoCu) = 2-site kaolinite model with bidentate variable charge and ion exchange site (no Cu Sorption on exchange site)</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>The International Conference of Population and Development (ICPD) held in Cairo in 1994, presented a Program of Action (PoA) which had pledges to achieve the goal of universal access to reproductive health (RH) services for every one in all countries till 2015 [##UREF##0##1##,##UREF##1##2##]. In all, 179 countries became signatories and pledged to make change in their legislation and reproductive health (RH) related policies according to program of action. Five years later in 1999, a review of ICPD-PoA, known as ICPD+5 revealed that there was a need of sufficient domestic and external resources to be invested in order to achieve the goals of ICPD in next 15 years in many countries. In 2000, world leaders expressed that there is a need to have explicit goals to measure the pace of socio-economic development at country level all over the world. Among these goals, one explicit goal was on universal access to RH information and services, similar to the one described in ICPD-POA. In the same year, there was UN Millennium Summit where the transformation of International Development Goals (IDGs) into the Millennium Development goals (MDGs) took place. However, surprisingly only eight goals instead of nine were presented; the goal on the RH was dropped [##UREF##2##3##]. However, after lobbying by many governments, nongovernmental organizations and others, world leaders at the September 2005 UN World Summit in New York endorsed incorporating universal access to reproductive health into the MDGs. A comprehensive review of ICPD at the mid point to 2015 was recognized in 2004 as ICPD+10, which yet again discovered many countries lagging behind in RH indicator nor they are anyway near to the progress demonstrated in developing regions of the world [##UREF##3##4##,##UREF##4##5##].</p>", "<p>Pakistan is the signatory of ICPD's PoA and MDGs both and the Government of Pakistan is geared to achieve the targets till 2015. Although, ICPD agenda sets a ground for all the countries to ensure the access to RH through primary health care (PHC), yet all the programs and the health care system in the country failed to ensure the provision of essential RH services such as RH education, family planning counseling, safe delivery services, post-natal and safe abortion services to the majority of women population in the country [##UREF##5##6##]. For addressing this alarming situation and dismal state of RH and women's health indicators in the country, it becomes imperative to identify \"the missing links\" between the ICPD agenda, government's policies, national programs, and the efforts launched to achieve MDGs. This paper explores the gaps and missing links in the journey from ICPD 1994 to MDGs 2001. The conclusions are drawn for identifying the commonalities between ICPD and millennium agendas other international treaties and government's policies, strategic plans and programs to suggest modalities to embark upon or scale up concrete initiatives for achieving MDGs.</p>", "<title>Methodology</title>", "<p>Literature review was carried out for the period of 1994–2001, thus selecting the published literature on either ICPD or MDGs using Google, Medline and websites of various organizations. Key words used for the search included Millennium Development Goals; ICPD; Reproductive health; Developing Countries; and Pakistan. Peer reviewed articles, reports, strategy papers and official publications of government, UN agencies, World Health Organization, multilateral and international donors, NGOs and various MDGs monitoring agencies were consulted. For describing the scenario in the local context, a search period of 1994–2005 was determined in which official documents and reports of Government of Pakistan were reviewed.</p>" ]

[ "<title>Methodology</title>", "<p>Literature review was carried out for the period of 1994–2001, thus selecting the published literature on either ICPD or MDGs using Google, Medline and websites of various organizations. Key words used for the search included Millennium Development Goals; ICPD; Reproductive health; Developing Countries; and Pakistan. Peer reviewed articles, reports, strategy papers and official publications of government, UN agencies, World Health Organization, multilateral and international donors, NGOs and various MDGs monitoring agencies were consulted. For describing the scenario in the local context, a search period of 1994–2005 was determined in which official documents and reports of Government of Pakistan were reviewed.</p>" ]

[ "<title>Results</title>", "<title>International response to reproductive health</title>", "<p>For addressing the pace of population growth and related issues in developing countries, United Nations held a conference at Cairo in 1994. One of the outcomes of this conference was the call of new paradigm in reproductive health. This new paradigm increases the emphasis on human rights, human development and individual well-being which should be the center of all RH related programs and policies [##UREF##1##2##]. The key goals which were embedded in the ICPD-PoA were:</p>", "<p>• By 2005, 60% of primary health care and family planning facilities should offer the widest achievable range of safe and effective family planning methods, essential obstetric care, prevention and management of reproductive tract infections, including sexually transmitted infections (STIs), and barrier methods to prevent infection; 80% of facilities should offer such services by 2010, and all should do so by 2015.</p>", "<p>• Skilled attendants should assist at least 40% of all births where the maternal mortality rate is very high; and 80% globally by 2005. This coverage should be 50% and 85% by 2010; and 60% and 90% by 2015.</p>", "<p>• The gap between the proportion of individuals using contraceptives and the proportion expressing a desire to space or limit their families should be reduced by half by 2005, by 75% by 2010, and by 100% by 2015 [##UREF##1##2##].</p>", "<p>Among the 15 principles of PoA, it was clear that issues such as family planning, infant mortality and morbidity, maternal mortality and morbidity and sexually transmitted infections (STIs) have been placed in such context where these are sighted from the broader angle of RH for women and men of all ages. Empowerment of women through ensuring their ability to control their own fertility is the cornerstone of population and development-related programs. The right based approach is the major theme of ICPD inclusive of inclusive of STIs and prevention of HIV, human sexuality and gender relations, reproductive rights for adolescents, family planning. In pursuance, all the countries agreed to provide RH services accessible through primary health care system. After five years (in 1999), another session was held in which all the ICPD signatories and European Union got together and adopted a document named \"Key actions for the further implementation of the Program of Action of ICPD\". At this stage one particular addition was the inclusion of HIV/AIDS preventive services especially for pregnant women. The major focus of this conference was to how to overcome the identified barriers for achieving the goals set in Cairo particularly human and legal impediments in access of services. At least 20% of resources for RH programs were suggested to be earmarked for meeting the adolescents' information and services needs [##UREF##6##7##].</p>", "<p>With the agenda to provide development in the economical, social and environmental domains, the international community adopted the International Development Goals (IDGs). Interestingly, one goal was exclusively on providing and improving access to RH services for all females of appropriate age [##UREF##7##8##]. In the year 2001, MDGs were introduced whereby RH was not included at all in the eight goals. Several reasons have been quoted so far among which most cited is the difficulty for the governments to sustain the commitment to broader rights issue, while facing the opposition around the world [##REF##15828526##9##]. However, goals 4–6 still address RH directly i.e. maternal health, infant mortality and HIV/AIDS.</p>", "<p>In 2004, the 37^thsession of the United Nations Commission on Population and Development undertook a comprehensive review of progress in the last ten years (known as ICPD+10) on all aspects of the ICPD PoA. ICPD+10 acknowledged that full implementation of the Cairo agenda is essential to the attainment of Millennium Development Goals (MDGs), and that this link must be stressed at the five year review of the Millennium Declaration. The main barriers identified, however, remain unresolved. These include inadequacies in the healthcare systems, unclear impact of health sector reforms, lack of a national system for government reporting and accountability, negative impact of development institutions and donor policies and inadequate NGOs' policy advocacy capacity. Ascertaining the position assumed for various themes of ICPD in different international conference held after 1994 till MDGs in 2001 is presented in the Table ##TAB##0##1##.</p>", "<title>Translation of ICPD, program of action in pakistan</title>", "<p>In 1950, Pakistan had a population of about 40 million people; today it is around 160 million [##UREF##8##10##]. According to National Health Survey of Pakistan (1990–94), it was lack of adequate RH services responsible for a high fertility rate and a high maternal mortality ratio in Pakistan. Most of the deliveries 80% were conducted by traditional birth attendants or the near-relatives [##UREF##9##11##]. Pakistan National Health Policy 1997 did reflect the holistic approach to address the issues of RH with the inclusion of rights through primary health care (PHC) as described in ICPD agenda. Despite the government's high level of commitment towards increasing the RH and women's health services, the health of the population suffered a setback due to frequent political changes, the structural adjustment program, inflation and lower social sector allocations. The momentum continued at the policy level under the Ninth Five Year Plan (1999–2003). A draft National RH Policy was proposed in 2000 using the ICPD definition of RH including the ensuring of reproductive rights and women's empowerment for participation in \"all aspects of reproductive decision making on a basis of equality with men\" [##UREF##10##12##]. The policy, however, was never formally approved. On the other hand, progress in term of reaching major targets has been painfully slow [##UREF##11##13##]. Some of the highest rates of under 5 mortality and infant mortality are found in Pakistan [##REF##15070640##14##]. While there is little population-based information on maternal mortality, available data indicate that maternal mortality rates are unacceptably high and also intransigent to change [##UREF##12##15##]. Among others the main challenge is low access (both in terms of availability and affordability) to good quality nutrition and poor management of health care and childhood illnesses. One explanation is inadequate public health expenditure in face of ever increasing demand. According to a report by WHO Commission on Macroeconomics and Health, US$34 per capita is required for a package of essential health services in Pakistan The total expenditure on health in Pakistan is US$18 per capita out of which the total government health expenditure is US$4 per capita, which falls drastically short of the recommended level [##UREF##13##16##]. Pakistan's lack of effort in allocating public resources where needs are high also applies to the health sector. Yet, Pakistan's public expenditure on health stood at just 0.57% of GDP in 2007, the second lowest of the 29 countries of Asia Pacific [##UREF##14##17##]. The government of Pakistan has been spending 0.6 to 1.19% of its GDP and 5.1 to 11.6% of its development expenditure on health over the last 10 years, more than 45% of this meager budget would be consumed by curative services, mostly at tertiary hospitals [##UREF##15##18##]. Due to poor quality and unavailability of basic health care services, the RH of the people is also getting worse. According to Pakistan Demographic and Health Survey (PDHS) 2006–2007, the Total Fertility Rate (TFR) is 4.1 (which was 4.3 in the year 2000) and the contraceptive prevalence rate (CPR) is lower than ever (30 percent), which shows that the country is not on track neither for the MDGs nor for the ICPD. In spite of having a vast infrastructure, the PHC network is under-utilized and provides limited services to the rural and peri-urban populations [##UREF##16##19##,##UREF##17##20##]. A recent survey indicates that, nationally, only 20.6% of the people used the public sector network for their health care needs [##UREF##18##21##].</p>", "<title>Other national policies, programs and projects articulating RH agenda</title>", "<p>In 1997, government revised and updated the first <bold><italic>National Health Policy of 1990</italic></bold>, including the specific objective of \"expending the delivery of RH services including family planning both in urban and rural areas of Pakistan\". At this period of time (1997), there were 4,250 Lady Health Visitors (LHVs) and 50,000 trained birth attendants (TBAs). On the other hand, there were geographical imbalances in the distribution of health facilities and manpower in rural and urban areas. The <bold><italic>National Health Policy of 1997 </italic></bold>were based on the goal \"Health for all\" through PHC, therefore the vision for the health sector development was made for the year 2010. For prevention and treating common ailment at the community level, <bold><italic>the Prime Ministers Program for Family Planning and Primary health care </italic></bold>was started in 1994. There are 100,000 lady health workers (LHW) working in this program with a system of supervision and monitoring of Lady Health Supervisor looking after 20–25 LHWs. In this program, one specific goal is on expanding the family planning services availability in urban slums and rural areas of Pakistan. However, main purpose of the program is to bridge the gap between the community and health services through referral system [##UREF##19##22##,##UREF##20##23##]. In the year 1999, the <bold><italic>RH Service Package </italic></bold>was developed with the joint effort of Ministries of Health and Population Welfare. For providing broad guidelines, eight components of RH were included in this package; comprehensive family planning, maternal health care and safe motherhood, pre and post abortion care, infant health care, prevention of STDs and HIV, management of infertility, detection of breast and cervical cancers, and management of RH related problems of men. This package was aimed to impart all the skills to TBAs, midwives, Lady Health Workers, Lady Health Visitors, health technicians at the Basic Health Units//Rural Health Centers, lady doctors and male doctors. In addition, the package also provides a complete framework for involving NGOs [##UREF##21##24##]. Thereafter, a draft <bold><italic>RH Policy </italic></bold>was also presented in 2000 based on the ICPD's PoA but was never approved by Ministry of Health or Population welfare [##UREF##10##12##]. In the year 2001, the <bold><italic>National Health Policy (NHP) </italic></bold>was presented with overall national vision for the health sector based on \"Health-For-All\" approach. The NHP had ten key areas, among which key area 4 somehow explains the need for gender equity in the health sector focusing on RH services provision to the women of childbearing age at the doorsteps [##UREF##22##25##]. In the same year, <bold><italic>Population Policy </italic></bold>of Pakistan was also launched, which explicitly identified the issues related to increasing population of the country. Fortunately, this policy did carry the core mission of ICPD in its vision, \"to achieve population stabilization by 2020 through the expeditious completion of the demographic transition that entails declines both in fertility and mortality rates\" [##UREF##23##26##]. With the parallel goals of 'eliminating poverty' and 'ensuring gender equity', recognized as essential for achieving RH agenda, <bold><italic>National Policy for Development and Empowerment of Women </italic></bold>was introduced in 2002 which reflected government's yet another reaffirmation on 'women and girls access to quality health care services and all other pre-requisites to enjoying full health, including reproductive and mental health'. Issues such as RH rights, strengthening of basic health facilities, providing affordable and preventive primary health care particularly RH services for the women were addressed in this policy [##UREF##24##27##]. Later on, when many developing countries adopted the <bold><italic>Poverty Reduction Strategy Paper </italic>(PRSP) </bold>with explicit strategies linking MDGs with poverty reduction initiatives, Pakistan introduced its PRSP in 2003. This paper clearly stated that the medium term health strategy is focused towards raising public sector health expenditures through a focus on prevention and control of disease, RH, child health and nutrient deficiencies. In this context, the number of LHWs is increased to 100,000 to provide the PHC at the doorstep through an integrated community based approach [##UREF##25##28##]. Though, RH inclusion is restricted only to some explicit services, the government's intention, however, has attracted some donors' assistance for maternal and child health projects. The government currently is revising the PRSP which again do not reflect RH promotion agenda of ICPD [##UREF##26##29##]. Additional file ##SUPPL##0##1## shows the position of various RH constituents across different policies and strategy papers of government of Pakistan.</p>" ]

[ "<title>Discussion</title>", "<p>The ICPD agenda has been declared as the most comprehensive programme including the goals and targets, which has actually broadened the spectrum of reproductive health. It was a complete paradigm shift for those, who always limited RH to family planning. While the MDGs introduced later were merely indicators to monitor the progress and moreover completely missed a goal encompassing RH agenda of ICPD. Therefore, RH is considered as a 'missing link' for MDGs, despite the fact that some quarters still believe that the essence of RH is present in goal 4 (child mortality), goal 5 (maternal mortality) and goal 6 (HIV/AIDS, Malaria and tuberculosis). If at all we agree that the complex RH agenda of ICPD is present in MDGs, the broader issue of rights which was stitched with RH is clearly dropped in MDGs. The maternal mortality reduction goal, for example, cannot be achieved without access to the full range of reproductive health services, and without empowerment of women. Women need a stronger voice, and there is a need for much stronger reflection of women's own health needs in prioritization of health services.</p>", "<p>In the context of Pakistan government's policies, all efforts had been geared to achieve the targets of MDGs. Hitherto, the policies and programs started after MDGs in Pakistan have missed the true RH agenda altogether. Therefore, the concept of reproductive rights has not been much visible in the policies and the process of women empowerment could never gain real momentum in Pakistan except in last few years. All the programs and projects seldom supported RH issues with rights approach. Lot of focus and investment on maternal and child health programs is yet to deliver results because maternal mortality ratio (MMR) in Pakistan is still one of the highest in the region than the rest of the developing world [##UREF##27##30##]. Maternal mortality ratio is alarmingly high in Pakistan, gone up from 350 per 100,000 live births in 2000–01 to 400 per 100,000 live births in 2004–05 [##UREF##28##31##]. The issue of maternal mortality highlighted in ICPD agenda was linked with unskilled birth attendants. According to a survey done in 2003, only 44% of recent mothers received antenatal care and only 28% delivered in health care facility [##UREF##16##19##]. Another reason which is highlighted through the literature review for frightening maternal mortality ratio is increasing number of unsafe abortions. Abortion has always been inadequately addressed in all of policies (see additional file ##SUPPL##0##1##) because it has always been considered a taboo and made a religious issue. So far, very few studies have been conducted in the country for knowing the burden contributed by unsafe/illegal abortion to the maternal mortality. National study on abortion produced by the Population Council revealed high level of unwanted pregnancy, induced abortion and post-abortion complications [##REF##17385379##32##]. Despite living in the domain of Islam, many countries found workable strategies for this problem by giving it a different position [##UREF##29##33##,##UREF##30##34##]. Another linked issue is the inadequate family planning services which also increase the number of illegal abortions in the country. Lady Health Workers (LHWs) were always considered as the key players in providing FP services at the doorsteps in the communities. Yet after fifteen years, the program has not shown its expected impact; the contraceptive prevalence rate (CPR) is as low as 28–30% [##UREF##28##31##]. Independent evaluations of LHW program pointed out the difficulty faced by LHWs in reaching out to vulnerable populations in the remotest and conservative parts of the country. According to ICPD, there is a need of increasing constructive collaboration among NGOs and government for providing accessible and affordable services of RH to population. NGOs actually helped promoting the services of RH in the country. Despite clear emphasis in ICPD agenda for increasing the donors' contribution to the countries to provide funds to improve their RH indicators [##UREF##31##35##], it did not virtually happene due to continuous changes in donor preferences after MDGs. Among other reasons, the Global Gag Rule consistently reduced the funds for RH programs and projects in many developing countries [##UREF##32##36##]. The case is not different for Pakistan, where many international donor agencies are working but the focus is more towards the programs addressing MDGs on AIDS, TB, Malaria, etc [##UREF##33##37##].</p>", "<p>Several countries are using various frameworks and processes, such as PRSPs, sector wide approaches (SWAps) and administrative reforms to promote the ICPD agenda through international cooperation with donors. For instance, in Canada, the Canadian International Development Agency (CIDA) cooperates with its partners and concerned stakeholders to categorize and promote ICPD-driven priorities, working within national poverty strategies and sector reforms. In Japan, the government employed SWAps and PRSPs proactively and provided support for basic data collection for poverty analysis and for enhancing national capacities to collect, analyze and publicize basic data for implementation of the ICPD PoA. In Norway, the MDGs are used to set priorities and as a reference in the dialogue with development partners to emphasize the significance of addressing such issues as maternal health and the prevention of HIV/AIDS. Sweden also promotes the ICPD and ICPD+5 agenda through PRSPs, SWAps and sector reforms and through constant dialogue with governments and stakeholders participating in programmes pertaining to sexual and RH and rights; the needs of young people; gender equality and the role of men; and HIV/AIDS prevention, care and support. In Switzerland, the Swiss Agency for Development and Cooperation (SDC) has built up its policies, strategies and guidelines aimed at contributing to the achievement of the MDGs and ICPD goals. For instance, its new health policy aims to improve the health of the underprivileged and most vulnerable populations in order to supplement the efforts for poverty reduction and sustainable development. Similarly, in United Kingdom, the Department for International Development (DFID) is advocating the use of PRSP and budgetary support mechanisms based on the priorities expressed by developing countries themselves and where key MDGs and RH indicators are used to follow the progress. In the United States, the Government is placing increased accent on poverty reduction. A 'Millennium Challenge Account' has been created, whereby funds are allocated for poverty-reduction efforts in some partner countries [##UREF##34##38##]. Some of the expected outcomes of working on common grounds between ICPD and MDGs are hence shown in figure ##FIG##0##1##.</p>" ]

[ "<title>Conclusion</title>", "<p>Besides continuous efforts of the international RH community, the donor preference for investing in RH programs did not change much particularly for developing countries like Pakistan. Now after years of inception of MDGs, many countries are still not on track to progress to achieve the targets set out in 2001 and Pakistan is one of these countries lagging behind with maternal and child mortalities rates higher than many developing counties [##UREF##35##39##]. The half way point MDGs monitoring report of the government narrates that MDG 5 on maternal health is one of the most important but most difficult to achieve of the eight goals. The government is committed to work with NGOs and the private sector to complement the information and services that it is itself providing [##UREF##28##31##].</p>", "<p>Pakistan has many policies, programs and projects for giving a proper place to the goals of MDGs. For instance, National Maternal and Child Health Policy put a great deal of emphasis on raising awareness about safe motherhood, newborn's health, family planning and increasing number of skilled human resource. Still the program is not getting the desired outcomes [##UREF##36##40##]. Being a signatory of both of the international agendas (ICPD and MDGs), Pakistan needed to articulate its policies to keep the balance between the two agendas which is, however, not visible. The national policies are deficient in addressing the common RH problems (adolescent RH, abortion, referral mechanisms etc) and on the other hand, the entire emphasis seems to be on promoting family planning alone. There are, however, certainly some common grounds which have been experimented by various countries and we can learn lessons from those best practices. An inter-sectoral approach and SWAps would be required to achieve such ambitious goals set out in ICPD-PoA while working towards MDGs. An approach which would necessitate involvement of NGOs, donors and other stakeholders from the civil society for launching combined efforts to address a complex horde of issues around RH [##REF##15484612##41##]. The Commission on Macroeconomics and Health recommends increasing resource allocation to education and health; deploying more female health providers in rural areas; strengthening primary health care services and Emergency Obstetric Care (EmOC); and initiating meaning reforms which are capable of elevating the social status of women [##UREF##13##16##]. Government's commitment has to be reiterated in terms of strengthening and expanding the promising LHW program by attracting more donor support and raising the workers incentives. These endeavors should lead to formulate evidence based national policies, RH services which are affordable, accessible and culturally acceptable and finally a responsive health system. Poverty reduction strategies, reforms in education and health sector and planning for 2015 to achieve MDGs could be actually harmonized to deliver desired outcomes that were set in ICPD 1994. This would, however, necessitate sector wide approaches for designing various programs, building confidence of donor community, believing in NGOs credibility and overall strong political will to improve RH and especially women's health indicators of under-served segments of population in the country.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>The ICPD agenda of reproductive health was declared as the most comprehensive one, which had actually broadened the spectrum of reproductive health and drove the states to embark upon initiatives to improve reproductive health status of their populations. However, like all other countries, Pakistan also seems to have shifted focus of its policies and programs towards achieving MDGs. As a result, concepts highlighted in the ICPD got dropped eventually. In spite of specific goals on maternal and child mortalities in MDGs and all the investment and policy shift, Pakistan has still one of the highest maternal mortality ratios among developing countries. Lack of synchronized efforts, sector wide approaches, inter-sectoral collaboration, and moreover, the unmet need for family planning, unsafe abortions, low literacy rate and dearth of women empowerment are the main reasons. Being a signatory of both of the international agendas (ICPD and MDGs), Pakistan needed to articulate its policies to keep the balance between the two agendas. There are, however, certainly some common grounds which have been experimented by various countries and we can learn lessons from those best practices. An inter-sectoral cooperation and sector wide approaches would be required to achieve such ambitious goals set out in ICPD-Program of Action while working towards MDGs. There is a need of increasing resource allocation, strengthening primary health care services and emergency obstetric care and motivating the human resource employed in health sector by good governance. These endeavors should lead to formulate evidence based national policies, reproductive health services which are affordable, accessible and culturally acceptable and finally a responsive health system.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>FGA made substantial contributions to conception and design, acquisition of data, analysis and interpretation of data. BTS supervised the concept and design, helped in literature search and synthesis, and contributed in producing drafts. SS supervised data compilation and production of all the drafts. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Expected outcomes of working on common grounds between ICPD and MDGs.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Global stance on reproductive health in international treaties</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>ICPD 1994 PoA</bold></td><td align=\"center\"><bold>ICPD+5 1999</bold></td><td align=\"center\"><bold>ICPD+10 2004</bold></td><td align=\"center\"><bold>Beijing Conf 1995</bold></td><td align=\"center\"><bold>MDGs 2000</bold></td></tr></thead><tbody><tr><td align=\"left\">Reproductive Rights</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">RH care services</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Make RH services accessible through PHC</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Educate adolescents</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Community participation by decentralizing the management</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td><td align=\"center\">×</td></tr><tr><td align=\"left\">RH services for Migrants</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Family Planning Services</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Abortion</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Promote breast feeding</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Involvement of NGOs</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Institute system of monitoring &amp; evaluation</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Involvement of political &amp; community leaders</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Proper referral mechanism</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Expand/upgrade training in RHC providers</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td></tr><tr><td align=\"left\">Reducing maternal mortality and morbidity</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td><td align=\"center\">√</td></tr><tr><td align=\"left\">Emphasis on donor support</td><td align=\"center\">√</td><td align=\"center\">√</td><td align=\"center\">×</td><td align=\"center\">×</td></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Table 2. National policies showing the position of various reproductive health components.</p></caption></supplementary-material>" ]

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[ "<graphic xlink:href=\"1742-4755-5-4-1\"/>" ]

[ "<media xlink:href=\"1742-4755-5-4-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Worldwide, around 13 million people inject drugs [##UREF##0##1##]. The first cases of HIV related to injecting drug use were reported in the United States of America in 1982 in the <italic>MMWR </italic>bulletin from the Centers for Disease Control and Prevention (CDC), Atlanta [##REF##6815471##2##]. As of September 1982, 13% of the AIDS cases in United States of America were already people who inject drugs [##REF##6815471##2##].</p>", "<p>By the late 1980s and 1990s, concentrated epidemics of HIV in PWID were restricted to North and South America and Europe. Since the beginning of this century, explosive epidemics of HIV have occurred among PWID in Eastern Europe and in many countries of South, Central and South-East Asia. Cases of HIV infection within the community of PWID were recently reported from 10 African countries, disrupting the geographical barrier for a globalized phenomenon [##UREF##1##3##].</p>", "<p>Harm reduction is a new name for an old concept. One of the first harm reduction activities was described in Great Britain in 1926, when Sir Humphrey Rolleston, President of the Royal College of Physicians, proposed the use of morphine or heroin for the treatment of opium addiction. This decision was the beginning of a pragmatic and humanitarian approach to the treatment of drug addiction [##UREF##2##4##].</p>", "<p>In 1984, to control an outbreak of hepatitis B in the Netherlands and pressured by the Association of Drug Addicts (Junkies' Union), the health authorities of the City of Amsterdam implemented one of the first known needle exchange programme with a very successful outcome [##REF##2872527##5##]. When the first cases of HIV transmitted by the sharing of needles were recognized in 1985, the technology developed in Amsterdam was applied, again with good results[##REF##2872527##5##]. This approach has subsequently been proven to be extremely effective in controlling HIV epidemics among PWID [##UREF##3##6##, ####UREF##4##7##, ##REF##7502102##8##, ##UREF##5##9####5##9##].</p>", "<p>The offer of treatment for drug dependence has proven to be a very effective tool in controlling the HIV/AIDS epidemic arising from injecting drug use. From abstinence-based treatment, to detoxification or self-support treatment (such as Narcotics Anonymous), all these measures have some impact on the epidemic [##UREF##6##10##]. However, substitution therapy, in the case of opioids, is probably the most effective and scientifically proven strategy to treat drug dependence [##UREF##6##10##,##UREF##7##11##].</p>", "<p>There is no published information on when methadone was first used to treat heroin dependence. Apart from reducing or eliminating illicit heroin and other drug use as well as other benefits, methadone maintenance treatment (MMT) reduces the level of involvement with crime associated with opioid use [##UREF##6##10##,##UREF##7##11##]. Besides methadone, other opioid substitution therapies (OSTs) are available such as buprenorphine (both included in the WHO Model List of Essential Drugs in 2005) [##UREF##8##12##].</p>", "<p>Another important strategy to control the HIV/AIDS epidemic among PWID is the offer of antiretroviral therapy (ART) for those in need [##UREF##9##13##, ####UREF##10##14##, ##UREF##11##15####11##15##]. A comprehensive package of harm reduction interventions (including needle and syringe programmes [NSPs], substitution therapy [ST], and care, support and treatment for PWID) is crucial for controlling the HIV/AIDS epidemic and is being implemented in many countries. It is now supported by all UN agencies [##UREF##12##16##].</p>", "<p>Since the establishment of the Global Programme on AIDS, WHO has been working in a strategic and systematic way in the field of HIV/AIDS and drug use. WHO is one of the leading UN agencies promoting harm reduction and the main interlocutor with the health system involvement in harm reduction. Its work is organized into a number of components: establishing an evidence base; advocating for effective policies and programmes; developing normative standards, tools and guidelines; supporting countries in implementing programmes; ensuring access to essential medicines (such as methadone and buprenorphine), diagnostics and commodities; and mobilizing resources [##UREF##13##17##]. The Organization has officers working on harm reduction in almost all the WHO Regions who focus on controlling epidemics caused by injecting drug use. In principle resolutions are based on available evidence and backed by science and experts opinions, but as a multilateral organization there are also political elements that can influence on the decision making process.</p>", "<title>The Western Pacific and Asia Regions</title>", "<p>Although national HIV prevalence levels are still very low in the Asia-Pacific region, the huge population sizes of many Asian countries mean that very large absolute numbers of people are being infected each year with HIV [##UREF##14##18##]. Urgent responses are required; effective responses in some areas of the epidemic by countries such as Thailand and Cambodia have shown how much can be done [##UREF##15##19##,##REF##17020409##20##]. Unlike in Africa, the Asian epidemics are concentrated in identifiable high-risk groups (primarily those involving PWID who share needles, sex workers and men who have sex with men). Hence, HIV in the Asia region could be controlled if these high-risk groups are targeted with specific interventions [##UREF##16##21##,##UREF##17##22##].</p>", "<p>Many countries in the Asia-Pacific region face difficult public policy and legislative problems with regard to sex work, homosexuality and drug use. In addition, widespread poverty, and a general lack of access to effective health-care services by the poor and disadvantaged in both rural and urban areas means that the challenges of developing targeted intervention programmes, and ensuring coverage of vulnerable groups, are particularly acute [##REF##17020409##20##].</p>", "<p>The WHO Western Pacific Region comprises 37 countries from the Mekong River Valley in Asia to countries in the Pacific. Many of the epidemics in the Region are currently driven by needle-sharing among PWID. The epidemic of HIV is clearly driven by injecting drug use in three of the countries (China, Malaysia and Viet Nam). China accounts for 75% of the total population of the Region. Three other countries in the Region are beginning to build a comprehensive response to limit the burden of the HIV epidemic related to injecting drug use (Cambodia, Lao PDR and the Philippines). The other 31 countries are considered very Low Prevalence countries (with the exception of Papua New Guinea considered as the only country in the region with a generalized epidemic, but with a clear sexually transmitted epidemic). In the present paper we concentrate the information in the 6 key countries for the subject.</p>", "<title>Cambodia</title>", "<title>The epidemic in Cambodia</title>", "<p>The first case of HIV infection was notified in Cambodia in 1991. By 2003, approximately 123,000 people were living with HIV including 57,000 women and 9,000 children out of a total population of 14,071,000 [##UREF##18##23##,##UREF##19##24##]. An estimated 19,800 adults had developed AIDS by 2005 [##UREF##20##25##].</p>", "<p>National prevalence of HIV among those aged 15–49 years has declined from 1.2% in 2003 to 0.9% in 2006 [##UREF##21##26##] with HIV transmission occurring primarily through sexual contact [##UREF##18##23##]. In June 2007, HIV sentinel surveillance (HSS)-based data from the Center for HIV/AIDS/Dermatology/STIs (NCHADS) revealed that in 2006 the number of people living with HIV/AIDS (PLHA) was approximately 67,200, showing that the number of PLHA has decreased over time [##UREF##21##26##].</p>", "<p>In 2004, about 20,000 people were using amphetamine-type stimulants (ATS) and 2,500 were heroin users, of whom 1,750 might have been PWID [##UREF##22##27##]. Local nongovernmental organization (NGO) reports using small sample sizes put the HIV prevalence among PWID in the capital, Phnom Penh, at around 15%, and of ATS users at around 5% or less [##UREF##23##28##]. Knowledge of HIV transmission through shared needles/syringes is poor among PWID [##UREF##24##29##]. Consequently, patterns of the epidemic seem to be changing from one driven by sexual contact to one mixed with injecting drug use.</p>", "<title>Response to the epidemic in Cambodia</title>", "<p>Cambodia developed a policy for mounting a strategic response to harm reduction in 2003. The HIV/AIDS National Strategic Plan of the National AIDS Authority (NAA) explicitly promotes harm reduction as an evidence-based intervention [##UREF##25##30##]. The drug control master plan for Cambodia, developed by the National Authority for Combating Drugs (NACD), refers to the need to implement a comprehensive approach to HIV/AIDS [##UREF##26##31##].</p>", "<p>A memorandum of understanding (MoU) was signed between the NACD and NAA in 2004 to collaborate in preventing drug-related HIV/AIDS. An illicit drug-related HIV and AIDS working group (DHAWG) was then established to integrate HIV/AIDS into the full range of illicit drug-related activities nationwide and now meets quarterly.</p>", "<p>Capacity building for harm reduction has been undertaken of several provincial NGOs and Government social service agencies. Two local NGOs in Phnom Penh have been operating comprehensive harm reduction community outreach and drop-in centre activities – including NSPs – under NACD authorization since 2005. Cambodia now has at least 11 centres for the treatment and rehabilitation of drug users located around the country [##UREF##27##32##]. However, service capacity in all such centres is extremely limited according to Multi Agencies Rapid Assessment of treatment and rehabilitation centres in Cambodia. Phnom Penh conducted in December of 2007 [unpublished]. Minimum standards for such centres have now been drafted for Government approval.</p>", "<p>In 2008, the Government announced its intention to establish a methadone maintenance programme in Phnom Penh (document N° DG-DHS). Planned for September 2008, referrals will be established to services for voluntary counselling and testing (VCT), sexually transmitted infections (STIs) and tuberculosis (TB), prophylaxis and treatment of opportunistic infections (OIs)/ART as well as emergency medical assistance. NCHADS is also developing detailed plans to establish several VCT demonstration sites in the capital to attract drug users; this approach will then be scaled up nationwide. In 2008, NCHADS also plans to commence referral for prisoners to VCT, and drug treatment and rehabilitation centres nationwide.</p>", "<title>The role of WHO in Cambodia</title>", "<p>Since its support to a qualitative assessment of drug use in 2004 in collaboration with the US CDC, WHO in Cambodia has become the co-lead agency with the United Nations Office on Drugs and Crime (UNODC) for drug use in the Joint UN Theme Group on HIV/AIDS [##UREF##28##33##]. WHO's work includes technical assistance to develop and implement a continuum of care for drug users in all settings in Cambodia using evidence-based international good practices.</p>", "<p>In collaboration with a range of partners, WHO (i) provides support for the operationalization of the DHAWG and associated costed National Strategic Plan for Drug Use and HIV/AIDS; (ii) provides technical assistance for the NSP policy, guidelines, standard operating procedures (SOPs) and implementation plan (with related training in 2006); (iii) provides technical support to establish an MMT programme; (iv) gives technical advice for the development of policies, guidelines and SOPs related to drug dependency detoxification and treatment, and related resource mobilization for both community and closed settings; (v) supports linkages between the NACD, NCHADS, National Programme for Mental Health (NPMH) and NGOs working with drug-using communities for an effective response to the epidemic; (vi) supports communication initiatives including the development of guidelines in the Khmer language targeting health, social and education service providers, law enforcement personnel and parents, as well as four harm reduction video educational interventions for PWID, entertainment workers, ATS users and inhalant/solvent users; (vii) provides technical assistance to the Government and its NGO partners for resource mobilization, such as the Global Fund and the Swedish International Development Agency (SIDA).</p>", "<title>China</title>", "<title>The epidemic</title>", "<p>China sits between the \"Golden Triangle\" and \"Golden Crescent\" – two of the three biggest opiate suppliers in the world – and has seen a significant surge in the number of illicit drug users since the 1980s. Heroin is the main illicit drug used in China, with amphetamine and polydrug use on the rise.</p>", "<p>China's first case of HIV was reported in 1985 and first case due to injecting drug use in 1989 [##REF##15498242##34##]. By December 2007, there were an estimated 700,000 PLHA in China [##UREF##29##35##]. The national HIV prevalence is 0.05% (range 0.04% to 0.07%) [##UREF##30##36##]. Prevalence among PWID increased from 1.95% in 1996 to 6.48% in 2004, and is rising and spreading from these groups to the general population [##UREF##30##36##].</p>", "<p>PWID continue to engage in high-risk behaviours. Recently published national surveillance data show that 40% of participating PWID reported needle-sharing [##UREF##29##35##]. Estimated data indicate a focused spread of HIV infection among PWID. At the end of 2005, there were about 288,000 drug users living with HIV/AIDS, accounting for 44.3% of the total estimated HIV cases [##UREF##31##37##]. The epidemic is concentrated in Yunnan, Xinjiang, Guangxi, Guangdong, Guizhou, Sichuan and Hunan provinces, with each province having an HIV prevalence of more than 5% among PWID and over 10,000 HIV-positive PWID. Together, they account for 89.5% of all people infected through injecting drug use[##UREF##30##36##]. As of 30 December 2005, 1.16 million drug users were registered with the Ministry of Public Security (MPS) [##UREF##31##37##].</p>", "<title>Response to the epidemic in China</title>", "<p>The unique pattern of the HIV/AIDS epidemic in China – high HIV infection rate among PWID and former plasma donors (FPDs), but a relatively low overall infection rate in the country – provides a window period for taking action [##REF##18172388##38##]. China has achieved remarkable national progress in its comprehensive response to HIV/AIDS. The first and second five-year Action Plans (2001–2005 and 2006–2010) were formulated; the second aimed to cover no less than 90% of most-at-risk populations and vulnerable migrants with effective prevention interventions. By 2010, drug maintenance treatment clinics should be set up to provide services for no less than 70% of opium users (mainly heroin users) in counties and cities with more than 500 registered drug users. No less than 50% of PWID in the areas implementing NSPs should be provided with clean needles and syringes[##UREF##32##39##]. In 2006, the State Council issued the AIDS Prevention and Treatment Regulations that include promotion of programmes for drug users such as drug-maintenance treatment and other effective interventions [##UREF##33##40##]. Although the regulation does not explicitly mention needle exchange programmes, implementation of the approach in 775 sites in 17 provinces indicates the endorsement of this approach in the country [##UREF##32##39##].</p>", "<p>In February 2003, the Ministry of Health (MOH), MPS and the State Food and Drug Administration (SFDA) issued an interim \"Opium abusers community-based drug maintenance treatment protocol\" to start piloting MMT [##UREF##34##41##]. In July 2006, the three agencies revised the protocol to support expansion of the MMT programme in 22 provinces [##UREF##35##42##].</p>", "<p>A 2007 evaluation survey conducted in the first phase of eight MMT clinics found a positive change in the self-reported rate of injecting drug use, drug-related illegal offences, employment opportunities and family relations [##UREF##29##35##]. The average frequency of drug injection declined from 90 to two times per month and self-reported criminal behaviours reduced from 20.7% to about 3.8% [##REF##18172377##43##]. Entry requirements deterred many people from accessing the services, especially migrants and others without the required documents [##UREF##32##39##]. In 2006, the Government made adjustments to methadone delivery, such as permitting access to methadone clinics anywhere, linkages to other services, mobile methadone provision and waiving of residency documents [##UREF##32##39##].</p>", "<p>By December 2007, China had 503 functional MMT clinics. Cumulatively, over 97,554 drug users had entered the programme. In addition, 45,121 PWID had regularly attended NSPs [##UREF##36##44##]. These clinics regularly provide free HIV testing and counselling services to all who join the MMT programme. China has set a target of operating around 700 MMT clinics by the end of 2008 [##UREF##36##44##].</p>", "<p>The Chinese government has taken bold steps to scale up HIV testing and counselling, offer free ART to AIDS patients, and expand primary prevention measures such as MMT and NSPs for drug users, and condom promotion for sex workers and men who have sex with men (MSM). The remarkable achievements in such a short period of time indicate that China is strongly committed to limiting the epidemic and maintaining a low HIV prevalence in the future [##REF##18172388##38##].</p>", "<p>Although the current policy environment is favourable for harm reduction activities, China faces several difficult challenges in establishing a comprehensive HIV/AIDS response among PWID. These include (i) difficulty in coordination among different bodies; (ii) inadequate implementation of prevention strategies; (iii) increasing the demand for care, support and treatment for PWID to reach all those in need; and (iv) need for effective control of HIV/AIDS transmission inside closed settings.</p>", "<p>In China, eligible HIV-positive PWID in the community have access to free ART since 2003 through referral linkages between MMT clinics, hospitals and CDC in China. Over 31 000 adult and paediatric patients have been treated [##REF##18172383##45##]. China is also piloting ART in prisons in Guangxi, Yunan, Sichuan and Hunan. Prisoners on ART are mainly drug users.</p>", "<title>The role of WHO in China</title>", "<p>WHO assists China to confront the challenges it faces, by providing timely information about new approaches and technologies that are later adapted and adopted according to China's needs. WHO works with several key partners on various issues through the UN Theme Group on HIV/AIDS and Drug Use.</p>", "<p>Specifically, WHO supports China in the following areas: (i) policy development and advocacy (e.g. supporting pilot NSP and MMT projects); (ii) providing HIV prevention education; (iii) training staff in drug detoxification and drug dependence treatment in closed settings; (iv) providing technical support for the provision of drug dependence treatment from pilot projects to scaling up; (v) advocacy for testing and counselling; (vi) care, support and treatment for PWID; and (vii) monitoring and evaluation of harm reduction projects.</p>", "<p>WHO is also working with the Government to change the common perception that drug users are criminals instead of people who are ill and in need of care, support and treatment.</p>", "<title>Lao PDR</title>", "<title>The epidemic</title>", "<p>Lao PDR is experiencing an impressive development in the recent years. According to UNAIDS Report of 2008, Lao PDR is currently losing the status of a considered land-locked country and being fast transformed in a land linked country [##UREF##37##46##]. A high way being developed by the Asian Development Bank and the Great Mekong Sub-Region Governments (the Mekong Highway Project) is faster optimizing the mobility of the population and the development of the entertainment industry [##UREF##38##47##].</p>", "<p>Lao PDR is a low HIV-prevalence country. To date, the HIV epidemic has been driven by multipartner client-sex worker behaviours, with some data showing that HIV infection may spread as well among MSM [##UREF##37##46##]. It is estimated that 3700 people are living with HIV in the country, which has a population of 5,924,000. The estimated prevalence is around 0.1% among the 15–49 years' age group [##UREF##39##48##].</p>", "<p>Lao PDR has Myanmar, China (Yunnan), Viet Nam, Thailand and Cambodia as its neighbours and injecting drug use has been reported in all these countries. Lao PDR is in the border of the Golden Triangle which is one of the important sources of opium globally speaking. Lao PDR is also a neighbor of countries that are producing methamphetamines and is therefore being considered as a transit country for methamphetamine and its precursors [##UREF##37##46##]. The traditional use of opium is still the main drug used in Lao PDR but there are increased reports in the use of methamphetamines and injection of opium and this trend seems to be a recent phenomenon. The national behavioural surveillance survey (BSS) done in 2001 did not indicate any injecting drug use among the sample [##UREF##40##49##]. The second round of BSS in 2004 indicated that up to 11% of sex workers in one province indicated that they had ever injected drugs[##UREF##41##50##]. Anecdotal evidence shows that injecting drug use is becoming more common, though the HIV epidemic has not yet clearly started among PWID.</p>", "<title>Response to the epidemic in Lao PDR</title>", "<p>The response to the HIV/AIDS epidemic in Lao PDR started early and has a high level of public commitment. Lao PDR developed a National Strategy and Action Plan 2006–2010, with clear priority targets. A costed action plan forms the basis for the resource mobilization of the country. According to UNAIDS 99.52% of the funds comes from external resources [##UREF##37##46##]. Global Fund round 6 is one of the important sources of funds to support the response to the epidemic in Lao, which also has funds from USAID, AusAID, SIDA, among others. It is important to notice that Lao PDR included its action plan for HIV/AIDS in their 6^thNational Socio-Economic Development Plan, elevating the fight against the epidemic for a higher level of development concerns of the country [##UREF##37##46##].</p>", "<p>Recently, with the support of the UN system, the Lao PDR Government set up a Task Force on HIV and Drug Use with the objectives of developing a policy, proposing concrete activities to address the vulnerability of drug users to HIV, and developing guidelines for harm reduction and treatment of drug abuse [##UREF##42##51##]. This Task Force is jointly chaired by the Lao PDR National Commission for Drug Control and Supervision, and the Ministry of Health, and is composed of different stakeholders enlarging the participation of many different sectors in the response of the HIV/AIDS Epidemics.</p>", "<p>Harm reduction for PWID is embedded in the National HIV/AIDS/STI Strategy 2006–2010 [##UREF##43##52##]. This includes providing a supportive environment for PWID (advocacy, legal and policy framework, review and update of the national policy) and providing PWID with the means to protect themselves from the consequences of drug use, as well as scaling up towards universal access. So far the harm reduction activities are very incipient in the country and rely on outreach work.</p>", "<p>An access to ART project was started in 2003, which at the moment covers around 700 patients in two centres of the country. Even if a larger number of people are in need of ART according to estimates, there are no known people in need of ART who are not receiving it. According to the Universal Access Report launched by WHO, UNAIDS and UNICEF in June of 2008, Lao PDR is one of the few countries in the world where the coverage for people in need of ARV bounds 100% [##UREF##44##53##].</p>", "<title>The role of WHO in Lao PDR</title>", "<p>WHO supports the Task Force technically (with UNODC and UNAIDS) and financially by strengthening coordination, carrying out a rapid assessment of the injecting drug use situation, organizing study tours, developing and adapting guidelines for the treatment of addiction, organizing advocacy workshops and supporting the secretariat of the Task Force.</p>", "<p>The main partnership of WHO in the country is with the Sweden Cooperation for a 2 years project (2008/2009) specifically dedicated to the implementation of Harm Reduction as a key strategy to avoid or mitigate the epidemic in Lao PDR.</p>", "<p>As Lao PDR does not yet have an HIV epidemic caused by injecting drug use, this gives the country the opportunity to start a meaningful harm reduction programme and thereafter try to prevent an epidemic.</p>", "<title>Malaysia</title>", "<title>The epidemic</title>", "<p>The first case of HIV was diagnosed in Malaysia in 1986 [##UREF##45##54##]. By December 2007, the estimated number of PLHA in Malaysia was 69,000 out of a total population of 25,347,000 [##UREF##46##55##]. The majority of reported cases were in the age group of 20–39 years, the younger and potentially more productive segment of the country's population. During the same period, there were 76,389 reported HIV infections of which 70,300 were in males and 6089 in females (cumulative); 73.7% of HIV infections occurred among PWID [##UREF##47##56##].</p>", "<p>As a consequence of the large proportion of PWID in the population with HIV/AIDS, the epidemic in Malaysia is clearly a concentrated epidemic, since HIV prevalence has been less than 1% among the general population but consistently higher than 5% (between 3% and 20%) in PWID [##UREF##48##57##]. The first round of the national BSS conducted during 2003–2004 showed a high frequency of sharing injecting equipment among PWID (71.5%) [##UREF##46##55##]. Males account for more than 90% of the reported cases; however, the epidemic is rapidly advancing among females [##UREF##46##55##,##UREF##47##56##]. The proportion of reported HIV infections transmitted through homo/bisexual and heterosexual contacts is also increasing [##UREF##46##55##]. There is a high level of prevalence in specific populations and certain regions, as more than 10% of commercial sex workers in Kuala Lumpur were found to be positive for HIV in a study conducted in the year 2000.</p>", "<title>Response to the epidemic in Malaysia</title>", "<p>From a highly punitive approach of sending drug users to forced treatment centers as the only strategy by the beginning, the response to the HIV/AIDS epidemic in Malaysia has been stepped up in the past 18 months [##UREF##49##58##]. Responsibility for drug treatment rests since 2006 with the Ministry of Health, and Malaysia's National Strategic Plan on HIV/AIDS for 2006–2010 includes calls for methadone and buprenorphine, needle exchange and free ART [##UREF##50##59##]. Malaysia now has six NSPs coordinated by the Malaysian AIDS Council (MAC) [##UREF##49##58##]. These projects handle more than twice the expected number of clients. At the end of 2007, 3600 PWID had been reached by NSPs [##UREF##49##58##]. A target has been set of reaching 20,000 PWID by 2010 [##UREF##49##58##].</p>", "<p>MMT has been scaled up continuously since it was introduced in October 2005. The country now has 74 MMT services serving more than 4000 PWID. As of 31 December 2007, a total of 4,135 drug addicts had been registered and enrolled into the Government MMT programme, which is totally free for patients. Furthermore, the expansion of methadone availability in Malaysia is being also amplified by the inclusion of General Practitioners. In April 2008, the MMT programme was extended into the prison system starting with a pilot project in Pengkalan Chepa prison in one of the eastern states. Methadone availability is being enhanced and monitored by the Ministry of Health. The cost has been reduced several fold, but qualified counsellors are scarce [##UREF##49##58##].</p>", "<p>At present, 40% of those who fulfill the criteria for initiating ART are under treatment (personal communication, Dr Christopher KC Lee, during the WHO symposium on Drug use and HIV in Kuala Lumpur, Malaysia, 3 December 2007). This is a great development in comparison with 10% 18 months ago (personal communication, Dr Christopher KC Lee, during the WHO symposium on Drug use and HIV in Kuala Lumpur, Malaysia, 3 December 2007). However, Malaysia still needs to develop the sexual component of its response to the HIV/AIDS epidemic due to the rapid spread among the female population.</p>", "<title>The role of WHO in Malaysia</title>", "<p>WHO has been constantly and consistently providing technical support for capacity building. The first contribution to the Government of Malaysia in this field was in 2004 when an Injecting Drug User Behaviour Survey Study was conducted with technical and financial support from WHO. This study was a baseline for a series of decisions that the Government took to better develop its strategy to confront the epidemic.</p>", "<p>In September 2004, a workshop on the development of the National Strategic Plan on HIV/AIDS was conducted, again with WHO support. The Plan was developed in the workshop itself and the first draft was designed by a WHO consultant to support the Government of Malaysia. This strategy was later reviewed in 2005, also with WHO support, when the Government of Malaysia presented their evaluation of the Millennium Development Goals (MDGs) and regretted that the only goal that Malaysia did not achieve at that point in time was MDG 6 – failure to control HIV/AIDS.</p>", "<p>Again in 2005, in conjunction with the Asian Parliamentarian Forum, WHO supported a dialogue in the Malaysian Parliament advocating for their support to harm reduction. This activity brought about strong political support for harm reduction.</p>", "<p>In 2006, WHO conducted a Bi-Regional Workshop (WPRO and SEARO) in Malaysia and an Informal Consultation to develop guidance for care, support and treatment for PWID. This was crucial for developing the next step of engaging PWID in treatment with ARVs.</p>", "<p>Technical support was also provided for the monitoring and evaluation exercises associated with the pilot NSP and MMT programmes. WHO Malaysia hired highly respected international consultants to help conduct an in-depth analysis of the MMT as well as NSP programmes. There was no seminar or event in that field where WHO was not clearly involved.</p>", "<p>WHO also supported a Rapid Assessment Study among PWID; and their initial findings were presented during the Symposium on Drug use and HIV in Kula Lumpur, Malaysia, held on 3 December 2007. The study concluded that the majority of subjects initiated drug use before the age of 18 years and shift to injecting very fast. Heroin is the main drug of injection; however, an increasing number of people use ATS as their main drug of choice. Rates of sharing of injection equipment are very high and condom use is less than 20% with all kinds of partners. The data will be released in 2008 by WHO and the University of Sains, Malaysia.</p>", "<p>The country's response to the HIV/AIDS epidemic among PWID was analysed in depth at a national AIDS conference and a national symposium on Drug use and HIV promoted by WHO and partners in December 2007. The achievements were acknowledged both within and outside Malaysia. Malaysia's understanding of its epidemic pattern is increasing based on evidence, and the country is stepping up its response by scaling up methadone clinics, NSPs, as well as care, support and treatment for PWID.</p>", "<p>At present, besides ongoing technical assistance, WHO is providing support for policy development in the area of Government and public acceptance of harm reduction programmes.</p>", "<title>The Philippines</title>", "<title>The epidemic</title>", "<p>The HIV epidemic in the country has been described as low prevalence [##UREF##51##60##]. There were 7,490 people estimated to be living with HIV in 2007, out of an adult population of 44,608,300 (15–49 years old), with an HIV prevalence rate of 0.017%. HIV in the Philippines is predominantly sexually transmitted (85%) [##UREF##51##60##].</p>", "<p>However, drivers of the epidemic in PWID have been documented. In 2007, an integrated HIV behavioural and serological surveillance (IHBSS) showed that 52% of PWID had shared needles and syringes the last time they injected; condom use was only 24%; and prevalence of hepatitis C among PWID was 88% in Cebu City and 6% in Zamboanga City [##UREF##52##61##]. At present, there are about 9,984–20,316 PWID in the country [##UREF##53##62##].</p>", "<p>The National HIV and AIDS Registry, a passive form of surveillance, recorded a total of 3,061 reported cases of HIV from January 1984 to December 2007, of whom 7 were PWID [##UREF##53##62##].</p>", "<title>Response to the epidemic in the Philippines</title>", "<p>The Department of Health (DOH), as chair of the Philippine National AIDS Council, a multisectoral policy-making body on HIV prevention, is the lead government agency mounting a national response to the HIV epidemic. The country's responses are geared towards universal access to prevention, treatment, care and support, including protecting the rights of PLHA and their families [##UREF##54##63##].</p>", "<p>The following prevention strategies are being implemented: community outreach and education, scaling-up counselling and testing, early diagnosis and management of STIs, 100% condom use programme (15 sites), prevention of mother-to-child transmission (PMTCT, pilot implementation), provision of post-exposure prophylaxis, and a harm reduction programme for PWID (3 sites) [##UREF##55##64##].</p>", "<p>Implementing a harm reduction programme in the Philippines is challenging because of the illegal nature of drug use. Despite a law on the prevention and control of AIDS (Republic Act 8504), a more recent law, the Dangerous Drugs Act (Republic Act 9165) emphasizes the supply and demand reduction approach to control drugs. Recognizing these conflicting mandates, the National AIDS STI Prevention and Control Programme and the Philippine National AIDS Council (PNAC) Secretariat initiated discussions with the Dangerous Drugs Board, the Philippine Drug Enforcement Agency, and other relevant partners, to come up with more appropriate and acceptable approaches that would treat the PWID situation in the country as a public health concern to be addressed rather than as a criminalized, legal issue.</p>", "<p>While central government agencies tried to work at the policy level, NGOs, in coordination with the local health departments and local stakeholders, started providing harm reduction services among PWID including community outreach, peer education, referral networking to counselling, provision of clean needles and syringes, psychosocial support, and referral and treatment for STIs and other health-related concerns. Outreach work was initiated in 1995 by the Program for Appropriate Technology in Health (PATH) in partnership with the University of Southern Philippines Foundation, through the AIDS Surveillance and Education Project of USAID. Other NGOs such as Remedios AIDS Foundation, KABALIKAT, USAID-Local Enhancement and Development (LEAD) for Health Project were also involved in outreach education work among PWID. Currently, the Philippine NGO Council for Population, Health and Welfare, Inc. and the Tropical Disease Foundation continue to implement PWID harm reduction programmes through the Global Fund AIDS projects.</p>", "<p>In 2007, the Asian Development Bank's Regional Technical Assistance Project complemented the country's initiatives by supporting the conduct of a situation and response analysis of PWID-related work in the country and of IHBSS among PWID in the cities of Zamboanga and General Santos [##UREF##56##65##].</p>", "<p>Currently, 800 PWID are reached by prevention services through three major outreach service delivery points, which includes provision of clean needles/syringes [##UREF##55##64##,##UREF##57##66##,##UREF##58##67##].</p>", "<p>In the area of care and support, there are 11 treatment hubs with trained HIV AIDS Core Teams that provide clinical and psychosocial care and support to PLHA. ART is provided free since 2005. The baseline CD4 count is also done free at the STI AIDS Cooperative Central Laboratory (funding support from Global Fund). As of December 2007, there are 390 PLHA enrolled for free ART and are receiving extended care and support services [##UREF##55##64##].</p>", "<title>Role of WHO</title>", "<p>WHO remains the major provider of assistance to the DOH in advocating for sustained efforts to support the harm reduction programme among PWID and to dispel the perception that this is not effective and not needed in the Philippines. WHO is the lead agency on matters pertaining to health, and in preventing the transmission of HIV through injecting drug use (since there is no UNODC office in the Philippines). In conjunction with other UN agencies, WHO supports the evidence-based development of harm reduction strategies and ensures that only scientifically effective harm reduction strategies are introduced, adapted and continuously implemented in the Philippines in order to address the public health concerns of people who inject drugs.</p>", "<p>WHO supported a study on behaviour patterns among PWID admitted to rehabilitation centres; the results were initially disseminated in January 2008. WHO also conducted the first orientation on PWID harm reduction programme (2007) among DOH and UN staff, and among high-level officials of the DOH, Department of Interior and Local Government, and the PNAC Secretariat. WHO is a key member of the Harm Reduction Working Group which will draft appropriate national guidelines on the harm reduction programme in the Philippines.</p>", "<title>Viet Nam</title>", "<title>The epidemic</title>", "<p>After the first HIV case was diagnosed in 1990, transmission and reporting of cases accelerated such that it was estimated that there were 293,000 PLHA in Viet Nam at the end of 2007 [##UREF##59##68##]. Cumulative reporting up to end of December 2007 documented 156,210 HIV infections; 62,145 cases of AIDS and 34,476 deaths due to AIDS [##UREF##60##69##]. The majority of the reported cases (83.16%) were aged between 20 and 39 years; 57.28% of the total were between 13 and 29 years; 82.77% of cases were male and prevalence among women was slowly increasing [##UREF##59##68##]. Estimated adult HIV prevalence is 0.5% [##UREF##61##70##].</p>", "<p>Since 1990, the majority of reported HIV infections and AIDS cases have been in PWID (50–60%), though heterosexual transmission, particularly through commercial sex, appears to be increasing [##UREF##60##69##]. With a low prevalence of HIV in the general population and high prevalence in PWID (28.6% nationally), the HIV epidemic remains \"concentrated\" [##UREF##59##68##]. In the Viet Nam Integrated Behavioural and Biological Surveillance Survey of 2005–2006, around one third of PWID reported sharing of syringes in the previous six months and more than 50% reported unprotected sex with sex workers [##UREF##62##71##].</p>", "<title>Response to the epidemic in Viet Nam</title>", "<p>The Ministry of Health (MoH) is the lead agency for harm reduction activities. HIV prevention measures were initiated in 1993 and predominantly involved mass education and small-scale needle/syringe distribution. In 2003, the first of the large donor-funded prevention projects started with financial support from the UK Department for International Development (DFID) and Norwegian Directorate for Development Cooperation (Norad) in 19 provinces and two cities (initially under MoH-WHO co-managment, later by MoH with technical assistance from WHO). In 2005, the response was expanded by the addition of the World Bank-funded MoH Viet Nam HIV/AIDS Prevention Project in 18 provinces and two cities (six provinces and the two cities overlap) [##UREF##63##72##].</p>", "<p>An impressive government HIV/AIDS response over the past five years has seen an expanding public health response and the National Assembly pass the Law on HIV/AIDS Prevention and Control in 2006 and associated Decree 108/2007 ND-CP in 2007 [##UREF##64##73##,##UREF##65##74##]. Protracted and careful advocacy on the part of the Communist Party Commissions, local NGOs, international community members and dedicated National Assembly members facilitated passage of the 2006 Law.</p>", "<p>Under the Law, the MoH is specifically mandated to lead harm reduction activities for HIV prevention among risk groups and to work with the Ministry of Public Security (MoPS) and Ministry of Labour, Invalids and Social Affairs (MoLISA) to ensure the implementation of needle and syringe, condom distribution and OST programmes.</p>", "<p>The MoH Viet Nam Administration of HIV/AIDS Control (VAAC)-led projects for prevention have expanded since the HIV/AIDS Law, in particular, coverage with NSPs increased from 21 provinces in 2005 to 42 provinces in 2007. During 2007, expansion of all projects led to the distribution by government health services of more than 11 million needles and syringes (sufficient to provide around one quarter of the registered PWID with one per day), and more than 100 million condoms – predominantly through the activities of more than one thousand peer outreach workers [##UREF##66##75##,##UREF##67##76##].</p>", "<p>In 2007, VAAC, in collaboration with other MoH departments and international partners, developed national guidelines and a proposal for pilot MMT programmes for 1500 patients. Treatment commenced at three sites each in Hai Phong and Ho Chi Minh City during the first half of 2008 with support from the US Government President's Emergency Plan for AIDS Relief (PEPFAR), WHO, DFID and World Bank [##UREF##68##77##].</p>", "<p>By the end of September 2007, a total of 14,180 adults were receiving ART in 64 provinces – a 5.7-fold increase from the end of 2005 (or 28.4% of those needing ART) [##UREF##60##69##]. Though the proportion of ART patients who are former or active PWID is unclear, scaling up of ART created opportunities for direct collaboration between health staff and PLHA support groups whose risk behaviour had previously marginalized them. This was important for mobilization of appropriate peer workers for outreach in harm reduction.</p>", "<p>The national network has more than 80 Treatment and Education Centres, which are institutions for drug users (and sex workers) who are required to go through drug detoxification, education and occupational training for one to two years (except in Ho Chi Minh City which has a five-year requirement). Implementation of small-scale provision of ART commenced this network in 2007 with PEPFAR support. Substantial expansion is planned under the Global Fund Programme in 2008 and beyond. Many of these closed settings, housing over 60,000 drug users, have a high prevalence of HIV (30–60%) and burden of AIDS-related illnesses, but until now have been without adequate resources to provide HIV prevention, treatment or care [##UREF##60##69##].</p>", "<title>The role of WHO in Viet Nam</title>", "<p>In response to requests from the MoH, WHO has been a principal provider of technical assistance for harm reduction activities, which are largely conducted by the health sector. WHO efforts to increase the coverage and quality of harm reduction interventions for the MoH-DFID/Norad-funded HIV prevention project in 21 provinces has been through the development of guidance documents, tools, identification of good practices for the needle-syringe and condom programmes for entertainment establishments, street-based sex workers and other groups at risk through non-pharmacy outlets, and capacity building, including participatory training for managers and peer outreach workers.</p>", "<p>Building on these experiences, WHO has been taking a lead role in supporting VAAC, with support from DFID and SIDA, to develop the national technical guidelines on the needle-syringe and condom programmes, in collaboration with PEPFAR, UNAIDS, UNODC and others. Furthermore, development of strategic and operational collaboration between MOH, MOLISA, MOPS and their local entities are being promoted and supported by Joint UN Team on HIV in which WHO plays an active role.</p>", "<p>Through 2007, WHO and international partners supported the complex collaborative development process for the MMT guidelines, implementation proposal, training curriculum and methadone procurement.</p>", "<p>WHO provided key support to OST/NSP study tours for the MoH in 2007 to sites in Hong Kong, Malaysia, Indonesia and Australia, including participation to provide translation into a familiar language and organizational context. WHO continues to collaborate with UNODC and UNAIDS to ensure that partnerships between the MoH and MoPS/MoLISA remain supportive of harm reduction.</p>", "<p>WHO has continued to support expansion of HIV treatment and care including ART for active PWID and development of the National HIV Monitoring and Evaluation Framework including refinement of indicators related to PWID and Sex Work.</p>", "<p>Challenges remain for WHO, working with advocacy partners, to expand the supportive political environment for harm reduction in Viet Nam and in the development of effective HIV prevention and care linkages between closed settings ('Treatment and Education' centres/prisons) and communities.</p>", "<title>WHO Regional Office for the Western Pacific (WPRO)</title>", "<p>In 2003, the WHO Region for the Western Pacific and Asia developed a workplan in support of harm reduction that embraced HIV/AIDS prevention, care, support and treatment for PWID. It was based on assessment missions to countries with varied situations with regard to HIV and the use of drugs including China, Cambodia, Lao PDR, Malaysia and Viet Nam. Consultations were also held also with key partners in this area, including UNAIDS, UNODC, CDC-Global AIDS Program, Family Health International (FHI) and Burnet Center for Harm Reduction. The framework used reflects WHO's overall management plan and expected results: to develop tools and guidelines; to strengthen country capacity; and to provide regional support for country programme development.</p>", "<p>One of the expected results was the development of tools and guidelines:</p>", "<p>(1) A publication entitled <italic>Drug dependence detoxification and treatment guidelines for low-resource, high HIV-risk settings</italic>. These protocols and associated training packages have been developed as a joint initiative with the Australian National Drug and Alcohol Research Centre, one of the WHO Collaborating Centres. The package is being field-tested in Cambodia in the second semester of 2008. A final version will be published by the end of 2008.</p>", "<p>(2) A manual on <italic>HIV/AIDS care and treatment for people who inject drugs </italic>was published in March 2008.</p>", "<p>(3) <italic>HIV testing and counselling in settings attended by people who inject drugs </italic>is scheduled for publication in 2008.</p>", "<p>These tools and guidelines will be extremely helpful for Members States and civil society to further develop harm reduction strategies in the Region.</p>", "<p>(4) A revised framework to address TB-HIV Co-Infection in the Western Pacific Region, was launched in July of 2008 and dedicated one chapter for TB-HIV in Closed Settings and among people who inject drugs.</p>", "<p>A second main task from the workplan is to give support to Member States. It is important to state that HIV Programmes in WHO country offices in the region count with a focal person for Harm Reduction in the six mentioned countries. Their contribution is being crucial. Consistency and technical back-up for the work of WHO country offices in the Region is provided by WPRO. The HIV/STI Focus Unit of WPRO had an important role to play in the achievements made by the six countries discussed in this paper.</p>", "<p>The third main task is to provide regional support. A standing participation in the UN Regional Task Force has been an important contribution from WHO to a collective effort. WPRO is also working hard to develop regional alliances with crucial partners (UNODC, UNAIDS, UNICEF, DFID, AusAID, SIDA, WHO/SEARO, International Network of People Using Drugs [INPUD], and others) for better development of harm reduction strategies to tackle the epidemics in the Region. Together with UNODC, WPRO will organize a meeting during the 20^thInternational Harm Reduction Conference in Bangkok, in 2009, of all the relevant community-based organizations in the field of drug use. WPRO is also collaborating with the Australian National Council on Drugs and the Burnet Institute to better develop a network on drug research in the Pacific Area, almost unexplored in terms of the health consequences of the misuse of illegal drugs.</p>", "<p>At present, the main objectives of the WPRO HIV/AIDS and STI Unit in the field of harm reduction are to harmonize (as much as possible) the response to the HIV/AIDS epidemics among PWID in different countries of the Region; help countries to develop better policies, legislations and practices to facilitate their response; increase the availability of advocacy tools; reinforce the main package of interventions comprising NSP, Drug Dependence Treatment (mostly but not only OST) and care, support and treatment (including ARV). Co-infections of TB and Hepatitis C are also being addressed. WHO is in a privileged position among the UN agencies to be the interlocutor with the health sector, supported by science, evidence-based results and political will. WHO also has the technical expertise to take the lead in helping to promote the changes needed to adequately face the epidemic among and from people who inject drugs.</p>" ]

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[ "<title>Conclusion</title>", "<p>Injecting drug use is driving HIV epidemics in many countries and accounts for almost a third of new infections outside sub-Saharan Africa [##UREF##1##3##]. Across the estimated 13 million PWID globally, drug use patterns, behaviours and contexts vary widely [##REF##17506148##78##]. The common thread that runs through all epidemic situations in the Asia-Pacific region is that the major HIV risk behaviour groups affected (PWID, MSM, sex workers and their clients) are socially marginalized and engage in socially unacceptable and often illegal behaviours [##UREF##17##22##]. Many countries in Asia face difficult public policy and legislative problems with regard to sex work, homosexuality and drug use. In addition, widespread poverty, and a general lack of access to effective health and welfare services by the poor and disadvantaged in both rural and urban areas, means that the challenges of developing targeted intervention programmes, and ensuring coverage of vulnerable groups, are particularly acute. Attention to these challenges is urgently required [##REF##17506148##78##]. Supportive policies, including policies that ensure equitable access to HIV services for drug users; a conducive legal and social environment; laws that do not compromise access to HIV services for drug users through criminalization and marginalization; and campaigns to reduce stigma and discrimination, are needed to combat the epidemics [##REF##17506148##78##]. Until there is full public and policy-maker acceptance of the need to develop and expand effective risk behaviour change, and reduction or elimination programmes, HIV will continue to spread in the Asia-Pacific region [##UREF##16##21##].</p>", "<p>In conjunction with many other partners, WHO pioneers the promotion and development of evidence-based strategies for harm reduction in the Region. Because of the efforts made, harm reduction is no longer a marginal strategy in the Region. While the progress made has been impressive, it is important to consolidate the advances and scale up interventions to better confront the epidemics driven by injecting drug use.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>The epidemic of HIV/AIDS linked to injecting drug usage is one of the most explosive in recent years. After a historical epicentre in Europe, South and North America, at present it is clearly the main cause of dissemination of the epidemic in Eastern Europe and some key Asian countries. Recently, 10 African countries reported the spread of HIV through people who inject drugs (PWID), breaking one of the final geographical barriers to the globalization of the epidemic of HIV among and from PWID.</p>", "<p>Several countries of the Asia and Pacific Region have HIV epidemics that are driven by injecting drug usage. Harm reduction interventions have been implemented in many countries and potential barriers to implementation are being overcome. Harm reduction is no longer a marginal approach in the Region; instead, it is the core tool for responding to the HIV/AIDS epidemic among PWID. The development of a comprehensive response in the Region has been remarkable, including scaling up of needle and syringe programmes (NSPs), methadone maintenance treatment (MMT), and care, support and treatment for PWID. This development is being followed up by strong ongoing changes in policies and legislations. The main issue now is to enhance interventions to a level that can impact the epidemic.</p>", "<p>The World Health Organization (WHO) is one of the leading UN agencies promoting harm reduction. Since the establishment of the Global Programme on AIDS, WHO has been working towards an effective response to the HIV epidemic among PWID. WHO's work is organized into a number of components: establishing an evidence base; advocacy; development of normative standards, tools and guidelines; providing technical support to countries; ensuring access to essential medicines, diagnostics and commodities; and mobilizing resources.</p>", "<p>In this paper, we trace the course of development of the HIV/AIDS epidemic among and from PWID in the Western Pacific and Asia Region (WPRO) as well as WHO's role in supporting the response in some of the key countries: Cambodia, China, Lao PDR, Malaysia, the Philippines and Viet Nam.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>DJ and MF were responsible for the Vietnam piece of the paper. DR developed the Lao PDR piece of the manuscript. GS was the main contributor for the Cambodian piece of the paper. HT and NS contributed to the piece of the paper on Malaysia. HY and KP were the main responsible for the piece of the paper about China. MS was in charge of the piece of Philippines in the manuscript. FM as the main author overviewed the paper and was responsible for the overall manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to express their gratitude to the following persons: Dr Pengfei Zhao, Technical Advisor, HIV/AIDS and STI, WHO Viet Nam; Ms Thien Nga Nguyen, National Programme Officer, Targeted HIV Prevention, Viet Nam; Ms Lisa Ng Bow, STP of the HIV team in China; Ms Andrea Boudville, Youth Ambassador of Australia, Project assistant, China; Dr Wiwat Rojanapithayakorn HIV/AIDS Team Leader WHO China; Dr Ji Guoping, Senior Programme Officer for HIV/AIDS China. The authors would also like to give special thanks to Dr Bandana Malhotra for her incredible contribution during the whole process of writing this paper.</p>" ]

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[ "<title>Background</title>", "<p>Offspring vary in their need and condition and parents must assess these parameters to provide optimal care. Therefore, offspring should communicate their needs to the parents and parents should act upon these signals. Studies on altricial animals show that offspring induce and maintain parental care by visual, acoustic, olfactory and tactile stimuli [##UREF##0##1##, ####UREF##1##2##, ##UREF##2##3##, ##UREF##3##4##, ##REF##6747504##5##, ##UREF##4##6####4##6##]. Maternal behaviour changes over time either due to a shift in maternal state or to changing stimulus characteristics of the young [##UREF##2##3##]. In rodents, maternal behaviour is influenced strongly by the age of pups and litter size [##REF##4706768##7##,##UREF##5##8##]. Absence of sufficient stimuli may result in females abandoning offspring or even the complete brood [##UREF##6##9##,##UREF##7##10##]. In order to understand principles of resource allocation, maternal responsiveness to offspring stimuli and its change over time needs to be determined.</p>", "<p>Rodents are an established model in such studies on maternal behaviour and parent-offspring conflict. Yet, most studies have been conducted on altricial species. Reproductive patterns differ for altricial and precocial rodent species particularly due to the fact that young of the latter begin early to contribute to their energy requirements by independent food intake [##REF##9279926##11##]. In many species the sucking stimulus affects milk supply and the length of time to weaning [##UREF##5##8##,##REF##12604644##12##]. For example in rats, lactation can be maintained far beyond normal weaning by repeatedly fostering younger pups to a mother [##UREF##5##8##]. However, in contrast to rats, the milk yield curve in guinea pigs (<italic>Cavia aperea </italic>f. <italic>porcellus</italic>) is rather fixed [##REF##536477##13##]. Mothers terminate lactation and only tend to prolong the lactation period slightly when given much younger foster pups [##UREF##8##14##]. Thus, these findings raise the question as to whether guinea pig mothers adjust their responses to experimentally manipulated offspring demand [##UREF##8##14##, ####UREF##9##15##, ##UREF##10##16####10##16##].</p>", "<p>Previous studies showed that guinea pig females reduce milk output when litter size is reduced. In contrast, they do not increase milk yield proportionally to increases in litter size, at least not in litters consisting of more than three pups [##REF##536477##13##]. With an average litter size of more than three pups, but only two teats, competition between litter mates about access to milk is likely to occur and models of scramble competition describe pup-interactions better than honest signalling models [##UREF##9##15##]. Pups show moderately aggressive behaviour in the form of tussling. However, a previous study showed that pups do not succeed in getting access to a teat through tussling. Instead, hungrier pups respond faster to the presence of the mother and thereby gain preferential access to a teat [##UREF##9##15##].</p>", "<p>One strategy by pups to obtain attention by the mother is to activate her by calling [##UREF##11##17##]. Vocal communication is important for precocial species where offspring actively moves around. Guinea pig mothers recognize their pups not only by olfactory cues but also by vocal cues and pup calls can induce female vocal responses [##UREF##12##18##,##UREF##13##19##]. As mothers of larger litters cannot nurse their complete litter simultaneously and as larger litters are weaned later [##UREF##14##20##], females with larger litters can be expected to be generally more responsive to their offspring for a longer period than females with small litters.</p>", "<p>To test the hypothesis that mothers adjust responsiveness to calling pups according to litter size, we provided females with small or large litters through cross-fostering and conducted playback experiments with pup separation calls to test maternal responsiveness. We tested whether lactating mothers of larger (four-pup) experimental litters abandoned their two suckling pups more often than mothers of smaller (two-pup) experimental litters when another pup's separation calls were broadcast. We also tested the mothers' responsiveness to pup separation calls at different times in the lactation period (day 8 and 20; weaning occurs between day 25 and 30 depending on circumstances) and predicted that mothers with large experimental litters should respond stronger at both stages during lactation than mothers with small and less needy experimental litters.</p>" ]

[ "<title>Methods</title>", "<p>We conducted two playback experiments on outbred domestic guinea pigs at the University of Bielefeld, Germany. All subjects were kept indoors on a 14:10 (L:D) photoperiod at 20–23°C. Laboratory guinea pig chow (Höveler, Langenfeld, Germany) and water were provided <italic>ad libitum</italic>, supplemented with hay and fresh food. Females were allowed to breed in groups of two females and one male. 60 multiparous females were paired. Three days prior to the expected parturition date, females were kept singly in holding compartments (0.89 m × 0.89 m × 0.50 m). We created two- and four-pup litters by cross-fostering pups. To treat every litter equally, we cross-fostered pups even if a female's original litter size corresponded to the later experimental litter size, so that each female raised at least one foster pup and most females raised only foster pups and no own pup. We cross-fostered pups from litters born at the same day or on two subsequent days. Due to low synchrony of birth dates we could use only 28 females as experimental animals (13 litters of two and 15 litters of four pups). Original litter sizes did not differ significantly in experimental groups of two- and four-pup litters (Mann-Whitney <italic>U</italic>-test; <italic>U </italic>= 73.5, N₁= 13, N₂= 15, p = 0.27).</p>", "<title>Playback Stimuli</title>", "<p>As playback stimuli we used pup separation calls [##UREF##13##19##]. For separation, a pup was removed from its holding compartment and placed in an enclosure (0.30 × 0.25 × 0.20 m) in an adjacent room. Separation lasted maximally 10 min. As this duration is within the range of natural feeding intervals, we did not provide food and water. We recorded pup separation calls (Fig. ##FIG##0##1##) using a Sennheiser ME 66/K6 directional microphone and a Sony TCD-D100 DAT-recorder. The microphone was located 30 cm above of the box. To avoid that potential developmental changes in call structure with age could confound responses [##UREF##15##21##], we recorded calls from pups of the same age as the pups of the experimental females at the time of the experiment (see below). Recordings were sampled at 44.1 kHz with a resolution of 16 bit and were transferred to a PC. We used Cool Edit 2000 (Syntrillium Corporation, Phoenix, USA) to generate playback files, and to normalize the recorded call series to the same peak amplitude to maintain natural variation in sound amplitude among calls. From the recordings we generated files with a 30 s call sequence (113 ± 6 calls within 30 s) that was repeated 15 times interspersed with 30 s silence so that each playback file had a duration of 15 min. This pattern of calling was within the range of natural calling sequences. In order to avoid pseudoreplication, calls from 72 different pups were used to produce 72 playback files so that each female received in each experimental part a file with separation calls from a different unfamiliar unrelated pup (experiment 1: n = 28; experiment 2: two-pup litter mothers: n = 11, four-pup litter mothers: n = 11, females were tested on day 8 (part 1) and on day 20 (part 2)). Unfamiliar pup separation calls were used because females with small litters did not have three pups which would have been required to generate a unique playback file for each of the three playbacks a female received. Since not all mothers with their pups participated in the experiments due to asynchrony in birth dates, we used preferentially these non-experimental pups for recordings. In a previous study we showed that females respond strongly to unfamiliar pup calls [##UREF##13##19##]. The use of calls recorded from pups of different litter sizes were balanced across experimental groups. Litter size of pups from which calls were recorded (small (one or two pups) versus larger (four or five pups)) did not affect female responses on neither day 8 nor on day 20 (Mann-Whitney <italic>U</italic>-tests; number of calls; all <italic>U </italic>&gt; 7, all p &gt; 0.5; approach, all <italic>U </italic>&gt; 3, all p &gt; 0.06).</p>", "<title>Experimental setup and playback experiments</title>", "<p>All experiments were conducted indoors using a test-arena (1.48 × 0.98 × 0.47 m) in an experimental room acoustically separated from the colony room. In order to familiarize subjects to handling and the test environment, each subject was placed together with its pups in the test-arena for 15 to 30 min two times on the days prior to the experiments.</p>", "<title>Experiment 1</title>", "<p>Here we examined whether mothers of four-pup litters abandoned their suckling pups in response to playback more often than mothers of two-pup litters. We tested lactating females (n = 28) together with two of their pups on day 7 of lactation. On both sides, the test-arena was equipped with huts for shelter and a loudspeaker (Creative Inspire 2.1 2400) placed on each hut (Fig. ##FIG##1##2##). Since mother and pups could lie down for suckling anywhere in the box, we equipped both sides of the test-arena with a loudspeaker. Prior to the experiment all pups were separated from their mothers for 90 to 120 min to ensure that pups were hungry at the start of the experiment. Guinea pigs nurse every 20 to 60 min [##UREF##14##20##]. Thus the separation time is within natural feeding sequences since often not all pups have access to milk during one nursing bout. To maintain possibilities for some social interactions between the pups and their mother, all pups of the litter were jointly separated from their mother by a wire mesh in their holding compartment permitting visual, olfactory and acoustic contact with the mother, but without the possibility to suckle.</p>", "<p>For the playback experiment, a mother was transferred together with two of its pups to the test-arena. In four-pup litters, we randomly selected two pups while the other two pups remained in their holding compartment. When both pups were suckling (mother in nursing position and both pups under the mother for at least 30 s) the playback session started. Playbacks were played directly from a PC and lasted for 15 min. The separation calls were broadcast from the loudspeaker opposite to the animals' position in the box.</p>", "<title>Experiment 2</title>", "<p>Here we tested whether mothers' responsiveness towards pup separation calls changes with offspring age in relation to experimental litter size of two or four pups. Mothers (without their pups) received a playback of pup calls on day 8 and day 20 of lactation; both parts followed the same general experimental procedure. The test-arena was equipped with one hut and one loudspeaker. Guinea pigs use huts for shelter, so we standardized the starting position of the female by providing a hut on the side of the test-arena opposite to the loudspeaker. We exchanged the position of hut and loudspeaker alternatingly between females, in order to control for possible side preferences. For playback, females were taken from their holding compartment and transferred directly to the test-arena. They were accustomed to the environment for 15 min after which the pre-playback period started. Each playback session consisted of a 15 min pre-playback period, and a 15 min playback period. Playbacks were played directly from a PC and females were under the hut at the onset of playback in all trials. In total, 22 females (two-pup litter mothers: N = 11, four-pup litter mothers: N = 11) received playback on day 8 and day 20. Six females had to be excluded because the playback trial either on day 8 or day 20 was disturbed, precluding a comparison between responses on day 8 and 20 in these cases.</p>", "<p>In all experiments, calls were broadcast with a peak sound pressure level (SPL) of 75 dB as measured at 1 m with a sound level meter (Brüel &amp; Kjær precision SPL meter 2233). This corresponds to the amplitude of natural calling as measured on 10 pups (unpublished data). After the experiments, subjects were returned immediately to their regular holding compartment.</p>", "<title>Weaning</title>", "<p>To determine weaning age, pups were placed together with their mother in an elevated observation box (0.72 × 0.54 × 0.25 m) with a plexiglass bottom. Through the bottom it was possible for the observer to distinguish whether pups were suckling or only sitting under the mother. The subjects were familiarized to the box repeatedly during lactation. The observations took place once a day for 30 min from lactation day 18 on until a litter was weaned. When no suckling behaviour was recorded on three subsequent days, the first of these three days was defined as the day of weaning.</p>", "<title>Response measures and statistical analyses</title>", "<p>Responses were recorded by direct observations. The observer [M.K.] sat silently in the same room sidewise to the centre of the test-arena and recorded the subject's behaviour (see below). For experiment 1 we counted how often mothers abandoned their two suckling pups. Since mothers and pups could reunite during the experiment, more than one abandoning of the pups per trial was possible. As responses in experiment 2 we recorded the subjects' vocal and spatial behaviour. In order to quantify the approach toward the loudspeaker, we divided the test-arena into four zones (Fig. ##FIG##1##2##). The observer recorded the subject's vocalizations and position at 10-second intervals over the 15 min playback period. Thus, we obtained 90 data points for vocalizations and for location within each playback session. For analyses we calculated (a) the number of intervals in which vocalizations occurred, (b) the latency to vocalize (in number of intervals), (c) the number of intervals females spent near the loudspeaker (in zone 4) and (d) the latency to approach zone 4 (in number of intervals). Responses were analyzed with Mann-Whitney-U tests and Wilcoxon matched pairs signed-ranks using SPSS 12.5. Two-tailed tests were used throughout. Weaning was analyzed using an analysis of variance, with original and experimental litter size as fixed factors.</p>" ]

[ "<title>Results</title>", "<p>Mothers of four-pup litters abandoned their pups significantly more often and significantly earlier than mothers of two-pup litters (Figs. ##FIG##2##3a, b##; Mann-Whitney <italic>U</italic>-tests; abandoned: <italic>U </italic>= 47; N₁= 13, N₂= 15; p = 0.014; latency to abandon: <italic>U </italic>= 45.5; N₁= 13, N₂= 15; p = 0.015). Except for one female, four-pup-litter mothers abandoned their pups at least once per trial. Moreover, two-pup-litter mothers decreased the time spent near the loudspeaker significantly from day 8 to day 20 of the lactation period (Fig. ##FIG##3##4a##; Wilcoxon test; T = 3, N = 11, p = 0.01) whereas mothers of four-pup litters did not (Fig. ##FIG##3##4a##; Wilcoxon test; T = 34.5, N = 11, p = 0.91). Similarly, calling activity of two-pup-litter mothers decreased significantly from day 8 to day 20 (Fig. ##FIG##3##4b##; Wilcoxon test; T = 0, N = 11, p = 0.001), whereas that of four-pup litter mothers in contrast remained high (Fig. ##FIG##3##4b##; Wilcoxon test; T = 28.5, N = 11, p = 0.72).</p>", "<p>In four-pup litters, neither mothers' latency to vocalize (Wilcoxon test; T = 10, N = 6, p = 0.13, five females had tied scores) nor latency to approach (Wilcoxon test; T = 17, N = 11, p = 0.95) differed significantly between day 8 and day 20. Mothers of two-pup litters had a higher latency to vocalize on day 20 than on day 8 (Wilcoxon test; T = 9, N = 11, p = 0.03) and tended to approach the speaker later on day 20 than on day 8 (Wilcoxon test; T = 5, N = 11, p = 0.078).</p>", "<p>Large experimental litters were weaned on day 30 ± 4.2 (mean ± SD, N = 15), significantly later than small experimental litters, which were weaned on day 25 ± 3.1 (mean ± SD, N = 13). Mothers' original litter size did not influence weaning age significantly (ANOVA: experimental litter size, F_1,27= 10.26, p = 0.004; original litter size, F_1,27= 2.09, p= 0.12). When cross fostering, we controlled for differences in pup birth weigh among litters, so that pups of small and large experimental litters did not differ in mean birth weight (small litters: 83 ± 16 (mean ± SD), N = 13; large litters: 87 ± 20, N = 15; T-test: T = -0.503, p = 0.62). Consistent with earlier studies [##UREF##9##15##,##UREF##16##22##] we found lower growth rates in larger litters, which were also weaned later than smaller litters. Because of later weaning, pups of large litters did not differ from pups of small litters in body mass at time of weaning.</p>" ]

[ "<title>Discussion</title>", "<p>Mothers of large experimental litters abandoned their suckling pups more often than mothers of small experimental litters when separation calls of another pup were broadcast. Moreover, mothers of small litters decreased their responsiveness to pup calls from day 8 to day 20, whereas those of large litters remained strongly responsive. Mothers of small experimental litters also weaned the pups earlier than did mothers of large experimental litters. Thus, guinea pig mothers adjusted their level and time period of responsiveness to experimental litter size.</p>", "<p>Earlier experiments had shown that guinea pig females responded, apart from a general decrease of nursing activity over time [##UREF##17##23##], little if at all, to changes in pup demand by increasing milk yield [##REF##536477##13##] or by adjusting nursing performance [##UREF##8##14##,##UREF##10##16##]. These experiments suggested that females pay surprisingly little attention to pup demand or pup state. However, these studies described nursing behaviour and milk yield and did not observe maternal behavioural responsiveness depending on litter size as our playback experiments did. Thus the playback experiments complement previous studies by showing that females indeed adjust behavioural responsiveness to litter size, even if the litter size they are rearing is not the one they had produced. These results also fit with earlier findings that larger litters are weaned later [##UREF##9##15##,##UREF##10##16##] and suggest that maternal motivation is increased through stimuli provided by larger litters. Previous studies on other rodents also had shown that maternal responsiveness depends on litter size. Maternal nest attendance decreased with increasing litter size in golden hamsters (<italic>Mesocricetus auratus</italic>) [##REF##11483351##24##] and rats <italic>(Rattus norvegicus</italic>) [##UREF##18##25##] which may be due to the increased temperature in the nest or disturbances caused by the activity of many pups. Mongolian gerbil mothers (<italic>Meriones unguiculatus</italic>) with larger litters spent less time in the nest, but licked and sniffed more than mothers with small litters [##UREF##19##26##]. In contrast to these measures of maternal care, our playback experiments provide evidence for changes in maternal responsiveness to pup separation calls in relation to litter size.</p>", "<p>The pup separation calls we tested, differ functionally from begging calls tested in other species. They are emitted only when pups are out of contact with their mother and are not given before and during suckling interactions. Playback experiments on pigs (<italic>Sus scrofa domestica</italic>) demonstrated a stronger response of mothers to needy piglets [##UREF##20##27##]. In these experiments, the smallest and slowest growing young in the litter which had just missed a nursing and were isolated in a relatively cool enclosure, called most intensely. Similarly, in birds a positive relationship between begging intensity and parental feeding rate could be found [##UREF##3##4##,##UREF##21##28##, ####UREF##22##29##, ##UREF##23##30##, ##UREF##24##31####24##31##]. Great tit (<italic>Parus major</italic>) nestlings showed an increase in mean begging rates from experimentally reduced to enlarged broods. Their parents adjusted the feeding rates that were similar per nestling over three brood size [##UREF##25##32##].</p>", "<p>Also, it has been suggested that piglet calls function mainly as a signal to the sow by piglets that are excluded from the current nursing episode [##UREF##20##27##]. Even though our experiments could be interpreted similarly, this function does not seem to apply to the separation calls as used in guinea pigs. Fey and Trillmich [##UREF##9##15##] never observed pups to utter separation calls when they were near their mother but had temporarily no access to the teats in litters of four. These pups would rather dig in under the mother, presumably to wait for an opportunity to access a teat. For female guinea pigs, finding lost pups may play a major role in protection of those pups and may also be important in thermoregulation, particularly for young pups that have only limited energy reserves to maintain thermoregulation. As energy input via milk plays only a minor role late in lactation [##UREF##10##16##], the benefits of lengthening the lactation period may rather be of social function or to support pups' thermoregulation.</p>", "<p>Causally, differences in maternal responsiveness might have been linked to differences in hormonal state, as suggested by correlative studies in humans. In humans, maternal approach behaviour was directly associated with levels of cortisol and multiple regressions revealed that the infants' vocal behavior significantly predicted maternal level of cortisol [##UREF##26##33##]. Mothers showing the highest levels of maternal approach responses were those with a high cortisol concentration and either a positive maternal attitude, or a vocally more active infant. Based on these data, they speculate that for the new mother to exhibit a high level of responsiveness to her infant, she must attain a certain level of arousal [##REF##3287416##34##], which can be produced by elevated cortisol [##REF##4303377##35##]. Moreover, Fey &amp; Trillmich [##UREF##9##15##] showed that maternal cortisol levels in guinea pigs decreased as pups grew older, and mothers rearing a litter of four pups maintained, although not significantly so, higher cortisol levels than those with litters of two pups. Thus, auditory stimuli may affect maternal responsiveness via the general adaptive functions of arousal and evocation of maternal behavior.</p>", "<p>As predicted, guinea pig mothers with large litters actively interrupted nursing and responded to pup separation calls by approaching the loudspeaker whereas mothers of small litters most often did not. This indicates that mothers pay attention to litter size and do not respond when calling pups cannot be their own. We previously showed that females can recognize the calls of their own offspring [##UREF##13##19##] but nevertheless are responsive to calls of unfamiliar pups. This suggests that the costs of such false alarms are lower than the costs of missed detections [##UREF##27##36##]. Such a pattern of response is not unusual as also in ungulate hider species a similar unspecific response of mothers to separation calls has been reported [##UREF##28##37##]. In these species, females do not know the exact hiding location of their offspring and use vocalizations to reunite with the fawns [##UREF##29##38##,##REF##16947115##39##]. Mule deer (<italic>Odocoileus hemionus</italic>) and white-tailed deer (<italic>Odocoileus virginianus</italic>) mothers defend their young vigorously against predators. The fawns' calls activated the mothers and in mule deer, females even responded to separation calls of white tailed deer calves [##UREF##11##17##,##UREF##28##37##]. These authors argue that it may pay more to mistakenly defend a foreign young than to lose the own fawn. However, as females also approached the loudspeaker in an aggressive manner when they were together with their own fawn, factors other than the separation from their fawn must also affect responsiveness to playback by female deer. In contrast to larger mammals, in guinea pigs and their wild ancestors, females have little possibility to actively defend their offspring, as mammalian and bird predators are able to kill the mother as well as the offspring. Therefore, the response by guinea pig mothers is likely to function to reunite with young gone astray rather than in directly defending them. Mothers with larger offspring numbers then presumably respond stronger than those with fewer offspring as it is more likely to lose young in larger litters. Reuniting with these young quickly and thereby preventing them from calling is likely to reduce the danger of attracting the attention of predators.</p>" ]

[ "<title>Conclusion</title>", "<p>Our findings demonstrate that guinea pig mothers adjust maternal responsiveness to increased litter size through an increased response to pup calls and an increase in time to weaning. This contradicts earlier findings which seemed to indicate that maternal responsiveness was determined largely during pregnancy and indicates a more complex mother-pup relation than documented previously.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>In parent-offspring communication, vocal signals are often used to attract attention and offspring might call to induce parental behaviour. In guinea pigs (<italic>Cavia aperea </italic>f. <italic>porcellus</italic>) mothers wean larger litters later than small ones, but it is unknown whether this difference depends on processes induced during pregnancy or is influenced post-natally by the number of pups present. We here tested with playback-experiments using pup separation calls whether mothers with cross-fostered large experimental litters (four-pup-litters) were more responsive to offspring calls and maintained responsiveness for longer than mothers with small experimental litters (two-pup-litters). Mothers were tested when two pups were suckling i.e. when both teats were occupied.</p>", "<title>Results</title>", "<p>Mothers of four-pup litters responded stronger to broadcast pup separation calls than those with two-pup litters. Additionally, we tested the mothers' responsiveness to pup separation calls in the absence of their pups on day 8 and 20 of lactation. Mothers of four-pup litters responded stronger and showed no decrease in responsiveness from day 8 to 20, whereas mothers of two-pup litters responded less and decreased responsiveness from day 8 to 20. Mothers of four-pup litters also weaned their pups 5 days later than those of two-pup litters.</p>", "<title>Conclusion</title>", "<p>Measured by their response to pup calls and by time to weaning, guinea pig mothers adjust maternal responsiveness to litter size. This behaviour is likely to be an adaptive strategy in resource allocation during reproduction.</p>" ]

[ "<title>Authors' contributions</title>", "<p>MK, FT and MN designed the experiments and wrote the manuscript. MK conducted the experiments and analyzed the data.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank the animal care takers and specifically Ursula Rennemann for taking care of the animals during the experimental periods. We thank Karen Fey for helpful suggestions on designing the experiment. We also thank Sandra Düpjan for helpful discussions and comments on earlier drafts of this manuscript. The research was funded in part by a research grant provided by the German research foundation to M.N. and F.T. (DFG grant NA 335/7).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Sound spectrogram of a series of pup separation calls. Calls shown were recorded from an eight days old individual.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Experimental setup for experiment 1: The test-arena was equipped with huts for shelter on both sides of the test-arena and a loudspeaker placed on each hut. The zone closest to the loudspeaker that was used in a given trial was labelled as zone one and the most distant zone as zone four. Mother and pups could lie down for suckling anywhere in the arena. Stimuli were broadcast from the loudspeaker opposite to the animals' position.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Responses of two-pup (<italic>N </italic>= 13) and four-pup (<italic>N </italic>= 15) mothers; (a) frequency to abandon the suckling pups, and (b) latency to abandon the suckling pups (10 sec intervals) during playback of another pup's calls (experiment 1). Each boxplot depicts median with inter-quartile range; whiskers extend to max. 1.5 times the inter-quartile range, outliers are shown as circles.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Responses of two-pup (<italic>N </italic>= 11) and four-pup litter (<italic>N </italic>= 11) mothers; (a) intervals spent in zone 4 (closest to the loudspeaker) and (b) intervals with vocalizations during playback of unfamiliar pup calls on day 8 and day 20 of lactation (experiment 2). Each box plot depicts median with inter-quartile range; whiskers extend to max. 1.5 times the inter-quartile range, outliers are shown as circles.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1742-9994-5-13-1\"/>", "<graphic xlink:href=\"1742-9994-5-13-2\"/>", "<graphic xlink:href=\"1742-9994-5-13-3\"/>", "<graphic xlink:href=\"1742-9994-5-13-4\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>The Childhood Health Assessment Questionnaire (CHAQ) is the most widely utilized functional status measure in paediatric rheumatology today. The CHAQ consists of a disability index (30 items; 8 domains), and a discomfort scale (two visual analogue scales) and can be completed by children as well as their parents/guardians. The CHAQ has shown to be a valid, reliable, and sensitive functional status measure in children with Juvenile Idiopathic Arthritis (JIA) [##REF##7986222##1##]. Over the years the use of the CHAQ has also broadened to other childhood rheumatic conditions [##REF##11361197##2##, ####REF##9307867##3##, ##REF##8666645##4##, ##REF##12508408##5####12508408##5##].</p>", "<p>Despite its advantages and wide use, the CHAQ suffers from a ceiling effect [##REF##15593357##6##]. Therefore it is difficult to discriminate distinct levels of function at the mild end of the disability continuum and to assess improvement in health for less impaired patients [##REF##15593357##6##]. Lam et al. (2004) tried to influence this ceiling effect by testing different response options (visual analogue scale (CHAQ_VAS), categorical (CHAQ_Cat), and choice (CHAQ_Choice)) and by adding eight more challenging items [##REF##15593357##6##]. Respondents were instructed to compare their capabilities to that of their age peers over the last week. The different response options made it possible to asses not only patient's limitations (original CHAQ), but also the patient's strengths. Lam et al. added more challenging items so as to allow less impaired patients to score below the ceiling [##REF##8666645##4##]. The results showed greater sensitivity, a more normal distribution, and a diminished ceiling effect for all three response options. The CHAQ_Catshowed best concordance as a proxy report and might be easiest to complete.</p>", "<p>The scoring rules applied to the original CHAQ are rather complex. The thirty items of the disability index assess eight domains of physical function. Of each domain three components are evaluated: (a) difficulty to perform each activity (0 = no difficulty, 1 = some difficulty, 2 = much difficulty, 3 = unable to do), (b) use of special aids or devices, and (c) required need for assistance of another person. The total score is the average of the highest score in each domain. If component b or c is scored, the minimum score for that domain is two. Takken et al. (2006) questioned the importance of these rules and explored the use of less complex score calculation methods [##REF##16468046##7##]. Their results indicated that calculating the average of the thirty items improves sensitivity to change.</p>", "<p>The main goal of this study was to evaluate the score distributions of the original [##REF##11510312##8##] and the revised version of the Dutch CHAQ_Cat. Furthermore, we wanted to explore the individual influence of different score calculation methods and the eight more challenging items as proposed by Lam et al. (2004) on these score distributions. We hypothesised 1: The revised CHAQ to have a more normal score distribution than the original CHAQ, 2: A less complex score calculation method to improve the score distribution of the original CHAQ, and 3: The eight more challenging items to have a positive influence on the score distributions of both questionnaires.</p>" ]

[ "<title>Methods</title>", "<title>Questionnaires</title>", "<p>The revised CHAQ with the categorical response option was translated and adapted following the absolutist approach with forward translations, consensus meetings, panel review, back translation, and, finally, authorisation by the developers [##REF##8263569##9##].</p>", "<p>Varying with score calculation methods and the eight more challenging items resulted in seven different (score-) versions of the CHAQ (Figure ##FIG##0##1##).</p>", "<title>Participants</title>", "<p>Two convenience samples of children with JIA were studied. As we were studying the ceiling of the CHAQ, patients with remitting disease were also included. Sample A included 59 children from a transition of care study in patients between 12 and 25 years of age. They completed the original CHAQ and the eight more challenging items. Sample B were 31 children who attended the outpatient physical therapy department of the Wilhelmina Children's Hospital (WKZ) and Medical Center Utrecht, for a regular check-up between May 2005 and December 2005. They completed the translated version of the revised CHAQ.</p>", "<title>Statistical analysis</title>", "<p>Data were entered and analysed using SPSS 11.5 for Windows. To evaluate the score distributions of the seven (score-) versions of the CHAQ, box-and-whisker plots and the Kolmogorov-Smirnov (K-S) one-sample test of normality was used. Box-and-whisker plots give a visual representation of the median, the quartiles, and the smallest and greatest value in the distribution. The K-S test statistic represents the largest absolute difference between the observed distribution and theoretical cumulative distribution functions. A p-value less than .05, was considered statistically significant. To analyse the differences between the groups on anthropometric parameters a Student t test was used.</p>" ]

[ "<title>Results</title>", "<title>Participants</title>", "<p>The 59 children from sample A had a mean age of 14.85 (8–25) years and a mean duration of joint complaints of 8.30 (0–20) years. They scored a median of .25 on the original CHAQ with a score range of 0 to 2.86. The 31 patients from sample B had a mean age of 10.81 (4–18) years and a mean duration of joint complaints of 2.90 (0–11) years. They scored a median of -.22 on the revised CHAQ with a score range of -1.55 to +1.05. The characteristics of the participants from both samples are summarized in Table ##TAB##0##1##. Group B was significantly younger (p &lt; .0000) and had significantly shorter disease (p &lt; .0000) compared to group A.</p>", "<title>Hypothesis 1</title>", "<p>As hypothesized, the box-and-whisker plot of the revised CHAQ shows a more normal score distribution than that of the original CHAQ (Figure ##FIG##1##2##). This is also reflected in the K-S one-sample test of normality, with a p-value of .008 for the original CHAQ and .136 (statistically significantly normal) for the revised CHAQ.</p>", "<title>Hypothesis 2</title>", "<p>We also hypothesized that replacing the original score calculation method for a less complex one would improve the score distribution of the original CHAQ. The box-and-whisker plots in the first column of Figure ##FIG##1##2## however show the opposite. After omitting the questions about aids and assistance (Alternative) the ceiling effect raised. The ceiling effect rose even further when the average scores of thirty items were calculated (Mean).</p>", "<title>Hypothesis 3</title>", "<p>Finally, the eight more challenging items indeed have a positive influence on the score distributions of both questionnaires. The middle column of Figure ##FIG##1##2## shows that adding the eight more demanding items to the Alternative and Mean version of the original CHAQ fully compensates for the raise in ceiling effect as seen in the first column. Removing the eight more challenging items from the revised CHAQ (Third column, Figure ##FIG##1##2##), shows a similar change in the score distribution as in the original CHAQ, raising the ceiling effect.</p>" ]

[ "<title>Discussion</title>", "<p>We have shown that the revised version of the Dutch CHAQ_Catshows a significantly normal distribution statistically compared to the original Dutch CHAQ. However, opposed to our hypothesis, a less complex score calculation method of the original CHAQ did not improve the score distribution. Thirdly, the eight more demanding items as proposed by Lam et al. (2004) did have a positive influence on the score distribution of the original CHAQ as well as the revised CHAQ.</p>", "<p>Our results are in agreement with the findings of Lam et al. (2004), but also show a crucial difference. The score distribution of the revised CHAQ was significantly normal statistically, but the score range was very narrow. This limits the applicability of the questionnaire in clinical research and clinical settings, because of a decreased ability to detect changes over time. This difference could be explained by the homogeneous groups in this study with only JIA patients. Lam et al. (2004) included patients with JIA, as well as other rheumatic disorders, injuries, fractures, spina bifida, and hemophilia with a history of haemarthroses. A second possible explanation is seen in the cultural differences. Dutch children seem to underestimate their capabilities compared to Canadian children. Even though they could score between -2 and +2 (+1 and +2 perform better than peers) on the CHAQ_cat, almost all respondents scored below 0.</p>", "<p>Our results did not concur with Takken et al. (2006), who concluded that the original score calculation method of the CHAQ could be replaced with a less complex one without clinical and psychometrical consequences.</p>", "<p>A limitation of this study was that the samples we used were convenience samples consisting of different patients. Sample A was an existing historical data-set of children from a transition of care study in children with JIA between 12 and 25 years of age, and the data of sample B were gathered retrospectively from patient files during January and February of 2006. Both samples did not complete the original as well as the revised CHAQ, but only one or the other (of the two). Therefore the observed differences could in part be caused by differences in patient characteristics, such as age and duration of joint complaints.</p>", "<p>The results of this study confirm a ceiling effect using the original CHAQ-30 with either score calculation method. This emphasises the need for further exploration to improve the CHAQ. The original CHAQ-38, with the \"mean\" score calculation method as well as the revised CHAQ, show less ceiling and therefore are a better alternative for future studies in paediatric rheumatology. However, there is a need for further prospective studies to support our findings.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Objectives</title>", "<p>Evaluating the original, and the revised version of the Dutch Childhood Health Assessment Questionnaire (CHAQ). To explore the effect of different score calculation methods and eight more challenging items as proposed by Lam et al. (2004) on the score distribution in a population of patients with Juvenile Idiopathic Arthritis (JIA).</p>", "<title>Methods</title>", "<p>Two convenience samples of 59 and 31 children with JIA were studied. Box-and-whisker plots and the Kolmogorov-Smirnov (K-S) one-sample test of normality were used, to explore the score distributions.</p>", "<title>Results</title>", "<p>The results of this study confirm a ceiling effect when using the original CHAQ-30 with either score calculation method. The original CHAQ with the added eight more challenging items and the \"mean\" score calculation method, as well as the revised CHAQ showed less ceiling effect.</p>", "<title>Conclusion</title>", "<p>The original CHAQ-38 with the \"mean\" score calculation method as well as the revised CHAQ are a possible alternative for future studies. However, there is a need for further prospective studies to improve the CHAQ and to support our findings.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>JWO summarized the existing literature, prepared and analyzed data of samples A and B and prepared the draft of the manuscript. PhP offered the data set of sample A and supervised data analysis of this sample. TT and JN developed the methodology and supervised the statistical procedures. PJMH facilitated the logistics, the use of the two datasets and senior read the manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank Dr. Brian M. Feldman, from the Department of Paediatric Rheumatology of SickKids, Toronto, Canada, for his contribution to this study.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Score calculation methods of the seven different versions of the Childhood Health Assessment Questionnaire (CHAQ).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Box-and-whisker plots of the seven different versions of the Childhood Health Assessment Questionnaire (CHAQ) Score calculations as described in Fig 1.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Participant characteristics of sample A and B.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Sample A (n = 59; 18 ♂)</td><td align=\"center\">Sample B (n = 31; 16 ♀)</td></tr></thead><tbody><tr><td align=\"left\">Age, mean (range)</td><td align=\"center\">14.85 (8–25)</td><td align=\"center\">10.81* (4–18)</td></tr><tr><td align=\"left\">Duration of joint complaints, mean (range)</td><td align=\"center\">8.34 (0–20)</td><td align=\"center\">2.90* (0–11)</td></tr><tr><td align=\"left\">Original CHAQ, median (range)</td><td align=\"center\">.25 (0–2.86)</td><td align=\"center\">-</td></tr><tr><td align=\"left\">Revised CHAQ, median (range)</td><td align=\"center\">-</td><td align=\"center\">-.22 (-1.55 – +1.05)</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Sample A = patients from the transition of care study in patients with JIA; Sample B = patients who attended the outpatient physical therapy department of the Wilhelmina's Children Hospital and Medical Center Utrecht, for a regular check-up between May 2005 and December 2005. *) p &lt; .0000</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1546-0096-6-14-1\"/>", "<graphic xlink:href=\"1546-0096-6-14-2\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Stress has become frequent in developed countries, as terrorist threats, actions and their aftermaths are experienced in otherwise stable populations. Concern about consequences for offspring whose mothers were stressed during pregnancy derives from strong evidence, from experimental biology, that intrauterine stress can affect neurodevelopment, altering behaviors in animals that are thought relevant to models of cognition, aggression, anxiety and depression [##REF##17515892##1##]. Prenatal stress changes the way that glucocorticoids and sex hormones regulate neurogenesis in the developing brain, e.g. in the hippocampus [##REF##18264994##2##]. By modifying the fetal hypothalamic-adrenal axis (HPA) and other systems, stress in pregnancy perturbs endocrine function in animal models of diabetes, cardiovascular disease and metabolic syndrome. Recent work shows sex differences in fetal responses to maternal stress [##REF##15142991##3##, ####REF##16455779##4##, ##REF##17822726##5##, ##REF##17367828##6####17367828##6##] that may be specific to the gestational age at which the stress is applied experimentally. In humans, too, there is strong evidence that maternal stress in pregnancy can lead to type 2 diabetes, hypertension and metabolic syndrome in the offspring [##REF##17515892##1##]. There are added concerns regarding a contribution of intrauterine stress to human attention deficits, cognitive performance, anxiety, depression, autism and schizophrenia [##REF##17355398##7##,##REF##17444884##8##]. As in experimental animals, there is some evidence in humans for unequal responses of males and females to stress at different stages of intrauterine life [##REF##17444884##8##].</p>", "<p>Epidemiologic observations have linked the incidence of schizophrenia to various maternal stressors during pregnancy, including bereavement [##REF##727894##9##,##REF##18250252##10##], famine [##REF##1449385##11##,##REF##16077049##12##], military invasion [##REF##9715334##13##], flood [##REF##10093869##14##] and earthquake [##REF##10532619##15##]. Reduced cognitive ability [##REF##15240860##16##] and autism [##REF##17619130##17##] have also been linked to such stresses. Until recently, the literature has been limited by low statistical power and it has been seldom possible to separate short term psychic stressors from the long term influence of disrupted environments, diets or lifestyles that might act as chronic stressors during childhood. Moreover, possible effects of season have generally been ignored, as well as demographic variables that tend to vary among births at different seasons (e.g. parental ages and social class).</p>", "<p>While earlier studies lacked specificity regarding the timing of stress and its character, there is emerging evidence that it is early rather than later pregnancy that is the period when maternal stress is most damaging to the fetus [##REF##18250252##10##,##REF##1449385##11##]. Studies in non-human primates also point to very early gestation as the most sensitive period in which intrauterine stress causes adverse outcomes [##REF##10218255##18##]. It is well known from experimental teratology that organ development proceeds in the embryo and fetus in an orderly sequence; anatomical defects can be induced experimentally by radiation, teratogens and/or malnutrition only during short windows of vulnerability. The same is true of the brain [##REF##8455820##19##]. Since for schizophrenia neither mechanism nor lesion is known, identification of a window of vulnerability, if confirmed in other studies, might help understand its etiology or pathogenesis.</p>", "<p>We questioned whether we could detect any change in the incidence of schizophrenia in the Jerusalem Perinatal Study cohort [##REF##17439536##20##] following the Arab-Israeli war of June 1967 (the \"Six Day War\"). That stressor was short-lived; anxiety would have begun on May 18 [##UREF##0##21##] and escalated during preparations for war over the next two weeks. The population of Jerusalem would have been most stressed during the 3 days of bombardment on June 5–7. The war ended with widespread relief on June 11^th[##UREF##0##21##,##UREF##1##22##]. Israelis suffered minimal disruption of the environment and there were no obvious toxic exposures and no famine. Thus we consider this a \"natural experiment\", albeit uncontrolled, in which acute anxiety was divorced from the usual consequences of war. The stress would have been of sufficiently short duration, allowing us to classify its timing by month of gestation, rather than by trimester. Others investigated effects of this war, but applied their research to the whole of Israel and only to trimesters of pregnancy; they found no significant change in the incidence of schizophrenia [##REF##12892867##23##]. We also postulated a priori that effects would vary by sex of offspring and would be most obvious in families likely to be most stressed, i.e. those living nearest to the border, and those with lower social class and lower education.</p>" ]

[ "<title>Methods</title>", "<p>This study relies on the Jerusalem Perinatal Study, a population-based research cohort derived from all births from 1964–76 in Western (Israeli) Jerusalem. The cohort includes data from the birth certificate and additional information from interviews with mothers, depending on the year of birth. The methods are summarized elsewhere [##REF##17439536##20##,##REF##5365594##24##] and characteristics of the population described [##REF##17439536##20##]. The file has been used for research on schizophrenia [##REF##11296097##25##,##REF##17113267##26##] and for other follow-up studies [##REF##17440938##27##, ####REF##17202115##28##, ##REF##17476589##29####17476589##29##].</p>", "<p>Israel has maintained a national Psychiatric Registry since 1950; it includes a summary of all admissions to psychiatric wards and day facilities. The diagnoses for individuals with psychosis have been validated [##REF##15714193##30##]. The Registry has been used for epidemiologic and clinical research in schizophrenia by us [##REF##11296097##25##,##REF##17113267##26##,##REF##16740377##31##] and others [##REF##10964874##32##, ####REF##16626941##33##, ##REF##15229054##34####15229054##34##]. This study is based on data from a pilot study that we undertook to determine whether a linkage was feasible. Personnel at Israel's Ministry of Health matched the Jerusalem cohort to the Psychiatric Registry, using only the offspring's identity numbers. They defined schizophrenia broadly, depending on one or more episodes with discharge diagnoses coded as F20–F29, ie schizophrenia, schizotypal disorder, delusional disorders, non-affective psychoses and schizoaffective disorders (International Classification of Diseases, 10th Revision), hereafter called \"schizophrenia\". They defined \"other\" as individuals without schizophrenia who had any admission(s) recorded in the Registry; these would have included affective, anxiety, personality and eating disorders, and substance abuse. A date of incidence was provided, i.e. date of first event in the Registry. The file was made anonymous by removal of identifying information; because of this, and the way the file was created, we could not aggregate siblings, assess associations within families, study severity of disease or disaggregate the \"other\" category. Creation and use of the file was approved by institutional review boards in Israel and New York and certified as exempt from the requirement of individual informed consent.</p>", "<title>Statistical analysis</title>", "<p>Offspring born in different years were followed up to different ages, so Cox proportional hazards models [##UREF##2##35##] were employed to estimate the effects of maternal stress and covariates, using the PROC PHREG methods provided by SAS (SAS Institute Inc, Cary, NC). The time to diagnosis or death was treated in days from birth; surviving individuals were censored on Jan 1^st1998. For analyses relying on the whole cohort (for which there were no data on gestational age) we estimated fetal age in June 1967 by counting back from the date of birth. We did this using both calendar months and \"standard months\" of ~30.4 days, based on the integer value of 12 times (day of birth/365.25) +1, starting from 1^stJan 1964. We also conducted a sensitivity analysis, shifting the standard month by +15, and -15 days. For a sub-cohort with data on gestational age, we analyzed the data in relation to the estimated dates of conception, defined as date of onset of last menstruation + 16 days. Date of last menstruation was available for 5,100 offspring and for 6,357 others the expected date of delivery was given, from which we assumed that conception had occurred 266 days earlier.</p>", "<p>Covariates chosen for inclusion in the proportional hazards models were those that were significant independent predictors of the incidence of schizophrenia in this cohort, and also varied by season of birth (in this cohort) or following disasters (in others). Such variables included paternal age, treated as a linear continuous variable with unknowns (0.8%) set to the mean (age 30); we treated time since marriage similarly, with unknowns (1.7%) set to the median (5 years), as previously reported [##REF##11296097##25##]. Other variables treated as dichotomies or sets of mutually exclusive categories were maternal age (two categories, i.e. 30–34 and 35+ compared with a reference group of all others); male sex (versus others); the lower third of social class versus (based on the fathers' occupation [##REF##591301##36##]); calendar month (11 categories, the reference category being set arbitrarily at September); and residential area (based on census tract at birth). Results are given as adjusted relative risks of schizophrenia (RRs, i.e. hazard ratios) with 95% confidence intervals (CI), no allowance being made for multiple testing.</p>" ]

[ "<title>Results</title>", "<p>Of the 91,451 live born subjects, 88,829 (97.2%) were traced; linkage with the Psychiatric Registry identified 637 with schizophrenia-related diagnoses and 676 with other psychiatric disorders. As we previously reported [##REF##11296097##25##] the cumulative incidence was estimated as 1.0% by age 30 and in a proportional hazards model, variables significantly predicting incidence included paternal age (relative risk (RR) = 1.39 per decade, 95% confidence limits = 1.2–1.6, p &lt; .0001; male sex (1.4, 1.2–1.6, p = .0002); length of the parents' marriage (0.80, 0.73–0.89, p &lt; .0001 per 5 years); and low social class (1.2, 1.0–1.5, p = .0141). Maternal age was less strongly associated with schizophrenia; compared to age &lt; 30, the RRs associated with ages 30–34 and 35+ were 1.2 (0.94–1.5) and 1.5 (1.1–2.1, p = .0066). All the aforementioned estimates were adjusted for each other.</p>", "<p>We considered whether there were secular or seasonal trends in incidence that might confound the interpretation of findings for any one year (data not tabulated). We found no evidence for change in incidence over the years; comparing offspring born in 1964–67 and 1968–71 with a reference group based on 1972–76 the RRs for schizophrenia were 1.0 (0.90–1.4) and 1.1 (0.9–1.4) respectively, after adjusting for parents' characteristics. There was no significant variation in schizophrenia estimated for any single year and no meaningful trend with the data reanalyzed with \"epidemiologic\" years set from April-March, July-June or October-September. Regarding season, while there were some variations in incidence between individual calendar months, these were not obviously seasonal; furthermore, we found no significant trend for schizophrenia by testing season as sine and cosine transformations of time in an annual cycle, together with their first harmonics. We concluded that it was appropriate to compare the cohort born to women who were pregnant in June 1967 with the entire data set, adjusting for calendar month of birth and demographic variables.</p>", "<p>Table ##TAB##0##1## shows the raw data assessing effects of the war. The left side of the table shows the cohorts defined by calendar month of birth, while the right side of table shows the data re-calculated using standard months of ~30.4 days. The use of standard months shifts few subjects to an earlier or later interval but maintains the general findings. There were 450–500 births per month in 1967 and 1968, except in February 1968 in which there were somewhat fewer, corresponding to a decrease in conceptions in June 1967, i.e. during the war and soon after, or an increased fetal loss. The raw data suggest a two- to three-fold excess of schizophrenia in the cohort born in January 1968, whose mothers would have been in the second month of pregnancy in June 1967. There was a similar excess of other disorders in the cohort born a month earlier, who would have been in the third month of intrauterine life in June 1967. There were somewhat fewer cases of schizophrenia than expected in the cohort born in August 1967 (exposed in the seventh month), and somewhat more of other disorders in the cohort born in June 1967 (exposed in the final month or at birth). There was no unusual incidence of schizophrenia or other conditions among offspring conceived in the three months after the war, or in those born in the three months before it.</p>", "<p>Table ##TAB##1##2## shows the RRs of schizophrenia by sex, estimated using proportional hazards methods to control for confounding variables; and table ##TAB##2##3## shows the same for other psychiatric conditions. The nine birth cohorts exposed in each month of intrauterine life are compared, simultaneously, with the remainder of the cohort. The incidence of schizophrenia was more than doubled for offspring who were in the second month of gestation in June 1967. The risk for other psychiatric disorders was also increased for those who were in the third month of pregnancy at that time, confirming the findings in table ##TAB##0##1##. In both schizophrenia (table ##TAB##1##2##) and other conditions (table ##TAB##2##3##) effects observed after the war were stronger in females than in males.</p>", "<p>When the intrauterine exposure to the war was classified by trimesters rather than by months, differences were smaller and not significant. Offspring whose mothers were in the first, second and third trimesters during the war showed adjusted RRs, respectively of 1.33 (0.80–2.12), 0.95 (0.53–1.71) and 0.62 (0.30–1.26). For other psychiatric conditions the corresponding RRs were 1.13 (0.67–1.93), 0.68 (0.33–1.38) and 1.49 (0.94–2.34).</p>", "<p>We conducted a post-hoc analysis of schizophrenia comparing the cohort presumed to have been in the second month of gestation at the time of the June 1967 war versus all others (data not tabulated). The excess incidence was observed more in offspring of fathers aged &lt; 30 (RR = 3.7, 1.4–10.0, based on 5 cases in 227 offspring versus 194/39,602) than in offspring of fathers aged 30+ (1.5, 0.5–4.3, based on 4/405 vs 284/47,691); more in association with the two lower social classes (4.3, 1.7–11, 7/210 vs 186/23,687) than in the four higher social classes (0.9, 0.2–3.6, 2/427 vs 298/64,505) and more in those whose mothers had 0–8 years of education (3.2, 1.4–7.5, 7/254 vs 209/29,661) than in those with 9+ years of education (0/331 vs 193/52,504). Residence in census tracts bordering the 1948 border was not a general risk factor for schizophrenia in the whole cohort (RR = 1.1, 0.6–2.0 based on 9 cases in 1,125 offspring); however, this residential area showed an excess risk of schizophrenia in those who were in the second month of intrauterine life during the war (RR = 33, 2.7–400 based on 2 cases in 7 offspring versus a reference group of 7 cases in 1116 offspring).</p>", "<p>We did not extend the study to cover the 1973 war because insufficient time had passed for the accrual of cases of schizophrenia. A preliminary analysis, however, suggested consistent findings; there was an increased incidence of schizophrenia in offspring of mothers who had been in the second month of gestation in October 1973 (RR = 1.4, 0.6–3.5) and of other conditions in those who were in the third month (RR = 1.9, 0.9–4.1).</p>", "<p>We questioned whether the excess risk of schizophrenia after the June 1967 war might be associated with changes in the distribution of birth weight or gestational age, since maternal stress is believed to contribute to pre-term birth [##REF##15715585##37##] and low birth weight has been associated with schizophrenia [##REF##16306181##38##]. In this cohort, there was a weak and non-significant relationship between low birth weight (&lt; 2500 g) and schizophrenia (RR = 1.2, 0.9–1.7) after controlling for confounding variables. In the cohort estimated to have been in the second month of intrauterine life in June 1967 we observed an unusually low proportion of low birth weight offspring (3.2% versus 6.3% expected). Controlling for low birth weight, however, increased the RR for schizophrenia and narrowed its confidence interval. Similarly, controlling for low birth weight led to a small increase in the RR of other psychiatric disorders, for those in the third month of gestation during the war.</p>", "<p>To corroborate the findings from the whole cohort, we studied the sub-cohort (N = 11,467) with data on of last menstrual date and/or expected date of delivery. From the 11,040 traced live-born offspring, we excluded 1,421 with uncertain gestational age (day of month set at \"0\" or \"10\"), leaving 9,519 available for analysis, with 91 cases of schizophrenia. Figure ##FIG##0##1## shows adjusted relative risks of schizophrenia according to estimated gestational age in the war. There were wide confidence limits so that none of the RRs were statistically significant; however, they confirm an increased incidence of schizophrenia and other conditions in offspring whose mothers were stressed in early pregnancy (specifically in the second month) and fewer than expected cases of schizophrenia following stress in later pregnancy. This conclusion was unchanged after controlling for pre-term births (i.e. gestations of less than 37 weeks) or for low birth weight (&lt; 2500 g). The figure also suggests an excess incidence of other conditions in early pregnancy.</p>", "<p>Conclusions for this study were not altered further adjustment for ethnic groups or by restricting the cohort to singleton births or to Jews.</p>" ]

[ "<title>Discussion</title>", "<p>This pilot study shows that a time-limited threat likely to have caused severe anxiety in pregnant women was associated with an altered incidence of schizophrenia in the offspring. Although based on small numbers, our results are consistent with the studies from Finland [##REF##727894##9##], the Netherlands [##REF##1449385##11##] and Denmark [##REF##18250252##10##] that pointed to early pregnancy as a period of vulnerability to stress, for schizophrenia. Our prior hypothesis, building on knowledge from teratology, was that fetal effects of maternal stress, if found, would be limited to a short window of time, though we did not specify in advance which would be the most vulnerable month.</p>", "<p>This study's finding of sex differences is also consistent with previous publications linking schizophrenia to famine in the Netherlands and China. The Dutch famine of 1945 [##REF##1449385##11##] was followed by a significantly increased incidence of schizophrenia in females born after maternal starvation during the first trimester, or in both first and second trimesters, but was not significantly altered by starvation in the second or third trimesters. In males, schizophrenia was not significantly related to the Dutch famine; however, there was a subtle decrease in its incidence following maternal starvation during the second trimester [##REF##1449385##11##] a subsequent study showed those males to be suffering more from unipolar affective disorders [##REF##10671386##39##]. The Chinese famine of 1959–61 was followed by an increased incidence of schizophrenia among adults born in those years, with a decreased proportion of males among cases [##REF##16077049##12##], suggesting that the increase might have been more severe among females, or that females vulnerable to schizophrenia might have survived better than similarly vulnerable males. After the 9/11 terrorist attack in New York, there was evidence for a selective loss (i.e. spontaneous abortion) of male fetuses. This was observed not only in New York [##REF##16936298##40##] but also in California [##REF##15734763##41##], so it can be attributed to maternal stress alone, rather than to a toxic environment. Thus, the sex difference in schizophrenia observed in the Jerusalem, Dutch and Chinese cohorts might be explained either by greater vulnerability of females to stress (or starvation), or by a greater mortality of vulnerable males.</p>", "<p>The most convincing evidence that schizophrenia can follow intrauterine stress derives from investigations of mothers bereaved in pregnancy. Bereavement is a stressor that is not normally accompanied by famine or a toxic environment. In a national register in Finland, Huttunen and Niskanen compared the offspring of 167 mothers whose husbands died during their pregnancy versus those of 168 similarly bereaved after delivery [##REF##727894##9##]. There was an excess incidence of schizophrenia in the first group, especially when the husband's death occurred early in gestation. A much larger study was reported recently by Khashan et al using the national registry in Denmark; with a follow-up of 10–32 years they observed 1893 cases of schizophrenia (0.3% of the cohort) [##REF##18250252##10##]. The death of one or more of the mother's first degree relatives was linked to a statistically significant excess of schizophrenia, with RR = 1.6–1.7, if the death occurred in the first trimester. Furthermore, the Danish study showed a non-significant reduction in schizophrenia if the death occurred in the third trimester; our findings are similar. Neither the Finnish nor the Danish studies separated males from females; future studies should do this and attempt to determine specificity of timing in gestation, more narrowly than by trimester.</p>", "<p>Strengths of the Jerusalem study include its prospective design, a follow-up of 22–34 years, an unusually circumscribed psychological stressor and our ability to stratify by sex, consider season and control for potential confounders such as paternal age. Use of a previously defined cohort and of Israel's national Psychiatric Registry assures an unbiased ascertainment of \"exposure\" relative to \"outcome\", without the need to rely on maternal recall or question the diagnosis; diagnoses of psychoses have been recently validated [##REF##15714193##30##]. An additional advantage is the availability of a sub-cohort with information of gestational age, which, though small, permits us to corroborate the findings based on the entire cohort. A limitation is the small numbers. Also, in common with most other previous studies, ours suffers from the drawback from the absence of information on length of gestation. If maternal stress were to lead to an excess of pre-term births in vulnerable pregnancies, and if these were the same individuals vulnerable to schizophrenia in the future, then there might be a systematic bias in the estimation of gestational age in the affected cases; gestations might have been more advanced that we can estimate. Because of this, our results should be regarded as \"hypothesis generating\" rather than proof that the moment of greatest vulnerability to schizophrenia occurs in the second, rather than any other, gestational month. Others limitations are that we cannot assess in this pilot study which of the \"other\" diagnostic categories were related to the June 1967 war; and because the cohort has not yet reached middle age, not all potential cases of schizophrenia have become known. We do not know how individual mothers experienced the war, what was their previous or ancestral response to stress, or whether they were injured or bereaved in June 1967 and might have been medicated; and we do not yet know whether the risk of schizophrenia in the offspring might have been modified by events in post-natal life.</p>", "<p>There is overwhelming experimental evidence that stress to pregnant mammals alters neurodevelopment in the offspring and affects their subsequent behavior, both in childhood and as adults [##REF##14717652##42##, ####REF##15919579##43##, ##REF##16169164##44##, ##REF##16469780##45####16469780##45##]. Furthermore, maternal stress permanently programs metabolic and cardiovascular physiology [##REF##17515892##1##] in the offspring, with consequences for longevity. Almost all of the experimental work, however, has applied stress in mid- or later pregnancy. Mechanisms are unclear and the nature and reasons for sex differences even more so, but experimental and human data suggest that both the neurobehavioral and metabolic effects seem to depend on the same mechanisms, or similar ones [##REF##17444884##8##,##REF##17663659##46##]. These mechanisms involve perturbation of the HPA axis, glucocorticoids and catecholamines [##REF##16169164##44##,##REF##17663659##46##,##REF##15811500##47##], changes in the \"set points\" for physiologic feedback loops (e.g. leptin, insulin, cortisol) [##REF##15944068##48##] and alterations in ways individuals sense and respond, in the future, to dynamic changes in the environment [##REF##17444884##8##]. Current thinking is that the signal is achieved by epigenetic changes (e.g. methylation at CpG islands, or modification of histones) that alter gene expression and that genetic variability may alter vulnerability (e.g. deficiencies in genes affecting 1-carbon metabolism (methylation)); if so, genetically vulnerable individuals might be protected by modification of the diet at the time of being stressed.</p>", "<p>The knowledge that maternal stress affects the fetus has important implications for mental health in a world threatened by acute violence and war. Terrorist acts have stressed whole populations nation-wide, while more locally, hurricanes and earthquakes are recurring stressors in some countries. Smaller communities or individuals can be affected acutely by tornados, episodes of community violence, accidents, bereavement, domestic violence or rape. A significant component of the public burden of mental illness may follow such frights to pregnant women. The subject of intrauterine stress and major psychiatric disorders deserves further scrutiny. Well designed research studies should be aimed at elucidating the pathways to risk and at defining strategies and interventions for prevention.</p>" ]

[ "<title>Conclusion</title>", "<p>This study confirms previous reports of an excess incidence of schizophrenia in offspring born to mothers who experienced stress in early pregnancy. It suggests both sex specificity and a relatively narrow window of vulnerability, in the second month of pregnancy.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Schizophrenia has been linked with intrauterine exposure to maternal stress due to bereavement, famine and major disasters. Recent evidence suggests that human vulnerability may be greatest in the first trimester of gestation and rodent experiments suggest sex specificity. We aimed to describe the consequence of an acute maternal stress, through a follow-up of offspring whose mothers were pregnant during the Arab-Israeli war of 1967. A priori, we focused on gestational month and offspring's sex.</p>", "<p>In a pilot study linking birth records to Israel's Psychiatric Registry, we analyzed data from a cohort of 88,829 born in Jerusalem in 1964–76. Proportional hazards models were used to estimate the relative risk (RR) of schizophrenia, according to month of birth, gender and other variables, while controlling for father's age and other potential confounders. Other causes of hospitalized psychiatric morbidity (grouped together) were analyzed for comparison.</p>", "<p>There was a raised incidence of schizophrenia for those who were in the second month of fetal life in June 1967 (RR = 2.3, 1.1–4.7), seen more in females (4.3, 1.7–10.7) than in males (1.2, 0.4–3.8). Results were not explained by secular or seasonal variations, altered birth weight or gestational age. For other conditions, RRs were increased in offspring who had been in the third month of fetal life in June 1967 (2.5, 1.2–5.2), also seen more in females (3.6, 1.3–9.7) than males (1.8, 0.6–5.2).</p>", "<p>These findings add to a growing literature, in experimental animals and humans, attributing long term consequences for offspring of maternal gestational stress. They suggest both a sex-specificity and a relatively short gestational time-window for gestational effects on vulnerability to schizophrenia.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>DM conceived and coordinated the studies of schizophrenia and participated in drafting the manuscript. CC, KRK and MCP reviewed literature and participated in drafting the manuscript. SF and DN participated in design and coordination of the study. YF oversaw management of the Jerusalem cohort in Israel. SH conceived the analysis and participated in drafting the manuscript. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-244X/8/71/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>Supported by grants from the National Institutes of Health: 1R01 MH059114 (DM); 2 K24 MH001699 (DM); 1R01 CA080197 (SH); 5K23MH066279-02 (CC) and from the National Alliance for Research of Schizophrenia and Depression (NARSAD) (DM, SH). The authors thank Ezra Susser and Caitlin Warinsky for their contributions to the intellectual and editorial components of this manuscript.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Relative risks of schizophrenia and other psychiatric conditions in offspring born to mothers pregnant during war of June 1967.</bold> Sub-cohort of 9,519 offspring with information on gestational age.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Numbers of offspring born (N), cases of schizophrenia (Schiz) and other psychiatric disorders (Other psych) in the months surrounding June 1967, by month of birth and estimated stage of life during the war.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Estimated stage of life during war of June 1967</bold></td><td align=\"right\"><bold>Date of birth</bold></td><td align=\"center\" colspan=\"3\"><bold>Data based on calendar month of birth</bold></td><td align=\"center\" colspan=\"3\"><bold>Data based on standard month of birth</bold></td></tr></thead><tbody><tr><td/><td/><td align=\"right\">N</td><td align=\"right\">Schiz</td><td align=\"right\">Other psych</td><td align=\"right\">N</td><td align=\"right\">Schiz</td><td align=\"right\">Other psych</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\" colspan=\"2\"><bold>Before conception (months)</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">   -3</td><td align=\"right\">May 1968</td><td align=\"right\">505</td><td align=\"right\">4</td><td align=\"right\">2</td><td align=\"right\">505</td><td align=\"right\">4</td><td align=\"right\">2</td></tr><tr><td align=\"left\">   -2</td><td align=\"right\">Apr 1968</td><td align=\"right\">512</td><td align=\"right\">2</td><td align=\"right\">4</td><td align=\"right\">512</td><td align=\"right\">2</td><td align=\"right\">4</td></tr><tr><td align=\"left\">   -1</td><td align=\"right\">Mar 1968</td><td align=\"right\">498</td><td align=\"right\">3</td><td align=\"right\">5</td><td align=\"right\">498</td><td align=\"right\">3</td><td align=\"right\">5</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\" colspan=\"2\"><bold>Gestational age (months)</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">   1</td><td align=\"right\">Feb 1968</td><td align=\"right\">410</td><td align=\"right\">4</td><td align=\"right\">3</td><td align=\"right\">420</td><td align=\"right\">5</td><td align=\"right\">3</td></tr><tr><td align=\"left\">   2</td><td align=\"right\">Jan 1968</td><td align=\"right\">486</td><td align=\"right\">10</td><td align=\"right\">1</td><td align=\"right\">493</td><td align=\"right\">9</td><td align=\"right\">3</td></tr><tr><td align=\"left\">   3</td><td align=\"right\">Dec 1967</td><td align=\"right\">501</td><td align=\"right\">3</td><td align=\"right\">11</td><td align=\"right\">484</td><td align=\"right\">3</td><td align=\"right\">9</td></tr><tr><td align=\"left\">   4</td><td align=\"right\">Nov 1967</td><td align=\"right\">443</td><td align=\"right\">4</td><td align=\"right\">1</td><td align=\"right\">443</td><td align=\"right\">4</td><td align=\"right\">1</td></tr><tr><td align=\"left\">   5</td><td align=\"right\">Oct 1967</td><td align=\"right\">470</td><td align=\"right\">4</td><td align=\"right\">4</td><td align=\"right\">470</td><td align=\"right\">4</td><td align=\"right\">4</td></tr><tr><td align=\"left\">   6</td><td align=\"right\">Sept 1967</td><td align=\"right\">466</td><td align=\"right\">4</td><td align=\"right\">3</td><td align=\"right\">466</td><td align=\"right\">4</td><td align=\"right\">3</td></tr><tr><td align=\"left\">   7</td><td align=\"right\">Aug 1967</td><td align=\"right\">488</td><td align=\"right\">1</td><td align=\"right\">6</td><td align=\"right\">488</td><td align=\"right\">1</td><td align=\"right\">6</td></tr><tr><td align=\"left\">   8</td><td align=\"right\">Jul 1967</td><td align=\"right\">483</td><td align=\"right\">4</td><td align=\"right\">5</td><td align=\"right\">460</td><td align=\"right\">4</td><td align=\"right\">5</td></tr><tr><td align=\"left\">   9</td><td align=\"right\">Jun 1967</td><td align=\"right\">480</td><td align=\"right\">3</td><td align=\"right\">10</td><td align=\"right\">503</td><td align=\"right\">3</td><td align=\"right\">10</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\" colspan=\"2\"><bold>Post-natal age (months)</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">   1</td><td align=\"right\">May 1967</td><td align=\"right\">512</td><td align=\"right\">3</td><td align=\"right\">3</td><td align=\"right\">496</td><td align=\"right\">3</td><td align=\"right\">3</td></tr><tr><td align=\"left\">   2</td><td align=\"right\">Apr 1967</td><td align=\"right\">424</td><td align=\"right\">4</td><td align=\"right\">5</td><td align=\"right\">424</td><td align=\"right\">4</td><td align=\"right\">3</td></tr><tr><td align=\"left\">   3</td><td align=\"right\">Mar 1967</td><td align=\"right\">471</td><td align=\"right\">4</td><td align=\"right\">4</td><td align=\"right\">476</td><td align=\"right\">4</td><td align=\"right\">6</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Numbers of cases, relative risks (RR) and 95% confidence limits (CL) for schizophrenia, by standard month of birth and sex.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Estimated gestational month in June 1967</bold></td><td align=\"center\"><bold>Date of birth</bold></td><td align=\"center\" colspan=\"3\"><bold>Total, including unknown sex</bold></td><td align=\"center\" colspan=\"3\"><bold>Males</bold></td><td align=\"center\" colspan=\"3\"><bold>Females</bold></td></tr><tr><td/><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td/><td/><td align=\"right\"><bold>Cases</bold></td><td align=\"right\"><bold>RR¹</bold></td><td align=\"left\"><bold>95% CL¹</bold></td><td align=\"right\"><bold>Cases</bold></td><td align=\"right\"><bold>RR</bold></td><td align=\"left\"><bold>95% CL¹</bold></td><td align=\"right\"><bold>Cases</bold></td><td align=\"right\"><bold>RR</bold></td><td align=\"left\"><bold>95% CL¹</bold></td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">Feb 1968</td><td align=\"right\">5</td><td align=\"right\">1.09</td><td align=\"left\">0.44–2.72</td><td align=\"right\">5</td><td align=\"right\">2.01</td><td align=\"left\">0.81–5.41</td><td align=\"right\">0</td><td align=\"right\">-</td><td align=\"left\">-</td></tr><tr><td align=\"center\">2</td><td align=\"center\">Jan 1968</td><td align=\"right\">9</td><td align=\"right\"><bold>** </bold>2.28</td><td align=\"left\">1.12–4.65</td><td align=\"right\">3</td><td align=\"right\">1.17</td><td align=\"left\">0.36–3.83</td><td align=\"right\">6</td><td align=\"right\">*** 4.33</td><td align=\"left\">1.71–11.0</td></tr><tr><td align=\"center\">3</td><td align=\"center\">Dec 1967</td><td align=\"right\">3</td><td align=\"right\">0.76</td><td align=\"left\">0.24–2.44</td><td align=\"right\">1</td><td align=\"right\">0.43</td><td align=\"left\">0.06–3.16</td><td align=\"right\">2</td><td align=\"right\">1.23</td><td align=\"left\">0.29–5.28</td></tr><tr><td align=\"center\">4</td><td align=\"center\">Nov 1967</td><td align=\"right\">4</td><td align=\"right\">1.07</td><td align=\"left\">0.38–3.00</td><td align=\"right\">3</td><td align=\"right\">1.30</td><td align=\"left\">0.40–4.27</td><td align=\"right\">1</td><td align=\"right\">0.71</td><td align=\"left\">0.09–5.34</td></tr><tr><td align=\"center\">5</td><td align=\"center\">Oct 1967</td><td align=\"right\">4</td><td align=\"right\">0.82</td><td align=\"left\">0.30–2.27</td><td align=\"right\">3</td><td align=\"right\">1.17</td><td align=\"left\">0.36–3.83</td><td align=\"right\">1</td><td align=\"right\">0.44</td><td align=\"left\">0.06–3.22</td></tr><tr><td align=\"center\">6</td><td align=\"center\">Sept 1967</td><td align=\"right\">4</td><td align=\"right\">0.99</td><td align=\"left\">0.36–2.74</td><td align=\"right\">2</td><td align=\"right\">0.92</td><td align=\"left\">0.22–3.88</td><td align=\"right\">2</td><td align=\"right\">1.06</td><td align=\"left\">0.25–4.50</td></tr><tr><td align=\"center\">7</td><td align=\"center\">Aug 1967</td><td align=\"right\">1</td><td align=\"right\">0.26</td><td align=\"left\">0.04–1.89</td><td align=\"right\">0</td><td align=\"right\">-</td><td align=\"left\">-</td><td align=\"right\">1</td><td align=\"right\">0.94</td><td align=\"left\">0.12–7.22</td></tr><tr><td align=\"center\">8</td><td align=\"center\">Jul 1967</td><td align=\"right\">4</td><td align=\"right\">0.97</td><td align=\"left\">0.35–2.67</td><td align=\"right\">1</td><td align=\"right\">0.45</td><td align=\"left\">0.06–3.26</td><td align=\"right\">3</td><td align=\"right\">1.58</td><td align=\"left\">0.47–5.30</td></tr><tr><td align=\"center\">9</td><td align=\"center\">Jun 1967</td><td align=\"right\">3</td><td align=\"right\">0.64</td><td align=\"left\">0.20–2.03</td><td align=\"right\">1</td><td align=\"right\">0.35</td><td align=\"left\">0.05–2.57</td><td align=\"right\">2</td><td align=\"right\">1.07</td><td align=\"left\">0.25–4.55</td></tr><tr><td colspan=\"11\"><hr/></td></tr><tr><td align=\"center\">Comparison group (all others)</td><td align=\"center\">1964–76</td><td align=\"right\">602</td><td align=\"right\">1</td><td align=\"left\">reference</td><td align=\"right\">355</td><td align=\"right\">1</td><td align=\"left\">reference</td><td align=\"right\">245</td><td align=\"right\">1</td><td align=\"left\">reference</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Numbers of cases, relative risks (RR) and 95% confidence limits (CL) for other psychiatric conditions, by standard month of birth and sex.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Estimated gestational month in June 1967</bold></td><td align=\"center\"><bold>Date of birth</bold></td><td align=\"center\" colspan=\"3\"><bold>Total, including unknown sex</bold></td><td align=\"center\" colspan=\"3\"><bold>Males</bold></td><td align=\"center\" colspan=\"3\"><bold>Females</bold></td></tr><tr><td/><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td/><td/><td align=\"right\"><bold>Cases</bold></td><td align=\"right\"><bold>RR¹</bold></td><td align=\"left\"><bold>95% CL²</bold></td><td align=\"right\"><bold>Cases</bold></td><td align=\"right\"><bold>RR</bold></td><td align=\"left\"><bold>95% CL¹</bold></td><td align=\"right\"><bold>Cases</bold></td><td align=\"right\"><bold>RR</bold></td><td align=\"left\"><bold>95% CL¹</bold></td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">Feb 1968</td><td align=\"right\">3</td><td align=\"right\">0.73</td><td align=\"left\">0.23–2.34</td><td align=\"right\">3</td><td align=\"right\">1.11</td><td align=\"left\">0.34–3.64</td><td align=\"right\">0</td><td align=\"right\">-</td><td align=\"left\">-</td></tr><tr><td align=\"center\">2</td><td align=\"center\">Jan 1968</td><td align=\"right\">3</td><td align=\"right\">0.60</td><td align=\"left\">0.19–1.92</td><td align=\"right\">2</td><td align=\"right\">0.61</td><td align=\"left\">0.15–2.52</td><td align=\"right\">1</td><td align=\"right\">0.57</td><td align=\"left\">0.08–4.25</td></tr><tr><td align=\"center\">3</td><td align=\"center\">Dec 1967</td><td align=\"right\">9</td><td align=\"right\"><bold>** </bold>2.51</td><td align=\"left\">1.22–5.17</td><td align=\"right\">4</td><td align=\"right\">1.82</td><td align=\"left\">0.63–5.24</td><td align=\"right\">5</td><td align=\"right\">*** 3.55</td><td align=\"left\">1.31–9.65</td></tr><tr><td align=\"center\">4</td><td align=\"center\">Nov 1967</td><td align=\"right\">1</td><td align=\"right\">0.22</td><td align=\"left\">0.03–1.61</td><td align=\"right\">0</td><td align=\"right\">-</td><td align=\"left\">-</td><td align=\"right\">1</td><td align=\"right\">0.51</td><td align=\"left\">0.07–3.77</td></tr><tr><td align=\"center\">5</td><td align=\"center\">Oct 1967</td><td align=\"right\">4</td><td align=\"right\">1.02</td><td align=\"left\">0.37–2.87</td><td align=\"right\">1</td><td align=\"right\">0.46</td><td align=\"left\">0.06–3.39</td><td align=\"right\">3</td><td align=\"right\">1.76</td><td align=\"left\">0.52–5.93</td></tr><tr><td align=\"center\">6</td><td align=\"center\">Sept 1967</td><td align=\"right\">3</td><td align=\"right\">0.90</td><td align=\"left\">0.28–2.92</td><td align=\"right\">1</td><td align=\"right\">0.63</td><td align=\"left\">0.09–4.71</td><td align=\"right\">2</td><td align=\"right\">1.14</td><td align=\"left\">0.27–4.87</td></tr><tr><td align=\"center\">7</td><td align=\"center\">Aug 1967</td><td align=\"right\">6</td><td align=\"right\">1.56</td><td align=\"left\">0.67–3.65</td><td align=\"right\">3</td><td align=\"right\">1.20</td><td align=\"left\">0.37–3.91</td><td align=\"right\">3</td><td align=\"right\">2.25</td><td align=\"left\">0.66–7.69</td></tr><tr><td align=\"center\">8</td><td align=\"center\">Jul 1967</td><td align=\"right\">5</td><td align=\"right\">1.04</td><td align=\"left\">0.42–2.60</td><td align=\"right\">4</td><td align=\"right\">1.81</td><td align=\"left\">0.64–5.13</td><td align=\"right\">1</td><td align=\"right\">0.38</td><td align=\"left\">0.05–2.79</td></tr><tr><td align=\"center\">9</td><td align=\"center\">Jun 1967</td><td align=\"right\">10</td><td align=\"right\">* 1.97</td><td align=\"left\">1.01–3.85</td><td align=\"right\">6</td><td align=\"right\">1.89</td><td align=\"left\">0.80–4.46</td><td align=\"right\">4</td><td align=\"right\">2.11</td><td align=\"left\">0.73–6.10</td></tr><tr><td colspan=\"11\"><hr/></td></tr><tr><td align=\"center\">Comparison group (all others)</td><td align=\"center\">1964–76</td><td align=\"right\">633</td><td align=\"right\">1</td><td align=\"left\">reference</td><td align=\"right\">363</td><td align=\"right\">1</td><td align=\"left\">reference</td><td align=\"right\">270</td><td align=\"right\">1</td><td align=\"left\">reference</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>1. Adjusted for paternal age (continuous), maternal age (30–34, 35+ versus all others), low social class (father's occupation group 5,6 versus 1–4), years married and month of birth. 2. Additionally adjusted for sex. <bold>** p &lt; .03; *** p &lt; .003</bold>.</p></table-wrap-foot>", "<table-wrap-foot><p>1. Adjusted for paternal age (continuous), maternal age (30–34, 35+ versus all others), low social class (father's occupation group 5,6 versus 1–4), years married and month of birth. 2. Additionally adjusted for sex. * p &lt; .05; **p &lt; .02 *** p &lt; .003.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-244X-8-71-1\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Several studies note that International Medical Graduates (IMGs) experience additional problems relative to their Canadian counterparts such as loneliness, social isolation, concerns related to family members left behind in home countries, a decrease in social status with an accompanying diminishment of self-esteem, lack of financial resources and worries about visas/immigration issues [##REF##16141132##1##,##REF##10211237##3##]. Although some demographic commonalities exist among IMGs (such as generally being older, previously trained and/or practicing, and responsible for supporting a family), heterogeneity is also found due to variations in their life stages and perceptions of health and health care [##REF##11154193##4##,##REF##12719314##5##]. Furthermore, the level of medical training they have received prior to entering residency varies, which may prove challenging to supervisors. To address the difficulties IMGs face, previous studies find that exposure to an orientation program prior to entering postgraduate training is beneficial [##REF##8505686##6##].</p>", "<p>However, most orientation programs tend to concentrate on a specific skill, namely communication or cultural-sensitivity training. In a pilot study conducted at one Canadian medical school, IMGs participated in an 18-hour communication program, focusing on doctor-patient and doctor-colleague interaction during the first year of residency. Although the sample size was small, self-evaluations scores showed significant improvement after these sessions [##REF##17470106##7##]. In another study, IMGs in one residency program were divided into two experimental groups to measure Emotional Resilience, Flexibility, Perceptual Acuity and Personal Autonomy. After cultural-sensitivity training, the experimental group (Group A) scored significantly higher in flexibility, emotional resilience and perceptual acuity than the control group. These IMGs were more self-confident, willing to learn from others, and able to correctly assess verbal and non-verbal cues [##REF##10211237##3##].</p>", "<p>In light of this, a needs assessment study was conducted at the University of Toronto to explore the extent that these specific issues were challenging for IMGs in a residency program from the perspective of Program Directors and foreign-trained physicians themselves.</p>" ]

[ "<title>Methods</title>", "<title>Survey Instrument</title>", "<p>Separate surveys were created for IMGs and Program Directors using iterative input from an expert panel of three faculty members. These individuals have worked with IMGs over the past four years with particular emphasis on mentoring, teaching and developing remediation plans.</p>", "<p>Ten common issues were posed to both groups and covered the following three topics: Clinical Knowledge and Skills (3), Communication and Working Relations (4), and Macro Issues (3). These issues were identified by the expert panel as being the most pertinent and common across all subspecialties. For the purpose of this study, Macro Issues were defined as areas of concern affecting institutional, environmental or cultural experience and performance.</p>", "<p>Currently, there is limited research exploring the impact of macro-level issues as challenges to the medical training of IMGs. Adapting to a new environment involves much more than learning how to communicate effectively. Essentially, the culture and principles, as well as the rules and procedures inherent in everyday operations of an organization, must be learned. Whether this translates to learning how to request a MRI or how to use software to track a patient's medical records, experiencing difficulty in adapting to a new environment may be mitigated by learning about these issues. Hence, under this premise, the survey included macro-level issues such as knowledge of the Canadian Healthcare System, knowledge of the hospital system (e.g. how to use pagers and computer software as well as adapting to hospital protocols) and hospital and pharmaceutical formularies.</p>", "<p>Using a 5-point Likert scale, IMGs indicated to what extent each issue posed as a challenge to them during their residency. Program Directors were asked to what extent these issues were challenges to IMGs using the same scale. Further, both groups were asked whether an orientation program, in the form of a horizontal curriculum, was necessary for incoming IMGs. For this study, a horizontal curriculum is defined as a course of study with specific learning objectives for the purpose of obtaining a goal (i.e. providing a smoother transition of IMGs into residency programs at the University of Toronto).</p>", "<title>Recruitment</title>", "<p>In the 2005 – 2006 academic year, a total of 118 IMGs were enrolled in all residency programs at the University of Toronto, as identified through the Postgraduate Medical Education registration database. IMGs were defined as individuals (regardless of citizenship status and source of funding) who obtained their medical degree outside of Canada at an accredited medical school, and training in a residency program recognized by the Royal College of Physicians and Surgeons of Canada and/or the College of Family Physicians of Canada. With the University of Toronto being the largest medical school in Canada offering almost all specialty and subspecialty residency training programs, 73 residency Program Directors were identified as potential participants.</p>", "<p>Due to the number of IMGs and the difficulty in recruiting (i.e. multiple training sites), email invitations were sent out which included a link to complete the survey on-line. To increase the response rate, residents were given the option to include their email address for a chance to win an iPOD.</p>", "<p>Email invitations were sent out to all Program Directors with the survey attached, as well as instructions on how to complete the on-line questionnaire. In the event that the former was chosen, Program Directors were given the option to fax or email completed surveys. To encourage the participation of Program Directors, these multiple accommodating methods were offered. Three follow-up emails were sent to IMGs and two follow-up emails were sent to Program Directors.</p>", "<p>Participation for both groups was voluntary and subjects were given the option to withdraw at any time. Ethics approval was obtained by the University of Toronto Research Ethics Board for this study.</p>", "<title>Analysis</title>", "<p>Frequencies for all eleven close-ended questions were calculated, as well as the mean rating for each of the 10 Likert-scale questions.</p>" ]

[ "<title>Results</title>", "<p>The response rate for IMGs was 74% (87 out of 118) and the response rate for Program Directors was 62% (45 out of 73). Mean scores for all ten topics and corresponding standard deviations are presented in Table ##TAB##0##1##.</p>", "<p>Among the IMGs surveyed, Knowledge of the Canadian Health Care System received the highest mean score, followed by Knowledge of Pharmaceuticals and Hospital formularies (3.69), and Knowledge of Hospital Systems (3.69). The lowest mean rating scores were Basic Clinical Skills (2.78), Working Relations with Other Residents (3.05) and Working Relations with Other Healthcare Students and Allied Healthcare Professionals (3.13).</p>", "<p>In contrast, the three highest mean scores among Program Directors were Communication with Patients (4.40), Communication with Team Members (4.33) and Basic Clinical Skills (4.28). The lowest mean scores were Knowledge of Hospital Systems (3.19), Specialty-specific Clinical Knowledge (3.37), and Specialty-specific Clinical Skills (3.46). Mean scores for Program Directors were higher relative to IMG trainees for all challenges presented in two categories: Knowledge and Skills and Communication and Working Relations. Mean scores for all Macro Issues were lower among Program Directors relative to the mean scores of IMGs.</p>", "<p>Approximately three-quarters of all participants agreed that an orientation program specifically targeted for IMGs is needed. When broken down by group, 93% of all Program Directors surveyed believed that an orientation program was necessary. A smaller majority (63%) of IMGs believed such a program would be beneficial.</p>" ]

[ "<title>Conclusions and discussion</title>", "<p>Among the IMGs and Program Directors surveyed at our medical school, the majority agreed that an orientation program for all IMGs is required before starting a residency program. Such a program is currently provided for IMGs in the Faculty of Medicine and is reported to be insufficient (Childs and Herbert, Assessing IMG Performance at Ontario Medical Schools 2002–06 Final Report, December 2007). This finding is supported by previous work conducted in the United States. Mylonakis, Mega, and Schiffman [##REF##10219231##8##] found that 37% of US Internal Medicine Program Directors agreed that a pre-residency training program should be mandatory prior to IMGs entering training. Other studies by Levey [##REF##1303634##9##], Kidd and Zulman [##REF##8309372##10##] and Kramer [##REF##16141132##1##] found similar results.</p>", "<p>Mean scores for Basic Clinical Skills differed between IMGs and Program Directors and may be related to the variability of training IMGs possess prior to entering the Canadian medical education system. With regards to Communication and Working Relations, mean scores were relatively higher among Program Directors, which may indicate they are more concerned with the communication skills and interprofessionalism of IMGs, in comparison to IMGs themselves. This is consistent with previous literature [##REF##15203520##11##,##REF##17470106##7##].</p>", "<p>These findings are not exclusive to foreign-trained physicians. Yahes and Dunn [##REF##8715879##12##] found that the biggest challenge experienced by foreign-trained nurses was a lack of communication skills. After completing two-hour sessions over the course of 12 weeks (dealing with group interaction, non-verbal cues, pronunciation and voice intonation) subjects reported a higher rate of job satisfaction and collegiality. Nursing administrators also noted a decrease in the number of complaints from physicians and staff with regards to communicating with these foreign-trained nurses.</p>", "<p>All three Macro-level Issues (Knowledge of the Canadian Health Care System, Knowledge of Pharmaceutical and Hospital Formularies and Knowledge of Toronto Hospital Systems) received the highest mean scores among IMGs. System issues may prove especially challenging to IMGs who are required to learn the values of a new country's healthcare system and the culture of a hospital and its numerous administrative protocols, in addition to their medical curriculum. Program Directors may feel such issues are not challenges or may only view these as pertinent once the trainee begins his/her residency.</p>", "<p>These concurrent surveys of IMG residents and their Program Directors at the University of Toronto illustrated that both cohorts feel that IMGs need better integration into their residency programs. Interestingly, the groups differed in the areas of concern with residents acknowledging their anxiety about a lack of knowledge and comfort in many macro areas, namely institutional and societal transition areas, whereas Program Directors were more concerned with areas of performance indicators in communication, collaboration and basic clinical skills. Each group responded based on their needs and anxieties, possibly indicating that they need to be educated about each other's perspectives.</p>", "<p>IMGs are forming a major part of our training cohort, thus representing an increasing number of physicians entering into practice as a short-term solution to health human resource needs. A proliferation of IMG entries has not been accompanied by robust strategies to optimize their integration and bridge their transition into residency. In this study, IMGs have identified specific challenges as have their Program Directors. A comprehensive and integrated program is needed to facilitate the success of IMGs.</p>", "<title>Limitations</title>", "<p>The project was designed as a needs assessment study to explore the extent to which specific issues were challenging to IMGs from the perspective of IMG trainees and Program Directors. As it stands, the survey instrument has only face validity.</p>", "<p>Secondly, this study is exploratory in nature. As the survey only provided pre-selected issues, participants were restricted in ranking the choices presented. Follow-up studies using focus groups with IMGs may help to expand on their experiences or uncover specifics that cannot be captured using close-ended questions. The same qualitative methods should be used to explore the perceptions of Program Directors, not only for contrast, but also to identify other issues that may not be shared by the IMG cohort.</p>", "<p>Conclusions of this study are specific to the perceptions of IMGs and Program Directors of medical residency programs at the Faculty of Medicine at the University of Toronto. It cannot be concluded that IMGs and Program Directors at other Canadian medical schools or elsewhere perceive these issues as challenges, or to the same extent as those who participated in this study.</p>" ]

[ "<title>Conclusions and discussion</title>", "<p>Among the IMGs and Program Directors surveyed at our medical school, the majority agreed that an orientation program for all IMGs is required before starting a residency program. Such a program is currently provided for IMGs in the Faculty of Medicine and is reported to be insufficient (Childs and Herbert, Assessing IMG Performance at Ontario Medical Schools 2002–06 Final Report, December 2007). This finding is supported by previous work conducted in the United States. Mylonakis, Mega, and Schiffman [##REF##10219231##8##] found that 37% of US Internal Medicine Program Directors agreed that a pre-residency training program should be mandatory prior to IMGs entering training. Other studies by Levey [##REF##1303634##9##], Kidd and Zulman [##REF##8309372##10##] and Kramer [##REF##16141132##1##] found similar results.</p>", "<p>Mean scores for Basic Clinical Skills differed between IMGs and Program Directors and may be related to the variability of training IMGs possess prior to entering the Canadian medical education system. With regards to Communication and Working Relations, mean scores were relatively higher among Program Directors, which may indicate they are more concerned with the communication skills and interprofessionalism of IMGs, in comparison to IMGs themselves. This is consistent with previous literature [##REF##15203520##11##,##REF##17470106##7##].</p>", "<p>These findings are not exclusive to foreign-trained physicians. Yahes and Dunn [##REF##8715879##12##] found that the biggest challenge experienced by foreign-trained nurses was a lack of communication skills. After completing two-hour sessions over the course of 12 weeks (dealing with group interaction, non-verbal cues, pronunciation and voice intonation) subjects reported a higher rate of job satisfaction and collegiality. Nursing administrators also noted a decrease in the number of complaints from physicians and staff with regards to communicating with these foreign-trained nurses.</p>", "<p>All three Macro-level Issues (Knowledge of the Canadian Health Care System, Knowledge of Pharmaceutical and Hospital Formularies and Knowledge of Toronto Hospital Systems) received the highest mean scores among IMGs. System issues may prove especially challenging to IMGs who are required to learn the values of a new country's healthcare system and the culture of a hospital and its numerous administrative protocols, in addition to their medical curriculum. Program Directors may feel such issues are not challenges or may only view these as pertinent once the trainee begins his/her residency.</p>", "<p>These concurrent surveys of IMG residents and their Program Directors at the University of Toronto illustrated that both cohorts feel that IMGs need better integration into their residency programs. Interestingly, the groups differed in the areas of concern with residents acknowledging their anxiety about a lack of knowledge and comfort in many macro areas, namely institutional and societal transition areas, whereas Program Directors were more concerned with areas of performance indicators in communication, collaboration and basic clinical skills. Each group responded based on their needs and anxieties, possibly indicating that they need to be educated about each other's perspectives.</p>", "<p>IMGs are forming a major part of our training cohort, thus representing an increasing number of physicians entering into practice as a short-term solution to health human resource needs. A proliferation of IMG entries has not been accompanied by robust strategies to optimize their integration and bridge their transition into residency. In this study, IMGs have identified specific challenges as have their Program Directors. A comprehensive and integrated program is needed to facilitate the success of IMGs.</p>", "<title>Limitations</title>", "<p>The project was designed as a needs assessment study to explore the extent to which specific issues were challenging to IMGs from the perspective of IMG trainees and Program Directors. As it stands, the survey instrument has only face validity.</p>", "<p>Secondly, this study is exploratory in nature. As the survey only provided pre-selected issues, participants were restricted in ranking the choices presented. Follow-up studies using focus groups with IMGs may help to expand on their experiences or uncover specifics that cannot be captured using close-ended questions. The same qualitative methods should be used to explore the perceptions of Program Directors, not only for contrast, but also to identify other issues that may not be shared by the IMG cohort.</p>", "<p>Conclusions of this study are specific to the perceptions of IMGs and Program Directors of medical residency programs at the Faculty of Medicine at the University of Toronto. It cannot be concluded that IMGs and Program Directors at other Canadian medical schools or elsewhere perceive these issues as challenges, or to the same extent as those who participated in this study.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>International Medical Graduates (IMGs) training within the Canadian medical education system face unique difficulties. The purpose of this study was to explore the challenges IMGs encounter from the perspective of trainees and their Program Directors.</p>", "<title>Methods</title>", "<p>Program Directors of residency programs and IMGs at the University of Toronto were anonymously surveyed and asked to rate (using a 5-point Likert scale; 1 = least important – 5 = most important) the extent to which specific issues were challenging to IMGs and whether an orientation program (in the form of a horizontal curriculum) should be implemented for incoming IMGs prior to starting their residency.</p>", "<title>Results</title>", "<p>Among the IMGs surveyed, Knowledge of the Canadian Healthcare System received the highest mean score (3.93), followed by Knowledge of Pharmaceuticals and Hospital formularies (3.69), and Knowledge of the Hospital System (3.69). In contrast, Program Directors felt that Communication with Patients (4.40) was a main challenge faced by IMGs, followed by Communication with Team Members (4.33) and Basic Clinical Skills (4.28).</p>", "<title>Conclusion</title>", "<p>IMGs and Program Directors differ in their perspectives as to what are considered challenges to foreign-trained physicians entering residency training. Both groups agree that an orientation program is necessary for incoming IMGs prior to starting their residency program.</p>" ]

[ "<title>Competing interests</title>", "<p>Funds have been received from the Ontario Ministry of Health by the Postgraduate Medical Education Office to design an Orientation Program for incoming IMGs. Results from this study were strictly used as one component to assist the Director of Education and Research in designing the program. No formal report of this study has been disseminated to this funder or other sponsors.</p>", "<p>The Postgraduate Medical Education Office is financing this manuscript, including the article-processing fee. This office employs both Dr. Sarita Verma, Vice-Dean, and Rachelle Zulla, Research and Data Analyst. Dr. Baerlocher is currently a resident in the Department of Medical Imaging. None of the contributing authors hold stocks or shares in this organization and no patents related to the content of the manuscript have been submitted. All authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>SV is responsible for the conception and design of this study, as well as critically revising the final draft. The acquisition of data, analysis and interpretation of data, as well as writing and editing the final version, was done by RZ. MOB contributed by interpreting the data and contributing to writing the final version of this paper. All authors have read and approved this manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1472-6920/8/42/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to acknowledge the participation of all the IMGs and Program Directors that completed the surveys. We also wish to thank Loreta Muharuma, Director of Operations, for helping to compile the list of residents and Program Directors. We would also like to thank Dr. Kevin Imrie and Dr. Susan Glover Takahashi for their help in designing the survey and providing initial feedback. The authors would like to especially thank Dr. Brian Hodges for reviewing the manuscript and providing valuable feedback and Laura Toth for editing the final version.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Mean scores of challenges faced by IMGs from the perspective of IMGs and their program directors</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>IMGs</bold></td><td align=\"center\"><bold>PROGRAM DIRECTORS</bold></td></tr><tr><td/><td align=\"center\"><bold>M (SD)</bold></td><td align=\"center\"><bold>M (SD)</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Knowledge and skills</bold></td><td/><td/></tr><tr><td align=\"left\">Basic clinical skills</td><td align=\"center\">2.78 (1.195)</td><td align=\"center\">4.28 (1.007)</td></tr><tr><td align=\"left\">Specialty-specific clinical knowledge</td><td align=\"center\">3.28 (1.227)</td><td align=\"center\">3.37 (1.176)</td></tr><tr><td align=\"left\">Specialty-specific clinical skills</td><td align=\"center\">3.33 (1.198)</td><td align=\"center\">3.46 (1.031)</td></tr><tr><td align=\"left\"><bold>Communication and working relationships</bold></td><td/><td/></tr><tr><td align=\"left\">Communication with patients</td><td align=\"center\">3.49 (1.200)</td><td align=\"center\">4.40 (0.698)</td></tr><tr><td align=\"left\">Communication with team members</td><td align=\"center\">3.41 (1.177)</td><td align=\"center\">4.33 (0.644)</td></tr><tr><td align=\"left\">Working relations with other residents</td><td align=\"center\">3.05 (1.219)</td><td align=\"center\">3.80 (0.631)</td></tr><tr><td align=\"left\">Working relations with other healthcare students and allied healthcare professionals</td><td align=\"center\">3.13 (1.228)</td><td align=\"center\">4.00 (0.577)</td></tr><tr><td align=\"left\"><bold>Macro issues</bold></td><td/><td/></tr><tr><td align=\"left\">Knowledge of the Canadian Healthcare System</td><td align=\"center\">3.93 (1.097)</td><td align=\"center\">3.55 (0.852)</td></tr><tr><td align=\"left\">Knowledge of pharmaceuticals and Hospital Formularies</td><td align=\"center\">3.69 (0.980)</td><td align=\"center\">3.56 (0.959)</td></tr><tr><td align=\"left\">Knowledge of Hospital System</td><td align=\"center\">3.69 (1.060)</td><td align=\"center\">3.19 (0.764)</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>M = mean score</p><p>SD = standard deviation</p></table-wrap-foot>" ]

[]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Prion diseases, also known as transmissible spongiform encephalopathies, are fatal neurodegenerative disorders that occur when the normal, cellular prion protein (PrP^C) is converted into a conformationally altered isoform (PrP^Sc) that is self-propagating and infectious [##UREF##0##1##,##REF##9811807##2##]. While the properties of PrP^Scand its role in the disease process have been extensively characterized, the normal physiological function of PrP^Chas yet to be resolved. Mice genetically lacking PrP^Cexhibit no gross anatomical or developmental abnormalities, and have been largely uninformative for deducing a physiological function of PrP^C[##REF##1373228##3##, ####REF##7999308##4##, ##REF##11823413##5####11823413##5##]. Several potential functions have been proposed for PrP^C, including protection from apoptosis and oxidative stress, maintenance of synaptic integrity, regulation of copper metabolism, cell signaling, and cell adhesion (reviewed in [##REF##17451912##6##]). Whatever the physiological function of PrP^C, it has become increasingly clear that expression of PrP^Cis necessary to mediate the toxicity induced by PrP^Sc[##REF##14593181##7##, ####REF##8552188##8##, ##REF##15933194##9####15933194##9##]. Therefore, determining the normal function of PrP^Cwill likely provide important insight into the neurotoxic mechanisms underlying prion diseases.</p>", "<p>The most compelling evidence for a functional activity of PrP^Ccomes from studies in mice expressing either certain N-terminally deleted forms of PrP or the PrP paralog, Doppel (Dpl). Several different deletions that encompass a highly conserved sequence of 21 amino acids in the central region of PrP all cause a spontaneous neurodegenerative illness when expressed in the brains of transgenic mice [##REF##9568713##10##, ####REF##17245436##11##, ##REF##17245437##12####17245437##12##]. A neurodegenerative phenotype is also observed in mice in which Dpl, a PrP paralog that is normally expressed in testes and structurally resembles the C-terminal globular domain of PrP, is ectopically expressed in the brain [##REF##11226243##13##, ####REF##8606772##14##, ##REF##10525406##15##, ##REF##11179214##16####11179214##16##]. Strikingly, neurodegeneration induced by deleted PrP molecules and Dpl is reversed by co-expression of wild-type PrP [##REF##9568713##10##, ####REF##17245436##11##, ##REF##17245437##12####17245437##12##,##REF##11734625##17##]. These results have been interpreted to mean that deleted PrP and Dpl activate a common neurotoxic pathway, and that this pathway is suppressed by the presence of wild-type PrP.</p>", "<p>The dramatic rescuing effect by wild-type PrP in these transgenic mice raises the possibility that PrP^Cpossesses a generalized neuroprotective activity that could counteract the effects of other toxic stimuli [##REF##17451912##6##,##REF##16675391##18##]. One kind of evidence consistent with this idea derives from studies of cultured neurons or mice that lack PrP expression. For example, it has been reported that neurons cultured from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice are more susceptible than wild-type neurons to several kinds of oxidative stress including exposure to xanthine oxidase, hydrogen peroxide, and copper ions [##REF##11782965##19##]. There is also evidence that PrP^Cmay play a protective role <italic>in vivo </italic>during focal cerebral ischemia or traumatic brain injury. PrP^Cexpression levels increase after these kinds of injury and lesion size is larger in <italic>Prn-p</italic>^{<italic>0/0 </italic>}compared to wild-type mice [##REF##14753456##20##,##REF##15531106##21##]. Retinal photoreceptors from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice have also been reported to be more susceptible to light-induced apoptosis [##REF##16952355##22##].</p>", "<p>Several <italic>in vitro </italic>systems have also been described in which increased PrP expression has been found to exert a protective effect against apoptotic insults [##REF##15645198##23##]. In one such system, human fetal neurons in culture were induced to undergo apoptosis by microinjection of a plasmid encoding the pro-apoptotic protein, Bax. Co-injection of a PrP-encoding cDNA efficiently prevented Bax-induced neuronal death [##REF##11522774##24##]. This protective effect has been attributed to the presence of a cytosolic form of PrP, which is thought to inhibit conformational activation of Bax [##REF##15846375##25##, ####REF##12917444##26##, ##REF##17494694##27####17494694##27##]. In a second example, serum deprivation of two kinds of immortalized hippocampal cell lines (HpL and NpL) derived from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice triggered an apoptotic response that was rescued by transfection with a PrP-encoding plasmid [##REF##17446686##28##, ####REF##10421360##29##, ##REF##12914801##30####12914801##30##]. Over-expression of PrP^Chas also been reported to render MCF-7 breast carcinoma cells resistant to apoptosis induced by TNF-α, TRAIL, and Bax [##REF##15846375##25##,##REF##17494694##27##,##REF##14744790##31##,##REF##18006836##32##]. PrP expression also correlated with increased resistance of SGC7901 gastric carcinoma cell lines to several chemotherapeutic agents [##REF##15386405##33##]. Finally, work in our own laboratory has shown that expression of mammalian PrP markedly protects <italic>S. cerevisiae </italic>from Bax-induced cell death [##REF##15753097##34##]. Although these studies utilize a variety of cell types and a range of different stimuli to induce cell death, it is possible that the protective activity of PrP observed in each case reflects a common, underlying molecular mechanism. However, the nature of this mechanism remains unknown.</p>", "<p>In this study, we have re-examined the cytoprotective activity of PrP in three different mammalian cell systems similar to those that have been previously published. We first attempted to reproduce the rescue effect of PrP in TNF-α-treated MCF-7 cells and serum-deprived HpL cells. To examine the protective activity of PrP in primary neurons, we assessed the ability of PrP to inhibit apoptosis of cerebellar granule neurons induced by expression of exogenous Bax and by activation of endogenous Bax following potassium and serum withdrawal [##REF##8922404##35##]. While our results demonstrate a weak cytoprotective effect by PrP in each of these systems, the degree of protection was considerably less than in previously published studies. The modest cytoprotective effects observed here lead us to consider whether PrP possesses any physiologically relevant neuroprotective activity, and if so, whether the toxic stimuli used did not effectively activate the relevant PrP-dependent pathways. This work has important implications for the design of experimental strategies aimed at uncovering the mechanisms of PrP^Ccytoprotection.</p>" ]

[ "<title>Methods</title>", "<title>Cell lines</title>", "<p>MCF-7 and HpL cells were cultured in DMEM supplemented with 10% FCS, 2 mM glutamine, and penicillin/streptomycin, and were maintained in a humidified incubator at 37°C in 5% CO₂.</p>", "<p>MCF-7 cells were transfected with a pcDNA3 plasmid encoding wild-type human PrP using Lipofectamine 2000 (Invitrogen, Carlsbad, CA) according to the manufacturer's protocol. Forty-eight hours later, cells were split into 700 μg/ml G418 (Tissue Culture Support Center, Washington University in St. Louis) for two weeks. Cells were harvested as pools and maintained in 300 μg/ml G418. PrP expression was detected by Western blotting of cell lysates using the monoclonal anti-PrP antibody, 3F4 (1:1000) [##REF##1710287##65##].</p>", "<p>HpL3-4 cells were transfected with wild-type mouse PrP cDNA contained in a pcDNA3.1(+)/hygro vector (Invitrogen). After transfection with Lipofectamine 2000, cells were selected in media containing 200 μg/ml hygromycin B (Invitrogen). Upon selection of stable lines, cells were maintained in 100 μg/ml hygromycin B.</p>", "<p>PrP expression was assessed by Western blotting using the monoclonal 3F4 antibody (MCF-7 cells), or by immunofluorescence staining (HpL cells, see below).</p>", "<title>Immunofluorescence staining of HpL cells</title>", "<p>HpL cells were fixed with 4% paraformaldehyde, permeabilized with 0.5% Triton-X100 in PBS, and blocked in 5% goat serum in PBS. Cells were incubated with the monoclonal anti-PrP antibody 8H4 [##REF##9671761##66##], and co-stained with antibodies to the Golgi marker, giantin (1:1000; Covance, Berkley, CA). In some experiments, cells were stained with antibodies to GFAP (1:1000; Dako, Carpinteria, CA), MAP-2 (1:1000; Sigma, St. Louis, MO) and NeuN (1:1000; Chemicon, Temecula, CA). After incubation with primary antibodies, cells were treated with Alexa Fluor secondary antibodies (Alexa-488 goat anti-mouse IgG and Alexa-594 goat anti-rabbit IgG) prior to imaging using a Nikon OptiPhot-2 microscope and MetaMorph imaging software.</p>", "<title>Measurement of death and viability of MCF-7 and HpL cells</title>", "<p>Stably transfected pools of MCF-7 cells expressing human PrP were treated with 100 ng/ml recombinant TNF-α (PeproTech, Rocky Hill, NJ) in growth medium for 43 hours. Stimulation of cell death by serum deprivation in HpL3-2 and HpL3-4 cells was performed as previously described [##REF##10421360##29##].</p>", "<p>For MTT viability assays, medium was replaced with 0.32 mg/ml MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide; Sigma, St. Louis, MO) in Locke's buffer for 30–60 minutes. Cells were solubilized with DMSO and the absorbance was read at 575 nm in a microplate reader (Bio-Tek, Winooski, VT). Experimental values were expressed as a percentage of the absorbance values in non-treated control samples.</p>", "<p>For flow cytometry analysis, cells were washed once with PBS prior to trypsinization and fixation in 70% cold ethanol. After fixation, cells were washed in PBS/1% BSA, pelleted, and resuspended in propidium iodide (PI) working solution containing 30 μg/ml PI (Sigma) and 0.25 mg/ml RNAse A (Qiagen, Valencia, CA) in PBS/1% BSA. The volume of PI working solution was normalized for cell number. Flow cytometry was performed on a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA), and the data was analyzed using CELLQUEST analysis software (BD Biosciences).</p>", "<title>Quantitative RT-PCR analysis</title>", "<p>mRNA was purified from HpL3-4 and HpL3-2 cells and wild-type mouse brain and testes using the RNAwiz reagent (Ambion, Austin, TX). cDNA was generated, and expression of GFAP, NF-L, and Doppel was analyzed by quantitative RT-PCR using an ABI-PRISM 7000 Sequence Detection System (Applied Biosystems, Foster City, CA). Primers specific for GFAP, NF-L, and Doppel were designed using the Primer Express program. Primer pairs used were as follows: GFAP forward (CTGGAGGTGGAGAGGGACAA), GFAP reverse (CAGCCTCAGGTTGGTTTCATCT), NF-L forward (CCGGCCGCCACCAT), NF-L reverse (CCACATAGCGCCGCTTGTA), Dpl forward (GCTGGTGGGCAAAGGTAGAC), Dpl reverse (TGAAACGCTACACGTTGTACTTTCA). Data were normalized to GAPDH expression using forward (GGTGGACCTCATGGCCTACA) and reverse (AGGGCCTCTCTCTTGCTCAGT) primers.</p>", "<title>Cerebellar granule neuron (CGN) cultures</title>", "<p>CGNs were cultured from wild-type C57BL/6J × CBA/J mice or from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice [##REF##1373228##3##]. Cultures were prepared from 5-day-old mouse pups as described previously [##REF##8922404##35##]. Neurons were suspended in K25+S medium (Basal Media Eagle with Earle's salts without glutamine, 10% dialyzed FCS, 2 mM glutamine, 25 mM KCl, and 0.02 mg/ml gentamicin) and plated in chamber slides coated with poly-D-lysine at a density of 560,000 cells/cm². Two hours after plating, the medium was changed to K25 medium (no serum) supplemented with B27 (Invitrogen). Four days after plating, conditioned medium was removed and replaced with fresh K25+B27 medium. CGNs were co-transfected with 1 μg DNA (1:1 ratio of mouse Bax and pEGFP-N1 (Clontech, Mountain View, CA)) using Lipofectamine 2000. Mouse Bax cDNA was obtained from Open Biosystems (#MMM1013-64655; Huntsville, AL), PCR amplified, and cloned into the pcDNA3.1(+)/hygro plasmid (Invitrogen). After 2 hours, the neurons were returned to conditioned K25+B27 medium.</p>", "<p>Transfected CGNs were fixed in 4% paraformaldehyde/5% sucrose in PBS for 10 minutes at room temperature. Nuclei were stained with DAPI for 10 minutes. Death of EGFP-positive neurons was determined morphologically based on chromatin condensation, degeneration of neurites, and cell body shrinkage. At least 100 neurons were individually scored for each experiment. Cells were imaged using a Nikon OptiPhot-2 microscope and MetaMorph imaging software.</p>", "<p>CGNs were subjected to reduced extracellular potassium (5 mM) and serum deprivation as previously described [##REF##8922404##35##]. Following this manipulation, neurons were washed twice with Locke's buffer and incubated for 10 minutes in 5 μM calcein AM (Invitrogen) in Locke's buffer at 37°C. CGNs were washed once with Locke's buffer and lysed in PBS/0.1% Triton-X100 followed by quantitation of the fluorescence signal on a microplate fluorimeter (Bio-Tek). Experimental values were expressed as a percentage of the calcein AM fluorescence values in K25+S control samples at each timepoint.</p>" ]

[ "<title>Results</title>", "<title>Expression of PrP in MCF-7 cells weakly suppresses death induced by TNF-α</title>", "<p>To test the observation that PrP^Crescues MCF-7 human breast carcinoma cells from TNF-α-mediated cell death [##REF##14744790##31##], we first determined the sensitivity of MCF-7 cells to TNF-α treatment using two different assays: MTT dye reduction, and flow cytometry after propidium iodide staining to measure the proportion of cells with sub-2n DNA content. Treatment of untransfected MCF-7 cells with 100 ng/ml TNF-α diminished cell viability over time, with the MTT signal reduced to ~30% after 72 hrs (Figure ##FIG##0##1A##). A similar time course of cell death was observed by flow cytometry, with the proportion of cells containing sub-2n DNA reaching ~65% by 72 hrs (Figure ##FIG##0##1B##). These data confirm the susceptibility of MCF-7 cells to cell death induced by treatment with TNF-α in the absence of exogenous PrP expression.</p>", "<p>To test the rescuing effect of PrP, we generated pools of MCF-7 cells that were transfected either with an empty vector, or with vector encoding human PrP. We analyzed three independent pools of vector-transfected cells which express low levels of endogenous PrP, and six pools of cells expressing high levels of transfected PrP (~20–25-fold over endogenous) (Figure ##FIG##1##2A##). Each pool was treated with 100 ng/ml TNF-α for 43 hrs, and then assayed by MTT and flow cytometry. We observed that the PrP-expressing pools displayed a small, but statistically greater viability compared to vector-transfected pools based on the MTT assay (Figure ##FIG##1##2B##): 47% (PrP) vs. 38% (vector) (p = 0.0042). Less cell death was also observed in PrP-expressing cells than in vector controls, as measured by the proportion of cells with sub-2n DNA content (Figure ##FIG##1##2C##): 35% (PrP) vs. 42% (vector).</p>", "<title>PrP weakly suppresses death of immortalized hippocampal neurons following serum deprivation</title>", "<p>PrP has also been reported to exert a protective activity in immortalized hippocampal cell lines derived from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice (HpL cells) subjected to serum deprivation [##REF##10421360##29##]. We obtained two independently generated HpL cell lines (HpL3-2 and HpL3-4) and tested their susceptibility to serum withdrawal. Both lines underwent cell death over a comparable time course, with ~30% of the cells remaining viable after 72 hrs (Figure ##FIG##2##3A##).</p>", "<p>We then generated stably transfected lines of HpL3-4 cells expressing wild-type mouse PrP, and tested their susceptibility to cell death following serum deprivation. We analyzed four independent lines that expressed differing levels of PrP, based on immunofluorescence staining (Figure ##FIG##2##3B##). PrP-expressing and vector-transfected lines were deprived of serum for 96 hrs, and cell death was measured by flow cytometry (Figure ##FIG##2##3C##). Data was normalized relative to untreated controls. We observed a modest rescuing effect that was correlated with the level of PrP expression level. Two lines expressing the highest levels of PrP displayed a reduced level of cell death that was statistically significant relative to a vector control (PrP4-1, p = 0.0068; PrP4-2, p = 0.0022). All PrP-expressing clones showed less cell death than a vector control clone (V1-2), in which &gt; 50% of the cells were dead by 96 hrs.</p>", "<title>HpL cells do not express neuronal markers or Doppel</title>", "<p>Since PrP did not dramatically rescue HpL cells from serum deprivation as previously reported [##REF##10421360##29##], we sought to confirm the identity of these cells by analyzing their expression of various neuronal and astrocytic markers using immunofluorescence and quantitative RT-PCR (Table ##TAB##0##1##). As previously reported [##REF##17446686##28##,##REF##10421360##29##], neither the HpL3-2 nor HpL3-4 lines expressed appreciable levels of GFAP. Surprisingly, however, we did not detect expression of the neuronal markers NeuN, MAP2, or the 68 K neurofilament light-chain subunit (NF-L). These cells were previously reported to express NF-L [##REF##10421360##29##]. Using the same antibodies, we previously observed high levels of the neuronal and astrocytic markers in brain (Table ##TAB##0##1##) [##REF##15262264##36##].</p>", "<p>HpL cells are derived from hippocampal neurons cultured from Rikn <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice, in which an intergenic splicing event caused Doppel to be ectopically expressed in brain under control of the PrP promoter [##REF##15950943##37##,##REF##11152682##38##]. Unexpectedly, quantitative RT-PCR and immunofluorescence analysis failed to detect expression of Doppel in the HpL3-2 or HpL3-4 cells (Table ##TAB##0##1##).</p>", "<title>PrP does not significantly reduce death of cerebellar granule neurons (CGNs) induced by exogenous Bax</title>", "<p>To test the hypothesis that PrP can inhibit Bax-induced cell death, we transiently transfected a cDNA encoding mouse Bax into CGNs cultured from either <italic>Prn-p</italic>^+/+or <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice. A separate plasmid encoding EGFP was co-transfected into the neurons as a marker of transfected cells. In healthy neurons, EGFP fluorescence was distributed evenly throughout the soma (Figure ##FIG##3##4A##, white arrow) and continuously along the neurites (Figure ##FIG##3##4A##, inset). By DAPI staining, the nucleus of healthy cells was relatively large, and filled with multiple nucleoli (Figure ##FIG##3##4B##, white arrow). Cell death induced by Bax resulted in characteristic morphological changes that were easily visualized by EGFP and DAPI fluorescence. Dying granule cells displayed a soma that was shrunken (Figure ##FIG##3##4C##, yellow arrow), as well as coalescence of EGFP into large, unconnected aggregates or beads along the neuritic process, indicative of neuritic degeneration (Figure ##FIG##3##4C##, inset). Co-staining with DAPI also revealed pyknotic nuclei (Figure ##FIG##3##4D##, yellow arrow).</p>", "<p>Eight hours after transfection of <italic>Prn-p</italic>^{<italic>0/0 </italic>}cultures with the Bax plasmid, 39% of EGFP-positive neurons were degenerating based on morphological criteria (Figure ##FIG##3##4E##). Cultures from <italic>Prn-p</italic>^+/+mice displayed a reduced percentage of apoptotic neurons (23%), although this difference was not statistically significant (p = 0.3038). By 16 hrs after transfection, <italic>Prn-p</italic>^{<italic>0/0 </italic>}cultures contained more degenerating CGNs than <italic>Prn-p</italic>^+/+cultures, a difference that approached but did not reach statistical significance (21% vs. 7%, respectively; p = 0.0665). Cultures derived from either <italic>Prn-p</italic>^{<italic>0/0 </italic>}or <italic>Prn-p</italic>^+/+mice transfected with empty vector (without Bax) contained &lt; 2% apoptotic CGNs.</p>", "<title>CGNs expressing PrP are slightly more resistant to cell death induced by potassium/serum deprivation</title>", "<p>To determine whether PrP protects neurons from death due to activation of endogenous Bax, CGNs from wild-type and <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice were transferred to medium containing reduced potassium and no serum. To improve viability, CGNs are routinely cultured in the presence of serum under depolarizing conditions with elevated potassium (25 mM). Reducing potassium to 5 mM and removing serum causes the cells to undergo Bax-dependent apoptosis [##REF##2886565##39##,##REF##9314540##40##]. Using calcein AM fluorescence to detect viable neurons, we observed that incubation in low-potassium medium without serum (K5-S) gradually reduced the viability of <italic>Prn-p</italic>^+/+CGNs to 56% of the value for cells maintained in control medium (K25+S) after 48 hrs (Figure ##FIG##4##5##, open circles). CGNs cultured from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice consistently followed a slightly faster reduction in viability, with 45% of the neurons surviving after 48 hrs (Figure ##FIG##4##5##, open triangles). The difference in viability between the two types of neurons was statistically significant at 24 and 48 hrs (p = 0.0358 and 0.0302, respectively). These data demonstrate that endogenous PrP expression slightly reduces, but does not prevent, Bax-dependent cell death of CGNs induced by lowering extracellular potassium and removing serum.</p>" ]

[ "<title>Discussion</title>", "<p>In this study, we tested the ability of PrP to protect cultured cells from several kinds of cytotoxic insults using assays similar to those that have previously been published by other investigators. We examined the effect of PrP expression on the viability of MCF-7 breast carcinoma cells treated with TNF-α, HpL3-4 immortalized hippocampal neurons deprived of serum, and cultured cerebellar granule neurons induced to undergo two kinds of Bax-dependent apoptosis. In contrast to previously published reports, we failed to detect a robust protective effect of PrP in any of these assays. These results have led us to critically reevaluate the function of PrP as a cytoprotective molecule.</p>", "<title>The protective activity of PrP in MCF-7 and HpL3-4 cells is more modest than previously described</title>", "<p>In a DNA microarray analysis, Diarra-Mehrpour et al. [##REF##14744790##31##] found that PrP expression was up-regulated 17-fold in a sub-line of MCF-7 cells that was resistant to TNF-α-induced apoptosis. These investigators then showed that adenovirally-mediated over-expression of PrP in the parental TNF-α-sensitive MCF-7 cell line conferred resistance to TNF-α, an effect that correlated with reduced cytochrome c release from mitochondria. In their experiment, ~80% of PrP-expressing cells remained viable after TNF-α treatment compared with ~30% for untransduced cells. In our hands, in contrast, over-expression of PrP in MCF-7 cells by a similar amount had a much more modest effect, increasing viability after TNF-α treatment from 38% to 47% (Figure ##FIG##1##2B##).</p>", "<p>Although a number of published studies have utilized HpL3-4 cells to demonstrate a neuroprotective activity of PrP [##REF##17446686##28##, ####REF##10421360##29##, ##REF##12914801##30####12914801##30##,##REF##15950943##37##,##REF##15896301##41##, ####REF##15596141##42##, ##REF##14550262##43##, ##REF##14645931##44##, ##REF##15670743##45##, ##REF##16547418##46####16547418##46##], only two report quantitative data concerning the ability of PrP to rescue these cells from serum deprivation [##REF##15896301##41##,##REF##15596141##42##]. In one of these studies [##REF##15596141##42##], stable expression of PrP in HpL3-4 cells was reported to reduce cell death by 80% relative to vector controls based on LDH assays of cell death. However, the LDH data were normalized to the values for vector-transfected cells after 24 hours of serum deprivation, so it is not possible to gauge of the absolute amount of cell death occurring in these experiments. In the second study [##REF##15896301##41##], serum deprivation reduced the viability of vector-transfected cells by only a modest amount (to 75% of the value for untreated cells) and PrP expression restored viability to nearly 100% after 24 hours. In our experiments, stable expression of PrP in several independent HpL3-4 cell lines produced only a small reduction in cell death, amounting to &lt; 20%, even in lines expressing the highest levels of PrP (Figure ##FIG##2##3C##).</p>", "<p>It is unclear what factors account for the discrepancies between our results and those reported in previous studies. In the case of MCF-7 cells, one possible reason may be a difference in the methods used to introduce exogenous PrP: stable transfection in our experiments vs. adenoviral transduction in the study of Diarra-Mehrpour et al. [##REF##14744790##31##]. However, both methods achieved similar levels of over-expression (~25-fold). Alternatively, genetic variation between different lines of MCF-7 cells may play a role. Susceptibility of MCF-7 cells to TNF-α treatment is greatly influenced by genetic factors, leading to cell line variants with differing sensitivities to TNF-α-induced apoptosis [##REF##3620713##47##,##REF##9810003##48##]. Signaling molecules influencing the response to TNF-α also differ between variants of MCF-7 cells, including PKCε, JNK, p53, and NF-κB [##REF##16785234##49##, ####REF##17668322##50##, ##REF##12446776##51##, ##REF##10213465##52##, ##REF##9419972##53####9419972##53##]. The diversity of factors that affect TNF-α-mediated cell death in MCF-7 cells suggest that the previously described protective effect by PrP may be specific for a particular strain variant and may not be generally reproducible in other cell types.</p>", "<p>Similar genetic changes may have occurred in HpL3-4 cells, since we did not detect expression of NF-L or Doppel by quantitative RT-PCR (Table ##TAB##0##1##). The absence of NF-L expression in the HpL3-4 and HpL3-2 cells suggests that they may have lost their neuronally differentiated characteristics, which may be required for the rescue activity.</p>", "<title>PrP does not strongly rescue cultured neurons from Bax-dependent apoptosis</title>", "<p>We have proposed several possible mechanisms to explain how PrP could exert a protective effect against Bax-mediated cytotoxic insults [##REF##17451912##6##]. PrP may act on death receptors at the cell surface, it may influence the activity of pro- and anti-apoptotic molecules by physical interaction or via signal transduction pathways, or it could work within intracellular organelles to influence cell death pathways. To test whether PrP could modulate Bax-dependent pathways, we utilized cultured CGNs in an attempt to recapitulate the dramatic rescue activity that was described in analogous experiments on human primary neurons [##REF##11522774##24##]. We chose to utilize CGNs for two reasons. First, CGNs undergo Bax-dependent apoptosis in response to reduced extracellular potassium and serum deprivation, and this process has been analyzed extensively to gain insight into the mechanisms of programmed cell death [##REF##9314540##40##,##REF##12879973##54##]. Second, CGNs have been used by others to demonstrate a neuroprotective activity of PrP against Dpl [##REF##15459186##55##,##REF##17703189##56##].</p>", "<p>In contrast to the previous study [##REF##11522774##24##], we failed to observe a robust protective effect of PrP against apoptosis induced either by ectopic expression of Bax or by activation of endogenous Bax via potassium depletion and serum deprivation. In these experiments, the presence of PrP enhanced cell viability by at most 15%. The reasons for this discrepancy are unclear, but differences in neuronal populations (cortical versus cerebellar), species (human versus mouse), or PrP expression level may play a role. With regard to the last point, Bounhar et al. utilized microinjection of a cDNA-encoding plasmid in order to boost PrP expression in neurons that presumably already contained endogenous PrP, although no data were presented on the degree of over-expression achieved [##REF##11522774##24##]. In contrast, we compared neurons completely lacking PrP to those containing normal endogenous levels. It is possible that Bax rescue activity is only observed with supraphysiological expression levels of PrP.</p>", "<p>The role of Bax in the physiological activity of PrP^Cremains uncertain, with some studies suggesting a functional connection between the two proteins and others arguing against it. Our own studies [##REF##15753097##34##] as well as those of others [##REF##17156017##57##] demonstrate that <italic>S. cerevisiae </italic>yeast cells expressing mammalian PrP are protected from Bax-induced cell death. In addition, PrP expression was shown to reduce cell death in MCF-7 cells by inhibiting a pro-apoptotic conformational change in Bax [##REF##15846375##25##]. Deletion of the Bax gene rescues neuronal loss in Tg(PG14) mice expressing a disease-associated mutant PrP with impaired neuroprotective activity [##REF##15618403##58##,##REF##17510630##59##] but does not prevent neuronal death in transgenic mice expressing PrPΔ105-125 or PrPΔ32-134 [##REF##17251426##60##]. Bax deletion has no effect on the disease course in scrapie-infected mice [##REF##16854590##61##,##REF##18032675##62##]. Since PrP is largely present on the cell surface and Bax is localized to the cytosol, interaction between the two proteins, if it occurs, must either be indirect or else involve rare cytosolic forms of PrP [##REF##12917444##26##,##REF##17494694##27##]. Relevant to this issue, there is evidence that cytosolic PrP physically associates with the Bax antagonist, Bcl-2 [##REF##16707568##63##], but not with Bax itself [##REF##15846375##25##].</p>", "<title>Cell culture models to investigate the cytoprotective activity of PrP</title>", "<p>In a number of cell types, expression of PrP seems to exert a protective effect against several different toxic insults [##REF##17451912##6##,##REF##15645198##23##]. Although we failed to observe a robust protective activity when we re-examined three of the published systems, we did note that the presence of PrP was associated with a small improvement (&lt; 20%) in cell viability in some of our experiments. Whether these effects observed in cell culture experiments reflect a physiologically relevant activity of PrP^Cremains to be determined. It is possible that they represent <italic>in vitro </italic>artifacts due to PrP over-expression or other factors. Alternatively, PrP^Cmay possess a cytoprotective activity <italic>in vivo </italic>that is not easily reproduced in cell culture models. This might be the case if the cellular stresses applied experimentally do not adequately mimic those operative in brain tissue, or because cultured cells lack some of the relevant PrP-dependent death pathways.</p>", "<p>At present, the most compelling evidence for a role of PrP in cytoprotective and cytotoxic phenomena comes from mice expressing Dpl or PrP forms harboring deletions that span residues 105–125 [##REF##9568713##10##, ####REF##17245436##11##, ##REF##17245437##12####17245437##12##,##REF##10525406##15##]. These molecules produce a dramatic neurodegenerative phenotype that is dose-dependently suppressed by co-expression of wild-type PrP. Therefore, it would seem that cell culture systems capable of reproducing this phenomenon would be the most useful tools for investigating the toxic and protective activities of PrP^C. Several reports have appeared in which expression of Dpl or deleted PrP forms in cultured cells impairs viability, with co-expression of wild-type PrP suppressing this effect [##REF##15950943##37##,##REF##15459186##55##,##REF##17703189##56##,##REF##16766127##64##]. Further development of these and other cell models will greatly aid in deciphering the physiological function of PrP^C, and how it might be subverted during the disease process.</p>" ]

[ "<title>Conclusion</title>", "<p>In this study, we investigated the cytoprotective activity of PrP^Cin several mammalian cell culture systems. In each system tested, expression of wild-type PrP elicited a modest protective effect, although less than in previously published studies. We conclude that the cytoprotective activity of PrP^Cobserved <italic>in vivo </italic>is not easily recapitulated <italic>in vitro</italic>. Either the cellular stresses employed do not engage a PrP^C-dependent pathway, or cytoprotection is not a physiologically relevant activity of PrP^C.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The physiological function of the cellular prion protein (PrP^C) remains unknown. However, PrP^Chas been reported to possess a cytoprotective activity that prevents death of neurons and other cells after a toxic stimulus. To explore this effect further, we attempted to reproduce several of the assays in which a protective activity of PrP had been previously demonstrated in mammalian cells.</p>", "<title>Results</title>", "<p>In the first set of experiments, we found that PrP over-expression had a minimal effect on the death of MCF-7 breast carcinoma cells treated with TNF-α and <italic>Prn-p</italic>^{<italic>0/0 </italic>}immortalized hippocampal neurons (HpL3-4 cells) subjected to serum deprivation. In the second set of assays, we observed only a small difference in viability between cerebellar granule neurons cultured from PrP-null and control mice in response to activation of endogenous or exogenous Bax.</p>", "<title>Conclusion</title>", "<p>Taken together, our results suggest either that cytoprotection is not a physiologically relevant activity of PrP^C, or that PrP^C-dependent protective pathways operative <italic>in vivo </italic>are not adequately modeled by these cell culture systems. We suggest that cell systems capable of mimicking the neurotoxic effects produced in transgenic mice by N-terminally deleted forms of PrP or Doppel may represent more useful tools for analyzing the cytoprotective function of PrP^C.</p>" ]

[ "<title>Abbreviations</title>", "<p>CGN: cerebellar granule neuron; Dpl: Doppel; EGFP: enhanced green fluorescent protein; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GFAP: glial fibrillary acid protein; LDH: lactate dehydrogenase; MTT: 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide; NF-L: neurofilament light chain; PG14: nine-octapeptide insertional mutation in PrP; PrP: prion protein; PrP^C: cellular isoform of PrP; PrP^Sc: scrapie isoform of PrP; Tg: transgenic; TNF-α: tumor necrosis factor-α; TRAIL: tumor necrosis factor-related apoptosis inducing ligand.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>HC and DH conceived of the study, designed experiments, analyzed data, and wrote the manuscript. HC performed experiments. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We gratefully thank Cheryl Adles and Su Deng for mouse maintenance and genotyping. We also acknowledge Leanne Stewart for primer design and quantitative RT-PCR assistance. <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice were obtained from Charles Weissmann. Helen Piwnica-Worms and Lynn White (Washington University) provided expertise for the flow cytometry analysis. Greg Longmore (Washington University) provided MCF-7 cells. HpL3-2 and HpL3-4 cells were a gift from Shu Chen (Case Western Reserve) and Takashi Onodera (University of Tokyo, Japan), respectively. We also thank Man-Sun Sy and Rick Kascsak for, respectively, 8H4 and 3F4 antibodies. This work was supported by grants to D.A.H. from the N.I.H. (R01NS052526 and R01NS040975). H.M.C. was supported by the Markey Pathway at Washington University and a pre-doctoral fellowship from the N.I.H.(5F31NS046910).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Untransfected MCF-7 cells undergo cell death following treatment with recombinant TNF-α</bold>. (A) MCF-7 cells were treated with 100 ng/ml TNF-α, and cell viability was assessed using the MTT assay. Absorbance values are expressed as a percentage of those in non-treated control samples at each timepoint. Error bars are derived from triplicate wells of one representative experiment. (B) Flow cytometry analysis of untreated or TNF-α-treated MCF-7 cells. Cells were trypsinized, fixed in ethanol, and incubated with propidium iodide prior to analysis by flow cytometry. 10,000 cells were counted for each condition. Data are expressed as the percentage of cells containing sub-2n DNA content in one representative experiment.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Expression of human PrP mildly suppresses TNF-α-mediated death of MCF-7 breast carcinoma cells</bold>. (A) PrP expression was assessed by western blotting of three pools of vector-transfected MCF-7 cells (lanes 1–3) and six pools of MCF-7 cells transfected with a human PrP plasmid (lanes 4–9). (B) Pools of MCF-7 cells were treated with 100 ng/ml of recombinant TNF-α for 43 h. Cell viability was determined by the MTT assay. Absorbance values are expressed as a percentage of those in non-treated control samples. Data represent the mean ± SEM from 3 vector-transfected pools and 6 PrP-transfected pools. *p = 0.0042, human PrP vs. vector. (C) Pools of MCF-7 cells were treated with 100 ng/ml of recombinant TNF-α for 43 h. Cell viability was determined by flow cytometry after staining with propidium iodide. 10,000 cells were counted for each condition, and data are expressed as the percentage of cells containing sub-2n DNA. Data are derived from 4 MCF-7(hPrP) pools (mean ± SEM) and one vector control pool.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Stable expression of PrP weakly suppresses death of immortalized <italic>Prn-p</italic>^{<italic>0/0 </italic>}hippocampal neurons after serum deprivation</bold>. (A) Two untransfected lines of <italic>Prn-p</italic>^{<italic>0/0 </italic>}HpL cells (3–2 and 3–4) were subjected to 72 hours of serum deprivation. Cell viability was determined by MTT assay. Absorbance values are expressed as a percentage of those in non-treated control samples at each timepoint. Data are from one representative experiment. (B) Immunofluorescence analysis of mouse PrP expression in two PrP-expressing lines of HpL3-4 cells (4-1 and 4-2), and one vector-transfected line. PrP was detected by staining with the PrP antibody (green). Cells were counterstained with giantin, a marker for the Golgi apparatus (red). PrP expression was detectable on the cell surface and in the Golgi apparatus. Bar = 50 μm. (C) HpL3-4 cell lines were subjected to 96 hours of serum deprivation, after which cell viability was determined by flow cytometry after propidium iodide staining. 10,000 cells were counted for each condition. Data are expressed as the percentage of cells containing sub-2n DNA content, and represent the mean ± SEM from three independent experiments. *p &lt; 0.01, PrP vs. vector. Relative PrP expression for each cell line is indicated below each set of bars by the number of \"+\" symbols.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>PrP does not significantly reduce death of cerebellar granule neurons induced by exogenous Bax</bold>. (A-D) Representative fluorescence images of cerebellar granule neurons from <italic>Prn-p</italic>^{<italic>0/0 </italic>}mice transfected with plasmids encoding EGFP and mouse Bax. Four days after transfection, cultures were stained with DAPI, and EGFP-positive neurons were scored as healthy (A, B) or apoptotic (C, D) based on morphological criteria. These criteria included the distribution of EGFP in the soma and neurites, and the appearance of DAPI staining in the nucleus (see text). (E) CGNs cultured from <italic>Prn-p</italic>^+/+or <italic>Prn-p</italic>^{<italic>0/0 </italic>}pups were transfected with plasmids encoding Bax and EGFP. Cultures were fixed and stained with DAPI either 8 or 16 hours after transfection, and scored for apoptotic morphology. Data represent the mean ± SEM from at least three independent experiments. The difference between <italic>Prn-p</italic>^{<italic>0/0 </italic>}and <italic>Prn-p</italic>^+/+neurons did not reach statistical significance at either time point (p &gt; 0.05).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>CGNs expressing PrP are slightly more resistant to cell death induced by potassium/serum deprivation</bold>. CGNs cultured from <italic>Prn-p</italic>^{<italic>0/0 </italic>}and <italic>Prn-p</italic>^+/+mice were cultured in K25+S medium for 7 days, after which they were transferred to K5-S medium for the designated times. Cell viability was assessed by measurement of calcein fluorescence on a microplate fluorimeter. Fluorescence values in K5-S medium are expressed as a percentage of those in K25+5 medium at each time point. Data represent the mean ± SEM for at least two independent experiments. * p &lt; 0.05, <italic>Prn-p</italic>^+/+vs. <italic>Prn-p</italic>^{<italic>0/0</italic>}.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Analysis of marker proteins in HpL3-2 and HpL3-4 cells by immunofluorescence and quantitative RT-PCR.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>SAMPLE</bold></td><td align=\"center\" colspan=\"3\"><bold>IMMUNOFLUORESCENCE</bold></td><td align=\"center\" colspan=\"3\"><bold>qRT-PCR</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>NeuN</bold></td><td align=\"center\"><bold>MAP2</bold></td><td align=\"center\"><bold>GFAP</bold></td><td align=\"center\"><bold>NF-L</bold></td><td align=\"center\"><bold>GFAP</bold></td><td align=\"center\"><bold>Doppel</bold></td></tr></thead><tbody><tr><td align=\"left\">HpL3-2</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"left\">HpL3-4</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"left\">Brain</td><td align=\"center\">+ *</td><td align=\"center\">+ *</td><td align=\"center\">+ *</td><td align=\"center\">+</td><td align=\"center\">+</td><td align=\"center\">N/A</td></tr><tr><td align=\"left\">Testes</td><td align=\"center\">N/A</td><td align=\"center\">N/A</td><td align=\"center\">N/A</td><td align=\"center\">N/A</td><td align=\"center\">N/A</td><td align=\"center\">+</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>* Immunofluorescence detection of NeuN, MAP2, and GFAP in brain sections was performed previously [##REF##15262264##36##].</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1750-1326-3-11-1\"/>", "<graphic xlink:href=\"1750-1326-3-11-2\"/>", "<graphic xlink:href=\"1750-1326-3-11-3\"/>", "<graphic xlink:href=\"1750-1326-3-11-4\"/>", "<graphic xlink:href=\"1750-1326-3-11-5\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Norovirus is one of the four genera currently accepted into the family <italic>Caliciviridae</italic>. Other genera in this family include Sapovirus, which causes gastroenteritis in humans, as well as Lagovirus and Vesivirus, neither of which are pathogenic for humans. Noroviruses are small, non-enveloped viruses with a diameter of approximately 27–35 nm. They have a positive-sense, single stranded RNA genome [##UREF##0##1##]. Norwalk virus, the prototype strain of the genus norovirus, was first described in 1972 in association with an outbreak of gastroenteritis and vomiting involving children and staff at an elementary school in Norwalk, Ohio [##REF##10804141##2##].</p>", "<p>Noroviruses are now recognized as a common cause of human infectious gastroenteritis in all age groups, especially in restaurants and institutions such as nursing homes and hospitals [##REF##15065694##3##, ####REF##9359742##4##, ##REF##8769621##5####8769621##5##]. They are one of the main causes of foodborne gastroenteritis [##REF##9413535##6##,##REF##10511517##7##]. Furthermore, several animal noroviruses genetically closely related to human noroviruses have been recently discovered [##REF##18294883##8##, ####REF##9687878##9##, ##REF##102800##10####102800##10##]. Their existence raises important questions about animal reservoirs and potential zoonotic transmission [##REF##18294883##8##]. The diagnostic of human and bovine noroviruses is impaired by the difficulties to replicate it in cell culture [##REF##14718622##11##], although a tridimensional culture system was recently shown to be able to grow human noroviruses [##REF##17552092##12##]. The full-length sequencing of different human norovirus genomes has allowed the development of reverse transcription polymerase chain reaction (RT-PCR) [##UREF##1##13##,##REF##8380940##14##], which has become the gold standard for norovirus diagnosis [##REF##11148001##15##]. Due to the genetic diversity among noroviruses, it is very difficult to find an appropriate primer pair that is both sensitive and specific for detection of all noroviruses. The most conserved region of the genome is the RNA polymerase gene and several primer pairs have been selected in that region [##REF##11148001##15##], as the one used in this assay [##REF##12367660##16##]. Real-time RT-PCR assays are more and more developed and has become the method of choice for the detection and the characterization of norovirus. Many different real-time RT-PCR assays for norovirus genogroups I and II had been developed [##REF##12682144##17##, ####REF##17822552##18##, ##REF##17959761##19####17959761##19##] and co-detection of human and animal noroviruses was described in a multiplex assay [##REF##17616614##20##] or simultaneously [##REF##18424068##21##].</p>", "<p>Noroviruses are usually detected in clinical specimens (faeces and vomit) and contaminated food, water or sewage [##REF##7487032##22##, ####REF##1280649##23##, ##REF##8973536##24##, ##REF##10618226##25####10618226##25##]. Such samples commonly contain components reported to be (RT-)PCR inhibitors [##UREF##2##26##,##REF##9157172##27##], leading to a high risk of false negative results or a decrease of the Ct value. A control to adequately detect problems with either RNase contamination or RT-PCR inhibitors is necessary to avoid false-negative responses for samples submitted for diagnosis [##REF##12734248##28##,##REF##9327537##29##]. An internal control is crucial to diagnostic (RT-)PCR assays. It is co-amplified with the target sequence and a negative result indicates a total (RT-)PCR failure. Also partial decrease of amplification capability can be estimated compared with the decrease of the internal control Ct value (internal control in the sample versus internal control alone).</p>", "<p>The aim of this study was the development of a SYBR Green real time RT-PCR method able to detect the most important genogroups of noroviruses circulating in the human and bovine populations. This assay includes an internal RNA control and has been designed and validated for the diagnosis of noroviruses in human and bovine stool samples. Melting curve analysis allows the distinction between the internal control and norovirus amplicons and gives some indication about the species of origin. Moreover, the use of this single tube assay, cheaper than a TaqMan analysis, has the great advantages to detect (RT-)PCR inhibition that may lead to false negative results.</p>" ]

[ "<title>Methods</title>", "<title>Human and animal stool specimens</title>", "<p>Fifty seven human and 29 bovine stool samples were tested. Human samples were selected from faeces collected over a 2-year period (2000–2002) by the Medical Microbiological and Virological Laboratory of the University hospital of Liege and from outbreaks in Belgium provided in part by the Institute for Public Health in Brussels and the Virology Laboratory of the St Luc University hospital (2006–2007). Bovine samples were taken from faeces collected by the regional animal diagnostic laboratories \"ARSIA\" (<italic>Association Régionale de Santé et d'Identification Animales</italic>) in Belgium over a two year period (2002–2003). All bovine and human samples had been tested previously for norovirus by conventional one-step RT-PCR and sequenced for confirmation. The stool specimens were stored at -80°C. All positive samples were used in this study and 36 negative samples were randomly selected.</p>", "<title>Processing of stool samples, RNA extraction and conventional RT-PCR</title>", "<p>The all procedure was already described [##REF##18424068##21##]. Briefly, stool samples were 10-fold diluted in phosphate-buffered saline and RNA was extracted using the QIAamp viral RNA Mini Kit (Qiagen, Leusden, The Netherlands). A one-step RT-PCR kit, the Access RT-PCR System (Promega, Leiden, The Netherlands), was used with broadly reactive primer pairs, developed for the detection of noroviruses in stool specimens from humans or bovines [##REF##18424068##21##].</p>", "<title>Real-time RT-PCR system</title>", "<p>The real-time PCR assays were carried out on the iCycler (Biorad, Nazareth, Belgium) using iScript One-step RT-PCR kits for SYBR-Green assay (Biorad, Nazareth, Belgium) and used 2 μl of extracted RNA with 25 μl of master-mix with primers at 300 nM final concentration.</p>", "<p>The primer set used was JV12Y-JV13I [##REF##12367660##16##]. The quantity of 117,500 copies of the internal RNA control was added with each sample. The iCycler RT-PCR protocol included the following parameters: reverse transcription for 18 minutes at 48°C, 5 minutes at 95°C, followed by 45 cycles of 10 seconds at 95°C, 20 seconds at 48°C and 45 seconds at 60°C. Data were obtained during the elongation period. After the RT-PCR reaction, melting curve analysis was performed. To remove inhibition, BSA was added at a final concentration of 400 ng/μl in the RT-PCR mix or the extracted RNA was 10-fold diluted. A negative sample was added every 18 samples. All positive samples were confirmed by sequencing RT-PCR products.</p>", "<title>Statistical validation</title>", "<p>Agreement of the mean melting temperature obtained with the real-time SYBR Green assay (repeatability, 35 duplicates and 10 triplicates, and reproducibility, 33 twice and 5 threefold) was measured according to a method described by Petrie and Watson [##UREF##3##39##].</p>", "<p>Comparison between melting temperatures obtained with the real-time SYBR Green assay in each group (human noroviruses, bovine noroviruses and internal control) was performed using Wilcoxon rank tests and assuming unequal variance and data not distributed as a normal distribution [##UREF##4##40##].</p>", "<p>All statistical analyses were carried out with Stata/SE [##UREF##5##41##]. Relative sensitivity and specificity were estimated with 95% confidence intervals assuming a binomial exact distribution. The limit of statistical significance of the conducted tests was defined as <italic>P </italic>≤ 0.05 and the Kappa coefficient was calculated.</p>" ]

[ "<title>Results</title>", "<title>Validation of the SYBR Green real-time RT-PCR assay – control of inhibition</title>", "<p>The set up of the internal RNA control had been previously described [##REF##18424068##21##] and the primers used in the SYBR Green real-time RT-PCR had been validated for their specificity by Vennema and collaborators [##REF##12367660##16##].</p>", "<p>Serial dilution of the norovirus internal RNA control transcribed <italic>in vitro </italic>demonstrated that 2 μl of the 10⁹fold dilution contained adequate template to produce a detectable product by melting curve analysis following real-time RT-PCR. This corresponds to a quantity of 1.9 × 10^-6ng of internal RNA control or 5,800 copies [##REF##18424068##21##].</p>", "<p>Amplification of the internal RNA control produced amplicons with a melting temperature 3°C lower than norovirus amplicons (Figure ##FIG##0##1##).</p>", "<p>The exact amount of internal control to add in the mix with each RNA extraction from stool samples was determined using the detection limit of the internal control in real-time SYBR Green RT-PCR and checking the non-competitive amplification between the internal control and norovirus RNA. Different amounts of internal RNA control were added with 10-fold serial dilutions of extracted norovirus RNA. At the same time, a serial dilution of extracted norovirus RNA without internal control was tested with the SYBR Green real-time RT-PCR assay (data not shown). The quantity to add to a 25 μl mix was 3.8 × 10^-5ng of internal RNA control, corresponding to 117,500 copies. The performances of the assay were evaluated using serially diluted internal RNA control (10-fold dilutions) from 5.8 × 10⁶to 5.8 × 10¹¹copies and linearity was obtained (Figure ##FIG##1##2##).</p>", "<p>Most of the values obtained with the SYBR Green assay were within the 95% limits of agreement (mean of differences +/- 1.96 S.D. of the differences) showing satisfactory agreement (data not shown). For repeatability and reproducibility, the standard errors of measurement were less than 0.291°C and 0.354°C respectively. The mean melting temperatures were significantly lower for the internal control than both human and bovine noroviruses. Moreover the mean melting temperature for human noroviruses was significantly lower than the melting temperature for bovine noroviruses (Wilcoxon rank tests, P &lt; 0.001) (Figure ##FIG##2##3##).</p>", "<title>Analysis of human and bovine stool samples</title>", "<p>The comparison of the results obtained with the SYBR Green and the conventional RT-PCR assay is shown in table ##TAB##0##1##. In a first stage, the SYBR Green assay was performed on extracted RNA from stool samples. Three kinds of results were obtained: negative if a peak at 81.5°C was shown in the melting curve, positive if a peak around 85–88°C was shown and inhibition of reaction if there was an absence of these peaks (Figure ##FIG##0##1##). Samples containing human genogroup I or II noroviruses and bovine genogroup III noroviruses were tested and often showed different melting temperatures. The majority of bovine norovirus amplicons showed a melting temperature around 3°C higher than the human noroviruses (Figure ##FIG##2##3##).</p>", "<p>The use of the internal control for norovirus real-time RT-PCR diagnosis in 86 stool samples identified inhibition of RT-PCR in 32.6% of stool samples tested in this study (Table ##TAB##0##1##). Two different methods were used on extracted RNA from samples showing inhibition. One is a 10-fold dilution of the extracted RNA before testing with the SYBR Green assay and the second one is the addition of bovine serum albumin (BSA) in the mix. Among the 28 samples showing inhibition, a 10-fold dilution was active in all samples compared to BSA that failed to remove inhibition from 4 samples.</p>", "<p>Considering the SYBR Green assay as the gold standard (Table ##TAB##0##1##), the relative sensitivity of the conventional RT-PCR used in this study was 92.6% (95% confidence interval (CI) 82.1–97.9). The relative specificity was 100% (CI 91–100) for all techniques. Confirming these results, Kappa value showed a high level of agreement between conventional RT-PCR and the SYBR Green real-time RT-PCR (Kappa value: 0.90; CI 0.81–0.99).</p>" ]

[ "<title>Discussion</title>", "<p>In this study we developed a sensitive and broadly reactive real-time SYBR Green RT-PCR assay that interestingly detects human genogroups I and II and bovine genogroup III noroviruses in a single tube, including an internal control. This assay takes into account that samples may contain inhibitors of PCR or RT-PCR [##REF##7487032##22##,##REF##1280649##23##]. The method uses one-step, hot start RT-PCR with thermostable DNA polymerase. The one step protocol simplifies the method and reduces the risk of contamination of RNA. Moreover it is useful for routine diagnosis as there is no post-amplification processing of the product.</p>", "<p>The genetic diversity of noroviruses makes though to select a pair of primers capable of detecting all the different norovirus genogroups. The commonly used JV12-13 primer pair has been replaced by JV12Y-13I, which contains degenerated bases to allow the detection of a larger panel of noroviruses [##REF##12367660##16##]. This primer pair is able to detect noroviruses belonging to human genogroups I and II and bovine noroviruses belonging to genogroup III [##REF##10653567##30##]. The variability in the melting temperature between human and bovine noroviruses can be also explained by the genetic diversity among norovirus sequences [##REF##12393155##31##,##REF##15574915##32##], even if the amplicon is located in the polymerase region highly conserved among noroviruses. Therefore, this assay has the rare advantage to detect norovirus strains irrespectively of their origin (human or bovine). There are few methods described that allow the detection of both human and bovine noroviruses. Compared to the method recently published by Wolf and collaborators [##REF##17616614##20##], our assay has the advantage to detect noroviruses in the same reaction tube and to control for inhibition of the reaction. It is also to detect mixed infection (presence of human and bovine noroviruses in the same sample), by the presence of two distinct peaks.</p>", "<p>A common problem with RT-PCR is the presence of (RT)-PCR inhibitors which may cause false negative results. Therefore, to avoid such false negative results, the internal RNA control set up previously [##REF##18424068##21##] was used in this real-time SYBR Green RT-PCR assay. It was synthesized <italic>in vitro </italic>from a foreign DNA template, in order to decrease interference with norovirus amplicons [##REF##12088820##33##,##REF##9003630##34##]. It has the advantages of representing no risk for human or animal health because it does not contain any infectious material, and being stable compared to live control viruses that can evolve and change during their replication. The norovirus amplification is favored compared to the internal control because the RT-PCR of the later results in a larger product. It is an essential property for its function. It means a decrease of the Ct value of the internal control if noroviruses are present in the sample.</p>", "<p>With this internal RNA control, inhibition can be detected without the need of additional primer pairs or an additional reaction run for this purpose and the effective identification of samples containing endogenous inhibitors of RT-PCR is allowed. This improvement is crucial for early intervention and control in norovirus outbreaks.</p>", "<p>With routine samples used for diagnosis, 36.8% of human samples and 24.1% of bovine samples showed presence of inhibition that can vary a lot among samples and may depend on the type of sample but also on the intrinsic characteristics of the sample (for example, herbivorous or omnivorous diet). When inhibition was detected in samples, the extracted RNA was tested a second time with the SYBR Green assay, on 10-fold diluted RNA or with BSA added in the RT-PCR mix. Sample dilution is often effective as the inhibitory factors can be diluted out, however, enough quantities of target nucleic acid must be present in order to be detected after dilution [##REF##16597869##35##]. The addition of BSA, that is able to scavenge a variety of inhibitory substances [##REF##8975603##36##], does not have this inconvenience. Our experience in using those two techniques to remove inhibitors led to the conclusion that a 10-fold dilution is more efficient and reproducible than the addition of BSA.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, the real-time assay described in this study is an accurate, sensitive, specific and quick method for the detection of a wide range of noroviruses belonging to genogroups I, II and III. At the same time it offers a method to detect samples containing inhibitors, avoiding false negative results by using an internal control. This assay will be applicable to clinical diagnosis in human and animal laboratories, detection of viruses in food or environmental samples. It is the first SYBR Green real-time assay that uses a single primer pair able to detect human and bovine noroviruses simultaneously. A 10-fold dilution of RNA appears to be the method of choice to remove inhibition.</p>", "<p>The melting curve analysis gives presumption for the virus origin regarding the host and points out interesting samples to sequence for further studies (bovine norovirus with a melting temperature similar to the human norovirus ones). This property is of upmost importance regarding classification and study of transmission routes of noroviruses. This requires sequencing step in addition to detection. Although neither a zoonotic transmission, nor identification of an animal reservoir of norovirus have been already identified in natural condition, experimental evidence of cross infection was provided with successful inoculation of pigs with human norovirus [##REF##18294883##8##,##REF##17041218##37##]. Moreover bovine noroviruses have been detected in the food chain, in a bivalve mollusc sample which was contaminated with human noroviruses [##REF##16517625##38##]. This increases the risk of crossing the species barrier and the probability of the emergence of recombinant viruses. In that context, a diagnostic assay that has the capacity to detect both human and bovine noroviruses is of high interest.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Noroviruses are single-stranded RNA viruses belonging to the family <italic>Caliciviridae</italic>. They are a major cause of epidemic and sporadic gastroenteritis in humans and clinical signs and lesions of gastroenteritis were reported in bovines. Due to their genetic proximity, potential zoonotic transmission or animal reservoir can be hypothesized for noroviruses. RT-PCR has become the \"gold standard\" for the detection of noroviruses in faecal and environmental samples. With such samples, the control for inhibition of the reaction during amplification and detection is crucial to avoid false negative results, which might otherwise not be detected. The aim of the reported method is to detect, with a SYBR Green technology, a broad range of noroviruses with a control for inhibition.</p>", "<title>Results</title>", "<p>A SYBR Green real-time RT-PCR assay was developed making use of a foreign internal RNA control added in the same tube. This assay is able to detect human and bovine noroviruses belonging to genogroups I, II and III and to distinguish between norovirus and internal control amplicons using melting curve analysis. A 10-fold dilution of samples appears to be the method of choice to remove inhibition. This assay was validated with human and bovine stool samples previously tested for norovirus by conventional RT-PCR.</p>", "<title>Conclusion</title>", "<p>This SYBR Green real-time RT-PCR assay allows the detection of the most important human and bovine noroviruses in the same assay, and avoids false negative results making use of an internal control. Melting curves allow the discrimination between the internal control and norovirus amplicons. It gives preliminary information about the species of origin. The sensitivity of the developed assay is higher than conventional RT-PCR and a 10-fold dilution of samples showed a better efficiency and reproducibility to remove RT-PCR inhibition than addition of bovine serum albumin.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>AS designed the internal control and the SYBR Green assay and did the real-time analyses. She drafted the manuscript. DZ carried out the conventional RT-PCR analyses of stool samples, and participated in analytical methods. AM was involved in the laboratory analyses and the draft of the manuscript. CS performed the statistical analysis. AS and ET conceived the study. ET is the head of the laboratory. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported in part by SPF \"Santé publique, Sécurité de la Chaîne alimentaire et Environnement\" (RF6185), by Belgian Science Policy – Science for a Sustainable Development (SSD) (SD/AF/01), by the \"Région Wallonne\" (415701) and the University of Liège.</p>", "<p>The authors thank Miss Pascaline Peeters for technical assistance during her practice training period and the staff of the Virology Laboratory for technical assistance. We thank especially Dr Geneviève Christiaens, Dr Patrick Goubau, Katelijne Dierick and Nadine Botteldoorn for their kind assistance and efficacy to collect samples. We thank Drs Czaplicki, Lomba (Association Régionale de Santé et d'identification animale) and De Mol (Microbiology, Faculty of Medicine, University of Liège) for their assistance in the collection of animal and human samples respectively. We are very grateful to Jennifer Cannon for her careful reading of the manuscript.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Distinction between norovirus amplicons and internal control amplicon allowed by the melt curve analysis</bold>. The internal control has a melting temperature around 81.5°C, human norovirus amplicons, around 85.5°C and bovine norovirus amplicons has a melting temperature around 88.5°C. Such differences in temperature are clearly visible on the curve.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Linearity of the SYBR Green assay</bold>. (A) Detection of 10-fold serial dilution of a positive human sample by the SYBR Green assay performed from 5.8 × 10⁶to 5.8 × 10¹¹molecules. (B) Standard curve of these dilutions, each dot representing the result of amplification for each quantity.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Frequency occurrence of amplicon melting temperature for human noroviruses, bovine noroviruses, and the internal control</bold>. The majority of bovine norovirus amplicons has a melting temperature around 88.5°C, about 3°C higher than the human ones. Though some bovine samples shown have a melting temperature similar to the human norovirus ones.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Comparison of the detection of human and bovine noroviruses by the conventional RT-PCR assay and the SYBR Green assay</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td align=\"center\" colspan=\"6\">SYBR Green RT-PCR</td><td/></tr></thead><tbody><tr><td/><td/><td align=\"center\" colspan=\"2\">+</td><td align=\"center\" colspan=\"2\">-</td><td align=\"center\" colspan=\"2\">Inhibition</td><td/></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"center\">Conventional</td><td align=\"center\">+</td><td align=\"center\">44</td><td align=\"center\"><bold>50</bold></td><td align=\"center\">0</td><td align=\"center\"><bold>0</bold></td><td align=\"center\">6</td><td align=\"center\"><bold>0</bold></td><td align=\"center\">50</td></tr><tr><td align=\"center\">RT-PCR</td><td align=\"center\">-</td><td align=\"center\">1</td><td align=\"center\"><bold>4</bold></td><td align=\"center\">13</td><td align=\"center\"><bold>32</bold></td><td align=\"center\">22</td><td align=\"center\"><bold>0</bold></td><td align=\"center\">36</td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td/><td/><td align=\"center\">45</td><td align=\"center\"><bold>54</bold></td><td align=\"center\">13</td><td align=\"center\"><bold>32</bold></td><td align=\"center\">28</td><td align=\"center\"><bold>0</bold></td><td align=\"center\">86</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Normal font: SYBR Green assay on RNA directly; <bold>bold font</bold>: SYBR Green assay modified to remove inhibition using 10-fold dilution of extracted RNA.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1743-422X-5-94-1\"/>", "<graphic xlink:href=\"1743-422X-5-94-2\"/>", "<graphic xlink:href=\"1743-422X-5-94-3\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Proventricular dilatation disease (PDD) is considered by many to be the greatest threat to aviculture of psittacine birds (parrots). This disease has been documented in multiple continents in over 50 different species of psittacines as well as captive and free-ranging species in at least 5 other orders of birds [##REF##1920678##1##, ####REF##17359314##2##, ##UREF##0##3##, ##REF##18087938##4##, ##REF##9382728##5####9382728##5##]. Most, if not all major psittacine collections throughout the world have experienced cases of PDD. It has been particularly devastating in countries like Canada and northern areas of the United States where parrots are housed primarily indoors. However, it is also problematic in warmer regions where birds are typically bred in outdoor aviaries. Moreover, captive breeding efforts for at least one psittacine which is thought to be extinct in the wild, the Spix's macaw (<italic>Cyanopsitta spixii</italic>), have been severely impacted by PDD.</p>", "<p>PDD is an inflammatory disease of birds, first described in the 1970s as Macaw Wasting Disease during an outbreak among macaws (reviewed in [##UREF##0##3##]). PDD primarily affects the autonomic nerves of the upper and middle digestive tract, including the esophagus, crop, proventriculus, ventriculus, and duodenum. Microscopically, the disease is recognized by the presence of lymphoplasmacytic infiltrates within myenteric ganglia and nerves. Similar infiltrates may also be present in the brain, spinal cord, peripheral nerves, conductive tissue of the heart, smooth and cardiac muscle, and adrenal glands. Non-suppurative leiomyositis and/or myocarditis may accompany the neural lesions [##UREF##1##6##, ####REF##1874676##7##, ##REF##3579790##8##, ##REF##1485869##9####1485869##9##]. Clinically, PDD cases present with GI tract dysfunction (dysphagia, regurgitation, and passage of undigested food in feces), neurologic symptoms (e.g. ataxia, abnormal gait, proprioceptive defects), or both [##UREF##0##3##]. Although the clinical course of the disease can vary, it is generally fatal in untreated animals [##UREF##0##3##].</p>", "<p>The cause of PDD is unknown, but several studies have raised the possibility that PDD may be caused by a viral pathogen. Evidence for an infectious etiology stems from the initial outbreaks of Macaw Wasting Disease, and other subsequent outbreaks of PDD [##REF##17359314##2##,##UREF##2##10##]. Reports of pleomorphic virus-like particles of variable size (30–250 nm) observed in tissues of PDD affected birds [##REF##3579790##8##] led to the proposal that paramyxovirus (PMV) may cause the disease; however, serological data has shown that PDD affected birds lack detectable antibodies against PMV of serotypes 1–4, 6, and 7, as well as against avian herpes viruses, polyomavirus, and avian encephalitis virus [##UREF##0##3##]. Similarly, a proposed role for equine encephalitis virus in PDD has been ruled out [##UREF##3##11##]. Enveloped virus-like particles of approximately 80 nm in diameter derived from the feces of affected birds have been shown to produce cytopathic effect in monolayers of macaw embryonic cells [##REF##8819297##12##], but to date no reports confirming these results or identifying this possible agent have been published. Likewise, adeno-like viruses, enteroviruses, coronaviruses and reoviruses have also been sporadically documented in tissues or excretions of affected birds [##UREF##0##3##,##REF##16595304##13##,##UREF##4##14##] yet in each case, follow-up evidence for reproducible isolation specifically from PDD cases or identification of these candidate agents has not been reported. Thus, the etiology of PDD has remained an open question.</p>", "<p>To address this question, we have turned to a comprehensive, high throughput strategy to test for the presence of known or novel viruses in PDD affected birds. We employed the Virus chip, a DNA microarray containing representation of all viral taxonomy to interrogate 2 PDD case/control series independently collected on two different continents for the presence of viral pathogens. We report here the detection of a novel bornavirus signature in 62.5% of the PDD cases and none of the controls. These bornavirus-positive samples were confirmed by virus-specific PCR testing, and the complete genome sequence has been recovered by ultra-high throughput sequencing combined with conventional PCR-based cloning.</p>", "<p>Bornaviruses are a family of negative strand RNA viruses whose prototype member is Borna Disease Virus (BDV), an agent of encephalitis whose natural reservoir is primarily horses and sheep [##REF##16469519##15##]. Although experimental transmission of BDV to many species (including chicks [##REF##7789148##16##]) has been described, there is little information on natural avian infection, and existing BDV isolates are remarkable for their relative sequence homogeneity. The agent reported here, which we designate avian bornavirus (ABV) is highly diverged from all previously identified members of the <italic>Bornaviridae </italic>family and represents the first full-length bornavirus genome cloned directly from avian tissue. Subsequent PCR screening for similar ABVs confirmed a detection rate of approximately 70% among PDD cases and none among the controls. Sequence analysis of a single complete genome and all of the additional partial sequences that we have recovered directly from the PDD case specimens suggests that the viruses detected in cases of PDD form a new, genetically diverse clade of the <italic>Bornaviridae</italic>.</p>" ]

[ "<title>Methods</title>", "<title>PDD case and control definitions, specimen collection, and RNA extraction for pan-viral microarray screening</title>", "<p>Two independent sets of PDD case and control specimens collected from two distinct geographic locations were independently prepared for pan-viral microarray screening and subsequent PCR screening. Sampling collection and inclusion criteria for each set are described below. Detailed information on each sample, along with results from histology, microarray, and PCR assays are provided in Additional file ##SUPPL##4##5##: Summary of clinical and molecular data for specimens provided in this study.</p>", "<title>United States PDD case/control series</title>", "<title>Specimen collection</title>", "<p>All specimens provided for initial screening were crop tissue biopsies obtained from live psittacine birds to be used as normal controls or multiple tissue samples collected from clinically diseased birds at the time of euthanasia. Specimens were collected from client-owned birds from approximately August 2006 to May 2008 (All samples collected by S. Clubb). All of these samples originated from the southeast region of Florida. Crop biopsy tissue was collected from live birds under isoflurane anaesthesia. Following routine surgical preparation and sterile technique, the skin was incised over the center of the crop. The crop tissue was exposed and a section of tissue removed taking care to include large visible blood vessels. Fresh crop biopsy tissue was trimmed into tissue slices &lt; 5 mm thick and submersed in RNAl<italic>ater </italic>(Qiagen, Inc., USA, Valencia, CA) solution immediately upon harvest and frozen within 2 minutes of collection at -20°C to -80°C according to manufacturer's protocol, and held in this manner until shipped. A duplicate sample was fixed in 10% buffered formalin for routine histological examination with H &amp; E stain. Time of frozen storage varied (2 weeks to 12 months) as samples were accumulated prior to shipping frozen. Clinically affected birds submitted as positives were euthanized under isoflurane anaesthesia and mixed tissues (proventriculus, ventriculus, heart, liver, spleen, kidneys, brain) were placed into RNAlater within 1 minute of death and frozen within 2 minutes of death. Duplicate samples were collected for histopathologic diagnosis of PDD.</p>", "<title>Inclusion criteria</title>", "<p>PDD-positive cases were required to meet the following criteria 1) Clinical history of characteristic wasting/malabsorption syndrome with dilation of the proventriculus and/or ventriculus and presence of undigested food in the stool and in most cases, a clinical history of ataxia or other CNS signs consistent with clinical PDD, and 2) histopathology confirming the presence of moderate to extensive lymphoplasmacytic ganglioneuritis affecting crop tissue and at least one of the following additional areas: proventriculus, ventriculus, brain, adrenal gland, or myocardium. PDD-negative controls were required to be from birds with no evidence of lymphoplasmacytic neurogangliitis on histopathology derived either from 1) normal birds with no clinical history of PDD or no known exposure to PDD or 2) birds which died of other causes. Crop biopsies from samples from living birds classified as suspicious cases were also submitted. Suspicious cases were defined histologically as having lymphocytes and plasma cells surrounding neurons but not infiltrating into the neurons. An additional specimen derived from a live bird raised with two necropsy-confirmed PDD birds in Virginia was also collected for analysis. Here, only cloacal swab and blood specimens were available and the lack of histopathological confirmation and crop tissue excluded this specimen from the ABV-PDD association analysis. However, we did perform ABV PCR on these clinically suspicious specimens and the resulting viral sequences isolated were included in the subsequent comparative sequence analyses.</p>", "<title>RNA extractions</title>", "<p>For RNA extractions, specimens were thawed in RNALater, sliced into 0.5 mm × 0.5 mm pieces, transferred to 2 ml of RNABee solution (Tel-Test, Inc., Friendswood, TX), homogenized with freeze thawing and scapel mincing, then extracted in the presence of chloroform according to manufacterer's instructions. Resulting RNA was next incubated with DNase (DNA-free, Applied Biosystems/Ambion, Austin, TX) to remove any potential contaminating DNA present in the specimen.</p>", "<title>Israeli case/control series</title>", "<title>Specimen collection</title>", "<p>Tissue samples were obtained from psittacine birds submitted to the Division of Avian and Fish Diseases, Kimron Veterinary Institute (KVI) Bet Dagan, Israel, for diagnostic necropsy between July 2004 and March 2008. A few additional specimens were obtained through private veterinarians. Some tissues were kept for nearly 4 years frozen either at -20°C or -80°C prior to testing, while others were fresh tissues from recent cases. The types of banked frozen tissue varied from case to case, while for some of the older cases only gastrointestinal content had been banked. Clinical histories for these birds were available from the submission forms or through communication with the submitting veterinarians. The results of ancillary tests performed at the KVI were available through the KVI computerized records.</p>", "<title>Inclusion criteria</title>", "<p>Only cases for which appropriate histological sections were available for inspection were considered for this study. These had to include brain and at least two of the following tissues: crop, proventriculus, ventriculus. The tissue-types examined for each bird for which specimens were provided are listed in Data File S1. PDD-positive cases were required to have evidence of lymphoplasmacytic infiltration of myenteric nerves and/or ganglia within one or more of the upper GI tract tissues mentioned above. These were all derived from birds that had been suspected to have PDD based on their clinical case histories and/or necropsy findings. PDD-negative controls had no detectable lesions and no evidence of non-suppurative encephalitis. For most birds in the PDD-negative group, a cause of death (other than PDD) has been determined. Two birds that came from a known PDD outbreak, but showed only cerebral lymphoplasmacytic perivascular cuffing, were classified as 'suspicious'. These were excluded from the statistical analysis, as were all other birds for which a PDD status could not be clearly determined and classified as 'inconclusive' (e.g. due to poor tissue preservation, poor section quality, or scarcity of myenteric nerves within the tissues examined).</p>", "<title>RNA extraction</title>", "<p>When possible, a sample of brain as well as a combined proventricular/ventricular sample was prepared for RNA extraction for each bird. If not available, other tissues and/or gastrointestinal content were used (see Additional file ##SUPPL##4##5##: Summary of clinical and molecular data for specimens provided in this study). Frozen samples were allowed to thaw for 1–2 hours at room temperature prior to handling. Then, under a laminar flow biohazard hood and using aseptic technique, approximately 1 cm³of each tissue was macerated by two passages through a 2.5 ml sterile syringe and transferred into sterile test tubes containing 4 ml nuclease-free PBS. The content of the tubes was mixed by vortex for 30 sec, and the tubes were placed overnight at 4°C. RNA extraction was performed on the following day, using either the QIAamp^®viral RNA kit (Qiagen, Valencia, CA; batch1&amp;2, specimens 1–8) or the TRI Reagent^®kit (Molecular Research Center, Cincinnati, OH; all other specimens), following the manufacturers' instructions. The end product was either provided lyophilized (batches 1 and 2, samples 1–9) as a dry pellet, or re-suspended in 40 ul nuclease-free water.</p>", "<title>Virus chip hybridization experiments</title>", "<p>Microarray analysis of specimens was carried out as previously described [##REF##16983602##18##]. Briefly, 50–200 ng of DNAse-treated total RNA from each sample was amplified and labelled using a random-primed amplification protocol and hybridized to the Virochip. Microarrays (NCBI GEO platform GPL3429) were scanned with an Axon 4000B scanner (Axon Instruments). Virochip results were analyzed using E-Predict [##REF##16168085##28##] and vTaxi (K. Fischer et al., in preparation).</p>", "<title>PCR primers for detection of avian bornaviruses</title>", "<title>Microarray-based Bornaviridae PCR primers</title>", "<p>Initial PCR primers were generated based on two of the 70 mer microarray probes with hybridization signal in the <italic>Bornaviridae </italic>positive arrays that localize to positions 3676–3745 and 4201–4270 of the Bornaviridae reference sequence [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"NC_001607\">NC_001607</ext-link>]. Subsequences within each of these probes (BDV_LconsensusF: 5'-CCTCGCGAGGAGGAGACGCCTC-3' and BDV_LconsensusR: 5' CTGCTCTTGGCTGTGTCTGCTGC-3'; positions 3710–3729 and 4252–4230, respectively of the NCBI <italic>Bornaviridae </italic>reference sequence) that are 100% conserved across the 12 other fully sequenced bornavirus genome isolates in NCBI (huP2br [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AB258389\">AB258389</ext-link>], Bo/04w [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AB246670\">AB246670</ext-link>], No/98 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311524\">AJ311524</ext-link>], H1766 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311523\">AJ311523</ext-link>], He/80/FR [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311522\">AJ311522</ext-link>], V/FR [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311522\">AJ311522</ext-link>], virus rescue plasmid pBRT7-HrBDVc [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY05791\">AY05791</ext-link>], CRNP5 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114163\">AY114163</ext-link>], CRP3B [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114162\">AY114162</ext-link>], CRP3A [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114161\">AY114161</ext-link>], He/80 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"L27077\">L27077</ext-link>], and V [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"U040608\">U040608</ext-link>]) were utilized for initial follow-up PCR and sequence confirmation of microarray screening results. Briefly, 1 ul of the randomly amplified nucleic acid prepared for microarray hybridization from all specimens was utilized as template for 35 cycles of PCR, under the following conditions: 94°C, 30 seconds; 50°C, 30 seconds; 72°C, 30 seconds. Resulting PCR products were gel purified, subcloned into the TOPO TA cloning vector pCR2.1 (Invitrogen, USA, Carlsbad CA) and sequenced with M13F and M13R primers.</p>", "<title>Generation of ABV consensus PCR primers</title>", "<p>Sequences recovered from BDV_LconsensusF and BDV_LconsensusR PCR products were aligned, and an additional set of ABV consensus primers biased towards the ABV sequences were identified: ABV_LconsensusF, 5'-CGCCTCGGAAGGTGGTCGG-3' (maps to positions aligning with residues 3724–3742 of BDV reference genome) and ABV_LconsensusR, 5'-GGCAYCAYCKACTCTTRAYYGTRTCAGC-3' (maps to positions aligning with residues 4233–4257 of BDV reference genome). Using identical PCR cycling conditions as described above for the microarray-based <italic>Bornaviridae </italic>PCR assay, these ABV consensus primers were found to be &gt; 100X more sensitive for ABV detection compared to BDV_LconsensusF and BDV_LconsensusR primers, and were thus utilized to re-screen the initial set of PDD case and control samples provided for microarray analysis (no additional positives identified) and all subsequently provided samples. Two additional PCR primers in the N (ABV_NconsensusF: 5'-CCHCATGAGGCTATWGATTGGATTAACG-3' and ABV_NconsensusR: 5'-GCMCGGTAGCCNGCCATTGTDGG-3') and M (ABV_MconsensusF: 5'-GGRCAAGGTAATYGTYCCTGGATGGCC-3' and ABV_PconsensusR: 5'-CCAACACCAATGTTCCGAAGMCG-3') that mapped to conserved sequences shared between the complete ABV genome sequence and the 14 other fully sequenced BDV genomes in the NCBI database were also employed for PCR screening of PDD cases and controls.</p>", "<title>Ultra high-throughput sequencing</title>", "<title>Sample preparation and sequencing</title>", "<p>500 ng of total RNA derived from one of the PDD case specimens was linearly amplified via modification of the MesssageAmp aRNA kit (Applied Biosystems/Ambion, Austin, TX). To ensure the amplification of both mRNA and vRNA present in the specimen, T7-tailed random nonamer was mixed in an equimolar ratio with the manufacturer-provided T7-oligo(dT) primer during the 1^ststrand synthesis step. The resulting aRNA was next used as input for a modified version of Genomic DNA sample preparation protocol for ultra high-throughput Solexa sequencing (Illumina, Hayward, CA). 400 ng of the input aRNA was reverse-transcribed with reverse transcriptase (Clontech Laboratories, Inc., Mountain View, CA) using a random nonamer tailed with 19 bp of the Solexa Long (5'-CACGACGCTCTTCCGATCTNNNNNNNNN-3') primer sequence (Illumina, Hayward CA). Following termination of reaction, first strand cDNA products were purified from the reaction with Qiagen MinElute spin column (Qiagen USA, Valencia CA). To ensure stringent separation from primers, the MinElute eluate was then filtered through a Microcon YM30 centrifugal filter (Millipore Corp., Billerica, MA). The resulting eluate served as template for 2^ndstrand synthesis in a standard Sequenase 2.0 (USB, Cleveland, OH) reaction primed with a random nonamer tailed with 22 bp (5'-GGCATACGA GCTCTTCCGATCTNNNNNNNNN-3') of the Solexa Short primer sequence (Illumina, Hayward CA). Double-stranded DNA products were separated from primers and very short products through a second Qiagen MinElute spin column run followed by a Microcon YM50 centrifugal filter. This eluate was used as template for 10 cycles of PCR amplification with the full length Solexa L and S primers using KlenTaq LA DNA polymerase mix (Sigma-Aldrich, St. Louis, MO). PCR product was purified from the reaction with a MinElute spin column. Following cluster generation, Solexa sequencing primer was annealed to the flow cell, and 36 cycles of single base pair extensions were performed with image capture using a 1G Genome Analyzer (Illumina, Hayward, CA). The Solexa Pipeline software suite version 0.2.2.6 (Illumina, Hayward, CA) was utilized for base calling from these images. Using software default quality filters, cycles 4–36 were deemed high quality, resulting in a total of 1.4 million 33 mer reads for downstream sequence analyses.</p>", "<title>Identification of Bornaviridae reads</title>", "<p>Reads sharing 100% identity to each other or the Solexa amplification primers were filtered, reducing our initial set of 1.4 million reads to a working set of 600,000 unique reads. In order to quickly assess the homology of this set of reads to different sequence databases, we employed an iterative strategy using ELAND (<bold>E</bold>fficient <bold>L</bold>ocal <bold>A</bold>lignment of <bold>N</bold>ucleotide <bold>D</bold>ata) and BLAST analyses. To filter reads from our analysis potentially derived from psittacine host tissue, the working set of reads were aligned to a database of all <italic>Aves </italic>sequences from NCBI (n = 918,511) using ELAND, which tolerates no more than 2 base mismatches, and discards both low quality reads and reads with low sequence complexity. Reads that did not align to the <italic>Aves </italic>database by ELAND analysis were next re-aligned to the <italic>Aves </italic>database for high stringency blastn analysis (e = 10^-7, word size = 11), followed by progressively lower stringencies (down to e = 10-2, word size = 8), corresponding to reads containing only 22 nucleotide identities to sequences in the <italic>Aves </italic>database. To identify reads with some homology to <italic>Bornaviridae </italic>sequences in the resulting set of 322,790 host-filtered reads, we re-implemented the ELAND/iterative blastn analysis strategy (down to ≥ 15 nucleotides identity) using a database of all NCBI BDV sequences (n = 207) augmented by our previously recovered ABV sequences (n = 5). An additional iterative tblastx analysis was incorporated to capture distantly related reads that shared similarity to the known BDV sequences only at the level of predicted amino acid sequence (down to ≥ 6 amino acid identity).</p>", "<title>Complete ABV vRNA genome sequence recovery by RT-PCR</title>", "<title>Initial genome sequence recovery</title>", "<p>Sequences from 33 mer reads from the deep sequencing with a minimum of 91% sequence identity with known BDV sequences present in the NCBI database were utilized to generate a set of primers for additional cloning and sequence recovery by RT-PCR of both mRNA and vRNA present in the clinical specimen. In this manner, we generated a hybrid assembly derived from multiple overlapping clones and 5' RACE products encompassing the ABV genome sequence.</p>", "<title>vRNA genome sequence recovery</title>", "<p>To ensure recovery of accurate sequence across the ABV genome, especially at splice junctions and transcription initiation and termination sites, we utilized the sequence from ABV hybrid assembly to design primers for recovery of 3 overlapping products by RT-PCR directed against the vRNA present in the specimen. Aliquots of 500 ng of DNAse-treated total RNA extracted from the clinical specimen were annealed with 3 primers complementary to the predicted vRNA sequences: ABV1r, 5'-ATGACCAGGACGAGGAGATG-3' (maps to residues 8831-8812 of vRNA), ABV2r, 5'-CCTGTGAATGTCTCGTTTCTG-3' (maps to residues 5754-5733 of vRNA), and ABV3r 5-TTCTTTCAGCAACCACTGACG-3' (maps to residues 2563-2543 of vRNA). Reverse transcription was carried out at 50°C for 1 hr with SuperScriptIII (Invitrogen, Carlsbad CA) according to manufacturer's instructions. Following RNase H treatment, PCR was performed on the resulting cDNA with Phusion polymerase (NEB, Ipswich, MA) with the primers used for reverse transcription and the following primers: ABV1f: 5'-GGATCATTCCTTGATGATGTATTAGC-3', (maps to residues 5567-5589) ABV2f: 5'-CAAATGGAGAGCCTGATTGG-3' (maps to residues 2378-2397) ABV3f: 5'-AATCGGTAAGTCCAGAGTCAAGG-3' (maps to residues 155-177). All products were amplified for 35 cycles under the following conditions: 98°C, 3 minutes; 98°C, 10 seconds, 50°C, 30 seconds, 72°C 3 minutes. Resulting products were gel purified, and subcloned into the TOPO T/A cloning vector pCR2.1 after incubation with Taq polymerase and dATP for 10 minutes at 72°C. For each product, 4 independent transformants were prepared for standard dideoxy sequencing on an ABI3730 sequencer (ElimBio, Hayward CA). Forward and reverse reads spanning each clone were generated using M13F and M13R and additional overlapping primers spaced at 600–800 bp intervals across the each of the clones.</p>", "<title>5' and 3' RACE to sequence at vRNA termini</title>", "<p>vRNA RT-PCR products containing uncapped vRNA termini were captured using the First Choice RLM RACE kit (Ambion, Austin TX) with the following modifications to the standard protocol: 1) tobacco acid phosphotase treatment was omitted, 2) a phosphorylated RNA, RNAligate, 5'-p-GUUAUCACUUUCACCC-3' (gift of J. Shock, DeRisi lab) was substituted for the 3' RNA ligation-mediated RACE primer provided in the kit and ligated to 3' ends as per manufacterer's 5' RACE protocol, and 3) in the 3' RACE reverse transcription reactions, two reverse transcription reactions were performed and carried forward in parallel: one with random decamers and one with a DNA oligo complementary to oJSmer utilized in the RNA ligation step (ligateRC, 5'-p-GGGTGAAAGTGATAAC-3'). For 5' RACE, a single round of PCR was sufficient to generate a product using the vRNA specific primer ABV5RaceOuter, 5'-CAGTCGGTTCTTGGACTTGAAGTATCTAGG-3' (maps to residues 346-317 of vRNA) and manufacturer provided outer PCR primer. For 3' RACE, nested PCR was required to recover detectable PCR product of expected size using outer PCR primers oJSmerRC and the gene specific primer ABV3RaceOuter, 5'-CCCGTCTACTGTTCTTTCGCCG-3' (maps to residues 8479-8497 of vRNA), followed by inner PCR using Tailed_RNAligateRC, 5'-AAGCAGTGGTAACAACGCAGAGTACGGGTGAAAGTGATAAC-3' and the gene specific primer, ABV3RaceInner, 5'-GCAATCCAGGAATAAGCAAGCACAAA-3' (maps to residues 8595-8620 of vRNA). Both of the RACE PCR reactions were carried out with Platinum Taq polymerase (Invitrogen, Carlsbad, CA) in 35 cycles of gradient PCR (with varying annealing temperature): 94°C, 30 seconds; 55–58°C, 30 seconds; 72°C, 30 seconds. Resulting PCR products were gel purified and subcloned into TOPO T/A cloning vector pCR 4.0. For the 5' RACE products, 7 independent transformants from 3 independently generated PCR products were subcloned and sequenced with M13F and M13R primers. For the 3' RACE products, 6 independent transformants from 4 independently generated PCR products were subcloned and sequenced with M13F and M13R primers. Terminal sequences reported here reflect the majority consensus sequence obtained from these reads.</p>", "<title>Genome sequence assembly</title>", "<p>Genome sequence assemblies from both initial genome sequence recovery and vRNA genome sequence recovery were generated using Consed, version 16.0 software [##REF##9521923##29##]. All bases from the resulting vRNA genome sequence assembly are covered at least 4× with a minimum Phred value of 20.</p>", "<title>Blinded PCR screening of additional PDD cases and controls</title>", "<p>Beyond the initial set of 16 specimens provided for microarray analysis, specimens from a total of 38 additional PDD cases, PDD controls, and PDD suspicious birds with varied clinical histories were provided to us blinded by our 2 collaborators (see Additional file ##SUPPL##4##5##: Summary of clinical and molecular data for specimens provided in this study).</p>", "<title>Sample processing</title>", "<p>For specimens provided in tissue form from the US collaborators, total RNA was extracted as described above with RNABee, DNase treated, then reverse-transcribed and PCR-amplified according to our random amplification protocol for microarray sample preparation (Materials and Methods). Specimens provided from Israel in the form of extracted RNA were similarly DNAse-treated and amplified prior to PCR screening.</p>", "<title>PCR screening</title>", "<p>1 ul of the randomly amplified material generated from these RNA samples was used as input template for ABV consensus PCRs as described above. In parallel, as an independent control for input specimen RNA integrity, PCR for glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA was performed on all specimens using designed based on Friedman-Einat et al [##REF##10480986##30##] and <italic>Gallu gallus </italic>GAPDH sequence: Gg_GAPDHf: 5'-AGTCATCCCTGAGCTSAAYGG*GAAGC-3' (bp708-733 in Gallus gallus cDNA (NCBI accession NM_204305), * indicates the junction of GAPDH exon 8 and 9 spanned by this primer), Gg_GAPDHr 5'-ACCATCAAGTCCACAACACGG-3' (Spans bp 1037-1017 in Gallus gallus GAPDH cDNA (NCBI accession NM_204305), maps to GAPDH exon 12). After PCR results were tallied, clinical information on all specimens tested was unmasked. A complete accounting of ABV, GAPDH PCR results, specimen type and clinical status is provided in Additional file ##SUPPL##4##5##: Summary of clinical and molecular data for specimens provided in this study.</p>", "<title>Sample inclusion for association analysis</title>", "<p>To reduce potential confounding due to differences in viral detection resulting from specimen tissue source, only specimens derived from upper GI tract tissue (crop, proventriculus/ventriculus) that tested positive by GAPDH mRNA PCR were included in association analysis presented in Table ##TAB##2##3##. This consisted of a total of 21 specimens, 7 of which were derived from histologically confirmed PDD cases and 14 derived from histologically negative control specimens.</p>", "<title>Samples excluded from association analysis</title>", "<p>The remaining 17 samples were excluded from the analysis because they were either 1) GAPDH-positive or GAPDH-negative samples derived from specimen other than upper GI tract tissue (GI content, brain, liver, or intestine) or 2) derived from cases that were histologically or clinically 'suspicious', but unconfirmed PDD cases. Six additional ABV PCR positives were identified among this set of samples excluded from the statistical analyses: 1 derived from GI content from a confirmed PDD case, and 5 derived from a variety of tissues from the PDD suspicious cases.</p>", "<title>Phylogenetic and comparative sequence analysis</title>", "<p>Multiple sequence alignments of complete genome sequences or partial sequences derived from PCR screening studies were generated with ClustalW [##REF##7984417##31##] version 1.83. Resulting alignments were used for scanning pairwise sequence analysis (window size, 100; step size 1 nucleotide steps). Additional ClustalW alignments and neighbor-joining phylogenetic trees were generated using Mega software, version 4.0.2 [##REF##17488738##32##].</p>" ]

[ "<title>Results</title>", "<title>Microarray-based detection of a Bornaviridae signature in PDD cases</title>", "<p>To identify a possible viral cause of PDD, we applied the Virus chip, a DNA microarray containing 70 mer oligonucleotide probes representing all known viral sequences conserved at multiple nodes of the viral taxonomic tree [##REF##17494722##17##,##REF##16983602##18##] to identify viral signatures unique to histologically confirmed cases of PDD. At the outset of this study, specimens from two independently collected PDD case/control series were available for this investigation (Figure ##FIG##0##1##, Materials and Methods). The first series (n = 8), from samples originating in the United States, consisted of crop biopsy specimens from 3 histologically confirmed PDD cases and 5 controls that were provided for nucleic acid extraction and follow-up Virus chip analysis. The samples from the second series (n = 8) originated in Israel, where total RNA and DNA from proventriculus, ventriculus and brain specimens were extracted from 5 PDD cases and 3 controls. For each series, total RNA was reverse-transcribed with random primers, PCR-amplified, and fluorescently labeled and hybridized to the Virus chip microarray as previously described [##REF##16983602##18##].</p>", "<p>In these combined PDD case/control series, a <italic>Bornaviridae </italic>signature was detectable in 62.5% of the cases and none of the controls (Table ##TAB##0##1##). In the US cohort, which contained only GI tract specimens, we detected a bornavirus in 2 of 3 cases. Surprisingly, in samples from the Israeli PDD case/control series for which we had both GI tract and brain specimen RNA for each animal, we detected the <italic>Bornaviridae </italic>signature in 3 of the cases, but only in samples derived from brain tissue. These signatures were unambiguously confirmed by follow-up PCR and sequence recovery, using primers based on the sequences of the most strongly annealing <italic>Bornaviridae </italic>oligonucleotides on the microarray (Figure ##FIG##1##2##, Array probes and PCR probes tracks). These analyses revealed the presence of a set of surprisingly divergent avian bornaviruses (ABVs) in the PDD cases; the recovered sequences shared less than 70% sequence identity to any of the previously identified mammalian bornavirus isolates in the NCBI database.</p>", "<title>Recovery of complete genome sequence of a divergent avian bornavirus (ABV) from a PDD case via ultra high-throughput sequencing and conventional RT-PCR</title>", "<p>To determine if the sequence fragments we detected among specimens derived from PDD cases corresponded to the presence of a full-length bornavirus, we performed unbiased deep sequencing on a PCR-confirmed bornavirus positive PDD case that contained the highest concentration of RNA. To recover both mRNA and vRNA present in the sample, RNA from this specimen was linearly amplified with both oligo(dT) and random hexamer primers, and then PCR-amplified using a modified random amplification strategy compatible with the Solexa sequencing platform (Materials and Methods). An initial set of 1.4 million 33 mer reads was obtained from this template material. Filtering on read quality, insert presence, and sequence complexity reduced this data set to 600,000 unique reads. Additional ELAND and iterative BLAST analyses ([##REF##9254694##19##] Materials and Methods) of these reads against all avian sequences in NCBI (including ESTs, n = 918,511) identified reads in the dataset with at least 22 nucleotides of sequence identity likely derived from host transcripts randomly amplified during sequencing sample preparation. The 322,790 reads that passed this host filter were next screened for the presence of bornavirus sequence through similar ELAND and iterative BLAST analyses (Materials and Methods) using a database generated from all Borna Disease virus (BDV) sequences present in NCBI (n = 207) and the sequences we had recovered from PCR follow-up of the PDD samples that tested positive for bornavirus by Virus chip microarray (n = 5). These analyses provided us with 1400 reads with at least a match of 15 or more nucleotides (blastn) or 7 or more predicted amino acids (tblastx) to known BDV sequences.</p>", "<p>Mapping these 1400 reads onto their corresponding positions on a consensus sequence for the 14 publicly available BDV genome sequences revealed spikes of high read coverage distributed discontinuously across the entire span of the BDV genome consensus. Reads containing blastn scores ≥ 90% identity to known BDV sequences were used as source sequences for primer design for PCR and sequence recovery of additional bornavirus sequence from both mRNA and vRNA templates present in the PDD specimen. Sequences recovered in this manner facilitated subsequent primer design for recovery of complete genome sequence via RT-PCR of 3 large overlapping fragments of the genome and 5'- and 3'-RACE (Figure ##FIG##1##2A##, vRNA RT-PCR track) directly from negative stranded vRNA present in the total RNA extracted from this clinical specimen.</p>", "<p>As our initial PCR results suggested, the bornavirus genome sequence we recovered is quite diverged from all known BDV genomes, including the BDV isolate No/98, a divergent isolate sharing only 81% sequence identity with all other BDV genomes [##REF##10823873##20##]. Overall, this newly recovered bornavirus genome sequence shares only 64% sequence identity at the nucleotide level to each of the complete BDV genomes. Scanning pairwise sequence identity analysis indicates this genetic divergence exists across the entire genome (Figure ##FIG##1##2A##, Sequence identity shared with BDV genomes track). Given this divergence, we re-examined the depth and distribution of the 322,790 reads from this specimen that passed the host filter to determine if we had missed reads derived from the recovered ABV in our initial screen against all BDV sequences. Not surprisingly, this retrospective BLAST analysis revealed an additional 2600 reads from across the recovered bornavirus genome that were missed in the initial BLAST analyses due to the lack of sequence conservation between the ABV sequence and the available BDV sequences (Figure ##FIG##1##2A##, Solexa reads track). In total, approximately 1% of all the high throughput shotgun reads could be mapped to the recovered bornavirus genome.</p>", "<p>Despite this sequence divergence, this avian bornavirus genomic sequence possesses all of the hallmarks of a <italic>Bornaviridae </italic>family member (Figure ##FIG##1##2A##): six distinct ORFs encoding homologs of the N, X, P, M, G, and L genes are detectable. Likewise, non-coding regulatory sequence elements (the inverted terminal repeat sequences ([##REF##15728364##21##], see Additional file ##SUPPL##0##1##: Alignment of bornavirus genomes 5' and 3' termini), the transcription initiation and termination sites ([##REF##8083989##22##], see Additional file ##SUPPL##1##2##: Alignment of transcription initiation and termination sites in bornavirus genomes), and each of the signals for pre-mRNA splicing ([##REF##8035500##23##], see Additional file ##SUPPL##2##3##: Alignment of splice donor and acceptor sequences in bornavirus genomes) are all conserved in sequence and location, with the exception of the splice acceptor site 3 at position 4560 that has been previously found in a subset, but not all BDV genomes [##REF##11172106##24##,##REF##11070091##25##]. Taken together, these data provide evidence that our analysis has uncovered a novel divergent avian bornavirus (ABV) present in cases of PDD.</p>", "<p>Phylogenetic and pairwise sequence analyses support this conclusion. Genomic and sub-genomic phylogenetic analyses of nucleotide sequences place the recovered ABV sequence on a branch distant from representative members of the 4 distinct genetic isolates of BDV for which complete genome sequences are available (Figure ##FIG##1##2B##, see Additional file ##SUPPL##3##4##: Phylogenetic relationships between sub-genomic loci of ABV and representative BDV genomes). Strikingly, the ABV genome sequence segregates to a position virtually equidistant from both the set of 3 closely related BDV isolates (V/Ref, H1766, and He/80) and the divergent No/98 BDV isolate (Figure ##FIG##1##2B##). Moreover, in contrast to the previously identified divergent No/98 isolate, which retains a high level of conservation with other BDV isolates at the amino acid level, the ABV isolate also shows significant sequence divergence in the predicted amino acid sequence of every ORF in the genome (Table ##TAB##1##2##).</p>", "<title>PCR screening of additional PDD cases and controls suggests an association between the presence of ABV and PDD</title>", "<p>Recovery of the complete ABV genome sequence confirmed that the microarray hybridization signature we detected accurately reflected the presence of bornaviruses in our PDD specimens. With these results in hand, we designed a set of PCR primers to perform ABV-specific PCR screening of an independent set of PDD case and control specimens to investigate the association between the presence of ABV and clinical signs and symptoms of PDD. An additional set of 21 samples derived from upper GI tract specimens (crop, proventriculus or ventriculus) from PDD cases and controls were screened for ABV sequences in a blinded fashion (Materials and Methods). For this analysis, we targeted three regions of the genome: 1) the L gene region of the genome that we used for PCR confirmation of the microarray results, (Figure ##FIG##1##2##, PCR probes track), 2) a subregion within the N gene and 3) a subregion within the M gene (Materials and Methods). PCR for glyceraldehyde 3 phosphate dehydrogenase (GAPDH) mRNA was performed in parallel with the ABV PCR on all specimens to control for integrity of RNA provided from each specimen. Of the 21 specimens analyzed, 5 were positive for ABV by PCR and confirmed by sequence recovery. Unmasking the clinical status of these samples revealed that 7 of the samples were derived from confirmed PDD cases and 14 samples were derived from PDD controls. Among the PDD cases, we found 71% (5/7) to be positive by ABV PCR (Table ##TAB##2##3##). In contrast, all PDD controls were negative by ABV PCR, and positive only for GAPDH mRNA. This PCR analysis provides an independent test of the statistical significance of the association between the presence of ABV and histologically confirmed PDD (P = 0.01, Fisher's Exact Test). Although we do not observe ABV in 100% of PDD cases in this series (see Discussion), our results nonetheless indicate a significant association of ABV with PDD.</p>", "<title>Additional ABV isolates identified through PCR screening</title>", "<p>Because we applied stringent inclusion criteria for the above-described association analysis study, a number of ABV (+) and ABV (-) samples were excluded. From these materials, six additional ABV isolates were detected – 5 derived from cases considered clinically suspicious and a sixth isolate derived from a confirmed PDD case for which only GI content and liver specimens were available. Additional PCR screening of a set of 12 PDD control crop biopsy specimens provided to us unblinded again yielded solely ABV PCR (-) and GAPDH (+) results. These samples were excluded from the association analysis because we knew their clinical status prior to screening. We note that inclusion of these samples in statistical analyses would not diminish the association of ABV with known or suspected PDD.</p>", "<title>Sequence analysis of ABV isolates indicates at least 5 divergent isolates in this branch of the Bornaviridae family</title>", "<p>Recovery of partial sequence from additional isolates of ABV (from the above PDD case/control specimens as well as an additional samples derived from known or suspected PDD cases (Materials and Methods)) from 3 distinct regions of the ABV genome provided the opportunity to further investigate the genetic diversity within this new branch of the <italic>Bornaviridae</italic>. Here, our description of results is restricted to comparison with representative members of the 4 major isolates of BDV, but virtually identical results were obtained when all available BDV sequences were analyzed.</p>", "<p>As we observed for the complete ABV genome sequence, phylogenetic analysis of the recovered subgenomic ABV sequences revealed that each of the ABV isolates we recovered resides on a branch distant from the BDV isolates (Figure ##FIG##2##3##). PCR with the L gene consensus primers detected 14 isolates corresponding to 4 genetic subgroups of ABV. Each of these isolates were also detected with at least one of primer sets corresponding to the more highly expressed N gene and more conserved M gene regions of the genome; however, PCR with these two additional primer sets identified 2 additional ABV isolates that segregate to a genetically distinct 5^thsubgroup among the ABVs (ABV5, Figure ##FIG##2##3B## and ##FIG##2##3C##). Although these 5 distinct branches correlate largely according to the geographic origin of the isolates, the genetic diversity we detect cannot be ascribed solely to differences in geographic origin of the isolates, since one of the branches (ABV4) is comprised of isolates derived from both the U.S. and Israel. Likewise, we did not detect an obvious correlation between host species and genetic subgroup of ABV among the recovered isolates.</p>", "<p>Pairwise sequence analyses of the nucleotide and predicted amino acid sequence from the L region of the genome provide additional evidence for surprising genetic diversity among the ABV branches compared to that seen among the BDV branches (Table ##TAB##3##4##). Although derived from coding sequences of one of the more divergent genes of the bornavirus genome (Table ##TAB##1##2##, L gene), the region of the L gene we have used for PCR screening is relatively conserved among the BDV isolates, ranging from 81–98% at the nucleotide level, and 96–99% at the amino acid level (Table ##TAB##3##4##). In contrast, the sequence identity shared across this region of the genome among the ABV branches of the tree ranges from 77–83% at the nucleotide level and 86–94% at the amino acid level. Taken together with the phylogenetic analysis described above, these data provide evidence that these ABV isolates form a new, genetically diverse branch of the <italic>Bornaviridae </italic>phylogeny that is significantly diverged from the founder BDV isolates.</p>" ]

[ "<title>Discussion</title>", "<p>It has been almost 40 years since the first description of PDD. Although a viral etiology has long been suspected, a convincing lead for a responsible viral pathogen has been lacking. By combining veterinary clinical investigation with genomics and molecular biology, we have identified a genetically diverse set of novel avian bornaviruses (ABVs) that are likely to play a significant role in this disease. Through microarray analysis and follow-up PCR, we detected ABV sequences in 62.5% of the PDD cases in a set of specimens from two carefully collected PDD case/control series originating from two different continents. We confirmed that these assays faithfully reflect the presence of full-length bornavirus in ABV PCR positive specimens through cloning of the complete ABV vRNA sequence directly from RNA extracted from one of these ABV PCR positive PDD case specimens. We next found evidence for a significant association between the presence of ABV and clinically confirmed PDD in follow-up blinded PCR screening of a set of additional PDD cases and controls, with ABV was detected in 71% of PDD cases and none of the controls (P = 0.01, Fisher's Exact Test).</p>", "<p>Almost all prior sightings of bornaviruses in nature have been among mammals, and the mammalian isolates have been remarkably homogeneous at the sequence level (Table ##TAB##1##2## and [##REF##16469519##15##]). The latter is a surprising feature for RNA viruses, whose RNA-dependent RNA polymerases typically have high error rates. By contrast, the ABV isolates reported here are quite diverged from their mammalian counterparts, and show substantial heterogeneity among themselves. We note with interest that a single earlier report suggesting a potential avian reservoir for bornaviruses has been presented [##REF##11561971##26##]. In that study, RT-PCR based on mammalian BDV sequences was used to recover partial sequences from stool collected near duck ponds where wild waterfowl congregate. However, the resulting sequences shared ca. 98% amino acid sequence homology to the mammalian BDVs, raising the possibility that these putative avian sequences might have resulted from possible environmental or laboratory contamination [##REF##16469519##15##]. Our ABV isolates, which are unequivocally of avian origin, are clearly very different from these sequences; it remains to be seen if other wild birds can indeed harbor BDV-like agents. The expanded sequence diversity of the bornaviruses discovered here should facilitate design of PCR primers that will enable expanded detection of diverse bornaviral types in future epidemiological studies.</p>", "<p>The known neurotropism of bornaviruses makes them attractive and biologically plausible candidate etiologic agents in PDD, since (i) PDD cases have well-described neurological symptoms such as ataxia, proproceptive defects and motor abnormalities; and (ii) the central GI tract pathology in the disorder results from inflammation and destruction of the myenteric ganglia that control peristaltic activity. However, despite our success in ABV detection in PDD, we did not observe ABV in every PDD case analyzed. There are several possible explanations for this result. First, we do not know the tissue distribution (tropism) of ABV infection, or how viral copy number may vary at different sites as a function of the stage of the disease. By weighting our sample collection towards clinically overt PDD, we may have biased specimen accrual towards advanced disease. At this stage, where destruction of myenteric ganglial elements is often extensive, loss of infected cells may have contributed to detection difficulties (We note with interest in this context that in one of our case collections from Israel, virus detection occurred preferentially in CNS rather than in GI specimens). There are many precedents for such temporal variation in clinical virology – for example, in chronic hepatitis B viral loads typically decline by several orders of magnitude over the long natural history of the infection [##REF##15014185##27##]. It is also possible that our detection rate may merely reflect suboptimal selection of PCR primers employed for screening; after all, our consensus primer selection was based on sequences we had recovered (L gene consensus primers) or sequence homology between the first fully sequenced ABV genome we recovered and a set of highly related mammalian BDV genome sequences (N and M gene consensus primers). We now recognize that there is substantial sequence variation within the ABVs (see Fig. ##FIG##2##3##); as more sequence diversity is recognized, better choices for more highly conserved primers will become apparent and could impact upon these prevalence estimates.</p>", "<p>Finally, there could actually be multiple etiologic agents in PDD, with ABV infection accounting for only ~70% of the cases. Certainly both human and veterinary medicine are replete with examples of multiple agents that can trigger the same clinical syndrome – for example, at least 5 genetically unrelated viruses (hepatitis viruses A-E) are associated with acute hepatitis, and at least 3 of these can be implicated in chronic liver injury; similarly, several agents (RSV, rhinoviruses and occasionally influenza viruses) are implicated in bronchiolitis. To investigate this possibility, further high-throughput sequencing analysis of PDD cases that were negative for bornaviruses by PCR screening is currently underway.</p>", "<p>Although ABV is clearly a leading candidate etiologic agent in PDD, formally establishing a causal role for ABV in PDD will require further experimentation. Such experiments could include (i) attempts to satisfy Koch's postulates via cultivation of ABV, followed by experimental transmission of infection and disease in inoculees, (ii) examination of seroprevalence rates in flocks with high and low PDD incidences, (iii) documentation of seroconversion accompanying development of PDD-like illnesses and (iv) examination of PDD cases by immunohistochemistry or in situ hybridization for evidence of colocalization of ABV infection at sites of histopathology. The recovery and characterization of a complete ABV genome and multiple isolates from this diverse new branch of the <italic>Bornaviridae </italic>family now opens the door to such investigations.</p>" ]

[ "<title>Conclusion</title>", "<p>By combining clinical veterinary medical investigation with comprehensive pan-viral microarray and high throughput sequence analyses, we have identified a highly diverged set of avian bornaviruses directly from tissues of PDD cases, but not controls. These results are significant for a number of reasons. First, they provide a compelling lead in the long-standing search for a viral etiology of PDD, and pave the way for further investigations to assess the link between ABV and PDD. Second, these results also unambiguously demonstrate the existence of an avian reservoir of bornaviruses, expanding our understanding of the bornavirus host range. Finally, these results also provide the first evidence that the <italic>Bornaviridae </italic>family is not confined to a set of genetically homogeneous species as was previously thought, but actually encompasses a set of heretofore unanticipated genetically diverse viral species.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Proventricular dilatation disease (PDD) is a fatal disorder threatening domesticated and wild psittacine birds worldwide. It is characterized by lymphoplasmacytic infiltration of the ganglia of the central and peripheral nervous system, leading to central nervous system disorders as well as disordered enteric motility and associated wasting. For almost 40 years, a viral etiology for PDD has been suspected, but to date no candidate etiologic agent has been reproducibly linked to the disease.</p>", "<title>Results</title>", "<p>Analysis of 2 PDD case-control series collected independently on different continents using a pan-viral microarray revealed a bornavirus hybridization signature in 62.5% of the PDD cases (5/8) and none of the controls (0/8). Ultra high throughput sequencing was utilized to recover the complete viral genome sequence from one of the virus-positive PDD cases. This revealed a bornavirus-like genome organization for this agent with a high degree of sequence divergence from all prior bornavirus isolates. We propose the name avian bornavirus (ABV) for this agent. Further specific ABV PCR analysis of an additional set of independently collected PDD cases and controls yielded a significant difference in ABV detection rate among PDD cases (71%, n = 7) compared to controls (0%, n = 14) (P = 0.01; Fisher's Exact Test). Partial sequence analysis of a total of 16 ABV isolates we have now recovered from these and an additional set of cases reveals at least 5 distinct ABV genetic subgroups.</p>", "<title>Conclusion</title>", "<p>These studies clearly demonstrate the existence of an avian reservoir of remarkably diverse bornaviruses and provide a compelling candidate in the search for an etiologic agent of PDD.</p>" ]

[ "<title>List of abbreviations</title>", "<p>ABV: Avian bornavirus; BDV: Borna diseae virus; PDD: Proventricular dilatation disease.</p>", "<title>Competing interests</title>", "<p>Sequence information obtained here has been disclosed for patenting purposes. ALK, AG, SC, PS-C, KF, KS, CYC, AL, AG, SKB, DG, and JLD were all party to this disclosure in conjunction with UCSF Office of Technology Management.</p>", "<title>Authors' contributions</title>", "<p>ALK participated in the conception, design, and coordination of the study, performed specimen extraction of specimens from Florida case/control study, array analyses for both sets of PDD case/control series, follow-up PCR screening and sequencing of samples and wrote the manuscript, AG orchestrated and collected the PDD case/control specimens from Israel and coordinated the clinical and histopathology analyses, and nucleic acid extraction for samples from Israel, and participated in revising the manuscript, SC orchestrated and collected the Florida PDD case/control specimens and oversaw the clinical and histopathologic analyses of these samples from Florida, and participated in revising the manuscript, PS-C carried out filtering and iterative BLAST analysis of ultra high throughput sequence data for ABV genome sequence recovery, participated in primer design and complete genome sequence recovery, and drafting the manuscript, KF participated in array analysis, developed pipeline for ultra high throughput sequence analysis, and participated in design of filtering and iterative BLAST analysis, KS performed modified library preparation for ultra high throughput sequencing and participated in revising the manuscript, CYC performed ultra high throughput sequencing and participated in revising the manuscript, AL, SM, and YF participated in clinical evaluation, specimen collection and extraction of samples from Israel, AG participated in extraction of specimens from Florida and follow-up microarray analysis and high throughput sequencing, CCW developed additional primers for PCR follow-up studies, SBK assisted in the selection of the PDD case/control specimens from Florida and participated in review of clinical and histological status of cases and controls included in the study, DG and JLD oversaw the overall conception and design of the project and supervised all phases of its execution and the drafting and revision of the manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>Jenny Shock (DeRisi lab, UCSF) for providing RNA oligos for 3' RACE experiments; Prof. Shmuel Perl, head of the Division of Pathology (KVI), for allowing us access to the KVI histopathology specimen collection; Dr. Asaf Berkovich (KVI) for assistance with specimen preparation and retrieval, Dr. Uri Bendheim, Dr. Revital Harari, and Dr. Anthony Poutous for submitting case material from their practices; and the Lahser Interspecies Research Foundation for providing funding for US specimen collection and veterinary care. The remainder of this work was supported by HHMI grants to JLD and DG.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Clinical presentation of proventricular dilatation disease (PDD) cases and controls</bold>. A. Necropsy view of control (left panel) African gray parrot (<italic>Psittacus erithacus</italic>) that died of other causes. The normal-sized proventriculus is not visible in this view as it lies under the left liver lobe (L). Necropsy view of a great green macaw (<italic>Ara ambiguus</italic>) with PDD (right panel). The proventriculus (PV) is markedly distended and extends laterally well beyond the left lobe of L. The heart (H) is marked for orientation. B. Contrast fluoroscopy view of control (left panel) African gray parrot (<italic>Psittacus erithacus</italic>) 1.5 hours after administration of barium sulfate. The kidney (K) is marked for orientation. The outline of both the PV and V is clearly visible, with normal size and shape. Within the intestinal loops (IL), wider and thinner sections represent active peristalsis. Right panel, representative PDD case, Eclectus parrot (<italic>Eclectus roratus</italic>) 18 hours after administration of barium. The PV is markedly distended and contains most of the contrast material, with less in the V and within the IL. A large filling defect (*) representing impacted food material. The kidney (K) is shown for orientation. These findings are typical for PDD; however PDD was not confirmed by histology in this case. C. Proventriculus histopathology. Hematoxylin and eosin staining of proventriculus histological sections from a blue and yellow macaw (<italic>Ara ararauna</italic>) with PDD. Proventricular gland (G) is shown for orientation. Left panel, normal appearing myenteric ganglion detected within the proventriculus of this case (arrow); right panel, marked lymphoplasmacytic infiltration present within a myenteric ganglion (arrows). Right panel inset, higher magnification. D. CNS histopathology. Hematoxylin and eosin staining of a cerebral section from a control (left panel) African gray parrot (<italic>Psittacus erithacus</italic>) that died of other causes. Right panel, African gray parrot (<italic>Psittacus erithacus</italic>) with PDD. Perivascular cuffing is evident around blood vessels (arrows). Inset, higher magnification.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Avian bornavirus (ABV) genome sequence recovery and comparative analysis to Borna disease virus (BDV) genomes</bold>. A. <italic>Bornaviridae </italic>genome schematic. Grey bar at base, non-segmented negative sense viral RNA (vRNA) of <italic>Bornaviridae </italic>genome; coordinates of major sequence landmarks highlighted below. Green bars and dashed lines, transcription initiation sites (TISs); red bars, transcription termination sites. Distinct ORF-encoding transcription products and the gene products they encode are diagrammed above: TIS1 transcripts encoding nucleocapsid (N) gene, pink; TIS2 transcripts encoding phosphoprotein (P) and X genes, green; TIS3 transcripts encoding the matrix (M), glycoprotein (G) and polymerase (large or 'L') gene, blue. Exons, thick solid black lines; introns, thin solid black lines; dashed black lines, 3'ends of transcripts generated transcription termination read-through; shaded boxes, location of ORFs in transcripts; reading frames for ORFs from multiple genes generated from TIS3 indicated at right. Array probes track, <italic>Bornaviridae </italic>oligonucleotide 70 mer probes from the Virochip array. PCR primers track, primers generated for PCR follow up and screening of specimens in this study for detection of <italic>Bornaviridae </italic>species with expected product diagrammed below. vRNA RT-PCR track, overlapping vRNA clones and RACE products recovered directly from RNA extracted from crop tissue of a histologically confirmed case of PDD. Solexa reads track shows distribution of 33 mer reads with at least 15 bp sequence identity to recovered ABV genome sequence. Sequence identity with BDV genomes track shows scanning average pairwise nucleotide sequence identity (window size of 100 nucleotides, advanced in single nucleotide steps) shared between ABV and all BDV genome sequences in NCBI. A dashed line on the graph indicates 50% identity threshold for reference. B. Phylogenetic analysis of ABV genome and the 4 representative BDV genome isolates. Neighbor-joining phylogenetic trees based on nucleotide sequences of the ABV genome sequence [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781967\">EU781967</ext-link>] and the following representative BDV genome sequences: H1766 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311523\">AJ311523</ext-link>], V/Ref [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"NC_001607\">NC_001607</ext-link>], He/80 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"L27077\">L27077</ext-link>], and No/98 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311524\">AJ311524</ext-link>)] Scale bar, genetic distance.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Comparison of sequences recovered from ABV PCR screening to 4 representative genetic isolates of BDV</bold>. Neighbor-joining Phylogenetic tree of ABV nucleotide sequences recovered by PCR screening with ABV consensus primers for subsequences within the L gene (A), the M gene (B), or the N gene (C).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>ABV detection in PDD</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">cases^a</td><td align=\"center\">controls^b</td><td align=\"center\">totals</td></tr></thead><tbody><tr><td align=\"left\">Virochip⁺</td><td align=\"center\">5</td><td align=\"center\">0</td><td align=\"center\">5</td></tr><tr><td align=\"left\">Virochip^-</td><td align=\"center\">3</td><td align=\"center\">8</td><td align=\"center\">11</td></tr><tr><td align=\"left\">totals</td><td align=\"center\">8</td><td align=\"center\">8</td><td align=\"center\">16</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Predicted amino acid sequence similarity between ABV, the divergent BDV-No/98 and other BDV genomes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"4\"><bold>Average % pairwise amino acid identity (min, max)*:</bold></td></tr></thead><tbody><tr><td align=\"left\">Genome locus</td><td align=\"center\"><italic>ABV and BDV</italic></td><td align=\"center\"><italic>ABV and No/98</italic></td><td align=\"center\"><italic>BDVs</italic></td><td align=\"center\"><italic>No/98 and BDV</italic></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">N (nucleocapsid)</td><td align=\"center\">72.5 (72.5, 73.0)</td><td align=\"center\">72.0</td><td align=\"center\">98.9 (97.3, 100)</td><td align=\"center\">97.0</td></tr><tr><td align=\"left\">X (p10 protein)</td><td align=\"center\">40.7 (40.0, 41.0)</td><td align=\"center\">45.0</td><td align=\"center\">96.9 (96.2, 97.8)</td><td align=\"center\">80.6 (80.0, 81.0)</td></tr><tr><td align=\"left\">P (phosphoprotein)</td><td align=\"center\">59.9 (59.0, 61.0)</td><td align=\"center\">61.0</td><td align=\"center\">98.9 (98.6, 99.2)</td><td align=\"center\">96.8 (96.0. 97.0)</td></tr><tr><td align=\"left\">M (matrix)</td><td align=\"center\">84.0</td><td align=\"center\">84.0</td><td align=\"center\">98.2 (97.7, 99.4)</td><td align=\"center\">98.4 (98.0, 99.0)</td></tr><tr><td align=\"left\">G (glycoprotein)</td><td align=\"center\">65.8 (65.0, 66.0)</td><td align=\"center\">66.0</td><td align=\"center\">98.4 (96.3, 98.9)</td><td align=\"center\">93.4 (93.0, 94.0)</td></tr><tr><td align=\"left\">L (polymerase)</td><td align=\"center\">68.0</td><td align=\"center\">68.0</td><td align=\"center\">98.8 (98.6, 99.0)</td><td align=\"center\">93.0</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Analysis of significance of ABV detection rate in PDD</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">cases</td><td align=\"center\">controls</td><td align=\"center\">totals</td></tr></thead><tbody><tr><td align=\"left\">ABV PCR⁺</td><td align=\"center\">5</td><td align=\"center\">0</td><td align=\"center\">5</td></tr><tr><td align=\"left\">ABV PCR^-</td><td align=\"center\">2</td><td align=\"center\">14</td><td align=\"center\">16</td></tr><tr><td align=\"left\">totals</td><td align=\"center\">7</td><td align=\"center\">14</td><td align=\"center\">21</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Average pairwise sequence identity shared between ABV and BDV isolates*</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">ABV1</td><td align=\"center\">ABV2</td><td align=\"center\">ABV3</td><td align=\"center\">ABV4</td><td align=\"center\">Ref/V</td><td align=\"center\">H1766</td><td align=\"center\">He/80</td><td align=\"center\">No/98</td></tr></thead><tbody><tr><td align=\"left\">ABV1</td><td align=\"center\">100</td><td align=\"center\"><bold>77</bold></td><td align=\"center\"><bold>79</bold></td><td align=\"center\"><bold>79</bold></td><td align=\"center\"><bold>61</bold></td><td align=\"center\"><bold>61</bold></td><td align=\"center\"><bold>61</bold></td><td align=\"center\"><bold>62</bold></td></tr><tr><td align=\"left\">ABV2</td><td align=\"center\">86</td><td align=\"center\">100</td><td align=\"center\"><bold>80</bold></td><td align=\"center\"><bold>78</bold></td><td align=\"center\"><bold>59</bold></td><td align=\"center\"><bold>59</bold></td><td align=\"center\"><bold>58</bold></td><td align=\"center\"><bold>60</bold></td></tr><tr><td align=\"left\">ABV3</td><td align=\"center\">89</td><td align=\"center\">89</td><td align=\"center\">100</td><td align=\"center\"><bold>83</bold></td><td align=\"center\"><bold>59</bold></td><td align=\"center\"><bold>59</bold></td><td align=\"center\"><bold>58</bold></td><td align=\"center\"><bold>58</bold></td></tr><tr><td align=\"left\">ABV4</td><td align=\"center\">87</td><td align=\"center\">87</td><td align=\"center\">94</td><td align=\"center\">100</td><td align=\"center\"><bold>61</bold></td><td align=\"center\"><bold>60</bold></td><td align=\"center\"><bold>60</bold></td><td align=\"center\"><bold>59</bold></td></tr><tr><td align=\"left\">Ref/V</td><td align=\"center\">68</td><td align=\"center\">64</td><td align=\"center\">64</td><td align=\"center\">67</td><td align=\"center\">100</td><td align=\"center\"><bold>98</bold></td><td align=\"center\"><bold>96</bold></td><td align=\"center\"><bold>82</bold></td></tr><tr><td align=\"left\">H1766</td><td align=\"center\">68</td><td align=\"center\">64</td><td align=\"center\">64</td><td align=\"center\">67</td><td align=\"center\">99</td><td align=\"center\">100</td><td align=\"center\"><bold>95</bold></td><td align=\"center\"><bold>83</bold></td></tr><tr><td align=\"left\">He/80</td><td align=\"center\">68</td><td align=\"center\">64</td><td align=\"center\">64</td><td align=\"center\">67</td><td align=\"center\">99</td><td align=\"center\">99</td><td align=\"center\">100</td><td align=\"center\"><bold>81</bold></td></tr><tr><td align=\"left\">No/98</td><td align=\"center\">67</td><td align=\"center\">65</td><td align=\"center\">63</td><td align=\"center\">67</td><td align=\"center\">97</td><td align=\"center\">96</td><td align=\"center\">96</td><td align=\"center\">100</td></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p><bold>Alignment of bornavirus genomes 5' and 3' termini</bold>. Bornavirus genome organization overview diagrammed as in Figure ##FIG##1##2##. Sequences in alignments shown are complementary to vRNA sequence, genome isolate names shown at left. 3' end sequence recovered for ABV genome and other BDV genomes is shown in left panel, 5' end sequence recovered for ABV genome and other BDV genomes is shown in right panel. Accession numbers for genomes aligned: hu2Pbr [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AB258389\">AB258389</ext-link>], Bo/04w [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AB246670\">AB246670</ext-link>], H1766 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311523\">AJ311523</ext-link>], Ref [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"NC_001607\">NC_001607</ext-link>], V [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"U04608\">U04608</ext-link>], V/FR [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311521\">AJ311521</ext-link>], CRNP5 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114163\">AY114163</ext-link>], CRP3B [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114162\">AY114162</ext-link>], CRP3A [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114161\">AY114161</ext-link>], He/80/FR [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311522\">AJ311522</ext-link>], He/80 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"L27077\">L27077</ext-link>], pBRT7-HrBDVc [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY705791\">AY705791</ext-link>], No/98 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311524\">AJ311524</ext-link>], ABV [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781967\">EU781967</ext-link>].</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p><bold>Alignment of transcription initiation and termination sites in bornavirus genomes</bold>. Panel A, alignment of the 3 bornavirus transcription initiation sites (TIS) and 6 nucleotides of flanking sequences. Panel B, alignment of the 4 bornavirus transcription termination sites. Source genomes for alignments are shown at left. Black trianges highlight ABV sequences.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p><bold>Alignment of splice donor and splice acceptor sequences in bornavirus genomes</bold>. Panel A, alignment of splice donor 1 and splice acceptor 1 sequences; Panel B, alignment of splice donor 2 and splice acceptor 2 sequences; Panel C, alignment of splice acceptor 3 sequences. Source genomes for alignments are shown at left.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p><bold>Phylogenetic relationships between sub-genomic loci of ABV and representative BDV genomes</bold>. Neighbor-joining trees generated for the indicated nucleotide sequences of ABV and a representative set of BDV genomes are shown for each ORF in the bornavirus genome. Accession numbers of representative BDV genomes are: Ref/V [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"NC_001607\">NC_001607</ext-link>], H1766 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311523\">AJ311523</ext-link>], He/80 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY705791\">AY705791</ext-link>], No/98 [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311524\">AJ311524</ext-link>].</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p><bold>Summary of clinical and molecular data for specimens provided in this study</bold>. Microsoft Excel file containing two spreadsheet (US specimens and Israel specimens) summarizing clinical and epidemiologic information available for each specimen, as well as the associated results from the described microarray/PCR/sequence experiments.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>^a3 crop biopsies from US source and 5 brain and proventriculus/ventriculus biopsies from Israel source were examined, with ABV detected in 2 of crop specimens and 3 brain specimens. ^b5 crop biopsies from US source and 3 brain and proventriculus/ventriculus biopsies from Israel source were examined.</p></table-wrap-foot>", "<table-wrap-foot><p>*Values without parentheses have no deviation in % pairwise amino acid identity among compared isolates.</p></table-wrap-foot>", "<table-wrap-foot><p>P = 0.01, Fisher's Exact Test</p></table-wrap-foot>", "<table-wrap-foot><p>PCR fragment examined corresponds to bp 3735–4263 of antigenomic strand of BDV V/Ref genome isolate [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"NC_001607\">NC_001607</ext-link>]. Bold text, average % nucleotide identity; plain text, average % predicted amino acid identity. ABV1 isolate [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781953\">EU781953</ext-link>], ABV2 isolates [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781954\">EU781954</ext-link> and GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781962\">EU781962</ext-link>–<ext-link ext-link-type=\"gen\" xlink:href=\"EU781966\">EU781966</ext-link>], ABV3 isolate [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781955\">EU781955</ext-link>], ABV4 isolates [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"EU781956\">EU781956</ext-link>–<ext-link ext-link-type=\"gen\" xlink:href=\"EU781961\">EU781961</ext-link>], Ref/V isolates [GeneBank:<ext-link ext-link-type=\"gen\" xlink:href=\"NC_001607\">NC_001607</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311521\">AJ311521</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"U04608\">U04608</ext-link>], H1766 isolates GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311523\">AJ311523</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AB258389\">AB258389</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AB246670\">AB246670</ext-link>], He/80 isolates [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"L27077\">L27077</ext-link>, GenBan:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311522\">AJ311522</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY05791\">AY05791</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114163\">AY114163</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114162\">AY114162</ext-link>, GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AY114161\">AY114161</ext-link>], No/98 isolate [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"AJ311524\">AJ311524</ext-link>].</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Multi modal postoperative pain management has become standard of care especially in day case surgery [##REF##17350437##1##]. Local anaesthesia applied prior to incision has been shown to have positive effects not only on the postoperative course but also to reduce the needs for main anaesthetic [##REF##11388531##2##, ####REF##16507194##3##, ##REF##18088436##4####18088436##4##]. The effects of pre-treatment, premedication with NSAIDs as well as pre-incisional local anaesthesia have convincingly been shown to have a major impact on the postoperative pain course [##REF##15728066##5##]. We found, in a previous study, pre-incisional local anaesthesia to have also clear intra-operative anaesthetic sparing effects [##REF##18088436##4##]. The intra-operative effects, the effects on the main anaesthetic requirement, of preoperative administration of a Coxibs are, however, not well studied. Hypothetically administration of Coxibs preoperatively could have intra-operative effects by its prostaglandin inhibitory effect and thereby additive analgesic effects reducing the need for main anaesthetic.</p>", "<p>The aim of the present study was to evaluate the effects of adding a Coxib pre-operatively on the need for main anaesthetic during balanced anaesthesia for elective day surgery.</p>" ]

[ "<title>Methods</title>", "<p>After informed consent 44 healthy American Society of Anesthesiology physiological status 1–2 patients; healthy patients aged 18 to 70 years scheduled for elective ankle surgery in general anaesthesia, as day cases, were eligible for inclusion. Patients with history of any previous reaction to NSAIDs or Coxibs, renal disease, not fully controlled cardiovascular disease or psychiatric disease requiring Litium therapy were excluded. Seventeen males and 27 females; mean age 45 (SD 14) years, mean weight 80 (SD 15) was included.</p>", "<p>The study protocol, a prospective randomised study of the effects of pre-operative administration of a Coxib on the intra-operative anaesthetic requirements during elective day surgery was approved by ethical board at Karolinska Institut in Stockholm.</p>", "<p>Primary study end-point: mean end-tidal sevoflurane concentration during surgery to maintain a Cerebral State index 40 – 50.</p>", "<p>Secondary study variables;</p>", "<p>• Need for rescue analgesics during recovery</p>", "<p>• Need for rescue analgesia during the first 24 postoperative hour</p>", "<p>• PONV</p>", "<p>• Patients' satisfaction</p>", "<p>The patients were randomised into two groups by computer prepared randomisation;</p>", "<p>• Group A had etoricoxib 120 mg oral pre-surgery – preoperative group</p>", "<p>• Group B had etoricoxib 120 mg oral right after end-of-surgery – postoperative group</p>", "<p>All patients followed the routine pre and postoperative protocol of our institution.</p>", "<p>They were asked to refrain from eating for 6 hours and drinking for 2 hour prior to surgery.</p>", "<p>After establishment of an intravenous line all patients were given 8 mg betamethasone, and a sedation dose of 30 – 40 mg propofol; washing and dressing while sedated.</p>", "<p>Two electrodes were applied on the forehead and one on the masteoid in accordance to the instructions for Cerebral State Monitor. The Cerebral State Index (CSI) derived from a Cerebral State Monitor (Danmeter A/S, Kildemosevej 13, DK-5000 Odense C, Denmark) was followed during the entire procedure.</p>", "<p>All patients had induction of anaesthesia with a combination of 8–9 μg/kg alfentanil as a iv. injection and propofol sufficient to allow insertion of a laryngeal mask airway. All patients were breathing spontaneous; no muscle relaxant was given.</p>", "<p>Right after insertion of the laryngeal mask sevoflurane in oxygen/air 1 L/min was introduced as main anaesthetic. During surgery a CSI of 40 – 50 was set as adequate depth of anaesthesia. The Sevoflurane was titrated aiming for a Cerebral State Index of 40 – 50 throughout surgery; the vaporizer setting was increased to 8% if signs of light anaesthesia and decreased stepwise by 2% if signs of excessive anaesthesia. Any other signs of inadequate or excessive anaesthesia by means of changes in heart rate, blood pressure or movements were also acknowledged. During wound close sevoflurane was discontinued and fresh gas flows were increased. All patients had local anaesthesia (bupivacaine 5 mg/ml 10 cc) in the wound area at end of surgery cc infiltrated in open surgery and injected in to the joint in arthroscopy patients in accordance to the routine of the department.</p>", "<p>Cerebral State Index, end-tidal sevoflurane concentrations, heart rate, systolic blood pressure and respiratory rate were recorded every 3^rdminute during surgery. Mean end-tidal sevoflurane concentration during maintenance of anaesthesia was calculated as primary study variable.</p>", "<p>Immediately after surgery all patients were moved to the recovery area, if fully awake and alert an Observer Assessment of Sedation Score of 5, possibly bypassing conventional recovery room stay. After arrival in recovery area all patients had an initial oral loading dose of 30 mg/kg paracetamol in accordance to the routines of the department. The postoperative group was together with the paracetamol given 120 mg etoricoxib orally; in the pre-operative group no further analgesics were given. Rescue analgesia, oxicodone orally, was provided in case patient graded pain on a 4 graded scale; no pain, mild pain, pain, severe pain. Patients were discharged when awake, and ambulant with minimal and acceptable levels of subjective pain (no/mild pain) in accordance with the standardised protocol of the institution.</p>", "<p>At discharge all patients were provided with dextropropoxyphene 100 mg as oral rescue analgesic. All patients were also asked to fill in a postoperative questionnaire about pain, need for rescue analgesia, emesis, sleep disturbance and overall pain treatment satisfaction.</p>", "<title>Statistics</title>", "<p>All values are given as mean and standard deviation. End-tidal concentration during maintenance and all other continuous data was compared between groups by ANOVA, differences in category data was analysed by Chi-Square test, and a p &lt; 0.05 was considered statistical significant.</p>", "<p>The number of patients, 22 in each group studied, was derived on a power calculation based on the assumption that in the control group, the group receiving the etoricoxib after surgery would have a mean end-tidal concentration of 1.2 with a standard deviation of 0.23 and that a reduction of 0.2 would be a clinically significant difference.</p>", "<p>All statistics were made in StatView™ on a Macintosh computer system.</p>" ]

[ "<title>Results</title>", "<p>The groups were fully comparative; there was no significant difference in patient demographics Table ##TAB##0##1##. Time from etoricoxib premedication to start of anaesthesia was 25 (SD 4) minutes.</p>", "<p>All surgery and anaesthesia was uneventful and no complications or adverse effects were noticed. One patient in the etirocoxib group scheduled for arthroscopy had a conversion to open surgery in order to achieve effect resection of an exostosis but was still included in the analysis. Duration of procedures was also the same in both groups; mean duration of surgery (knife to skin to closed wound) was 21 (SD 7) minutes.</p>", "<p>The mean end-tidal sevoflurane concentration to maintain a CSI of 46 (SD 3.9) showed a difference by 0.34% for the pre and post-operative administered group of patients respectively (p &lt; 0.0001). No other differences were noticed intra-operatively; heart rate, blood pressure and respiratory rate were all well controlled during surgery and no other major signs of light or excessive anaesthesia were noticed. No additional analgesics were given during surgery.</p>", "<p>Emergence was rapid and all patients were safely \"fast-tracked\", by-passing the regular recovery room, into the phase II recovery area. Recovery times, time to allowing drinking and to ambulate were the same in both groups. In all 6 patients required rescue analgesia during stay in the recovery area. Five patients in the group receiving etoricoxib post-operatively/after surgery and one patient in the pre-operative group required rescue analgesia before discharge. No patients complained about nausea during the stay in the recovery area. Eligible for discharge did not differ; all patients were discharged home safely within 80 minutes from reaching the phase II recovery area (Table ##TAB##1##2##).</p>", "<p>Five patients were lost for follow-up, 3 in the pre-operative and 2 in the postoperative etoricoxib group of patients respectively. No significant difference was noticed in pain ratings or need for opioid rescue analgesia during the first 24 postoperative hours. Three patients in the pre-operative group and 5 in the postoperative group had at least one opioid rescue during the 24-hour follow-up period. Four and two patients in the pre and post treatment group respectively experienced PONV following discharge. No difference was seen in \"patients' satisfaction\" all thirty-nine patients followed graded postoperative pain management as satisfactory.</p>" ]

[ "<title>Discussion</title>", "<p>Our study is positive; we found a statistical significant difference between the pre- and post-operative administration of etoricoxib with regard to our primary study endpoint; mean end-tidal sevoflurane concentration needed to maintain a Cerebral State Index of 40–50 during elective minor day surgery.</p>", "<p>The interpretation of our results should be done with caution, as the study design is complex. It should indeed be acknowledged that our patients received a multi-modal analgesic regime and balanced anaesthesia. All patients received both betamethasone and alfentanil at induction. The synergistic interaction between sevoflurane and opioids, reducing the \"effective dose 50\" (MAC) is well documented [##REF##10472223##6##]. A clear sevoflurane sparing effect from small doses of fentanyl in day surgical anaesthesia has been shown both with and without monitoring of anaesthetic depth [##REF##12027841##7##]. The main anaesthetic sparing effects of local anaesthesia is also well recognised [##REF##11388531##2##,##REF##16507194##3##]. We found in an earlier study, designed similar to the present, a clear effect from a peripheral local anaesthesia block on the sevoflurane requirement during minor orthopaedic day surgery, Hallux Valgus surgery [##REF##18088436##4##]. Romunstad et al has also convincingly shown the analgesic properties postoperatively of steroids [##REF##16428536##8##], improving not only pain but also overall patient satisfaction. There are no studies, however, documenting any intra-operative effects from the use of steroids. The aim of the present study was to looking at the potential effect of pre-treatment with a Coxib on the intra-operative sevoflurane requirement. The mean end-tidal sevoflurane concentration was statistical significant different between the groups studied. No other intra or postoperative effects were, however noticed. Intra operative vital signs did not show any major differences and the decreased intra-operative anaesthesia requirement did no translate into any other difference; no significant impact on emergence time or recovery characteristics was noticed. Slightly more patients needed rescue analgesia before discharge in the post-administered group of patients. It should be acknowledge that the number of patients in the study were limited and based on a power analysis to show intra-operative effects only. Provision of oral analgesic shortly after end of anaesthesia may have a slow onset of action due to delayed enteric absorption contributing to the differences seen in postoperative rescue analgesia requirements. The results with regard to postoperative pain should also take into account that all patients had etoricoxib either before or right after surgery but also alfentanil, betamethasone at induction, local anaesthesia (bupivacaine) at wound closure and a loading dose of 30 mg/kg paracetamol orally at arrival in the phase II recovery area.</p>", "<p>The hypothesis of the present study was that adding a Coxib, etoricoxib, prior to start of surgery would exhibit not only beneficial effects on the postoperative pain course but also exhibit intra-operative effects thereby reducing the need for main anaesthetic. Similar to what we previously found for local anaesthesia as an ankle block for Hallux Valgus surgery [##REF##18088436##4##]. Intra-operative effects of NSAIDs have not been extensively studied. Ding et al have made two studies comparing ketorlolac to fentanyl during laparoscopic surgery in general anaesthesia. In the first study 60 mg ketorolac produced the same intraopeartive course as fentanyl 50 – 100 microgram [##REF##1388338##9##]. In the second, they found ketorolac to be inferior to fentanyl in blunting response to incision, no major difference between the fentanyl and ketorolac group was seen in haemodynamic variables [##REF##8346816##10##]. Ramirez-Ruiz et al compared ketorolac with fentanyl for MAC-sedation and in that setting ketorolac was found less effective as compared to fentanyl [##REF##8534465##11##]. In another MAC-sedation study, by Yang et al, ketorolac had a significant fentanyl sparing effect [##REF##11989050##12##]. Turan et al have also studied the intra-operative effects of Coxibs [##REF##12401617##13##]. They found preoperative rofecoxib to have clear intra-operative effects during ENT-surgery in MAC-sedation.</p>", "<p>There are limitations with the present study. The study design is not double-blinded; still the aim was to achieve equivalent depth of anaesthesia in both groups of patients by the use of the Cerebral State Index as an objective measure of anaesthetic depth. The cortical retrieved processed EEG index describes the balance between stimulation and anaesthetic depth [##REF##11983658##14##] and also the interaction between analgesia and anaesthetics [##REF##12027841##7##]. One may of course argue whether the groups were comparable with regard to depth of anaesthesia. Depth of anaesthesia is not easily defined. The introduction of EEG, depth-of-anaesthesia monitors, has made major change to anaesthetic practice. These devices make it possible to quantify the anaesthetic state in real-time on-line. Anaesthetic depth-monitors have been shown to improve anaesthetic delivery [##REF##17943802##15##]. We used the Cerebral State Index to quantify depth of anaesthesia. The CSI has been shown to be more or less identical to the Bi-spectral index in determining anaesthetic depth [##REF##16430792##16##,##REF##17312217##17##]. We tried to make the groups as comparable as possible. We provided induction and analgesics in as standardised doses as possible, however titrating sevoflurane to maintain the EEG derived depth of anaesthesia monitoring in a rather narrow pre-defined range during surgery. A study design quit different from that of Hirota et al, where a dose of NSAIDs was added to a steady-state intra-venous anaesthesia without and surgical stimulation [##REF##12113610##18##]. In disagreement with their hypothesis they could see no change in BIS from the addition of a conventional non-selective NSAID. It is, however, well known that BIS as well as CSI are both insensitive to the effects of certain anaesthetics [##REF##10562773##19##,##REF##15954953##20##].</p>", "<p>It is from the present clinical study not possible to make any comments as to the potential mode of action; in what way etoricoxib interacts intra-operatively. Further studies are indeed needed in order to verify our results found in minor day surgery and to evaluate whether the intra-operative effects noticed in the present study could translate into clinical significant benefits, e.g. decrease time for recovery and decreased incidence and severity of side effects related to depth of anaesthesia such as postoperative nausea and vomiting, dizziness and fatigue; all factors of major importance to the ambulatory surgical patient satisfaction and turn over.</p>" ]

[ "<title>Conclusion</title>", "<p>There is today a huge and most reassuring clinical experience in that NSAIDs/Coxibs have profound effects in reducing pain, need for opioid rescue analgesia and improving patients satisfaction when used for postoperative pain management in day surgery. When added to a multi-modal pain management and provided already pre-operatively etoricoxib seems to exhibit intra-operative effects, potentially reducing the need for main anaesthetic.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Anti-inflammatory drugs, NSAIDs, have become an important part of the pain management in day surgery. The aim of the present study was to evaluate the effect of Coxib premedication on the intra-operative anaesthetic requirements in patients undergoing elective ankle surgery in general anaesthesia.</p>", "<title>Type of study</title>", "<p>Prospective, randomized study of the intra-operative anaesthetic-sparing effects of etoricoxib premedication as compared to no NSAID preoperatively.</p>", "<title>Methods</title>", "<p>The intra-operative requirement of sevoflurane was studied in forty-four ASA 1–2 patients undergoing elective ankle day surgical in balanced general anaesthesia.</p>", "<p>Primary study endpoint was end-tidal sevoflurane concentration to maintain Cerebral State Index of 40 – 50 during surgery.</p>", "<title>Results</title>", "<p>All anaesthesia and surgery was uneventful, no complications or adverse events were noticed. The mean end-tidal sevoflurane concentration intra-operatively was 1.25 (SD 0.2) and 0.91 (SD 0.2) for the pre and post-operative administered group of patients respectively (p &lt; 0.0001). No other intra-operative differences could be noted. Emergence and recovery was rapid and no difference was noticed in time to discharge-eligible mean 52 minutes in both groups studied. In all 6 patients, 5 in the group receiving etoricoxib post-operatively, after surgery, and one in the pre-operative group required rescue analgesia before discharge from hospital. No difference was seen in pain or need for rescue analgesia, nausea or patients satisfaction during the first 24 postoperative hours.</p>", "<title>Conclusion</title>", "<p>Coxib premedication before elective day surgery has an anaesthetic sparing potential.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>JJ has had the main responsibility for the study and manuscript preparation. All other authors have contributed equally.</p>" ]

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[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Patient's demographics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Pre-treatment </bold>(n = 22)</td><td align=\"center\"><bold>Post-treatment </bold>(n = 22)</td></tr></thead><tbody><tr><td align=\"left\"><bold><italic>Sex (male/female)</italic></bold></td><td align=\"center\">6/16</td><td align=\"center\">11/11</td></tr><tr><td align=\"left\"><bold><italic>Age (year.)</italic></bold></td><td align=\"center\">47 ± 12</td><td align=\"center\">42 ± 15</td></tr><tr><td align=\"left\"><bold><italic>Weight (kg)</italic></bold></td><td align=\"center\">80 ± 16</td><td align=\"center\">80 ± 15</td></tr><tr><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Surgery</italic></bold></td><td/><td/></tr><tr><td align=\"left\"><italic>Peroneus ligament</italic></td><td align=\"center\">5</td><td align=\"center\">7</td></tr><tr><td align=\"left\"><italic>Fibulo-talar ligament</italic></td><td align=\"center\">12</td><td align=\"center\">11</td></tr><tr><td align=\"left\"><italic>Arthroscopy of the ankle</italic></td><td align=\"center\">5</td><td align=\"center\">4</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Intra and post operative observations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Pre-treatment </bold>(n = 22)</td><td align=\"center\"><bold>Post-treatment </bold>(n = 22)</td></tr></thead><tbody><tr><td align=\"left\"><bold><italic>Duration of surgery (min.)</italic></bold></td><td align=\"center\">21 ± 6</td><td align=\"center\">21 ± 7</td></tr><tr><td align=\"left\"><bold><italic>Propofol (mg/kg)</italic></bold></td><td align=\"center\">2.36 ± 0.45</td><td align=\"center\">2.41 ± 0.44</td></tr><tr><td align=\"left\"><bold><italic>Alfentanil μg/kg</italic></bold></td><td align=\"center\">0.92 ± 0.09</td><td align=\"center\">0.96 ± 0.09</td></tr><tr><td align=\"left\"><bold><italic>CSI</italic></bold></td><td align=\"center\">46 ± 5</td><td align=\"center\">46 ± 3</td></tr><tr><td align=\"left\"><bold><italic>Et Sevo mean (%)</italic></bold></td><td align=\"center\">0.909 ± 0.17</td><td align=\"center\">1.246 ± 0.23 **</td></tr><tr><td align=\"left\"><bold><italic>Discharge (min.)</italic></bold></td><td align=\"center\">52 ± 5</td><td align=\"center\">52 ± 9</td></tr><tr><td align=\"left\"><bold><italic>Analgesics before discharge (No. of Pat.)</italic></bold></td><td align=\"center\">1/21</td><td align=\"center\">5/17</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>** p &lt; 0.0001 ANOVA</p><p>Et Sevo; end tidal concentration of sevoflurane</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Elbow Stiffness with loss of function is a common disabling problem that usually arises as a complication of trauma [##REF##7962149##1##, ####REF##6736093##2##, ##REF##3343270##3##, ##UREF##0##4##, ##REF##624574##5####624574##5##], but may also occur following burns[##REF##104047##6##,##REF##4055874##7##]. or head injury [##REF##6809389##8##,##REF##816002##9##] or in association with degenerative, inflammatory or haemophiliac [##REF##1053876##10##] arthropathy and congenital malformations [##UREF##1##11##]. The degree of stiffness is related to the severity of the injury and the duration of immobilisation at initial treatment [##UREF##2##12##,##REF##10629338##13##]. Loss of elbow extension commonly produces a significant functional deficit [##REF##7240327##14##]. Elbow contractures can be classified as extrinsic or intrinsic according to the underlying aetiology [##REF##2324148##15##]. Extrinsic contractures involve the peri-articular soft-tissues with a normal or near normal articular surface. Intrinsic factors include disruption of the normal articular surface, osteophytes, intra-articular loose bodies and secondary osteoarthritis.</p>", "<p>When non-operative treatments such as static or dynamic splinting [##UREF##3##16##, ####REF##1900125##17##, ##REF##8194222##18##, ##REF##489654##19##, ##REF##2928396##20##, ##UREF##4##21##, ##REF##1002273##22####1002273##22##] fail then surgery is often considered. Many surgical techniques have been described for established contractures with significant functional impairment. These include: manipulation-under-anaesthesia [##REF##1995685##23##]; arthroscopic release [##REF##8198192##24##, ####REF##8323612##25##, ##REF##8679028##26####8679028##26##]; open capsulectomy via anterior [##REF##3171294##27##, ####REF##1277677##28##, ##REF##1400551##29##, ##REF##2229112##30##, ##UREF##5##31####5##31##], posterior [##REF##10629338##13##], medial [##REF##10697317##32##,##UREF##6##33##], lateral [##REF##2229112##30##,##REF##2624082##34##, ####REF##9840628##35##, ##REF##10660702##36##, ##REF##9768890##37####9768890##37##], or combined approaches [##REF##2599703##38##].</p>", "<p>We present our experience of the 'mini-open' lateral approach to the elbow to correct an extension deficit in a series of patients with an established post-traumatic flexion contracture of both intrinsic and extrinsic types [##REF##9840628##35##]. This approach facilitates access to the anterior capsule, the lateral ligament complex and radio-capitellum joint. It is also possible to access the posterior part of the elbow joint and olecranon of required.</p>" ]

[ "<title>Methods</title>", "<p>Between 1998 and 2004, 23 patients referred to our unit were treated surgically for a post traumatic flexion contracture of the elbow. The indication for surgery in all was an established functionally significant extension deficit that had failed non-operative treatment with at least 9 months having elapsed since injury. In each case the contracture was classified as extrinsic or intrinsic after assessment with clinical examination and plain radiographs and the pre-operative flexion contracture recorded. All patients consented to have their surgery under general anaesthesia and regional block with a tourniquet. The lateral column approach was used with a small 8 cm (10 cm if larger patient) incision centred over the lateral epicondyle (Figure ##FIG##0##1##). The same operative sequence was followed for all patients. All patients had a section of anterior capsule, extending across the entire anterior aspect of the joint, excised under direct vision (Figure ##FIG##1##2##). If the radial head was significantly damaged and determined at this point to be a block to extension then it was excised. Next if extension was still limited and the lateral collateral ligament complex appeared tight it was z-lengthened rather than sacrificed. Cases of intrinsic contracture also had any intra-articular lesion addressed. Any implanted metalwork that was easily accessible and may influence movement or cause pain was also removed as were any olecranonosteophytes identified on pre-operative imaging. If ulnar nerve symptoms and signs were present then an ulnar nerve release with subcutaneous transposition was performed via a separate medial incision. No distracting devices were used. The tourniquet was released, haemostasis secured with electro-cautery and a drain placed in the peri-articular soft-tissues. The residual \"on-table\" passive deformity was assessed after wound closure and before the application of dressings.</p>", "<p>Post-operatively the limb was immobilised overnight in maximum extension using a plaster slab. The drain was removed and the cast replaced by a static, extension thermoplastic splint the next day. All patients were discharged on the first post-operative day. No prophylaxis was given to prevent heterotopic bone formation. The splint was worn continuously for two weeks and then at night for six weeks. Physiotherapy with active extension exercises commenced after two weeks in the presence of satisfactory wound healing. Short-term results were assessed by clinical review while medium-term follow-up was conducted using a telephone questionnaire and patient based deformity outlines as previously used by Morrey [##REF##9278082##39##]. The telephone questionnaire consisted of two questions; 'Are you happy with the results of your surgery?' and 'In retrospect would you have the surgery again?'. These assessment methods were used as most patients were tertiary referrals to our unit, living many miles away and were reluctant to return for a further appointment as they were satisfied and doing well.</p>" ]

[ "<title>Results</title>", "<p>In the study group there were 15 males and 8 females. The median age was 35 yrs (range 16 – 52 yrs). The contracture was post-traumatic in all cases (fracture with dislocation n = 9; fracture n = 9; dislocation n = 3; and soft-tissue injury n = 2). Sixteen patients had an extrinsic contracture and 7 patients had an intrinsic aetiology.</p>", "<p>All patients underwent anterior capsulectomy and additional procedures included: Z-lengthening of lateral collateral ligament n = 8; excision of radial head n = 3; removal of metalwork n = 3; excision of olecranon osteophyte n = 2; and ulna nerve transposition (via a separate medial incision) n = 2. Patient demographics, operative procedures and serial elbow deformities are listed in Table ##TAB##0##1##.</p>", "<p>Short term follow-up was available at 7.5 months (95%CI 4 – 11) in all patients and medium term follow-up at 43 months (95%CI 30 – 56) in 20 patients (87%). Overall, the mean pre-operative flexion deformity was 55 degrees (95%CI 48 – 61). Surgery reduced the mean \"on-table\" deformity to 17 degrees (95%CI 12 – 22). The short term mean residual deformity was 25 degrees (95%CI 19 – 30) and 32 degrees (95%CI 25 – 39) at medium term follow-up. The improvement in the fixed-flexion deformity was significant at both short-term and medium-term follow-up (paired t-test – p &lt; 0.01).</p>", "<p>Sub group analysis of extrinsic and intrinsic groups revealed:</p>", "<p><bold>Group One (extrinsic) </bold>patients had a mean pre-operative flexion deformity of 53 degrees (95%CI 47 – 59); a mean \"on-table\" correction to 13 degrees (95%CI 7 – 19); short term deformity of 20 degrees (95%CI 16 – 25); and medium term deformity of 28 degrees (95%CI 22 – 34).</p>", "<p><bold>Group Two (intrinsic) </bold>patients had a mean pre-operative flexion deformity of 57 degrees (95%CI 40 – 74); a mean \"on-table\" correction to 25 degrees (95%CI 15 – 35); short term deformity of 33 degrees (95%CI 21 – 46); and medium term deformity of 48 degrees (95%CI 32 – 64). The difference between the groups was significant at short term (two sample independent t-test – p = 0.02) and medium term (p = 0.05) follow-up.</p>", "<p>All patients were satisfied with their surgery and would undergo it again. No patients reported a loss or change in their maximum flexion. One patient had a post-operative complication with transient dysaesthesia in the distribution of the ulnar nerve that lasted for six weeks. There were no cases of haematoma, infection or post-operative instability.</p>" ]

[ "<title>Discussion</title>", "<p>Historically, open release was performed via extensive surgical approaches such as the anterior approach that also included a biceps tenotomy [##REF##1277677##28##,##UREF##5##31##]. Urbaniak used the anterior approach to perform a capsulectomy [##REF##4055840##40##], but this does not allow access to the posterior structures of the elbow and is therefore not as useful. The medial approach does permit access to the anterior and posterior parts of the joint and exposes the ulnar nerve [##REF##10697317##32##] but the radial head and lateral ligament complex are beyond its reach. Contracture release via the lateral approach exposes all the relevant pathology [##REF##2229112##30##] and in patients with an isolated extension deficit can be performed through a \"mini\" lateral incision [##REF##9840628##35##].</p>", "<p>Whatever the approach, the goal of surgical treatment is to restore a functional range of movement. Morrey showed that a flexion contracture of greater than 30° has a significant effect on elbow function [##REF##7240327##14##] and Kraushaar proposed that patients participating in gymnastics, racquet or throwing sports were even less tolerant of an extension deficit [##REF##10543603##41##]. In our series, all but one of the patients had a pre-operative flexion contracture greater than 30° and complained of functional restriction with daily activities. The patient with a deformity of 20° felt that her functional requirements were such that this represented a significant limitation.</p>", "<p>We used deformity outlines for medium term follow up as most patients were tertiary referrals to our unit, living many miles away and were reluctant to return for a further appointment to report a favourable outcome. Patients were asked to get a family member draw around the affected upper limb with the elbow in maximum extension and the forearm in neutral rotation, Morrey has successfully reported on this previously [##REF##9278082##39##].</p>", "<p>While the ability of surgery to restore a functional range of movement is documented in a number of studies results have been variable. Morrey [##REF##10660702##36##] and Wada [##REF##10697317##32##] managed to restore a functional arc in 50%, while Schindler [##REF##1718358##42##] only achieved this in 30% of cases. The patients in our study did not have significant restriction of flexion and were therefore only treated for lack of extension. In 18 of the 23 cases (79%) the flexion contracture was corrected to less than 30° providing a functional range. In the sub-group of patients with extrinsic contracture all patients had a correction to less than 30°.</p>", "<p>There remains some controversy regarding the optimal post-operative regimen following surgery. Continuous passive motion (CPM) has been advocated as an adjunct to surgery [##REF##3171294##27##,##REF##2229112##30##]. Morrey initially used a regimen of CPM followed by dynamic splinting [##REF##2324148##15##]. This programme required a protracted in-patient stay and has been subsequently revised to three days of CPM as an in-patient followed by dynamic splinting upon discharge [##UREF##2##12##]. Wada, in a non-randomised trial, found no difference in the outcome of patients receiving CPM after surgery [##REF##10697317##32##], a finding corroborated by Chantelot who reviewed the factors influencing surgery for elbow contracture [##REF##12666286##43##]. In our series, the patients were splinted in maximum extension at the end of surgery. A thermoplastic moulded splint was custom-made and the patients were discharged on the first post-operative day. The splint remained in place for two weeks, after which they progressed to physiotherapy and night splinting for six weeks. Despite having a comprehensive post-operative regimen in place, the final correction at last clinical review was, on average, 5–10° less than that achieved at the time of surgery with further deterioration in the medium-term. Similar deterioration has been observed in other series [##REF##12666286##43##, ####REF##10637883##44##, ##REF##15568530##45####15568530##45##], and patients need to be warned that final deformity correction is likely to fall short of that achieved at the time of surgery and discharge. Despite this all patients in our series were satisfied with their outcome.</p>", "<p>The ulnar nerve is at risk during retraction and with one patient having a transientulnar nerve palsy, we recommend careful positioning of retractors during this procedure.</p>", "<p>We agree with others that all pathology pertinent to this type of flexion contracture can be addressed via the limited lateral approach. We also found that patients recovered quickly with an attendant short in-patient stay (&lt;24 hours). While careful consideration of the potential outcome should be given when using this technique for intrinsic contractures, our results show that for extrinsic contractures with an extension deficit, the limited lateral approach provides a safe reliable way of restoring a functional range in a high percentage of patients.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Varying surgical techniques, patient groups and results have been described regards the surgical treatment of post traumatic flexion contracture of the elbow. We present our experience using the limited lateral approach on patients with carefully defined contracture types.</p>", "<p>Surgical release of post-traumatic flexion contracture of the elbow was performed in 23 patients via a limited lateral approach. All patients had an established flexion contracture with significant functional deficit. Contracture types were classified as either extrinsic if the contracture was not associated with damage to the joint surface or as intrinsic if it was.</p>", "<p>Overall, the mean pre-operative deformity was 55 degrees (95%CI 48 – 61) which was corrected at the time of surgery to 17 degrees (95%CI 12 – 22). At short-term follow-up (7.5 months) the mean residual deformity was 25 degrees (95%CI 19 – 30) and at medium-term follow-up (43 months) it was 32 degrees (95%CI 25 – 39). This deformity correction was significant (p &lt; 0.01). One patient suffered a post-operative complication with transient dysaesthesia in the distribution of the ulnar nerve, which had resolved at six weeks. Sixteen patients had an extrinsic contracture and seven an intrinsic. Although all patients were satisfied with the results of their surgery, patients with an extrinsic contracture had significantly (p = 0.02) better results than those with an intrinsic contracture. (28 degrees compared to 48 degrees at medium term follow up).</p>", "<p>Surgical release of post-traumatic flexion contracture of the elbow via a limited lateral approach is a safe technique, which reliably improves extension especially for extrinsic contractures. In this series <underline>all</underline> patients with an extrinsic contracture regained a functional range of movement and were satisfied with their surgery.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>MDB collected data, analysed results and aided manuscript writing. AJC collected data and aided manuscript writing. JLR wrote the paper. All authors read and approved the final manuscript.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>A clinical photograph showing the anterior capsule of the elbow through the lateral approach.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>A clinical photograph showing the excised anterior capsule.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Demographics of patients who underwent surgical correction of post-traumatic flexion contracture of the elbow</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td/><td/><td/><td align=\"center\" colspan=\"4\">Deformity (degrees)</td></tr><tr><td/><td/><td/><td/><td/><td colspan=\"4\"><hr/></td></tr><tr><td align=\"center\">Patient</td><td align=\"center\">Age</td><td align=\"left\">Diagnosis</td><td align=\"left\">Classification</td><td align=\"left\">Operation</td><td align=\"center\">Pre-op</td><td align=\"center\">Peri-op</td><td align=\"center\">Short Term</td><td align=\"center\">Medium Term</td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">30</td><td align=\"left\">Soft Tissue Injury</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">40</td><td align=\"center\">0</td><td align=\"center\">20</td><td align=\"center\">35</td></tr><tr><td align=\"center\">2</td><td align=\"center\">44</td><td align=\"left\">Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">40</td><td align=\"center\">0</td><td align=\"center\">10</td><td align=\"center\">10</td></tr><tr><td align=\"center\">3</td><td align=\"center\">16</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">60</td><td align=\"center\">5</td><td align=\"center\">15</td><td align=\"center\">15</td></tr><tr><td align=\"center\">4</td><td align=\"center\">38</td><td align=\"left\">Fracture</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">65</td><td align=\"center\">30</td><td align=\"center\">30</td><td align=\"center\">30</td></tr><tr><td align=\"center\">5</td><td align=\"center\">29</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC, ZLCL</td><td align=\"center\">55</td><td align=\"center\">30</td><td align=\"center\">30</td><td align=\"center\">40</td></tr><tr><td align=\"center\">6</td><td align=\"center\">48</td><td align=\"left\">Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC, ZLCL</td><td align=\"center\">60</td><td align=\"center\">20</td><td align=\"center\">30</td><td align=\"center\">30</td></tr><tr><td align=\"center\">7</td><td align=\"center\">31</td><td align=\"left\">Fracture</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">40</td><td align=\"center\">5</td><td align=\"center\">10</td><td align=\"center\">20</td></tr><tr><td align=\"center\">8</td><td align=\"center\">49</td><td align=\"left\">Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">70</td><td align=\"center\">0</td><td align=\"center\">30</td><td align=\"center\">30</td></tr><tr><td align=\"center\">9</td><td align=\"center\">29</td><td align=\"left\">Fracture</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC, ZLCL</td><td align=\"center\">45</td><td align=\"center\">20</td><td align=\"center\">20</td><td align=\"center\">30</td></tr><tr><td align=\"center\">10</td><td align=\"center\">41</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">60</td><td align=\"center\">15</td><td align=\"center\">20</td><td align=\"center\">30</td></tr><tr><td align=\"center\">11</td><td align=\"center\">35</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">60</td><td align=\"center\">10</td><td align=\"center\">15</td><td align=\"center\">40</td></tr><tr><td align=\"center\">12</td><td align=\"center\">16</td><td align=\"left\">Fracture</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">50</td><td align=\"center\">20</td><td align=\"center\">20</td><td align=\"center\">30</td></tr><tr><td align=\"center\">13</td><td align=\"center\">26</td><td align=\"left\">Soft Tissue Injury</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC, ZLCL</td><td align=\"center\">70</td><td align=\"center\">10</td><td align=\"center\">10</td><td align=\"center\">N/A</td></tr><tr><td align=\"center\">14</td><td align=\"center\">52</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC</td><td align=\"center\">40</td><td align=\"center\">10</td><td align=\"center\">20</td><td align=\"center\">20</td></tr><tr><td align=\"center\">15</td><td align=\"center\">40</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, ZLCL, EOO</td><td align=\"center\">60</td><td align=\"center\">20</td><td align=\"center\">40</td><td align=\"center\">40</td></tr><tr><td align=\"center\">16</td><td align=\"center\">29</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC, ZLCL</td><td align=\"center\">50</td><td align=\"center\">30</td><td align=\"center\">30</td><td align=\"center\">45</td></tr><tr><td align=\"center\">17</td><td align=\"center\">18</td><td align=\"left\">Fracture</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, ERH</td><td align=\"center\">70</td><td align=\"center\">30</td><td align=\"center\">40</td><td align=\"center\">45</td></tr><tr><td align=\"center\">18</td><td align=\"center\">37</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, ERH</td><td align=\"center\">20</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">N/A</td></tr><tr><td align=\"center\">19</td><td align=\"center\">41</td><td align=\"left\">Fracture/Dislocation</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, EOO</td><td align=\"center\">60</td><td align=\"center\">20</td><td align=\"center\">40</td><td align=\"center\">N/A</td></tr><tr><td align=\"center\">20</td><td align=\"center\">26</td><td align=\"left\">Fracture</td><td align=\"left\">Extrinsic</td><td align=\"left\">AC, ROM</td><td align=\"center\">50</td><td align=\"center\">30</td><td align=\"center\">30</td><td align=\"center\">10</td></tr><tr><td align=\"center\">21</td><td align=\"center\">50</td><td align=\"left\">Fracture</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, ZLCL, ROM, UNT</td><td align=\"center\">60</td><td align=\"center\">40</td><td align=\"center\">50</td><td align=\"center\">40</td></tr><tr><td align=\"center\">22</td><td align=\"center\">43</td><td align=\"left\">Fracture</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, ERH</td><td align=\"center\">50</td><td align=\"center\">30</td><td align=\"center\">30</td><td align=\"center\">45</td></tr><tr><td align=\"center\">23</td><td align=\"center\">32</td><td align=\"left\">Fracture</td><td align=\"left\">Intrinsic</td><td align=\"left\">AC, ZLCL, ROM, UNT</td><td align=\"center\">90</td><td align=\"center\">30</td><td align=\"center\">40</td><td align=\"center\">70</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Key: AC = Anterior Capsulectomy; ZLCL = Z-lengthening Lateral Collateral Ligament; ERH = Excision of Radial Head; EOO = Excision of OlecranonOsteophyte; ROM = Removal of Metalwork; UNT = Ulna Nerve Transposition.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1749-799X-3-39-1\"/>", "<graphic xlink:href=\"1749-799X-3-39-2\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>One of the major problems in aquaculture of salmonids such as Atlantic salmon (<italic>Salmo salar L</italic>.) and rainbow trout (<italic>Oncorhynchus mykiss</italic>) is production loss due to ectoparasites like sea lice [##UREF##0##1##], which are easily spread between individuals in densely populated sea cages. The term sea lice is collectively used for ectoparasitic copepods (Copepoda, Caligidae) found on marine fish species, including salmonid fish. The main species of concern in North Atlantic marine salmonid aquaculture causing infections are <italic>Lepeophtheirus salmonis </italic>and <italic>Caligus elongatus</italic>. The parasites undergo several developmental stages, including planktonic stages and stages where the parasite is attached to or moving on the fish surface, feeding on mucus and blood [##UREF##1##2##,##REF##12396223##3##]. The main effects of sea lice infestations are general stress and osmoregulatory problems due to disruption of the skin by the feeding behaviour of the parasites [##REF##10092971##4##].</p>", "<p>Emamectin benzoate (EB) is currently the dominant peroral pharmaceutical drug used for the treatment and control of sea lice infestations on salmonids. EB is commonly used due to its effectiveness against all stages of sea lice infection [##UREF##2##5##]. EB is the active ingredient in SLICE, a commercial drug commonly used for sea lice control in Atlantic salmon farming. It is commonly used in many countries including Norway, UK, Canada and Chile that are producing large quantities of Atlantic salmon in aquaculture [##UREF##3##6##]. EB (4''-deoxy-4'' epi-methylamino-avermectin B₁) is a semi-synthetic avermectin, a group of insecticides that were originally isolated from soil microorganisms [##UREF##4##7##] and used for the control of insect pests in edible crops [##UREF##5##8##]. The mechanism of action of the avermectins in invertebrates is the binding to glutamate-gated chloride channels leading to an influx of chloride ions, thus giving a hyperpolarized cell. An additional mechanism is increasing the production of the inhibitory neuro-transmitter GABA at nerve endings, which prolongs the binding of GABA to the receptor, thus mediating the same effect. In invertebrates, avermectins act on muscle cells and synapses in the peripheral nervous system, causing paralysis and eventually death of the parasite. In mammals however, the toxic effect is low since the avermectins do not cross the mammalian blood brain barrier, and thus do not affect GABA-mediated neurons at in the central nervous system (CNS). According to the EU legislation described in the directive EC 2377/90, EB thus has been given a Maximum Residue Limit (MRL) in edible tissue of 100 ng/g. In fish, the blood brain barrier is not as impermeable as in mammals and CNS depression and deaths have been reported in salmon using avermectin at therapeutic doses.</p>", "<p>Orally administered EB is readily absorbed and distributed to tissues in salmonids [##REF##15053560##9##]. Metabolism of EB in fish is rather limited, resulting in sustained tissue concentrations. Eventually, absorbed and metabolized EB is excreted in feces via bile in the liver, a process that probably involves enterohepatic recirculation of EB, as observed in SLICE-treated rainbow trout [##REF##15053560##9##]. Possible effects of EB medication on the fish is therefore most likely to be manifested in hepatocyte cells in the liver, although very little is known about toxicological effects of EB on salmonid fishes. Roy et al. [##UREF##6##10##] examined the tolerance of Atlantic salmon and rainbow trout to EB exposure, and signs of EB toxicity included lethargy, dark coloration, inappetance and loss of coordination but no pathognomonic signs of toxicity during gross necropsy or histopathological examinations [##UREF##2##5##]. With the rapidly increasing number of known gene sequences in many species, transcriptional analysis has become one of the cornerstones of modern biology. So far more than 430 000 Atlantic salmon gene sequences from Atlantic salmon have been deposited in the Genbank, making it possible to search for biomarkers based on transcriptional responses to external stimuli with techniques like qPCR and microarray. The Consortium for Genomic Research on All Salmon Project (cGRASP) [##UREF##6##10##]. at the University of Victoria, Canada, has produced a large-scale cDNA microarray containing about 16000 clones that can be used in search of genome-wide responses to environmental stressors and medication in salmonid fishes [##REF##16164747##11##].</p>", "<p>The aim of this work was to examine to which degree EB has a toxic effect or is imposing stress on Atlantic salmon treated with the anti-salmon lice medication SLICE that contains EB as the active component. Juvenile Atlantic salmon were orally administered a daily EB dose of 50 μg/kg fish, mixed into the feed over a standard seven day medication period [##REF##15720522##12##]. Tissue residues of EB were measured in liver, muscle and skin at day 7 (end of the treatment period), 14 and 35. Microarray and qPCR techniques were used to search for transcriptional biomarkers for EB toxicity or stress induction in liver of medicated fish.</p>" ]

[ "<title>Methods</title>", "<title>Experimental fish</title>", "<p>Juvenile Atlantic salmon (<italic>Salmo salar L</italic>.) were obtained from the Institute of Marine Research, Bergen, Norway and maintained in flow-through seawater tanks (32‰ salinity, mean temperature 9.1°C). Prior to challenge, fish were randomly assigned to two 500 L tanks and raised in these throughout the experiment. One group of fish was kept as a control, whereas the other was treated with EB. An overview of the experimental design can be seen in Fig. ##FIG##0##1##.</p>", "<title>Fish treatment</title>", "<p>The medicated feed was produced by adding EB in a concentration of 1 mg/100 g to dry feed. The experimental fish were administered an oral standard medication regime of 50 μg EB per kg fish daily for seven days. The feeding rate was 0.5% body weight per day. Ten individual fish were collected at time 0 (untreated), thereafter 30 individual fish were collected at day 7, 14 and 35, from one control (n = 15) and one EB treated group (n = 15) at each time. A total of 100 fish were used in the experiment. No mortality was observed throughout the experiment. On average, the fish weighed 132 ± 21 g at time 0, 147 ± 25 g at day 7, 147 ± 27 g at day 14 and 189 ± 28 g at day 35 (mean ± SD). Non-medicated fish were fed a commercial dry pellet salmon feed at 0.5% body weight per day. The fish were killed by a blow to the head, after being removed from the tanks. No anesthetics were used.</p>", "<title>Tissue sampling</title>", "<p>Fish tissues for EB analysis were dissected out and stored at -20°C before further processing. Approximately 100 mg of tissue was sliced off the liver and immediately flash-frozen in liquefied nitrogen for RNA extraction. Tissue specimens for RNA extraction were stored at -80°C before further processing.</p>", "<title>Emamectin benzoate analysis</title>", "<p>Fish tissue samples (1.5 g) were homogenized in 1 ml of 0.9% NaCl in water and 300 μl of a solution of 1.5 μg/ml of ivermectin (internal standard) in methanol. After homogenization, 6 ml acetonitrile was added followed by shaking, sonication for 10 min and centrifugation. To the supernatant, 5 ml n-heptane was added followed by thorough shaking and removal of the n-heptane layer. Water (20 ml) was then added and the sample was subjected to solid phase extraction using a OASIS HLB 6 cc cartridge (Waters Corporation, Milford, Mass. USA) conditioned with 5 ml methanol followed by 4 ml of distilled water. After loading the sample, the column was washed with 3 ml of 33% acetonitrile in water and 3 ml of n-heptane prior to elution of EB by 3 ml of methanol. The column was dried by vacuum before the final elution of EB. The eluate was evaporated to dryness under a stream of nitrogen using a Reacti-Therm heating unit at 50°C and a Reacti-Evaporating unit (Pierce, Rockford, IL, USA). The dry residue was reconstituted in 300 μl methanol and 100 μl n-heptane, shaken for 30 sec and centrifuged for 3 min at 2000 rpm (Eppendorf 5810 R, Hamburg, Germany). The methanol fraction was filtered through a 0.45 μm syringe filter prior to injection into the high performance liquid chromatographic system (HPLC). Ivermectin and EB were supplied by Sigma-Aldrich Chemie (Steinheim, Germany). Methanol, acetonitrile, ammonium-acetate (all HPLC-grade) and n-heptane, acetic acid (100%; PA-grade) were all from Merck (Darmstadt, Germany). The water used was purified with a MilliQ water purification system (Millipore, Bedford, MA, USA). Standards were made by dissolving 50 mg ivermectin and emamectin in 10 ml of methanol.</p>", "<p>The concentration of EB in muscle was determined using an Agilent 1100 series HPLC connected to a MSD Quadropole mass-spectrometer (Agilent Technologies, Waldbronn, Germany). The analytical column was a 125 × 4 mm LiChrosphere C-18, 5 μm with a 4 × 4 mm LiChrosphere 100 RP-18, 5 μm guard column (Agilent Technologies, Palo Alto, CA, USA). The column temperature was 35°C. The mobile phase contained 50 mM ammonium acetate: acetonitrile: MilliQ water (5:75:20) and the elution profile was isocratic. The flow rate was 0.8 ml/min, giving elution times of 9.2 min for EB and 12.1 min for ivermectin. The injected sample volume was 40 μl. The mass-spectrometer was tuned in positive selected ion monitoring (SIM) mode with ion peaks at <italic>m/z </italic>of 982.5 for ivermectin and 886.4 for emamectin. The following tune parameters were used: APCI vaporizer temperature 450°C, corona current 5.0 μA, capillary voltage 2500 V, nebulizer pressure 60 psi, drying gas 4 l/min and fragmentor voltage 70 V. The calibration curve for emamectin was prepared in replicate by spiking muscle samples with standard solutions of emamectin to yield 2.5, 12.5, 25.0 and 50.0 ng/g. Ivermectin (300 ng/g) was added to each sample and acted as internal standard. The limit of quantification (LOQ) method was determined to be 5.0 ng/g and the limit of detection (LOD) to be 2.5 ng/g. The method for detection and quantification of emamectin used in this study are accredited in accordance with the international standard ISO/IEC 17025:1999 [##UREF##7##13##].</p>", "<title>RNA extraction</title>", "<p>Liver tissues from 70 individuals were thoroughly homogenized before RNA extraction with zirconium beads (4 mm) in a MM 301 homogenizer (Retsch GmbH, Haan, Germany). Total RNA was extracted using Trizol reagent (Invitrogen, Life Technologies, Carlsbad, CA, USA), according to the manufacturer's instructions and stored in 50 μl RNase-free MilliQ H₂O. Genomic DNA was eliminated from the samples by DNase treatment using DNA-free according to the manufacturer's description (Ambion, Austin, TX, USA). The RNA was then stored at -80°C before further processing. The quality of the RNA was assessed with the NanoDrop^®ND-1000 UV-Vis Spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) and the Agilent 2100 Bioanalyzer (RNA 6000 Nano LabChip^®kit, Agilent Technologies, Palo Alto, CA, USA).</p>", "<title>Microarray analysis</title>", "<p>A total of 42 RNA samples out of the total of 70 samples were prepared for microarray analysis. The RIN values for these 42 samples ranged from 9.3 to 10.0 (mean ± SD: 9.9 ± 0.2). RNA was extracted from six fish, three males and three females, from each group as shown in Fig. ##FIG##0##1##. cDNA synthesis was made with the 3DNA Array 350 HS kit according to the manual (Genisphere Inc., Sterling Drive, PA, USA). A common reference design was utilized with the experimental samples in the Cy5 channel and the reference samples in the Cy3 channel, hybridized to the cGRASP v.2.0 16 K cDNA microarray [##REF##16164747##11##]. Every 42 samples, both experimental and control were individually hybridized with the common reference, with 6 biological replicates for each group. No technical replicates were run. Hybridization was performed with a HS 4800 TM Hybridization station (Tecan, Männedorf, Switzerland), whereas scanning was performed with a LS Reloaded Scanner (Tecan, Männedorf, Switzerland). GenePix software (Axon Instruments, Union City, CA, USA) was used to analyze the scans. The reference was prepared from a pool of liver RNA from 50 individuals collected in an independent Atlantic salmon experiment.</p>", "<p>The data files from GenePix v.5.1 were processed using J-Express Pro v.2.8 [##REF##11301307##14##] to filter and normalize the hybridization data and compile the transcription matrix (gene by sample) for further analysis. The foreground signal intensity values for each channel were extracted for each spot from the data files according to the GenePix software manual (Axon Instruments, Union City, CA, USA). All flagged and control spots were filtered out before the data were normalized using global lowess [##UREF##8##15##]. After normalization, weak spots with FG &lt; BG + 1.5*BG_SD in both channels were filtered out. All arrays were then compiled into a single expression profile data matrix containing the normalized log ratios of the two foreground signal intensities. Rows with more than 75% missing values were removed from the matrix, and the remaining missing values were estimated using LSimpute_adaptive [##REF##14978222##16##]. Finally the data was divided into sub-datasets for the individual sampling days, and genes with at most 25% estimated missing values were allowed in the final expression matrix.</p>", "<p>The search for differentially expressed genes was performed both on a single gene and gene set level. A two class paired SAM [##REF##11309499##17##] v.2.1 analysis, as implemented in J-Express, was used to look for differentially expressed genes on a gene by gene basis, while GSEA [##REF##16199517##18##,##UREF##9##19##] also implemented in J-Express, was used to look for sets of genes sharing common characteristics that were differentially expressed between the classes examined. Gene sets were created on the basis of Gene Ontology (Gene Ontology Consortium [##UREF##10##20##]), by mapping the GO annotations in the cGRASP v.2.0 annotation file (dated August 2007) to the GO accession numbers in the Gene Ontology OBO file dated 08.06.07. <italic><underline>Parameters of GSEA </underline></italic>– Parallel analyses were run with probes collapsed to genes, using the gene description column, as well as non-collapsed expression matrix as input. Gene sets smaller than 10 and larger than 500 were excluded from the analysis. GSEA was run with SAM score as the ranking statistic. Significance of the gene set analysis was tested by permuting the scores over the genes (10000 iterations).</p>", "<title>qPCR</title>", "<p>In order to verify the microarray data, qPCR was used to quantify the transcriptional levels of eight differentially regulated genes in the same 42 RNA samples as used for microarray analysis. For verification, genes were picked from the statistical analysis of microarray (SAM) lists; two up-regulated and one down-regulated genes based on q-statistics [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"CB511007\">CB511007</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"CB509633\">CB509633</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"CB514814\">CB514814</ext-link>], and one up-regulated and three down-regulated genes based on fold-change [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"CA056074\">CA056074</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"CB488966\">CB488966</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"CA053315\">CA053315</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"CB491960\">CB491960</ext-link>]. In addition, one gene was picked that appeared to be un-regulated but was included in several gene sets (HLA class II histocompatibility antigen, gamma chain [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"CK990815\">CK990815</ext-link>]. qPCR assays were designed using Primer Express 2.0 software (Applied Biosystems, Foster City, CA, USA) to select appropriate primer sequences from gene sequences included on the array. Since some of the primers did not span exon-exon borders, all RNA samples were subjected to DNase treatment to avoid genomic DNA contamination. PCR primer sequences, GenBank accession numbers and amplicon lengths of the genes selected for qPCR verification are shown in Table ##TAB##0##1##.</p>", "<p>A two-step qPCR protocol was developed to measure the mRNA levels of the eight target genes and the three reference genes (β-actin, elongation factor 1A_B(EF1A_B) and acidic ribosomal protein (ARP)) in liver tissue of Atlantic salmon. The reverse transcription reactions were run in duplicate on 96-well reaction plates with the GeneAmp PCR 9700 machine (Applied Biosystems) using TaqMan Reverse Transcription Reagent containing Multiscribe Reverse Transcriptase (50 U/μl) (Applied Biosystems). Twofold serial dilutions of total RNA were made for efficiency calculations. Five serial dilutions (1000 – 63 ng) in triplicates were analyzed by qPCR in separate sample wells and the resulting crossing thresholds (Cts) recorded. Total RNA input was 500 ng in each reaction for all genes. No template control (ntc) and RT-control (a duplicate RNA sample analysis where only the RT enzyme is left out) reactions were run for quality assessment. RT-controls were not performed for every individual sample, but were run for each assay or gene, with the same sample as used to make the dilution curves on the 96 well plates. Reverse transcription was performed at 48°C for 60 min by using oligo dT primers (2.5 μM) for all genes in 30 μl total volume. The final concentration of the other chemicals in each RT reaction was: MgCl₂(5.5 mM), dNTP (500 mM of each), TaqMan RT buffer (1×), RNase inhibitor (0.4 U/μl) and Multiscribe reverse transcriptase (1.67 U/μl).</p>", "<p>2.0 μl cDNA from each RT reaction for all genes was transferred to a new 96-well reaction plate and the qPCR run in 20 μl reactions on the LightCycler^®480 Real-Time PCR System (Roche Applied Sciences, Basel, Switzerland). qPCR was performed by using SYBR Green Master Mix (LightCycler 480 SYBR Green master mix kit; Roche Applied Sciences), which contains FastStart DNA polymerase and gene-specific primers (500 nM each). PCR was achieved with initial denaturation and enzyme activation for 5 min at 95°C, followed by 40 cycles of 10 s denaturation at 95°C, 20 s annealing at 60°C and 30 s elongation at 72°C. The <italic>geNorm </italic>VBA applet for Microsoft Excel was used to determine a normalization factor from the three examined reference genes used to calculate mean normalized expression (MNE) for ACTB, EF1A_Band ARP. The Ct values were transformed to quantities using standard curves, according to the <italic>geNorm </italic>manual [##REF##12184808##21##]. <italic>geNorm </italic>determines the individual stability of a gene within a pool of genes, and calculates the stability according to the similarity of their transcription profile by pair-wise comparison, using the geometric mean as a normalizing factor. The gene with the highest M, i.e. the least stable gene, is then excluded in a stepwise fashion until the most stable genes are determined. Here a normalizing factor based on all three examined reference genes was used to calculate the MNE.</p>", "<p>Independent and a priori of the microarray analysis, the transcriptional levels of two additional genes that were assumed to be affected by the EB treatment were quantified by qPCR. In this examination, mRNA levels were quantified in 10 individuals from each group, as opposed to n = 6 in the microarray and subsequent qPCR verification analysis. The PCR primers and probes used to quantify these transcripts were based on Genbank sequences not included on the cGRASP array. PCR primer sequences used for quantification of the genes encoding β-actin, EF1A_Band ARP, used as reference genes, and HSP70 and GST π, were based on the following Genbank accession numbers [GenBank:<ext-link ext-link-type=\"gen\" xlink:href=\"BG933897\">BG933897</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"BG933853\">BG933853</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"AY255630\">AY255630</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"AJ632154\">AJ632154</ext-link>;<ext-link ext-link-type=\"gen\" xlink:href=\"BQ036247\">BQ036247</ext-link>], respectively. TaqMan 3'-Minor groove binder-DNA (MGB) probes were used to quantify these genes as described by Olsvik et al. [##REF##16293192##22##]. Analyzed with <italic>geNorm </italic>[##REF##12184808##21##], EF1A_Bwas found to be the most stable reference gene, and therefore used to calculate mean normalized expression with the <italic>qGene </italic>tool [##REF##12074169##23##]. Except for the β-actin and EF1A_Bassays, the PCR primers or probes did not span exon-exon borders. All RNA samples were therefore treated with DNase (Ambion) according to the manufacturers instructions. Amplified PCR products were sequenced as described above and subsequently compared to the database using BLAST to ensure that the correct mRNAs were analyzed.</p>", "<title>Statistics</title>", "<p>The GraphPad Prism 4.0 (GraphPad Software, Inc., San Diego, CA, USA) and J-Express Pro (Molmine, Bergen, Norway) software were used for the statistical analyses in this work. Linear regression and correlation analysis were performed with GraphPad Prism, whereas significance of microarray (SAM) and gene set enrichment analysis (GSEA) were performed with J-Express Pro. A wide range of statistics can be used to calculate differential transcription between two groups. T-test and S-score (regularized t-score) that is used in SAM [##REF##11309499##17##] are commonly used tests. SAM was used here because it is well adapted to microarrays and reports q-values for assessment of statistical significance of the results after correcting for multiple testing. Gene set enrichment analysis (GSEA) calculates an enrichment score (ES) for a given gene set using rank of genes and infers statistical significance of each ES against ES background distribution calculated by permutation of the original data set [##REF##16199517##18##,##REF##15941488##24##]. For qPCR validation an alpha level of 0.05 was considered significant, while for SAM and GSEA a threshold of 10% false discovery rate was used to control for multiple testing in the genome wide data analysis.</p>" ]

[ "<title>Results</title>", "<title>Pharmacokinetics</title>", "<p>The concentrations of EB in liver, muscle and skin at days 7, 14 and 35 after the initiation of emamectin benzoate medication are shown in Fig. ##FIG##1##2##. At day 7 the mean concentration of EB in samples of liver was 33 ng/g, whereas the mean concentrations in muscle were 1 ng/g. The skin did not contain EB in concentrations above the level of detection (LOD) at day 7. At day 14 the mean concentrations in liver, muscle and skin were 9002, 81 and 369 ng/g, respectively. The corresponding mean concentrations at day 35 were 4902, 34 and 258 ng/g respectively. Overall, the EB concentrations were highest at day 14, and had dropped by day 35.</p>", "<title>Gene expression profiling data</title>", "<p>The microarray data revealed only small alterations in transcript levels in the EB-medicated fish compared to the control at day 7, 14 and 35. The SAM analysis showed that only three genes were significantly differentially expressed at day 7; type IV antifreeze protein precursor, MHC class I antigen alpha chain BL3-7 and an unknown gene. At day 14 only two genes displayed differential transcription levels, thrombospondin-4 precursor and purine nucleoside phosphorylase. Correspondence analysis (CA) is used to look for the greatest co-variances (between samples and genes) in the data. The plot gives a global view of the data and can reveal clustering of samples according to their biological groups. At day 7, the CA plot showed that there is a tendency of separation of the EB-medicated and the control groups (Fig. ##FIG##2##3A##). Since the pharmacokinetic measurements reveal the highest EB concentration in the liver at day 14, we expected to see more differences between the two groups at this time point. Although it was not possible to draw a straight line between the points to separate the two groups, the CA plot clearly showed a tendency of separation between the two groups at day 14 (Fig. ##FIG##2##3B##). On the contrary, there did not seem to be major differences between the two groups on day 35 based on the global CA plot. The microarray data has been submitted to ArrayExpress with MIAME required documentation and is available under the accession number E-BASE-9.</p>", "<title>Gene set enrichment analysis</title>", "<p>The overall effects of EB treatment on hepatic transcriptional levels were modest, which may have reduced the significance of biologically relevant genes because their signal intensities were relatively low. It was therefore decided to evaluate the data using the newest Gene Ontology annotations of the arrayed probes to identify significant biological changes. Table ##TAB##1##2## shows gene sets up-regulated at day 7, ordered by the normalized enrichment score, with a false discovery rate (FDR) cutoff of approximately 10%, meaning that we expected a maximum of 1 out of 10 gene sets to be false positives. Probes annotated to the same gene were not collapsed before performing GSEA that resulted in the FDR values shown in Table ##TAB##1##2##. Multiple probes on the array mapped to the same gene in a gene set will produce more significant FDR values, but as long as the Atlantic salmon genome is relatively poorly annotated, i.e. with unknown gene function, isoforms and splice variants, this strategy was selected in order not to lose valuable biological information. By collapsing data at the level of gene symbols, one risks an unintended merging of information from every pair of paralogue genes in the salmon genome. On the other hand, by not collapsing the data, one risks the pitfall of some gene sets being favored in the statistical calculation due to several probes for the same gene contributing to a particular gene set. A similar biological picture of inflammation and oxidative stress was also seen in the collapsed data set, but not at the same 10% FDR level of significance. Up-regulated gene sets at day 14 are shown in Table ##TAB##2##3##. No gene sets were significantly down-regulated at day 7 or at day 14. Table ##TAB##3##4## shows up- and down-regulated gene sets at day 35, again with a FDR cutoff of approximately 10%.</p>", "<title>qPCR verification</title>", "<p>The qPCR results supported the microarray data (Table ##TAB##0##1##), with differences only in the scale of estimated up-regulation or down-regulation. Even with the small fold changes in transcriptional levels observed in this experiment there was a significant correlation between the microarray and the qPCR data (Pearson correlation, r²= 0.92, P &lt; 0.0001; Fig. ##FIG##3##4##).</p>", "<p>Independent of the microarray data, the transcriptional levels of two genes encoding stress-responsive proteins were quantified. HSP70 and GST are both well known to respond to external stress in animals, and have often been used as biomarkers. At day 7, the transcriptional levels of both HSP70 (2-way ANOVA, P &lt; 0.01) and GST (2-way ANOVA, P &lt; 0.05) were higher in the control group compared to the EB-treated group (Fig. ##FIG##4##5A## and ##FIG##4##5B##). No significant differences were seen at day 14, whereas both genes showed significantly higher mRNA levels at 35 day in the EB-treated groups compared to the control groups (2-way ANOVA; HSP70, P &lt; 0.05, GST, P &lt; 0.01).</p>" ]

[ "<title>Discussion</title>", "<p>Very few genes were significantly differentially regulated in liver (the major detoxifying organ) of EB-medicated fish compared to the control fish at the end of the medication period (day 7), seven days after the end of medication (day 14) and 28 days after the end of the medication (day 35), analyzed by a two class unpaired SAM analysis. Only small fold-change alterations were found in liver, less than two for most of the genes. The results suggest that a standard seven-day treatment with orally administered EB during sea lice treatment (50 μg/kg fish) has only modest physiological impacts on Atlantic salmon.</p>", "<p>According to EU legislation the Maximum residue limit (MRL) for EB in fish products for human consumption is 100 ng/g. In all examined tissues the highest EB levels were measured at day 14, seven days after the end of the treatment period. Even at this time point, the EB levels in muscle were below the MRL, suggesting that filet, with the skin removed, is within accepted limits throughout the medication period. The liver in particular, accumulated much higher amounts of EB; at day 14 the level was 9002 ng/g, whereas the concentration in skin was 369 ng/g. These concentrations are in line with earlier published results from examinations of EB-treated Atlantic salmon [##REF##15053560##9##,##REF##15720522##12##]. In a distribution study, Sevatdal et al. [##REF##15720522##12##] reported the highest concentrations in excretory organs, liver and kidney, using autoradiography. High activity in bile suggested that this is the major excretory route. In contrast to our results, they found the highest quantity in liver at Day 7, the last day of administration, whereas in kidney the highest quantities were seen at day 28. Their experiment was performed at higher ambient water temperatures (15–19°C) as compared to the temperature applied in our study (9°C). This may explain the slower distribution of EB to the liver in our experiment. Our results clearly show that EB is easily accumulated in liver of Atlantic salmon and that residues remain in this organ for many weeks. Potential transcriptional effects of EB administration in the fish should therefore most likely be seen in the liver at the end of the medication period or seven days after the end of the treatment.</p>", "<p>Gene set enrichment analysis (GSEA) is an analysis method that evaluates the expression of biological pathways on a priori defined gene sets, e.g. biological pathways, rather than looking at individual genes, to identify significant biological changes in microarray data sets [##REF##16199517##18##]. GSEA is therefore especially useful when the transcriptional changes in a given microarray data set are minimal or moderate. GSEA has been applied widely as a tool for gene-set analysis using Gene Ontology (GO) terms. Atlantic salmon is currently not covered by the Gene Ontology Consortium. However GO information is included in the cGrasp annotation file, which contains annotations as of August 2007.</p>", "<p>At the end of the medication period (Day 7), nine gene sets were found to be up-regulated (FDR level of 10%) in the treatment group compared to the control group. Six of these gene sets consist of genes encoding proteins involved in protein folding, i.e. isomerase and oxidoreductase activities, partly overlapping between the various gene sets. These proteins can also act as chaperones. Protein disulfide isomerase activity (molecular function: GO:0003756) ranked number one. Among the proteins ranked in these seven gene sets are protein disulfide isomerase precursors (PDI) A2 (PDIA2), A3 (PDIA3) and A6 (PDIA6), sequestosome-1 (Sqstm-1), PDI prolyl 4-hydroxylase subunit beta (P4HB), arginyl-tRNA synthetase (RARS), prostaglandin E synthase 3 (PTGES3), phosphoglycerate mutase 1 (PGAM1), ADP-ribosylation factor GTPase activating protein 3 (ARFGAP3) and arfaptin-1 (ARFIP1). Also included in the top gene set is CYP1A, the major phase I enzyme in the cytochrome P450 system, an enzyme regulated by a number of physiological conditions and xenobiotics. The CYP system is a central catalyst of oxidative reactions including hydroxylation, epoxidation and dealkylation. Although the constitutive level of CYP1A in fish is low, several factors, exogenous as well as endogenous, can affect the CYP1A expression in fish [##REF##7786195##25##]. The major phase I metabolic pathway of ivermectin and EB in rainbow trout and Atlantic salmon is demethylation [##REF##15053560##9##,##UREF##11##26##]. This may explain the induction of the CYP1A system found in this study. Protein disulfide isomerases are endoplasmic reticulum (ER) resident proteins that catalyze the formation, reduction, and isomerization of disulfide bonds in proteins and are thought to play a role in folding of disulfide-bonded proteins [##REF##7556671##27##]. The majority of disulfide-linked cytosolic proteins are thought to be enzymes that transiently form disulfide bonds while catalyzing redox processes. Cumming et al. [##REF##15031298##28##] recently showed that reactive oxygen species (ROS) can act as signaling molecules by promoting the formation of disulfide bonds within or between redox-sensitive proteins. Our results suggest that EB treatment may have mediated oxidative stress in the liver, a finding, however, not supported by the levels of HSP70 mRNA at Day 7 (quantified by qPCR, Fig. ##FIG##4##5A##). On the contrary, HSP70 mRNA expression was significantly higher in the control group at day 7, indicating that the control fish might have been stressed during the first 7 days of the experiment. Only at day 35 was the HSP70 mRNA level significantly higher in the medicated group. Heat shock proteins are a family of highly conserved proteins that protect the cells against cytotoxic effects of protein degradation [##UREF##12##29##]. Many types of external stress can induce HSPs in fish, including oxidative stress [##UREF##13##30##,##REF##14740253##31##], even though their value as biomarkers of various form of stress in fish has been questioned [##REF##12600675##32##]. Judged by the enriched gene sets at day 35, oxidative stress seems to have been a transient response, since none of these gene sets contained HSPs.</p>", "<p>Neither GST π showed increased transcriptional levels at day 7 (Fig. ##FIG##4##5B##); only at day 35 was the transcriptional level of GST significantly higher in the EB-treated group compared to the control group. The GSTs are a family of biotransforming enzymes that protect cells against injury from a number of endogenous and environmental chemicals. Trute et al. [##REF##17184855##33##] characterized GSTs in Coho salmon (<italic>Oncorhynchus kisutch</italic>). They found two major GST isoforms in liver, the π and θ-class GSTs, but noted that they might have a limited capacity to conjugate substrates of various toxicants and endogenous compounds associated with cellular oxidative stress. We have recently shown that the GST π class is inducible by β-naphthoflavone in Atlantic salmon [##REF##18053248##34##]. The results presented here suggest that that the π class GST is inducible by EB in Atlantic salmon and that EB may undergo glutathione conjugation. This metabolite has however not yet been described in fish.</p>", "<p>The other three gene sets up-regulated at Day 7 in the EB-medicated fish consist of genes encoding proteins involved in protein modification processes (GO:0006464), i.e. peptidyl-asparagine modification [GO:0018196]. Proteins encoded by genes in these gene sets include among others dolichyl-diphosphooligosaccharide-protein glycosyltransferase (defender against cell death 1, DAD1) and various DAD1 subunits, keratinocyte-associated protein 2 (KRTCAP2), strumpellin (KIAA0196), alpha-1,6-mannosyl-glycoprotein 2-beta-N-acetylglucosaminyltransferase (Mgat2), arginine/serine-rich coiled coil protein 1 (RSRC1) and cytochrome c oxidase subunit-1 (MT-CO1). DAD1 was initially identified as a negative regulator of apoptosis in the BHK21-derived tsBN7 cell line, and is a subunit of the mammalian oligosaccharyltransferase [##REF##8413235##35##]. It has been shown that loss of the DAD1 protein triggers apoptosis [##REF##8413235##35##]. The thrombospondin-4 precursor (THBS4), belonging to the thrombospondin family, a group of proteins involved in the positive regulation of apoptosis, was significantly down-regulated at day 7, verified by qPCR analysis. These findings suggest that EB treatment may have affected the regulation of apoptosis. Although involved in a number of biological processes, the proteins encoded by the genes comprising these two pathways, suggest that EB treatment might have affected protein stability and folding at day 7, possible via induced oxidative stress.</p>", "<p>The most significant up-regulated gene sets at day 14 suggest that EB treatment induced an inflammatory response (prostaglandin biosynthetic process GO:0001516) in the liver. Proteins encoded by genes in the top six gene sets include prostaglandin E synthase 3 (PTGES3), HLA class II histocompatibility antigen gamma chain (CD74), H-2 class II histocompatibility antigen gamma chain (Cd74), H-2 class II histocompatibility antigen, A-B alpha chain precursor (H2-Aa), fibrinogen gamma chain precursor (Fqq), myosin-9 (Myh9), hematopoietic SH2 domain-containing protein (Hsh2d), zinc finger protein 706 (ZFP706) and 15-hydroxyprostaglandin dehydrogenase (NAD⁺) (Hpgd). Prostanoids, including eicosanoids and metabolites of eicosapolyenoic fatty acids, are not stored by cells but rather synthesized in many cell types in response to cell-specific proteolytic or hormonal stimuli [##REF##2655580##36##]. These processes are usually receptor-mediated, but may also be elicited by mechanical stresses on cells [##REF##2655580##36##]. Up-regulation of prostanoids further suggests that EB treatment mediated oxidative stress, as free radicals may oxidize unsaturated fatty acids [##REF##9478043##37##], i.e. eicosanoids. Surprisingly, the prostanoid pathways were down-regulated at day 35, suggesting a counter-reaction in gene transcription.</p>", "<p>Several gene sets were differentially changed at day 35, indicating that EB still affected transcription in hepatic cells one month after the end of the medication period. Protein dimerization activity (GO:0046983) was listed as the most up-regulated gene set. Also up-regulated was endonuclease activity (GO:0048256). These findings suggest that EB treatment affected protein binding and nucleotide cleavage even at day 35, although further examinations are needed in order to elucidate to long-term effects of EB medication in salmon.</p>", "<p>qPCR is a commonly used validation tool for microarray analysis. Microarray and qPCR data often disagree, and no standard definition for validation exists [##REF##17242735##38##]. It is well documented that both qPCR and microarray analysis have inherent pitfalls that may influence transcriptional levels quantified with each method. In this work we picked 8 of the most significant genes from the SAM analysis for qPCR verification, of which most were changed less than 2-fold. The qPCR data were in line with the array data, although the down-regulated genes showed higher discrepancy than the up-regulated genes, for an unknown reason.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, this study has shown that a standard seven-day EB treatment has only modest effects on the transcription of genes in liver of Atlantic salmon. Based on GSEA, the medication seems to have produced a temporary oxidative stress response that appeared to affect protein stability and folding, followed by a secondary inflammation.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Emamectin benzoate (EB) is a dominating pharmaceutical drug used for the treatment and control of infections by sea lice (<italic>Lepeophtheirus salmonis</italic>) on Atlantic salmon (<italic>Salmo salar </italic>L). Fish with an initial mean weight of 132 g were experimentally medicated by a standard seven-day EB treatment, and the concentrations of drug in liver, muscle and skin were examined. To investigate how EB affects Atlantic salmon transcription in liver, tissues were assessed by microarray and qPCR at 7, 14 and 35 days after the initiation of medication.</p>", "<title>Results</title>", "<p>The pharmacokinetic examination revealed highest EB concentrations in all three tissues at day 14, seven days after the end of the medication period. Only modest effects were seen on the transcriptional levels in liver, with small fold-change alterations in transcription throughout the experimental period. Gene set enrichment analysis (GSEA) indicated that EB treatment induced oxidative stress at day 7 and inflammation at day 14. The qPCR examinations showed that medication by EB significantly increased the transcription of both HSP70 and glutathione-S-transferase (GST) in liver during a period of 35 days, compared to un-treated fish, possibly via activation of enzymes involved in phase II conjugation of metabolism in the liver.</p>", "<title>Conclusion</title>", "<p>This study has shown that a standard seven-day EB treatment has only a modest effect on the transcription of genes in liver of Atlantic salmon. Based on GSEA, the medication seems to have produced a temporary oxidative stress response that might have affected protein stability and folding, followed by a secondary inflammatory response.</p>" ]

[ "<title>Authors' contributions</title>", "<p>PAO and BTL planned and designed the experiment. PAO carried out the transcriptional analysis and drafted the manuscript. KKL and EM were involved in qPCR and microarray work. BTL and OBS made the pharmacokinetic study. KP and AKS were involved in experimental design and statistical analysis of the microarray experiments. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank Rolf Hetlelid Olsen for help with fish handling and medication. Atle van Beelen Granlund, the Norwegian Microarray Consortium, Trondheim, is thanked for doing the microarray hybridizations. The authors also would like to thank Audun Høylandskjær, Merat Behzadzadeh and Lene Kristin Støten for excellent analytical work. Ben Koop and Willie Davidson (cGRASP <email>web.uvic.ca/grasp</email>), University of Victoria, Canada, are acknowledged for providing the cGRASP arrays.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Experimental design. Treatment, sampling and number of fish used for gene transcription analysis. Total number of individuals sampled, number of samples used for microarray analysis (MA) and qPCR (PCR) are given for each sampling time. A total of 100 Atlantic salmon were used in the experiment. RNA was extracted from 70 individuals, 10 from each of the 7 groups. For microarray (MA, n = 6) and qPCR verification analysis the same 6 individuals were used; a total of 42 samples were analyzed, with 6 biological replicates from each group (3 males and 3 females). For array-independent qPCR analysis of HSP70 and GST, n = 10 in each group (total n = 70). EB = Emamectin benzoate.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Pharmacokinetics. Uptake and drug residues of EB in Atlantic salmon, (<italic>Salmo salar L</italic>.), administered a standard daily oral dose of 50 μg/kg for 7 days (mean ± SEM). The levels of EB were quantified in 6 individuals in liver (the same individuals as used for microarray analysis) and 15 individuals in muscle and skin tissues. &lt;DL: below detection limit.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Correspondence analysis (CA) of arrays after day 7 (A) and day 14 (B). C = controls, E = EB-treated. n = 6, except in the control group at day 7 (n = 4) and the control group at day 14 (n = 5).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>qPCR verification. Linear correlation between microarray and qPCR fold changes. Pur: puridine nucleoside phosphorylase, HLA: HLA class II histocompatibility antogen, gamma chain, Seq: sequestosome, Thromb: thrombospondin 4 precursor, LAIE Fc r: low-affinity immunoglobulin epsilon Fc receptor, NADH: NADH ubiquinone oxireductase chain 1, CYP2A5: cytochrome P450 2A5, CYP2B19; cytochrome P450 2B19.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p>Mean normalized expression (MNE) of A) HSP70 and B) GST in liver of Atlantic salmon (<italic>Salmo salar L</italic>.) orally medicated with the anti-salmon louse medicine SLICE (that contains 50% EB) for 7 days (mean ± SEM.). Samples were taken at day 0 (start of administration), day 7 (end of oral administration), day 14 and day 35. Analyzed by 2-way ANOVA. Overall ANOVA P-value shown in each graph. Significant differences at each time-point are also shown in the graphs. n = 10 in all groups except control day 35 where n = 7.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>PCR primers and TaqMan MGB probes, Genbank accession numbers, amplicon sizes and fold changes (microarray and qPCR verification) for the studied genes.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Gene</bold></td><td align=\"left\"><bold>Accession no.</bold></td><td align=\"left\"><bold>Forward primer (5'-3')</bold></td><td align=\"left\"><bold>Reverse primer (5'-3')</bold></td><td align=\"left\"><bold>TaqMan MGB probe</bold></td><td align=\"center\"><bold>Amplicon size (bp)</bold></td><td align=\"center\"><bold>Microarray</bold></td><td align=\"center\"><bold>qPCR</bold></td></tr></thead><tbody><tr><td align=\"left\">Thrombospondin 4 precursor Day 14</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CB509633\">CB509633</ext-link></td><td align=\"left\">GCAGCGGTACTTTAGGTTGGA</td><td align=\"left\">ATCAGGGCCCGTTTCTATGA</td><td/><td align=\"center\">141</td><td align=\"center\">-1.6</td><td align=\"center\">-1.7</td></tr><tr><td align=\"left\">Purine nucleoside phosphorylase Day 14*</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CB514814\">CB514814</ext-link></td><td align=\"left\">GCCCCCTTCATGGGTACAC</td><td align=\"left\">AACGCCTGAACGAACGAATG</td><td/><td align=\"center\">135</td><td align=\"center\">2.1</td><td align=\"center\">1.6</td></tr><tr><td align=\"left\">CYP2B19 Day 7</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CA053315\">CA053315</ext-link></td><td align=\"left\">AGCCTGTGACCTCTCCACAGTAA</td><td align=\"left\">CGGCACAAAACCTCCAGAAG</td><td/><td align=\"center\">134</td><td align=\"center\">-3.2</td><td align=\"center\">-2.2</td></tr><tr><td align=\"left\">CYP2A5 Day 7</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CB491960\">CB491960</ext-link></td><td align=\"left\">AGGTTTGGTGCCGGTGAAA</td><td align=\"left\">ATGATGGATTCTTTGCTTTTGGA</td><td/><td align=\"center\">125</td><td align=\"center\">-3.2</td><td align=\"center\">-1.7</td></tr><tr><td align=\"left\">Low affinity immunoglobulin epsilon Fc receptor Day 14*</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CB511007\">CB511007</ext-link></td><td align=\"left\">CCACTCACAGGGCACATCAA</td><td align=\"left\">GTGGTCAGATGGGTCCAGATTT</td><td/><td align=\"center\">133</td><td align=\"center\">2.8</td><td align=\"center\">2.1</td></tr><tr><td align=\"left\">NADH-ubiquinone oxireductase chain 1 Day 7</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CB488966\">CB488966</ext-link></td><td align=\"left\">GGCCGGCACGAGTAGTCA</td><td align=\"left\">GGCAGTGGCACAAACCATTT</td><td/><td align=\"center\">133</td><td align=\"center\">-3.3</td><td align=\"center\">-1.2</td></tr><tr><td align=\"left\">Sequestosome-1 Day 14*</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CA056074\">CA056074</ext-link></td><td align=\"left\">GGGACAGAAAGAGAAGGCAGTATT</td><td align=\"left\">GCCCTGGACACCATCCACTA</td><td/><td align=\"center\">131</td><td align=\"center\">1.3</td><td align=\"center\">1.1</td></tr><tr><td align=\"left\">HLA class II histocompatibility antigen, gamma chain Day 14*</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CK990815\">CK990815</ext-link></td><td align=\"left\">TTATATGCTGTCCGAAGGCAAA</td><td align=\"left\">CCCTCCCCCAAAAAATACACA</td><td/><td align=\"center\">141</td><td align=\"center\">1.1</td><td align=\"center\">1.2</td></tr><tr><td align=\"left\">Heat shock protein 70</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"AJ632154\">AJ632154</ext-link></td><td align=\"left\">TCAACGATCAGGTCGTGCAA</td><td align=\"left\">CGTCGCTGACCACCTTGAA</td><td align=\"left\">CCGACATGAAGCACTGG</td><td align=\"center\">141</td><td/><td/></tr><tr><td align=\"left\">Glutathione S-transferase pi</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BQ036247\">BQ036247</ext-link></td><td align=\"left\">ATTTTGGGACGGGCTGACA</td><td align=\"left\">CCTGGTGCTCTGCTCCAGTT</td><td align=\"left\">TTCTCGACAAAGCTC</td><td align=\"center\">81</td><td/><td/></tr><tr><td align=\"left\">β-actin</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BG933897\">BG933897</ext-link></td><td align=\"left\">CCAAAGCCAACAGGGAGAAG</td><td align=\"left\">AGGGACAACACTGCCTGGAT</td><td align=\"left\">TGACCCAGATCATGTTT</td><td align=\"center\">91</td><td/><td/></tr><tr><td align=\"left\">EF1AB</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BG933853\">BG933853</ext-link></td><td align=\"left\">TGCCCCTCCAGGATGTCTAC</td><td align=\"left\">CACGGCCCACAGGTACTG</td><td align=\"left\">CCAATACCGCCGATTTT</td><td align=\"center\">59</td><td/><td/></tr><tr><td align=\"left\">ARP</td><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"AY255630\">AY255630</ext-link></td><td align=\"left\">TCATCCAATTGCTGGATGACTATC</td><td align=\"left\">CTTCCCACGCAAGGACAGA</td><td align=\"left\">CAAATGTTTCATTGTCGGCG</td><td align=\"center\">101</td><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Gene sets significantly up-regulated after 7 days of medication (day 7).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Rank</bold></td><td align=\"left\"><bold>Gene Sets – Up-regulated</bold></td><td align=\"center\"><bold>Size</bold></td><td align=\"center\"><bold>Nom P-value</bold></td><td align=\"center\"><bold>FDR (%)</bold></td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"left\">Protein disulfide isomerase activity</td><td align=\"center\">26</td><td align=\"center\">0.0</td><td align=\"center\">1.72</td></tr><tr><td align=\"center\">2</td><td align=\"left\">Intramolecular oxidoreductase activity, transposing S-S bonds</td><td align=\"center\">26</td><td align=\"center\">0.0</td><td align=\"center\">0.86</td></tr><tr><td align=\"center\">3</td><td align=\"left\">Peptidyl-asparagine modification</td><td align=\"center\">16</td><td align=\"center\">0.0</td><td align=\"center\">3.2</td></tr><tr><td align=\"center\">4</td><td align=\"left\">Protein amino acid N-linked glycosylation via asparagine</td><td align=\"center\">16</td><td align=\"center\">0.0</td><td align=\"center\">2.4</td></tr><tr><td align=\"center\">5</td><td align=\"left\">Intramolecular oxidoreductase activity</td><td align=\"center\">36</td><td align=\"center\">0.0</td><td align=\"center\">2.89</td></tr><tr><td align=\"center\">6</td><td align=\"left\">Protein localization</td><td align=\"center\">37</td><td align=\"center\">0.0</td><td align=\"center\">11.7</td></tr><tr><td align=\"center\">7</td><td align=\"left\">Isomerase activity</td><td align=\"center\">52</td><td align=\"center\">0.0</td><td align=\"center\">10.9</td></tr><tr><td align=\"center\">8</td><td align=\"left\">Peptidyl-amino acid modification</td><td align=\"center\">23</td><td align=\"center\">0.0</td><td align=\"center\">10.79</td></tr><tr><td align=\"center\">9</td><td align=\"left\">Oligosaccharyl transferase complex</td><td align=\"center\">19</td><td align=\"center\">0.0</td><td align=\"center\">10.66</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Gene sets significantly up-regulated 7 days after the end of the medication period (day 14).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Rank</bold></td><td align=\"left\"><bold>Gene Sets – Up-regulated</bold></td><td align=\"center\"><bold>Size</bold></td><td align=\"center\"><bold>Nom P-value</bold></td><td align=\"center\"><bold>FDR (%)</bold></td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"left\">Prostanoid biosynthetic process</td><td align=\"center\">19</td><td align=\"center\">0.0</td><td align=\"center\">0.38</td></tr><tr><td align=\"center\">2</td><td align=\"left\">Prostaglandin biosynthetic process</td><td align=\"center\">19</td><td align=\"center\">0.0</td><td align=\"center\">0.19</td></tr><tr><td align=\"center\">3</td><td align=\"left\">Cytokine binding</td><td align=\"center\">21</td><td align=\"center\">0.0</td><td align=\"center\">0.37</td></tr><tr><td align=\"center\">4</td><td align=\"left\">Regulation of macrophage activation</td><td align=\"center\">15</td><td align=\"center\">0.0</td><td align=\"center\">0.44</td></tr><tr><td align=\"center\">5</td><td align=\"left\">Ecosanoid biosynthetic process</td><td align=\"center\">29</td><td align=\"center\">0.0</td><td align=\"center\">0.49</td></tr><tr><td align=\"center\">6</td><td align=\"left\">Ecosanoid metabolic process</td><td align=\"center\">29</td><td align=\"center\">0.0</td><td align=\"center\">0.41</td></tr><tr><td align=\"center\">7</td><td align=\"left\">Carbohydrate binding</td><td align=\"center\">34</td><td align=\"center\">0.0</td><td align=\"center\">0.47</td></tr><tr><td align=\"center\">8</td><td align=\"left\">Macrophage activation</td><td align=\"center\">18</td><td align=\"center\">0.0</td><td align=\"center\">0.6</td></tr><tr><td align=\"center\">9</td><td align=\"left\">Myeloid leukocyte activation</td><td align=\"center\">18</td><td align=\"center\">0.0</td><td align=\"center\">0.54</td></tr><tr><td align=\"center\">10</td><td align=\"left\">Sugar binding</td><td align=\"center\">29</td><td align=\"center\">0.0</td><td align=\"center\">0.98</td></tr><tr><td align=\"center\">11</td><td align=\"left\">Monosaccharide binding</td><td align=\"center\">16</td><td align=\"center\">0.0</td><td align=\"center\">1.79</td></tr><tr><td align=\"center\">12</td><td align=\"left\">Glutamate dehydrogenase [NAD(P)+] activity</td><td align=\"center\">14</td><td align=\"center\">0.0</td><td align=\"center\">2.99</td></tr><tr><td align=\"center\">13</td><td align=\"left\">Leukocyte activation</td><td align=\"center\">37</td><td align=\"center\">0.0</td><td align=\"center\">3.58</td></tr><tr><td align=\"center\">14</td><td align=\"left\">Activation of MAPK activity</td><td align=\"center\">12</td><td align=\"center\">0.0</td><td align=\"center\">4.6</td></tr><tr><td align=\"center\">15</td><td align=\"left\">Intracellular protein transport</td><td align=\"center\">41</td><td align=\"center\">0.0</td><td align=\"center\">5.8</td></tr><tr><td align=\"center\">16</td><td align=\"left\">Protein amino acid N-linked glycosylation via asparagines</td><td align=\"center\">17</td><td align=\"center\">0.0</td><td align=\"center\">5.94</td></tr><tr><td align=\"center\">17</td><td align=\"left\">Peptidyl-asparagine modification</td><td align=\"center\">17</td><td align=\"center\">0.0</td><td align=\"center\">5.59</td></tr><tr><td align=\"center\">18</td><td align=\"left\">Oxidoreductase activity, acting on the CH-NH2 group of donors, NAD or NADP as acceptor</td><td align=\"center\">17</td><td align=\"center\">0.0</td><td align=\"center\">5.54</td></tr><tr><td align=\"center\">19</td><td align=\"left\">Mannose binding</td><td align=\"center\">12</td><td align=\"center\">0.01</td><td align=\"center\">5.34</td></tr><tr><td align=\"center\">20</td><td align=\"left\">Antigen processing and presentation of exogenous peptide antigen via MHC class II</td><td align=\"center\">24</td><td align=\"center\">0.0</td><td align=\"center\">8.97</td></tr><tr><td align=\"center\">21</td><td align=\"left\">Antigen processing and presentation of peptide antigen via MHC class II</td><td align=\"center\">24</td><td align=\"center\">0.0</td><td align=\"center\">8.55</td></tr><tr><td align=\"center\">22</td><td align=\"left\">Transition metal ion binding</td><td align=\"center\">31</td><td align=\"center\">0.0</td><td align=\"center\">8.69</td></tr><tr><td align=\"center\">23</td><td align=\"left\">Peptidyl-amino acid modification</td><td align=\"center\">24</td><td align=\"center\">0.01</td><td align=\"center\">10.94</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Gene sets significantly up-regulated or down-regulated 28 days after the end of the medication period (day 35).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Rank</bold></td><td align=\"left\"><bold>Gene Sets – Up-regulated</bold></td><td align=\"center\"><bold>Size</bold></td><td align=\"center\"><bold>Nom P-value</bold></td><td align=\"center\"><bold>FDR (%)</bold></td></tr></thead><tbody><tr><td/><td align=\"left\"><bold>Up-regulated</bold></td><td/><td/><td/></tr><tr><td align=\"center\">1</td><td align=\"left\">Protein dimerization activity</td><td align=\"center\">60</td><td align=\"center\">0.0</td><td align=\"center\">3.72</td></tr><tr><td align=\"center\">2</td><td align=\"left\">Second-messenger-mediated signaling</td><td align=\"center\">20</td><td align=\"center\">0.0</td><td align=\"center\">1.86</td></tr><tr><td align=\"center\">3</td><td align=\"left\">Endonuclease activity</td><td align=\"center\">21</td><td align=\"center\">0.0</td><td align=\"center\">3.31</td></tr><tr><td align=\"center\">4</td><td align=\"left\">Protein heterodimerization activity</td><td align=\"center\">29</td><td align=\"center\">0.0</td><td align=\"center\">4.75</td></tr><tr><td align=\"center\">5</td><td align=\"left\">mRNA catabolic process</td><td align=\"center\">20</td><td align=\"center\">0.0</td><td align=\"center\">4.74</td></tr><tr><td align=\"center\">6</td><td align=\"left\">mRNA catabolic process, nonsense-mediated decay</td><td align=\"center\">17</td><td align=\"center\">0.0</td><td align=\"center\">6.18</td></tr><tr><td align=\"center\">7</td><td align=\"left\">Endonuclease activity, active with either ribo- or deoxyribonucleic</td><td/><td/><td/></tr><tr><td/><td align=\"left\">acids and producing 5'-phosphomonoesters</td><td align=\"center\">19</td><td align=\"center\">0.0</td><td align=\"center\">9.22</td></tr><tr><td align=\"center\">8</td><td align=\"left\">Endoribonuclease activity, producing 5'-phosphomonoesters</td><td align=\"center\">19</td><td align=\"center\">0.0</td><td align=\"center\">8.07</td></tr><tr><td align=\"center\">9</td><td align=\"left\">Phosphoprotein phosphatase activity</td><td align=\"center\">22</td><td align=\"center\">0.0</td><td align=\"center\">7.2</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Down-regulated</bold></td><td/><td/><td/></tr><tr><td align=\"center\">1</td><td align=\"left\">Nucleobase, nucleoside, nucleotide kinase activity</td><td align=\"center\">25</td><td align=\"center\">0.0</td><td align=\"center\">0.09</td></tr><tr><td align=\"center\">2</td><td align=\"left\">Telomerase holoenzyme complex</td><td align=\"center\">24</td><td align=\"center\">0.0</td><td align=\"center\">0.66</td></tr><tr><td align=\"center\">3</td><td align=\"left\">Prostaglandin biosynthetic process</td><td align=\"center\">18</td><td align=\"center\">0.0</td><td align=\"center\">2.04</td></tr><tr><td align=\"center\">4</td><td align=\"left\">Prostanoid biosynthetic process</td><td align=\"center\">18</td><td align=\"center\">0.0</td><td align=\"center\">1.53</td></tr><tr><td align=\"center\">5</td><td align=\"left\">Kinase activity</td><td align=\"center\">41</td><td align=\"center\">0.0</td><td align=\"center\">1.33</td></tr><tr><td align=\"center\">6</td><td align=\"left\">Nucleotide kinase activity</td><td align=\"center\">12</td><td align=\"center\">0.0</td><td align=\"center\">1.63</td></tr><tr><td align=\"center\">7</td><td align=\"left\">Kinase regulator activity</td><td align=\"center\">11</td><td align=\"center\">0.0</td><td align=\"center\">2.65</td></tr><tr><td align=\"center\">8</td><td align=\"left\">Pigment granule</td><td align=\"center\">15</td><td align=\"center\">0.0</td><td align=\"center\">6.8</td></tr><tr><td align=\"center\">9</td><td align=\"left\">Melanosome</td><td align=\"center\">15</td><td align=\"center\">0.0</td><td align=\"center\">6.04</td></tr><tr><td align=\"center\">10</td><td align=\"left\">Peptide antigen transport</td><td align=\"center\">10</td><td align=\"center\">0.0</td><td align=\"center\">9.18</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>* = up-regulated genes</p></table-wrap-foot>", "<table-wrap-foot><p>Gene set enrichment analysis (GSEA) with a false discovery rate (FDR) cut-off of approximately 10%. Nominal P values are also shown, as well as gene set sizes (number of genes in each gene set). No gene sets were significantly down-regulated after 7 days of medication, with a FDR lower than about 10%.</p></table-wrap-foot>", "<table-wrap-foot><p>Gene set enrichment analysis (GSEA) with a false discovery rate (FDR) cut-off of approximately 10%. Nominal P values are also shown, as well as gene set sizes (number of genes in each gene set). No gene sets were significantly down-regulated 7 days after the end of the medication period, with a FDR lower than about 10%.</p></table-wrap-foot>", "<table-wrap-foot><p>Nominal P values are shown, as well as gene set sizes (number of genes in each gene set). Gene set enrichment analysis (GSEA) with a false discovery rate (FDR) cut-off of approximately 10%.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2210-8-16-1\"/>", "<graphic xlink:href=\"1471-2210-8-16-2\"/>", "<graphic xlink:href=\"1471-2210-8-16-3\"/>", "<graphic xlink:href=\"1471-2210-8-16-4\"/>", "<graphic xlink:href=\"1471-2210-8-16-5\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The penetration of biomass-derived ethanol (bioethanol) into the road transport fuels market has the potential to reduce greenhouse gas (GHG) emissions, improve fuel security, stimulate the agricultural sector and provide new markets for technology development and application. The 2006 global market for bioethanol was 20.2 million tonnes oil equivalent (mtoe), and was dominated by US and Brazilian production and consumption (45.4% and 43.9% of the total, respectively). Global growth (averaging 10.9% since 2001) has been fuelled predominantly through internal expansion of the juggernaut US and Brazilian programmes, but increasingly through expansion into the European and Asia-Pacific markets (see Figure ##FIG##0##1## and [##UREF##0##1##]). This trend is expected to continue with the European Biofuels Directive targeting a 10% road transport fuel market share across the EU by 2020 (approximately 37 mtoe.yr^-1, see [##UREF##1##2##]) in addition to an envisioned 30% replacement of current US petroleum consumption with biofuels by 2030 [##UREF##2##3##]. Bioethanol supply chains are anticipated to make a large contribution towards these targets through both domestic production and expanding international trade [##UREF##3##4##].</p>", "<p>Current bioethanol production utilises so-called 'first-generation' technologies, processing sugar and hydrolysed starch crops using mature fermentation and separation processes. The effectiveness of these supply chains is the subject of much debate, and is constrained by the chain energetic efficiencies (ratio of primary energy inputs to derived ethanol high heating value (HHV), 0.79 MJ_PEIMJ^-1_EtOH, see [##REF##16439656##5##]), GHG abatement potential (reduction of net CO₂emissions per unit HHV substituted, 62.5 kg_CO2GJ^-1_EtOH, see [##UREF##4##6##]) and, most significantly, the availability of feedstocks that compete for land and agricultural market resources with food crops. Given land use concerns it is unlikely that US grain ethanol production, despite yield increases, will increase beyond three times the current production level [##UREF##5##7##].</p>", "<p>Improved 'second-generation' pretreatment and fermentation technologies can alleviate this resource constraint through the utilisation of lignocellulosic (LC) biomass feedstocks. Diverse and abundant sources of LC biomass have been identified, including forestry and agricultural industry residues, dedicated energy crops and urban waste streams. The United Stated Department of Agriculture identified a potential 1.3 billion oven dry tonnes (odt) per year from US forestry and agriculture by the mid-21st century, requiring only modest changes in land use, agricultural and forestry practices [##UREF##2##3##].</p>", "<p>LC-derived bioethanol is only recently starting to penetrate the global market. Its production currently involves the application of utility-intensive dilute acid or steam-explosion pretreatment and hydrolysis technologies to a range of 'residual' feedstocks, including wood chips, wheat straw, corn stover and bagasse. Scales of between 3000 and 30,000 m³_EtOHyear^-1have been implemented at the pilot and demonstration scale, while early commercial plants of up to 200,000 m³_EtOHyear^-1are expected to come online in 2008 (see [##UREF##5##7##]). These current technologies suffer from system interactions that result in a range of undesirable downstream impacts on enzymatic and microbial conversion efficiencies, leading to low-titre concentrations and subsequently high distillation energy requirements.</p>", "<p>A document published by the US Genomics:GTL Program [##UREF##6##8##] recognises a high capacity for technological improvements in all aspects of the supply chain. These range from increases in the yield (15 to 25 odt ha^-1year^-1for high-yielding dedicated energy crops), stress tolerance and the lignin, cellulose, hemicellulose composition of energy crops, to enhanced pretreatment efficiency and greatly improved fermentation tolerance to titre concentration (40%_EtOHis considered an optimistic target). Such advances could radically improve the process through enhanced lignin recovery for downstream electricity generation and reduced utility requirements, resulting in greater energetic efficiency and surplus utility availability. This would substantially increase net energy yields from agricultural land (Table ##TAB##0##1##). It is concluded that there exists substantial technological headroom for improvement of the LC-bioethanol system based on changes in agricultural biomass sources, pre-processing and fermentation microbial communities, with a trajectory towards consolidated bio-processing (CBP) in a single vessel [##UREF##7##9##].</p>", "<p>A question not considered in the literature is the resulting impact that such technological developments in LC-bioethanol feedstocks and processing technologies will have on the structure of the supply chain. Issues of facility location, economies of scale and logistical interconnection have been studied in the literature, albeit in the limited context of single plants encompassing all process steps (pretreatment, fermentation, separation, purification) taking place at one 'central' facility and utilising current technologies (that is, dilute acid hydrolysis [##UREF##8##10##, ####REF##16719086##11##, ##REF##16439654##12##, ##UREF##9##13##, ##UREF##10##14####10##14##]). Open questions remain, namely:</p>", "<p>• What is the optimal configuration of multi-plant systems, areas of supply and demand and interconnecting logistics?</p>", "<p>• Is there potential for process decentralisation through exploiting logistical cost gaps that arise from the large variation in material energy densities observed within current and future bioethanol supply chains?</p>", "<p>The energetic density of biomass is low (3.0 to 4.6 GJ m^-3for baled and chipped poplar, respectively), resulting in high logistics costs compared with pure/intermediate ethanol concentrations (the energy density of pure ethanol is 26.8 GJ m^-3). These logistics costs act against the economies of scale available in conversion processes. This combination of factors may 'disrupt' the conventional perspectives on LC ethanol supply chains by making decentralised production infrastructures feasible, if not optimal. In such infrastructures, logistics costs would arise largely from the transport of high-energy density ethanol of intermediate purity.</p>", "<p>The key goals of this work are:</p>", "<p>• to develop a framework and methodology for assessing different spatial infrastructures of LC-bioethanol supply chains and their impact on system economics; and</p>", "<p>• to investigate the evolution of the bioethanol supply chain with the development of dedicated energy crops and improved conversion technologies.</p>", "<p>The next section details the methods applied in developing a model that characterises system economics, logistical flows and economies of scale in processing. The specific sources of data and assumptions underlying prescribed model parameters are also presented. We then present the results of an application of the model to a range of scenarios. These are followed by a detailed discussion regarding the limits of the modelling framework. The final section draws conclusions from the analysis presented.</p>" ]

[ "<title>Methods</title>", "<p>The LC-bioethanol supply chain system is assessed through the development of a spatially explicit model that combines production and logistics. This is based on the modelling approaches commonly applied in the optimisation of multi-site supply chain systems design [##UREF##11##15##,##UREF##12##16##] and operational planning [##UREF##13##17##]. The formulation builds on a model first developed and applied in the context of optimising future hydrogen infrastructures [##UREF##14##18##]. The model is formulated as a mixed-integer linear programming (MILP) model in GAMS [##UREF##15##19##] and solved to determine cost-optimal supply chain configurations. The modelling approach can be summarised as follows.</p>", "<p>Given the following input data:</p>", "<p>1) Spatial distribution of biomass supply</p>", "<p>2) Spatial distribution of energy demand (ethanol, electricity, heat)</p>", "<p>3) Material and energetic requirements of processing steps</p>", "<p>4) Technology capital and operating costs</p>", "<p>5) Distance, capacity and costs of biomass and ethanol logistics</p>", "<p>6) Market structure</p>", "<p>a. Hydrated or anhydrous ethanol market</p>", "<p>b. Commodity market prices</p>", "<p>Determine the optimal:</p>", "<p>1) Regional purchase and supply strategy</p>", "<p>2) Facility location</p>", "<p>3) Facility scale and process-unit composition</p>", "<p>4) Logistical interconnectivity and material flows</p>", "<p>5) Production costs</p>", "<p>The model formulation requires a large amount of information (input data) to be captured analytically within model parameters. The methods used to model process economics (including economies of scale), supply-demand distributions, logistics and processing performance are therefore presented. We also present mathematical formulations that are considered to have a significant impact on the model behaviour or that should be of specific interest to the reader. A concise summary of the full mathematical formulation is provided in Additional file ##SUPPL##0##1##. <italic>Current </italic>and <italic>Future </italic>scenarios are developed for feedstock and processing technology.</p>", "<title>Economics</title>", "<p>Capital costs for both processing and logistics units are annualised through a periodic payment of total installed capital cost (<italic>C</italic>) as an annuity (<italic>R</italic>) as shown in Equation 1. A capital lifetime (<italic>n</italic>) is assigned specifically to each system component. A moderate discount rate (<italic>i</italic>) of 8% is assumed, representing the risk associated with the return on investment relative to an alternative allocation of capital. This figure is lower than that used by Kaylen et al [##UREF##8##10##] (15%) in order to represent the reduced risk in bioethanol investment anticipated under increased oil prices, and in line with increasing fiscal policy support for alternative energy technologies.</p>", "<p></p>", "<p>Operating costs are assigned on an annual throughput basis (for example, in dollars per odt per year for raw materials). They account for required treatment-specific feedstocks (that is, enzymes, acids, denaturant), utilities (water, electricity, heat), labour, maintenance and overheads. Labour, maintenance and overheads are allocated between process components relative to fraction of total capital cost.</p>", "<title>Economies of scale</title>", "<p>The economies of scale available in process unit capital and operating costs represent a key cost driver of the spatial system configuration, resulting in a preference (in the absence of other factors) for large, centralised facilities. Process plant economies of scale are typically captured through a continuous power law relating plant scale (<italic>P</italic>₁) and capital cost (<italic>C</italic>₁) through a scaling factor (α) relative to a base case with plant scale <italic>P</italic>₀and capital costs <italic>C</italic>₀:</p>", "<p></p>", "<p>Econometric studies are required to determine the scale factor (α). Hamelinck et al [##UREF##7##9##] and Wooley et al [##UREF##10##14##] identified the scaling factor for individual components for both current and future LC-bioethanol technologies. This facilitates disaggregation of the plant into specific processing steps in order to allow plant scale and process-unit composition at each location to be assessed. Capital cost scale factors are identified as 0.8 for alternative hydrolysis and fermentation technologies [##UREF##7##9##]. Economies of scale in operating costs were identified by Kaylen et al [##UREF##8##10##]. They identified the significant economies of scale available in administrative plant overheads (α = 0.25) compared with those operating costs linear with production (that is, α = 1 in the case of stoichiometric pretreatment treatment reagents).</p>", "<title>Spatial distributions</title>", "<p>The hypothetical geographical area of study is discretised into a grid of homogeneous regions. We always use a 5 × 5 grid, that is, 25 regions. However, the size of each region is varied between 25, 50 and 100 km². This allows the impact of local supply and demand distributions, system boundaries and the optimal configuration of multiple-plant infrastructures to be assessed at a range of length scales. For example, an optimal plant configuration identified at the 25 km²scale may not have access to sufficient easily accessible ('endogenous') resources in order to reach a truly 'optimal' plant scale. Furthermore, the optimum at the 25 km²scale may not remain optimal when the boundary is expanded to encompass a larger region containing additional plants. The optimal scale for assessment, balancing local spatial detail with global plant interactions, can therefore be identified as that scale which first approaches the minimum unit ethanol production cost (dollars per litre). This has important implications in spatially explicit infrastructure modelling wherein spatial resolution represents the dominant computational cost.</p>", "<p>Hypothetical demand and supply scenarios are assigned through the specification of rural, semi-rural and urban land-cover types for each region. These are characterised by their agricultural land and population densities (Table ##TAB##1##2##). Values were derived from an assessment of the UK land-cover database [##UREF##16##20##] and regressed against population density derived from UK census data [##UREF##17##21##]. These values are therefore representative of UK and, more generally, European agricultural conditions. This does not affect the generality of the framework proposed here, as other regions can be considered by using different parameters. The discussion of the results, however, will necessarily be focussed on the UK and EU.</p>", "<p>Regional typologies are mapped onto the grid to generate the two 'generic' spatial distributions considered here. The <italic>Centralised </italic>distribution represents a central urban region with a peripheral semi-rural and rural boundary region. The <italic>Corner-Point </italic>distribution has the urban region located at the corner of the system, again with a peripheral semi-rural and rural boundary. This imposes a hard boundary on the urban demand epicentre, representative of a coastal or national border. These distributions are presented schematically in Figure ##FIG##1##2##.</p>", "<title>Feedstock supply</title>", "<p>A 10% fractional availability of agricultural land for biomass sourcing is assumed, approximating the current EU set-aside quota. Feedstocks are characterised in terms of their lignin, hemicellulose and cellulose fraction and the higher heating value derived from the component fractions. The <italic>Current </italic>scenario process feedstock represents a generic crop residue such as wheat straw or corn stover. Harvested yield is assumed at 5 odt ha^-1year^-1. The <italic>Future </italic>scenario feedstock is assumed to represent a high-yielding hybrid poplar. Harvested yield is assumed at 25 odt ha^-1yr^-1for a three-year coppice cycle. A summary of feedstock properties is provided in Table ##TAB##2##3##. A farm gate commodity cost of $53.9 odt^-1is assumed for both feedstocks (converted from UK cost data) in order to allow economies of scale and logistics cost drivers to be isolated.</p>", "<title>Ethanol demand</title>", "<p>Demand is assumed continuous at 2000 W per capita for electricity and heat and 980 W per capita for gasoline road-transport fuel demand [##UREF##18##22##]. Ethanol is assumed as a direct substitute for gasoline energy demand. The potential for heat provision from the ethanol refinery is limited to 10% of the regional heat demand, reflecting network installation and heat loss constraints in radial heat distribution.</p>", "<p>The calculation of absolute regional demand requires subsequent allocation of per capita demand to total regional population, itself a function of population density and absolute spatial length scale. Population density was allocated in defining each of the three regional typologies (Table ##TAB##1##2##). Despite projected US and UK population increases of approximately 45% and 7% respectively by 2050, population growth is not considered when developing the <italic>Future </italic>scenario. The spatial distribution of demand, rather than its absolute magnitude, remains the dominant driver for optimal trade-offs in the system.</p>", "<title>Process technology</title>", "<p>A generic process flowsheet for the LC-bioethanol production process is presented in Figure ##FIG##2##3##. This represents the network of feedstock, product and intermediate commodities, process technologies and their respective material and energetic interconnectivity. Incorporated process technologies and relative energetic flows are specific to the <italic>Current </italic>technology scenario.</p>", "<p>The process flowsheet is composed of the pretreatment and fermentation process (<italic>Process</italic>), which generates a low-density ethanol titre (5.0wt%_EtOH, L) from a biomass feedstock (B). The ethanol titre is concentrated through a purification train consisting of a stripping column (<italic>Stripping</italic>) to generate a medium-density intermediate (35.0wt%_EtOH, M), a rectification column (<italic>Rectification</italic>) to generate the ethanol-water azeotrope (94.0wt%_EtOH, H) and a membrane purification process (<italic>Purification</italic>) to generate the pure, anhydrous ethanol product (P). The <italic>Future </italic>scenario eliminates the need for the stripping step as fermentation titres are assumed to approach 35.0wt%_EtOHthrough developments in microbial resistance to ethanol concentration. In addition, high titres via process intensification of fermentation (for example, fermentation with simultaneous ethanol stripping [##UREF##19##23##]) have already been demonstrated.</p>", "<p><italic>Stripping </italic>(or <italic>Rectification </italic>in the <italic>Future </italic>scenario) also generates a silage residue stream (S), which contains the unconverted cellulose and lignin fractions and the process water removed in the stripping column. This is passed to a solids separation unit (<italic>Solids Separation</italic>) which generates wet fuel (WF) and waste water (W) streams. The wet fuel is subsequently dried (<italic>Drying</italic>) to generate a dry fuel (DF) which is converted into hot-utility (HU) and electricity (E) in a combined heat and power unit (CHP).</p>", "<p>The <italic>Current </italic>process technology is assumed to represent a single-stage saccharification and fermentation (SSF) process with pretreatment and fermentation conversion efficiencies of 75% and 95%, respectively. Overall conversion was assumed equal for both cellulose and hemicellulose fractions. The <italic>Future </italic>processing technology is envisaged to embody the principles of CBP with pre-processing and fermentation conversion efficiencies of 98% and 95%, respectively [##UREF##7##9##].</p>", "<p>A transition to CBP technologies will significantly reduce the capital and operating costs of processing (that is, pre-processing, hydrolysis and fermentation) by an estimated 63% (see [##UREF##7##9##]). In optimal single-plant systems, increasing unit logistics costs balance against decreasing unit process and capital costs as the scale of the system increases (see [##UREF##9##13##] for a more detailed discussion). Thus, a reduction in capital and operating cost intensity, as embodied in the transition to CBP technologies, results in a downsizing of optimal single plants. This effect is countered in this work through the assumption of increased biomass yields per unit area in the <italic>Future </italic>scenario; this serves to reduce unit logistics costs.</p>", "<title>Energy integration</title>", "<p>Feedstock composition affects the relative process energy flows (see Figure ##FIG##2##3##) through the respective allocation of feedstock HHV through pretreatment and fermentation efficiency, relative to each of the cellulose, hemicellulose and lignin fractions (assumed inert) to ethanol and residual fuel process streams. The resultant residual fraction is assumed to be combusted to provide a 25 bar steam input to a hypothetical Rankine cycle. This is designed to incorporate three pass-out turbines each generating power and steam utility at a specific pressure (11, 4 and 1 bar saturated steam). Turbine pressure ratios are scaled to match the internal process hot utility ratio requirements derived from [##UREF##7##9##]. Surplus electricity and heat represent valuable revenue streams.</p>", "<p>As the front-end (pre-processing) of current processes require a large amount of heat, it is hard to decouple this from the back-end (utility generation), in particular because heat cannot be feasibly transported over large distances. Future pre-processing methods, identified by [##UREF##7##9##], apply steam explosion and compressed liquid hot water in order to hydrolyse the cellulose and hemicellulose fractions. These technologies continue to be hot utility intensive and therefore incompatible with <italic>Process </italic>decentralisation. The potential for the development of ambient processing is therefore explored. Proposed technologies include CO₂explosion [##REF##9841652##24##], oxidative delignification (H₂O₂-catalysed enzymatic hydrolysis), and biological pretreatments (a concise review is provided by [##REF##12058826##25##]). <italic>Future </italic>scenario <italic>Process </italic>hot utility requirements are therefore assumed negligible, substantially improving net energetic efficiency.</p>", "<title>Logistics</title>", "<p>Logistics encompass all flows of mass and energy within the processing network. While this can be facilitated through pipeline or conveyor on site, it must be expanded to incorporate road, rail, pipeline and cable modes of transportation <italic>between </italic>sites (that is, located within different <italic>regions</italic>). Thus both <italic>internal </italic>and <italic>external </italic>process flows are characterised through a two-tier logistics network. Solid road transport using a 120 m³capacity trailer is assumed for feedstock biomass and both wet and dry residual fuels. Liquid road transport using 27 m³liquid tanker is assumed for dilute ethanol solutions (5%, 35% and 94% ethanol by weight) and pure ethanol. Rail logistics are not considered to be competitive owing to their high costs compared with road logistics over the relevant range of transport distances [##UREF##20##26##]. Pipeline transport is considered a feasible transport mode for all ethanol intermediate fractions, pure ethanol and wastewater. Heat is not considered mobile between regions, while electricity is assumed transported by existing electric cable at zero cost.</p>", "<p>Logistics costs (<italic>C</italic>^{<italic>L</italic>}) are modelled for each commodity in terms of duration (<italic>C</italic>^{<italic>T</italic>}) and distance (<italic>C</italic>^{<italic>D</italic>}) as</p>", "<p></p>", "<p>The parameters in Equation 3 capture annualised capital, maintenance, labour and fuel costs and general overheads. Logistics costs specific to each commodity, mode of transport, source and destination are then a function of distance (<italic>L</italic>, assuming an empty return trip), the tortuosity of each mode (<italic>τ</italic>), transfer speed (<italic>ν</italic>) and total time spent loading and unloading (<italic>LUT</italic>). Here index <italic>i </italic>represents each specific commodity while <italic>g </italic>and <italic>k </italic>represent the source and destination region respectively. Logistics for biomass collection and ethanol distribution <italic>within </italic>each region are derived from an equivalent study completed for each region type.</p>", "<title>Intermediate purity ethanol logistics</title>", "<p>In addition to the development of a framework for multi-plant infrastructure design, this work is focussed on assessing the potential for spatial decoupling of processes within the processing chain, resulting in distributed processing and centralised purification systems. The drivers for such behaviour can be characterised by two parameters: (1) the logistics ratio (LR)</p>", "<p></p>", "<p>which represents the ratio between biomass and ethanol logistics costs (applicable at a range of purities); and (2) the economies of scale ratio (EoSR)</p>", "<p></p>", "<p>which represents the ratio between the economies of scale factor (<italic>α</italic>) for front-end <italic>Process </italic>and downstream purification stages.</p>", "<p>A decrease in <italic>LR </italic>can be achieved through the availability of pipeline technologies for both pure ethanol distribution (this is already standard practice in Brazil) and intermediate titres (that is, dilute 'crude' ethanol). The feasibility of pipeline distribution for slurries exhibiting solids concentrations of up to 30% on a wet basis was investigated by Kumar et al [##REF##15607196##27##] for the case of corn stover transportation. Pipeline operating costs were assumed as $3.07× 10^-3m^-3km^-1for pure ethanol [##REF##16719086##11##] and $9.29 × 10^-2odt^-1km^-1for a slurry representative of fermentation broths containing the residual lignin [##REF##15607196##27##].</p>", "<p>An increase in the EoSR can be envisioned to represent some degree of efficient downscaling and modularisation of the pretreatment and fermentation processes relative to downstream purification and utility generation. This would imply a shift in the capital and operating cost structure, in particular regarding labour and administrative overheads, such that costs are less dependent on scale. Such a scenario is also consistent with a supportive scheme of subsidies for small-scale producers, which would shift the balance of capital and operating costs within the processing system downstream.</p>", "<title>Model formulation</title>", "<p>Commodity purchase, sale, processing and logistics are linked through a mass balance specific to each commodity within each region as illustrated in the following equation</p>", "<p></p>", "<p>The model is then solved in order to minimise total system logistics (both inter and intra-regional), process capital and operating costs:</p>", "<p></p>", "<p>A <italic>Current </italic>technology scenario is characterised as an SSF process utilising an agricultural residue feedstock and embedded within either a centralised or corner-point supply-demand distribution at the 50 km²grid scale. A <italic>Future </italic>technology scenario, employing an ambient CBP process utilising a hybrid poplar short rotation coppice (SRC) feedstock, is also considered. A summary of the technological parameters relevant to each scenario is provided in Table ##TAB##3##4##. Sensitivity to centralised and corner-point distributions, regional scale (25, 50 and 100 km²regions), and more detailed technological scenarios regarding logistics (Equation 4) and economies of scale (Equation 5) ratios are also explored.</p>" ]

[ "<title>Results</title>", "<p>Cost-optimal configurations illustrating optimal plant location and biomass sourcing at the 50 km²scale are presented and compared in Figure ##FIG##3##4##. Ethanol distribution logistics do not represent a significant driver of the spatial system owing to a comparatively low cost and therefore are not presented. A number of system performance metrics are provided for each spatial distribution, scale and technology scenario in Table ##TAB##4##5##.</p>", "<p>The <italic>Current </italic>technological system splits into 141 × 10⁶l year^-1and 297 × 10⁶l year^-1capacity plants for both spatial scenarios (Figures ##FIG##3##4a## and ##FIG##3##4b##). The average biomass transport distance () is 83.7 km with a maximum range of 140 km. A higher spatial resolution would allow a more accurate maximum range to be determined.</p>", "<p>The higher biomass yield in the <italic>Future Centralised </italic>scenario (Figure ##FIG##3##4c##) supports a larger plant(s) for the same sourcing footprint. A single plant of 2.97 × 10⁹l year^-1is observed, sourcing biomass over an average distance of 106.9 km. Whilst this appears large by current standards, it represents a plant of approx. 2.2 GW ethanol output capacity, comparable with small petrochemical refining operations. This is the only scenario tested which complies with the optimal L:C Ratio of approximately 0.8 as derived by Wright and Brown [##UREF##9##13##] for single-plant systems (Table ##TAB##4##5##). Therefore this metric is not considered a robust indicator of optimality for systems of multiple plants located within heterogeneous biomass supply distributions.</p>", "<p>The future technology appears more sensitive to the spatial distribution scenario. In the corner-point case (Figure ##FIG##3##4d##) a three-plant system is observed comprising a range of smaller plant capacities of 0.66, 1.085 and 1.23 × 10⁹l year^-1. The average biomass transport distance is reduced to 66.1 km. It would appear that a shift to high-yielding energy crops and CBP drives an increased sensitivity to the spatial distribution of biomass and, to a lesser extent, ethanol demand. This suggests that ethanol distribution becomes a factor. Note that while spatial structure and L:C ratio differ greatly, the cost of ethanol production remains very close.</p>", "<p>The sensitivity of the corner-point distribution to the spatial scale of the system provides further insight into the influence of technological development on the optimal plant configuration and logistical flows. These are presented in Figure ##FIG##4##5##.</p>", "<p>At the 25 km²scale, the single, centrally located plant configuration dominates (Figures ##FIG##4##5a## and ##FIG##4##5d##). This location minimises the average unit biomass transportation distance to the single plant. The increased lignin yield in a transition to a hybrid poplar feedstock and the significant decrease in process and separation hot utility requirements results in an excess potential hot utility generation (limited to 10% of potential regional demand) for the <italic>Suburban </italic>plant location region. As a result, a CHP plant is established supplying 48 MW_eand 59 MW_thwithin the high population density urban region (grid 1).</p>", "<p>For both technological scenarios at the 100 km²scale (Figures ##FIG##4##5c## and ##FIG##4##5d##) a dedicated plant is located within the sparse suburban region while a number of plants compete for biomass resource throughout the rural periphery. Observed plant scales range between 150 and 540 × 10⁶l year^-1for the <italic>Current </italic>and 1.24 and 2.38 × 10⁹l year^-1for the <italic>Future </italic>scenario. The average biomass transport distance is 101.9 km for the <italic>Current </italic>scenario and 81.6 km for the <italic>Future </italic>scenario.</p>", "<p>System performance metrics are presented in Table ##TAB##4##5## for each of the tested scenarios. For both technological scenarios, there is negligible sensitivity in ethanol production cost to spatial distribution. The <italic>Current </italic>technology exhibits a clear reduction in production cost with increasing spatial scale owing to a significant increase in available resource and thus achievable economies of scale in production. This effect is less pronounced in the <italic>Future </italic>scenario owing to a proportional increase in biomass costs and an apparent trend to the optimal scale for system operation, as indicated by the minimum in production costs for the <italic>Corner-Point </italic>scenario at a scale of 50 km².</p>", "<title>Intermediate purity ethanol logistics</title>", "<p>The potential for systems involving the logistics of crude, intermediate concentration ethanol has been investigated through an assessment of sensitivity to increases in the Logistics Ratio (LR, Equation 4) through the incorporation of pipelines for the movement of both pure and intermediate ethanol concentrations. These have been tested for the <italic>Future </italic>scenario at the 50 km²grid scale, as this was identified as close to the production cost optimum (Table ##TAB##4##5##).</p>", "<p>The base-case EoSR for <italic>Future </italic>technologies is 1.28. Scenarios driving EoSR to 1.45 and 1.65 have been investigated. Figure ##FIG##5##6## presents the EoSR scenarios for the <italic>Centralised </italic>distribution. Figure ##FIG##5##6a## demonstrates that a small reduction in the economies of scale in <italic>Process </italic>operations drives the optimal system configuration from the centralised system observed in Figure ##FIG##3##4c## to one encompassing multiple, smaller-scale facilities, ranging between 525 × 10⁶l year^-1and 954 × 10⁶l year^-1, located within the suburban boundary.</p>", "<p>The scenario in which EoSR = 1.65, observed in Figure ##FIG##5##6b##, assumes upper and lower bound scaling factors of 0.92 and 0.55 for <italic>Process </italic>and combined <italic>Purification </italic>and <italic>Utility </italic>respectively. This results in the centralisation of purification and utility generation whilst biomass processing to intermediate ethanol concentrations is decentralised within the suburban periphery. The intermediate ethanol titre is transported between sites via liquid tanker.</p>", "<p>The introduction of pipeline technologies promotes decoupling and decentralisation of <italic>Process </italic>operations (Figure ##FIG##5##6b##) for both EoSR = 1.45 and 1.65 scenarios. This structural adaptation in the case of the EoSR = 1.45 scenario is driven through a significant reduction in pure ethanol logistics costs through pipeline, rather than liquid tanker, transport. Previously, economies of scale in centralised <italic>Purification </italic>and <italic>Generation </italic>were outweighed by increased ethanol distribution costs to the <italic>Suburban </italic>and <italic>Rural </italic>periphery. This is the first observed case wherein ethanol distribution logistics are clearly driving the optimal system configuration. A modest reduction in ethanol production costs of 3.3% is observed through the introduction of pipeline transport of pure ethanol for the <italic>Future Centralised </italic>scenario. Details of system metrics for each of the EoSR and ethanol transport mode scenarios are outlined in Table ##TAB##5##6##.</p>", "<p>The sensitivity to the negligible <italic>Process </italic>heat assumption for the <italic>Future </italic>technology, resulting from the development of ambient processing methods, was assessed for the EoSR = 1.65 scenario. A hot utility requirement equivalent to 30% (per odt of biomass processed) of that required for the <italic>Current </italic>scenario was assumed. The resulting system abandons ethanol intermediates and switches to a system of decentralised, fully integrated plants similar to that observed in Figure ##FIG##5##6a##.</p>" ]

[ "<title>Discussion</title>", "<p>The model results presented provide insight into the optimal system configurations for a range of potential scenarios in response to economies of scale and logistical factors. However, the model neglects the impacts of the system dynamics on system performance. The conceptual model should therefore be expanded with a discussion of dynamic factors applicable to the operational, planning and strategic timeframes. Opportunities for future work are presented.</p>", "<p>Storage-related issues, such as storage location, and its role in dictating supply chain structure, have been neglected within the model. This is because storage does not have an influence on the spatial structure of the system in a steady-state model with known demands at each location. Assuming that constant operational profiles are desirable, because they minimise underutilised process capital, the drivers of biomass storage location reduce to two contributing factors: economies of scale in storage, and the degradation rate of biomass. It is clearly undesirable to incur monetary and energetic cost transporting biomass that will degrade prior to processing. An assessment of biomass storage location would therefore require an extension of the modelling framework presented to consider dynamics at the monthly or seasonal temporal resolution. Furthermore, it would require consideration of an expanded range of pretreatment and densification operations that impact on biomass energy density and propensity to microbial degradation. This will be considered in future work.</p>", "<p>In order to provide some insight into the scale of biomass storage required it is noted that the capacity required to house the total annual harvest within each rural region for the <italic>Future </italic>scenario at 50 km²scale would be of the order of 2.7 × 10⁶m³. Three-day buffer storage at a central plant, at the extreme scales of operation observed in, for example, the 2.9 × 10⁹l year^-1plant, requires approximately 46 × 10³m³of shed capacity. Furthermore, the total number of truck deliveries per day becomes a factor with regard to plants located in an urban region. At the suggested optimal scale, 50 deliveries per hour would be required. Constraints on feasible logistical operations could potentially become apparent well below this threshold.</p>", "<p>The assumption of negligible hot utility requirement in <italic>Future Process </italic>operation, achieved through the application of CO₂explosion and oxidative delignification, is considered highly optimistic. It is nevertheless posited within the cost assessment presented, in an attempt to incorporate potential new processes, as identified through the US Department of Energy Genomics:GTL Program [##UREF##6##8##]. The target of such processes is a shift away from relatively harsh thermochemical treatments through the identification of biological (microbial and enzymatic) pathways capable of reducing pretreatment severity. Solutions are envisaged in: (1) the genetic engineering of LC cell-wall structures to be more receptive to bio- and thermochemical treatments; (2) upstream processing during storage (ensilage); and (3) the development of 'ligninases', providing an enzymatic basis of lignin depolymerisation. The optimal configuration of biological pretreatment processes throughout the supply chain presents a fascinating challenge that requires open-minded consideration prior to innovation in order to prevent 'tunnel-vision' approaches with limited potential benefits.</p>", "<p>It can be argued that, as a result of a transition towards ambient pre-processing, the reaction rates achieved through intensive thermochemical treatments cannot be maintained. However, the principles of distributed processing are consistent with reduced reaction rates owing to the relaxation of time constraints in batch processing, wherein the shipping of ethanol of intermediate concentration can be scheduled to match batch process completion. As such, ambient processing could provide both production and storage capacity within a multi-site production, storage and collection schedule, the total vessel capacity being approximately the same in each case. A dynamic, combined production and logistical scheduling formulation of the model developed here would provide insight into the economic potential of such a system (see, for example, [##UREF##21##28##]).</p>", "<p>A dynamic formulation, at a seasonal or monthly resolution, would facilitate the investigation of the role of heat market interactions on the residual lignin treatment chain. This work assumes that all lignin is combusted within a CHP facility. Whilst representing the net energetic optimum for the system, with processing chain efficiencies for the <italic>Current </italic>and <italic>Future </italic>technologies of 44.4% and 66.8%, respectively, this has a significant impact on the process economics of plants at smaller scales. This is observed in the large range of ethanol production costs for the <italic>Current </italic>technology in Table ##TAB##4##5##. Indeed, the range of options for lignin treatment in pre-processing, downstream separation and eventual disposal/conversion requires further investigation owing to the significant impact on net chain energy efficiency. The lignin treatment chain also exhibits substantial feedback through system interactions regarding pretreatment severity and distillation energy requirements. Further assessment incorporating the option of dedicated combustion plants is considered. These could be more readily decentralised, compared with fully integrated CHP systems, reducing the sensitivity of decentralised processing configurations (Figure ##FIG##5##6b##) to <italic>Process </italic>hot utility requirements.</p>", "<p>This work attempts to capture strategic dynamics (5 to 25 years) through the assessment of a steady-state model within 'snapshot' technological scenarios. In reality, the transition from the current to the future state provides many challenging decisions regarding plant construction, plant shut-down and retrofit planning, and logistical infrastructure investment. Ensuring that (near-)optimal systems are achieved in the future hinges on whether optimal current configurations are robust under future conditions and on the migration pathway between the technologies that is anticipated.</p>", "<p>This work suggests that the general form of optimal configurations is robust for both <italic>Current </italic>and <italic>Future </italic>technological scenarios. While a five-fold increase in feedstock yield alone would drive a significant increase in optimal plant scale, this effect is tempered by a concurrent reduction in process capital and operating costs relative to logistics. Wright and Brown [##UREF##9##13##] provide a simple analytic model to test this result for isolated single-plant systems. In the case of multiple-plant infrastructures, locating and scaling the 'first' plant without consideration of the globally optimal system configuration under both current and future conditions could result in a legacy of system-wide sub-optimal performance extending throughout the lifetime of the plant. The model applied in this work therefore presents an invaluable tool in the strategic design of LC-bioethanol supply chain systems. A dynamic capacity start-up and shut-down extension of model framework will be developed and applied in future work.</p>" ]

[ "<title>Conclusion</title>", "<p>A spatially explicit whole-systems assessment of current and possible future LC-bioethanol infrastructures has been completed. Hypothetical future development scenarios (within the bounds of scientific and engineering postulates) for agricultural, processing and logistical (pipeline) technologies were applied in order to gain some insight into the potential evolution of the future infrastructure. Current technologies were characterised by agricultural residue feedstocks (for example, corn stover), dilute-acid hydrolysis and single-stage SSF. Future technologies were characterised by high-yielding energy crops (for example, hybrid poplar), a transition towards ambient pre-processing technologies and CBP.</p>", "<p>Optimal ethanol production costs for current technologies are highly sensitive to the spatial scale of the assessment. They decrease significantly from $0.71 to $0.58 per litre concurrent with increasing economies of scale in processing up to a limiting plant scale of 550 × 10⁶l year^-1. Future feedstocks and technologies realise significant cost reductions with production costs ranging from $0.33 to $0.36 per litre. Cost-optimal future systems were observed to be increasingly sensitive to the spatial distribution of biomass supply.</p>", "<p>The potential for decentralised production systems involving the logistics of crude, intermediate concentration ethanol has been considered. The large hot utility requirements of current pre-processing technologies and ethanol distillation stages prevent decoupling of front-end processing from the highly capital intensive, tail-end lignin treatment and utility generation. Future increases in feedstock yields repress the driver for front-end process decentralisation as they support larger, fully integrated plants over the same biomass sourcing footprints.</p>", "<p>An increase in the ratio of economies of scale factor between front-end processing (that is, pretreatment and fermentation) and downstream separation technologies was considered, embodying some degree of efficient downscaling and modularisation of the pretreatment and fermentation processes. At scale factor ratios of 1.45 and above, distributed front-end process systems were observed. However, these must be considered as highly sensitive to the assumption of ambient pretreatment technologies. The incorporation of pipelines as a feasible mode for transport of intermediate and pure ethanol titres had a limited impact on whole-system economics and spatial configuration.</p>", "<p>The modelling approach and formulation presented provide a valuable analytical tool for the optimisation of the spatial LC-bioethanol supply chain. In particular, it can provide insight into the optimal configuration of multiple-plant systems. This information is invaluable in ensuring (near-) cost-optimal strategic development within the sector at the regional and national scale. The framework is flexible and can thus accommodate a range of processing tasks, logistical modes, by-product markets and impacting policy constraints (obligations, subsidies). There exists great scope for application to real-world case studies through dynamic extensions of the formulation.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Lignocellulosic bioethanol technologies exhibit significant capacity for performance improvement across the supply chain through the development of high-yielding energy crops, integrated pretreatment, hydrolysis and fermentation technologies and the application of dedicated ethanol pipelines. The impact of such developments on cost-optimal plant location, scale and process composition within multiple plant infrastructures is poorly understood. A combined production and logistics model has been developed to investigate cost-optimal system configurations for a range of technological, system scale, biomass supply and ethanol demand distribution scenarios specific to European agricultural land and population densities.</p>", "<title>Results</title>", "<p>Ethanol production costs for current technologies decrease significantly from $0.71 to $0.58 per litre with increasing economies of scale, up to a maximum single-plant capacity of 550 × 10⁶l year^-1. The development of high-yielding energy crops and consolidated bio-processing realises significant cost reductions, with production costs ranging from $0.33 to $0.36 per litre. Increased feedstock yields result in systems of eight fully integrated plants operating within a 500 × 500 km²region, each producing between 1.24 and 2.38 × 10⁹l year^-1of pure ethanol. A limited potential for distributed processing and centralised purification systems is identified, requiring developments in modular, ambient pretreatment and fermentation technologies and the pipeline transport of pure ethanol.</p>", "<title>Conclusion</title>", "<p>The conceptual and mathematical modelling framework developed provides a valuable tool for the assessment and optimisation of the lignocellulosic bioethanol supply chain. In particular, it can provide insight into the optimal configuration of multiple plant systems. This information is invaluable in ensuring (near-)cost-optimal strategic development within the sector at the regional and national scale. The framework is flexible and can thus accommodate a range of processing tasks, logistical modes, by-product markets and impacting policy constraints. Significant scope for application to real-world case studies through dynamic extensions of the formulation has been identified.</p>" ]

[ "<title>List of abbreviations</title>", "<p>CBP: Consolidated bio-processing; CHP: Combined heat and power; DM: Dry matter; EoSR: Economies of scale ratio; F: Feedstock; GHG: Greenhouse gas; HHV: Higher heating value; LC: Lignocellulosic biomass; LR: Logistics ratio; MILP: Mixed Integer Linear Programming; ODT (odt): Oven-dry tonne(s); PEI: Primary energy input(s); SRC: Short rotation coppice; SSF: Simultaneous saccharification and fermentation.</p>", "<title>Authors' contributions</title>", "<p>AJD completed the majority of the work with regard to the system study, mathematical model development, results analysis and drafting of the manuscript. Both CSA and NS had substantial input into the structure and content of the manuscript. NS conceived of the study, steered its direction and provided support regarding computational issues. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank the TSEC-BIOSYS consortium, co-ordinated through the Centre for Environment Policy and Technology (ICEPT) at Imperial College London, who provided the funding to complete this research (grant number NERC/NE/C516279/1).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Global bioethanol market trends 1996–2005</bold>.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Spatial distribution scenarios</bold>. (a) Centralised. (b) Corner-Point. The size of the circles indicates the magnitude of the demand/supply.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>A process flowsheet for the <italic>Current </italic>technology scenario</bold>. The thickness of each arrow is representative of the relative energy content of that stream.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>System configurations at the 50 × 50 km²region scale</bold>. Refer to Figure 2 for the underlying supply and demand distributions. The relative scale of harvesting is represented by the disk <italic>radius</italic>. The relative scale of process operations is represented by disk <italic>area</italic>. This scheme was selected to enhance visual clarity.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>System configurations for the <italic>Corner-Point </italic>distribution</bold>. Refer to Figure 2b for the underlying supply and demand distribution.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>System configurations for the economies of scale ratio scenarios at the 50 × 50 km²region scale</bold>. Refer to Figure 2a for the underlying supply and demand distribution.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Performance metric comparison for starch- and LC-bioethanol life-cycles</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"4\">Metrics</td></tr><tr><td/><td colspan=\"4\"><hr/></td></tr><tr><td/><td align=\"center\">GWP</td><td align=\"center\">Energy efficiency</td><td align=\"center\">Land productivity</td><td align=\"center\">Cost</td></tr></thead><tbody><tr><td align=\"left\">Technology</td><td align=\"center\">kg_CO2GJ_F^-1</td><td align=\"center\">MJ_PEIMJ_F^-1</td><td align=\"center\">GJ ha^-1year^-1</td><td align=\"center\">£₂₀₀₆GJ^-1</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">Starch</td><td align=\"center\">81</td><td align=\"center\">0.79</td><td align=\"center\">58</td><td align=\"center\">14.97</td></tr><tr><td align=\"left\">Lignocellulosic</td><td align=\"center\">11</td><td align=\"center\">0.1</td><td align=\"center\">94.5</td><td align=\"center\">8.41</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">Source</td><td align=\"center\">[##REF##16439656##5##]</td><td align=\"center\">[##REF##16439656##5##]</td><td align=\"center\">[##UREF##22##29##]</td><td align=\"center\">[##UREF##23##30##]</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Agricultural land cover and population densities for rural, semi-rural and urban region types</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Region type</td><td align=\"center\">Agriculture<break/> (ha km^-2)</td><td align=\"center\">Population<break/> (Capita km^-2)</td></tr></thead><tbody><tr><td align=\"center\">Rural</td><td align=\"center\">65</td><td align=\"center\">75</td></tr><tr><td align=\"center\">Semi-rural</td><td align=\"center\">25</td><td align=\"center\">300</td></tr><tr><td align=\"center\">Urban</td><td align=\"center\">5</td><td align=\"center\">1500</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Feedstock properties</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Property</td><td align=\"center\">Unit</td><td align=\"center\">Crop<break/> residue</td><td align=\"center\">Hybrid<break/> poplar</td></tr></thead><tbody><tr><td align=\"center\">Yield</td><td align=\"center\">odt ha^-1year^-1</td><td align=\"center\">5.0</td><td align=\"center\">25.0</td></tr><tr><td align=\"center\">Cellulose</td><td align=\"center\">%_DM*</td><td align=\"center\">36.4</td><td align=\"center\">44.7</td></tr><tr><td align=\"center\">Hemicellulose</td><td align=\"center\">%_DM</td><td align=\"center\">22.6</td><td align=\"center\">18.6</td></tr><tr><td align=\"center\">Lignin</td><td align=\"center\">%_DM</td><td align=\"center\">16.6</td><td align=\"center\">26.4</td></tr><tr><td align=\"center\">Inert mass</td><td align=\"center\">%_DM</td><td align=\"center\">24.4</td><td align=\"center\">10.3</td></tr><tr><td align=\"center\">HHV</td><td align=\"center\">MJ.kg^-1</td><td align=\"center\">15.2</td><td align=\"center\">18.5</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p><italic>Current </italic>and <italic>Future </italic>scenario technology parameters</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Parameter</td><td align=\"center\">Unit</td><td align=\"center\">Current</td><td align=\"center\">Future</td></tr></thead><tbody><tr><td align=\"center\">Crop type</td><td align=\"center\">-</td><td align=\"center\">Straw residue</td><td align=\"center\">SRC hybrid poplar</td></tr><tr><td align=\"center\">Crop yield</td><td align=\"center\">odt ha^-1year^-1</td><td align=\"center\">5</td><td align=\"center\">25</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"center\">Pretreatment method</td><td align=\"center\">-</td><td align=\"center\">Dilute acid</td><td align=\"center\">CO2 explosion</td></tr><tr><td align=\"center\">Process integration</td><td align=\"center\">-</td><td align=\"center\">SSF</td><td align=\"center\">CBP</td></tr><tr><td align=\"center\">Pretreatment conversion*</td><td align=\"center\">%_cellulose</td><td align=\"center\">75.0</td><td align=\"center\">98.0</td></tr><tr><td align=\"center\">Fermentation conversion</td><td align=\"center\">%_sugars</td><td align=\"center\">95.0</td><td align=\"center\">95.0</td></tr><tr><td align=\"center\">Ethanol yield**</td><td align=\"center\">l_EtOHodt^-1</td><td align=\"center\">281</td><td align=\"center\">382</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"center\">Process titre</td><td align=\"center\">wt%_EtOH</td><td align=\"center\">5.0</td><td align=\"center\">35.0</td></tr><tr><td align=\"center\">Process hot utility</td><td align=\"center\">MJ MJ_EtOH^-1</td><td align=\"center\">0.17</td><td align=\"center\">0.00</td></tr><tr><td align=\"center\">Distillation hot utility***</td><td align=\"center\">MJ MJ_EtOH^-1</td><td align=\"center\">0.26</td><td align=\"center\">0.20</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>System performance metrics for spatial scale, spatial distribution and technological scenarios</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"3\">Scenario</td><td align=\"center\" colspan=\"3\">Current</td><td align=\"center\" colspan=\"3\">Future</td></tr><tr><td/><td/><td/><td colspan=\"6\"><hr/></td></tr><tr><td/><td/><td/><td align=\"center\" colspan=\"3\">Grid scale (km²)</td><td align=\"center\" colspan=\"3\">Grid scale (km²)</td></tr><tr><td/><td colspan=\"8\"><hr/></td></tr><tr><td/><td align=\"center\">Metric</td><td align=\"center\">Unit</td><td align=\"center\">25</td><td align=\"center\">50</td><td align=\"center\">100</td><td align=\"center\">25</td><td align=\"center\">50</td><td align=\"center\">100</td></tr></thead><tbody><tr><td align=\"center\">Centralised</td><td align=\"center\">Ethanol cost</td><td align=\"center\">$₂₀₀₇.l_EtOH^-1</td><td align=\"center\">0.714</td><td align=\"center\">0.605</td><td align=\"center\">0.579</td><td align=\"center\">0.350</td><td align=\"center\">0.328</td><td align=\"center\">0.328</td></tr><tr><td/><td align=\"center\"></td><td align=\"center\">km</td><td align=\"center\">53</td><td align=\"center\">70</td><td align=\"center\">114</td><td align=\"center\">53</td><td align=\"center\">107</td><td align=\"center\">97</td></tr><tr><td/><td align=\"center\">L:C ratio**</td><td align=\"center\">-</td><td align=\"center\">0.17</td><td align=\"center\">0.29</td><td align=\"center\">0.45</td><td align=\"center\">0.45</td><td align=\"center\">0.86</td><td align=\"center\">0.79</td></tr><tr><td/><td align=\"center\">No. plants</td><td align=\"center\">-</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">4</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">5</td></tr><tr><td/><td align=\"center\">Max. plant***</td><td align=\"center\">10⁶l year^-1</td><td align=\"center\">109</td><td align=\"center\">297</td><td align=\"center\">546</td><td align=\"center\">742</td><td align=\"center\">2970</td><td align=\"center\">2620</td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"center\">Corner-Point</td><td align=\"center\">Ethanol cost</td><td align=\"center\">$₂₀₀₇l_EtOH^-1</td><td align=\"center\">0.712</td><td align=\"center\">0.601</td><td align=\"center\">0.578</td><td align=\"center\">0.355</td><td align=\"center\">0.337</td><td align=\"center\">0.346</td></tr><tr><td/><td align=\"center\"></td><td align=\"center\">km</td><td align=\"center\">48</td><td align=\"center\">71</td><td align=\"center\">102</td><td align=\"center\">48</td><td align=\"center\">66</td><td align=\"center\">82</td></tr><tr><td/><td align=\"center\">L:C ratio</td><td align=\"center\">-</td><td align=\"center\">0.17</td><td align=\"center\">0.28</td><td align=\"center\">0.46</td><td align=\"center\">0.33</td><td align=\"center\">0.49</td><td align=\"center\">0.75</td></tr><tr><td/><td align=\"center\">No. plants</td><td align=\"center\">-</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">4</td><td align=\"center\">1</td><td align=\"center\">3</td><td align=\"center\">8</td></tr><tr><td/><td align=\"center\">Max. plant</td><td align=\"center\">10⁶l year^-1</td><td align=\"center\">109</td><td align=\"center\">297</td><td align=\"center\">533</td><td align=\"center\">742</td><td align=\"center\">1230</td><td align=\"center\">2380</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>System performance metrics for economies of scale ratio and logistical mode scenarios</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td/><td align=\"center\" colspan=\"2\">Liquid transport mode</td></tr></thead><tbody><tr><td align=\"center\">EoSR</td><td align=\"center\">Metric</td><td align=\"center\">Units</td><td align=\"center\">Tanker</td><td align=\"center\">Pipeline</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\">1.28</td><td align=\"center\">Ethanol cost</td><td align=\"center\">$₂₀₀₇l_EtOH^-1</td><td align=\"center\">0.328</td><td align=\"center\">0.317</td></tr><tr><td/><td align=\"center\"></td><td align=\"center\">km</td><td align=\"center\">107</td><td align=\"center\">107</td></tr><tr><td/><td align=\"center\">L:C ratio**</td><td align=\"center\">-</td><td align=\"center\">0.86</td><td align=\"center\">0.76</td></tr><tr><td/><td align=\"center\">No. plants</td><td align=\"center\">-</td><td align=\"center\">1</td><td align=\"center\">1</td></tr><tr><td/><td align=\"center\">Configuration</td><td align=\"center\">-</td><td align=\"center\">Integrated</td><td align=\"center\">Integrated</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\">1.45</td><td align=\"center\">Ethanol cost</td><td align=\"center\">$₂₀₀₇l_EtOH^-1</td><td align=\"center\">***</td><td align=\"center\">-</td></tr><tr><td/><td align=\"center\"></td><td align=\"center\">km</td><td align=\"center\">58</td><td align=\"center\">62</td></tr><tr><td/><td align=\"center\">L:C ratio</td><td align=\"center\">-</td><td align=\"center\">0.34</td><td align=\"center\">0.58</td></tr><tr><td/><td align=\"center\">No. plants</td><td align=\"center\">-</td><td align=\"center\">4</td><td align=\"center\">5</td></tr><tr><td/><td align=\"center\">Configuration</td><td align=\"center\">-</td><td align=\"center\">Integrated</td><td align=\"center\">Decentralised</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\">1.65</td><td align=\"center\">Ethanol cost</td><td align=\"center\">$₂₀₀₇l_EtOH^-1</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td/><td align=\"center\"></td><td align=\"center\">km</td><td align=\"center\">62</td><td align=\"center\">62</td></tr><tr><td/><td align=\"center\">L:C ratio</td><td align=\"center\">-</td><td align=\"center\">0.69</td><td align=\"center\">0.59</td></tr><tr><td/><td align=\"center\">No. plants</td><td align=\"center\">-</td><td align=\"center\">5</td><td align=\"center\">5</td></tr><tr><td/><td align=\"center\">Configuration</td><td align=\"center\">-</td><td align=\"center\">Decentralised</td><td align=\"center\">Decentralised</td></tr></tbody></table></table-wrap>" ]

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[]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Details of the mathematical model formulation.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>* Percentage dry matter content determined on a wet basis</p></table-wrap-foot>", "<table-wrap-foot><p>*Assumes equal conversion of both cellulose and hemicellulose fractions</p><p>**Pure ethanol product</p><p>***Distillation includes both <italic>Stripping </italic>and <italic>Rectification </italic>stages for the <italic>Current </italic>technology</p></table-wrap-foot>", "<table-wrap-foot><p>*The average unit-biomass transport distance</p><p>**The ratio between logistics costs and process capital and operating costs</p><p>***Maximum single-plant scale observed within system</p></table-wrap-foot>", "<table-wrap-foot><p>*The average unit-biomass transport distance</p><p>**The ratio between logistics costs and process capital and operating costs</p><p>***Production costs for EoSR scenarios are not considered valid owing to distortions of relative and absolute component costs</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1754-6834-1-13-1\"/>", "<graphic xlink:href=\"1754-6834-1-13-2\"/>", "<graphic xlink:href=\"1754-6834-1-13-3\"/>", "<graphic xlink:href=\"1754-6834-1-13-4\"/>", "<graphic xlink:href=\"1754-6834-1-13-5\"/>", "<graphic xlink:href=\"1754-6834-1-13-6\"/>" ]

[ "<media xlink:href=\"1754-6834-1-13-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>It is established that most of the olfactory sensory neurons (OSNs) express only one type of odorant receptor (OR) among a thousand gene choices [##REF##10089886##1##,##REF##10862701##2##]. Each OSN functions as a specialized sensor for the detection of diverse odorants in the environment. OSNs expressing the same OR converge their axons to the same glomerular pair in the olfactory bulb [##REF##7528109##3##,##REF##8001145##4##]. Thus, the one receptor-one neuron rule is essential for establishing the discrete sensory map of olfactory neuronal connections.</p>", "<p>The ability to discriminate odorants in the environment depends on OR-ligand interactions and signaling capacity within the OSNs. Several experimental approaches for investigating OR functions have been reported [##REF##9875846##5##, ####REF##9279469##6##, ##REF##15341529##7##, ##REF##17387175##8####17387175##8##]. Though heterologous systems allow rapid screening of ligand binding specificity of the ORs, validation of these results in the OSNs has been challenging without an efficient OSN culture system [##REF##9422698##9##]. One of the other challenges in olfaction is to understand the regulatory mechanism for OR selection in the OSNs. Transcriptional regulatory elements that control OR expression have been identified [##REF##12194868##10##,##REF##14593185##11##]. In addition, a negative feedback model for achieving single OR expression in each OSN has been proposed [##REF##14593185##11##, ####REF##15186780##12##, ##REF##14732684##13####14732684##13##]. The feedback inhibition of OR expression appears to require OR protein. Recent evidence indicates that the OR coding sequence plays a critical role in the suppression of multiple OR expression. Not only can endogenous OR expression be suppressed, but ectopic OR expression appears to be suppressed as well via the OR coding sequence [##REF##18045541##14##].</p>", "<p>An <italic>in vitro </italic>system that allows genetic manipulation will be helpful in determining the genes and the functions of their products that are involved in the regulation of OR expression and function. Several primary OSN culture techniques have been reported [##REF##9096146##15##, ####REF##15215289##16##, ##REF##2482777##17####2482777##17##]. Studies using cultured OSNs have primarily focused on investigating the regulatory mechanism of neurogenesis and differentiation, though responses to odorants and signaling molecule functions were reported in primary OSN cultures [##REF##1851216##18##,##REF##10613503##19##]. However, the expression of ORs and the genetic manipulation of OR expression in cultured OSNs have not been reported to date. Here we describe an OSN culture system that allows gene expression manipulation, monitoring of OR expression and testing of OR-ligand specificity. Lentiviral vectors are used to achieve a high percentage of infection of cultured OSNs and to express ectopically genes of interest. Using this system, we observed that OSNs allow expression of two ORs when introduced by lentiviral-mediated gene transfer.</p>" ]

[ "<title>Materials and methods</title>", "<title>Animals</title>", "<p>C57/BL6 mice were purchased from Charles River Laboratories (Wilmington, MA). Embryonic day 0 (E0) was defined by the day when the copulation plug was detected in the morning. The day of birth was defined as P0. All experimental procedures were conducted according to institutional and NIH guidelines and were approved by the Institution Animal Care and Use Committee.</p>", "<title>Cortical astrocyte feeder layer</title>", "<p>Primary astrocytes were isolated from P0 mouse neocortex and cultured according to a published protocol [##UREF##0##35##]. Before plating OSNs, astrocytes were plated and allowed to reach confluency on poly-D-lysine and laminin coated glass coverslips. The purity of the astrocytes was evaluated by immunostaining a sample of the astrocyte culture for glial fibrillary acidic protein to identify the astrocyte population and β-tubulin III to determine the presence of neurons. When no neurons were observed, astrocytes were used for OSN culture.</p>", "<title>Dissociated primary OSN culture</title>", "<p>E17 to P0 OE were dissected from the nasal cavity. After 40 minutes' incubation in 2 mg/ml dispase at room temperature, OE were separated from the underlining stroma using fine tungsten needles. The OE were incubated in Waymouth's MB 752/1 medium with N2 supplement (Invitrogen, Carlsbad, CA, USA) at 37°C for 2 hours before treatment with 0.05% trypsin for dissociation. After trypsinization, dissociated cells were plated at a density of 5 × 10⁴cells/cm²on the confluent astrocyte feeder layer. Dissociated OSNs were maintained in Waymouth's MB 752/1 medium with N2 supplement for up to 10 days.</p>", "<title>Production of lentiviral vectors</title>", "<p>The lentivirus backbone (pFUW) was kindly provided by C Lois [##REF##11786607##36##]. To generate pFUW-EGFP, we first modified pEGFP-N1 (BD Biosciences, San Jose, CA, USA) by eliminating two restriction sites, <italic>Hpa</italic>I and <italic>Mfe</italic>I, via site-directed mutagenesis using primers GFP-MH2 and GFP-MH2R (Table ##TAB##0##1##). EGFP sequences were then amplified from the modified pEGFP-N1 by PCR using primers GFP-LTF and GFP-LTR (Table ##TAB##0##1##) and cloned into the <italic>Eco</italic>RI site of the pFUW to obtain pFUW-EGFP. The I7 open reading frame sequence was obtain by PCR from mouse OE cDNA using primers I7-F and I7-R (Table ##TAB##0##1##) and cloned into pCR-blunt TOPO-II (Invitrogen) to generate pCR-I7. After the sequence was confirmed, the mouse I7 open reading frame was cloned into pFUW-EGFP between the <italic>Hpa</italic>I and <italic>Eco</italic>RI sites to produce pFUW-I7-EGFP. To generate pFUW-mCherry, primers GFP-LTF and mCRY-R were used to amplify the mCherry sequence from pRSET-B mCherry [##REF##15558047##37##] and cloned into pFUW. Similarly, pFUW-P2-mCherry, pFUW-MOR118-mCherry and pFUW-M72-mCherry were generated as described above using gene-specific primers (Table ##TAB##0##1##). Recombinant lentiviruses were produced as described [##REF##11786607##36##]. Titers of the viruses were between 10⁸and 10¹⁰pfu/ml. When infecting OSNs in culture, 10⁵pfu/ml viruses were added at the time of plating in all experiments. While growing astrocytes in the non-confluent cultures were capable of being infected by lentiviruses, similar to the dissociated OSNs, astrocytes in the confluent feeder layers were rarely infected. This characteristic phenomenon allows the investigation of lentiviral-mediated expression in the OSNs in our culture system.</p>", "<title>Immunohistochemistry</title>", "<p>Cultured cells were fixed with 4% paraformaldehyde for 15 minutes and immunostained as described previously [##REF##8063958##38##]. The sources and the dilutions of the primary antibodies were: monoclonal mouse anti-β-tubulin III 1:300 (Sigma, Saint Louis, MO, USA); rabbit anti-GAP-43 1:200 (Chemicon, Temecula, CA, USA); mouse anti-NCAM 1:100 (Developmental Studies Hybridoma Bank, Iowa City, IA, USA); chicken anti-OMP 1:1000 [##REF##16374708##39##]; rabbit anti-AC3 1:100 (Santa Cruz Biotechnology, Santa Cruz, CA, USA); rabbit anti-Gαolf 1:100 (Santa Cruz Biotechnology); rabbit anti-GFP 1:3000 (Invitrogen); rabbit anti-RFP 1:250 (MBL International Corp., Woburn, MA, USA); rabbit anti-MOR42-3 1:2000 (Osenses Pty Ltd, Flagstaff Hill, SA, Australia)</p>", "<title>RT-PCR analysis</title>", "<p>Total RNAs were extracted from the OSN cultures, including astrocyte feeder layer cells and astrocyte feeder layer only cultures, using TRIZOL reagent (Invitrogen). Template cDNAs were obtained by reverse transcription (RT) using oligo dT primers. Detection of cDNAs was done by PCR reactions using primers listed in Table ##TAB##0##1##. All RT-PCR products were confirmed by sequence analysis.</p>", "<title>Single-cell intracellular calcium imaging</title>", "<p>Before each experiment, cultured OSNs were loaded with 1 μM fura-2/AM (Molecular Probes/Invitrogen, Eugene, OR, USA) for 5 minutes in Ringer's solution containing 0.02% (v/v) pluronic acid (Molecular Probes/Invitrogen). After washing, cells were then incubated for an additional 30 minutes at 37°C. Coverslips with fura-2- loaded OSNs were then placed into the recording chamber continuously perfused with Ringer's solution and mounted on a Zeiss Axiovert 200 inverted microscope (Zeiss, Thornwood, NY, USA). Solution exchange was accomplished via a gravity-driven perfusion system, which allowed complete solution exchange in the recording area within 2 to 5 seconds. Fluorescence images of fura-2- loaded OSNs were acquired using a SenSys CCD camera (Roper Scientific, Tucson, AZ, USA). A lambda DG-4 filter changer (Sutter Instrument, Novato, CA, USA) was used for switching between 340 nm and 380 nm excitation wavelengths. Changes in intracellular calcium concentrations ([Ca²⁺]_i) were monitored as changes of the ratio of the fura-2- fluorescence intensity recorded at 340 nm and 380 nm excitation wavelengths (R_340/360). All experiments were performed at room temperature. Data acquisition and analysis were performed using MetaFluor v7.0 software (Universal Imaging, Downingtown, PA, USA). In each experiment transfected cells were identified by GFP fluorescence and time courses of R_340/360were simultaneously recorded from five to seven transfected cells.</p>" ]

[ "<title>Results</title>", "<title>Primary olfactory sensory neurons express olfactory specific markers <italic>in vitro</italic></title>", "<p>To establish an <italic>in vitro </italic>system to investigate the regulatory mechanisms of odorant receptor expression and function, we first extensively validated our primary OSN culture system. In our cultures, OSNs isolated from olfactory neuroepithelia (OE) of embryonic or neonatal mice were maintained on a confluent layer of cortical astrocytes. The neuronal identity of the cultured cells was characterized by their expression of neuronal specific β-tubulin III. Neurons in the cultures exhibited characteristic bipolar morphology with a short dendrite-like process and a long and thin axon-like neurite (Figure ##FIG##0##1A##). Neurons with multipolar morphology were initially present in the cultures, but gradually disappeared. At 1 day <italic>in vitro </italic>(1 DIV), 41.1% of the neurons were bipolar. The percentage of bipolar neurons increased to 65.4% at 2 DIV, 70.0% at 3 DIV, 88.9% at 4 DIV and 99.7% at 6 DIV (Figure ##FIG##0##1B##). While the percentage of the bipolar neurons increased, the density of the neurons in the cultures, which were plated at 1.5 × 10⁵cells/cm²initially, decreased from 41.6% of the plating density at 1 DIV to 16.9% at 5 DIV (Figure ##FIG##0##1C##). These data suggest that the bipolar neurons survived better than other types of neurons in our system.</p>", "<p>The initial decrease in neuronal numbers in the cultures may reflect lack of survival of the mature OSNs dissociated from OE. Olfactory marker protein (OMP) expression is the hallmark for mature olfactory sensory neurons. To evaluate the survival of OMP positive cells, we immunostained the OSN cultures from postnatal day (P)0 OE at different time points and counted the numbers of OMP positive cells. OMP positive neurons were initially present 1 hour after plating. Within eight randomly chosen fields (area = 0.18 mm²), 40 OMP positive cells were observed among 157 total neurons, which is around 25.5% at 1 hour after plating. At 1 DIV, the number of OMP positive cells was dramatically decreased in the cultures. Among 26,000 β-tubulin III positive neurons, only 10 OMP positive cells were observed. At 3 DIV and 5 DIV, no OMP cells were seen in the cultures (Figure ##FIG##1##2A##). We also noticed that OMP signals were barely detectable by RT-PCR at 3 DIV and 5 DIV (Figure ##FIG##1##2D##). Though few in number, OMP positive neurons reappear at 8 DIV (Figure ##FIG##1##2B##). These data suggest that mature OMP positive OSNs dissociated from OE lack the ability to survive under our culture conditions, but immature OSNs in the cultures have the potential to differentiate into OMP positive neurons when cultured for 8 DIV or longer.</p>", "<p>Do the bipolar neurons display molecular markers of OSNs? We observed that all neurons in the cultures, identified by β-tubulin III expression, expressed neuronal cell adhesion molecule (NCAM; Figure ##FIG##1##2A##), which is expressed by OSNs <italic>in vivo </italic>[##REF##2482777##17##]. In addition, at 3 DIV, all cultured neurons were also positive for GAP-43 immunostaining, which is a marker for immature OSNs (Figure ##FIG##1##2A##). Adenylyl cyclase (AC)3 and G_αolfare key players in mediating olfactory signals and are expressed in OSN dendrites and axons during development [##REF##17581954##20##]. Both AC3 and G_αolfexpression were detected in cultured OSNs at 3 DIV by both immunostaining and RT-PCR (Figure ##FIG##1##2##). AC3 and G_αolfprotein were distributed throughout the OSNs, including the cell body, and dendrite- and axon-like processes at 3 DIV. At 5 DIV, however, AC3 was primarily concentrated at the tip of the short dendritic like processes, and at low levels in the cell body and their axons. At 5 DIV, G_αolfimmunostaining signal was detected in the cell body and concentrated at the tip of the short dendritic-like processes as well (Figure ##FIG##1##2C##). We observed that AC3 and G_αolftranscript levels were higher at 5 DIV when compared to those at 3 DIV (Figure ##FIG##1##2D##). Cyclic nucleotide gated channel A2 subunit (CNGA2) was also expressed in the cultured OSNs at 3 DIV and 5 DIV (Figure ##FIG##1##2D##). Expression of progenitor and neuronal precursor markers were also examined using RT-PCR. Both Mash1, an amplifying progenitor marker, and Ngn1, a neuronal precursor marker, are expressed in OE <italic>in vivo </italic>[##REF##15925585##21##]. However, we did not detect expression of these two genes in the OSN cultures at 3 DIV and 5 DIV. NeuroD, which is expressed in immature OSNs <italic>in vivo </italic>[##REF##10639731##22##], was detected in the OSN cultures at both 3 DIV and 5 DIV (Figure ##FIG##1##2D##).</p>", "<p>Do cultured OSNs express odorant receptors? In this study, we examined the expression of five different ORs, I7, P2, M72, MOR118-1 and MOR182-5. The chromosome locations and the onset of expression of each of these ORs during development are different [##REF##10559395##23##,##REF##11739580##24##]. In cultured OSNs, all five OR transcripts were detected by RT-PCR at 3 DIV (Figure ##FIG##2##3##). As controls, OR transcripts were not detected in the cortical astrocyte feeder layer cells. To examine whether OR proteins were produced and to determine the number of OSNs expressing a selected OR in the cultures, we performed immunostaining using an OR-specific antibody. Polyclonal MOR42-3 antibody was used to detect expression of this OR in the OSN cultures. The MOR42-3 antibody was first validated in the OE; we observed that the MOR42-3 antibody recognized a small subset of olfactory sensory neurons in the zone 1 region of the OE, consistent with published results [##REF##10089886##1##]. MOR42-3 immunoreactivity was localized in the OSN cell bodies, dendrites and ciliary processes. At 3 DIV, MOR42-3 positive neurons were observed. MOR42-3 immunoreactivity, similar to that of the OE, was distributed in the OSN cell body and concentrated in the dendrite-like process (Figure ##FIG##2##3B##). Among 4 × 10⁴neurons screened, MOR42-3 immunopositive neurons were found at the frequency of 0.06% (24 out of 1 × 10⁴) in the OSN cultures.</p>", "<title>Efficient gene transfer using lentiviruses</title>", "<p>The difficulty of culturing and genetically manipulating cultured OSNs has impeded the progress of using <italic>in vitro </italic>approaches to investigate molecular mechanisms of OSN differentiation and odorant signaling. Though various transfection techniques and a biolistic gene transfer technique for cultured OSNs have been attempted, the efficiency of the gene transfer and survival rate of the OSNs were low (unpublished data; see also [##REF##12084939##25##]). In this study, we evaluated the effectiveness of lentiviral vector-mediated transfection in OSN cultures. VSV-G pseudotyped lentiviruses carrying an enhanced green fluorescent protein (EGFP) expression cassette were added to the OSN cultures at the time of the plating. When 10⁵pfu/ml of lentiviruses were added to the cultures, we observed that nearly 100% of β-tubulin III positive OSNs expressed GFP at 3 DIV (Figure ##FIG##3##4A##). The morphology of the OSNs infected by lentiviruses was not changed, at this defined viral concentration, compared to that of non-infected cultures (Figure ##FIG##3##4A##). The axon lengths of the lentiviral infected OSNs were not significantly different compared to those of control non-infected cultures; when axon lengths of the control OSNs were normalized to 1 (standard error (SE) = 0.18), the average axon length of GFP lentiviral vector-infected neurons was 1.02 ± 0.15 (<italic>t</italic>-test, <italic>p </italic>&gt; 0.8) (Figure ##FIG##3##4B##). Therefore, lentiviral infection allows high efficiency of gene transfer and does not alter survival and morphology of the OSNs in culture.</p>", "<title>Functional expression of I7 in cultured OSNs</title>", "<p>With the efficient lentiviral vector-mediated gene transfer technique, we then asked whether we could express functional OR in cultured OSNs. Expression of functional OR in heterologous cells has proven to be challenging due to their inefficient trafficking to the cell surface [##REF##9875846##5##,##REF##9332724##26##]. The expression of exogenous ORs in OSNs in the nasal epithelium using adenoviral vector has been reported and the rat odorant receptor I7 introduced to OSNs <italic>in vivo </italic>has proven to be functional [##REF##9422698##9##]. Adenoviral vectors, however, showed toxicity towards the cultured OSNs and significantly decreased OSN survival at 3 DIV. Recombinant lentiviruses carrying the mouse I7 coding sequence fused with EGFP were added to the culture at the concentration of 10⁵pfu/ml. All OSNs in the lentiviral-infected cultures expressed I7-GFP detected by GFP immunostaining. I7-GFP was distributed in the OSNs, including the cell body, and the axon- and dendrite-like processes (Figure ##FIG##4##5A##).</p>", "<p>To examine whether ectopically expressed I7 in cultured OSNs are functional receptors, we tested whether these infected OSNs would respond to octanal (octyl aldehyde), which is one of the documented I7 odorant ligands. It is reported that functional odorant receptors can trigger an increase in [Ca²⁺]_iin OSNs when stimulated by their odorant ligands. To measure [Ca²⁺]_i, cultured OSNs were loaded with fura-2/AM and cells with stable basal levels of [Ca²⁺]_iwere selected for recording. As a control, we first examined whether cultured OSNs infected with recombinant GFP-expressing lentivirus respond to the presence of octanal. Octanal at 100 μM rarely elicits responses in a majority of the cultured OSNs expressing GFP alone (Figure ##FIG##4##5Bi##). Among 64 cells tested, one cell showed a [Ca²⁺]_iincrease in response to octanal, suggesting that this cell may express endogenous functional receptors. It has been shown that propionic acid is not a ligand for the I7 receptor [##REF##9422698##9##]. In OSN cultures infected with I7 lentiviral vectors, none of the I7-expressing cells showed responses to 100 μM propionic acid (n = 28; Figure ##FIG##4##5Bii##); however, all I7-expressing cells tested displayed an increase in [Ca²⁺]_iin response to 100 μM octanal (n = 31; Figure ##FIG##4##5Biii##). This result indicates that ectopically expressed mouse I7 in cultured OSNs are functional ORs.</p>", "<title>Expressing functional I7 does not alter OSN axon extension</title>", "<p>ORs play important roles in OSN axon convergence. The site of the axon convergence could be influenced by the level of OR expression suggested by OR knock-in animal models. Expression of the OR has also been shown to be linked to the expression of certain cell surface adhesion molecules [##REF##17129788##27##]. In our culture system, OSN axons migrate on the surface of the feeder layer astrocytes. Whether over-expressing ORs influences the rate of OSN axon extension has not been examined. Utilizing the OSN cultures, we examined this question by comparing the axon length of the OSNs between I7-expressing and control cultures. At 3 DIV, when the average axon length in the control noninfected cultures was normalized to 1, the average axon length of the I7 lentiviral vector-infected culture was 1.00 ± 0.17 (mean ± SE, n = 56, <italic>t</italic>-test <italic>p </italic>&gt; 0.9; Figure ##FIG##3##4B##). Therefore, over-expressing I7 does not alter the extension of the OSN axons. In addition, when OSNs are grown at a density of the 5 × 10⁴/cm², we did not observe any fasciculation between I7-expressing OSN axons.</p>", "<title>Expression of two exogenous ORs is possible in cultured OSNs</title>", "<p>In mammals, one OSN selectively expresses one type of OR from among approximately 1000 OR genes. We attempted to co-express two ORs using two lentiviral vectors, each expressing an OR under the control of an exogenous human ubiquitin promoter. In this set of experiments, lentiviral vectors expressing a I7-GFP fusion protein were added to the cultures simultaneously with P2-mCherry, M72-mCherry, or MOR118-mCherry expressing viruses for the convenience of visualization. We examined ectopic OR expression by GFP and mCherry immunostaining at 3 DIV, 5 DIV, 7 DIV, and 10 DIV. All expression combinations described above showed identical results. Using the previously defined viral titer, all OSNs in the culture expressed both ectopic ORs and no single ectopic OR expressing OSNs were observed at 3 DIV. The expression of the ectopic ORs did not appear to change with regard to their co-localization and levels in all the OSNs examined at 7 DIV when compared with those at 3 DIV (Figure ##FIG##5##6##). This co-expression persists till 10 DIV, the longest time investigated. No significant changes in the levels of each individual OR were observed.</p>" ]

[ "<title>Discussion</title>", "<p>In this study we report that cultured primary OSNs express endogenous ORs along with other characteristic odorant signaling molecules. Lentiviral vector-mediated gene transfer allows efficient and successful ectopic expression of functional ORs in culture. The mouse OSN culture system described here will enable future studies of OR ligand specificity and transcription regulation within its intrinsic cellular environment.</p>", "<title><italic>In vitro </italic>characteristics of primary OSNs resemble their <italic>in vivo </italic>characteristics</title>", "<p>In the OSN culture system reported here, several modifications were made to enhance the survivability and morphology of the OSNs compared to other published studies [##REF##9096146##15##,##REF##8348301##28##]. Dissociated OE cells were plated on a feeder layer of confluent astrocytes instead of directly on matrix coated coverglass to enhance their attachment, survivability and differentiation. Defined, serum-free media supported the survival of neurons and inhibited cell proliferation and neurogenesis. Consistent with previous reports, OMP expression was present immediately after the plating and was undetectable at 3 DIV [##REF##9096146##15##]. A rapid decrease in OMP positive cells indicated that the culture condition does not support the survival of mature OSNs dissociated from the OE. In addition, a larger numbers of multipolar neurons were present at 1 DIV. The percentage of bipolar neurons increased almost 100% from 1 DIV to 6 DIV, while the number of multipolar neurons decreased. This change in the cell population in the OSN cultures suggests that mature OMP positive neurons and multipolar neurons were not well supported under our culture conditions. We do not have evidence at this point as to whether the multipolar neurons represent certain populations of OSNs. All multipolar neurons were GAP43 and NCAM positive in the cultures. Since all OSNs in the cultures were positive for GAP43 staining at 3 DIV, the OSNs in the cultures are most likely immature neurons. Expression of neuronal progenitor markers Mash1 and Ngn1 was not detected at 3 DIV in the culture. This observation is consistent with the idea that the culture conditions do not support neurogenesis. In addition, it also suggests that the precursors dissociated from the OE either did not survive in the cultures or progressed along their differentiation path to become immature OSNs at 3 DIV. The small number of OMP positive neurons detected at 8 DIV leads us to suggest that OMP positive mature OSNs can be generated under these defined culture conditions.</p>", "<p>OSNs are bipolar neurons with their dendritic process extending towards the surface of the nasal cavity. At the tip of the dendrite, the ending swells into a knob-like morphology and ciliary processes extend out from the dendritic-knob. OR proteins and signaling proteins mediating the odorant activity are found to be enriched in the ciliary processes [##REF##10613503##19##,##REF##9368882##29##]. In cultured OSNs, signaling molecules exhibit preferential localization at the tip of the dendritic-like process. G_αolfand particularly AC3 were both initially distributed throughout the cell body, axon and dendritic processes, and eventually accumulated at the tips of the dendrites. The concentrated subcellular localization of AC3 and G_αolfat the dendritic tip is evident at 5 DIV, and resembles their <italic>in vivo </italic>distribution [##REF##2255909##30##,##REF##1550671##31##]. Though olfactory signaling molecules and several OSN specific markers were present, the cultured OSNs did not recapitulate all cellular and molecular characteristics of mature OSNs <italic>in vivo</italic>. Only a small proportion of OMP positive neurons differentiated from immature neurons and only at 8 DIV or later in the culture. It is possible that OMP expression may be partially dependent upon the presence of the cellular targets of the OSNs. Overall, this culture technique provided an efficient method to culture OSNs, whose morphology, molecular characteristics and maturation progression in culture resembled those observed <italic>in vivo</italic>.</p>", "<title>Odorant receptor expression and function in cultured OSNs</title>", "<p>Based on the developmental timing and the distribution of OR expression in the epithelium, it was concluded that OR expression precedes OMP expression [##REF##7576628##32##]. As it is not practical to examine the expression of all ORs, we selected five ORs that represent OR genes located on different chromosomes that are turned on at different developmental time points [##REF##11739580##24##,##REF##10559395##23##]. All ORs examined were expressed in our OSN culture. Since cultured OSNs are obtained from embryonic day (E)17-P0 mouse OE, it is possible that all ORs are expressed by P0. A recent study of the septal organ demonstrated clearly that OR expression is temporally asynchronous [##REF##18214836##33##]. The onset of OR expression in the septal organ can span several days from E16 to P0. Similar expression onset asynchrony is also reported in the main OE [##REF##10559395##23##]. The density and distribution of OR expressing OSNs also vary within the OE. Therefore, it is possible that not all ORs can be detected in the cultured OSNs.</p>", "<p>Investigations of OR ligand specificity have been challenging due to the difficulty of expressing ORs in heterologous cells. Amino-terminal modification by adding a rhodopsin tag to the OR coding sequence enhanced the ability of OR to be transported to the plasma membrane [##REF##9875846##5##]. However, this extracellular modification may alter ligand receptor binding specificity [##REF##15337685##34##]. Accessory proteins, including odorant receptor transporting proteins and Ric8b, are known to aid in the efficiency of OR expression [##REF##17387175##8##]. Combinations of these accessory factors and signal transduction molecules allow expression of a subpopulation of ORs and subsequent high throughput screening for their ligand. However, many intrinsic differences within the heterologous systems, including availability and subcellular localization of the signaling molecules and the concentration of OR expressed, could all influence the experimental outcome. ORs expressed in their intrinsic environment by OSNs presumably behave most closely to their <italic>in vivo </italic>state [##REF##9422698##9##].</p>" ]

[ "<title>Conclusion</title>", "<p>In this study, we report an efficient technique for ectopic expression of ORs in OSNs. Using lentiviral vectors, we report close to 100% infection of the cultured OSNs. This high infection efficiency allows not only easy access to the OR-expressing cells but also monitoring of changes using molecular and biochemical approaches. In addition, we provide evidence that the ectopically expressed mouse I7 is functional. Though an earlier report indicated that mouse I7 is more sensitive to heptanol, later evidence argued for mouse I7 to respond to multiple aldehyde compounds [##REF##15337685##34##]. To define the functionality of ectopic mouse I7, but without the intent to discriminate ligand-receptor specificity among aldehydes, we used a higher concentration of octanal (100 μM) as an agonist for receptor-induced odorant responses. Calcium imaging experiments confirmed that I7-expressing OSNs responded to odorant stimulation. Consistent with the finding that endogenous ORs are expressed by cultured OSNs, we detected occasional responsive cells among control cultures. This observation suggests that endogenous ORs are functional receptors as well. The cultured OSN system reported here provides an efficient way to express functional ORs and to study ligand specificity in their intrinsic cellular environment.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Olfactory discrimination depends on the large numbers of odorant receptor genes and differential ligand-receptor signaling among neurons expressing different receptors. In this study, we describe an <italic>in vitro </italic>system that enables the expression of exogenous odorant receptors in cultured olfactory sensory neurons. Olfactory sensory neurons in the culture express characteristic signaling molecules and, therefore, provide a system to study receptor function within its intrinsic cellular environment.</p>", "<title>Results</title>", "<p>We demonstrate that cultured olfactory sensory neurons express endogenous odorant receptors. Lentiviral vector-mediated gene transfer enables successful ectopic expression of odorant receptors. We show that the ectopically expressed mouse I7 is functional in the cultured olfactory sensory neurons. When two different odorant receptors are ectopically expressed simultaneously, both receptor proteins co-localized in the same olfactory sensory neurons up to 10 days <italic>in vitro</italic>.</p>", "<title>Conclusion</title>", "<p>This culture technique provided an efficient method to culture olfactory sensory neurons whose morphology, molecular characteristics and maturation progression resembled those observed <italic>in vivo</italic>. Using this system, regulation of odorant receptor expression and its ligand specificity can be studied in its intrinsic cellular environment.</p>" ]

[ "<title>Abbreviations</title>", "<p>AC: adenylyl cyclase; CNGA2: cyclic nucleotide gated channel A2 subunit; DIV: days <italic>in vitro</italic>; E: embryonic day; EGFP: enhanced green fluorescent protein; NCAM: neuronal cell adhesion molecule; OE: olfactory neuroepithelia; OMP: olfactory marker protein; OR: odorant receptor; OSN: olfactory sensory neuron; P: postnatal day; SE: standard error</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>HC carried out all the experiments in this study, and participated in acquisition, analysis and interpretation of the data. SD and AF participated in the design and execution of the calcium imaging study. AF participated in drafting the manuscript. QG conceived of the study, and participated in its design, coordination, interpretation of the data and drafting of the manuscript. All authors read and approve the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Richard Tucker and the members of the Gong lab for helpful discussions and critical reading of the manuscript. This investigation was conducted in a facility constructed with support from Research Facilities Improvement Program Grant Number C06 RR12088-01 from the National Center for Research Resources, National Institutes of Health. This study is supported by National Science Foundation IBN0324769 and National Institutes of Health DC06015 (to QG).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Primary olfactory sensory neuron culture</bold>. A) Olfactory sensory neurons were identified by β-tubulin III expression and were bipolar with a short dendrite-like and a long axon-like process, resembling their <italic>in vivo </italic>morphology. B) Percentage of bipolar neurons among all neuronal cells was at 41.1% after one day <italic>in vitro </italic>(DIV). The percentage of bipolar neurons increased to 99.7% at 6DIV. C) The average survival rate of the cultured olfactory sensory neurons, when compared to plating cell density, was 41.6 ± 4.2% at 1DIV, 29.9 ± 3.1% at 2DIV, 24.7 ± 2.7% at 3DIV, 19.3 ± 2.1% at 4DIV and 16.9 ± 1.8% at 5DIV. Values are mean ± standard deviation from three independent experiments at each data point. Bar = 30 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Cultured olfactory sensory neurons express characteristic markers</bold>. A) Cultured olfactory sensory neurons identified by β-tubulin III (β-Tub III) expression (green) also express neuronal cell adhesion molecule (NCAM; red) and GAP-43 (red) and olfactory marker protein (OMP; red) at 3 DIV. B) OMP positive cells were identified at 8 days <italic>in vitro </italic>(DIV). C) Adenylyl cyclase (AC)3 (arrowhead) and G_αolf(arrowhead and cell body) expression (red) at 5 DIV. D) OMP, AC3, G_αolf, cyclic nucleotide gated channel Ay subunit (CNGA2) and NeuroD expression were detected by RT-PCR at 3 DIV and 5 DIV. Mash1 expression was not detected at 3 DIV or 5 DIV. GAPDH expression served as quantity control. Olfactory epithelium (OE) cDNA was used as a positive control and feeder layer astrocyte (As) cDNA was used as a negative control. E) CNGA2 primers were designed to span an intron and, therefore, were able to discriminate PCR products amplified from genomic DNA (G D), which is 710 bp, or olfactory sensory neuron culture cDNA, which is 429 bp. Bar = 20 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Primary olfactory sensory neurons express endogenous odorant receptors</bold>. A) Odorant receptor transcripts were detected in cultured olfactory sensory neurons by RT-PCR. Cyclic nucleotide gated channel Ay subunit (CNGA2) primers were designed to discriminate PCR products amplified from genomic DNA (710 bp; G) or olfactory sensory neuron culture cDNA (429 bp; O). The odorant receptor transcripts were not detected in cortical astrocytes (As). All selected odorant receptor transcripts, including M72, P2, I7, MOR118 and MOR182-5, were detected in cultured olfactory sensory neurons at 3 days <italic>in vitro </italic>(DIV). B) Odorant receptor protein expression was detected in cultured olfactory sensory neurons. Olfactory sensory neurons were identified by β-tubulin III expression (green in <italic>ii</italic>). MOR42-3 immunostaining positive neurons (red in <italic>i</italic>) were detected among cultured olfactory sensory neurons (merge in <italic>iii</italic>) at 3 DIV. Bar = 20 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Lentiviral vector mediated gene transfer in primary olfactory sensory neurons</bold>. A) When 10⁵pfu/ml recombinant enhanced green fluorescent protein (EGFP)-expressing lentiviral vectors were added to the primary olfactory sensory neuron culture, all β-tubulin III (β-Tub III) positive neurons (red) expressed EGFP (green). B) Lentiviral infection and ectopic expression of EGFP do not alter olfactory sensory neuron (OSN) morphology or axon length. When normalized as 1 ± 0.19 in the control (n = 74), OSN axon average lengths were 1.02 ± 0.15 (n = 56; <italic>t</italic>-test <italic>p </italic>&gt; 0.8) in GFP lentiviral vector-infected cultures and 1.00 ± 0.17 (n = 60; <italic>t</italic>-test <italic>p </italic>&gt; 0.9) in mouse I7 lentiviral vector-infected cultures. Values are mean ± standard error from three independent experiments. Bar = 30 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Over-expressed mouse I7 odorant receptors are functional</bold>. A) A mouse I7-green fluorescent protein (GFP) fusion protein expression cassette was introduced into cultured olfactory sensory neurons by recombinant lentiviral vector. I7-GFP expression recognized by GFP immunostaining (green) was detected in the olfactory sensory neurons identified by β-tubulin III expression (red). I7-GFP is distributed in the olfactory sensory neuron cell body, axon- and dendrite-like processes. B) Time course of the ratio of fura-2 fluorescence intensity at 340 nm and 380 nm (R_340/380) recorded from olfactory sensory neurons expressing GFP alone (B<italic>i</italic>) or I7-GFP (B<italic>ii and </italic>B<italic>iii</italic>) in the presence of 100 μM octanal (B<italic>i </italic>and B<italic>iii</italic>) or 100 μM propionic acid (B<italic>ii</italic>). Arrows indicate timing of application of octanal or propionic acid. Each trace represents an average of R_340/380time courses recorded simultaneously from five to seven cells in a representative experiment. Bar = 20 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Expression of two exogenous odorant receptors in cultured olfactory sensory neurons</bold>. olfactory sensory neurons (OSNs) were infected with I7-green fluorescent protein (GFP) and MOR118-mCherry or I7-GFP and M72-mCherry recombinant lentiviral vectors. The expression of the odorant receptors were detected by GFP or RFP immunostainings (A-F). A, B) At 7 days <italic>in vitro </italic>(DIV), all OSNs expressing I7 (A) also express MOR118 (B). D-F) Similarly, olfactory sensory neurons expressing I7 (D) can also express M72 (E) in the same cells (F). Bar = 30 μm.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Primer sequences for this study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Primer name</td><td align=\"left\">Sequence</td></tr></thead><tbody><tr><td align=\"left\">Eco OMP</td><td align=\"left\">GAATTCATGGCAGAGGACGGGCCACAGAAG</td></tr><tr><td align=\"left\">OMP Xho</td><td align=\"left\">CTCGAGTCAGAGCTGGTTAAACACCACAG</td></tr><tr><td align=\"left\">AC3F</td><td align=\"left\">CAGCCAGCAGCCAACATGCCG</td></tr><tr><td align=\"left\">AC3R</td><td align=\"left\">CTTCCAGCTCATCCTGCTGCTG</td></tr><tr><td align=\"left\">GolfF2</td><td align=\"left\">ATGGGCCTATGCTACAGCCTGCGG</td></tr><tr><td align=\"left\">GolfR2</td><td align=\"left\">CTGACCGGAACTGGTTCTCAGGGTTG</td></tr><tr><td align=\"left\">CNGF2</td><td align=\"left\">GGTGCTGGATTACTTCTCAGACAC</td></tr><tr><td align=\"left\">CNGR</td><td align=\"left\">CCAGGTAGCCATATTCAGGGTCAG</td></tr><tr><td align=\"left\">GAPDH-F</td><td align=\"left\">ATGGTGAAGGTCGGTGTGAACG</td></tr><tr><td align=\"left\">GAPDH-R</td><td align=\"left\">AGTGATGGCATGGACTGTGGTC</td></tr><tr><td align=\"left\">M72-F</td><td align=\"left\">GTTAACATGGCTGCAGAGAATCAATC</td></tr><tr><td align=\"left\">M72-R</td><td align=\"left\">GAATTCAAAGACTCTTCTCCTCAGTG</td></tr><tr><td align=\"left\">P2-F</td><td align=\"left\">GGATCCATGACCTGGGGAAACTGGAC</td></tr><tr><td align=\"left\">P2-R</td><td align=\"left\">GAATTCTAGTTTCTGAGGGCCCAGAG</td></tr><tr><td align=\"left\">I7-F</td><td align=\"left\">GTTAACATGGAGCGAAGGAACCACAC</td></tr><tr><td align=\"left\">I7-R</td><td align=\"left\">GAATTCACCATCTCTGCTGGATTTC</td></tr><tr><td align=\"left\">OR118F</td><td align=\"left\">ATGGCGAACAGCACTACTGTTACTG</td></tr><tr><td align=\"left\">OR118R</td><td align=\"left\">TGTCTGGCTGAACTTTTGGAACTTGC</td></tr><tr><td align=\"left\">OR203F</td><td align=\"left\">ATGGAGGTGAACAGGACCCTGGTGACT</td></tr><tr><td align=\"left\">OR203R</td><td align=\"left\">TGGCTTCATGATTTTTCTCAGAGCC</td></tr><tr><td align=\"left\">GFP-LTF</td><td align=\"left\">GAATTCGCCACCATGGTGAGCAAGGGCG</td></tr><tr><td align=\"left\">GFP-LTR</td><td align=\"left\">CAATTGCTTAAGATACATTGATGAGTTTGG</td></tr><tr><td align=\"left\">GFP-MH2</td><td align=\"left\">AATGAATGCAATAGTTGTTGATAACTTGTTTATTG</td></tr><tr><td align=\"left\">GFP-MH2R</td><td align=\"left\">CAATAAACAAGTTATCAACAACTATTGCATTCATT</td></tr><tr><td align=\"left\">mCRY-R</td><td align=\"left\">GCGGCCGCTTTACTTGTACAGCTCGTCCATGCC</td></tr><tr><td align=\"left\">NeuroD-F</td><td align=\"left\">CAAGGTGGTACCTTGCTACTCCAAG</td></tr><tr><td align=\"left\">NeuroD-R</td><td align=\"left\">GGAATAGTGAAACTGACGTGCCT</td></tr><tr><td align=\"left\">Mash-F1</td><td align=\"left\">TGCCAGGCTCTCCTGGGAATGG</td></tr><tr><td align=\"left\">Mash-R1</td><td align=\"left\">CTGGTTCGGATAGATACAAATAG</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>In the RT-PCR experiments, olfactory marker protein transcripts were amplified by primers Eco OMP and OMP Xho, Adenylyl cyclase 3 by AC3F and AC3R, G_αolfby GolfF2 and GolfR2, cyclic nucleotide gated channel A2 subunit by CNGF2 and CNGR, NeuroD by NeuroD-F and NeuroD-R, Mash1 by Mash-F1 and Mash-R1, GAPDH by GAPDH-F and GAPDH-R, receptor M72 by M72-F and M72-R, I7 receptor by I7-F and I7-R, P2 receptor by P2-F and P2-R, MOR118 by OR118F and OR118R, and MOR182-5 by OR203F and OR203R.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1749-8104-3-22-1\"/>", "<graphic xlink:href=\"1749-8104-3-22-2\"/>", "<graphic xlink:href=\"1749-8104-3-22-3\"/>", "<graphic xlink:href=\"1749-8104-3-22-4\"/>", "<graphic xlink:href=\"1749-8104-3-22-5\"/>", "<graphic xlink:href=\"1749-8104-3-22-6\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Memory can be divided into declarative and non-declarative processes. Declarative or explicit memory is the conscious recall of knowledge about facts and events and is particularly well developed in the vertebrate brain. Non-declarative or implicit memory is the non-conscious recall of skilled behavior and other tasks and includes simple associative forms such as classical conditioning and non-associative forms such as sensitization [##REF##9539121##1##,##REF##8942955##2##]. During sensitization an animal learns about the properties of a single noxious stimulus enabling the formation of a learned fear response. The cellular and molecular mechanisms that underlie the storage of implicit memory have been most extensively analyzed in the gill- and siphon-withdrawal reflex of marine mollusk <italic>Aplysia</italic>. This organism offers several unique advantages for the study of learning and memory, such as a relatively simple and tractable central nervous system, large identified neurons, and well-characterized neural circuits related to specific behaviors that can be modified by learning [##UREF##0##3##]. In <italic>Aplysia</italic>, sensitization of the gill- and siphon-withdrawal reflex is induced by a strong stimulus to its tail [##UREF##1##4##]. Repetitive stimuli produce long-term sensitization that lasts days to several weeks whereas a single stimulus induces short-term sensitization lasting only minutes to a few hours [##REF##3572827##5##,##REF##4748675##6##]. These two forms of memory can be reconstituted in dissociated sensory-motor neuron cultures by the modulatory neurotransmitter serotonin (5-HT) [##REF##3958793##7##]. A single pulse of 5-HT induces short-term facilitation (STF), whereas five applications of 5-HT induce long-term facilitation (LTF) [##REF##3775383##8##].</p>", "<p>In contrast to the short-term synaptic changes, which involve covalent modifications of preexisting molecules leading to an alteration of preexisting synaptic connections, long-term synaptic changes require the synthesis of new macromolecules including mRNAs and proteins [##REF##3775383##8##, ####REF##2921606##9##, ##REF##2562494##10##, ##REF##11691980##11####11691980##11##]. In addition, long-term changes are accompanied by structural modifications including the growth of new synaptic connections between the sensory neurons and their target motor neurons [##REF##1356372##12##,##REF##2389145##13##]. These features of long-term, learning-related synaptic plasticity, are highly conserved throughout evolution of the nervous system. A variety of experimental systems, ranging in complexity from <italic>Aplysia </italic>to rodents, have been used to examine the molecular mechanism underlying long-term synaptic changes [##REF##9539121##1##,##REF##8942955##2##,##REF##2562494##10##,##REF##11691980##11##]. In this review, we focus on the role of nuclear transcription factors in the presynaptic sensory neurons of <italic>Aplysia </italic>during LTF.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Whereas the induction of short-term memory involves only covalent modifications of constitutively expressed preexisting proteins, the formation of long-term memory requires gene expression, new RNA, and new protein synthesis. On the cellular level, transcriptional regulation is thought to be the starting point for a series of molecular steps necessary for both the initiation and maintenance of long-term synaptic facilitation (LTF). The core molecular features of transcriptional regulation involved in the long-term process are evolutionally conserved in <italic>Aplysia, Drosophila</italic>, and mouse, and indicate that gene regulation by the <underline>c</underline>yclic AMP <underline>r</underline>esponse <underline>e</underline>lement <underline>b</underline>inding protein (CREB) acting in conjunction with different combinations of transcriptional factors is critical for the expression of many forms of long-term memory. In the marine snail <italic>Aplysia</italic>, the molecular mechanisms that underlie the storage of long-term memory have been extensively studied in the monosynaptic connections between identified sensory neuron and motor neurons of the gill-withdrawal reflex. One tail shock or one pulse of serotonin (5-HT), a modulatory transmitter released by tail shocks, produces a transient facilitation mediated by the cAMP-dependent protein kinase leading to covalent modifications in the sensory neurons that results in an enhancement of transmitter release and a strengthening of synaptic connections lasting minutes. By contrast, repeated pulses of 5-hydroxytryptamine (5-HT) induce a transcription- and translation-dependent long-term facilitation (LTF) lasting more than 24 h and trigger the activation of a family of transcription factors in the presynaptic sensory neurons including ApCREB1, ApCREB2 and ApC/EBP. In addition, we have recently identified novel transcription factors that modulate the expression of ApC/EBP and also are critically involved in LTF. In this review, we examine the roles of these transcription factors during consolidation of LTF induced by different stimulation paradigms.</p>" ]

[ "<title>A model system for examining the molecular biology of long-term memory – the <italic>Aplysia</italic> sensory to motor neuron synapse</title>", "<p>In sensory-motor neuron cultures, STF and LTF can be induced by applying 5-HT. One pulse of 5-HT activates PKA and PKC, probably via the activation of different types of G proteins. Activated PKA phosphorylates a potassium channel (S channel), resulting in the elevated influx of calcium leading to an increase in membrane excitability and spike broadening. PKC facilitates the mobilization of synaptic vesicles to the presynaptic active zone. Together, these kinases enhance transmitter release by modifying preexisting molecules [##REF##8551327##14##, ####REF##6957886##15##, ##REF##7807208##16##, ##REF##2172477##17####2172477##17##].</p>", "<p>LTF induced by repeated pulses of 5-HT requires the synthesis of both new proteins and RNAs. Inhibitors of protein or RNA synthesis selectively block LTF, but not STF when applied within a critical time window that encompasses the training protocol [##REF##3775383##8##]. Analogous to STF, cAMP-dependent protein phosphorylation is also involved in LTF and cAMP analogs induce LTF [##REF##2454509##18##]. Bacskai and colleagues first demonstrated that in response to repeated pulses of 5-HT the catalytic subunit of PKA translocates into the nucleus of the presynaptic sensory neuron to activate CREB-1 [##REF##7682336##19##]. Repeated pulses of 5-HT also induce phosphorylation of MAPK and the activated MAPK also translocates into the nucleus of the sensory neuron where it removes the repressive influence of ApCREB-2 [##REF##9208858##20##].</p>", "<p>Dash et al. provided the first evidence of the involvement of cAMP-inducible genes expressed during LTF in <italic>Aplysia</italic>. Microinjection of CRE (cAMP-responsive element) oligonucleotides into the nucleus of sensory neurons selectively blocked 5-HT-induced LTF without affecting short-term changes [##REF##2141668##21##]. These data first suggested that LTF requires the activation of cAMP-inducible genes, and that CRE oligonucleotides prevent interactions between CRE-binding protein (CREB)-related transcription factors and these genes. Using a newly developed gene transfer technique, Kaang and colleagues next showed directly that four or more pulses of 5-HT stimulate CRE-mediated gene expression. Moreover, transcription induced by 5-HT requires the phosphorylation of CREB on Ser¹¹⁹by PKA [##REF##8384857##22##]. Indeed Bartsch et al. went on to show that injection of phosphorylated CREB into the sensory neuron can by itself initiate the long-term process [##REF##9790528##23##]. Collectively these results suggested that a signaling axis composed of cAMP-PKA-CREB participates in the molecular cascade leading to the expression of LTF. Subsequent studies confirmed the involvement of a number of related downstream molecules in the induction of LTF, including CAMAP, ApC/EBP, and ApAF.</p>", "<title>ApCREBs – Central modulators of LTF</title>", "<p>In <italic>Aplysia</italic>, ApCREB1a and ApCREB2 have been characterized as an activator and repressor of LTF, respectively. ApCREB2 is a homolog of mammalian CREB2/ATF4 which is also identified as a transcriptional repressor [##REF##1534408##24##,##REF##8521521##25##]. Inhibition of ApCREB2 by injecting antiserum or double-strand RNA (dsRNA) into sensory neurons allowed a single pulse of 5-HT to produce translation-dependent LTF and the growth of new synapses [##REF##8521521##25##,##REF##12524159##26##]. Conversely, injection of an anti-CREB1 antibody into sensory neurons selectively blocked LTF. Moreover, introduction of the phosphorylated transcriptional activator, ApCREB1a, was sufficient to induce LTF. [##REF##9790528##23##]. PKA-mediated activation of ApCREB1a stimulated the downstream transcription factor, ApC/EBP, via recruiting CBP and subsequently facilitating histone acetylation [##REF##12437922##27##]. For activation of downstream gene expression by ApCREB1a, the inhibitory constraint of ApCREB2 must be relieved. This de-repression is mediated by the phosphorylation of ApCREB2 by nuclear translocated MAPK [##REF##9208858##20##,##REF##4345439##28##]. Together these results suggest that LTF requires not only the activation of memory-enhancer genes but also the inactivation of memory-suppressor genes. Moreover, CREBs appear to play a critical role in maintaining the dynamic balance between these positive and negative factors.</p>", "<p>CREB, a basic leucine zipper transcription factor, is also reported to be involved in long-term plasticity in the nervous systems of other organisms, including fly and mouse. In transgenic <italic>Drosophila</italic>, expression of dCREB2b led to the blockage of long-term memory, whereas dCREB2a facilitated memory [##REF##7720066##29##,##REF##7923376##30##]. Similarly, CREB-deficient mice displayed impaired long-term potentiation (LTP) and long-term memory [##REF##7923378##31##]. The threshold for late phase LTP was lowered in the hippocampus from mice expressing the constitutively active form of CREB [##REF##11893339##32##].</p>", "<title>ApC/EBP – A key downstream gene for LTF</title>", "<p>In view of the critical roles of CREB in memory consolidation, characterization of its downstream effectors has been a major focus of research in both invertebrate and vertebrate learning models [##REF##16202713##33##, ####REF##7625697##34##, ##REF##9530494##35####9530494##35##]. In <italic>Aplysia </italic>the CCAAT enhancer-binding protein (ApC/EBP), an immediate early gene during the consolidation phase of LTF, was found by Alberini et al. to be a downstream target of ApCREB1 [##REF##8137425##36##]. The C/EBP family of transcription factors contains a basic leucine-zipper domain. Specifically, expression of ApC/EBP is rapidly induced in response to 5-HT treatment and this occurs to an immediate early gene in a translation-independent manner [##REF##8137425##36##]. Inhibition of ApC/EBP by injection of ERE oligonucleotides, ApC/EBP antiserum or dsRNA into the sensory neurons in sensory-to-motor neuron cultures during a critical time window blocked 5-HT-induced LTF [##REF##8137425##36##,##REF##11533225##37##]. Moreover, a single pulse of 5-HT which normally induces only STF, produces LTF when ApC/EBP is overexpressed in the sensory neuron [##REF##11533225##37##]. These findings support the idea that ApC/EBP is both necessary and sufficient to consolidate short-term memory into long-term memory. However, since overexpression of ApC/EBP alone does not induce LTF, an additional component must be required for converting STF to LTF. Lee and colleagues used the RNA interference technique designed to block the function of ApC/EBP and similarly found that this blocked LTF in <italic>Aplysia </italic>[##REF##12524159##26##,##REF##11533225##37##]. Moreover, in addition to these studies in <italic>Aplysia</italic>, C/EBPβ and -δ are induced in the rodent hippocampus after inhibitory avoidance learning, suggesting that C/EBPs are highly conserved molecular components of the CREB-dependent signal pathway involved in memory consolidation [##REF##11150323##38##].</p>", "<p>ApC/EBP is also known to be induced by the neural activity. The depolarization-induced ApC/EBP induction appears to be mediated by transient induction of the nucleolar protein, ApLLP, which was recently characterized as a novel transcription factor induced by neural activity in <italic>Aplysia </italic>sensory neuron [##REF##16504946##39##]. Kim <italic>et al. </italic>also showed that a single pulse of 5-HT can produce LTF when the synapse is pretreated with high potassium solution. LTF induced by this protocol was completely blocked by the injection of anti-ApLLP or anti-ApC/EBP antibody [##REF##16504946##39##].</p>", "<p>One important feature of immediate early genes such as ApC/EBP, is that their expression is tightly regulated within a specific and narrow time window. ApC/EBP mRNA displays a peak expression at 2 h after induction that rapidly returns to the basal levels [##REF##8137425##36##]. Recent studies have found that the ApC/EBP 3' UTR contains putative AU-rich element (ARE) sequences which are cis-acting regulatory elements commonly found in labile mRNAs [##REF##16805836##40##]. Different sets of ARE binding proteins may interact with ApC/EBP mRNA to regulate its stability and/or translatability [##REF##11564879##41##, ####REF##12704645##42##, ##REF##11255003##43####11255003##43##]. Yim et al. found that an ARE binding protein, ApELAV binds to and stabilizes ApC/EBP mRNA, suggesting that post-transcriptional regulation of ApC/EBP may also play an important role during LTF [##REF##16805836##40##].</p>", "<title>ApAF – A binding partner for both ApCREB2 and ApC/EBP</title>", "<p>Both ApC/EBP and ApCREBs are transcription factors containing the basic leucine zipper (bZIP) domain in the C-terminus. This domain is involved in both DNA binding and multimerization [##REF##9790528##23##,##REF##8521521##25##,##REF##11483993##44##]. Using the bZIP domain of ApC/EBP as bait, Bartsch and colleagues screened a cDNA library to identify additional transcription factors acting downstream of ApCREB1. In this fashion, they cloned a novel transcription factor ApAF, whose activity is regulated by PKA [##REF##11106730##45##]. In contrast to ApC/EBP, which is induced in response to 5-HT, ApAF is a constitutively expressed gene. Interestingly, an <italic>in vitro </italic>binding assay revealed that ApAF interacts with both ApCREB2 and ApC/EBP, but not ApCREB1. Inhibition of ApAF by injection of a specific antibody blocked LTF induced by repeated pulses of 5-HT, suggesting that ApAF is necessary for LTF. Previously, it had been found that injection of phosphorylated ApCREB1a by itself or anti-ApCREB2 antibody combined with a single pulse of 5-HT induced LTF that phenocopied 5 × 5-HT-induced LTF [##REF##9790528##23##,##REF##8521521##25##]. ApAF is involved in both forms of LTF: an anti-ApAF antibody blocked LTF induced by phosphorylated CREB1a as well as that by ApCREB2 antibody injection paired with one pulse of 5-HT. Moreover, overexpression of ApAF enhanced both LTF induced by 5 × 5-HT and ApCREB2 antibody with 1 × 5-HT [##REF##11106730##45##]. Thus, ApAF may be a potential memory enhancer gene downstream of ApCREB1 and ApCREB2.</p>", "<p>To determine whether ApC/EBP is the critical partner of ApAF, Lee and colleagues investigated the effects of silencing the ApAF gene on LTF induced by ApC/EBP overexpression paired with one pulse of 5-HT [##REF##16966424##46##]. ApAF inhibition by dsRNA completely blocked LTF induced by both ApC/EBP overexpression and 5 × 5-HT. In combination with a single pulse of 5-HT, the ApAF-ApC/EBP heterodimer produced LTF, even in the absence of CRE- and CREB-mediated gene expression. These results provide direct evidence that the ApAF-ApC/EBP heterodimer is a key downstream effecter of ApCREB. Furthermore, ApAF enhances ERE-mediated gene expression by cooperating with ApC/EBP and phosphorylation at Ser-266 of ApAF by PKA is required for activation of the ApAF-ApC/EBP heterodimer during 5-HT-induced LTF [##REF##16966424##46##]. These data explain why ApC/EBP overexpression in the absence of 5-HT could not convert STF to LTF. The single pulse of 5-HT in ApC/EBP-induced LTF possibly functions in triggering the phosphorylation of ApAF by activated PKA.</p>", "<p>Lee et al. also examined the role of Ser-266 phosphorylation of ApAF in the relief of ApCREB2 repression [##REF##16966424##46##]. Overexpression of a dominant negative mutant of ApAF which cannot be phosphorylated at Ser-266 completely blocked both LTF induced by 5 × 5-HT and that by the ApC/EBP overexpression combined with 1 × 5-HT. Moreover, this mutant restored ApCREB1-mediated gene expression and 5-HT-induced LTF repressed by ApCREB2 as efficiently as its wild type counterpart, suggesting that Ser-266 phosphorylation of ApAF is not required to relieve ApCREB2 repression [##REF##16966424##46##]. However, the precise signaling pathway that regulates the interactions between ApAF and ApCREB2 remains to be characterized. Taken together, these studies of ApAF indicate that transcriptional regulation of memory consolidation is quite diverse and can recruit both direct and indirect interactions between transcription factors.</p>", "<title>CAMAP – A retrograde signal from the membrane to the CRE promoter</title>", "<p>Neurons display a distinct highly differentiated form which consists of three basic compartments: a cell body or soma which contains the nucleus harboring genomic information and two types of processes axons and dendrites. Dendrites are input elements of the neuron. Together with the cell body they receive synaptic contacts from other neurons. Axons are the output elements of the neuron. The branches of each axon form numerous synaptic connections with other neurons. It is well known that long-term synaptic plasticity requires the synthesis of both new RNAs and proteins. This raises three fundamental questions: 1) Does synaptic plasticity always occur in a cell-wide manner? 2) If not, how does the nucleus identify the correct synapses for delivery of gene products to achieve synapse-specific plasticity? 3) Is the nucleus the only site responsible for transcription and translation?</p>", "<p>To address the question of synapse specificity, Martin and her colleagues developed a new culture system in <italic>Aplysia </italic>consisting of a bifurcated <italic>Aplysia </italic>sensory neuron which makes synapses with two spatially separated motor neurons in culture [##REF##9428516##47##]. They found that 5-HT can induce branch-specific LTF that was dependent on CREB activation in the nucleus of presynaptic sensory neuron. Branch-specific LTF was also accompanied by synapse-specific growth of new sensory neuron synapses. These studies highlight the importance of a retrograde signal propagating from the stimulated synaptic site to the nucleus. The CREB-downstream molecules produced in the cell body can be captured by other synapses which have been tagged or marked. This synaptic mark is PKA-dependent; however, rapamycin-dependent local protein synthesis is required for LTF to persist for more than 72 h [##REF##9428516##47##,##REF##10535740##48##]. Further molecular studies have dissected the characteristics of the retrograde signal and the synaptic mark.</p>", "<p>An early step in the growth of new synaptic connections is the internalization of an NCAM immunoglobulin-related cell adhesion molecule – apCAM. In recent studies Lee et al. addressed the question: How does this internalization of apCAM relate to the activation of transcription? Lee found that CAMAP is an interacting partner of apCAM in the sensory neuron. CAMAP serves as a transcriptional co-activator that is also a crucial retrograde signaling molecule involved in the initiation phase of LTF [##REF##17512412##49##]. ApCAM is down-regulated upon application of 5-HT [##REF##1585176##50##]. Serotonin leads to clathrin-mediated endocytosis of the transmembrane isoform of apCAM (TM-ApCAM) from the surface membrane of sensory neurons and this internalization depends on phosphorylation of its cytoplasmic tail by MAPK [##REF##1585177##51##,##REF##9208859##52##]. When TM-apCAM was overexpressed in sensory neurons, five pulses of 5-HT failed to produce synaptic facilitation or enhancement of synaptic growth, suggesting that down-regulation of apCAM is required for both LTF and the presynaptic structural changes induced by 5-HT [##REF##15254221##53##]. Whereas MAPK is known to be involved in apCAM downregulation, the subcellular mechanisms responsible for apCAM internalization remain to be characterized. CAMAP (apCAM-Associated Protein) was cloned by yeast two-hybrid screening using the cytoplasmic tail of TM-ApCAM as bait [##REF##17512412##49##]. CAMAP is colocalized with apCAM at the surface of the plasma membrane in the basal state and is translocated to the nucleus of sensory neuron after treatment with 5-HT. Nuclear translocation and dissociation from apCAM are modulated by PKA-mediated phosphorylation of CAMAP. A phosphorylation-mimicking mutant of CAMAP can dissociate from apCAM and translocate to the nucleus in the absence of 5-HT stimulation [##REF##17512412##49##]. How does CAMAP translocate to the nucleus? Importins, which transport cargo molecules from the cytosol to nucleus, are critically involved in synaptic plasticity in both <italic>Aplysia </italic>and rodent brain [##REF##15603742##54##]. This raises the possibility that importin may transport CAMAP into the nucleus of the sensory neuron.</p>", "<p>In view of nuclear translocation of CAMAP from the plasma membrane, Lee et al. suggested that CAMAP acts as a retrograde signaling molecule in the induction of LTF. To act as a retrograde signal, a molecule must meet several criteria, specifically, 1) it should translocate into the nucleus from the synaptic site in response to stimuli that induce synaptic plasticity, such as LTF and LTP, 2) it should play a specific function in the nucleus, and 3) blockage of its translocation and function should inhibit the long-term synaptic change. CAMAP appears to fulfill all of the above requirements. First, CAMAP translocates to the nucleus following both cell-wide and synapse-specific applications of 5-HT. After 5-HT treatment, the mobility of CAMAP is significantly increased at the distal neurites of sensory neurons. Second, CAMAP binds to ApCREB1 in the nucleus, where it acts as a transcriptional co-activator that can induce ApC/EBP expression. Interestingly, the N-terminal region, but not full-length CAMAP displayed transcriptional activity. The C-terminus of CAMAP appears to act as an autoinhibitory domain. This inhibitory clamp is relieved by PKA phosphorylation of CAMAP. Details of the molecular mechanisms that underlie the co-activator function of CAMAP and the PKA phosphorylation-dependent restoration of transcriptional activity of the N-terminus of CAMAP are currently not known. Finally, blockage of CAMAP expression by dsRNA completely suppresses 5-HT-induced ApC/EBP upregulation and LTF. Moreover, CAMAP dsRNA blocks synapse-specific LTF induced by local application of 5-HT at the synapse. Taken together, these results indicate that CAMAP is a critical retrograde messenger in the initiation of LTF.</p>", "<p>The precise role of CAMAP in the internalization of apCAM remains unclear. We have recently found that overexpression of mutant CAMAP that cannot be phosphorylated by PKA impaired the 5-HT-induced internalization of apCAM [##REF##17512412##49##]. This finding suggests that CAMAP tethers apCAM to the plasma membrane in the basal state, and that the phosphorylation and nuclear translocation of CAMAP are necessary for the subsequent down-regulation of apCAM.</p>", "<title>Chromatin alteration and epigenetic changes in gene expression with memory storage</title>", "<p>Although epigenetic mechanisms were widely known to be involved in the formation and long-term storage of cellular information in response to transient environmental signals, the discovery of their putative relavance in adult brain function is relatively recent [##REF##12437922##27##,##REF##15654323##55##]. The epigenetic marking of chromatin, such as histone modification, chromatin remodeling and the activity of retrotransposons, may have long-term consequences in the transcriptional regulation of specific loci involved for long-term synaptic changes [##REF##16226449##56##].</p>", "<p>The contribution of histone tail acetylation, a modification that favors transcription and is associated with active loci, to LTF formation was first revealed by the study of Guan et al. in <italic>Aplysia </italic>neurons [##REF##12437922##27##]. This study found that both facilitatory and inhibitory stimuli bidirectionally alter the acetylation stage and structure of promoters driven by the expression of genes involved in the maintenance of LTF, such as ApC/EBP. It also demonstrated that enhancing histone acetylation with histone deacetylase (HDAC) inhibitors facilitates the induction of LTF (Guan et al. 2002). HDAC inhibitors have recently been shown to have similar effects during L-LTP in the Schaffer collateral pathway of mammals and to enhance memory formation in hippocampus-dependent tasks [##REF##15207239##57##, ####REF##15207240##58##, ##REF##15273246##59##, ##REF##15102957##60##, ##REF##17468743##61####17468743##61##]. HDAC inhibitor, sodium butyrate, has been shown to induce the growth of new dendrites and synapses, which might be an underlying mechanism of its memory enhancing effects [##REF##17468743##61##]. Moreover, mice with reduced histone acetyltransferase activity, such as different mouse models for Rubinstein-Taybi mental retardation syndrome, have deficits in both long-lasting forms of memory and LTP [##REF##15207239##57##,##REF##15207240##58##,##REF##15805310##62##,##REF##12930888##63##]. These results indicate that critical chromatin changes occur during the formation of long-term memory and that these changes are required for the stable maintenance of these memories.</p>", "<title>Perspectives</title>", "<p>During the last decade molecular studies have increased our understanding of the signaling and regulatory mechanisms that underlie LTF (Figure ##FIG##0##1##). Several research groups have generated a variety of cellular models of long-term memory by investigating 5-HT-induced LTF and other forms of long-term synaptic changes induced by different stimulation paradigms in <italic>Aplysia</italic>.</p>", "<p>Recently, operant conditioning was demonstrated in the gill-withdrawal and feeding behavior in <italic>Aplysia </italic>and an electrophysiological study revealed that operant and classical conditioning of feeding behavior differentially modify the intrinsic excitability of an identified neuron [##REF##16311590##64##, ####REF##12040200##65##, ##REF##16510722##66####16510722##66##]. PolyADP-ribose-polymerase 1 (PARP1) facilitates the transcription of long-term memory related genes by decondensing chromatin structure in neurons that mediate operant conditioning [##REF##15205535##67##]. However, the transcription factors involved in this behavioral modification are yet to be identified.</p>", "<p>Interestingly, ApC/EBP is the common downstream molecule of the novel transcription factors, ApLLP and CAMAP. ApC/EBP, which pairs with ApAF, could activate the transcription of effector genes critically involved in the consolidation and maintenance of long-term memory [##REF##8137425##36##]. Genes encoding structural proteins, such as clathrin light chain and the chaperon BiP were identified as late effector genes [##REF##7684236##68##,##REF##1360013##69##]. The elongation factor 1 alpha was also suggested to be essential for maintaining newly formed synapses [##REF##14578450##70##]. However, the number of late genes identified thus far represents only a beginning. Since the DNA-binding motifs of ApC/EBP and ApAF homodimer or heterodimer have been analyzed, completion of the ongoing <italic>Aplysia </italic>genome sequencing project should facilitate the identification of other novel late effector molecules [##REF##11106730##45##].</p>", "<p>Recently, advances have also been made in clarifying the molecular mechanisms that contribute to learning-related synaptic plasticity in the mammalian brain, particularly those that underlie the induction and expression of LTP and LTD [##REF##15450156##71##,##REF##15450161##72##]. When it comes to transcriptional regulation, however, our current understanding is far from complete. <italic>Aplysia </italic>was the first organism in which cAMP was shown to play a critical role in learning-related synaptic plasticity [##REF##4345439##28##,##REF##186870##73##]. Since signaling cascades that underlie the expression of long-term memory are surprisingly well conserved throughout the species, insights from the molecular studies of <italic>Aplysia </italic>should provide an important foundation for future studies into the transcriptional regulation of memory formation in the more complex mammalian brain.</p>", "<title>Authors' contributions</title>", "<p>All authors participated in developing the ideas, the writing, discussion and integration of the information. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Our special thanks go to Hyoung Kim for the graphic work of the figure. This work was supported by the Creative Research Initiative Program of the Korean Ministry of Science and Technology (to B.-K.K.).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Schematic model of signaling pathways underlying long-term facilitation in <italic>Aplysia </italic>sensory neuron</bold>. The repeated treatments with neurotransmitter 5-HT activate a G-protein coupled receptor that stimulates adenylyl cyclase, which in turn activates PKA. MAPK are also activated and translocates into the nucleus. At the synaptic site, PKA stimulates the nuclear translocation of the retrograde signal molecule CAMAP via phosphorylating its Ser¹⁴⁸. This phosphorylation results in both the dissociation from TM-apCAM and the restoration of its transcriptional activity from autoinhibition. In the nucleus, MAPK phosphorylates CREB2 which represses CREB1 and ApAF in the absence of 5-HT. Once freed from CREB2 and stimulated by PKA, CREB1 forms a homodimer to activate the downstream target gene, ApC/EBP. Translocated CAMAP acts as a co-activator of CREB1. ApC/EBP interacts with ApAF that is activated by PKA to form a core downstream effector of CREB1. ApC/EBP-ApAF heterodimer induces the late genes which are critical for the consolidation and maintenance of LTF. Robust neural activity induces and activates the transcription factor, ApLLP in the nucleus in a calcium-dependent manner. ApLLP induces ApC/EBP expression and lowers the threshold for LTF induction. Elucidating the downstream molecule of ApC/EBP remains to be challenged. SNS, strong noxious stimulus.</p></caption></fig>" ]

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[ "<title>Background</title>", "<p>Although morphine is the most widely used analgesic to treat moderate to severe pain its use is hindered by the development of physical dependence and tolerance to its analgesic effects. The utility of N-methyl-D-aspartate receptor (NMDAR) antagonists in both potentiating and prolonging the analgesic effects of morphine while attenuating analgesic tolerance and physical withdrawal symptoms has been widely reported (see [##REF##12373532##1##, ####REF##11730974##2##, ##REF##10972459##3##, ##REF##10706971##4##, ##REF##14636974##5####14636974##5##] for review). For example, the non-competitive NMDAR antagonist MK801 has been shown to modulate morphine analgesia, reverse analgesic tolerance and reduce withdrawal behaviors [##REF##15157688##6##, ####REF##15644592##7##, ##REF##1824728##8##, ##REF##8895234##9####8895234##9##]. Pharmacological manipulation of NMDA receptor activity may pose a useful strategy for increasing the efficacy of morphine as a treatment for chronic pain in the future.</p>", "<p>NMDARs are composed of NR1, NR2 (A, B, C, and D) and NR3 (A and B) subunits in the central nervous system. It is known that the NR2A and NR2B subunits predominate in the forebrain neurons, where they determine many functional properties of NMDARs [##REF##9463421##10##,##REF##7512349##11##]. For example, NR2B containing NMDA receptors desensitize less and take longer to recover from desensitization as compared to NR2A containing NMDA receptors [##REF##9463421##10##,##REF##7512349##12##]. The down regulation of NR2B expression throughout development is marked by a concomitant change in NMDA receptor function [##REF##16181726##13##]. The unique functional properties of NR2B make it an attractive target for those who wish to study the mechanisms behind experience dependent changes in synaptic plasticity and behavioral responses.</p>", "<p>The anterior cingulate cortex (ACC) plays important roles in emotion, addiction, learning and memory and persistent pain [##REF##15450163##14##, ####REF##7895011##15##, ##REF##11839523##16##, ##REF##12040168##17####12040168##17##]. Overexpression of NR2B in the ACC and other forebrain regions significantly enhanced learning and memory as well as chronic pain caused by peripheral inflammation [##REF##10485705##18##,##REF##11175877##19##]. NR2B receptors expressed in the ACC also appear to play a role in synaptic plasticity (including LTP and long-term depression (LTD)) and the expression of fear memory [##REF##16157280##20##,##REF##16319310##21##]. Since addiction and memory share certain intracellular cascades in common [##REF##16055762##22##,##REF##15450168##23##], we wanted to determine if NR2B receptors in the ACC play a role in the expression of analgesic tolerance and changes in plasticity occurring after chronic morphine use. Our results reveal a significant enhancement of NMDA NR2B mediated responses in the ACC after chronic morphine treatment and suggest that such an enhancement may contribute to the development of morphine tolerance.</p>" ]

[ "<title>Methods</title>", "<title>Animals</title>", "<p>Adult male (8–10 weeks old) C57Bl/6 mice from Charles River were used in all experiments. At the conclusion of experiments, animals were humanely killed by an overdose of inhaled anesthetic (isoflurane). The animals were housed on a 12 h: 12 h light: dark cycle with food and water available <italic>ad libitum</italic>. All mouse protocols are in accordance with NIH guidelines and were approved by the Animal Care and Use Committee at the University of Toronto. All experiments were performed blind to the treatment.</p>", "<title>Hot-plate test</title>", "<p>The hotplate consists of a thermally-controlled metal plate (55°C), surrounded by four Plexiglas walls (Columbia Instruments; Columbus, Ohio). The time between placement of the animal on the plate and the licking or lifting of a hindpaw is measured with a digital timer. Mice are removed from the hotplate immediately after the first response and a cut-off time of 30 seconds was imposed to prevent tissue damage. Response latencies are reported as a percentage of maximal possible effect (MPE) [(response latency-baseline response latency)/(cut off latency-baseline response latency)*100].</p>", "<title>Morphine administration</title>", "<p>To test for acute morphine induced antinociception, Ro 256981 (Tocris Cookson, St Louis, MO, 5 mg/kg in saline) or an equivalent volume of saline was injected 10–15 minutes before morphine (10 mg/kg s.c.). To study the role of NR2B in the expression of analgesic tolerance, mice were injected once a day for eight days with 10 mg/kg morphine (s.c.) and received Ro 256981 (5 mg/kg, i.p.) before the last morphine injection. To test for a role in the acquisition of tolerance, mice were injected with Ro 256981 (5 mg/kg, i.p.) before morphine (10 mg/kg s.c.) daily for eight days.</p>", "<title>ACC cannula implantation and microinjection</title>", "<p>Under ketamine and xylazine anesthesia, 24-gauge guide cannulas were implanted bilaterally into the ACC (0.7 mm anterior to Bregma, ± 0.4 mm lateral from the midline, 1.7 mm beneath the surface of the skull). Mice were given at least 2 weeks to recover after cannula implantation. For intra-ACC injections, mice were anesthetized with 2–3% isoflurane anesthesia in a gas mixture of 30% O₂balanced with nitrogen and placed in a Kopf stereotaxic instrument. A 30-gauge injection cannula was 0.1 mm lower than the guide. The microinjection apparatus consisted of a Hamilton syringe (5 ml), connected to an injector needle (30 gauge) by a thin polyethylene tube, and motorized syringe pump. Ro 256981 (1.0 μg/μl, in saline) was infused into each side of the ACC at a rate of 0.05 μl/min, an equivalent volume of saline was used as a control. After injection, the microinjection needle was left in place for at least 5 minutes.</p>", "<title>Whole-cell Patch Clamp Recordings</title>", "<p>Mice were anesthetized with 1–2% isoflurane before decapitation. Coronal slices containing the ACC (300 μm) were prepared using methods reported previously [##REF##16319310##21##]. Slices were then transferred to a room temperature submerged recovery chamber with oxygenated (95% O₂and 5% CO₂) solution containing (in mM): NaCl, 124; NaHCO₃, 25; KCl, 2.5; KH₂PO₄, 1; CaCl₂, 2; MgSO₄, 2; glucose, 10. After a one-hour recovery period, slices were placed in a recording chamber on the stage of an Axioskop 2FS microscope (Zeiss, Thornwood, NY) equipped with infrared DIC optics for patch clamp recordings. Postsynaptic currents were recorded with an Axon 200B amplifier (Molecular Devices, Union City, CA). Excitatory postsynaptic currents (EPSCs) were recorded from layer II/III neurons with an Axon 200B amplifier (Molecular devices, CA) and stimuli were delivered by a bipolar tungsten stimulating electrode placed in layer V of ACC slices. Electric square-wave voltage pulses (200 μs, 4–14 V) were generated using a Grass S88 stimulator (Grass instrument Co., Quincy, MA) attached to a Grass SIU5D isolator unit. EPSCs were induced by repetitive stimulations at 0.02 Hz and neurons were voltage clamped at -70 mV. The recording pipettes (3–5 MΩ) were filled with a solution containing (mM): 145 K-gluconate, 5 NaCl, 1 MgCl₂, 0.2 EGTA, 10 HEPES, 2 Mg-ATP, and 0.1 Na₃-GTP (adjusted to pH 7.2 with KOH). Unless stated otherwise, the membrane potential was held at -65 mV throughout all experiments.</p>", "<p>LTP was induced within 12 min after establishing the whole-cell configuration to prevent a wash out effect [##REF##15673679##59##]. The LTP induction protocol used (referred to as spike-timing protocol) pairing 3 presynaptic stimuli, which caused 3 EPSPs (10 ms ahead), with 3 postsynaptic APs at 30 Hz, paired 15 times every 5 s [##REF##16157280##20##]. The NMDA receptor-mediated component of EPSCs was pharmacologically isolated in ACSF containing: CNQX (20 μM) and picrotoxin (100 μM). The patch electrodes for NMDA receptor-mediated EPSCs contained (in mM) 102 cesium gluconate, 5 TEA chloride, 3.7 NaCl, 11 BAPTA, 0.2 EGTA, 20 HEPES, 2 MgATP, 0.3 NaGTP, and 5 QX-314 chloride (adjusted to pH 7.2 with CsOH). Neurons were voltage clamped at -20 mV and NMDA receptor-mediated EPSCs were evoked at 0.05 Hz. Access resistance was 15–30 MΩ and was monitored throughout the experiment. Data were discarded if access resistance changed more than 15% during an experiment. Statistical comparisons were performed using the Student's t-test.</p>", "<title>Data analysis and statistics</title>", "<p>Statistical comparisons were made using one way or two way repeated measures ANOVA (Student-Newmann-Keuls test was used for <italic>post hoc </italic>comparison). All data is represented by the mean +/- S.E.M. In all cases, p &lt; 0.05 is considered statistically significant.</p>" ]

[ "<title>Results</title>", "<title>NR2B plays a role in acute morphine-induced analgesia</title>", "<p>NMDA receptor antagonists are reported to potentiate, inhibit, or not to alter morphine antinociception with variable results arising from the use of different doses of antagonist and morphine, as well as experimental animals and tests for nociception [##REF##12373532##1##]. To determine the effect of Ro 256981 on acute morphine antinociception, mice were injected intraperitoneally with either Ro 256981 or saline (n = 4, i.p.) before receiving a single injection of morphine (10 mg/kg, s.c), and hot-plate response latencies were recorded every 30 min afterwards for three hours. Statistical analysis revealed a significant affect of treatment (p &lt; 0.05) and time (p &lt; 0.001) with a significant interaction between treatment and time (p &lt; 0.05). Significant differences between response latencies occurred 90, 120, 150 and 180 minutes after morphine injection (p &lt; 0.05 for all, Figure ##FIG##0##1A##). It is important to note that Ro 256981 is not in itself analgesic at this dose [##REF##16319310##21##]. These results suggest that Ro 256981 potentiates the analgesic effect of morphine.</p>", "<title>NR2B inhibition affects opioid analgesic tolerance</title>", "<p>To determine if antagonizing the activity of NR2B can affect opioid analgesic tolerance, mice (n = 8) were given eight daily injections of morphine (10 mg/kg, s.c.) and received Ro 256981 (5 mg/kg, i.p.) before the last morphine injection. One way repeated measures ANOVA revealed a significant affect of treatment (p &lt; 0.001) with significant increases in response latency occurring between Day 8 (Ro + morphine) and Days 6 and 7 (p &lt; 0.001, p &lt; 0.05 respectively, morphine alone, Figure ##FIG##0##1B##). However, Ro 256981 did not totally reverse the established opioid tolerance since there were still significant differences between response latencies on Day 8, as compared to Day 1 (p &lt; 0.01), Day 2 (p &lt; 0.01) and Day 3 (p &lt; 0.05). Interestingly, there was not a significant difference between responses on Day 8 and those on Days 4 and 5 (p = 1.00 and p = 0.61 respectively), suggesting that Ro 256981 administration on the 8^thday of morphine treatment restored morphine-induced antinociception to a level early on in the development of analgesic tolerance. Hot-plate responses were significantly longer on Days 4 and 5, as compared to Day 7 (p &lt; 0.001 for both).</p>", "<title>Attenuation of analgesic tolerance by chronic co-administration of Ro 256981 with morphine</title>", "<p>To determine if NR2B receptors play a role in the acquisition of opioid analgesic tolerance, Ro 256981 was co-administered daily with morphine. In this experiment, mice received either Ro 256981 (5 mg/kg, i.p., n = 11) before morphine (10 mg/kg, s.c.), morphine alone (n = 7) or saline (n = 5) daily for eight days. Statistical analysis revealed a significant affect of treatment (p &lt; 0.001) and day (p &lt; 0.001) as well as a significant interaction between treatment and day (p &lt; 0.001, Figure ##FIG##0##1C##). Importantly, there were no significant differences across days for mice receiving daily saline injections. Tolerance developed in mice receiving morphine alone (Day 1 vs. Day 8: p &lt; 0.001) and in mice receiving both Ro 256981 and morphine (Day 1 vs. Day 8: p &lt; 0.001). However, post-hoc analysis revealed significant differences in response latencies between treatment groups on individual days. For example, there was no difference between morphine treated and Ro 256981 and morphine treated mice on Day 1 (p = 0.74), but a significant difference arose on Day 2 (p &lt; 0.001) and persisted during Days 3, 4, 6 and 7 (p &lt; 0.001, p &lt; 0.01, p &lt; 0.05, p &lt; 0.05 respectively). It is also interesting to note that significant differences between morphine-treated mice and control mice receiving saline disappeared by the 6^thday of treatment (p = 0.28), which did not occur until the 8^thday in mice receiving both Ro 256981 and morphine (p = 0.17). Taken together, these results suggest that daily co-administration of Ro 256981 with morphine can hinder the development of opioid analgesic tolerance but not completely abolish its establishment, at least at the dose tested in this study.</p>", "<title>NR2B receptors in the ACC play a role in the expression of opioid tolerance</title>", "<p>To determine if inhibiting NR2B receptors in the ACC could reverse established analgesic tolerance, intra-ACC injections of Ro 256981 were performed in tolerant mice. Daily injections of morphine (10 mg/kg, s.c.) were administered to mice implanted bilaterally with cannulas directed to the ACC. Before testing hotplate response latencies on the eighth day, mice received either Ro 256981 (n = 7, 1 μg/μl, bilaterally) or saline (n = 5) injections in the ACC. While there were no differences in response latencies on the seventh day of testing between groups (p = 0.72), there was a significant difference in responses 30 minutes after microinjection (p &lt; 0.001, Figure ##FIG##1##2B##). The effect of Ro 256981 in the ACC was abolished by one hour after microinjection (p = 0.66). These results indicate that NR2B receptors in the ACC play a role in the behavioral responses associated with opioid analgesic tolerance.</p>", "<title>AMPA receptor mediated synaptic transmission after morphine treatment</title>", "<p>To determine whether synaptic transmission was altered in morphine tolerant mice, conventional whole-cell patch clamp recordings were performed in visually identified pyramidal neurons in layer II/III of the ACC. We recorded AMPA receptor-mediated miniature excitatory postsynaptic currents (mEPSCs) in saline or morphine-treated mice. In the presence of tetrodoxin (1 μM), AP5 (50 μM) and picrotoxin (100 μM), AMPA mEPSCs were pharmacologically isolated (Figure ##FIG##2##3A##). The frequency of mEPSCs in saline treated mice was 1.3 ± 0.2 Hz (n = 15). No significant difference was found in the frequency of mEPSCs in morphine treated mice (1.1 ± 0.1 Hz, n = 16, P = 0.48) compared to saline (Figure ##FIG##2##3A## and ##FIG##2##3B##). Likewise, there was no difference in mEPSC amplitude between saline treated (7.1 ± 0.3 pA, n = 16) and morphine treated mice (7.6 ± 0.3 pA, n = 16, P = 0.17) (Figure ##FIG##2##3A## and ##FIG##2##3C##). These results suggest that AMPA receptor-mediated synaptic transmission is normal in morphine tolerant mice.</p>", "<title>Functional upregulation of synaptic and extrasynaptic NR2B in morphine tolerant mice</title>", "<p>We have previously reported roles for the NR2B subunit in synaptic plasticity in the ACC [##REF##16157280##20##,##REF##16319310##21##,##REF##16045501##24##]. To determine if NR2B receptors in the ACC were affected by chronic morphine treatment, ACC neurons were held at a potential of -20 mV to relieve the Mg²⁺blockade and NMDA EPSCs were isolated in the presence of CNQX (50 μM) and picrotoxin (100 μM). Perfusion of Ro 256981 (3 μM) caused a substantial decrease in NMDA EPSCs (Figure ##FIG##3##4A##), referred to as the NR2B component. In saline treated mice, the NR2B component was 11.6 ± 3.8% of the total NMDA current (n = 6). A significant increase in the NR2B component was observed in morphine treated mice (25.6 ± 3.8% of total currents, n = 8, P &lt; 0.05) (Figure ##FIG##3##4A## and ##FIG##3##4B##). Next, a short train of stimuli consisting of 7 pulses at 200 Hz was used to study the extrasynaptic NR2B component in the ACC after chronic morphine treatment. Consistent with previous studies in the hippocampus [##REF##15146049##25##], this stimulation induced larger NMDA EPSCs with a slower decay (Figure ##FIG##3##4C##), suggesting that extrasynaptic NMDA receptors are involved. Ro 256981 (3 μM) blocked 34.1 ± 5.4% (n = 7) of the total train-induced NMDA current in saline treated mice (Figure ##FIG##3##4C## and ##FIG##3##4D##), while a significant increase in the NR2B component was again seen in morphine treated mice (53.7 ± 4.5%, n = 7, P &lt; 0.05) (Figure ##FIG##3##4C## and ##FIG##3##4D##). Taken together, these results suggest that chronic morphine treatment increases both synaptic and extrasynaptic NR2B NMDA receptor activity.</p>", "<title>Enhanced LTP in the ACC of morphine treated mice</title>", "<p>In the ACC, NR2B receptors contribute to the induction of long-term potentiation (LTP) [##REF##16157280##20##]. Since the function of NR2B was upregulated in the ACC of morphine treated mice, we investigated whether LTP was also enhanced. LTP was induced using the spike-timing protocol (see Materials and Methods) within 12 minutes after establishing the whole-cell configuration to avoid washout of intracellular contents that are critical for the establishment of synaptic plasticity. LTP was induced in the ACC of saline treated mice (141.7 ± 10.8% of baseline response, n = 7, p &lt; 0.05 compared with baseline response before the stimulation, Figure ##FIG##4##5A## and ##FIG##4##5C##) after obtaining a stable baseline of AMPA receptor-mediated responses. Interestingly, the same protocol resulted in a significantly enhanced potentiation in morphine treated mice (166.9 ± 13.6% of baseline response, n = 8 slices; P &lt; 0.05 compared with saline treated group, Figure ##FIG##3##4B## and ##FIG##3##4C##). These results suggest that chronic morphine treatment leads to the enhancement of LTP in the ACC.</p>" ]

[ "<title>Discussion</title>", "<p>In this study we demonstrate a role for the NMDA NR2B subunit in the expression and acquisition of analgesic tolerance and in responses to acute morphine analgesia. Additionally, we show that inhibiting NR2B receptors in the ACC can inhibit analgesic tolerance. Changes in synaptic plasticity associated with chronic drug use are well known, however, changes in prefrontal regions have not been documented. We show that morphine-tolerant animals not only show an increase in both the synaptic and extrasynaptic NR2B component of NMDA receptor responses but also exhibit facilitated LTP. This is the first study, to our knowledge, to look at the selective role of NMDA NR2B receptors in the expression and acquisition of opioid analgesic tolerance and in the expression of morphine-induced changes in synaptic plasticity in the ACC.</p>", "<p>Although a myriad of studies have reported on the effects of NMDAR antagonists on morphine induced analgesia, the results are often conflicting and are probably due to different doses, experimental animals, time courses and behavioral tests used [##REF##14592689##26##, ####REF##11438302##27##, ##REF##15820534##28####15820534##28##]. For example, sex differences in NMDAR antagonist induced modulation of morphine analgesia have been reported [##REF##15157688##6##,##REF##15820534##28##]. The direction of this modulation is also unclear, since some studies report that MK801 has no effect on morphine analgesia [##REF##9121809##29##, ####REF##7512709##30##, ##REF##10808085##31####10808085##31##] while others report an inhibition [##REF##2162721##32##,##REF##8358631##33##] and others an increase [##REF##15157688##6##,##REF##8895234##9##]. The NMDAR antagonists LY 235959, dextromethorphan and AP5 also potentiate morphine analgesia [##REF##9112078##34##, ####REF##12031857##35##, ##REF##9539609##36##, ##REF##8733757##37##, ##REF##8851162##38####8851162##38##].</p>", "<p>The ability of NMDAR antagonists to reduce the development of tolerance has been extensively demonstrated [##REF##10972459##3##]. MK801 attenuated the development of morphine tolerance and reduced withdrawal behaviors without affecting acute analgesia [##REF##1824728##8##]. The NMDA receptor antagonists LY274614, dextromethorphan, AP5 and ketamine were all shown to attenuate analgesic tolerance [##REF##8895234##9##,##REF##7512709##30##,##REF##8851162##38##, ####REF##8137155##39##, ##REF##8301558##40##, ##REF##7708410##41##, ##REF##10663418##42####10663418##42##]. Here we present evidence for a role of the NR2B subunit in development of analgesic tolerance. Although we are still unclear about the exact molecular mechanism for the NR2B containing NMDA receptor in morphine tolerance, one possible mechanism is that NR2B containing NMDA receptor may contribute to the induction of the synaptic process that may contribute to the establishment of morphine tolerance. Future studies are clearly needed to investigate this possibility. Since the use of most NMDAR antagonists is hindered by side-effects at clinically relevant doses, Ro 256981 may prove more useful in treating analgesic tolerance in patients.</p>", "<p>Previous studies report a role for the NR2B subunit in acute morphine analgesia with conflicting results [##REF##15157688##6##,##REF##8867919##43##,##REF##15993820##44##]. The NR2B antagonist ifenprodil was shown to both potentiated and prolong the analgesic effects of morphine at a dose that was itself antinociceptive [##REF##8867919##43##]. A more recent study showed that a lower dose of ifenprodil was not antinociceptive but still potentiated and prolonged morphine analgesia [##REF##15993820##44##]. A study reporting that Ro 256981 attenuated responses to morphine [##REF##15157688##6##] seemingly contradicts our present findings. However, it is important to note that different doses and nociceptive tests were used. The present study used 5 mg/kg Ro 256981 and the hotplate test while Nemmani and colleagues (2004) used 50 mg/kg and a hot water tail flick paradigm. Importantly, the dose of Ro 256981 used in the present study was previously shown not to affect motor coordination, acute thermal and mechanical sensitivity [##REF##16319310##21##].</p>", "<p>Human brain imaging shows that the ACC is strongly activated when subjects are exposed to drug-associated cues [##REF##9892292##45##, ####REF##10103096##46##, ##REF##12359667##47####12359667##47##]. For example, the ACC is activated during cocaine use and also during cue-induced craving for cocaine [##REF##9331351##48##,##REF##11296093##49##]. While lesion of the rat ACC did not affect cocaine self-administration, it was effective at preventing drug associated cues from inducing cocaine seeking behavior [##REF##9438674##50##]. Furthermore, when rats were exposed to an environment where they were previously allowed to self administer cocaine, immediate early gene expression, indicative of neuronal activity, was increased in the ACC [##REF##10632609##51##]. Neuronal activity was also increased in the ACC after exposure to a morphine-paired environment [##REF##10881035##52##,##REF##12589382##53##]. The mu opioid receptor is robustly expressed in the ACC [##REF##11714867##54##] and microinjection of morphine directly into the ACC reduced the affective component of pain [##REF##15996657##55##]. Acute and chronic morphine treatment reduced the extracellular levels of glutamate in the ACC [##REF##15804441##56##], suggesting that glutamatergic systems in the ACC may play a role in morphine's effects. Further studies are needed to identify the precise role that the ACC plays in the molecular and behavioral adaptations that occur with the chronic use of drugs of abuse.</p>", "<p>Although the relationship between NMDA receptors and the effects of morphine has been thoroughly investigated, fewer studies examine changes in NMDA receptor mediated responses after prolonged morphine use. Chronic morphine treatment enhanced NMDA receptor mediated responses in spinal cord dorsal horn neurons, however the individual contribution of NR2A or NR2B subunits was not addressed [##REF##16571979##57##]. In the present study, we report that chronic morphine treatment produced significant changes in the NMDA receptor mediated responses. These findings indicate that chronic morphine treatment may trigger long-term upregulation of NMDA receptors along the somatosensory pathways and pain perception related cortical areas. Our electrophysiological data indicate that alterations in NR2B receptor function may not only occur at synaptic sites, but also at extrasynaptic areas. This finding is consistent with recent evidence suggesting that NR2B subunits are located at extrasynaptic suites, and are recruited when repetitive stimulation allows for the spillover of glutamate [##REF##15146049##25##]. Further study is needed to uncover the molecular signaling pathways that are engaged when chronic morphine treatment leads to the modulation of NR2B receptor mediated responses.</p>", "<p>Recent studies show that NR2B receptor activation contributes, at least in part, to the induction of synaptic LTP in the ACC [##REF##16157280##20##]. We found that LTP was significantly enhanced in the ACC of morphine tolerant mice compared to saline treated animals, suggesting that NR2B receptor mediated responses were enhanced after chronic morphine treatment. We cannot rule out the possible contribution of other signaling molecules such as cAMP pathways and other messengers that are downstream from opiate receptors.</p>" ]

[ "<title>Conclusion</title>", "<p>In summary, we present evidence for a role of the NMDA subunit NR2B in morphine analgesia and opioid tolerance. We also show that inhibiting NR2B receptors in the ACC can inhibit behavioral responses in tolerant animals, suggesting for the first time that this prefrontal region plays a role in opioid tolerance. We have previously shown that NMDA NR2B receptors in the ACC play a role in persistent pain, memory and LTP [##REF##18329111##58##]. Our results support the idea that the alterations that occur in response to drugs of abuse are mirrored by the mechanisms that establish learning and memory and demonstrate a novel role for the ACC in the expression of opioid analgesic tolerance. Our results suggest that drugs targeting the NR2B subunit may prove useful in attenuating analgesic tolerance to morphine that occurs clinically.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Morphine is widely used to treat chronic pain, however its utility is hindered by the development of tolerance to its analgesic effects. While N-methyl-D-aspartate (NMDA) receptors are known to play roles in morphine tolerance and dependence, less is known about the roles of individual NMDA receptor subtypes. In this study, Ro 256981, an antagonist of the NMDA receptor subunit NR2B, was used to reduce the expression of analgesic tolerance to morphine. The mechanisms altered with chronic drug use share similarities with those underlying the establishment of long-tem potentiation (LTP) and behavioral memory. Since NMDA NR2B receptors in the anterior cingulate cortex (ACC) play roles in the establishment of LTP and fear memory, we explored their role in changes that occur in this region after chronic morphine. Both systemic and intra-ACC inhibition of NR2B in morphine-tolerant animals inhibited the expression of analgesic tolerance. Electrophysiological recordings revealed a significant increase in the NR2B component of NMDA receptor mediated excitatory postsynaptic currents (EPSCs), at both synaptic and extra-synaptic sites. However, there was no change in alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor mediated EPSCs. This study suggests that selective inhibition of NMDA NR2B receptors may prove useful in combating the development of analgesic tolerance to morphine and proposes a novel role for the ACC in opioid tolerance and morphine induced changes in synaptic plasticity.</p>" ]

[ "<title>Authors' contributions</title>", "<p>SK, FS and JQ performed the behavioral experiments, LJW carried out the electrophysiological experiments, SK and WLJ performed the statistical analysis, SK, LJW and MZ designed the study and wrote the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Supported by grants from the Canadian Institutes of Health Research (CIHR66975, CIHR81086), the EJLB-CIHR Michael Smith Chair in Neurosciences and Mental Health, and the Canada Research Chair to M. Z. L.-J.W. is supported by postdoctoral fellowships from the Canadian Institutes of Health Research and Fragile X Research Foundation of Canada.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>The role of NR2B receptors in acute morphine-induced analgesia and analgesic tolerance</bold>. (A) Morphine analgesia was greater in mice pretreated with Ro25-6981 (5 mg/kg, i.p., n = 5) compared to mice pretreated with saline (n = 4) beginning 90 min after injection. There was a significant effect of treatment (p &lt; 0.05) with significant differences occurring at 90, 120, 150 and 180 minutes after injection (p &lt; 0.05 for all). * represents a significant difference from saline injected mice. (B) Response latencies were significantly increased by Ro 256981 injection (5 mg/kg, i.p., n = 8). Day 7 vs. Day 8, p &lt; 0.001). * represents a significant difference from responses on Day 6 and 7. (C) Daily co-administration of Ro 256981 (5 mg/kg, i.p.) with morphine (10 mg/kg, s.c.) attenuates opioid analgesic tolerance (p &lt; 0.001) compared to mice receiving morphine (n = 7) or saline (n = 5). There was no difference between morphine treated and Ro256981+morphine treated mice on Day 1 (p = 0.74) but a significant difference arose on Day 2 (p &lt; 0.001) and persisted during Days 3, 4, 6 and 7 (p &lt; 0.001, p &lt; 0.01, p &lt; 0.05, p &lt; 0.05 respectively).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Antagonism of NR2B receptors in the ACC can reverse opioid analgesic tolerance compared to mice receiving saline in the ACC</bold>. (A) Analgesic tolerance in ACC cannulated mice developed over the seven-day test period. (B) Bilateral microinjection of Ro 256981 (1 μg in 1 μl, bilaterally, n = 7; filled circles) into the ACC significantly increased response latencies compared to mice receiving saline injections (n = 5; open circles) and to responses on Day 7.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>No change in mEPSCs in morphine treated mice</bold>. (A) Representative traces showing mEPSCs in saline (upper) or morphine treated mice (lower). (B) Pooled data showed that there is no difference in mEPSC frequency in saline (n = 16) and morphine treated groups (n = 16). (C) No difference in amplitude of mEPSCs in the ACC of saline (n = 16) and morphine treated groups (n = 16).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Enhanced NR2B NMDA receptor function in morphine-treated mice</bold>. (A) Representative traces showing that the NR2B component was revealed by application of Ro256981 (3 μM) in saline (upper) or morphine treated mice (lower). (B) Pooled data showed a significant increase in the NR2B component in morphine treated mice (n = 8) compared with that of saline group (n = 6). (C) A short train of stimuli (200 Hz, 7 pulses) induced lager NMDA EPSCs. The NR2B component, including extrasynaptic NR2B, was revealed by application of Ro 256981 (3 μM) in saline (upper) or morphine treated mice (lower). (D) Pooled data showed a significant increase in the NR2B component of short train-induced NMDA current in morphine treated mice (n = 7) compared with that of the saline group (n = 7).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Enhanced cingulate LTP in morphine treated mice</bold>. (A) LTP was induced with the spike-timing protocol in ACC neurons in wild-type mice (n = 7). (B) Enhanced potentiation was observed in morphine treated mice (n = 8). The insets show averages of six EPSCs at baseline responses (1) and 30 min (2) after LTP induction (arrow). The dashed line indicates the mean basal synaptic response. (C) There was a significant increase in LTP in morphine treated mice compared to saline treated group.</p></caption></fig>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Cortisol levels are maximal in the early morning and minimal in the late evening in humans [##REF##11324714##1##, ####REF##11403981##2##, ##REF##15204030##3####15204030##3##]. Dysregulation in the diurnal cortisol rhythm has been associated with depression and pathological aging [##REF##16483550##4##,##REF##16702789##5##]. For example, age-dependent increases in evening cortisol levels have been reported in healthy subjects [##REF##8675562##6##, ####REF##9393943##7##, ##REF##16014406##8####16014406##8##]. The study [##REF##8675562##6##] also found a phase advance in the morning acrophase in the aged subject group. In addition, nocturnal increases in cortisol in aged subjects were correlated with significant reductions in hippocampal and temporal lobe volume [##REF##10705166##9##]. Recently, a significant increase of serum cortisol levels during the evening- and night-time was found in demented patients, particularly those with Alzheimer's disease [##REF##16702789##5##].</p>", "<p>Previous studies have demonstrated that circadian-mediated cortisol levels also have an important role in cognition in an age-independent manner [##REF##11369936##10##, ####REF##10704520##11##, ##REF##16229931##12####16229931##12##]. For example, frequent time-zone travellers who experience disruption to their circadian rhythm had significantly higher cortisol levels during their average working day, which was associated with cognitive deficits and right temporal lobe atrophy [##REF##11369936##10##,##REF##10704520##11##]. However, little is known whether an atypical rhythm of diurnal cortisol levels is associated with cognitive deficits and neurological insults. The present study analyzed the relationship between diurnal cortisol levels and cognition in healthy female subjects.</p>" ]

[ "<title>Methods</title>", "<title>Subjects</title>", "<p>The subjects volunteered to participate in this study and had no medication history. Each subject filled in a questionnaire that provided information on health and lifestyle. This study was conducted in accordance with the Declaration of Helsinki.</p>", "<title>Cortisol Measurement</title>", "<p>The subjects were asked to collect saliva samples at three particular time points (8 am, 2 pm and 10 pm) on two normal working days from two independent weeks. To avoid season-mediated light/dark cycle variance, saliva samples were collected between May – August of the year. Saliva was collected by means of a sterile microbiological swab (Bibby Sterilin Ltd, Stafford, UK). Subjects were asked to keep samples in a fridge until collection. Saliva was extracted from the swab by centrifugation at 2000 rpm at a temperature of 4°C for 6 minutes. Salivary cortisol was determined by means of a cortisol salivary immunoassay kit (Salimetrics Ltd, Pennsylvania, USA) and read in a luminometer. Each sample was determined in duplicate to identify potential sample loading errors.</p>", "<title>Cognitive Tasks</title>", "<p>Before starting the experiment, the subjects were fully informed as to how to respond to the tasks by means of a visual instruction sheet. Subjects also completed a practice version of each task to ensure familiarisation with the procedure. The tasks were conducted with an Apple Macintosh computer using Macintosh stimulus presentation software (SuperLab; Cedrus, Wheaton, MD) [##UREF##1##34##] which presents images for the different cognitive tasks (for more details see Cho et al., 2000; Cho, 2001). All participants were tested in the afternoon between the hours of 2 pm and 5 pm to minimize possible differences in performance due to diurnal changes in cortisol.</p>", "<p>Each visual task began with a 5 sec presentation of a black cross in the centre of the screen to hold the subject's attention. Test pictures were presented in a pseudorandom and counter-balanced order. The tasks required the subjects to choose the correct key responses. In the attention task, 'press key p' was required if the black triangle appeared at the top of the square, and 'press key q' if it appeared on the bottom. No response was required for any other image (i.e., neutral stimulation). The language task was based on one previously used [##REF##15488907##35##] and involved an appropriate key response to presentation of a written word. Half of the words referred to man-made items (e.g., \"scissors\") while half were natural items (e.g., \"cat\"). Subjects were required to 'press key p' in response to a word referring to a natural item, and 'press key q' in response to a man-made item. No response was required for a neutral stimulation (black cross). All of the stimuli were highly familiar, concrete nouns according to the MRC psycholinguistic database [##REF##7321870##36##].</p>", "<p>Visual recognition memory was analysed using photographed images of novel and familiar objects. Images for the object recognition memory tasks were obtained from the websites <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.images.google.com\"/> and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.gettyimages.com\"/>. Familiar images were of everyday items (e.g., a chair or a shoe) while novel objects were obscure images the subjects were unlikely to have encountered ever before. The object discrimination task was based on the 'object familiarity detection task' used by Laatu and colleagues [##REF##12859283##37##]. In this task the subject was presented with a sequence of familiar and novel objects that were shown in a pseudorandom and counterbalanced order. The subject was asked to decide whether the picture presented was a familiar object or not by pressing one of two keys on the computer keyboard. Therefore correct performance required decisions based on whether or not the presented shape has a representation in the subject's long-term memory [##REF##12859283##37##]. For data analysis, responses to familiar images and responses to novel images were determined separately. The familiarity acquisition task used the same format as the object discrimination task but in this case, some images were repeated at later points in the sequence. Appearances of the same image were always parted by at least 7 other images (which didn't differ significantly between novel and familiar images). The reaction time to repeated presentations of novel images gave an indication whether or not the item was becoming familiar. A second difference between this task and the object discrimination task was that the subjects were asked to silently name the objects presented to them. If they could name them (familiar object) they were required to press one key, and if they were unable to name them (novel object) they were to press the other key. As this task concerned the reaction time to repeated novel images, this naming method was adopted in order to encourage the subjects to press the novel key if the image was indeed novel [##REF##12859283##37##]. Essentially the subjects were still categorising the objects as either familiar or novel. By the fourth presentation of the novel image the subject begins to recognise the object and thus respond more quickly to the image. In this recognition task the subjects are unaware that they are encoding visual information about the objects. In addition, they are not aware that they are being tested for their memory of novel images. Therefore this task is an incidental encoding delay task.</p>", "<p>In the spatial task, subjects were required to 'press key p' if the second presentation of a set of images were in the same position as when they first appeared, and 'press key q' if an image had changed its position. Repetitions of the same set of images were separated by a presentation of a black cross for a duration of 8 secs. The accuracy of correct responses (percentage) and reaction time (msec) were measured by the computer.</p>", "<title>Statistical analysis</title>", "<p>Statistical analyses were carried out using Student's non-paired <italic>t </italic>test, the Mann-Whitney U-test and regression analysis. Data are presented as Mean ± s.e.m. <italic>P </italic>&lt; 0.05 was taken as the level of significance throughout the analysis.</p>" ]

[ "<title>Results</title>", "<p>Subjects were 22- to 66-year-old women (Mean age = 40 yrs, age deviation = 12 yrs, n = 44 subjects) who had no neurological or psychiatric illness. Firstly, the present study analysed salivary-cortisol levels at three different time-points during the day (8 am, 2 pm and 10 pm), collected from two independent weeks (for more details see method). Since cortisol levels peak within an hour after wakeup, and decrease toward to bottom level at late evening [##REF##11369936##10##], three different time saliva collecting points (8 am, 2 pm and 10 pm) will represent a major diurnal cortisol rhythm during the day. To avoid sleep/wake cycle dependent variance of diurnal cortisol rhythm, subjects were set their wakeup time at 7:30 am and sleep time at 11:00 pm. In thirty-three subjects, cortisol level at 10 pm is the lowest profile within three time points (2.9 ± 0.2 nmol/L, filled symbol, Figure ##FIG##0##1A##). In eleven subjects, however, cortisol level at 10 pm is equal to higher than that of 2 pm (6.4 ± 1.5 nmol/L, opened symbol, Figure ##FIG##0##1A##). To clarify the pattern of cortisol levels at 10 pm, data were renormalized by cortisol levels at 2 pm (low cortisol_{10 pm}; 54 ± 3% of 2 pm cortisol level, n = 33, filled symbol; high cortisol_{10 pm}; 165 ± 27% of 2 pm cortisol level, n = 11, opened symbol, Figure ##FIG##0##1B##). Thus, we divided subjects into two groups based on normalized 10 pm cortisol level (i.e., low cortisol_{10 pm}group and high cortisol_{10 pm}group). There is no difference in the mean age of the high cortisol_{10 pm}group and the low cortisol_{10 pm}group (low cortisol_{10 pm}: 40 ± 2 years; high cortisol_{10 pm}: 40 ± 4 years; P &gt; 0.05).</p>", "<p>Next we analyzed whether there was any interaction between cortisol_{10 pm}and cognition. In the first series of experiments, we tested attention and language in both the low cortisol_{10 pm}group and the high cortisol_{10 pm}group. There was no significant difference in correct key response for both the attention, (low cortisol_{10 pm}: 95 ± 2% correct response, n = 32; high cortisol_{10 pm}: 89 ± 4% correct response, n = 11; P &gt; 0.05, Figure ##FIG##1##2A##) and the language task (low cortisol_{10 pm}: 95 ± 1%, n = 31; high cortisol_{10 pm}: 92 ± 1%, n = 9; P &gt; 0.05, Figure ##FIG##1##2A##). Similarly, there was no significant difference in correct key response reaction time between these two groups for both the attention (low cortisol_{10 pm}: 442 ± 22 msec, n = 32; high cortisol_{10 pm}: 463 ± 27 msec, n = 11; P &gt; 0.05, Figure ##FIG##1##2B##) and the language task (low cortisol_{10 pm}: 758 ± 15 msec, n = 31; high cortisol_{10 pm}: 746 ± 29 msec, n = 9; P &gt; 0.05, Figure ##FIG##1##2B##).</p>", "<p>In the next series of experiments, we analyzed visual object recognition memory and spatial memory in both subject groups (Figure ##FIG##1##2C##). In the novel object discrimination task, there was a significant difference in correct key response (low cortisol_{10 pm}: 83 ± 3% correct response, n = 33; high cortisol_{10 pm}: 59 ± 7% correct response, n = 11; P &lt; 0.005, Figure. ##FIG##1##2C##). In contrast, there was no significant difference in spatial memory performance between low cortisol_{10 pm}and high cortisol_{10 pm}group (Figure ##FIG##1##2C##).</p>", "<p>Next the relationship between normalized cortisol_{10 pm}level and percentage correct key response during the novel object discrimination task was examined by regression analysis. A significant correlation was found between these two variables (r = -0.44, r²= 0.19, P &lt; 0.01, n = 44, Figure ##FIG##2##3A##). This initial result implies that although high evening cortisol does not influence the recognition of previously-encoded, highly recognisable objects (low cortisol_{10 pm}: 97 ± 1% correct response, n = 33; high cortisol_{10 pm}: 93 ± 3% correct response, n = 11; P &gt; 0.05), it may specifically affect the processing and the ultimate familiarisation of new objects. To examine this further, we analysed the familiarity acquisition time of novel objects in both subject groups (Figure ##FIG##2##3B##). Firstly, there was no significant group difference in reaction time to the first appearance of a novel object (low cortisol_{10 pm}: 873 ± 19 ms, n = 29; high cortisol_{10 pm}: 888 ± 65 ms, n = 9, P &gt; 0.05, Figure ##FIG##2##3B##). However, a significant difference was found in the reaction time to the fourth appearance of the same novel object (low cortisol_{10 pm}: 619 ± 16 ms, n = 29; high cortisol_{10 pm}: 703 ± 31 ms, p &lt; 0.05, Figure ##FIG##2##3B##). This difference in reaction time was not observed at either the first (low cortisol_{10 pm}: 624 ± 12 ms, n = 29; high cortisol_{10 pm}: 657 ± 36 ms, n = 10, P &gt; 0.05, Figure ##FIG##2##3C##) or the fourth presentation of a familiar object (low cortisol_{10 pm}: 547 ± 14 ms, n = 29; high cortisol_{10 pm}: 546 ± 15 ms, n = 10, P &gt; 0.05, Figure. ##FIG##2##3C##).</p>" ]

[ "<title>Discussion</title>", "<p>The present study demonstrates a significant correlation between normalized cortisol_{10 pm}level and novel object discrimination and recognition. However, there was no significant relationship between cortisol_{10 pm}level and either attention or language. These results suggest no difference in either generic learning or visual perception between the two subject groups. Since the results are consistent with previous study [##REF##10704520##11##], salivary cortisol level associated with the circadian rhythm may have a specific role in non-semantic cognition. As yet, we do not know whether evening cortisol level has a particularly important role in non-semantic cognition. A recent study suggests that acute stress regulates memory in a circadian rhythm-mediated manner [##REF##16229931##12##]. Similarly, the current investigation also indicates that the timing of stress may be important in determining its effects on certain aspects of memory. Thus, the differentiation of circadian-mediated cortisol levels may have a critical role in the regulation of non-semantic cognition. It is still a matter of further investigation whether high cortisol_{10 pm}levels are due to individual differences in diurnal rhythm or basal stress levels [##UREF##0##13##], or an indication of natural aging in normal women [##REF##8675562##6##,##REF##4019712##14##,##REF##10195112##15##].</p>", "<p>The diurnal pattern of cortisol is considered relatively robust but is shown to be disrupted in shift workers [##REF##10709369##16##, ####REF##7951784##17##, ##REF##9613222##18####9613222##18##], transmeridian flyers [##REF##10704520##11##,##REF##7957025##19##] and disease states such as Alzheimer's disease [##REF##16702789##5##,##REF##11113605##20##] and depression [##REF##2862799##21##,##REF##15380401##22##]. In our study, we did notice that high cortisol_{10 pm}group had lower cortisol at 2 pm but higher at 10 pm. This suggests that high cortisol_{10 pm}group has a different diurnal frequency of cortisol than that of low cortisol_{10 pm}group. Alternatively cortisol cycle has shifted. Interestingly, variations in the diurnal pattern of salivary cortisol have been repeatedly identified among healthy populations. In these studies, most adults have a 'normal' cortisol cycle but a subset display an 'atypical' cortisol cycle [##REF##14644066##23##, ####REF##9149331##24##, ##REF##11166492##25####11166492##25##]. Therefore, some people do not have the expected diurnal rhythm of cortisol secretion which is what was detected in the current investigation [##REF##11166492##25##].</p>", "<p>In one particular study [##REF##17060048##26##], the majority of a subject group consisting of older individuals with memory complaints presented an atypical cortisol profile that was characterised by a normal morning peak, with evening levels that did not reach the typical low nadir phase. This implies that atypical diurnal cortisol release may have significant effects on memory function.</p>", "<p>Why is high evening cortisol in particular associated with recognition memory deficits? Recent studies have showed that stress induced in the morning, but not the afternoon, is associated with memory deficits [##REF##16229931##12##,##REF##10443770##27##,##REF##11818174##28##]. In these studies, the observed impacts are due to acute manipulations of cortisol that are reversible. However, little is known about whether or not chronic stress is more detrimental at a certain time point during the day. Potentially, high cortisol levels at a time when they should be low may have negative impact on cognitive function. Alternatively, high evening cortisol may well interfere with sleep duration or quality, lack of which is associated with cognitive deficits [##REF##16218081##29##]. In support of this, it was found that a lightening of sleep is accompanied by increases in cortisol, and the ability to enter REM (rapid eye movements) sleep cycles requires low cortisol levels at night, which are characteristic of this time of day [##REF##10443660##30##].</p>", "<p>The next question to answer is how does high cortisol_{10 pm}selectively affect object recognition with no effect on other aspects of cognition? High cortisol_{10 pm}may selectively induce transient changes in synaptic plasticity in specific neuronal circuitry such as perirhinal cortical synapses, which have been hypothesised as being an important brain region for visual object recognition [##REF##11253359##31##]. These cortisol levels may be not high enough or long enough in duration to regulate synaptic plasticity in other neuronal circuitries, such as the hippocampus. There is evidence to support this hypothesis; in rodents and non-human primates, the perirhinal cortical region showed the highest density of glucocorticoid receptor (GR)-immunoreactive and GR-mRNA-containing cells than other brain regions [##REF##9121734##32##,##REF##10844035##33##]. Therefore, the pharmacological feature of GR activation in the perirhinal cortex may be a potential answer.</p>", "<title>Conclusion</title>", "<p>Taken together, salivary cortisol level at the evening phase of the diurnal rhythm may have an important role in early deterioration of visual recognition memory in healthy female subjects. The loss of recognition memory, which is vital for everyday life, is a major symptom of the amnesic syndrome and early stages of Alzheimer's disease [##REF##11253359##31##]. Therefore, this study will promote a potential physiologic marker of early deterioration of recognition memory. It will be of future interest to reveal whether this deterioration of recognition memory is due to neurological insults in specific brain regions.</p>" ]

[ "<title>Conclusion</title>", "<p>Taken together, salivary cortisol level at the evening phase of the diurnal rhythm may have an important role in early deterioration of visual recognition memory in healthy female subjects. The loss of recognition memory, which is vital for everyday life, is a major symptom of the amnesic syndrome and early stages of Alzheimer's disease [##REF##11253359##31##]. Therefore, this study will promote a potential physiologic marker of early deterioration of recognition memory. It will be of future interest to reveal whether this deterioration of recognition memory is due to neurological insults in specific brain regions.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Diurnal rhythm-mediated endogenous cortisol levels in humans are characterised by a peak in secretion after awakening that declines throughout the day to an evening trough. However, a significant proportion of the population exhibits an atypical cycle of diurnal cortisol due to shift work, jet-lag, aging, and mental illness.</p>", "<title>Results</title>", "<p>The present study has demonstrated a correlation between elevation of cortisol in the evening and deterioration of visual object recognition memory. However, high evening cortisol levels have no effect on spatial memory.</p>", "<title>Conclusion</title>", "<p>This study suggests that atypical evening salivary cortisol levels have an important role in the early deterioration of recognition memory. The loss of recognition memory, which is vital for everyday life, is a major symptom of the amnesic syndrome and early stages of Alzheimer's disease. Therefore, this study will promote a potential physiologic marker of early deterioration of recognition memory and a possible diagnostic strategy for Alzheimer's disease.</p>" ]

[ "<title>Authors' contributions</title>", "<p>HG carried out all of the experiments. DW confirmed statistics and coordinated the manuscript. KC conceived the study, supervised all experiments and coordinated the manuscript. All authors assisted with writing the manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported by the Royal Society (KC), and UK Alzheimer's Research Trust (KC). DW is a recipient of UK Alzheimer's Research Trust PhD scholarship.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Salivary cortisol level was analysed by means of a cortisol salivary immunoassay kit (for more details, see method)</bold>. (A) Salivary cortisol samples were collected at three particular time points (8 am, 2 pm and 10 pm). Most subjects showed lower cortisol levels at 10 pm compared to that of 2 pm (low cortisol_{10 pm}, n = 33 subjects). Eleven subjects showed higher cortisol levels at 10 pm compared to that of 2 pm (high cortisol_{10 pm}). (B) Cortisol_{10 pm}indicates normalized 10 pm cortisol level (percent of 2 pm cortisol level). Error bars indicate s.e.m. Significant difference at *P &lt; 0.01, **P &lt; 0.0001.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Both the low cortisol_{10 pm}subject group and the high cortisol_{10 pm}subject group were compared to assess the correct key response and reaction time in cognitive performance</bold>. (A, B) Mean (± s.e.m.) correct response and reaction time in two groups. There is no significant difference between the low cortisol_{10 pm}group and the high cortisol_{10 pm}group in performance in either the attention or the language task. (C) Low cortisol_{10 pm}subjects show a significantly more accurate correct key response than that of high cortisol_{10 pm}subjects in the novel object discrimination task. *Significant group difference at p &lt; 0.005.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Correlation with evening corticosterone level and familiarity discrimination</bold>. (A) Cortisol_{10 pm}level was negatively correlated with performance in the novel object discrimination across the whole cohort (r = -0.44, r²= 0.19, P &lt; 0.01, n = 44). (B) Mean (± s.e.m.) reaction time to novel stimuli. The high cortisol_{10 pm}group were significantly slower at responding to the fourth repeated presentation of a novel object. *Significant group difference at p&lt;0.05. (C) Mean (± s.e.m.) reaction time to familiar object stimuli. There was no significant group difference (P &gt; 0.05). Filled bars indicate low cortisol_{10 pm}group, and open bars indicate high cortisol_{10 pm}group.</p></caption></fig>" ]

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{ "acronym": [], "definition": [] }

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Using an endophenotype-driven screen, a new study finds that α-calcium/calmodulin kinase II mutant mice exhibit a range of behavioral abnormalities related to schizophrenia. Perhaps most strikingly, this cluster of schizophrenia-related endophenotypes was associated with abnormal neurogenesis in the adult hippocampus, raising the possibility that disrupted adult neurogenesis lies at the core of this and other psychiatric disorders.</p>" ]

[ "<title>Editorial</title>", "<p>Schizophrenia is a chronic, debilitating form of mental illness, affecting more than 1% of the adult population [##REF##17015232##1##]. Current treatments are palliative at best – reducing the severity of symptoms rather than providing a cure – in part, because of the paucity of our understanding of the molecular bases of this complex, polygenic disorder. A more comprehensive understanding of the molecular underpinnings of schizophrenia is an essential foundation for the development more effective treatments (and eventual cure).</p>", "<p>A new study by Miyakawa and colleagues [this issue, Molecular Brain 2008, 1:6] sheds fresh light on potential molecular mechanisms underlying schizophrenia. In their study, the authors ran different lines of mutant mice through a comprehensive behavioral test battery in order to screen for behavioral abnormalities relevant to schizophrenia. In such a phenotypic screen, there are two critical decisions: First, which behaviors to focus on? As is the case with many psychiatric disorders, schizophrenia is characterized by a bafflingly heterogeneous collection of behavioral symptoms. These include both positive symptoms (e.g., hallucinations, delusions, disordered thought) and negative symptoms (e.g., anhedonia, decreased motivation, attentional problems and impaired working memory). Clearly, some of these abnormalities are uniquely human and impossible to model in a mouse (even for the most adept mouse psychiatrist). The solution, then, is to focus on a subset (rather than the entire constellation) of behavioral abnormalities that are nonetheless heritable and readily modeled in mice. Using this endophenotype-driven approach, Miyakawa and colleagues focused on characterizing working memory, anxiety, aggression and infradian and circadian rhythms in their mutant mice.</p>", "<p>The second critical decision is which mice to screen? Thousands of knockout, knockin and transgenic lines of mice have been engineered. As screening large numbers of mice is prohibitively time-consuming and expensive, it makes sense to narrow down the field to a more tractable number of players. Here, Miyakawa and colleagues took advantage of their previous work with mice that have a forebrain-specific deletion of calcineurin (CN). They found that these mice exhibited abnormalities in a number of behaviors related to schizophrenia [##REF##12851457##2##], and, therefore, in the present study they decided to screen 7 mouse lines with mutations related to either CN signaling or CN-related mechanisms. Of these 7, the mice with the most striking behavioral phenotype were those carrying a heterozygous null mutation for α-calcium/calmodulin kinase II (α-CaMKII^+/-mice). These are mice with a storied history in the field of learning and memory. Originally generated by Alcino Silva while a postdoctoral fellow in Susumu Tonegawa's lab at MIT, initial studies with the α-CaMKII homozygous mutants helped to establish that α-CaMKII plays an essential role in synaptic plasticity and hippocampal learning [##REF##1321493##3##,##REF##1378648##4##]. Subsequent studies using the heterozygous mutants suggested that α-CaMKII also plays a key role in cortical plasticity, and in the consolidation of remote memories [##REF##11357133##5##,##REF##8602534##6##].</p>", "<p>In their new study, Miyakawa and colleagues found that the behavioral phenotype of the α-CaMKII^+/-mice is more complex (and perhaps more abnormal) than previously appreciated. Perhaps most notably, the α-CaMKII^+/-mice have severe working memory deficits (tested either in a radial arm maze or delayed alternation task). Working memory deficits are a core symptom of schizophrenia, and working memory deficits have been consistently identified in other mouse models of schizophrenia (most recently, for example, in mice with mutations in <italic>Disrupted-in-schizophrenia-1 </italic>[<italic>Disc1</italic>] [##REF##17481393##7##,##REF##17984054##8##]). Adding to this collection of psychiatric-related behavioral phenotypes, further analyses revealed that the α-CaMKII^+/-mice are unusually aggressive (killing their cage mates given half a chance), less anxious and had dramatically disrupted patterns of daily activity.</p>", "<p>Because informative endophenotypes need not be restricted to the behavioral domain, next Miyakawa and colleagues took a look inside the brains of the α-CaMKII^+/-mice. Their analyses uncovered quite striking changes in the dentate gyrus of the hippocampus (a brain region that plays a key role in working memory). The dentate gyrus is a special place in the brain – it is one of two regions where new neurons continue to be generated throughout adulthood [##REF##18295581##9##]. Miyakawa and colleagues found that this process – hippocampal adult neurogenesis – was quite abnormal in the α-CaMKII^+/-mice. While more new neurons appeared to be produced (proliferation was increased by about 50%), these neurons did not appear to mature normally – the dentate gyrus of α-CaMKII^+/-mice contained a higher proportion of granule cells with immature properties (e.g., increased excitability and reduced dendritic branching and length). This shift in balance from mature to immature granule cells suggested to Miyakawa and colleagues that the α-CaMKII^+/-mice have an immature dentate gyrus.</p>", "<p>That changes in the regulation of neurogenesis in the adult hippocampus are associated with a cluster of behavioral endophenotypes related to schizophrenia in the α-CaMKII^+/-mice is particularly noteworthy. There is mounting interest in the potential role of adult neurogenesis in the pathology of a number of psychiatric illnesses, including schizophrenia and depression [##REF##18382230##10##]. For example, antidepressants may well work by increasing hippocampal neurogenesis [##REF##12907793##11##] and, while adult neurogenesis may be unaltered in depressed patients, recent reports suggest that levels of hippocampal neurogenesis are reduced in schizophrenic patients [##REF##16415915##12##]. The emerging hypothesis is that abnormal neurogenesis may contribute to abnormal hippocampal function [##REF##18382230##10##]. Since the hippocampus is involved in regulation of mood and cognition, such aberrant hippocampal processing may cumulatively lead to the sorts of disturbances in thought and mood found in schizophrenia and depression. This is an intriguing new hypothesis and, if true, suggests that in hunting down schizophrenia susceptibility genes it might make most sense to pay special attention to genes that regulate neuronal development and/or adult neurogenesis. In this regard, it is particularly exciting that perhaps the strongest candidate schizophrenia gene – <italic>Disc1 </italic>– is implicated in neuronal migration and differentiation [##REF##17825401##13##]. Consistent with this, α-CaMKII itself regulates neuronal development [##REF##11994750##14##], and the expression of a large number of genes that have been implicated in neuronal development (e.g., genes in the BDNF-MAPK pathway) were differentially regulated in the α-CaMKII^+/-mice.</p>", "<p>A final thought on the approach that Miyakawa and colleagues adopted in this study. In exploring gene-function relationships both forward-genetic (i.e., phenotype → gene(s)) and reverse-genetic (i.e., gene → phenotype(s)) approaches have traditionally been used [##REF##12668350##15##]. However, there are limitations associated with both approaches. In forward-genetic studies (such as ENU mutagenesis screens) identifying the causative mutation may be an especially time-consuming and expensive process. Similarly, in reverse-genetic studies (such as those using knockout mice) it is necessary to have a good idea about which gene to target and such <italic>a priori </italic>knowledge may often be lacking in complex polygenic disorders like schizophrenia. The strategy used by Miyakawa and colleagues blurs the boundaries between these two traditional classifications. Indeed, the use this hybrid strategy – a phenotypic screen of previously engineered mutant mice – is particularly powerful since it allows for the rapid association of schizophrenia-related endophenotypes with specific genes. A similar strategy has recently been used to identify genes for remote memory [##REF##18464936##16##]. By combining the best of both worlds, Miyakawa and colleagues bring us a step closer to understanding the molecular basis of schizophrenia.</p>" ]

[ "<title>Acknowledgements</title>", "<p>PWF is supported by a CIHR Canada Research Chair in Cognitive Neurobiology. MS. and MA-C are supported by Restracomp awards from The Hospital for Sick Children Research Institute. MA-C is additionally supported by an Ontario Graduate Scholarship award.</p>" ]

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[ "<title>Background</title>", "<p>Herbal extracts from traditional Chinese medicine can be formulated to develop novel herbal medicines as potent as synthetic medicines [##REF##15953563##1##, ####REF##15315266##2##, ##REF##12709543##3####12709543##3##]. We investigated <italic>in vitro </italic>anti-inflammatory properties of 20 medicinal herbs used in Chinese medicine in order to develop a new herbal formulation to treat inflammation. Three herbs, namely <italic>Radix Gentianae Macrophyllae </italic>(<italic>Qinjiao</italic>) [##REF##15802824##4##,##REF##15374610##5##], <italic>Rhizoma Coptidis </italic>(<italic>Huanglian</italic>) [##REF##16730935##6##] and <italic>Citri Unshiu Pericarpium </italic>(<italic>Wenzhou migan</italic>) [##REF##12458489##7##,##REF##10615874##8##], demonstrated anti-inflammatory effects in various experimental models. The primary ingredient in <italic>Radix Gentianae Macrophyllae </italic>is gentiopicroside which was shown to have anti-inflammatory effects in a murine model of hepatic injury [##REF##7997467##9##]. Berberine, which has strong anti-inflammatory effects [##REF##16500064##10##, ####REF##14732220##11##, ##REF##12850501##12####12850501##12##], is a major active constituent of <italic>Rhizoma Coptidis</italic>. Hesperidin [##REF##16557465##13##] and nobiletin [##REF##11016629##14##], both of which exhibit anti-inflammatory effects, are the active ingredients in <italic>Citri Unshiu Pericarpium </italic>[##REF##15240993##15##,##REF##12081153##16##]. Our <italic>in vitro </italic>screening and other available information suggests that these three herbs have potential anti-inflammatory effects. Therefore, these three herbs were selected for a formulation, i.e. KHU14. The present study tests the anti-inflammatory actions of KHU14 in several animal models of inflammation.</p>" ]

[ "<title>Methods</title>", "<title>Materials</title>", "<p>Carboxymethyl cellulose (CMC), dexamethasone, olive oil, 4-ethoxymethylene-2-phenyloxazolone, acetone, carrageenan, croton oil, Evans blue, and Griess regent (1% sulfanilamide and 0.1% N- [napthyl] ethylenediamine dihydrochloride in 2.5% H₃PO₄) were purchased from Sigma (USA). Celecoxib (capsules) was purchased from Pfizer Pharmaceuticals (Korea). ELISA kits for interleukin-2 and interferon-γ and the immunoassay kit for PGE₂were purchased from R&amp;D Systems (USA). RPMI 1640 (Gibco, UK) and DMEM (Invitrogen, UK), antibiotic-antimycotic solution (Gibco, UK) and fetal bovine serum (FBS, CAMBREX, USA) were used as media for cell culture. The 20 herbs used in the present study were purchased from Kyung Hee Oriental Medical Hospital.</p>", "<title>Animals</title>", "<p>Female <italic>BALB/c </italic>mice (5–6 weeks old, 16–18 g) and male ICR mice (5–6 weeks old, 16–18 g) were obtained from Orient Co Ltd (Korea). Male Wistar rats (5–6 weeks old, 200–300 g) were obtained from SLC Co Ltd (Japan). All animals were kept in plastic cages at 21–24°C under a 12 hour light/dark cycle and were given free access to pellet food and water. The mice were fed with 200 μl of the extract solution and the rats were fed with 2 ml of the same. This study complied with the internationally accredited guidelines and ethical regulations on animal research.</p>", "<title>Preparation of plant extracts</title>", "<p>Powdered <italic>Radix Gentianae Macrophyllae</italic>, <italic>Rhizoma Coptidis </italic>and <italic>Citri Unshiu Pericarpium </italic>were obtained from Kyung Hee Oriental Medical Hospital (South Korea). The powders of these herbs (200 g each) were mixed by blending and then extracted twice with 50% ethanol (1800 ml) at 80°C for 4 hours. The combined ethanolic extracts were filtered and concentrated in a rotary evaporator at 40°C. The yield (59.5 g), code named KHU14 (KHU referring to Kyung Hee University), was then dissolved in 0.5% carboxylmethyl cellulose (CMC) solution (0.5 g CMC in 100 ml of distilled water) for the subsequent <italic>in vivo </italic>experiments. The voucher specimens of the plants used in this study were stored in the department herbarium for future reference.</p>", "<title>Measurement of cell viability</title>", "<p>Cell viability was assessed by the 3'-(4,5-dimethylthiazole-2yl)-2,5-diphenyltetrazolium bromide (MTT) assay. RAW264.7 cells (1 × 10⁴cells/well) were seeded in triplicates of 24-well plates and cultured in 1 ml of Dulbecco's Modified Essential Medium (DMEM) containing 10% fetal bovine serum (FBS) overnight. After treated with KHU14 for one hour, cells were stimulated with 1 μg/ml of LPS for 72 hours and MTT (0.5 mg/ml) was added in the third hour. After the removal of the medium and the addition of 500 μl of DMSO to the well, the optical density (OD) absorbance was measured at 570 nm.</p>", "<title>Western blot anlysis</title>", "<p>RAW264.7 cells cultured (1 × 10⁶cells) in 60 mm dishes were serum-starved overnight. After the cells were treated with KHU14 for 1 hour, the cells were stimulated by LPS (1 μg/ml) for 24 hours. The cells were subsequently washed twice in PBS and treated with 50 μl of lysis buffer (20 mM Tris-Cl [pH 8.0], 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 20 μg/ml chymostatin, 2 mM PMSF, 10 μM leupeptin, and 1 mM 4-(2-aminoethyl) benzenesulfonyl fluoride [AEBSF]). The samples were separated with 12% SDS-PAGE and were then transferred to Hybond-ECL membranes (Amersham, USA). The membranes were first blocked with 6% nonfat milk dissolved in TBST buffer (10 mM Tris-Cl [pH 8.0], 150 mM NaCl, 0.05% Tween 20). The blots were then probed with various rabbit polyclonal antibodies for iNOS, COX-2 and β-actin (Cell Signaling Technology, USA) diluted 1:1000 in TBS for 2 hours and incubated with 1:1000 dilutions of goat anti-rabbit IgG secondary antibody coupled with peroxidase. The blots were developed with the ECL method (Amersham, USA). For re-probing, the blots were incubated in the stripping buffer (100 mM 2-mercaptoethanol, 2% SDS, 62.5 mM Tris-HCl [pH 6.7]) at 50°C for 30 minutes with occasional agitation.</p>", "<title>Preparation of activated peritoneal macrophages from mice</title>", "<p>Resident macrophages were obtained by peritoneal lavage according to a previously published method [##REF##15240719##17##]. Briefly, the mice were injected intraperitoneally with 1 ml of Brewer thioglycollate medium (3%); and peritoneal fluids were harvested after three days. The peritoneal exudates were centrifuged at 2000 rpm (931 × <italic>g</italic>, Allegra™ X-12R Centrifuge, Beckman Coulter, USA) for 5 minutes at 4°C. The cell pellets were washed twice with DMEM containing 10% FBS, 100 U/ml penicillin, 100 mg/ml streptomycin. The washed cells were stimulated with lipopolysaccharide (LPS, 1 μg/ml) and IFN-γ (1 ng/ml) for 96 hours on 96-well plates (2 × 10⁵cells in 200 μl of medium per well) for the nitric oxide (NO) assay, and 24 hours on 24-well plates (each well contains 1 × 10⁶cells in 1 ml of medium) for the prostaglandine E₂(PGE₂) assay.</p>", "<title>NO and PGE₂assays</title>", "<p>Total NO production may be measured by nitrite assay as NO is rapidly converted to nitrite and nitrate water. Briefly, 100 μl of the culture supernatant was incubated at room temperature for 10 minutes with 100 μl of Griess reagent (1% sulfanilamide, 0.2% N-(1-naphthyl) ethylenediamine dihydrochloride in 2.5% H₃PO₄). The OD was measured at 570 nm and nitrite concentration was determined with a standard curve. We used an enzyme immunoassay kit to measure the PGE₂production in the culture supernatant following the manufacturer's instructions (R&amp;D Systems, USA).</p>", "<title>Ear edema induced by croton oil</title>", "<p>The inner surface of the right ear of the male ICR mice was treated with 20 μl of freshly prepared croton oil (2.5% in acetone). The left ear was treated with 20 μl of acetone as control [##UREF##0##18##]. The thickness of the ear edema was measured with an engineering gauge (Model H, Peacock, Japan) 4 hours after the application of the irritant. Sixty minutes prior to the induction of edema, KHU14 (400 mg/kg of body weight), celecoxib (100 mg/kg of body weight) and vehicle (0.5% CMC) were orally administered to three groups of animals which had fasted for four hours. Edema was measured as the difference between the thickness of the control ear and that of the ear treated with croton oil.</p>", "<title>Paw edema induced by carrageenan</title>", "<p>Each of the male Wistar rats was injected with 0.1 ml of a freshly prepared suspension of carrageenan in saline (2.0 mg/ml) in the subplanta tissue of the right hind paw. An equal volume of saline was injected into the left hind paw as control. We made some modifications to the previously described murine paw edema model [##REF##17340525##19##]. The volume of the paw up to the tibiotarsal joint was measured with a plethysmometer (Model 7140, Ugo Basile, Italy) one, two and four hour(s) respectively after the induction of inflammation. Edema was measured as the difference between the volume of the paw of the control and that of the paw injected with carrageenan. Sixty minutes prior to the induction of edema, KHU14 (400 mg/kg of body weight), celecoxib (100 mg/kg of body weight) and vehicle (0.5% CMC) were orally administered to three groups of animals which had fasted for 15 hours.</p>", "<title>Capillary permeability increase induced by acetic acid</title>", "<p>Vascular permeability increase induced by acetic acid in the male ICR mice was determined following a modified Whittle method [##REF##3404148##20##]. KHU14 (400 mg/kg of body weight), celecoxib (100 mg/kg of body weight) and vehicle (0.5% CMC) were orally administered to three groups of mice respectively. Thirty minutes after the administration, each mouse was intravenously injected (at the tail) with 0.1 ml of 4% Evans blue (10 μl/g of body weight, Sigma, USA) in saline. Fifteen minutes after the intravenous injection, each mouse was intraperitoneally injected with 0.1 M acetic acid (10 μl/g body weight). The mice were sacrificed by ether 20 minutes after the acetic acid injection. The viscera were exposed for one minute to drain the blood and were washed with saline over a Petri dish. The wash was poured into 10 ml volumetric flasks through glass wool. Each flask contained 10 ml of distilled water and 0.1 ml of a sodium hydroxide solution (0.1 M) was added to the flask to clear any turbidity caused by proteins. The OD was measured at 590 nm.</p>", "<title>Cotton pellet test</title>", "<p>Two sterile cotton pellets (10 mg) were subcutaneously delivered into the dorsum of the male ICR mice anesthetized with ether. KHU14 (400 mg/kg of body weight), celecoxib (100 mg/kg of body weight) and vehicle (0.5% CMC) were orally administered to three groups of mice respectively once daily for seven days. The mice were sacrificed on the 7^thday by ether. The cotton pellets were removed, dried at 37°C for 24 hours and weighed. The results were expressed as the difference between the initial weight (10 mg) and the final dry weight of the cotton pellets.</p>", "<title>Delayed type hypersensitivity</title>", "<p>Female <italic>BALB/c </italic>mice were sensitized by epicutaneously applying 25 μl of a mixture of acetone and olive oil (4:1) containing 2% 4-ethoxymethylene-2-phenyloxazolone on the shaved abdomen and thorax skin as described by Blaylock <italic>et al</italic>. [##REF##8553376##21##]. KHU14 (400 mg/kg of body weight), dexamethasone (1 mg/kg of body weight) and vehicle (0.5% CMC) were orally administered to three groups of mice at one, three, and five days respectively after sensitization. One day after the last feed of test sample, all mice were challenged by applying 10 μl of 0.5% oxazolone in a mixture of acetone and olive oil (4:1) to the inner and outer surfaces of the right ear. The inhibitory effect of the test sample on the delayed type hypersensitivity (DTH) reaction was determined in comparison to the DTH reaction in 0.5% CMC-fed mice. The intensities of the DTH reaction were measured as the difference between the right ear thickness and the left ear thickness 24 hours after the 0.5% oxazolone challenge.</p>", "<title>Statistical analysis</title>", "<p>The results are expressed as mean and standard deviation (SD). The statistical significance between groups was determined by ANOVA and by non-parametric Kruskal-Wallis test with the GraphPad Prism 4 software (GraphPad, USA). P values less than 0.05 were considered to be statistically significant.</p>" ]

[ "<title>Results and discussion</title>", "<title>Selection of three herbal extracts from 20 herbs</title>", "<p>To develop potent multiple herbal extracts with anti-inflammatory effects, we evaluated the <italic>in vitro </italic>anti-inflammatory effects of each herbal extract in terms of the production of NO in LPS and IFN-γ-stimulated peritoneal macrophages (Table ##TAB##0##1##). Out of the 20 herbs, three were selected and combined to form KHU14 according to their anti-inflammatory effects and traditional usage in Chinese medicine and their major active ingredients. KHU14 was evaluated for its anti-inflammatory effects against those of a single herb (Table ##TAB##1##2##).</p>", "<title>Effects of KHU14 on cell viability and iNOS and COX-2 expression in RAW264.7 cells</title>", "<p>To identify the toxic effect of KHU14, we tested its effects on the viability of a murine macrophage cell line (RAW264.7) with 0.025% trypan blue dye exclusion method. The exposure of the cells to KHU14 (1–100 μg/ml) for 72 hours showed no significant adverse effect on the cell viability, while after exposure to KHU14 (200 μg/ml) for 72 hours, the cell viability was reduced to 80% of that of the control (Figure ##FIG##0##1A##). In addition, KHU14 (100 μg/ml) inhibited the expression of iNOS and COX-2 in an LPS-activated RAW264.7 cell line without causing cytotoxicity (Figure ##FIG##0##1B##).</p>", "<title>In vitro effects of KHU14 on NO and PGE₂in peritoneal macrophages</title>", "<p>Macrophages play a central role in the overproduction of pro-inflammatory cytokines and inflammatory mediators such as NO (Figure ##FIG##1##2A##) and PGE₂(Figure ##FIG##1##2B##). KHU14 (1–100 μg/ml) significantly inhibited LPS/IFN-γ-induced NO and PGE₂production in peritoneal macrophages in a dose-dependent manner. KHU14 (100 μg/ml) inhibited NO and PGE₂production by 27% and 49% respectively.</p>", "<title>In vivo effects of KHU14 on acute inflammation</title>", "<p>We employed three animal models of acute inflammation to evaluate the anti-inflammatory effects of KHU14: (1) inhibition of croton oil-induced ear edema in mice; (2) carrageenan-induced paw edema in rats; and (3) acetic acid-induced permeability test in mice.</p>", "<p>In the croton oil-induced ear edema model for testing the topical anti-inflammatory effects of KHU14, the control group which received 0.5% CMC increased 81.8% in ear thickness. The KHU14 and celecoxib groups increased 64.8% and 64.1% in ear thickness respectively. The results indicate that KHU14 and celecoxib reduced ear thickness by 20% (Figure ##FIG##2##3A##). In the carrageenan induced paw edema test, the paw volume increased 51.8% in the control group which received CMC, while it increased 31.4% and 32.3% in the celecoxib and KHU14 groups respectively. The results indicate that celecoxib and KHU14 reduced paw edema by 40% and 38% respectively (Figure ##FIG##2##3B##). In the acetic acid-induced permeability test, celecoxib group reduced permeability by 35%; KHU14, however, did not significantly reduce the permeability of Evan blue (Figure ##FIG##2##3C##).</p>", "<title>In vivo effects of KHU14 on chronic inflammation</title>", "<p>In the cotton pellet test, the dry cotton in CMC, celecoxib, and KHU14 groups weighted 74.7 mg, 63.3 mg, and 55.3 mg respectively (Figure ##FIG##3##4A##). KHU14 inhibited the infiltration of immune cells by 26% with statistical significance. In the oxazolone-induced DTH model, the right ear thickness of the control group increased 72.1%, while it increased 59.0% and 58.6% in the dexamethasone group and KHU14 group respectively. The results indicate that dexamethsone and KHU14 reduced ear swelling by 18% and 19% respectively (Figure ##FIG##3##4B##).</p>", "<p>The results of the present study suggest that KHU14 has considerable potency in anti-inflammatory action and that it can be used as an anti-inflammatory agent to treat certain inflammatory diseases. To further determine its therapeutic effects, we will evaluate the toxicity of KHU14 <italic>in vivo </italic>and in animal models of diseases such as collagen-induced arthritis [##REF##15240719##22##] and psoriasis-like skin diseases [##UREF##1##23##]. Future studies are warranted to determine the optimal combination ratio for this formulation. Furthermore, the action mechanisms by which KHU14 exerts its anti-inflammatory effects remain to be elucidated.</p>" ]

[ "<title>Results and discussion</title>", "<title>Selection of three herbal extracts from 20 herbs</title>", "<p>To develop potent multiple herbal extracts with anti-inflammatory effects, we evaluated the <italic>in vitro </italic>anti-inflammatory effects of each herbal extract in terms of the production of NO in LPS and IFN-γ-stimulated peritoneal macrophages (Table ##TAB##0##1##). Out of the 20 herbs, three were selected and combined to form KHU14 according to their anti-inflammatory effects and traditional usage in Chinese medicine and their major active ingredients. KHU14 was evaluated for its anti-inflammatory effects against those of a single herb (Table ##TAB##1##2##).</p>", "<title>Effects of KHU14 on cell viability and iNOS and COX-2 expression in RAW264.7 cells</title>", "<p>To identify the toxic effect of KHU14, we tested its effects on the viability of a murine macrophage cell line (RAW264.7) with 0.025% trypan blue dye exclusion method. The exposure of the cells to KHU14 (1–100 μg/ml) for 72 hours showed no significant adverse effect on the cell viability, while after exposure to KHU14 (200 μg/ml) for 72 hours, the cell viability was reduced to 80% of that of the control (Figure ##FIG##0##1A##). In addition, KHU14 (100 μg/ml) inhibited the expression of iNOS and COX-2 in an LPS-activated RAW264.7 cell line without causing cytotoxicity (Figure ##FIG##0##1B##).</p>", "<title>In vitro effects of KHU14 on NO and PGE₂in peritoneal macrophages</title>", "<p>Macrophages play a central role in the overproduction of pro-inflammatory cytokines and inflammatory mediators such as NO (Figure ##FIG##1##2A##) and PGE₂(Figure ##FIG##1##2B##). KHU14 (1–100 μg/ml) significantly inhibited LPS/IFN-γ-induced NO and PGE₂production in peritoneal macrophages in a dose-dependent manner. KHU14 (100 μg/ml) inhibited NO and PGE₂production by 27% and 49% respectively.</p>", "<title>In vivo effects of KHU14 on acute inflammation</title>", "<p>We employed three animal models of acute inflammation to evaluate the anti-inflammatory effects of KHU14: (1) inhibition of croton oil-induced ear edema in mice; (2) carrageenan-induced paw edema in rats; and (3) acetic acid-induced permeability test in mice.</p>", "<p>In the croton oil-induced ear edema model for testing the topical anti-inflammatory effects of KHU14, the control group which received 0.5% CMC increased 81.8% in ear thickness. The KHU14 and celecoxib groups increased 64.8% and 64.1% in ear thickness respectively. The results indicate that KHU14 and celecoxib reduced ear thickness by 20% (Figure ##FIG##2##3A##). In the carrageenan induced paw edema test, the paw volume increased 51.8% in the control group which received CMC, while it increased 31.4% and 32.3% in the celecoxib and KHU14 groups respectively. The results indicate that celecoxib and KHU14 reduced paw edema by 40% and 38% respectively (Figure ##FIG##2##3B##). In the acetic acid-induced permeability test, celecoxib group reduced permeability by 35%; KHU14, however, did not significantly reduce the permeability of Evan blue (Figure ##FIG##2##3C##).</p>", "<title>In vivo effects of KHU14 on chronic inflammation</title>", "<p>In the cotton pellet test, the dry cotton in CMC, celecoxib, and KHU14 groups weighted 74.7 mg, 63.3 mg, and 55.3 mg respectively (Figure ##FIG##3##4A##). KHU14 inhibited the infiltration of immune cells by 26% with statistical significance. In the oxazolone-induced DTH model, the right ear thickness of the control group increased 72.1%, while it increased 59.0% and 58.6% in the dexamethasone group and KHU14 group respectively. The results indicate that dexamethsone and KHU14 reduced ear swelling by 18% and 19% respectively (Figure ##FIG##3##4B##).</p>", "<p>The results of the present study suggest that KHU14 has considerable potency in anti-inflammatory action and that it can be used as an anti-inflammatory agent to treat certain inflammatory diseases. To further determine its therapeutic effects, we will evaluate the toxicity of KHU14 <italic>in vivo </italic>and in animal models of diseases such as collagen-induced arthritis [##REF##15240719##22##] and psoriasis-like skin diseases [##UREF##1##23##]. Future studies are warranted to determine the optimal combination ratio for this formulation. Furthermore, the action mechanisms by which KHU14 exerts its anti-inflammatory effects remain to be elucidated.</p>" ]

[ "<title>Conclusion</title>", "<p>The present study suggests that KHU14 exerts anti-inflammatory effects as it inhibits the production of NO and PGE₂in LPS/IFN-γ-stimulated peritoneal macrophages and reduces edema and the amount of infiltrated cells in animal models.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>KHU14, an ethanolic extract of <italic>Radix Gentianae Macrophyllae </italic>(<italic>Qinjiao</italic>), <italic>Rhizoma Coptidis </italic>(<italic>Huanglian</italic>) and <italic>Citri Unshiu Pericarpium </italic>(<italic>Wenzhou migan</italic>) was tested for its anti-inflammatory effects.</p>", "<title>Methods</title>", "<p>Three out of 20 herbs were found to have anti-inflammatory effects. The formulation of these herbs, i.e. KHU14 was tested for croton oil-induced ear edema, carrageenan-induced paw edema, acetic acid-induced capillary permeability, cotton pellet and delayed type hypersensitivity.</p>", "<title>Results</title>", "<p>KHU14 exhibited anti-inflammatory effects in animal models of acute and chronic inflammation. The anti-inflammatory activity of KHU14 observed was comparable to that of celecoxib. KHU14 inhibited the production of NO and PGE₂in LPS/IFN-gamma-stimulated peritoneal macrophages, and reduced edema and the amount of infiltrated cells in animal models.</p>", "<title>Conclusion</title>", "<p>KHU14 exhibited anti-inflammatory effects as demonstrated in typical immunological tests for anti-inflammation <italic>in vitro </italic>and <italic>in vivo</italic>.</p>" ]

[ "<title>Abbreviations</title>", "<p>CMC: carboxymethyl cellulose; DMEM: Dulbecco's Modified Essential Medium; DMSO: dimethyl sulfoxide; DTH: delayed type hypersensitivity; IFN-γ: interferon-gamma; iNOS: inducible nitric oxide synthase; LPS: lipopolysaccharide; NO: nitric oxide; OD: optical density; PGE₂: prostaglandine E₂; SD: standard deviation.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>KSK and HIR conducted the experiments and data analysis. EKP conducted the <italic>in vitro </italic>experiments. KJ and HJJ prepared herbal extracts. JHK and HY assisted the <italic>in vivo </italic>experiments. CKH, YBC and CJR were responsible for the data analysis. HIY helped draft the manuscript. KSK and MCY prepared the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported by a research grant (03-PJ9-PG6-SO01-002) from the Korean Ministry of Health and Welfare.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Effects of KHU14 on cell viability and iNOS and COX-2 expression in RAW264.7 cells</bold>. (A) Cell viability. (B) Western blot. RAW264.7 cells were treated with 0, 1, 10, 100, 200 μg/ml of KHU14 dissolved in DMSO one hour before stimulated with LPS (1 μg/ml) for 72 hours for measurement of cell viability. For western blot analysis, cells were stimulated with LPS for 24 hours in the presence of KHU14. The results are expressed as mean and SD.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Effects of KHU14 on the NO and PGE₂production in mouse peritoneal macrophages</bold>. The cells were treated with 0, 1, 10, 50 and 100 μg/ml of KHU14 dissolved in DMSO respectively 30 minutes before stimulated with LPS (1 μg/ml) + IFN-γ (1 ng/ml) for 24 hours. The supernatants were collected and used for the measurement of the amount of (A) NO and (B) PGE₂. The results are expressed as mean and SD.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Anti-inflammatory effects of KHU14 on animal models of acute inflammation</bold>. (A) Ear edema in mice (n = 10). (B) Paw edema in rats (n = 8). (C) Capillary permeability test (n = 15). The mice and rats were orally fed with KHU14 (400 mg/kg of body weight) and celecoxib (100 mg/kg of body weight). The control group received 0.5% CMC orally. NS: not significant.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Anti-inflammatory effects of KHU14 on a mouse model of chronic inflammation</bold>. (A) Cotton pellet test (n = 6). (B) DTH (n = 12). The mice were orally fed with KHU14 (400 mg/kg of body weight) and celecoxib (100 mg/kg of body weight) for cotton pellet test and dexamethasone (1 mg/kg of body weight) for DTH. The control group received 0.5% CMC orally. NS: not significant.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Effects of 20 single herbal extracts (100 μg/ml) on nitrite in mouse peritoneal macrophages stimulated by LPS and IFN-γ</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\">1</td><td align=\"left\">2</td><td align=\"left\">3</td><td align=\"left\">4</td><td align=\"left\">5</td><td align=\"left\">6*</td><td align=\"left\">7</td><td align=\"left\">8*</td><td align=\"left\">9</td><td align=\"left\">10</td><td align=\"left\">11</td><td align=\"left\">12</td><td align=\"left\">13</td><td align=\"left\">14</td><td align=\"left\">15*</td><td align=\"left\">16</td><td align=\"left\">17</td><td align=\"left\">18</td><td align=\"left\">19</td><td align=\"left\">20</td></tr></thead><tbody><tr><td align=\"left\">mean (μM)</td><td align=\"left\">61.3</td><td align=\"left\">55.4</td><td align=\"left\">52.2</td><td align=\"left\">48.8</td><td align=\"left\">50.2</td><td align=\"left\">45.3</td><td align=\"left\">41.8</td><td align=\"left\">47.9</td><td align=\"left\">50</td><td align=\"left\">44.9</td><td align=\"left\">50.1</td><td align=\"left\">65.8</td><td align=\"left\">40.6</td><td align=\"left\">39.1</td><td align=\"left\">38.2</td><td align=\"left\">53.1</td><td align=\"left\">45.3</td><td align=\"left\">39.1</td><td align=\"left\">38.4</td><td align=\"left\">40.1</td></tr><tr><td align=\"left\">SD</td><td align=\"left\">1.7</td><td align=\"left\">2.7</td><td align=\"left\">1.5</td><td align=\"left\">2.2</td><td align=\"left\">2.9</td><td align=\"left\">2.8</td><td align=\"left\">3.5</td><td align=\"left\">2.1</td><td align=\"left\">3.6</td><td align=\"left\">2.8</td><td align=\"left\">2.1</td><td align=\"left\">4.3</td><td align=\"left\">2.7</td><td align=\"left\">3.5</td><td align=\"left\">2.3</td><td align=\"left\">1.8</td><td align=\"left\">2.1</td><td align=\"left\">3.6</td><td align=\"left\">2.7</td><td align=\"left\">3.8</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Effects of KHU14 and its herbal components (100 g/ml) on nitrite in mouse peritoneal macrophages stimulated by LPS and IFN-γ</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\">KHU14</td><td align=\"left\"><italic>Radix Gentianae Macrophyllae</italic></td><td align=\"left\"><italic>Rhizoma Coptidis</italic></td><td align=\"left\"><italic>Citri Unshiu Pericarpium</italic></td></tr></thead><tbody><tr><td align=\"left\">Mean (μM)</td><td align=\"left\">40.2</td><td align=\"left\">49.2</td><td align=\"left\">41.9</td><td align=\"left\">50.7</td></tr><tr><td align=\"left\">SD</td><td align=\"left\">2.1</td><td align=\"left\">3.8</td><td align=\"left\">3.1</td><td align=\"left\">3.5</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>1 <italic>Sophora subprostrata</italic>; 2 <italic>Siegesbeckia pubescens</italic>; 3 <italic>Angelica acutiloba</italic>; 4 <italic>Vitex rotundifolia</italic>; 5 Anemarrhena asphodelodies; *6 <italic>Gentiana macrophylla; </italic>7 <italic>Poria cocos</italic>; *8 <italic>Citrus unshiu</italic>; 9 <italic>Eucommia ulmodies</italic>; 10 <italic>Polygonatum sibiricum</italic>; 11 <italic>Cinnamomum cassia</italic>; 12 <italic>Chaenomels sinensis</italic>; 13 <italic>Atractylodes lancea</italic>; 14 <italic>Aralia cordata</italic>; *15 <italic>Coptis chinensis</italic>; 16 <italic>Clematis mandshurica</italic>; 17 <italic>Phellodendron amurensis</italic>; 18 <italic>Scutellaria baicalensis</italic>; 19 <italic>Cimicifuga heracalensis</italic>; 20 <italic>Pueraria thunbergiana</italic></p><p>*: Selected herbs for the KUH14 formulation</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1749-8546-3-10-1\"/>", "<graphic xlink:href=\"1749-8546-3-10-2\"/>", "<graphic xlink:href=\"1749-8546-3-10-3\"/>", "<graphic xlink:href=\"1749-8546-3-10-4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Up to 15% of colorectal cancer (CRC) patients present with obstructive or perforated tumors and require emergency surgery. In this setting, colonic resections carry 10–20% mortality and 30–50 morbidity rates, due to the patients' poor condition [##UREF##0##1##,##REF##17880381##2##]. Ideally, these patients would benefit from preoperative insertion of a metallic stent, in order to eventually perform a semi-elective curative resection with primary anastomosis [##REF##17968980##3##]. Unfortunately, most of these procedures are performed out of hours, in elderly individuals, who are often dehydrated and hemodynamically unstable, due to concomitant sepsis [##REF##15213621##4##]: under these conditions, many experienced surgeons would consider prohibitive the risk to perform a primary anastomosis. It is therefore not surprising that the operation described by Henri Hartmann in 1921, consisting of resection of the offending part of the left/sigmoid colon, proximal end colostomy and closure of the rectal stump, remains popular today, and has continued to extricate surgeons and patients alike from many a delicate situation [##UREF##1##5##].</p>", "<p>This procedure gained wide acceptance in the 1970s for the management of complicated diverticulitis, and it is surprising that few series have focused on CRC patients, and addressed the oncological outcome of this procedure. Back in the early 80s, surgeons from the Mayo Clinic reported 54%, 23%, and 3% 5-year survival rates for Stage II, III and IV cancers respectively, but a majority of patients were electively operated [##REF##7235957##6##]. Subsequently, Kristiansen reported 5-year survival rate of 31% and that intestinal continuity was restored in seven (24%) of 29 patients who underwent HP for obstructive left-sided CRC [##REF##8256380##7##]. In addition, McArdle and Hole have demonstrated that emergency surgery for CRC is associated with high (8%) mortality and poor (39%) 5-year overall survival rates, even after a curative resection [##REF##15122613##8##]. It would therefore be tempting to consider that emergency HP for left-sided CRC is an obsolete operation, often performed with a palliative intent in elderly and/or very sick patients with a high risk of cancer-related as well as intercurrent death [##REF##15655630##9##].</p>", "<p>Many surgeons, however, still consider that HP remains a good option to achieve R0 resection, while minimizing surgical trauma in poor-risk CRC patients [##REF##16185593##10##,##REF##15943733##11##]. The aim of this study was to assess the surgical (operative mortality), oncological (long-term survival after curative resection) and functional (permanent colostomy vs. restoration of intestinal continuity) results of emergency HP for obstructive or perforated left-sided CRC.</p>" ]

[ "<title>Methods</title>", "<p>This is a retrospective analysis of all patients who underwent emergency Hartmann's procedure for CRC in our institution between 1995 and 2006. The University Hospital of Geneva is the only public medical institution in a mainly urban area, and thus provides primary care for 75–80% of a population of 500,000 inhabitants. An average number of 350 colectomies are performed each year in our institution, 90–95 being emergency resections. Initially, we considered all patients who were operated within 48 hours of their unplanned admission for colonic occlusion or colorectal perforation. Subsequently, we selected in this population patients with a final diagnosis of colorectal adenocarcinoma, as determined by histopathologic examination of the surgical specimen. The charts of 50 consecutive patients with obstructive/perforated left-sided CRC who underwent emergency HP were analyzed.</p>", "<p>The following parameters were included in the structured database:</p>", "<p><bold>1) Patients' demographics</bold>; gender; age; and ASA score,</p>", "<p><bold>2) Tumour characteristics</bold>; Location (left colon vs. rectum); mode of presentation (obstructive vs. perforated); TNM stage; and mode of dissemination for metastatic cancers (peritoneal vs. liver).</p>", "<p><bold>3) Modalities of HP (first stage)</bold>; type of resection (curative vs. palliative); degree of peritoneal contamination (none vs. purulent vs. stercoral); operative mortality, defined as death within 30 days of surgery; and postoperative complications. The operative report was assessed to determine with precision the reasons for not having performed a primary anastomosis; those included preoperative co-morbidities, peroperative hemodynamic instability, localized/generalized peritonitis, and doubtful viability of the proximal colon.</p>", "<p><bold>4) Modalities of HP reversal (second stage</bold>); delay between HP and restoration of intestinal continuity; operative mortality; and surgical complications. We also recorded the preoperative imaging and endoscopic investigations performed prior to reversal, such as CT scan, colonoscopy, PET scan</p>", "<p>Follow-up was carried out through routine visits at our Outpatient Surgical Oncology Clinic, for those patients who underwent adjuvant radiation or chemotherapy. Serum CarcinoEmbryonary Antigen (CEA) levels were assessed every three months during the first two years after surgery and every six months thereafter. Yearly colonoscopy and chest X-rays were performed routinely and abdominal CT scan or liver ultrasonography were performed in patients with raising CEA levels or clinical suspicion for tumour recurrence. Whenever possible, confirmation of data was obtained through interviews with the physicians or the patients. Primary outcome measure was overall survival; secondary outcome measures were: 1) disease-free survival; 2) surgical mortality; and 3) restoration of intestinal continuity (Hartmann's reversal).</p>", "<title>Statistical analysis</title>", "<p>Life-tables curves (global survival endpoints: death, irrespective of course, and tumor-free survival endpoints: definite tumor recurrence or death) were analyzed with the Kaplan-Meier method and distributions were compared by the log-rank test. In case of simultaneous analysis of more than 2 populations, statistical differences were assessed by an extension of Gehan's generalized Wilcoxon test, Peto and Peto's generalized Wilcoxon test and the log-rank test algorithms, using the Statistica 5.5. software (Statsoft Inc, Tulsa, OK, US). Continuous data were analyzed by bilateral Student t test and dichotomous data were analyzed by chi-square test. P values lower than 0.05 were considered significant.</p>" ]

[ "<title>Results</title>", "<p>Median age of patients was 75 (range 22–95) years and the indications for HP were obstruction (32) and perforation (18 patients). The median follow-up was 22 (range 5–111) months. All fifty patients were available for complete follow up, except one who left our country. 29 patients died during this study period, and at the time of last follow-up, 5 patients were alive with recurrence. Operative mortality and morbidity were 8% and 26% respectively. Patients' and tumours characteristics are summarized in Table ##TAB##0##1##. Fifteen patients presented with metastatic disease (12 = liver and 3 = carcinomatosis). For the whole group, overall 1-, 3-, and 5-year survival rates were 72%, 38% and 30% (Figure ##FIG##0##1##). 35 patients (70%) were operated with a curative intent, with a median survival of 28 months; in this group, overall 1-, 3- and 5-year survival rates were 80%, 54% and 40% (Figure ##FIG##1##2##). In univariate analysis, the mode of presentation (perforation vs. obstruction) was not associated with improved survival (p = 0.51) (Figure ##FIG##2##3##). By, contrast, the presence of lymph node metastases was associated with decreased 5-year survival (62% [Stage II] vs. 27% [Stage III], log-rank test, p = 0.02) (Figure ##FIG##3##4##).</p>", "<p>Eleven patients (22% for the whole group, but 31% of patients operated with a curative intent) had their operation reversed with a median delay of 225 (range 94–390) days. There were no death and no anastomotic dehiscence after the second stage of the procedure. However, two patients had unsuccessful attempt to restore intestinal continuity, one because of dense adhesions within the pelvis, the other because of local recurrence, which was undetected prior to surgery. In this subgroup, two patients eventually died from distant metastases.</p>" ]

[ "<title>Discussion</title>", "<p>The data presented here indicate that 70% of patients who underwent emergency surgery for obstructive/perforated left-sided CRC had a curative resection. In this group, 5-year survival rate was 40%. The prognosis was similar to elective procedures, and strongly related to tumour stage, more than to the mode of presentation. For stage II patients, 5-year overall survival rate was 62%, and Hartmann's reversal rate was 63%. For those patients who presented with Stage IV disease, HP was effective in palliating symptoms during a median survival of only 13 months.</p>", "<p>In accordance with population-based study from Burgundy [##REF##17687610##12##], our data demonstrate that, in this difficult clinical setting, resection for cure is still possible in 70% of cases. By contrast, the operative mortality (8%) and morbidity rates (26%) in this series compare favourably with other, reporting mortality rates in the 10–15% range for similar patients and conditions [##REF##8862074##13##, ####REF##12525912##14##, ##REF##9849728##15####9849728##15##]. It has been recognized, however, that the negative impact of emergency surgery on CRC outcome is confined to the immediate postoperative period [##REF##16228922##16##]. Among Stage II-III CRC patients surviving surgery, there is little difference in overall survival between patients undergoing emergency compared with elective operation [##REF##12544518##17##]. Thus, the goals of surgery in poor-risk patients with obstructive or perforated CRC are two-fold; 1) providing effective palliation of symptoms in patients with R1–R2 resections: and 2) minimizing surgical mortality in patients with R0 resections.</p>", "<p>As rightfully pointed out by Armbruster [##REF##11554135##18##], primary resection with anastomosis and HP are not competing operations, but two situation-dependent therapeutic alternatives. It should, however, be noted that the performance of a resection with primary anastomosis exposes the patients to the risk of anastomotic dehiscence; and that a leaking colorectal anastomosis is associated with a significant increase in local recurrence [##REF##15789125##19##,##REF##12790981##20##], as well as poor long-term survival [##REF##14515297##21##,##REF##15273549##22##]. Therefore, efforts should be made to avoid this complication and its consequences, such as wound infection, intra-abdominal sepsis and the need for subsequent re-operation, which inevitably delay administration of postoperative chemotherapy in Stage III patients, who would benefit the most from this adjuvant modality [##REF##16333005##23##].</p>", "<p>It is known that a high percentage of CRC patients who underwent HP end up with a permanent stoma. In our series, eleven patients only (22% for the whole group; 31% of patients operated with a curative intent) had their operation reversed with a median delay of 225 (range 94–390) days. In two additional patients reversal was attempted, but was considered unfeasible at the time of surgery. Similarly low reversal rates have been reported by other groups [##REF##17256137##24##,##REF##16108881##25##]. In our institution, Hartmann's reversal in patients with CRC is usually delayed for 8–10 months, but not more: experience from the Dutch Rectal cancer Trial has shown that if a stoma was not closed within the first year, it would probably become permanent [##REF##17395102##26##]. The interval between the two stages of the procedures allows for identification of good risk patients for stoma closure; patients with stage II tumours; patients with stage III cancers who subsequently underwent adjuvant chemotherapy; and socially active patients. By contrast, elderly patients with T4 or N2 tumours, who are at high risk for developing local recurrence, are candidates for a definitive colostomy.</p>" ]

[ "<title>Conclusion</title>", "<p>Hartmann's operation is effective in palliating symptoms in 30% of patients with obstructive/perforated stage IV left-sided CRC. For those who are candidates to a curative resection, this approach minimizes surgical mortality/morbidity and is associated with stage-dependent survival rates close to those of elective operations. Patients with stage II cancers have good oncological (62% 5-year survival rate) and functional (63% reversal rate) outcomes, and benefit the most from this surgical strategy. Some experts consider that the Hartmann's procedure is today \"out of vogue\"; it might be true for complicated diverticulitis, but probably not for the emergency management of left-sided colorectal cancer-the original indication for this time-honoured operation.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Up to 15% of colorectal cancer (CRC) patients present with obstructive or perforated tumours, and require emergency surgery. The Hartmann's procedure (HP) provides the opportunity to achieve a potentially curative (R0) resection, while minimizing surgical trauma in poor-risk patients. The aim of this study was to assess the surgical (operative mortality), and oncological (long-term survival after curative resection) results of emergency HP for obstructive or perforated left-sided CRC.</p>", "<title>Methods</title>", "<p>A retrospective review of 50 patients who underwent emergency HP for perforated/obstructive CRC in our institution between 1995 and 2006.</p>", "<title>Results</title>", "<p>Median age of patients was 75 (range 22–95) years and the indications for HP were obstruction (32) and perforation (18 patients). Operative mortality and morbidity were 8% and 26% respectively. 35 patients (70%) were operated with a curative intent; in this group, overall 1-, 3- and 5-year survival rates were 80%, 54% and 40%. In univariate analysis, the presence of lymph node metastases was associated with poor 5-year survival (62% [Stage II] vs. 27% [Stage III], log-rank test, p = 0.02). Eleven patients (22%) had their operation reversed with a median delay of 225 (range 94–390) days. In this subgroup, two patients died from distant metastases, but there were no instances of loco-regional recurrence.</p>", "<title>Conclusion</title>", "<p>Hartmann's operation remains a good option to palliate symptoms in 30% of patients with left-sided CRC who are not candidates to a curative resection. For those who have a curative resection, the oncological outcome is acceptable, especially stage II patients, who appear to benefit the most from this surgical strategy.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>PC and PG conceived of the study and wrote the manuscript. AA performed the statistical analysis. FG and BK coordinated the study and helped to draft the manuscript. PM supervised the study. All authors read and approved the final manuscript.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Overall survival.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Survival according to type of resection.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Overall survival according to mode of presentation.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Overall survival according to tumour stage.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Patients' and Tumour Characteristics (N = 50)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Parameter</bold></td><td/></tr></thead><tbody><tr><td align=\"left\"><bold>Gender</bold></td><td/></tr><tr><td align=\"left\"> Male</td><td align=\"left\">24</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">26</td></tr><tr><td align=\"left\"><bold>Age, median (range)</bold></td><td align=\"left\">75 (22–95)</td></tr><tr><td align=\"left\"><bold>Tumour location</bold></td><td/></tr><tr><td align=\"left\"> Colon</td><td align=\"left\">35</td></tr><tr><td align=\"left\"> Rectum</td><td align=\"left\">15</td></tr><tr><td align=\"left\"><bold>Tumour stage</bold></td><td/></tr><tr><td align=\"left\"> II</td><td align=\"left\">13</td></tr><tr><td align=\"left\"> III</td><td align=\"left\">21</td></tr><tr><td align=\"left\"> IV</td><td align=\"left\">16</td></tr><tr><td align=\"left\"><bold>Adjuvant treatment</bold></td><td/></tr><tr><td align=\"left\"> None</td><td align=\"left\">31</td></tr><tr><td align=\"left\"> Radiation therapy</td><td align=\"left\">3</td></tr><tr><td align=\"left\"> Chemotherapy</td><td align=\"left\">16</td></tr><tr><td align=\"left\"><bold>Restoration of intestinal continuity</bold></td><td/></tr><tr><td align=\"left\"> No</td><td align=\"left\">39</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">11</td></tr><tr><td align=\"left\"><bold>Cause of death (N = 29)</bold></td><td/></tr><tr><td align=\"left\"> Cancer</td><td align=\"left\">23 (local recurrence = 6)</td></tr><tr><td align=\"left\"> Postoperative</td><td align=\"left\">4</td></tr><tr><td align=\"left\"> Non cancer-related</td><td align=\"left\">2</td></tr></tbody></table></table-wrap>" ]

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[ "<graphic xlink:href=\"1477-7819-6-90-1\"/>", "<graphic xlink:href=\"1477-7819-6-90-2\"/>", "<graphic xlink:href=\"1477-7819-6-90-3\"/>", "<graphic xlink:href=\"1477-7819-6-90-4\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Osteosarcoma is the most common primary malignant tumour of bone, with the exception of multiple myeloma. It represents approximately 15% of all biopsy-analyzed primary bone tumours [##UREF##0##1##,##REF##9389923##2##]. It is most common in males and occurs primarily in the second decade of life. The most common location sites are the metaphysis of bone [##UREF##1##3##,##REF##16421923##4##]. The age of the patients, coinciding with the adolescent growth spurt as well as the location of tumour sites has led to the syllogism that factors related to skeletal growth are involved in the pathogenesis of this tumour [##REF##14752796##5##, ####REF##1067559##6##, ##UREF##2##7####2##7##]. Previous studies maintain that treatment with growth hormone and somatostatin affects the growth of osteosarcoma in animal models [##REF##8631606##8##, ####REF##10850839##9##, ##REF##12114446##10####12114446##10##]. Somatostatin is believed to exert antiproliferative effects on tumour cells through receptor-mediated stimulation of tyrosine phosphatase and inhibition of other endogenous growth factors, like growth hormone and insuline-like growth factor 1 [##REF##1346787##11##,##REF##2160951##12##]. In this respect, the presence of somatostatin receptors in human osteosarcoma may have a diagnostic, prognostic and therapeutic value [##REF##1356016##13##].</p>", "<p>In this study we aim to detect somatostatin receptors in human osteosarcomas and correlate this finding with the clinical outcome of the tumour.</p>" ]

[ "<title>Patients and methods</title>", "<p>Twenty-nine patients with primary osteosarcoma who were treated at the authors' institution between 1997 and 2006 were included in this study. Fourteen patients were female and fifteen were male. The average age at the time of diagnosis was 27.03 years (range 16–49 years) (Table ##TAB##0##1##). Preoperative evaluation included precision imaging techniques (plain radiographs, computed tomography and MRI of the lesion, computed tomography of the chest and full body scan with Tc99m). Distribution of anatomic tumour sites was as described in Table ##TAB##0##1##. The therapeutic protocol included neoadjuvant chemotherapy in all patients with high-dose methotrexate [##REF##16353204##14##, ####REF##1370176##15##, ##REF##17611853##16####17611853##16##]. During preoperative chemotherapy one patient died, while we operated on twenty-eight patients aiming at wide resection margins.</p>", "<p>Twenty-four patients underwent a limb salvage procedure, while in four patients amputation was the only surgical option in order to achieve adequate local control.</p>", "<p>Disease-free and overall survival was recorded in all patients (table ##TAB##1##2##).</p>", "<p>Histological specimens were available for all patients and were reviewed by one experienced pathologist (I.I.). The resected specimens were sliced coronally or axially or both to represent the largest portion of the tumour. The slices were fixed in 10% neutral buffered formaldehyde solution and embedded separately in paraffin. The sections were stained with haematoxylin and eosin and were used for immunohistochemistry. Polyclonal Rabbit Anti-Human somatostatin was used (Dako, Denmark) [##REF##342100##17##, ####REF##60437##18##, ##REF##60436##19####60436##19##] in order to detect the presence of somatostatin receptors [##REF##1968467##20##,##REF##7947094##21##]. The study was approved by the Metaxa Anticancer Hospital Ethical &amp; Scientific Committee.</p>" ]

[ "<title>Results</title>", "<p>Somatostatin receptors were expressed in four osteosarcoma's that exhibited aggressive features (figure ##FIG##0##1## and ##FIG##1##2##). These four tumours appeared in young patients (table ##TAB##2##3##) with an aggressive biologic behaviour having an event-free rate of 0% and an overall survival rate of 50% at 4.3 years (table ##TAB##3##4##). In contrast, the event-free survival rate of the twenty-five patients with negative growth hormone receptor status was 72% with an overall survival rate of 76% at 4.3 years.</p>", "<p>Case one represents a woman, 19-years-old, with a right proximal tibia tumour, stage II B+ on Enneking's staging system [##REF##3456859##22##]. She underwent neoadjuvant chemotherapy followed by femoral amputation. Histological examination revealed grade II osteosarcoma with osteoblastic, as well as chondroblastic areas and 80% tumour necrosis. Two years later there was a local recurrence in the stump of the sciatic nerve, which was treated with hip disarticulation and chemotherapy. Four years post-operative, this patient presented lung metastases, was treated with chemotherapy and eventually died after 1 year. In our retrospective histological study somatostatin receptors were detected.</p>" ]

[ "<title>Discussion</title>", "<p>The use of neoadjuvant chemotherapy in the treatment protocol of osteosarcoma in the late 70's improved disease-free survival, giving a cure rate of 60%–70% for patients with nonmetastatic osteosarcoma of the extremities at presentation [##REF##11118462##23##, ####REF##9789613##24##, ##REF##8996127##25####8996127##25##].</p>", "<p>Little is known about the aetiology and pathogenesis of this tumour. Genetic predisposition, viral aetiology, irradiation and alkylating agents have been suggested in the pathogenesis of osteosarcoma [##UREF##1##3##,##REF##189372##26##,##REF##4521231##27##]. Nowadays, molecular biology seems to be the next step in understanding pathogenesis and improving survival of osteosarcoma. Tumour location in the metaphysis as well as the age of the patients coinciding with the period of rapid body growth suggest that factors related to skeletal growth are involved in the pathogenesis of this tumour.</p>", "<p>Somatostatin is characterized as a hormone which inhibits the release of growth hormone from the anterior pituitary gland [##UREF##3##28##]. The present study demonstrates the existence of somatostatin receptors in human osteosarcoma. Further research is necessary to demonstrate the importance of this finding and its clinical relevance, since there is also evidence from animal studies that treatment with growth hormone and somatostatin affects the growth of osteosarcoma in animal models [##REF##8631606##8##, ####REF##10850839##9##, ##REF##12114446##10####12114446##10##]. There is also one study in pediatric patients having metastatic osteosarcoma treated with somatostatin analogue (OncoLar) which shows that the levels of Insulin-like growth factor-1 were reduced. However, this study did not yield significant clinical results [##REF##12218590##29##].</p>", "<p>To our knowledge, there is only one study on humans in the literature with 18 osteosarcoma patients where the authors investigated somatostatin receptors by virtue of scintigraphy. In this study a very high incidence of patients with somatostatin receptors was found (up to 75%). The authors found higher incidence in non-metastatic patients and concluded that there is a possible relation between the somatostatin receptors presence and the biological behaviour of the tumour. [##REF##14629833##30##]</p>", "<p>A limitation to our study is the small number of specimens that were analyzed, which makes statistical analysis unfeasible; however, because of the novelty of our study and since the tumours expressing somatostatin receptors had a more deleterious course with a very low disease-free and overall survival rate compared to osteosarcoma with negative receptor status, even though the percentage (14%) was much lower than that in the Rizzoli study [##REF##14629833##30##], we believe that this finding should be thoroughly evaluated and investigated with further studies.</p>" ]

[ "<title>Conclusion</title>", "<p>In this study we detected somatostatin receptors in human osteosarcomas. This finding seems to have a prognostic value, predicating a severe aggressive biologic behaviour of the tumour as well as possible therapeutic implications.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The location of osteosarcoma in the metaphysis as well as the age of the patients during the most rapid tumour growth suggest that factors related to skeletal growth are involved in the pathogenesis of this tumour. In this aspect this study aims to detect somatostatin receptors in human osteosarcomas and correlate this finding with the clinical outcome of the tumour.</p>", "<title>Patients and methods</title>", "<p>Immunohistochemical staining for the presence of somatostatin receptors as well as overall survival and disease free survival rates were retrospectively studied in twenty-nine osteosarcoma patients.</p>", "<title>Results</title>", "<p>Four osteosarcomas with several aggressive biologic behaviour expressed somatostatin receptors. In these four young patients the event free rate was 0% and the overall survival rate was 50% at 4, 3 years. In contrast the event free survival rate of the twenty-five patients with negative somatostatin receptor status was 72% with an overall survival rate of 76% at 4,3 years.</p>", "<title>Conclusion</title>", "<p>The present study demonstrates the existence of somatostatin receptors in human osteosarcoma. Tumours expressing somatostatin receptors seemed to be aggressive with a very low disease free and overall survival rate compared to osteosarcoma with negative receptor status.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>MI drafted the manuscript and carried out the design of the study and performed. II carried out the immunohistochemical studies. PJP, IP and SK participated in the design and coordination of the study and helped to draft the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank Panou Christina for text editing (email:<email>[email protected]</email>)</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Osteosarcoma somatostatin negative. Magnification ×400</bold>. This case of an osteosarcoma had no somatostatin receptors. Immunohistochemistry staining with somatostatin did not produce any reaction.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Osteosarcoma somatostatin positive. Magnification ×630</bold>. In this case staining with somatostatin produced a reaction appearing with an orange zone around the nuclei. This case of osteosarcoma is expressing somatostatin receptors.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Sex, Age, Location, Surgical Treatment, Outcome and GH receptor status of 29 patients with osteosarcoma.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Sex</bold></td><td align=\"center\"><bold>Age</bold></td><td align=\"center\"><bold>Location (Site)</bold></td><td align=\"center\"><bold>Surgical Treatment</bold></td><td align=\"center\"><bold>Oncologic outcome</bold></td><td align=\"center\"><bold>GH receptor status</bold></td></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"center\">M</td><td align=\"center\">28</td><td align=\"center\">Thoracic Spine</td><td align=\"center\">LSS</td><td align=\"center\">DOD<break/>(Died On Disease)</td><td/></tr><tr><td align=\"left\">2</td><td align=\"center\">F</td><td align=\"center\">16</td><td align=\"center\">Distal femur</td><td align=\"center\">LSS</td><td align=\"center\">NED<break/>(No Evident Disease)</td><td/></tr><tr><td align=\"left\">3</td><td align=\"center\">F</td><td align=\"center\">19</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">Amputation</td><td align=\"center\">DOD</td><td align=\"center\">+</td></tr><tr><td align=\"left\">4</td><td align=\"center\">F</td><td align=\"center\">17</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">Amputation</td><td align=\"center\">DOD</td><td align=\"center\">+</td></tr><tr><td align=\"left\">5</td><td align=\"center\">F</td><td align=\"center\">39</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">DOD</td><td/></tr><tr><td align=\"left\">6</td><td align=\"center\">M</td><td align=\"center\">28</td><td align=\"center\">Distal Femur</td><td align=\"center\">Amputation</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">7</td><td align=\"center\">M</td><td align=\"center\">16</td><td align=\"center\">Distal Fibula</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">8</td><td align=\"center\">M</td><td align=\"center\">22</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">DOD</td><td/></tr><tr><td align=\"left\">9</td><td align=\"center\">F</td><td align=\"center\">18</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">DOD</td><td/></tr><tr><td align=\"left\">10</td><td align=\"center\">F</td><td align=\"center\">27</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">11</td><td align=\"center\">F</td><td align=\"center\">18</td><td align=\"center\">Distal Femur</td><td align=\"center\">Amputation</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">12</td><td align=\"center\">F</td><td align=\"center\">35</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">13</td><td align=\"center\">M</td><td align=\"center\">16</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">14</td><td align=\"center\">M</td><td align=\"center\">24</td><td align=\"center\">Proximal Humerus</td><td align=\"center\">LSS</td><td align=\"center\">Disease Progression<break/>(Pulmonary metastases)</td><td align=\"center\">+</td></tr><tr><td align=\"left\">15</td><td align=\"center\">M</td><td align=\"center\">18</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">16</td><td align=\"center\">M</td><td align=\"center\">32</td><td align=\"center\">Distal Tibia</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">17</td><td align=\"center\">F</td><td align=\"center\">34</td><td align=\"center\">Hip</td><td align=\"center\">Died during chemotherapy</td><td align=\"center\">DOD</td><td/></tr><tr><td align=\"left\">18</td><td align=\"center\">F</td><td align=\"center\">49</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">19</td><td align=\"center\">F</td><td align=\"center\">24</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">20</td><td align=\"center\">M</td><td align=\"center\">44</td><td align=\"center\">Proximal Humerus</td><td align=\"center\">LSS</td><td align=\"center\">DOD</td><td/></tr><tr><td align=\"left\">21</td><td align=\"center\">F</td><td align=\"center\">39</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">Disease Progression<break/>(Local recurrence)</td><td/></tr><tr><td align=\"left\">22</td><td align=\"center\">F</td><td align=\"center\">25</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">23</td><td align=\"center\">M</td><td align=\"center\">18</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">24</td><td align=\"center\">M</td><td align=\"center\">44</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">25</td><td align=\"center\">M</td><td align=\"center\">40</td><td align=\"center\">Distal Femur</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">26</td><td align=\"center\">M</td><td align=\"center\">20</td><td align=\"center\">Proximal Humerus</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">27</td><td align=\"center\">M</td><td align=\"center\">30</td><td align=\"center\">Proximal Humerus</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr><tr><td align=\"left\">28</td><td align=\"center\">M</td><td align=\"center\">16</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">LSS</td><td align=\"center\">Disease Progression<break/>(Pulmonary metastases)</td><td align=\"center\">+</td></tr><tr><td align=\"left\">29</td><td align=\"center\">F</td><td align=\"center\">28</td><td align=\"center\">Proximal Tibia</td><td align=\"center\">LSS</td><td align=\"center\">NED</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Disease free and overall survival rate at 4, 48 years, in 29 patients with osteosarcoma.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Frequency</td><td align=\"center\">Percent</td></tr></thead><tbody><tr><td align=\"left\">NED<break/>(No Evident Disease)</td><td align=\"center\">18</td><td align=\"center\">62,0</td></tr><tr><td align=\"left\">Disease progression</td><td align=\"center\">3</td><td align=\"center\">10,4</td></tr><tr><td align=\"left\">DOD<break/>(Died On Disease)</td><td align=\"center\">8</td><td align=\"center\">27,6</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">29</td><td align=\"center\">100,0</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Mean Age of patients with positive staining vs. patients with negative staining for receptors of Growth Hormone.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Patients with Positive staining for receptors of Growth Hormone</td><td align=\"center\">Patients with Negative staining for receptors of Growth Hormone</td></tr></thead><tbody><tr><td align=\"center\">AGE (MEAN/RANGE)</td><td align=\"center\">19/16–24 years</td><td align=\"center\">28,32/16–49 years</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Disease free and overall survival rate at 4, 48 years in patients with positive staining vs. patients with negative staining for receptors of Growth Hormone.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Patients with Positive staining for receptors of Growth Hormone<break/>(Frequency/Percent)</td><td align=\"center\">Patients with Negative staining for receptors of Growth Hormone<break/>(Frequency/Percent)</td></tr></thead><tbody><tr><td align=\"left\">NED<break/>(No Evident Disease)</td><td align=\"center\">0/0,0</td><td align=\"center\">18/72,0</td></tr><tr><td align=\"left\">Disease progression</td><td align=\"center\">2/50,0</td><td align=\"center\">1/4,0</td></tr><tr><td align=\"left\">DOD<break/>(Died On Disease)</td><td align=\"center\">2/50,0</td><td align=\"center\">6/24,0</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">4/100,0</td><td align=\"center\">25/100,0</td></tr></tbody></table></table-wrap>" ]

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[ "<title>Background</title>", "<p>The prevalence of Human Immunodeficiency Virus (HIV) is a measure of disease burden which is important in evaluating HIV prevention programmes and in designing new preventive strategies. Most estimates of HIV prevalence in developing countries have been based on sentinel surveillance of pregnant women [##UREF##0##1##]. HIV prevalence among pregnant women in antenatal clinics (ANC) closely approximates HIV prevalence in the adult population. ANC data is sometimes used to estimates HIV prevalence in general female population, instead of the general adult population (both males and females). This assumption is, however, unfounded [##REF##9792387##2##]. Women who adopt abstinence or correct and consistent condom use in response to HIV prevention programmes are less likely to be pregnant and equally less likely to contract HIV infection. As such, sentinel surveillance of pregnant women would over-estimate HIV prevalence in the general female population. On the other hand, there is some evidence that HIV-1 could impair fertility [##REF##9677188##3##,##REF##9439494##4##]. If HIV infected women are less likely to be pregnant because of impairment of their fertility by the HIV virus, the use of sentinel surveillance would under-estimate the HIV prevalence.</p>", "<p>Research comparing ANC estimates of HIV prevalence with HIV prevalence from population-based studies has shown that ANC figures closely estimate the actual population prevalence [##REF##16579863##5##, ####REF##16118609##6##, ##REF##9677172##7####9677172##7##]. However, the findings have not been consistent [##REF##16044012##8##]. Saphonn et al (2002) reported that although the prevalence of HIV in ANC was good for monitoring trends, it over-estimated HIV prevalence in rural Cambodia [##REF##11980815##9##]. On the contrary, Changalucha et al (2002) reported that the prevalence of HIV from ANC underestimated community HIV prevalence in Tanzania [##REF##11873011##10##]. Grassly, et al (2006) reviewed studies that have been carried out in different countries and compared estimates from ANC sentinel surveillance with population based estimates [##UREF##1##11##]. They found that in 12 out of 15 countries, HIV prevalence from ANC surveillance closely estimated the actual population prevalence. However, prevalence from ANC over-estimated community prevalence in Kenya and Rwanda, but underestimated the community prevalence in Zambia. Assuming that prevalence from ANC surveillance is representative of pregnant women, and that errors resulting from laboratory testing are minimal, one major explanation of inaccuracies in the estimates is the differences in the fertility rates between HIV positive and negative women. The accuracy of HIV estimates from ANC also depends on the contraceptive prevalence and ANC coverage.</p>", "<p>Improved methods for estimating HIV prevalence such as population-based surveys can provide useful information on HIV prevalence levels and distribution, and improve HIV estimates at national and regional levels [##REF##16735296##12##]. However, surveys may be costly especially when there are frequent and nation-wide.</p>", "<p>Research on ANC sentinel surveillance has mainly been focused on the role of behavioural data in ANC surveillance [##REF##15930840##13##], uses of prevalence data [##REF##15867497##14##], coverage [##REF##15608893##15##], assessing the trends of HIV prevalence [##REF##16581759##16##, ####REF##15330569##17##, ##REF##16284536##18####16284536##18##], comparison between HIV prevalence from ANC and community prevalence [##REF##11980815##9##,##REF##11873011##10##] and methods of adjustment of estimates from ANC surveillance [##UREF##1##11##,##REF##12556694##19##]. In addition some research has addressed the differences in fertility according to HIV status [##REF##9792387##2##,##REF##11114835##20##]. Glynn et al (2000) reported that the birth interval was reduced in HIV positive multiparous women compared to HIV-negative multiparous women in three African cities, namely Yaounde (Cameroon), Kisumu (Kenya) and Ndola (Zambia) [##REF##11114835##20##].</p>", "<p>Using sentinel data of pregnant women, the prevalence of HIV in Cameroon rose from 0.5% in 1987 to 10.8% in 2000 and then dropped to 7.3% in 2002 (Ministry of Public Health, 2001 and 2003) [##UREF##2##21##]. A population-based survey conducted in 2004 estimated the overall adult HIV prevalence in Cameroon to be 5.5% [##UREF##3##22##]. It is not clear whether this represents a true decrease in the prevalence of HIV or an artifact due to the differences in the two methods of data collection. Knowledge about the accuracy of sentinel prevalence as a proxy for national HIV prevalence is indispensable especially in a country facing rapid changes in the HIV prevalence. Differential prevalence of HIV in pregnant and non-pregnant women has been reported to be significantly associated with age, marital status, parity, schooling, and contraceptive use [##REF##11546948##23##].</p>", "<p>The purpose of our study was to compare the fertility rates of HIV-infected and HIV-uninfected women using population-based data in order to make recommendations on the appropriate adjustments when using sentinel data in designing and evaluating HIV prevention programmes in Cameroon.</p>" ]

[ "<title>Methods</title>", "<title>Design</title>", "<p>This study is a cross-sectional, population-based survey that uses data from the 2004 Cameroon Demographic and Health Survey (DHS) [##UREF##3##22##]. Women of reproductive age (15 to 49 years) were interviewed about their past and current reproductive history and tested for HIV after obtaining informed consent. Ethical approval was sought from the Cameroon Ministry of Health prior to the original survey [##UREF##3##22##].</p>", "<title>Population and sampling</title>", "<p>The survey used a two stage cluster sampling technique. The sample frame was a list of all Enumeration Areas (clusters) established by a General Census of Population and Housing in 2003. The first stage involved selecting 466 clusters (primary sampling units) with a probability proportional to the size, the size being the number of households in the cluster. The second stage involved the systematic sampling of households from the selected clusters. All women aged 15 to 49 years in the selected households were interviewed. The details of the study methods have been published elsewhere [##UREF##3##22##]. The current report included only sexually active women aged 15 to 49 years.</p>", "<title>Laboratory analysis</title>", "<p>The HIV status was screened by direct ELISA test (Genscreen Plus Version, BioRad Laboratories) and confirmed by a competitive ELISA test (Wellcozyme HIV-1 recombinant, ABBOTT, specific for HIV 1) and a rapid test (Determine, ABBOTT, specific for HIV 2). Only positive samples (with direct ELISA) were confirmed with competitive ELISA and only discordant samples were tested with Determine. All positive results in this survey were HIV-1: no HIV-2 was detected. For internal quality control, 5% of the HIV negative samples on direct ELISA were confirmed by competitive ELISA and Determine. Details of the testing algorithm has been published elsewhere [##UREF##3##22##].</p>", "<title>Definitions</title>", "<title>Fertility rates</title>", "<p>We define the general fertility rate in this study as the total number of births in the 36 months preceding the survey divided by the total number of woman-years of exposure during that period (36 months) multiplied by 1000 [##UREF##4##24##]. The age-specific fertility rate is the value of fertility rate for seven five-year groups (15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49 years). Woman-years of exposure is the sum of the number of months exposed in the five-year age bracket during the time period divided by 12.</p>", "<title>Relative inclusion ratio</title>", "<p>The relative inclusion ratio (RIR) is the ratio of the fertility rate in HIV positive women of reproductive age to the fertility rate of HIV negative women of reproductive age (15–49 years). Nicoll et al used this ratio to compare the relative fertility in HIV infected and uninfected women, so as to determine the relative likelihood of including these two groups of women in a seroprevalence survey in antenatal clinics [##REF##9792387##2##]. A ratio of 1.00 suggests a good estimation; a ratio of less than 1.00 indicates an underestimation and a ratio of more than 1.00 is an over-estimation of the HIV prevalence in the general population. ANC-based HIV prevalence can be adjusted for the effect of differential fertility rates by using the formula \"Adjusted HIV Prevalence = {Unadjusted HIV Prevalence}/{RIR}\". For example if the Unadjusted ANC-HIV Prevalence is 7.5% and RIR is 0.75, then the Adjusted HIV Prevalence is 7.5/0.75 or 10.0%.</p>", "<title>Wealth index</title>", "<p>Wealth index was used as our measure of socio-economic status. A score was given to each available household amenity based on the Health, Nutrition and Population/Poverty Thematic Group of the World Bank [##UREF##5##25##]. The total score for each household constituted the wealth index score for that household. Each woman was assigned the wealth index score of her household. From this score we distinguished three equal-sized classes of participants according to their wealth, based on percentiles (&lt;33.33 percentile, 33.33 to 66.66 percentile and &gt;66.66 percentile).</p>", "<title>Statistical Analyses</title>", "<p>All cases in the DHS data are given weights to adjust for differences in probability of selection and to adjust for the non-response in order to produce the proper representation. Individual weights were used for secondary data analysis in this study. Data were analyzed using SPSS version 13.0 for Windows. The results are reported as rates or ratios with their corresponding 95% confidence intervals (CI) and a p-value less than 0.05 was considered significant.</p>" ]

[ "<title>Results</title>", "<title>Characteristics of the study population</title>", "<p>Overall, 4493 sexually active women participated in the survey, giving a response rate of 92.1%. Of this number, 336 (7.5%) were HIV positive. Table ##TAB##0##1## presents the characteristics of the study population by HIV status. The mean age of women and the mean age at first intercourse were not significantly different between HIV positive and HIV negative women. The median parity was 2 (range 0 to 12) for HIV positive and 2 (range 0 to 14) for HIV negative women (p &lt; 0.001). The prevalence of HIV infection was significantly higher in wealthier and more educated women (p &lt; 0.001 for each). The prevalence also varied according to the marital status: 3.5% amongst women who have never married, 6.2% amongst currently married and 18.5% in divorced or widowed women (p &lt; 0.001).</p>", "<title>Fertility rates</title>", "<p>Table ##TAB##1##2## presents the age-specific fertility rates for rural areas. In the rural area, the fertility rate in both HIV positive and HIV negative women increased from 15–19 years to a maximum at 20–24 years and then decreased monotonically till the 35–49 years. However, in all age brackets the fertility rate was lower in the HIV positive compared to the HIV negative women. The overall fertility rate was 157.7 births per 1000 woman-years (95% CI 118.4 to 204.1) in HIV-infected women compared to 243.7 births per 1000 woman-years (95% CI 229.7 to 258.2) in uninfected women. Consequently, all relative inclusion ratios (RIRs) were lower than unity, and the overall RIR was 0.65 (95% CI 0.59 to 0.71).</p>", "<p>Table ##TAB##2##3## compares the age-specific fertility rates of HIV positive and HIV negative women in urban areas. Similar trends are observed as in rural areas: fertility is higher in HIV negative than in HIV positive women in all but for the 15–19 year age brackets. However, the peak of fertility in urban areas is reached at a later age (25–29 years) than in rural areas (20–24 years). Like in rural areas, the overall fertility is lower in HIV positive (102.7 births per 1000 woman-years, 95% CI 80.7 to 129.0) than in HIV negative women (124.0 births per 1000 woman-years, 95% CI 116.0 to 1312.4) and consequently the relative inclusion ratio is low (0.83, 95% CI 0.76 to 0.89).</p>", "<p>Overall, the fertility rate in all HIV positive women (rural and urban combined) was 118.7 births per 1000 woman-years (95% CI 98.4 to 142.0) compared to 171.3 births per 1000 woman-years (95% CI 164.5 to 178.2) for HIV negative women. Consequently, the summary RIR was 0.69 (95% CI 0.62 to 0.75). These values of fertility rates are self-weighted in terms of age and rural-urban differences because the sample represents all women of reproductive age in Cameroon.</p>" ]

[ "<title>Discussion</title>", "<p>This study compared fertility rates in HIV-infected and uninfected women of reproductive age using population-based data. Our findings indicate that fertility rates are lower in HIV infected women compared to uninfected women in Cameroon.</p>", "<p>Our finding of low fertility in HIV positive women is consistent with reports from other authors [##REF##9677188##3##,##REF##9439494##4##]. We found low fertility rates in HIV positive women of all age groups but for urban HIV-infected teenagers (that is, 15–19 year olds) who had a higher fertility rate than their corresponding HIV negative counterparts in cities. We could not find any suitable explanation to this finding. However, since the teenagers in rural areas were similar to other adult women in terms of their RIR, the cause is unlikely to be biological. We therefore attributed the high fertility in urban HIV-infected teenagers to differences in sexual and reproductive attitudes and practices. Monitoring of HIV epidemic via antenatal sentinel surveillance requires regular adjustments for many factors such as the differences in distribution of HIV across different age groups and different sub-populations, and differences in fertility rates between the infected and the uninfected women [##REF##9534742##26##]. Adjustment for fertility rates is an important factor because modest changes in fertility can have profound effects on the validity of estimates from pregnant women [##REF##8970470##27##]. Nicoll et al suggested that adjusting for the differences in fertility rates was sufficient in countries with overwhelming epidemics where the infection was transmitted through one source (heterosexual route) and many people are unaware of their HIV status [##REF##9792387##2##]. The authors argued that it might be possible to use summary RIR in wider geographical area such as Sub-Saharan Africa. Our study reports the summary RIR for Cameroon. Since the study population was a representative sample of the all Cameroon women of reproductive age, our RIR is self-weighted for regional and age differences. Eighty three percent (83%) of Cameroonian women attend at least one antenatal visit during pregnancy [##UREF##3##22##]. However, the differences in utilization of antenatal services by HIV-positive and HIV-negative women could introduce bias in the ANC-based prevalence estimates.</p>", "<p>Our study used fertility rates (number of births per 1000 woman years of exposure over 36 months) instead of live birth rates (number of live births per 100 woman years of exposure) as reported by Nicoll et al [##REF##9792387##2##], because we consider that all pregnant women are equally likely to be tested for HIV infection irrespective of the birth outcome (dead or live births). Desgrées du Loû et al used parity as a proxy for fertility rate [##REF##10465096##28##]. Parity is a cumulative measure of fertility and is insensitive to recent changes in fertility. In Zambia, ANC-based HIV estimates were found to substantially underestimate declines in HIV prevalence in the general population [##REF##18304262##29##]. This was partly explained by changes in fertility-related behaviours among young women.</p>", "<p>We found a summary RIR of 0.69 which is lower than that reported by other authors [##REF##9439494##4##,##REF##10465096##28##,##REF##12888411##30##]. Nicoll et al reported a summary RIR of 1.03 for London and 0.80 for women else where in England and Wales [##REF##9792387##2##]. The differences may be explained by socio-cultural differences of the two populations. Desgrées du Loû et al in Ivory Coast reported a summary RIR of 0.84 which is higher than our summary RIR [##REF##10465096##28##]. This may be explained by the fact they used parity instead of fertility rates and collected data from antenatal clinics which may not accurately represent the whole population. Gray et al [##REF##9439494##4##] is a population-based study in Uganda reported an unadjusted RIR of 0.78. Similarly, in another population-based study Terceira et al reported an unadjusted RIR of 0.78 in rural Zimbabwe [##REF##12888411##30##]. The RIRs of these two studies are closer to that reported in our study and this could be explained by the fact that they all used population-based data for analysis.</p>", "<p>The application of HIV seroprevalence from pregnant women to the whole female population needs adjustment for the differences in fertility rates among HIV-infected and HIV-uninfected women. Following earlier publications, fertility rate is now taken into consideration by the Joint United Nations Programme on HIV/AIDS (UNAIDS) when estimating and projecting HIV prevalences [##REF##16735293##31##].</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, fertility rates are lower in HIV infected women compared to uninfected sexually active women in Cameroon. The findings of this study support the use of summary RIR for the adjustment of HIV prevalence (among adult female population) obtained from sentinel surveillance in antenatal clinics. Continuous monitoring of the fertility rates in HIV positive and HIV negative women should be an adjunct to HIV serosurveillance because fertility rates are not static, but change over time.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Most estimates of HIV prevalence have been based on sentinel surveillance of pregnant women which may either under-estimate or over-estimate the actual prevalence in adult female population. One situation which can lead to either an underestimate or an overestimate of the actual HIV prevalence is where there is a significant difference in fertility rates between HIV-positive and HIV-negative women. Our aim was to compare the fertility rates of HIV-infected and HIV-uninfected women in Cameroon in order to make recommendations on the appropriate adjustments when using antenatal sentinel data to estimate HIV prevalence</p>", "<title>Methods</title>", "<p>Cross-sectional, population-based study using data from 4493 sexually active women aged15 to 49 years who participated in the 2004 Cameroon Demographic and Health Survey.</p>", "<title>Results</title>", "<p>In the rural area, the age-specific fertility rates in both HIV positive and HIV negative women increased from 15–19 years age bracket to a maximum at 20–24 years and then decreased monotonically till 35–49 years. Similar trends were observed in the urban area. The overall fertility rate for HIV positive women was 118.7 births per 1000 woman-years (95% Confidence Interval [CI] 98.4 to 142.0) compared to 171.3 births per 1000 woman-years (95% CI 164.5 to 178.2) for HIV negative women. The ratio of the fertility rate in HIV positive women to the fertility rate of HIV negative women (called the relative inclusion ratio) was 0.69 (95% CI 0.62 to 0.75).</p>", "<title>Conclusion</title>", "<p>Fertility rates are lower in HIV-positive than HIV-negative women in Cameroon. The findings of this study support the use of summary RIR for the adjustment of HIV prevalence (among adult female population) obtained from sentinel surveillance in antenatal clinics.</p>" ]

[ "<title>Conflict of interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>EJ Kongnyuy conceived the study, and analyzed the data, and had primary responsibility for writing this paper. CS Wiysonge assisted in the critical revision of the manuscript for important intellectual content.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2458/8/309/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors are grateful to Measure DHS for providing them with the 2004 Cameroon DHS data.</p>" ]

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[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Distribution of socio-demographic characteristics of Cameroonian women of reproductive age by HIV status</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold><italic>Characteristic</italic></bold></td><td align=\"center\"><bold><italic>HIV positive N (%)</italic></bold></td><td align=\"center\"><bold><italic>HIV negative N (%)</italic></bold></td><td align=\"center\"><bold><italic>p-value</italic></bold></td></tr></thead><tbody><tr><td align=\"left\">Mean age, years (SD)</td><td align=\"center\">29.3 (7.6)</td><td align=\"center\">28.9 (9.1)</td><td align=\"center\">0.304</td></tr><tr><td align=\"left\">Median age at first intercourse (range)</td><td align=\"center\">16(10–26)</td><td align=\"center\">16 (8–33)</td><td align=\"center\">0.167</td></tr><tr><td align=\"left\">Median parity (range)</td><td align=\"center\">2 (0–12)</td><td align=\"center\">2 (0–14)</td><td align=\"center\">&lt;0.001</td></tr><tr><td align=\"left\">Median number of living children (range)</td><td align=\"center\">2 (0–9)</td><td align=\"center\">2 (0–12)</td><td align=\"center\">&lt;0.001</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Place of residence</italic></bold></td><td/><td/><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">Urban</td><td align=\"center\">228 (9.5)</td><td align=\"center\">2183 (90.5)</td><td align=\"center\">&lt;0.001</td></tr><tr><td align=\"left\">Rural</td><td align=\"center\">108 (5.2)</td><td align=\"center\">1973 (94.8)</td><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Marital status</italic></bold></td><td/><td/><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">Never married</td><td align=\"center\">37 (6.5)</td><td align=\"center\">529 (93.5)</td><td align=\"center\">&lt;0.001</td></tr><tr><td align=\"left\">Currently married</td><td align=\"center\">218 (6.2)</td><td align=\"center\">3274 (93.8)</td><td/></tr><tr><td align=\"left\">Formerly married</td><td align=\"center\">80 (18.5)</td><td align=\"center\">353 (81.5)</td><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Education</italic></bold></td><td/><td/><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">No school</td><td align=\"center\">37 (3.5)</td><td align=\"center\">1035 (96.5)</td><td align=\"center\">&lt;0.001</td></tr><tr><td align=\"left\">Primary</td><td align=\"center\">143 (8.1)</td><td align=\"center\">1619 (91.9)</td><td/></tr><tr><td align=\"left\">Secondary/higher</td><td align=\"center\">155 (9.4)</td><td align=\"center\">1502 (90.6)</td><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Religion</italic></bold></td><td/><td/><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">Christians</td><td align=\"center\">276 (8.7)</td><td align=\"center\">2896 (91.3)</td><td align=\"center\">&lt;0.001</td></tr><tr><td align=\"left\">Muslims</td><td align=\"center\">45 (5.5)</td><td align=\"center\">778 (94.5)</td><td/></tr><tr><td align=\"left\">Others</td><td align=\"center\">15 (3.0)</td><td align=\"center\">483 (97.0)</td><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Wealth index</italic></bold></td><td/><td/><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">low</td><td align=\"center\">57 (3.8)</td><td align=\"center\">1441 (96.2)</td><td align=\"center\">&lt;0.001</td></tr><tr><td align=\"left\">middle</td><td align=\"center\">132 (8.8)</td><td align=\"center\">1368 (91.2)</td><td/></tr><tr><td align=\"left\">high</td><td align=\"center\">146 (9.8)</td><td align=\"center\">1350 (90.2)</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Fertility rates and relative inclusion ratios (RIR) for HIV positive and HIV negative women by age in the rural area of Cameroon, 2004.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"4\"><bold>HIV positive women</bold></td><td align=\"center\" colspan=\"4\"><bold>HIV negative women</bold></td></tr></thead><tbody><tr><td align=\"center\">Age <break/>bracket<break/>(years)</td><td align=\"center\">Number of <break/>births<break/><bold>(A1)</bold></td><td align=\"center\">Woman-years <break/>at risk<break/><bold>(B1)</bold></td><td align=\"center\">Fertility rate <break/>(95% CI)<break/><bold>C1 = (A1/B1)*1000</bold></td><td align=\"center\">Number of <break/>births<break/><bold>(A2)</bold></td><td align=\"center\">Woman-years <break/>at risk<break/><bold>(B2)</bold></td><td align=\"center\">Fertility rate <break/>(95% CI)<break/><bold>C2 = (A2/B2)*1000</bold></td><td align=\"center\">RIR <break/>(95% CI)<break/><bold>C1/C2</bold></td></tr><tr><td colspan=\"8\"><hr/></td></tr><tr><td align=\"center\">15–19</td><td align=\"center\">4</td><td align=\"center\">43.4</td><td align=\"center\">92.2 (30.3–209.3)</td><td align=\"center\">238</td><td align=\"center\">1518.8</td><td align=\"center\">156.7 (137.7–177.6)</td><td align=\"center\">0.59 (0.51–0.67)</td></tr><tr><td align=\"center\">20–24</td><td align=\"center\">14</td><td align=\"center\">72.0</td><td align=\"center\">194.4 (110.7–318.5)</td><td align=\"center\">347</td><td align=\"center\">1316.7</td><td align=\"center\">263.5 (236.9–292.4)</td><td align=\"center\">0.74 (0.68–0.79)</td></tr><tr><td align=\"center\">25–29</td><td align=\"center\">14</td><td align=\"center\">89.3</td><td align=\"center\">156.8 (89.2–256.8)</td><td align=\"center\">234</td><td align=\"center\">987.0</td><td align=\"center\">238.1 (209.0–237.7)</td><td align=\"center\">0.66 (0.60–0.72)</td></tr><tr><td align=\"center\">30–34</td><td align=\"center\">9</td><td align=\"center\">61.0</td><td align=\"center\">147.5 (72.0–270.8)</td><td align=\"center\">167</td><td align=\"center\">815.3</td><td align=\"center\">204.8 (175.5–237.7)</td><td align=\"center\">0.72 (0.66–0.78)</td></tr><tr><td align=\"center\">≥ 35</td><td align=\"center\">3</td><td align=\"center\">56.7</td><td align=\"center\">52.9 (13.5–144.0)</td><td align=\"center\">141</td><td align=\"center\">1506.4</td><td align=\"center\">94.3 (79.7–110.75)</td><td align=\"center\">0. 56 (0.46–0.67)</td></tr><tr><td colspan=\"8\"><hr/></td></tr><tr><td align=\"center\"><bold>Total</bold></td><td align=\"center\">44</td><td align=\"center\">279.0</td><td align=\"center\">157.7 (118.4–204.1)</td><td align=\"center\">1127</td><td align=\"center\">4625.4</td><td align=\"center\">243.7 (229.7–258.2)</td><td align=\"center\">0.65 (0.59–0.71)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Fertility rates and relative inclusion ratios (RIR) for HIV positive and HIV negative women by age in the urban area of Cameroon, 2004.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"4\"><bold>HIV positive women</bold></td><td align=\"center\" colspan=\"4\"><bold>HIV negative women</bold></td></tr></thead><tbody><tr><td align=\"center\">Age <break/>bracket<break/>(years)</td><td align=\"center\">Number of <break/>births<break/><bold>(A1)</bold></td><td align=\"center\">Woman-years <break/>at risk<break/><bold>(B1)</bold></td><td align=\"center\">Fertility rate <break/>(95% CI)<break/><bold>C1 = (A1/B1)*1000</bold></td><td align=\"center\">Number of <break/>births<break/><bold>(A2)</bold></td><td align=\"center\">Woman-years <break/>at risk<break/><bold>(B2)</bold></td><td align=\"center\">Fertility rate <break/>(95% CI)<break/><bold>C2 = (A2/B2)*1000</bold></td><td align=\"center\">RIR <break/>(95% CI)<break/><bold>C1/C2</bold></td></tr><tr><td colspan=\"8\"><hr/></td></tr><tr><td align=\"center\">15–19</td><td align=\"center\">14</td><td align=\"center\">84.4</td><td align=\"center\">165.8 (98.1–257.9)</td><td align=\"center\">196</td><td align=\"center\">2139.9</td><td align=\"center\">91.6 (79.4–105.1)</td><td align=\"center\">1.81 (1.59–2.08)</td></tr><tr><td align=\"center\">20–24</td><td align=\"center\">20</td><td align=\"center\">177.0</td><td align=\"center\">113.0 (71.0–171.4)</td><td align=\"center\">240</td><td align=\"center\">1491.0</td><td align=\"center\">161.0 (141.6–182.3)</td><td align=\"center\">0.70 (0.63–0.77)</td></tr><tr><td align=\"center\">25–29</td><td align=\"center\">25</td><td align=\"center\">185.3</td><td align=\"center\">134.9 (89.5–196.0)</td><td align=\"center\">219</td><td align=\"center\">1151.6</td><td align=\"center\">190.2 (166.2–216.6)</td><td align=\"center\">0.71 (0.64–0.77)</td></tr><tr><td align=\"center\">30–34</td><td align=\"center\">6</td><td align=\"center\">104.2</td><td align=\"center\">57.6 (23.3–119.8)</td><td align=\"center\">140</td><td align=\"center\">1050.4</td><td align=\"center\">133.3 (113.8–155.4)</td><td align=\"center\">0.44 (0.35–0.52)</td></tr><tr><td align=\"center\">≥ 35</td><td align=\"center\">5</td><td align=\"center\">130.6</td><td align=\"center\">38.3 (14.2–83.2)</td><td align=\"center\">83</td><td align=\"center\">1470.8</td><td align=\"center\">56.4 (45.3–69.7)</td><td align=\"center\">0.68 (0.55–0.79)</td></tr><tr><td colspan=\"8\"><hr/></td></tr><tr><td align=\"center\"><bold>Total</bold></td><td align=\"center\">70</td><td align=\"center\">681.5</td><td align=\"center\">102.7 (80.7–129.0)</td><td align=\"center\">878</td><td align=\"center\">7079.7</td><td align=\"center\">124.0 (116.0–1312.4)</td><td align=\"center\">0.83 (0.76–0.89)</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>HIV = Human Immunodeficiency Virus</p></table-wrap-foot>", "<table-wrap-foot><p>CI = confidence interval; RIR = relative inclusion ratio; HIV = Human Immunodeficiency Virus</p></table-wrap-foot>", "<table-wrap-foot><p>CI = confidence interval; RIR = relative inclusion ratio; HIV = Human Immunodeficiency Virus</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Myocardial damage can be caused by multiple conditions including ischemia, trauma, toxins or inflammation. Cardiac-specific Troponin I (cTnI) is currently the most sensitive and specific marker of myocardial cell damage in the dog [##REF##9704624##1##,##REF##16594583##2##]. Cardiac-specific Troponin I is a protein that is expressed at high concentrations only in the myocardium. When cardiac myocytes are damaged, cTnI leaks into the bloodstream and can be detected in serum [##REF##9704624##1##,##REF##12164535##3##]. In normal dogs serum concentrations of cTnI are low or, most often, undetectable [##REF##11596740##4##].</p>", "<p>Canine pyometra is a common disease in countries where routine spaying of young dogs is not common practice. The condition may cause systemic inflammation, which may potentially damage multiple organs in the body, including the heart [##UREF##0##5##]. The presence of systemic inflammatory response syndrome (SIRS) may be predicted by certain clinical and laboratory parameters [##REF##9381665##6##]. The systemic inflammation can, if not successfully treated, progress to multiple organ dysfunction syndrome (MODS) and death [##REF##11727331##7##].</p>", "<p>The safest and most effective treatment for canine pyometra is ovariohysterectomy [##UREF##1##8##]. However, anaesthesia and surgery may cause myocardial ischemia with subsequent myocardial cell damage, especially in individuals with systemic inflammation and impaired circulation [##UREF##2##9##]. In humans, the occurrence of perioperative ECG abnormalities and \"silent myocardial ischemia\" is well recognised [##REF##2404426##10##]. One study documented myocardial ischemia 12 hours postoperatively (as measured by increased concentrations of cTnI) in healthy women undergoing caesarean section [##REF##11703237##11##]. It has been demonstrated that perioperative elevations of cTnI concentrations were associated with major cardiac complications up to 1 year after surgery [##REF##15023100##12##].</p>", "<p>Thus, myocardial injury is a potential cause of increased morbidity and mortality in dogs with pyometra before, during and after surgery. However, there are no reports concerning the occurrence and significance of perioperative myocardial damage in dogs undergoing anaesthesia irrespective of the underlying condition. The presence of myocardial damage may often be overlooked and difficult to detect when suspected if it does not lead to compromised cardiac function, arrhythmias or regional abnormal ventricular motion. Analysis of the serum concentration of cTnI can reveal both clinical and subclinical damage to the myocytes [##UREF##2##9##,##REF##9385123##13##].</p>", "<p>The aims of the present study were 1) to evaluate the occurrence of myocardial cell damage as indicated by increased serum concentrations of cTnI in dogs with pyometra and relate these to the severity of systemic inflammation and other clinical variables and 2) to evaluate the change in cTnI concentrations after anaesthesia and surgery.</p>" ]

[ "<title>Materials and methods</title>", "<p>This study was approved by the Uppsala County local ethical committee.</p>", "<title>Dogs</title>", "<p>Forty-six female dogs diagnosed with pyometra were recruited to the study at the Department of Small Animal Clinical Sciences, Swedish University of Agricultural Sciences (SLU), Uppsala between January 2004 and December 2005. At the time of arrival, a physical examination was performed on dogs presenting with a history compatible with pyometra (polyuria, polydipsia, anorexia, vomiting, lethargy, fever, vulvar discharge, recent oestrus). Blood samples analysed for complete blood count (CBC) and cardiac-specific Troponin I (cTnI) were collected and radiography and/or ultrasonography of the abdomen was performed, and dogs diagnosed with pyometra were included in the study. Dogs whose owners did not agree to ovariohysterectomy, and dogs with clinical or laboratory findings indicative of other organ-related or systemic disease were excluded from the study. Recorded data obtained from the case history and physical examination included age, weight, rectal temperature, heart rate and respiratory rate. A second serum sample for analysis of cTnI was collected 12–24 hours after surgery.</p>", "<p>Fifteen female dogs undergoing surgery for neutering (n = 12) or tumour mammae (n = 3) were recruited as control dogs. None of these dogs had a history or clinical signs indicative of other disease, and in the case of tumour mammae thoracic radiographs had shown that the dogs were free of visible pulmonary metastases. A physical examination was performed on all of these control dogs. Serum for analysis of cTnI was collected at presentation and 12–24 hours after surgery.</p>", "<title>Diagnosis of pyometra</title>", "<p>Abdominal radiography and/or ultrasonography were performed on all dogs. The radiological examination included left and ventrodorsal projections of the entire abdomen using the standard procedure at the Section for Diagnostic Imaging, Department of Clinical Sciences, SLU, Sweden. The diagnosis of pyometra was established when an enlarged (and, if ultrasonography was performed, fluid-filled) uterus was found, as previously described [##REF##15182288##14##,##REF##1440600##15##]. The diagnosis was confirmed by the presence of an enlarged uterus containing pus during the surgical procedure.</p>", "<title>Diagnosis of inflammatory response syndrome (SIRS)</title>", "<p>Dogs were grouped into two groups; SIRS-positive and SIRS-negative. Dogs that fulfilled two or more of the following criteria were considered SIRS-positive: 1) Resting heart rate &gt; 120/min; 2) respiratory rate &gt; 20/min; 3) rectal temperature above 39.2°C or below 38.1°C; and 4) total white blood cell count (WBC) above 16 × 10⁹or below 6 × 10⁹cells per l blood or more than 3% band neutrophils [##REF##9381665##6##].</p>", "<title>Sample handling</title>", "<p>Blood samples for hematological and biochemical analysis were taken from the distal cephalic vein into EDTA and serum Vacutainer^®tubes (Becton &amp; Dickinson, Meylon Cedex, France) and transported to the laboratory for analysis within one hour of collection.</p>", "<title>Ovariohysterectomy</title>", "<p>The dogs were premedicated with glycopyrrulate, methadone, acepromazine and carprofen. Anaesthesia was induced with propofol and maintained with isoflurane. In dogs that were considered an anaesthetic risk because of a severely compromised general condition (n = 5) anaesthesia was induced with diazepam and ketaminol and maintained with isoflurane. Ovariohysterectomy was performed using a standard ventral midline approach [##UREF##3##16##]. The procedure was performed within 24 hours in all dogs except one. The owners wished to delay surgery until after the weekend in this dog because of a good general condition. All dogs were treated with iv fluids before, during and after surgery. Approximately half of the dogs were treated with antibiotics perioperatively. All dogs received preoperative and postoperative opioids until discharge. No medications were given before the preoperative blood samples were collected.</p>", "<title>Haematology, cTnI analysis and blood biochemistry</title>", "<p>The CBC was performed using Abbott CELL-DYN 3500 (Abbott Diagnostics, Illinois, USA) in combination with manual microscopy in all cases except eight, where the haematology was performed using the QBC Vet Autoread (IDEXX Laboratories, Maine, USA). In these eight cases the CBC was performed in an emergency situation when the QBC Vet Autoread was the only option for analysis of haematology.</p>", "<p>Troponin I was analyzed using a commercially available method (IMMULITE Troponin I, Diagnostic Products Corporation, Los Angeles, USA). This is an immunometric method where antibodies raised against human cTnI bind to existing cTnI in the sample. The lower limit of detection for the cTnI assay is 0,2 μg/l. The possibility of using this method for detection of cTnI in serum samples from dogs was investigated in an earlier study [##REF##18786242##17##,##REF##17328800##18##]. The upper reference limit for normal dogs in our laboratory was 0.2 μg/l.</p>", "<p>Adjunct serum biochemical analyses were not included in the study protocol but were performed in some cases, preoperatively (Table ##TAB##0##1##). ALT, ALP, creatinine and glucose were analyzed using a commercially available method (IDEXX VET TEST Chemistry Analyzer, IDEXX Laboratories, Maine, USA).</p>", "<title>Statistics</title>", "<p>All statistical analyses were performed using a statistical programme (JMP v 5.0, SAS, Cary, USA). Serum concentrations of cTnI from SIRS-positive and SIRS-negative dogs were compared using Wilcoxon Rank Sum Test.</p>", "<p>The association between cTnI concentrations and haematological and blood-biochemical variables, and variables obtained from the physical examination were evaluated by a Spearman rank correlation. Values are reported as the median and interquartile range (IQR). The significance level was set at p &lt; 0.05.</p>" ]

[ "<title>Results</title>", "<title>Dogs with pyometra</title>", "<p>The median age of the 46 dogs with pyometra at presentation was 8.5 years (IQR 7.5–10) and median body weight 29 kg (IQR 9–32). The group comprised 8 mongrel dogs and 38 dogs of 22 different breeds.</p>", "<title>Control dogs</title>", "<p>The median age of the dogs in the control group was 5 years (IQR 2–8). Median body weight was 27 kg (IQR 20–32). The group comprised 3 mongrel dogs and 12 dogs of 12 different breeds.</p>", "<title>Preoperative cTnI-concentrations</title>", "<p>All of the dogs in the control group had undetectable preoperative cTnI concentrations (Table ##TAB##1##2##). Of the 46 dogs with pyometra, 13 (28%) had increased preoperative cTnI concentrations (range 0.3–13.2 μg/l) (Table ##TAB##2##3##).</p>", "<title>Postoperative cTnI concentrations</title>", "<p>Two (13%) of the control dogs had increased cTnI concentrations the day after surgery (0.4 and 3 μg/l, respectively) (Table ##TAB##1##2##). Eighteen (39%) of the pyometra dogs had increased postoperative cTnI concentrations (range 0.3–6.4 μg/l) (Table ##TAB##2##3##). Of the 13 dogs with increased preoperative cTnI concentrations, 8 had lower, 4 had increased, and one had unchanged cTnI concentrations after surgery. In seven dogs with nondetectable cTnI concentrations at presentation, increased levels were demonstrated postsurgically.</p>", "<p>Thus, in total, 20 dogs (43%) with pyometra had increased cTnI concentrations before or after surgery, and 7 dogs had pre- or postoperative cTnI concentrations of 1.0 μg/l or higher.</p>", "<title>Preoperative blood biochemistry</title>", "<p>None of the 27 dogs that had serum ALAT concentration analysed had a concentration exceeding the upper reference range. Similarly, only one out of the 33 dogs that had serum creatinine concentration analysed had a concentration exceeding the upper reference range for creatinine. Finally, 6 of the 23 dogs that had serum ALP concentration and 6 out of the 20 dogs that had serum glucose concentration analysed had a concentration exceeding the upper reference range.</p>", "<title>SIRS groups and outcome</title>", "<p>Eleven of the dogs with pyometra fulfilled all four SIRS criteria. Ten of the dogs fulfilled three criteria, 16 dogs fulfilled two criteria and 6 dogs one criterion for SIRS. Three dogs did not fulfil any of the SIRS criteria. Consequently the SIRS-positive group (two or more positive criteria) consisted of 37 dogs (80%) and the SIRS-negative group of 9 dogs (20%). All dogs except four were discharged within 48 hours of surgery. Reasons for delaying discharge in four dogs were resuturing of skin wound (n = 1), reduced general condition postoperatively (n = 1) and owner preference (n = 2). All dogs in the study recovered and survived the postoperative period (10 days).</p>", "<title>Comparison of cTnI concentrations and clinical parameters</title>", "<p>When the SIRS-positive and SIRS-negative groups were compared (both before and after surgery) there was no statistically significant difference in cTnI concentrations between the groups. The only significant association between the studied laboratory or clinical variables and cTnI concentration was preoperative percentage band neutrophils (PBN) and postoperative cTnI concentration (p = 0.016) (Figure ##FIG##0##1##). The preoperative PBN tended to be correlated with preoperative cTnI concentrations (p = 0.059).</p>" ]

[ "<title>Discussion</title>", "<p>In total, 20 out of 46 dogs (43%) with pyometra had increased concentrations of cTnI at some time during the study, which indicates that increased cTnI concentrations are common during the perioperative period in dogs with pyometra. This finding is supported by the results of our previous study in which increased preoperative cTnI concentrations were documented in 12% of 58 dogs with pyometra [##REF##17328800##18##]. The present study is different from our previous one because, to our knowledge, this is the first study that documents both pre-and postoperative measurements of cTnI concentrations in dogs with pyometra. It should be pointed out that only 7 of the 20 dogs with increased concentrations of cTnI (10 out of the total 31 samples with increased concentrations) had values ≥ 1.0 μg/l and none of the dogs measured higher than 13.2 μg/ml, indicating that cTnI concentrations were mildly increased in the majority of cases. The lower limit of detection of cTnI in our assay is 0,2 μg/l. It is possible that the upper reference range for cTnI in dogs is lower than 0,2 μg/l and that a greater number of dogs would have had increased concentrations of cTnI if we had used a more sensitive assay, as recently described [##REF##17890441##19##].</p>", "<p>The clinical significance of mild increases in cTnI concentrations is currently unknown. Studies have shown an association between the degree of increase in cTnI concentrations and the size of myocardial infarctions in dogs [##REF##9704624##1##,##REF##15234222##20##]. However, it has been suggested that reduced renal function can cause an increase in cTnI in the absence of myocardial cell damage [##UREF##4##21##]. Most of the dogs in our study had preoperative creatinine concentrations determined. However, in 5 of the dogs with increased cTnI-concentrations the preoperative creatinine concentration was not known. Although alternative causes for mildly increased cTnI concentrations are possible [##UREF##4##21##], it is likely that the degree of increase of cTnI concentration in serum provides an estimate of the extent of myocardial damage in our dogs.</p>", "<p>Detection of damaged myocardium may be useful for the clinician when managing a dog with pyometra because its presence could indicate that the dog might be at risk for adverse events such as ventricular arrythmias or unexpected death. Early identification of dogs at risk allows the clinician to take actions to avoid adverse cardiac events by monitoring the dog during the perioperative period and intervene early when indicated. Although none of the dogs had a history of known heart disease, one limitation of the study is that we did not rule out underlying subclinical cardiac disease in any of the participating dogs.</p>", "<p>A possible cause for the increased cTnI concentrations could be the presence of endotoxins into the circulation. Elevated plasma endotoxin concentrations have been documented in female dogs with pyometra [##REF##9360470##22##, ####REF##9853312##23##, ##REF##16722306##24####16722306##24##] and is thought to be responsible for some of the clinical signs [##REF##9853312##23##]. In most cases of canine pyometra, <italic>Escherichia coli (E. coli) </italic>can be cultured from the uterus [##REF##9360470##22##,##REF##9885130##25##]. Like other Gram negative bacteria, <italic>E. coli </italic>can release endotoxin during growth or when they die [##UREF##5##26##]. Endotoxins bind to receptors on cell-membranes and induce inflammation and cytokine production [##UREF##5##26##]. Depending on the extent of endotoxin release, the result is varying manifestations of inflammation, from local to systemic, and cellular damage, which could potentially affect myocardial cells and thereby result in elevated serum concentrations of cTnI. Indeed, SIRS has been documented to be part of the clinical picture in 57% of 53 dogs [##UREF##6##27##] and 53% of 59 dogs [##REF##17328800##18##] with pyometra. In our study, 37 out of 46 dogs (80%) fulfilled the chosen criteria for SIRS. However, we could not find an association between a diagnosis of SIRS and increased cTnI concentrations. These results are in accordance with our previous findings [##REF##17328800##18##]. The diagnosis of SIRS is difficult because some of the clinical parameters used to determine its presence (body temperature, respiratory rate, heart rate, neutrophil count) are influenced by the excitement and stress caused by the visit to the animal hospital and by the disease as such. This influence would lead to a falsely high number of SIRS-positive dogs in the study population. The criteria for a positive diagnosis of SIRS used in this study were chosen to minimize the risk of failure to identify SIRS, thereby minimizing the risk of the serious consequences to the patient that can arise when this diagnosis is missed [##REF##9381665##6##]. With a high sensitivity of 97% there is a concurrent low specificity (64%), explaining the risk of false positive diagnoses of SIRS in our population of dogs. It is possible that a correlation between cTnI concentrations and SIRS could be found if we could more reliably diagnose the presence of SIRS in an individual animal. C-reactive protein has been found to be a valuable marker of SIRS in dogs with pyometra and may be of value in future studies of dogs suspected to suffer from SIRS [##REF##15347619##28##].</p>", "<p>As a group, there was no significant change in the cTnI concentrations before and after surgery in the 46 dogs with pyometra. However, this lack of significance does not mean that changes have not occurred in individual dogs. Indeed, in 8 dogs the cTnI concentrations decreased after surgery and in 11 dogs the concentrations increased. A possible explanation for the decreased concentrations on the day after surgery could be the normal metabolism and elimination of cTnI from the body. The half-life of cTnI is reported to be 120 minutes [##UREF##2##9##]. One explanation for increased concentration of cTnI postsurgically could be that anaesthesia and surgery may cause further damage to the myocytes, in particular in individuals with systemic inflammation and impaired circulation, because of potential perioperative myocardial hypoxia. This phenomenon is well recognised in humans [##REF##2404426##10##,##REF##2247116##29##,##REF##15479316##30##] but has, to our knowledge, not been shown to occur in dogs. Another possible reason for myocardial injury during anaesthesia could be direct toxic effects of the anaesthetic agents. Ongoing myocyte damage because of SIRS or inflammation induced by systemically released endotoxin could also contribute to elevated concentrations of cTnI postsurgically. Two of the healthy control dogs in our study (which all had undetectable concentrations of cTnI preoperatively) had increased concentrations of cTnI after surgery. This could possibly be explained by the aforementioned perioperative hypoxia (or toxicity) and subsequent myocardial cell damage.</p>", "<p>The only studied variable that was significantly associated with cTnI concentrations was preoperative percentage of band neutrophils and postoperative cTnI concentrations (p = 0.016). The preoperative PBN and preoperative cTnI concentrations tended to be correlated (p = 0.059). A high PBN count in peripheral blood is considered a sign of a high demand of neutrophils in the tissues during inflammation [##UREF##7##31##]. The percentage of band neutrophils is, as mentioned earlier, one of the criteria used for the diagnosis of SIRS. Thus, the above-mentioned correlation might reflect myocyte damage caused by systemic inflammation.</p>" ]

[ "<title>Conclusion</title>", "<p>Mild to moderate increases in cTnI appears to be common in dogs with pyometra before and after surgery, but the clinical importance of this finding is uncertain. None of the studied clinical variables (including SIRS) were found to reliably predict increased preoperative cTnI concentrations. Because of the pre- and postoperative variation in cTnI concentrations it was not possible to identify a negative effect of anaesthesia and surgery on myocardial cell integrity. Consequently, analysing serum cTnI concentrations from dogs with pyometra could possibly help detect subclinical myocardial damage. Further studies are needed to investigate whether increased concentrations of cTnI are associated with a higher risk of perioperative complications.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Canine pyometra is a common disease in countries where routine spaying of young dogs is not common practice. This disease is known to lead to systemic inflammation potentially affecting multiple organs in the body, including the heart. Cardiac-specific Troponin I (cTnI) is a sensitive marker of myocardial cell damage, which can result from ischemia, trauma, toxins or inflammation. Dogs with pyometra are also exposed to anaesthesia which can potentially result in myocardial cell damage. The aims of the study were 1) to evaluate the occurrence of myocardial cell damage as indicated by increased serum concentrations of cTnI in dogs with pyometra and relate these to presence of systemic inflammation and 2) to evaluate the change in cTnI-concentrations after anaesthesia and surgery.</p>", "<title>Methods</title>", "<p>Serum cTnI concentration was measured preoperatively and one day after surgery in 46 female dogs with pyometra and 15 female dogs that underwent surgery for other reasons (ovariohysterectomy and mammary tumours).</p>", "<title>Results</title>", "<p>Forty-six female dogs of different breeds diagnosed with pyometra were included. The dogs had a median age of 8.5 years (IQR 7.5–10) and a median weight of 29 kg (IQR 9–32). Of the 46 dogs, 37 (80%) fulfilled the chosen criteria for systemic inflammatory response syndrome (SIRS) at inclusion. Thirteen (28%) of the dogs had increased cTnI concentrations (&gt; 0.2 μg/l) before surgery and 18 (39%) had increased cTnI-concentrations the day after surgery. The cTnI concentrations in the 13 dogs with increased preoperative cTnI concentrations decreased in 8 dogs, increased in 4 dogs, and was unchanged in one dog. Seven dogs with nondetectable preoperative cTnI concentrations had increased postoperative concentrations. The only significant association between the studied laboratory or clinical variables (including SIRS) and cTnI concentration was preoperative percentage band neutrophils (PBN) and postoperative cTnI concentration (P = 0.016). In total, 20 dogs (43%) had increased pre- or postoperative cTnI concentrations. Seven dogs (15%) had pre-or postoperative concentrations of cTnI of 1.0 μg/l or higher.</p>", "<title>Conclusion</title>", "<p>Mild to moderate increases in cTnI appears to be common in dogs with pyometra before and after surgery, but the clinical importance of this finding is uncertain. None of the studied clinical variables were found to reliably predict increased preoperative cTnI concentrations. Because of the pre- and postoperative variation in cTnI concentrations, it was not possible to identify a negative effect of anaesthesia and surgery on myocardial cell integrity.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>LP participated in the design of the study and carried out the practical recruitment of cases. She also drafted the manuscript. RH participated in the design of the study and the manuscript writing. JH participated in the design of the study and performed the statistical analysis. He also parcipitated in the writing of the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors wish to thank the Thure F and Karin Forsberg Foundation for funding our study, the technical staff at the Department of Small Animal Clinical Sciences for help with the collection of blood samples and Åsa Karlsson at the Section for Clinical Chemistry for help with the analyses of cTnI.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Scatterplot of postsurgical concentrations of cTnI by percentage band neutrophils in peripheral blood at presentation in 38 dogs (values missing in 8 dogs).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Median and interquartile ranges (IQR) of preoperative plasma biochemical variables (ALT, ALP, creatinine and glucose concentrations) in the study population of dogs with pyometra.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Biochemical variable</bold></td><td align=\"center\"><bold>Median</bold></td><td align=\"center\"><bold>IQR</bold></td><td align=\"center\"><bold>Reference interval</bold></td></tr></thead><tbody><tr><td align=\"center\"><bold>ALT </bold>(u/l) (n = 27)</td><td align=\"center\">16</td><td align=\"center\">10–36</td><td align=\"center\">10–100</td></tr><tr><td align=\"center\"><bold>ALP </bold>(u/l) (n = 23)</td><td align=\"center\">162</td><td align=\"center\">87–229</td><td align=\"center\">23–212</td></tr><tr><td align=\"center\"><bold>Creatinine </bold>(μmol/l) (n = 33)</td><td align=\"center\">82</td><td align=\"center\">67–100</td><td align=\"center\">44–159</td></tr><tr><td align=\"center\"><bold>Glucose </bold>(mmol/l) (n = 20)</td><td align=\"center\">6.8</td><td align=\"center\">5.9–7.1</td><td align=\"center\">4.3–6.9</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Age, weight, reason for surgery (n = neutering, tm = tumor mammae) and pre-and post-operative serum cTnI-concentrations in 15 female dogs undergoing elective surgery (control group).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Case No</td><td align=\"center\">Age (years)</td><td align=\"center\">Weight (kg)</td><td align=\"center\">Reason for surgery</td><td align=\"center\">Pre-operative cTnI (μg/l)</td><td align=\"center\">Post-operative cTnI (μg/l)</td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">9</td><td align=\"center\">28</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">2</td><td align=\"center\">4</td><td align=\"center\">38</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">3</td><td align=\"center\">6</td><td align=\"center\">22</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">4</td><td align=\"center\">4</td><td align=\"center\">8</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.4</td></tr><tr><td align=\"center\">5</td><td align=\"center\">5</td><td align=\"center\">20</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">6</td><td align=\"center\">9</td><td align=\"center\">31</td><td align=\"center\">tm</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">7</td><td align=\"center\">8</td><td align=\"center\">18</td><td align=\"center\">tm</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">8</td><td align=\"center\">7</td><td align=\"center\">22</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">9</td><td align=\"center\">9</td><td align=\"center\">10</td><td align=\"center\">tm</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">10</td><td align=\"center\">4</td><td align=\"center\">35</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">3.0</td></tr><tr><td align=\"center\">11</td><td align=\"center\">5</td><td align=\"center\">32</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">12</td><td align=\"center\">1</td><td align=\"center\">57</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">13</td><td align=\"center\">1</td><td align=\"center\">26</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">14</td><td align=\"center\">1</td><td align=\"center\">27</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr><tr><td align=\"center\">15</td><td align=\"center\">2</td><td align=\"center\">30</td><td align=\"center\">n</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Weight, age, white blood cell count (WBC), percentage band neutrophils (PBN), heart rate (HR), rectal temperature, respiratory rate (RR) above 20/min or not, pre-and post-operative cTnI-concentrations for 46 dogs with pyometra. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Case No</td><td align=\"center\">Weight (kg)</td><td align=\"center\">Age (years)</td><td align=\"center\">WBC (×109/ml)</td><td align=\"center\">Neutrophils (×109/ml)</td><td align=\"center\">PBN (%)</td><td align=\"center\">HR (bpm)</td><td align=\"center\">Temp (°C)</td><td align=\"center\">RR &gt;20</td><td align=\"center\">Pre-op cTnI (μg/l)</td><td align=\"center\">Post-op cTnI (μg/l)</td><td align=\"center\">SIRS-pos</td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">32</td><td align=\"center\">6.5</td><td align=\"center\">32</td><td align=\"center\">1.8</td><td align=\"center\">72</td><td align=\"center\">120</td><td align=\"center\">39.1</td><td align=\"center\">Y</td><td align=\"center\">13.2</td><td align=\"center\">6.4</td><td align=\"center\">+</td></tr><tr><td align=\"center\">2</td><td align=\"center\">7</td><td align=\"center\">11.5</td><td align=\"center\">7</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">128</td><td align=\"center\">40.4</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">3</td><td align=\"center\">11</td><td align=\"center\">7</td><td align=\"center\">11.4</td><td align=\"center\">5.9</td><td align=\"center\">0</td><td align=\"center\">80</td><td align=\"center\">38.6</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr><tr><td align=\"center\">4</td><td align=\"center\">28</td><td align=\"center\">11</td><td align=\"center\">28</td><td align=\"center\">6.9</td><td align=\"center\">89</td><td align=\"center\">104</td><td align=\"center\">39.6</td><td align=\"center\">-</td><td align=\"center\">0.7</td><td align=\"center\">0.7</td><td align=\"center\">+</td></tr><tr><td align=\"center\">5</td><td align=\"center\">11</td><td align=\"center\">8</td><td align=\"center\">11.3</td><td align=\"center\">10.9</td><td align=\"center\">12</td><td align=\"center\">-</td><td align=\"center\">39.9</td><td align=\"center\">-</td><td align=\"center\">1.2</td><td align=\"center\">0.4</td><td align=\"center\">+</td></tr><tr><td align=\"center\">6</td><td align=\"center\">33</td><td align=\"center\">10</td><td align=\"center\">33.5</td><td align=\"center\">9.7</td><td align=\"center\">0</td><td align=\"center\">110</td><td align=\"center\">38.8</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.3</td><td align=\"center\">-</td></tr><tr><td align=\"center\">7</td><td align=\"center\">29</td><td align=\"center\">3.5</td><td align=\"center\">29</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">140</td><td align=\"center\">39.3</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">8</td><td align=\"center\">30</td><td align=\"center\">8.5</td><td align=\"center\">30</td><td align=\"center\">15.5</td><td align=\"center\">43</td><td align=\"center\">144</td><td align=\"center\">39.9</td><td align=\"center\">N</td><td align=\"center\">2.0</td><td align=\"center\">1.0</td><td align=\"center\">+</td></tr><tr><td align=\"center\">9</td><td align=\"center\">12</td><td align=\"center\">13</td><td align=\"center\">12</td><td align=\"center\">26.8</td><td align=\"center\">91</td><td align=\"center\">-</td><td align=\"center\">38.3</td><td align=\"center\">N</td><td align=\"center\">0.3</td><td align=\"center\">0.4</td><td align=\"center\">+</td></tr><tr><td align=\"center\">10</td><td align=\"center\">10</td><td align=\"center\">12.5</td><td align=\"center\">9.7</td><td align=\"center\">1.6</td><td align=\"center\">12</td><td align=\"center\">134</td><td align=\"center\">39.9</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">11</td><td align=\"center\">27</td><td align=\"center\">7.5</td><td align=\"center\">26.6</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">128</td><td align=\"center\">39.4</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.4</td><td align=\"center\">+</td></tr><tr><td align=\"center\">12</td><td align=\"center\">35</td><td align=\"center\">7.5</td><td align=\"center\">35</td><td align=\"center\">14.2</td><td align=\"center\">0</td><td align=\"center\">140</td><td align=\"center\">39.2</td><td align=\"center\">Y</td><td align=\"center\">1.0</td><td align=\"center\">0.7</td><td align=\"center\">+</td></tr><tr><td align=\"center\">13</td><td align=\"center\">20</td><td align=\"center\">8</td><td align=\"center\">20.2</td><td align=\"center\">18.4</td><td align=\"center\">16</td><td align=\"center\">210</td><td align=\"center\">39.9</td><td align=\"center\">-</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">14</td><td align=\"center\">22</td><td align=\"center\">9.5</td><td align=\"center\">22.8</td><td align=\"center\">37.5</td><td align=\"center\">13</td><td align=\"center\">138</td><td align=\"center\">39.8</td><td align=\"center\">Y</td><td align=\"center\">0.3</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">15</td><td align=\"center\">9</td><td align=\"center\">12</td><td align=\"center\">9</td><td align=\"center\">23.6</td><td align=\"center\">94</td><td align=\"center\">100</td><td align=\"center\">40.9</td><td align=\"center\">Y</td><td align=\"center\">0.5</td><td align=\"center\">3.1</td><td align=\"center\">+</td></tr><tr><td align=\"center\">16</td><td align=\"center\">26</td><td align=\"center\">8</td><td align=\"center\">26.2</td><td align=\"center\">22.5</td><td align=\"center\">10</td><td align=\"center\">130</td><td align=\"center\">38.6</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.3</td><td align=\"center\">+</td></tr><tr><td align=\"center\">17</td><td align=\"center\">22</td><td align=\"center\">9</td><td align=\"center\">22</td><td align=\"center\">9.8</td><td align=\"center\">53</td><td align=\"center\">-</td><td align=\"center\">40.7</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">18</td><td align=\"center\">5</td><td align=\"center\">10</td><td align=\"center\">5.4</td><td align=\"center\">6.6</td><td align=\"center\">52</td><td align=\"center\">124</td><td align=\"center\">40.6</td><td align=\"center\">-</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">19</td><td align=\"center\">32</td><td align=\"center\">9</td><td align=\"center\">32.6</td><td align=\"center\">15</td><td align=\"center\">5</td><td align=\"center\">88</td><td align=\"center\">38.6</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">20</td><td align=\"center\">32</td><td align=\"center\">11</td><td align=\"center\">31.6</td><td align=\"center\">15.5</td><td align=\"center\">14</td><td align=\"center\">-</td><td align=\"center\">39</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.3</td><td align=\"center\">+</td></tr><tr><td align=\"center\">21</td><td align=\"center\">31</td><td align=\"center\">10</td><td align=\"center\">31</td><td align=\"center\">17.9</td><td align=\"center\">20</td><td align=\"center\">90</td><td align=\"center\">38.3</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">22</td><td align=\"center\">23</td><td align=\"center\">10</td><td align=\"center\">23</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">90</td><td align=\"center\">39.4</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">23</td><td align=\"center\">23</td><td align=\"center\">9</td><td align=\"center\">23.2</td><td align=\"center\">6.8</td><td align=\"center\">35</td><td align=\"center\">90</td><td align=\"center\">40.1</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.5</td><td align=\"center\">+</td></tr><tr><td align=\"center\">24</td><td align=\"center\">15</td><td align=\"center\">6</td><td align=\"center\">15.5</td><td align=\"center\">23.7</td><td align=\"center\">45</td><td align=\"center\">128</td><td align=\"center\">38.1</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">25</td><td align=\"center\">24</td><td align=\"center\">7</td><td align=\"center\">24.5</td><td align=\"center\">12.6</td><td align=\"center\">18</td><td align=\"center\">-</td><td align=\"center\">40.3</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">26</td><td align=\"center\">24</td><td align=\"center\">8.5</td><td align=\"center\">23.8</td><td align=\"center\">9.5</td><td align=\"center\">20</td><td align=\"center\">140</td><td align=\"center\">39.2</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">27</td><td align=\"center\">29</td><td align=\"center\">11</td><td align=\"center\">29</td><td align=\"center\">17.7</td><td align=\"center\">7</td><td align=\"center\">128</td><td align=\"center\">39.3</td><td align=\"center\">-</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">28</td><td align=\"center\">45</td><td align=\"center\">6</td><td align=\"center\">45</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">38.7</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr><tr><td align=\"center\">29</td><td align=\"center\">7</td><td align=\"center\">10</td><td align=\"center\">7.5</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">150</td><td align=\"center\">39.7</td><td align=\"center\">N</td><td align=\"center\">13.2</td><td align=\"center\">1.0</td><td align=\"center\">+</td></tr><tr><td align=\"center\">30</td><td align=\"center\">22</td><td align=\"center\">11</td><td align=\"center\">22.5</td><td align=\"center\">9.1</td><td align=\"center\">85</td><td align=\"center\">100</td><td align=\"center\">39.3</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">31</td><td align=\"center\">8</td><td align=\"center\">9</td><td align=\"center\">8.2</td><td align=\"center\">21.9</td><td align=\"center\">1</td><td align=\"center\">116</td><td align=\"center\">38.7</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">32</td><td align=\"center\">17</td><td align=\"center\">8.5</td><td align=\"center\">17</td><td align=\"center\">11.1</td><td align=\"center\">74</td><td align=\"center\">124</td><td align=\"center\">40.3</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.3</td><td align=\"center\">+</td></tr><tr><td align=\"center\">33</td><td align=\"center\">20</td><td align=\"center\">4.5</td><td align=\"center\">20</td><td align=\"center\">9.6</td><td align=\"center\">0</td><td align=\"center\">112</td><td align=\"center\">39.6</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">34</td><td align=\"center\">26</td><td align=\"center\">7.5</td><td align=\"center\">26.3</td><td align=\"center\">12.7</td><td align=\"center\">2</td><td align=\"center\">112</td><td align=\"center\">38.9</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr><tr><td align=\"center\">35</td><td align=\"center\">35</td><td align=\"center\">5</td><td align=\"center\">35.1</td><td align=\"center\">27</td><td align=\"center\">0</td><td align=\"center\">120</td><td align=\"center\">39.2</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr><tr><td align=\"center\">36</td><td align=\"center\">20</td><td align=\"center\">10</td><td align=\"center\">20</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">110</td><td align=\"center\">38.8</td><td align=\"center\">N</td><td align=\"center\">0.3</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr><tr><td align=\"center\">37</td><td align=\"center\">12</td><td align=\"center\">6</td><td align=\"center\">12</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">124</td><td align=\"center\">39.6</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">38</td><td align=\"center\">37</td><td align=\"center\">7</td><td align=\"center\">37.3</td><td align=\"center\">8.8</td><td align=\"center\">23</td><td align=\"center\">108</td><td align=\"center\">39.8</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">0.4</td><td align=\"center\">+</td></tr><tr><td align=\"center\">39</td><td align=\"center\">25</td><td align=\"center\">7</td><td align=\"center\">25</td><td align=\"center\">15.6</td><td align=\"center\">26</td><td align=\"center\">128</td><td align=\"center\">38.7</td><td align=\"center\">Y</td><td align=\"center\">0.4</td><td align=\"center\">0.5</td><td align=\"center\">+</td></tr><tr><td align=\"center\">40</td><td align=\"center\">33</td><td align=\"center\">8</td><td align=\"center\">33</td><td align=\"center\">8.8</td><td align=\"center\">0</td><td align=\"center\">90</td><td align=\"center\">38.5</td><td align=\"center\">Y</td><td align=\"center\">0.3</td><td align=\"center\">0.5</td><td align=\"center\">-</td></tr><tr><td align=\"center\">41</td><td align=\"center\">41</td><td align=\"center\">7</td><td align=\"center\">41</td><td align=\"center\">21</td><td align=\"center\">0</td><td align=\"center\">90</td><td align=\"center\">39.3</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">42</td><td align=\"center\">25</td><td align=\"center\">0.9</td><td align=\"center\">24.6</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">92</td><td align=\"center\">40.5</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr><tr><td align=\"center\">43</td><td align=\"center\">29</td><td align=\"center\">10</td><td align=\"center\">29.2</td><td align=\"center\">33.4</td><td align=\"center\">18</td><td align=\"center\">80</td><td align=\"center\">38.9</td><td align=\"center\">N</td><td align=\"center\">1.2</td><td align=\"center\">0.3</td><td align=\"center\">+</td></tr><tr><td align=\"center\">44</td><td align=\"center\">7</td><td align=\"center\">8</td><td align=\"center\">7.3</td><td align=\"center\">26.7</td><td align=\"center\">0</td><td align=\"center\">136</td><td align=\"center\">39.7</td><td align=\"center\">Y</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">45</td><td align=\"center\">17</td><td align=\"center\">7</td><td align=\"center\">17</td><td align=\"center\">5.1</td><td align=\"center\">0</td><td align=\"center\">140</td><td align=\"center\">39.9</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">+</td></tr><tr><td align=\"center\">46</td><td align=\"center\">15</td><td align=\"center\">4</td><td align=\"center\">14.7</td><td align=\"center\">13.5</td><td align=\"center\">3</td><td align=\"center\">120</td><td align=\"center\">38.9</td><td align=\"center\">N</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">&lt; 0.2</td><td align=\"center\">-</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>The last column indicates if the dog was classified as SIRS-positive (+) or not (-) using the chosen SIRS criteria. Where values for HR and RR are missing they were not noted in the records. Values for Neutrophils and PBN are missing in 8 dogs.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1751-0147-50-35-1\"/>" ]

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{ "acronym": [], "definition": [] }

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[ "<title>Conclusion</title>", "<p>Conjugated linoleic acid isomers are a group of zoochemicals that have a variety of physiological actions and potential health benefits, <italic>e.g</italic>., modulation of inflammation, lean body mass, atherosclerosis, and cancer. Most of the health effects of CLA isomers are based on reports with limited power of extrapolation of experiments with animal models and <italic>in vitro</italic>/<italic>ex viv</italic>o systems. Multiple factors in earlier animal studies might cause inaccurate extrapolation of CLA isomer effects to humans. First, interspecies-genetic differences may be a major consideration. Some of the health effects of CLA isomers seen in animal models might be species-specific, and might not be observable in humans. For example, the suppressive effect on hypertension was seen in CLA fed rats [##REF##18283099##162##, ####REF##15369804##163##, ##REF##14521947##164##, ##REF##12788078##165####12788078##165##], but not in humans [##REF##16549463##166##]. Second, animal studies used primarily adolescent animals, while human studies used mostly healthy, obese, or diabetic adults. Body composition, sensitivity to and metabolism of chemicals, and gene expression profiles in developing adolescent animals may be different from those seen in adult humans. This could influence the outcome of examining the effects of CLA isomers, in particular, on age-associated events, such as adiposity and atherogenesis. Although atherosclerosis-prone mice (<italic>i.e</italic>., C57BL/6) mimic humans, animal results have been inconclusive and the efficacy of CLA isomers maybe due to interspecies-gene differences. Third, animal studies have usually been of short durations with high dosages. This is of particular concern because extrapolated CLA isomer dosages for possible human consumption would require dose and duration adjustments for human lifespan and levels at or less than threshold toxicity.</p>", "<p>The effects of CLA isomers on body composition have been studied extensively in animals and have recently been repeated in human studies with conflicting findings. In part, the results may be inconclusive because a majority of the studies utilized CLA isomer mixture supplementation. Both dose- and isomer-dependent effects of CLA have been suggested in both the animal and human studies. Further research is needed to identify isomer-and/or dose-related efficacy and toxicity. In addition, recent studies have identified SNPs in genes related to lipid metabolism and antioxidant defense systems. It may be necessary to investigate the effects of CLA isomers on CVD risk at intra-species levels. Some recent animal studies have reported a positive correlation with other disease prevention and treatment, <italic>e.g</italic>., diabetes and inflammatory bowel disease [##REF##16698153##48##,##REF##15362034##49##,##REF##17322064##128##,##REF##16711598##129##] leading researchers to further evaluate the possible benefits of CLA isomer supplementation for humans.</p>", "<p>Earlier research showed that the ability of CLA isomers to act as anti-carcinogens and protectants against atherosclerosis may be due to its role as an antioxidant. However, in light of current research, the modulation of chronic diseases by CLA isomers may involve the control of redox status by regulating genes, whose products influence ROS generation, through redox-sensitive transcription factors including PPARγ and NF-κB. It is essential that investigation to develop an understanding about the molecular action of CLA isomers be encouraged so that we may learn how to use these compounds as adjuvants in chronic disease therapy.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Conjugated linoleic acid (CLA) has been the subject of extensive investigation regarding its possible benefits on a variety of human diseases. In some animal studies, CLA has been shown to have a beneficial effect on sclerotic lesions associated with atherosclerosis, be a possible anti-carcinogen, increase feed efficiency, and act as a lean body mass supplement. However, the results have been inconsistent, and the effects of CLA on atherogenesis appear to be dose-, isomer-, tissue-, and species-specific. Similarly, CLA trials in humans have resulted in conflicting findings. Both the human and animal study results may be attributed to contrasting doses of CLA, isomers, the coexistence of other dietary fatty acids, length of study, and inter-and/or intra-species diversities. Recent research advances have suggested the importance of CLA isomers in modulating gene expression involved in oxidative damage, fatty acid metabolism, immune/inflammatory responses, and ultimately atherosclerosis. Although the possible mechanisms of action of CLA have been suggested, they have yet to be determined.</p>" ]

[ "<title>Conjugated linoleic acid</title>", "<p>A group of <italic>trans</italic>-fatty acids, conjugated linoleic acid (CLA) has been purported to have diverse physiological functions and potential health benefits [##REF##10683436##1##, ####UREF##0##2##, ##UREF##1##3##, ##UREF##2##4##, ##REF##12468364##5##, ##REF##12055356##6####12055356##6##]. These unique geometric and positional isomers of octadecadienoic acid derived from linoleic acid (18:2n-6) have been found in only a limited number of foods or food products mostly derived from the fat of range animals. The highest levels of CLA are found in ruminant animals (beef, lamb and dairy cows) with beef, milk-fat, and cheese, the most common animal products containing CLA. During the biohydrogenation of linoleic acid to stearic acid, CLA is synthesized in the rumen as an intermediate by gram-negative bacteria, <italic>Butyrivibrio fibrisolvens </italic>[##UREF##3##7##]. CLA is also found in fish, monogastric animal products, and plant products, however, in much lower concentrations [##UREF##1##3##]. CLA isomers have been identified during the hydrogenation of fat, <italic>e.g</italic>., margarine production, and are found primarily in foods considered high in fat. Also, CLA is found in low concentrations in the lipids of human blood, tissue, and milk [##UREF##4##8##], presumably from dietary intakes. Although there are 28 different CLA isomers, the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer is predominantly found in the ruminant foods discussed earlier and accounts for &gt;90% of CLA intake in the human diet [##REF##16650752##9##]. The structures, shown in Figure ##FIG##0##1##, consist of 18 carbon atoms with two conjugated double bonds separated by a single bond, unlike linoleic acid, which is a non-conjugated diene [##REF##10683436##1##]. The conjugated double bonds of CLA isomers contribute to their higher susceptibility to autioxidation than the non-conjugated bonds of linoleic acid [##REF##12613847##10##]. Differences in chain length, degree of unsaturation, and position and stereoisomeric configuration of the double bonds affect fatty acid oxidation or lipid peroxidation. Usually, long-chain fatty acids are oxidized more slowly and unsaturated fatty acids are oxidized more rapidly than are saturated fatty acids. Lauric acid is highly oxidized, but PUFAs and monounsaturated fatty acids are fairly well oxidized [##REF##11010930##11##]. Oxidation of the long-chain, saturated fatty acids decreases with increasing carbon number.</p>", "<p>Many research groups have looked at the possibility of CLA isomers as anti-carcinogens. Most anti-carcinogens are plant products (phytochemical), therefore, CLA isomers are unusual find because it occurs in the highest concentration in animal products (zoochemical) with only trace amounts found in plant lipids. The possibility of CLA isomers working as a feed efficiency supplement and a lean body mass supplement has also been examined, along with its role in cancer prevention and stimulation of the immune system.</p>", "<p>With regard to potential health benefits, considerable attention has been given to anti-carcinogenic effects of CLA isomers; however, less attentions has been devoted toward its usefulness in preventing and reversing atherosclerosis and related diseases. The majority of research studies have been done using experimental animals and <italic>in vitro</italic>, with only recent investigations showing the effects of CLA isomers on humans. The purpose of this review is to assess and summarize current literature and knowledge on the possible health benefits of CLA isomers, particularly with respect to atherosclerosis as a chronic inflammatory disease.</p>", "<title>Pathology/etiology of atherosclerosis</title>", "<p>Cardiovascular disease (CVD) is a major cause of death in developed countries, and most cardiovascular events are secondary to atherosclerosis [##UREF##5##12##]. CVD causes high medical costs and losses of productivity. The high incidence of CVD mortality and morbidity and the economic toll of CVD emphasize the need for prevention and management of CVD associated risk factors. Although the risks for CVD are multifactorial, the three most important modifiable risk factors for atherosclerosis are: 1) smoking, 2) inactive lifestyle, and 3) elevated blood cholesterol levels from dietary sources. Of particular concern for the elevated blood cholesterol is increased low-density lipoprotein (LDL). Results of extensive epidemiological and clinical research support the direct association between elevated blood cholesterol and CVD risk.</p>", "<p>Atherosclerosis is a condition characterized by degeneration and hardening of the walls of the arteries and sometimes the valves of the heart. There is accumulation of lipids and other materials in the arteries which contributes to hypertension and vice versa. Figure ##FIG##1##2## schematically illustrates the major points of oxidized LDL in the process of plaque formation. The process of atherosclerosis begins with buildup of soft fatty streaks along the inner arterial walls often at branch points. With age, fatty streaks steadily grow and become hardened with minerals, leading to plaque. Consequently, plaque stiffens and narrows the artery lumen. By middle age, most people have well-recognized plaque formation [##UREF##6##13##]. Blood platelets respond to plaque as if it was a blood vessel injury produce clots which unlike the normal blood clotting events, do not readily dissolve and instead stick to the plaque, grow and restrict blood flow, <italic>i.e</italic>., thrombosis. Platelet activity is under the control of eicosanoids synthesized from 20-carbon omega-6 and omega-3 fatty acids, such as prostaglandins and thromboxanes. Complication may occur when blood clots break free from the walls of arteries and make their way to a smaller artery, and shut off the blood supply to tissue; this produces an embolism.</p>", "<p>LDL oxidation is thought to be the first step of atherogenesis, followed by foam cell, fatty streak, and plaque formation. It has been hypothesized that LDL can be transported through endothelial tight junctions and/or endothelial transcytosis from the lumen into the intima [##REF##17322415##14##], in which blood antioxidants are unlikely to be available, and undergo atherogenic oxidative changes. Modified LDL is then taken up by macrophages through multiple pathways. Minimally oxidized LDL (MM-LDL) is recognized by CD14 and toll-like receptor-4 (TLR4) [##REF##14501582##15##], while oxidized LDL binds to scavenger receptors (<italic>e.g</italic>., CD36, CD68, SR-A1, SR-B1). Aggregated forms of either MM-LDL or native LDL are endocytosed by activated macrophages [##REF##16178764##16##].</p>", "<p>Both oxidized LDL and activated macrophages by oxidized LDL uptake affect gene expression in neighboring endothelial cells (ECs), contributing to further atherogenic/inflammatory processes. Studies have documented that the oxidized LDL affect the pattern of gene expression in ECs, leading to up-regulated expression of target molecules. The oxidized LDL-induced molecules in ECs include monocyte chemoattractant proteins (MCPs), macrophage colony stimulating factors (M-CSFs), and cell adhesion molecules (CAMs) [##REF##11137085##17##,##REF##1695010##18##]. MCPs and M-CSFs are induced by MM-LDL, and are released from ECs. MCPs recruit monocytes to the ECs. M-CSFs promote the differentiation and proliferation of monocytes to macrophages (Figure ##FIG##1##2##). CAMs, cell surface proteins, are involved in binding with other cells or the extracellular matrix. These molecules contribute to foam cell formation by the recruitment of circulatory monocytes into vascular walls and by the stimulation of monocyte differentiation to macrophages.</p>", "<p>The differences in genetic susceptibility to atherosclerosis were investigated using animal and human models [##REF##10880418##19##, ####REF##17000557##20##, ##REF##16219313##21##, ##UREF##7##22####7##22##]. ECs from the atherosclerotic prone strain of C57BL/6J mice exhibited dramatic induction of MCP-1 and M-CSF in response to MM-LDL, while ECs from the atherosclerotic resistant strain of C3H/HeJ mice showed little or no induction of MCP-1 or M-CSF. Shi <italic>et al</italic>. [##REF##10880418##19##] provide the evidence that genetic factors influencing the endothelial response to oxidized LDL contribute to the genetic component in atherosclerosis. Levula <italic>et al</italic>.'s [##REF##17000557##20##] microarray study reveals the groups of target genes whose expressions are altered by oxidized LDL in human macrophages. The target genes are involved in 1) lipid metabolism, 2) inflammation, growth, and hemostasis, 3) metalloproteinases and tissue inhibitors of matrix metalloproteinases, 4) enzymes, 5) structural and binding proteins, and 6) annexins. The genes involved in inflammation include M-CSF1, MCP1, and ICAM1, all of which are induced in the macrophages by oxidized LDL, and correspond to the results of previous Shi <italic>et al</italic>.'s EC studies.</p>", "<p>Induced expression of CD68 and SR in human macrophages by oxidized LDL was also observed in Levula <italic>et al</italic>.'s microarray study. In addition, activated macrophages secrete inflammatory cytokines, such as TNF-α, that contribute to the induction of the expression of MCP-1, M-CSF, ICAM1, and VCAM1 in human aortic endothelial cells (HAECs) [##REF##16219313##21##] and the expression of ICAM1 and VCAM1 in human neonatal dermal lymphatic endothelial cells (HNDLECs) [##UREF##7##22##] and the development of atherosclerosis. Thus, the pro-inflammatory gene expression in ECs is mediated by either oxidized LDL or pro-inflammatory cytokines released from activated macrophages, resulting in augmented atherogenic/inflammatory events by recruiting circulatory monocytes.</p>", "<p>Moreover, oxidized LDL may modulate the apoptosis of vascular cells. Reeve <italic>et al</italic>'s [##REF##17374365##23##] microarray study demonstrated that 221 genes were differentially regulated by oxidized LDL in coronary artery smooth muscle cells (CASMC). Of particular interest are apoptotic genes, FasL, Bax, and p53, induced by oxidized LDL in CASMC. Oxidized LDL induces apoptosis of ECs via the mitogen-activated protein kinase (MAPK) pathway [##REF##17158646##24##]. Studies using EC and smooth muscle cell cultures demonstrated that multiple apoptotic signaling pathways were affected by ROS [##REF##11500945##25##].</p>", "<title>Roles of ROS in atherogenesis</title>", "<p>Reactive oxygen species (ROS) are implicated in atherogenesis. Risk factors for atherosclerosis are associated with an increased arterial wall flux of ROS that not only may oxidize biomolecules, but also directly produce phenotypic changes in vascular cells, including the induction of adhesion molecules and smooth muscle proliferation [##REF##16246957##26##].</p>", "<title>Sources of ROS</title>", "<p>Sources of ROS involved in atherogenesis include NADPH oxidases, nitric oxide synthases (NOS), lipoxygenases (LO), cyclooxygenases (COX), and the mitochondrial respiratory chain [##REF##16757157##27##]. Native LDL is modified by ROS generated by these enzymes in vascular tissues. NADPH oxidase is composed of a number of different subunits. There are seven homologues of the gp91phox (Nox-2) subunit. Nox-4 is predominantly expressed in ECs, though the expressions of Nox-1 and Nox-2 are also detected [##REF##17064675##28##]. During the respiratory burst in phagocytes, NADPH oxidase converts oxygen molecules to superoxide, which is a microbicidal oxygen metabolite. Then, superoxide is converted by superoxide dismutase (SOD) to hydrogen peroxide, which also kills microorganisms. ROS are also produced in ECs by endothelial NADPH oxidase [##REF##16246957##26##,##REF##16757157##27##]. Phagocytic NADPH oxidase and endothelial NADPH oxidase is one of the major ROS sources in the vasculature [##REF##16757157##27##]. Monocyte differentiation to macrophage is associated with the production and the release of ROS possibly through the induction of NADPH oxidase, resulting in further LDL oxidation [##REF##15203197##29##,##REF##12223313##30##]. NADPH oxidase generates superoxide on the extracellular side of the plasma membrane, and the enzyme can trigger intracellular signaling by superoxide transport via chloride channel-3 [##REF##17360969##31##]. Stepp <italic>et al</italic>. [##REF##12124224##32##] reported that native LDL and MM-LDL differentially increase vascular endothelial superoxide generation in canine carotid arteries, leading to vascular dysfunction and atherogenesis. Native LDL increases superoxide by an endothelial nitric oxide synthase (eNOS)-dependent mechanism whereas MM-LDL induces greater superoxide by the mechanisms dependent on eNOS, xanthine oxidase, and NADPH oxidase. Superoxide production by vascular tissues and its interaction with nitric oxide (NO) play important roles in vascular pathophysiology. Superoxide reacts rapidly with NO, reducing NO bioavailability and producing the oxidative peroxynitrite radical [##REF##11940543##33##]. Endothelial activation via LOX-1 produces additional ROS, generating a positive feedback loop for further LDL oxidation [##REF##16473764##34##]. ROS generated in a NADPH oxidase-dependent pathway mediate TNF-α-induced MCP-1 expression in ECs, and the induction of MCP-1 expression is suppressed by the antioxidant enzymes, SOD and catalase [##REF##14576080##35##]. Since phagocytic NADPH oxidase is the first line of the host defense system, selective suppression of vascular NADPH oxidase in local inflammatory lesions might be one of the therapeutic strategies [##UREF##8##36##].</p>", "<p>Cyclooxygenases (COX-1 or COX-2) and lipoxygenases (5-, 12-, or 15-LO) also contribute to ROS generation during arachidonic acid (AA) metabolism shown in Figure ##FIG##2##3##[##REF##16757157##27##,##REF##15107407##37##]. The initial products in AA metabolism are highly reactive peroxides. Overexpression or induction of COX-2 increases ROS in certain cell types [##UREF##9##38##,##REF##16934679##39##] and the effects of overexpression of COX-2 are cell-/tissue-specific [##REF##16818639##40##]. Constitutive COX-1 and inducible COX-2 catalyze the conversion of free PUFAs to prostanoids (prostaglandins and thromboxanes), while LO generates the leukotrienes. Prostanoids and leukotrienes comprise a large and complex family of biologically active lipids derived from PUFAs by insertion of molecular oxygen. Collectively, these compounds are termed eicosanoids. Both prostanoids and leukotrienes play important roles in inflammation. Non-esterified PUFA released from the sn-2 position (middle carbon of glycerol) of the membrane phospholipids by the action of specific phospholipases are substrates for COX, LO, or cytochrome P450 monooxygenases (CYP) [##REF##11748246##41##,##UREF##10##42##]. The metabolism of AA has two main pathways: the cyclic pathway leading to prostanoid formation and the linear pathway resulting in leukotriene formation. Two molecules of oxygen are added in the first step for the generation of prostaglandin G (PGG). The second step, via the peroxidase activity of COX, converts PGG2 into PGH2, the precursor for either thromboxanes or other prostaglandins. The peroxidase step is inhibited by aspirin or ibuprofen. LO is also a major source of extracellular superoxide release in a certain cell type during AA metabolism [##REF##15107407##37##]. The LO pathway is responsible for the formation of leukotrienes and hydroxyeicosatetraenoic acids (HETEs). LO isoforms act upon arachidonic acid to form 5-, 8-,12-, or 15-hydroperoxy eicosatetraenoic acids (HPETEs), which are unstable and can be reduced to the hydroxyl derivatives (HETE) <italic>in vivo</italic>. The range of HPETEs with biological activity is known as the leukotrienes. Both COX and LO products diffuse from cells and act locally at nanomolar levels on cell surface receptors linked to G-proteins. Activation of G-protein-associated receptors leads to changes in intracellular cAMP or calcium, which serve as second messengers that activate signaling mechanisms influencing various cellular functions. The COX products are modulators of thromboregulatory and chemotaxic responses, and inflammation. The LO products are involved in vascular permeability, vasoconstriction, and bronchoconstriction. The third route for eicosanoid production is via the CYP, in particular CYP4 family [##REF##9068972##43##], including epoxy derivatives of 20:4 ω-6 that can modulate calcium signaling, channel activity, transporter function, and mitosis. This mechanism seems to be more consequential in cells when COX and LO activities are minimal.</p>", "<p>This body of research has verified that multiple enzymes are involved in ROS generation that leads to atherogenesis. Hence, it is speculated that suppressing ROS generation may be a therapeutic target for preventing and alleviating atherosclerosis.</p>", "<title>Oxidation of biomolecules</title>", "<p>ROS play a role in LDL oxidation. LDLs are rich in polyunsaturated fatty acids (PUFAs), which are susceptible to oxidation [##UREF##5##12##]. Lipid peroxidation can commence by ROS and other mechanisms that result in abstraction of an electron from a PUFA [##UREF##11##44##]. The sequential carbon-centered radical undergoes rearrangement, and in the presence of oxygen, will add oxygen to form a peroxyl radical (ROO•). Propagation of the free radical reaction can occur by reaction of the peroxyl radical with another PUFA, generating the corresponding fatty acid hydroperoxide (ROOH) and another carbon-centered radical. Other factors, such as Fe⁺², and other oxidants can result in an amplification of the free radical process. Vitamin E is a nonenzymatic chain-breaking scavenger of lipid radicals generated in cell membranes; it protects against further lipid peroxidation. Vitamin C is an important antioxidant against lipid peroxidation because it has a high reactivity with the oxygen-centered radical. Oxygen-centered radicals have sufficient polarity to be accessible to the aqueous soluble vitamin C. Also, when vitamin E reacts with a radical, vitamin E is converted to its radical form which can be recycled to reduced vitamin E by reacting with vitamin C. Other reducing compounds such as glutathione and NADPH act in concert with vitamins E and C in an antioxidant cascade.</p>", "<p>LDL oxidation also results in changes in apolipoprotein B epitope. The oxidized apolipoprotein portion of LDL is subsequently recognized and internalized by SR-A, whereas the oxidized lipid moiety of LDL is bound to CD36 on macrophages [##REF##15607497##45##].</p>", "<title>Inflammation and fatty acids/other protective compounds</title>", "<title>Fatty acids</title>", "<p>The relationship between fatty acids and atherosclerosis and other inflammatory diseases has been suggested by epidemiological, clinical, and in-/ex-vivo studies. Increased intake of saturated fatty acids is positively associated with development of atherosclerosis and inflammation. In contrast, omega-3 (ω-3) fatty acids, such as eicosapentaenoic acid (EPA, C20:5) and docosahexaenoic acid (DHA, C22:6), have shown protective effects against CVD. EPA and DHA are major components of dietary fish and fish oils. Like EPA and DHA, CLA isomers, exhibit protective effects against atherogenesis [##REF##15588017##46##,##UREF##12##47##] and inflammatory bowel disease (IBD) [##REF##12468364##5##,##REF##16698153##48##,##REF##15362034##49##] and antioxidant effects [##UREF##13##50##] in <italic>in-/ex-vivo </italic>studies; however, clinical studies have been inconclusive.</p>", "<p>Most of the fatty acids synthesized or ingested have one of two fates: incorporation into triglycerides for the storage of metabolic energy or incorporation into the phospholipid components of membranes. The selection between the alternative fates depends on the need (<italic>i.e</italic>. growth and starvation) [##UREF##10##42##]. Fatty acids may differentially affect inflammatory processes and ultimately the etiology of atherosclerosis in three ways as:</p>", "<p>1) the components of membrane; fatty acids may serve as precursors of pro- or anti- inflammatory eicosanoids;</p>", "<p>2) the components of LDL; fatty acids may differentially modulate recognition of macrophage receptors and subsequent inflammatory processes and atherogenesis; and</p>", "<p>3) the regulators of gene expression; fatty acids may differentially regulate inflammatory gene expression, serving as ligands for transcription factors (<italic>e.g</italic>. PPARs).</p>", "<p>Almost all mammalian cells, except red blood cells, produce eicosanoids, which play a role in inflammation. Arachidonic acid (AA, C22:4) is the most important precursor of eicosanoid, and AA is synthesized from linoleic acid (LA, C18:2, ω-6) by enlongation and desaturation. In response to hormonal or other stimuli, phospholipase A2, present in most types of mammalian cells, attacks membrane phospholipids, releasing AA from the middle carbon of glycerol. Enzymes of the smooth endoplasmic reticulum then convert AA into eicosanoids, potent biological signaling molecules [##UREF##10##42##].</p>", "<p>LA (18:2, ω-6) and α-linolenic acid (ALA, 18:3, ω-3) serve as the precursors for longer-chain ω-6 (<italic>e.g</italic>., arachidonic acid: AA) and ω-3 fatty acids (<italic>e.g</italic>., EPA, DHA), respectively. Neither ω-3 nor ω-6 fatty acids can be synthesized in mammals due to the lack of certain types of desaturases. ω-3 Fatty acids cannot be generated from ω-6 fatty acids in mammals. Hence, the source of these PUFAs is limited to dietary intake [##REF##16540100##51##]. Dietary EPA, DHA, and CLA can partially replace AA derived from LA in the cell membrane [##REF##11441132##52##,##UREF##14##53##]. Usually the plentiful LA may exclude these fatty acids from incorporation into membrane phospholipids [##UREF##15##54##] and/or LDL. However, EPA, DHA and CLA may influence eicosanoid production from AA and subsequent immune and inflammatory processes. For example EPA and DHA decrease the synthesis of pro-inflammatory eicosanoids, such as leukotriene-4 and prostaglandin-2 by replacing AA in phospholipid bilayers and by inhibiting cycloxygenase activity [##REF##12438303##55##, ####REF##12939515##56##, ##REF##16892270##57####16892270##57##]. As components of LDL and/or membrane, these fatty acids may affect the inflammatory gene expression by altering signaling pathways. The unusual conformation structures (kinks) in unsaturated fatty acids interfere with the membrane motion [##UREF##10##42##] and possibly signal transduction. In addition, EPA and DHA reduce the expression of adhesion molecules induced by oxidized LDL in endothelial cells [##REF##12818567##58##, ####REF##10617974##59##, ##REF##8607877##60####8607877##60##]. ω-3 PUFAs suppress inflammatory gene expression by inhibiting TLR4 signaling pathway, whereas saturated fatty acids exhibit the opposite effect [##REF##16682810##61##], Thus, subsequently decreasing risk for CVDs.</p>", "<title>Phytochemicals/dietary antioxidants</title>", "<p>Several epidemiological studies have reported an inverse relationship between intake of vegetables and fruits (in particular those rich in antioxidant vitamins including vitamins C and E and β-carotene), and risk for CVD [##REF##9893151##62##, ####REF##11010927##63##, ##REF##11000647##64##, ##REF##12081821##65####12081821##65##]. The protective effects of these antioxidant vitamins on atherosclerosis have been intensively investigated in animal and human studies. According to the oxidative modification hypothesis, oxidized LDL is immunogenic and atherogenic and LDL oxidation triggers atherosclerotic processes. Therefore, the protection of LDL from oxidation may be crucial to the prevention of atherosclerosis; the antioxidant components of LDL may prevent LDL oxidation.</p>", "<p>Vitamin E is the generic term for all tocopherol and tocotrienol derivatives that exhibit the biological activity of α-tocopherol. There are eight naturally occurring isoforms synthesized in plants. α-Tocopherol is the most biologically and chemically active form of vitamin E. The hydroxyl groups at the C-6 position of tocopherols enable them to scavenge free radicals and superoxide. Although γ-tocopherol is predominant in the American diet, its plasma levels are only 10% of plasma α-tocopehrol levels (about 25 μmol/L α-tocopherol) [##REF##15090261##66##].</p>", "<p>α-Tocopherol is the major antioxidant in LDL and one LDL particle contains approximately six molecules of α-tocopherol. α-Tocopherol in LDL plays a role in preventing LDL oxidation. Vitamin E depletion in LDL may trigger LDL oxidation; and the addition of micromolar concentrations of vitamin E inhibits LDL oxidation. All other antioxidants, such as γ-tocopherol, carotinoids, and ubiquinol-10, are present in much smaller amounts than α-tocopherol. In contrast to α-tocopherol, carotenoids play only a minor or no role in LDL protection [##UREF##16##67##]. However, many clinical studies have failed to demonstrate the protective effects of vitamin E. One explanation may be that vitamin E exhibits prooxidant activity in the absence of co-antioxidant compounds capable of reducing the tocopherol radical [##REF##14697409##68##,##REF##10969031##69##]. A similar situation may occur with other antioxidants, such as β-carotene [##UREF##17##70##, ####REF##9550461##71##, ##REF##11179860##72####11179860##72##]. Depending on the concentrations, environmental conditions and presence of oxygen or other oxidants, compounds with antioxidant properties may exhibit prooxidant or other non-antioxidant properties.</p>", "<p>Polyphenolic compounds, such as resveratrol and catechins, are derived from plants, and the compounds have shown anti-atherogenic and anti-inflammatory effects. The beneficial effects of the compounds are attributed to their abilities to function as antioxidants by: 1) inhibition of prooxidant enzymes, such as lipoxygenases, cyclooxygenases, and xanthine oxidase, possibly through suppressing the activation of redox-sensitive transcription factors, NF-κB and activator protein-1 (AP-1), and 2) induction of antioxidant enzymes such as glutathione S-transferase, glutathione peroxidase (Gpx), superoxide dismutase (SOD), and catalase [##REF##16507749##73##,##REF##14519826##74##].</p>", "<title>Endogenous/enzymatic antioxidants</title>", "<p>Antioxidant enzymes are involved in the maintenance of intracellular and extracellular reducing reactions [##UREF##18##75##] and suppress the generation of free radicals as the first line of antioxidant defense [##UREF##5##12##]. Antioxidant enzymes include superoxide dismutase (SOD) and catalase. SOD is expressed in most cell types, and converts harmful superoxide to less harmful hydrogen peroxide and oxygen. Catalase catalyzes the dismutation of hydrogen peroxide to oxygen and water. Catalase has an iron redox center. Catalase is located predominantly within peroxisomes to protect from hydrogen peroxide generated during fatty acid β-oxidation within the cellular organelles [##REF##12456800##76##].</p>", "<p>The antioxidant enzymes play a role in preventing atherogenesis. Increased expression of GR in macrophages reduces atherosclerotic lesion formation in LDL receptor-deficient mice [##REF##17363688##77##]. Over-expression and/or induction of CuZn-SOD and catalase can be beneficial because of: 1) decreases in superoxide levels in ECs; 2) suppression of oxidative stress, e.g., age related; 3) protection against inflammatory events by inhibiting NF-κB activation; and 4) suppression of low-density lipoprotein (LDL) oxidation by ECs [##UREF##13##50##,##REF##12456800##76##,##REF##16973825##78##, ####REF##15590897##79##, ##REF##9648725##80##, ##REF##11172467##81####11172467##81##].</p>", "<title>Target genes/signaling pathway</title>", "<p>Atherosclerosis is a chronic inflammatory disease with an underlying abnormality in redox-mediated signals in the vasculature [##REF##10521248##82##]. ROS play a role in the signaling involved in atherogenic/inflammatory processes. There are two major redox-sensitive signaling pathways related to the atherogenic/inflammatory processes: NF-κB-, and peroxisome proliferator-activated receptor (PPAR)-mediated pathways. Fatty acids may act as gene regulators. CLA isomers are ligands with high to moderate affinity and activators of PPAR α and γ. CLA isomers may induce responsive genes of both PPAR α and γ <italic>in vivo </italic>[##REF##12055356##6##]. The <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer inhibits the NF-κB p50 and p65 subunits binding to DNA [##UREF##19##83##]. Also, CLA isomers may involve the control of redox status by regulating genes, whose products influence ROS generation, through transcription factors (PPARγ and NF-κB), which are concentration-dependent [##UREF##20##84##].</p>", "<title>NF-κB</title>", "<p>NF-κB is a redox-sensitive transcription factor expressed in all cell types; it recognizes and binds to specific DNA sequences (5'-GGGRNNYYCC-3'). NF-κB activation is triggered by the IκB kinase (IKK)-mediated degradation of inhibitor κB (IκB), which regulates NF-κB. NF-κB is activated by intra-/extra-cellular ROS and/or ROS-modified target biomolecules, and is involved in regulating immune and inflammatory responses. NF-κB-mediated target genes include: inflammatory cytokines (<italic>e.g</italic>., TNF-a, IL-1, IL-2, M-CSF), chemokines (<italic>e.g</italic>., MCP-1), adhesion molecules (<italic>e.g</italic>., ICAM-1, VCAM-1), inflammatory enzymes (<italic>e.g</italic>., iNOS, COX-2), and apoptotic regulators (<italic>e.g</italic>., Fas ligand, Fas, p53) [##REF##15346645##85##].</p>", "<p>Oxidized LDL may affect atherogenesis in part via the NF-κB activation pathway. Oxidized LDL activates NF-κB as well as <italic>C. pneumoniae </italic>[##REF##14967815##86##]. Resveratrol, an antioxidant polyphenol derived from plants, attenuates TNF-α-induced inflammatory gene expression and monocyte adhesion to human coronary arterial endothelial cells (HCAECs) by inhibiting NF-κB activation, suggesting that the anti-inflammatory actions of resveratrol are responsible for anti-atherogenic effects [##REF##16973825##78##]. Oxidized LDL exerts biphasic effects on NF-κB: 1) inflammatory effects by up-regulating inflammatory gene expression via NF-κB activation at lower concentrations of oxidized LDL; and 2) immunosuppressive effects by inhibiting NF-κB activation triggered by inflammatory agents such as lipopolysaccharide (LPS) at higher concentrations of oxidized LDL [##REF##15346645##85##]. HUVECs incubated with LPS which causes inflammatory gene expression via TLR4 activation, induce the expressions of TLR4, LOX-1, ICAM-I, and E-selectin, and increase monocyte adhesion to endothelium and NF-κB activation levels, suggesting the atherogenic process is mediated through TLR4/NF-kB pathways [##REF##16266460##87##]. There are two types of TLR4/NF-κB pathways identified: MyD88-dependent and independent pathways. MyD88 is a common downstream adaptor molecule for most TLRs, and recruits other molecules required to activate NF-κB. Saturated fatty acids trigger TLR4 and downstream NF-κB activations, resulting in inflammatory gene expression (<italic>i.e</italic>. COX2 or iNOS). In contrast, unsaturated fatty acids inhibit TLR4/NF-κB activation. This inhibition may be due to the alteration of fatty acid components in membrane lipid rafts, which may lead to the disruption of the recruitment of the downstream signaling components [##REF##16682810##61##].</p>", "<title>PPARs</title>", "<p>PPARs (PPARα, PPARβ, and PPARγ), a group of nuclear receptors, belong to the steroid hormone receptor superfamily [##REF##16403683##88##]. PPARs heterodimerize with the 9-cis retinoic acid receptor (RXR) and bind to peroxisome proliferator response elements (PPREs: 5'-<underline>AGGTCA</underline>n<underline>AGGTCA</underline>-3') which are located in enhancer sites of target genes (Figure ##FIG##3##4##). PPARα and PPARγ are expressed in vascular endothelial cells and smooth muscle cells as well as adipose tissues [##REF##15590897##79##,##REF##11818483##89##]. PPARα and PPARγ play a role in inflammation, adipogenesis, and insulin sensitization. Thiazolidinediones (TZDs), a group of synthetic PPARγ ligands, have shown beneficial effects as atheroprotective drugs. 15-Deoxy-Δ^12,14-prostaglandin J2 (15d-PGJ2), an prostanoid, is a natural ligand and an activator for PPARγ. 15-LOX products, 9- and 13-hydroxy-octadecadienoic acids (HODEs), are also PPARγ activators [##REF##11818483##89##]. Therefore, these eicosanoids, 15d-PGJ2 and HODEs, support the implication of PPARγ in inflammation.</p>", "<p>PPARγ activation may be involved in oxidized LDL-induced inflammatory gene expression and macrophage lipid metabolism [##REF##15607497##45##,##REF##9568716##90##,##REF##9636198##91##]. Although CD36 is up-regulated by oxidized LDL via PPARγ activation, PPARγ activation suppresses oxidized LDL-induced inflammatory effects by inhibiting inflammatory gene expression. Kunsch and Medforld [##REF##10521248##82##] suggest that PPARγ participates in a positive feedback loop and that alternative or downstream pathways may trigger PPARγ activation resulting in anti-inflammatory effects. For example, 15d-PGJ2 is known to be an endogenous PPARγ activator. 15d-PGJ2 may be a possible anti-inflammatory mediator, though the physiological levels of 15d-PGJ2 may be insufficient to modulate PPARγ activation [##REF##12975467##92##]. PPAR activators are negative regulators of macrophage activation and antagonize the activities of the transcription factors, AP-1, STAT, and NF-κB, involved in inflammatory gene expression [##REF##9422508##93##,##REF##10542237##94##].</p>", "<p>Lipoprotein lipase (LPL), a lipolytic enzyme, may play an important role in regulating early atherogenesis. LPL neither acts on nor binds to oxidized LDL. LDL(-) is a form of native LDL containing intermediately modified subfractions with higher electronegative charge and is taken up by LDL receptors. Lipid peroxidation is greater in LDL(-) than in native LDL; LDL(-) exhibits inflammatory effects. Ziouzenkova <italic>et al</italic>. [##REF##12878589##95##] demonstrated that LPL-treated LDL(-) reduced inflammatory gene expression in human ECs by suppressing NF-κB and AP-1 activations and by increasing the expression of IκB, a target gene for PPARα, via PPARα activation. In contrast, LDL(-) alone increased the inflammatory responses. 9- and 13-HODEs, both known as PPARγ activators, are released during the hydrolysis of both native LDL and LDL(-), resulting in PPARα activation and anti-inflammatory effects.</p>", "<p>Expression of antioxidant enzymes, Cu/Zn SOD and catalase, may be modulated through both PPARγ and NF-κB activations. Possible multiple binding sites for PPARγ and NF-κB have been identified: 1) within the promoter region of <italic>SOD1</italic>, and 2) one binding site for NF-κB within the promoter region of catalase. NF-κB activation is associated with the induction of proinflammatory gene expression. Although Cu/Zn SOD is an antioxidant enzyme, it is induced to convert superoxide to hydrogen peroxide that is still microbicidal; it also serves as a host defense with NADPH oxidase in phagocytes. Furthermore, the treatments of possible PPARγ activators increase both PPARγ and NF-κB DNA binding activities, indicating that these two redox-sensitive transcription factors coordinate and propagate feedback loops between each other.</p>", "<title>Interactions between genes and diet: Risk factors</title>", "<p>Single-nucleotide polymorphisms (SNPs) are a genetic variation of differences in a single nucleotide between individuals. The gene-diet interaction between common SNPs located in candidate genes and dietary factors related to lipid metabolism has been recently reported [##REF##16815124##96##]. These candidate genes include: <italic>APOA1 </italic>(75G→A) encoding apolipoprotein A-I, an apolipoprotein of HDL, and <italic>PPARA </italic>(Leu162Val) encoding PPARα. Ordovas <italic>et al</italic>. and Tai <italic>et al</italic>. suggest specific interactions between these polymorphisms and lipid profiles. HDL-cholesterol concentrations increased significantly with increasing PUFA intake in women with the A allele (G/A and A/A) in <italic>APOA1</italic>, while HDL-cholesterol concentrations decreased as PUFA intake increased in women with the homologous G allele (G/G) in <italic>APOA1 </italic>[##REF##11756058##97##]. The Leu162Val polymorphism in <italic>PPARA </italic>is associated with increased plasma concentrations of total cholesterol, LDL cholesterol, and apolipoprotein B [##REF##12006394##98##]. Thus, these interactions influence CVD risk in different directions through effects on two different CVD risk factors: HDL cholesterol through the polymorphism in <italic>APOA1</italic>and triacylglycerol through the polymorphism in <italic>PPARA</italic>. The effects of Pro12Ala polymorphism in <italic>PPARG2 </italic>on type 2 diabetes and obesity are also reported. The 12Ala allele (Ala/Ala) in <italic>PPARG2 </italic>confers a reduced risk for type 2 diabetes and decreased obesity-associated insulin resistance in the French Caucasian population [##REF##15784141##99##]. Furthermore, the associations of polymorphisms in genes involved in antioxidant defense systems, with CVD and other diseases, have been proposed. A human sodium-dependent vitamin C transporter, SVCT1, is encoded by <italic>SLC23A1</italic>, and mediates intestinal absorption and renal absorption of L-ascorbic acid [##REF##12845532##100##]. <italic>SLC23A1 </italic>appears to have population-specific variants, and populations with discrete genetic variants might require different recommended values of vitamin C intake to maintain health and/or to prevent disease [##REF##15316768##101##]. An antioxidant enzyme, SOD2 (Mn-SOD), is constitutively expressed in most cells. The SOD2 polymorphism, 16Val homozygous, may be a predisposing factor for lung cancer, cardiomyopathy, diabetic complications, hypertension, and CVD [##REF##15534883##102##, ####REF##10425186##103##, ##REF##12815947##104##, ##REF##17331249##105####17331249##105##] and may influence longevity [##REF##15621215##106##]. <italic>GPX1 </italic>encodes Gpx1, and may be a target gene for exploring roles of its variants in the etiology of various human diseases [##REF##17156480##107##]. Genetic variations may also affect inflammatory responses. TLR4 is a pattern recognition innate immunity receptor that binds LPS found in gram-negative bacterial walls and possibly oxidized LDL [##REF##14501582##15##]. The Asp299Gly TLR4 polymorphism may decrease the risk of atherosclerosis by reducing TLR4 receptor signaling and subsequent inflammatory response [##REF##16682810##61##,##REF##12124407##108##].</p>", "<p>Thus, genetic variations are widely distributed in various components involved in atherogenesis. The total genetic variations between individuals may differently influence the risk for and the etiology of atherosclerosis and CVD. It may be possible to provide individuals with dietary/therapeutic guidance tailored to their genotypes, given adequate information on the interaction between specific genetic polymorphisms and diet [##REF##16470010##109##]. In other words, genetic variations might predict the significant differences in disease etiology between different species, thus suggesting the limitation of animal studies. Hence, nutrigenetics and nutrigenomics would be new powerful tools for investigating the relations between diseases and genes at individual/intra-species levels.</p>", "<title>Experimental studies of CLA isomers</title>", "<title>Animal studies</title>", "<title>Rabbits</title>", "<p>The possibility that the anti-atherogenic properties of CLA isomers may influence atherosclerotic lesions and blood lipid levels has been tested in animal models.</p>", "<p>Rabbit studies suggest protective and/or therapeutic effects of CLA isomer treatments. Rabbits fed an atherogenic diet and supplemented with CLA isomer mixture (<italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer: <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer = 1:1; 0.5 g CLA diet/day/rabbit) had significantly less aortic fatty lesions and lower levels of plasma triglycerides and LDL-cholesterol, compared to control animals [##REF##7980704##110##]. A rabbit study by Kritchevsky <italic>et al</italic>. [##REF##15588017##46##] also reported reduced atheromatous lesions to the same extent in all CLA-fed groups (90 days): 1% (final dietary concentration) each of the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer, the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer, and the two isomer mixture, compared to control group.</p>", "<p>A dose-dependent effect of CLA isomer mixture (<italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer: <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isome r = 1:1) on atherosclerotic regression was demonstrated in two rabbit studies [##UREF##12##47##,##REF##10953669##111##]. New Zealand white rabbits fed a 0.1% (final dietary concentration) CLA isomer mixture diet after receiving an atherogenic diet, showed an inhibition of atherogenesis, while rabbits fed a 1% CLA mixture diet exhibited a 30% regression of established atherosclerosis [##UREF##12##47##]. Dose-dependent regression of established atherosclerosis was seen in rabbits fed CLA isomer mixtures ranging between 1 and 10 g/kg body weight. However, both serum cholesterol and triglyceride levels were higher in CLA fed groups than in control group, despite a dose-dependent reduction of lipid levels within the range of CLA isomer mixtures [##REF##10953669##111##].</p>", "<title>Mice</title>", "<p>Mouse model studies suggest the anti-atherogenic effects of CLA isomers, and some of those studies indicate that the effects of CLA are tissue- (<italic>i.e</italic>, hepatoxicity described later in this section), isomer-, and dose-specific.</p>", "<p>Atherosclerotic prone strain C57BL/6 mice fed an atherogenic diet containing 2.5 or 5 g/kg body weight CLA isomer mixture (<italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer: <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer = 1:1) for 15 weeks developed higher serum HDL-cholesterol (total cholesterol ratio and lower serum triacylglycerol concentration) than controls. However, despite causing a serum lipoprotein profile considered to be less atherogenic, addition of CLA isomer mixture to the atherogenic diet increased the development of aortic fatty streaks. Mice consuming a diet of 2.5 g CLA isomer mixture/kg body weight, but not 5.0 g CLA isomer mixture/kg body weight, developed a significantly greater area of fatty streaks than the controls [##REF##10434852##112##], suggesting dose-specificity. A study by Arbones-Mainar <italic>et al</italic>. [##REF##16530768##113##] showed isomer-specific effects on the development of atherosclerosis. The <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer diet (1% final dietary concentration for 12 weeks fed to apolipoprotein E knockout mice) increased the values of blood lipid, an inflammatory marker (8-iso prostaglandin E), atherosclerotic plaque, and macrophage content and activation. However, the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer diet (1%) inhibited atherogenic development. Moreover, de Roos <italic>et al</italic>. [##REF##16055499##114##] documented that CLA isomers differentially affect plasma lipid levels as well as the markers of insulin resistance and inflammation in apolipoprotein E knockout mice. The <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer lowered these values suggesting beneficial properties, whereas the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer increased the values indicating detrimental properties. In Nestel <italic>et al</italic>'s study [##REF##16473358##115##] using insulin deficient apoE deficient mouse models, 0.9% (final dietary concentration) <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer diet failed to reduce the severity of aortic atherosclerosis, though plasma triglyceride levels decreased, and HDL cholesterol levels increased.</p>", "<title>Hamsters</title>", "<p>Like mouse models, hamster models have shown protective effects, some of which are isomer-specific. Hamsters fed a CLA isomer mixture diet (<italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer: <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer = 1:1, final dietary concentrations 0.06, 0.11, and 1.1%) showed significantly reduced plasma levels in total cholesterol, non-high-density lipoprotein cholesterol, and triglycerides [##REF##9209699##116##]. In Wilson <italic>et al</italic>'s study [##UREF##21##117##] using hamster models, animals on the hypercholesterolemic diet (HCD) supplemented 1% (final dietary concentration) CLA isomer mixture diet (<italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer: <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer = 1:1) showed 47% fewer aortic fatty streaks and lower plasma cholesterol levels than control. In addition, the CLA isomer mixture diet reduced the development of early aortic atherosclerosis to a greater degree than linoleic acid, possibly through changes in LDL oxidation susceptibility in hypercholesterolemic hamsters. Both the <italic>cis</italic>-9, <italic>trans</italic>-11 and <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer (1% diet of each isomer) fed groups of hamsters had non-significantly decreased fatty streak lesions. However, neither diet affected plasma cholesterol levels [##REF##15919237##118##]. Wilson <italic>et al</italic>. [##REF##16555470##119##] later reported the adverse effects of the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer, but not the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer, suggesting an isomer-dependent effect of CLA on atherogenesis in hypercholesterolemic hamster models. In the Wilson <italic>et al</italic>'s study, hamsters were divided into four groups and were fed for up to 12 weeks: 1) an HCD, 2) an HCD with 0.5% (of diet) <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer, 3) an HCD with 0.5% (of diet) <italic>trans</italic>-10, <italic>cis-</italic>12 CLA isomer, or 4) an HCD with linoleic acid (LA). Both CLA fed groups had lower blood cholesterol levels. However, the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer fed group had higher plasma triglyceride and glucose levels compared with the control at 12-weeks of treatment, while the plasma triglyceride and glucose levels of the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer fed group were reduced. Wilson et al. concluded that the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer may be detrimental if fed separately from the cis-9, trans-11 CLA isomer. In contrast, Navarro <italic>et al</italic>. demonstrated favorable effects of the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer on lipid metabolism in the blood and the liver of hamsters fed an atherogenic diet for 6 weeks and no effects of the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer on the same lipid metabolisms [##REF##15000450##120##]. Studies by Valeille <italic>et al</italic>. [##REF##15778275##121##,##REF##16614421##122##] exhibited the anti-atherogenic and anti-inflammatory effects of the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer in hyperlipidemic hamsters.</p>", "<title>Inter-/intra-species, tissue-, isomer-specificities</title>", "<p>At dietary levels of 0.1–1%, the CLA isomer mixture caused substantial regression of established atherosclerosis in earlier rabbit models [##REF##15588017##46##,##UREF##12##47##,##REF##10953669##111##]. This was a unique and important finding, because once established, aortic lesions in rabbits will regress only under unusual circumstances. Regression of pre-established lesions has never been achieved by dietary means or by simple pharmacologic intervention <italic>in vivo</italic>. However, the use of rabbit models for atherosclerotic studies may not be suitable. Unlike humans, the majority of rabbit blood cholesterol is β-VLDL. Therefore, the aortic lesions caused by feeding atherogenic diets to rabbits may not be comparable to those seen in humans. In contrast, LDLR- or apo-E-deficient mouse models mimic human atherosclerosis [##REF##16270280##123##]. Thus, the effects of dietary CLA isomer supplementation have not been consistent between these different animal models. Even between rats and mice, a different species response to CLA isomers has been indicated. Any response of peroxisome proliferattion to CLA isomers may be greater in mice than in rats [##REF##10566884##124##]. CLA isomers are known to be PPAR activators [##REF##12055356##6##]. Differences in CLA-mediated hepatic gene induction between mice and rats have also been found [##UREF##22##125##]. Hepatic fat accumulation caused by the <italic>trans</italic>-10, <italic>cis-</italic>12 CLA isomer has been reported mainly in mice, and hepatic fat accumulation is associated with the loss of adipose tissue induced by the <italic>trans-</italic>10, <italic>cis</italic>-12 CLA isomer [##REF##17217560##126##]. Adipose tissues are important endocrine organs that produce inflammatory mediators such as TNFα and IL-6 and -8, and adipocytokines (adiponectin and leptin). Adipocytokines are key regulators of insulin resistance. Adiponectin and leptin affect immune and inflammatory functions [##UREF##23##127##]. The dramatic decrease in adiponectin concentrations is important to the development of hepatic steatosis and insulin resistance induced by CLA. Removing CLA from the diet rescued leptin and adiponectin levels and attenuated insulin resistance induced by dietary CLA in mice. However, if a PPARγ activator, rosiglitazone, was added to CLA-TG diet (38.5% <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer), the reduction in adipose mass and serum leptin and adiponectin levels was reversed [##REF##17322064##128##].</p>", "<p>An opposite response to that found in mice, CLA mixture diet (39.2% the <italic>cis</italic>-9, <italic>trans</italic>-11 and 38.5% <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomers) reduces hepatic steatosis and plasma lipids in rats [##REF##16711598##129##,##REF##17368879##130##]. Beyond rodent models, the genetic differences between mice and humans should be considered. For example, mice contain more copies of cytochrome P450 than do humans [##UREF##24##131##]. Cytochrome P450 is involved in microsomal ω-oxidation of fatty acids, eicosanoid synthesis, and detoxification of xenobiotics. The <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer significantly reduces cytochrome P450 gene expression in mouse livers, and the reduction may contribute to CLA-induced fatty livers as well as the induction of enzymes associated with fatty acid synthesis [##REF##17217560##126##]. Thus, not only are there differences in CLA-mediated cytochrome P450 gene expression, there are additional differences in fatty acid metabolism and eicosanoid formation, between humans and mice. As described in Section 6, single nucleotide polymorphisms (SNPs) among human individuals, such as SNPs in <italic>APOA1</italic>, <italic>PPARA</italic>, <italic>PPARG</italic>, <italic>SOD2</italic>, <italic>Gpx1</italic>, and <italic>TLR4</italic>, may also cause differences in lipid metabolism and the risk for atherosclerosis. In addition, the age of animals fed CLA and examined may be another consideration. Many atherosclerotic studies used adolescent individuals for their animal models. Adolescent animals are still growing; their body composition is still changing. The gene expression profile and sensitivity to and metabolism of chemicals in a developmental stage differ from those in adults. Such differences may make the extrapolation to humans from animals and explanations of study results more difficult. Thus, there are several factors to be considered when investigating the effects of CLA isomers as therapeutic or chemopreventive agents for atherosclerosis: dose-dependency and isomer-specificity, as well as inter- and intra-species differences. Therefore, genetic and genomic research using human subjects and/or human cells are urgently needed to determine the effects of each isomer.</p>", "<title>Human Studies</title>", "<p>CLA is being sold as a panacea with several alleged benefits including altering body composition, <italic>i.e</italic>., to reducing obesity and building lean body mass [##UREF##25##132##]. Safety of long-term (≥ 12 months) CLA supplementation was examined in several clinical trials. A randomized, double-blind study was conducted, in which obese individuals were given 6 g/day of either CLA isomer mixture (<italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50) or placebo (high oleic sunflower oil) for 12 months. Although body composition did not differ between the CLA-supplemented group (n = 27) or the placebo group (n = 23), lower levels of adverse effects (alterations in the liver function, glucose and insulin levels, insulin resistance, and white blood cell counts) were observed in the CLA-supplemented group than in the control group. The investigators concluded that CLA isomer mixture as Clarinol™ is safe for use in obese humans for up to one year at the recommended dosage [##REF##15354322##133##]. Another long-term (one year) CLA isomer mixture supplementation study was performed in a double-blind fashion [##REF##15159244##134##]. Healthy overweight humans (n = 180) were randomly divided into three groups: 1) CLA free fatty acid (<italic>cis</italic>-9,<italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; 3.6 g CLA isomers/day as FFA forms), 2) CLA-triacylglycerol group (<italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; 3.4 g CLA isomers/day as TAG forms), and 3) placebo (olive oil). The CLA isomer mixture supplementation decreased body fat mass in healthy overweight adult humans. However, there were significant increases in: LDL levels in the CLA-FFA group, HDL levels in the CLA-TAG group, and lipoprotein levels in both CLA groups. Adverse effects, mostly gastrointestinal, were reported by 11.4% of the subjects, and likely resulted from the daily ingestion of oil or of the gelatin capsule alone. Overall, the adverse effects did not differ significantly between the CLA groups and the placebo group, indicating that CLA isomer mixture was tolerated as well as olive oil as the control. One hundred twenty five of 180 subjects who finished this study, continuously participated in the CLA isomer mixture supplementation study for an additional year, thus, total 2 years [##REF##15795434##135##]. Two-year-CLA isomer mixture supplementation groups significantly reduced body weight, BMI, body fat mass, energy intake and serum leptin levels, compared with the baselines at month 0. However, serum lipoprotein and aspartate amino transferase levels, and whole blood leukocyte and thrombocyte counts were significantly increased in the CLA groups. Gaullier et al. concluded that CLA isomer mixture supplementation for 24 months in healthy, overweight adults was well-tolerated, and that CLA isomer mixture may be beneficial as a weight loss supplement. Another one-year CLA isomer mixture supplementation study [##UREF##26##136##] was conducted in a randomized, double-blind, placebo-controlled fashion. No significant differences in body weight or body fat regain were observed between the CLA group (<italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; 3.4 g/day as TAG forms; n = 40) and placebo (4.5 g olive oil; n = 43). No significant differences in adverse effects or indexes of insulin resistance were observed between the groups. However, a significant increase in the number of leukocytes was observed in the CLA group. Although the investigators did not obtain a perfect group match for body weight at randomization, they concluded that the CLA isomer mixture supplementation for one year has no preventative effect on body weight and body fat regain after the weight loss induced by a low calorie diet for eight weeks in obese subjects.</p>", "<p>Many studies have investigated the effects of short-term (mostly 12 weeks or 8 weeks) CLA supplementation. In a six-month double-blind CLA isomer mixture supplementation study [##REF##17313718##137##], 118 healthy overweight and obese adult humans were randomized into two groups supplemented with either 3.4 g/day CLA isomer mixture (<italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50) or placebo. CLA significantly decreased body fat mass, in particular in legs of both males and females and in females with BMI &gt;30 kg/m², at either month 3 or 6, compared with placebo. Lean body mass increased in the CLA supplemented group. The safety parameters including blood lipids, inflammatory and diabetogenic markers remained within the normal range, and adverse events did not differ between the groups in the study. It was concluded that the CLA isomer mixture supplementation in healthy, overweight, and obese subjects decreases body fat mass in specific regions and was well tolerated. The dose-dependent effects of CLA were reported in a CLA isomer mixture supplementation study of 12 weeks [##REF##17449580##138##]. Forty eight obese subjects were divided into three groups: 1) 3.2 g/day CLA (<italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50), 2) 6.4 g/day CLA, and 3) placebo (8 g safflower oil). CLA isomer mixture supplementation at the higher dose increased inflammatory markers, IL-6 and C-reactive protein (CRP), however, remained within normal ranges. A significant increase in lean body mass was also found in the same treatment group. No severe adverse effects were reported. The authors concluded that the CLA isomer mixture intervention was well-tolerated. Beneficial effects on immune functions have been reported in a double-blind, randomized CLA isomer mixture supplementation study [##REF##15674307##139##]. Twenty-eight healthy adults received either high oleic sunflower oil (placebo) or 3.0 g/day CLA (<italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; triglyceride form) for 12 weeks. The CLA group showed significantly reduced levels of the proinflammatory cytokines, TNF-α and IL-β, and increased levels of the anti-inflammatory cytokine, IL-10. Immunoglobulin levels were also altered: CLA isomer mixture decreased Ig E levels, and increased both Ig M and Ig A levels. Another CLA isomer mixture supplementation study (2.2 g/day; <italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; 8 weeks) investigated the effects of CLA isomer mixture on inflammation in a double-blind, randomized, placebo-controlled model using healthy middle-aged males [##REF##17368881##140##]. The CLA isomer mixture supplementation significantly reduced concanavalin A-stimulated peripheral blood mononuclear cell IL-2 secretion, suggesting anti-inflammatory and anti-atherogenic effects of CLA isomer mixture. Other inflammatory markers, IL-6, CRP, and fibrinogen, were not affected in this study. Moloney <italic>et al</italic>. [##REF##15447895##141##] demonstrated that the CLA isomer mixture supplementation (3.0 g/day; <italic>cis-</italic>9, <italic>trans</italic>-11: <italic>trans-</italic>10, <italic>cis-</italic>12 = 50:50; 8 weeks) increased total HDL cholesterol concentrations and decreased the ratio of LDL cholesterol to HDL cholesterol without changes in inflammatory markers of CVD in subjects with type 2 diabetes. However, this CLA isomer mixture intervention did not show positive effects on insulin and glucose concentrations among the diabetic patients. In a Swedish study, 53 healthy humans were randomly assigned to CLA isomer mixture supplementation (4.2 g/day; <italic>cis-</italic>9, <italic>trans</italic>-11: <italic>trans-</italic>10, <italic>cis-</italic>12 = 50:50; 12 weeks) in a double-blind fashion. Supplementation with a CLA isomer mixture reduced the proportion of body fat and affected fatty acid metabolism. However, no effects were found for CLA isomer mixture on body weight, serum lipids, glucose metabolism or plasminogen activator inhibitor 1 [##REF##11592727##142##]. In Noone <italic>et al</italic>.'s double-blind placebo-controlled study [##UREF##27##143##], the CLA isomer mixture treatment (3 g/day; cis-9, trans-11:trans-10, cis-12-CLA = 50:50; 8 weeks) showed reduced plasma triacylglycerol levels in normolipaemic human subjects.</p>", "<p>A study using 49 healthy male subjects showed the isomer-/dose-dependent (0.59, 1.19, 2.38 g/day of the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer; 0.63, 1.26, 2.52 g/day of the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer; 8 weeks) opposite effects of CLA on plasma total cholesterol and LDL-cholesterol levels: hypolipidemic properties of the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer and hyperlipidemic properties of the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer. However, neither CLA isomer supplementation affected insulin resistance [##UREF##28##144##]. Using the same healthy male subjects and the same supplementation design, Tricon <italic>et al</italic>. investigated the effects of two CLA isomers on immune cell functions [##REF##15585778##145##]. The results showed a dose-dependent reduction in the mitogen-induced activation of T lymphocytes and a negative relationship between the mitogen-induced T lymphocyte activation and the contents of each CLA isomer in mononuclear cells, suggesting beneficial effects in inflammatory diseases such as atherosclerosis.</p>", "<p>Additional adverse effects of CLA supplementation, in particular <italic>trans</italic>-10, <italic>cis</italic>-12 CLA, were reported. Riserus <italic>et al</italic>. demonstrated that the purified trans-10, cis-12 CLA isomer supplementation (3.4 g/day, 3 months), but not CLA mixture supplementation (3.4 g/day; <italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; FFA form, 3 months), increased oxidative stress, CRP, and proinsulin levels, and decreased insulin sensitivity in non-diabetic abdominally obese males [##REF##15168020##146##] and in males with metabolic syndrome [##REF##12370214##147##] in two double-blind, randomized, placebo- (3.4 g/day, olive oil) controlled studies. Like the study by Tricon et al. [##UREF##28##144##], Riserus <italic>et al</italic>.'s two studies also suggest the isomer-dependent detrimental effects of CLA. Another unfavorable effect of the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer was also reported in a human study examining non-enzymatic and enzymatic lipid peroxidation (8-iso-PGF_2αand 15-keto-dihydro-PGF_2α,respectively) in human plasma and urine. Sixty healthy subjects were divided into six groups: three CLA isomer mixture groups, (3.5 g/day, <italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50, 4 weeks) and three trans-10, cis-12 CLA isomer groups (4.0 g of the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer/day, 4 weeks): 1) the CLA supplement alone, 2) with vitamin E (D-α-tocopherol acetate), and 3) with COX-2 inhibitor (refecoxib). Although both CLA isomer mixture and the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer supplementations increased the eicosanoid levels in the urine, the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer supplementation with the COX-2 inhibitor suppressed the increase in urinary 15-keto-dihydro-PGF_2αlevels. This result suggests that increased lipid peroxidation in eicosanoid synthesis may be due to induced COX-2 expression by the CLA supplementations, in particular the <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer [##UREF##29##148##]. Taylor <italic>et al</italic>. [##REF##16339498##149##] documented that CLA isomer mixture supplementation (4.5 g/day; <italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50; 12 weeks) impaired endothelial function and increased markers of oxidative stress in 40 healthy white males, suggesting caution in the use of CLA isomers as an aid for weight loss.</p>", "<p>Overall, the effects of CLA isomers (or mixture) on atherogenic and/or inflammatory parameters in humans have not been definitive. Although a meta-analysis of 18 CLA human studies (including three single isomer studies) suggests the beneficial use of CLA isomers only as a body fat reducing supplement [##REF##17490954##150##], the therapeutic potentials of CLA isomers in inflammatory diseases including atherosclerosis remain to be determined. Differences in purity and content of CLA isomers may cause these conflicting results. Impurities might induce undesirable side effects [##REF##12558050##151##]. The variety of CLA isomer content in supplements and/or the differences in CLA dose might cause inconsistent results due to the dose- and/or isomer-dependent effects of CLA suggested by some other studies [##REF##17449580##138##,##UREF##28##144##,##REF##15168020##146##,##REF##12370214##147##]. Human subjects were not limited in diet (therefore, dietary fat intake, excluding supplemental fat intake, is of concern) and/or physical activities in some study designs. In addition, CLA isomer (or mixture) supplementations contained other fatty acids, including PUFAs and saturated fatty acids, at up to 20% in some study designs. The details of supplemental contents, other than CLA isomers, are not even provided in some other studies. Since CLA isomers are incorporated into membrane phospholipids, they may compete in enlongation and desaturation steps with other PUFAs that are precursors of arachidonic acid (AA, 20:3, ω-6). The competition in the incorporation may alter eicosanoid biosynthesis [##REF##9590630##152##], therefore, subsequent immune and inflammatory processes. An experiment by Brown <italic>et al</italic>. [##REF##11448613##153##] found that the presence of linoleic acid (LA) may affect the possible benefits of CLA isomers. LA, one of the PUFAs present in Western diets and the human body is a possible antagonist to CLA isomers. The plentiful LA may exclude CLA isomers from incorporation into phospholipids and drive it into storage as a component of neutral lipid [##REF##11441132##52##]. LA also inhibits EPA incorporation in membrane phospholipids from fish-oil supplements [##UREF##15##54##]. Like CLA isomers, dietary EPA and DHA partially replace AA derived from LA in the cell membrane. These ω-3 fatty acids are associated with decreased risk for CVD, and reduce the formation of pro-inflammatory eicosanoids [##UREF##14##53##]. The replacement of AA by ω-3 fatty acids may cause the alteration of fatty acid composition in membrane lipid bilayers influencing signaling pathways and subsequent immune and inflammatory processes. The anti-inflammatory effects of CLA isomers observed in a limited number of studies may be attributed to the replacement of AA generated by LA. In addition, saturated fatty acids have been reported to provoke inflammation by inducing pro-inflammatory gene expression through innate immune receptor (TLRs) activation [##REF##16682810##61##]. Thus, the coexistence of other fatty acids might potentially affect the results of any human studies with CLA isomers. Moreover, there may be divergent effects of CLA isomers in obese or diabetic subjects compared to the normal-weight or healthy subjects as well as differences determined by gender and/or genetics, <italic>i.e</italic>., SNPs in related genes. Further studies are needed to investigate the effectiveness and safety of CLA supplementation and to elucidate these confounding factors.</p>", "<title>CLA mediated gene expression</title>", "<p><italic>Adiposity plays an important role in fatty </italic>acid mobilization, fat storage, and formation of pro-and anti-inflammatory cytokines and chemokines [##REF##17322064##128##]. As mentioned above, atherosclerosis is viewed as a chronic inflammatory disease affecting lipid profiles. CLA isomers have been shown to influence lipid metabolism associated with inflammation and atherogenesis in <italic>in vitro </italic>studies. One possible mechanism by which CLA isomers could modulate atherogenesis is regulating the production of lipoproteins in the liver. Sterol element binding proteins (SREBP) are a group of membrane-bound transcription factors that bind to their specific DNA binding sites (SRE-1) to activate the expression of target genes that encode enzymes necessary for lipid synthesis, including the LDL receptor (LDLR) gene in sterol-depleted cells [##REF##8390995##154##]. A study by Ringseis et al. [##UREF##30##155##] reported that the <italic>trans-</italic>10, <italic>cis</italic>-12 CLA isomer, not the <italic>cis</italic>-9, <italic>trans</italic>-11 CLA isomer, induced LDLR gene expression via SREBP-2 in human hepatoma cells (HepG2). They concluded that the enhanced uptake of VLDL and LDL cholesterols by hepatic LDLR may account for the decreased plasma cholesterol levels in response to CLA isomer (or mixture) supplementations in a limited number of human and animal studies. An alternative pathway for CLA-mediated LDLR expression is also suggested. Yu-Poth et al. [##REF##14704295##156##] demonstrated that a CLA isomer mixture (50:50, 400 μmol/L final concentration) up-regulated LDL receptor (LDLR) mRNA and protein expression at three- to five-fold in HepG2 cells. The results of the study suggest the upregulation of the LDLR gene by CLA through a mechanism that is independent of SREBP-1 and acyl CoA: cholesterol acyltransferase (ACAT).</p>", "<p>Monocyte-endothalial interaction is a key step of atherogenesis. However, CLA isomers showed no effects on TNFα-induced adhesion molecule expression, monocyte adhesion, and chemokine release or on the molecular mechanisms regulating these processes in human aortic endothelial cells [##REF##16219313##21##]. This suggests that the anti-atherogenic effects of CLA isomers may not be associated with the reduction of monocyte-endothelial interactions.</p>", "<p>Several studies have investigated the implication of CLA isomers in eicosanoid synthesis and the role of CLA isomers in inflammation and atherogenesis. Dietary CLA may suppress the biosynthetic pathway of AA. CLA may suppress eicosanoid formation via direct action on COX and LOX, <italic>i.e</italic>., by inhibiting the expression or the activities of these enzymes [##REF##12468364##5##,##REF##12055356##6##]. Constitutive COX-1 and inducible COX-2 catalyze the conversion of free PUFAs to prostanoids, while LOX generates the leukotrienes. The <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer suppresses COX-2 expression and PGE₂release in rat macrophages either by inhibiting NF-κB activation <italic>in vivo </italic>and <italic>in vitro </italic>or by inhibiting the MAPK/ERK/JNK pathway. The trans-10, cis-12 CLA isomer inhibits the NF-κB p50 and p65 subunits binding to DNA [##UREF##19##83##]. The 50:50 mixture of CLA isomers inhibits the expression of both COX-2 and inducible nitric oxide synthase (iNOS) in LPS activated murine macrophages, resulting in decreases in prostaglandin E₂and NO synthesis [##REF##12468265##157##]. The effects of CLA on prostanoid formation can be either inhibitory or stimulatory, depending on isomer-specificity, chemical forms of CLA isomers (<italic>i.e</italic>., free fatty acid or esterified forms), or cellular states (i.e., resting or stimulated states) in human endothelial cells and platelets [##REF##12676356##158##]. CLA isomers have also been reported to reduce prostaglandin E2 synthesis in certain cell types in both humans and mice [##REF##15134143##159##].</p>", "<p>The beneficial effects of CLA isomers may be attributed to their properties as PPARα/γ activators [##REF##12468364##5##,##REF##16698153##48##,##UREF##30##155##,##UREF##31##160##]. Structurally, CLA resembles 13-HODE, as well as 15-HETE and 15d-PGJ2, which were all identified as natural activators of PPARγ [##REF##15362034##49##]. Ringseis et al[##UREF##31##160##] demonstrated that either the <italic>cis</italic>-9, <italic>trans</italic>-11 or <italic>trans</italic>-10, <italic>cis</italic>-12 CLA isomer (50 μmol/L) reduced AA proportions in human vascular smooth muscle cells (SMCs), TNFα-induced NF-κB DNA binding activity, mRNA levels of enzymes involved in eicosanoid synthesis (<italic>e.g</italic>., COX-2), and production of PGE2 and PGI2. These CLA isomer treatments increased PPARγ DNA binding activity. Furthermore, a PPARγ repressor suppressed the inhibitory actions on the eicosanoid formation and NF-κB DNA binding activity in the SMCs. Synthetic PPAR activators exert their anti-inflammtory actions, at least in part, by negatively regulating NF-κB activation [##REF##12468265##157##]. PPARγ and NF-κB may be involved in regulating genes, whose products influence ROS generation that contributes to inflammation and atherogenesis, and these transcription factors coordinate and propagate feedback loops between each other. Thus, anti-inflammatory and anti-atherogenic effects of CLA isomers may be associated with these redox-sensitive transcription factors.</p>", "<p>Although CLA isomers and ω-3 PUFAs have shown anti-inflammatory effects, they differ in the nature of their immunomodulatory properties. CLA isomers appear to enhance immune function, while ω-3 PUFAs are immunosuppressive [##REF##12468364##5##]. Tian <italic>et al</italic>.'s study [##REF##16540100##51##] using rats treated with 300 mg/kg/day of clofibrate, a PPARα activator, for up to 14 days, reported an increase in myocardial DHA proportion and a decrease in the portion of AA that is a precursor of pro-inflammatory eicosanoids (<italic>e.g</italic>., leukotriene B4 and prostaglandin E2). Tian <italic>et al</italic>. implicate enhanced uptake of ω-3 PUFAs from blood circulation and/or increased biosynthesis of ω-3 PUFAs in rats treated with the PPARα activator, in those results. Similarly, Attar-Bashi <italic>et al</italic>.'s human study [##REF##17275274##161##] investigated the effects of CLA isomers mixture [3.2 g/day, <italic>cis</italic>-9, <italic>trans</italic>-11: <italic>trans</italic>-10, <italic>cis</italic>-12 = 50:50, plus 11 g of alpha-linoleic acid (ALA), 8 weeks] as PPARα activators on DHA (22:6, ω-3) and EPA (20:5, ω-3) biosynthesis from ALA (18:3, ω-3) through Δ5- and Δ6-desaturases, both of which are possible PPARα target genes. The study demonstrated that ALA (18:3, ω-3) plus CLA isomer mixture increased EPA and decreased AA. However, the CLA isomer mixture supplementation did not affect DHA biosynthesis in humans. DHA synthesis from ALA needs additional peroxisomal oxidation. Thus, CLA isomers may play a role in PPARα-mediated gene expression and ω-3 PUFA-mediated anti-inflammatory effects.</p>", "<p>CLA isomers are readily metabolized <italic>in vivo </italic>via multiple pathways, and enlongated and desaturated metabolites of CLA have been detected in the liver and mammary tissue of rats and adipose tissue and sera of humans [##REF##12055356##6##]. Some studies have suggested the involvement of CLA metabolites in anti-atherogenic and ant-inflammatory processes [##REF##12468364##5##,##UREF##31##160##], though the Δ6-desaturase metabolites of CLA may not be important for the alterations in gene expression induced by CLA [##REF##12055356##6##].</p>", "<p>Thus, multiple signaling pathways, such as PPARα, PPARγ, NF-κB, and MAPK/ERK/JNK, may be involved in the anti-inflammatory and anti-atherosclerotic effects of CLA isomers.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>YKN, NF-D and STO designed and wrote this manuscript. YKN and NF-D conceived and participated in the design and coordination of the literature review. All authors read and approved the final manuscripts.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported in part by USDA/ARS, USDA-IFAFS #52100-9638 and the Nevada Experimental Station, University of Nevada, Reno.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Chemical structures of linoleic acid and isomers of conjugated acid (CLA).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Vascular events leading to the development of atherosclerotic lesions. </bold>Low density lipoprotein (LDL), scavenger receptor (SR).</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Metabolic pathways for the formation of prostaglandins, thromboxanes, and leukotrienes. </bold>Prostaglandin H₂(COX), lipoxygenase (LOX), 12-hydroperoxyeicosatetraenoate (12-HPETE), 5-hydroperoxyeicosatetraenoate (5-HPETE).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Role of PPARγ.</bold> Peroxisome proliferator response element (PPRE), retinoic X receptor (RXR), retinoic acid (RA), ligands (L).</p></caption></fig>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Bacterial endosymbionts currently attain a lot of interest, because of their widespread occurrence in arthropod hosts in which they often manipulate reproduction [##REF##16448417##1##,##REF##10547686##2##]. They are predominantly vertically transmitted from mother to offspring, although the lack between phylogenies of host and endosymbionts indicates that horizontal transfer should be possible [##REF##16448417##1##,##REF##10547686##2##]. The genera <italic>Wolbachia </italic>[##REF##10547686##2##,##REF##12683975##3##] and <italic>Rickettsia </italic>[##UREF##0##4##] belong to the best studied endosymbionts. Reproductive manipulations by these endosymbionts comprise parthenogenesis (i.e. infected virgin females produce daughters), feminization (infected genetic males reproduce as females), cytoplasmatic incompatibility (CI; in its simplest form a cross between infected male and an uninfected female results in the death of embryos), and male killing (i.e. infected male embryos die and female embryos develop into infected females). In arthropods, they are considered as selfish elements that enhance their own transmission to the disadvantage of the rest of the genome [##UREF##1##5##, ####REF##21227262##6##, ##REF##11483984##7####11483984##7##] and strongly act as an evolutionary force on their hosts [##UREF##2##8##, ####UREF##3##9##, ##UREF##4##10##, ##REF##10762384##11##, ##REF##16405591##12##, ##REF##17151259##13####17151259##13##].</p>", "<p>When the transmission efficiency from mother to offspring is (nearly) perfect [##UREF##4##10##,##UREF##5##14##, ####REF##10849086##15##, ##UREF##6##16##, ##REF##12487358##17####12487358##17##], male-killing bacteria are expected to approach fixation when benefits for surviving daughters stem from the death of their male kin [##UREF##1##5##,##UREF##7##18##]. They then vanish as the host population crashes [##UREF##1##5##,##REF##12487358##17##, ####UREF##7##18##, ##UREF##8##19##, ##REF##10905965##20####10905965##20##]. However, hosts do not reach extinction under these conditions if there is strong selection to prevent transmission of the parasite (e.g. through sexual selection of non-infected mates [##REF##12683975##3##]) or when the phenotype is suppressed by host genes [##REF##10762384##11##,##REF##16933972##21##,##REF##7498773##22##]. Turelli &amp; Hoffmann [##REF##7498773##22##] reported strong variation in transmission efficiency for CI-inducing endosymbionts between laboratory cultures and natural populations. Such variation can also be expected in male killing endosymbionts. Therefore, endosymbiont transmission rates may vary with temporal or spatial changes in the environment [##REF##12487358##17##] and male killer prevalence will be reduced because some males always survive. It remains, however, an open question why many natural host populations that lack these defense mechanisms can persist in spite of high infection rates.</p>", "<p>Male-killing bacteria are generally thought to attain low to intermediate prevalence in transient natural populations with only mild effects on host population sex ratio [##REF##10905965##20##]. Strong heterogeneity in infection rates at intermediate spatial scales has been reported [##UREF##6##16##,##REF##10905965##20##,##REF##10840973##23##, ####UREF##9##24##, ##REF##17174921##25##, ##UREF##10##26####10##26##]. Charlat and colleagues [##REF##17174921##25##] recently discovered that interactions with CI-inducing endosymbionts may explain natural variation in male killer prevalence in the butterfly <italic>Hypolimnas bolina</italic>. Similar natural variation in male-killing <italic>Wolbachia</italic>-infection was found in <italic>Drosophila </italic>[##REF##15571631##27##]. Interestingly, the latter found complete absence of infections in some populations despite the absence of resistance mechanisms.</p>", "<p>How spatial structure affects the spread of male-killing endosymbionts is poorly documented. In general, imperfect maternal inheritance and direct physiological costs to infection are acknowledged to impede their spread within local populations [##REF##12683975##3##]. Groenenboom &amp; Hogeweg [##UREF##11##28##] showed that a perfectly transmitted male-killer may invade in a single population with spatial structure (i.e. taking into account neighboring interactions between individuals) without driving the population to extinction. The emerging pattern formation by hosts is here responsible for its persistence under conditions of perfect transmission and fitness compensation. However, because (i) individual interactions in spatially structured insect populations go beyond direct neighbors and (ii) high dispersal rates between populations are necessary for metapopulation dynamics [##UREF##12##29##], it is doubtful that the local-scale mechanisms presented by [##UREF##11##28##] can be acknowledged as potential reasons for the presence of high male killer prevalence in natural insect populations.</p>", "<p>Dispersal is an important trait within a metapopulation context that is influenced by various selective pressures [##REF##15921049##30##,##UREF##13##31##]. These comprise avoidance of competition for resources [##UREF##14##32##], minimizing kin competition [##UREF##15##33##, ####REF##7078219##34##, ##REF##3626575##35##, ##REF##15560914##36##, ##UREF##16##37####16##37##], inbreeding avoidance [##REF##10506544##38##] or coping with temporal variability of resource availability [##UREF##17##39##, ####UREF##18##40##, ##REF##10433892##41####10433892##41##]. In general, individuals should disperse as long as their (inclusive) fitness expectations are higher outside their natal habitat [##UREF##19##42##,##UREF##20##43##]. Consequently, when dispersal costs are higher than expected fitness (e.g., due to high dispersal mortality) dispersal is disfavored (e.g., [##UREF##13##31##,##UREF##18##40##]). Dispersal rates therefore increase with increasing environmental stochasticity or external extinction probability and decrease when dispersal costs (dispersal mortality) increase (e.g. [##UREF##16##37##,##UREF##20##43##,##REF##12776889##44##]).</p>", "<p>Male killing endosymbionts affect host reproduction by relaxing offspring competition (both between kin [##UREF##1##5##,##UREF##7##18##,##UREF##21##45##] but also between non-kin [##UREF##22##46##]), altering sex ratio [##UREF##4##10##,##UREF##21##45##] and subsequent the within-population genetic structure [##REF##17151259##13##]. Because these manipulation are expected to influence the evolution of host dispersal strategies under different conditions of environmental stochasticity and dispersal mortality, we questioned (i) under which of these conditions male killing infections affect the evolution of dispersal rates, (ii) whether and under which environmental conditions male killing endosymbionts get fixated (host extinction) or disappear (curing) and (iii) under which of these condition high among-patch variation in infection prevalence can be retrieved. Our analyses are built on an individual-based model simulating the evolution of dispersal strategies in metapopulations under different levels of environmental stochasticity and dispersal mortality.</p>" ]

[ "<title>Methods</title>", "<title>The model</title>", "<title>The landscape</title>", "<p>For our simulation experiments we used an extended version of an individual-based model of insect dispersal in patchy landscapes of 100 habitat patches (<italic>n</italic>) with carrying capacities <italic>K </italic>[##REF##10849086##15##, ####UREF##6##16##, ##REF##12487358##17####12487358##17##]. Patch capacity was set to <italic>K </italic>= 100 individuals.</p>", "<title>The individual</title>", "<p>Each individual is characterized by its sex, its affiliation with a specific patch (<italic>i</italic>), by four alleles at two different diploid loci that determine male (<italic>d</italic>_{<italic>m</italic>}), respectively female (<italic>d</italic>_{<italic>f</italic>}) dispersal propensity. The allele values were initially randomly drawn from a uniform distribution [0–1]. Further, individuals are characterized by their infection status (infected versus uninfected) which they solely inherit from their mother. In our model, individuals simultaneously disperse before mating and production of offspring; each individual has only one opportunity to disperse. Dispersing individuals die with a probability <italic>μ </italic>(dispersal mortality), regardless of patch origin.</p>", "<title>Population dynamics</title>", "<p>Local population dynamics are governed by density-dependent reproduction of individuals. After mating with a randomly drawn local male (thus allowing polygamy), a female gives birth to Λ offspring, where Λ is a Poisson-distributed number with a patch- and time-specific mean, Λ_mean(<italic>t</italic>, patch). For each generation, the mean value of Λ_mean(<italic>t</italic>, patch) is drawn from a lognormal distribution with mean <italic>λ </italic>and a standard deviation <italic>σ</italic>. In our simulations, <italic>λ </italic>was set to 4, a value typical for arthropod demography. <italic>σ </italic>subsequently determines the degree of environmental fluctuations which are assumed to be uncorrelated in space and time. Offspring are randomly assigned to the male or female sex, but male offspring from infected females die immediately after conception. Remaining offspring develop into mature individuals with a density-dependent survival probability <italic>s</italic>:</p>", "<p></p>", "<p>Here <italic>N</italic>_{<italic>i </italic>}represents the expected population size in patch <italic>i. K is </italic>the carrying capacity of patch <italic>i </italic>(identical for all patches). This means that there is no fitness benefit for infected females, but for groups with infected females, population growth increases as female offspring are released from competition with males.</p>", "<title>Dispersal</title>", "<p>After all individuals have reached maturity, they disperse according to their genetically determined dispersal probability <italic>d </italic>(i.e., according to mean value of their sex-specific dispersal allele, <italic>d</italic>_{<italic>m </italic>}or <italic>d</italic>_{<italic>f</italic>}). The dispersal alleles were freely recombined during reproduction. We assume global dispersal; that is, a successful disperser reaches any patch in the landscape (except its home patch) with the same probability (1-<italic>μ</italic>)/(<italic>n-1</italic>). Dispersal probability was sex-specific and unconditional, i.e. assuming dispersing arthropods taking their decision without taking into account any information from the patch. Dispersal alleles were allowed to change by mutation, thus allowing for the evolution of sex-specific dispersal strategies. We implemented sex-specific dispersal because we expect male-killing endosymbionts to affect both local demography and sex-ratio, thereby potentially inducing different 'games' for males and females.</p>", "<title>Mutation rate and stochasticity</title>", "<p>To promote greater variability of genotypes in the first generations and to reduce the influence of mutations on the stability of the final result, we let mutation rates exponentially decrease from ~0.1 to &lt; 0.001 over the course of the simulation experiments (5000 generations; see e.g. [##UREF##6##16##]). A mutation comprises a shift towards a new random value from the initial uniform [0–1] distribution. No external catastrophes were simulated; instead we allowed demographic stochasticity and environmentally caused fluctuations (0 ≤ <italic>σ </italic>≤ 5) in offspring number (Λ).</p>", "<title>Simulation experiment</title>", "<p>We ran scenarios to test whether the presence of infections in the metapopulation influenced the dispersal rate of hosts, the metapopulation extinction probability and the eventual rate of infection. Therefore, simulations were run either without infections (<italic>I </italic>= 0) or with an initial female infection rate <italic>I </italic>= 0.10 randomly distributed over patches. Simulations for both scenarios were replicated (n = 100) for dispersal mortality and environmental stochasticity (Table ##TAB##0##1##). Because low or high initial infection rates allow for high rates of respectively curing or metapopulation extinction just by demographic fluctuations, we ran sensitivity analyses for relevant ranges of <italic>I </italic>and <italic>K </italic>(Table ##TAB##0##1##).</p>", "<p>Host infection rates were calculated as the number of infected females/total population size, sex-ratio as the number of females/total population size. Metapopulation extinction probability was calculated as the number of simulation runs with metapopulation extinctions divided by the total number of replicates for the respective scenario. Other metapopulation parameters were only estimated for the surviving ones.</p>" ]

[ "<title>Results</title>", "<p>The evolving mean population dispersal probabilities approached equilibrium after less than 2000 generations in all simulation experiments. Similarly, sex ratio, the proportion of infected individuals, and the number of infected populations stabilized after this number of simulation steps. The equilibrium fraction of occupied patches was in all cases, excluding extinct metapopulations, larger than 92% (lowest value 92.4% for <italic>μ </italic>= 0.3, <italic>σ </italic>= 4). In the reference simulation (no endosymbiont invasion), all patches were occupied under all conditions. The invasion of male-killing endosymbionts led to increased dispersal rates (Fig ##FIG##0##1##), especially under conditions of high <italic>μ </italic>and low <italic>σ</italic>. The increase was pronounced for males (Fig ##FIG##0##1A##<italic>versus </italic>Fig ##FIG##0##1C##) compared to females (Fig ##FIG##0##1B##<italic>versus </italic>Fig ##FIG##0##1D##).</p>", "<p>While extinction did not occur under reference simulations, the invasion of male-killing endosymbionts led to frequent metapopulation extinction under conditions of low <italic>μ </italic>and high <italic>σ </italic>(Fig. ##FIG##1##2A##). These are conditions that favor high host emigration and thus create more or less a panmictic population structure. Under conditions of high dispersal, metapopulations also occasionally lose endosymbiont infections stochastically and are therefore rescued from eventual extinction. In the case of low dispersal rates, fast deterministic extinction of infected populations may result in the extinction ('curing') of the endosymbiont (Fig. ##FIG##1##2B##).</p>", "<p>With more moderate emigration probabilities evolving (<italic>μ</italic>, <italic>σ </italic>both low, or intermediate <italic>μ </italic>and high <italic>σ</italic>), our simulations predict that endosymbionts reach infection rates beyond 80% in non extinct host or endosymbiont metapopulations (Fig ##FIG##2##3A##). Similarly, sex-ratio's become highly skewed towards females under such conditions (Fig. ##FIG##2##3B##). Clearly, among population variation in infection-rates (i.e. number of infected females/total population size) within surviving metapopulations is highest under conditions of high <italic>μ </italic>and low <italic>σ </italic>(with a considerable fraction of infection free populations; Fig. ##FIG##3##4##) and becomes more homogenous with generally high local infection rates in the surviving metapopulations as emigration probabilities go up (low <italic>μ </italic>and high <italic>σ</italic>).</p>" ]

[ "<title>Discussion</title>", "<p>Our simulations show that the invasion of male-killing endosymbionts in a host metapopulation affects the evolution of host dispersal rates. The overall infection rates will depend on the prevailing environmental stochasticity and dispersal mortality. Under conditions supportive for high dispersal in the host population, extinction of the whole host metapopulation, and consequently the parasite population too, become highly probable. In contrast, the probability of endosymbiont extinction increases under conditions that disfavor high dispersal.</p>", "<p>Extinction of the host metapopulation under high dispersal rates, which create a panmictic population structure, is similar as for mathematical models that considered single-population dynamics [##UREF##1##5##,##REF##10762384##11##]. However, the more important results of our simulations is (i) that low dispersal rates may lead to a deterministic extinction (curing) of the endosymbiont and that (ii) high infection rates may not necessarily lead to the extinction of the entire host (meta)population. As previously documented [##UREF##13##31##], emigration probability increases with decreasing costs of dispersal (<italic>μ</italic>) and increasing environmental variability (<italic>σ</italic>); thus curing occurred in simulations with low <italic>σ </italic>and high <italic>μ</italic>.</p>", "<p>Under all conditions, infected populations need male immigration from uninfected populations as male killing rapidly leads to a pure-female population with elevated dispersal rates. Consequently, the extinction probability of infected patches increases with the fraction of infected populations within the metapopulation because fewer and fewer males are produced in the whole metapopulation. This leads to disproportionally increase of the absolute numbers of patches that become extinct over the fraction of infected populations. In contrast, the recolonization of empty patches by infected females only linearly increases with the fraction of infected populations. This eventually leads to a stabilization of the fraction of infected populations, and subsequently the overall infection rates.</p>", "<p>Stabilization occurs predominantly through the negative feedback on patch extinction, by which the fraction of extinct patches in the next time step <italic>t+1 </italic>decreases when the fraction of extinct patches on a certain moment <italic>t </italic>is larger than 0.04 (Fig. ##FIG##4##5A##). Interestingly, a similar feedback also emerges for changes in infected (Fig ##FIG##4##5B##) and uninfected patches (Fig ##FIG##4##5C##). For uninfected patches and extinct patches, the negative feedback is only prominent when the number of uninfected or extinct populations is low. This implies that when the fraction of uninfected or extinct patches rises above this threshold (this occurs evidently in metapopulations that go extinct or get cured from the infection), stochastic dynamics may induce the curing or extinction of the metapopulation due to positive feedback probabilities. Obviously, this stabilizing mechanism by dispersal is responsible for the smaller range of local infection rates in metapopulations that persist under high dispersal (see Fig ##FIG##3##4B, C##) compared to conditions with low dispersal (fig ##FIG##3##4A##). More-over, the higher number of uninfected surviving females (and males evidently) induce a positive feedback on the founding of uninfected populations which on their turn have overall low chances to be colonized by infected females, eventually leading to the curing of the entire metapopulation.</p>", "<p>This finding confirms the prediction that frequencies of selfish gene elements (a.o., meiotic drive elements, cytoplasmatic incompatibility, male killers, feminizers; [##REF##10856947##47##]) are a dynamic consequence of local extinction-colonization events in spatially structured population [##REF##10856947##47##]. The only study [##UREF##11##28##] that explicitly addressed the persistence of male killing endosymbionts and infection prevalence within a spatial setting confirmed the importance of colonization-extinction dynamics, although at the local scale (i.e. within in a population). The resulting pattern formation (i.e., wave patterns by which infections spread quickly leave behind empty space that can only be filled by uninfected individuals) explained male killer persistence, even when transmission efficiency was perfect. In this spatial automata model [##UREF##11##28##], pattern formation was significantly affected by fitness compensations for survival. In our individual based model, however, no explicit fitness compensations were introduced. Instead, the reduced competition in infected populations fully compensates the fact that infected females lose half of their offspring. This compensation emerges by default and depends on the within-population infection rate. Interestingly, infected females also relax competition between non-kin offspring and consequently strongly influence interdemic (group) selection [##UREF##22##46##,##REF##10856947##47##].</p>", "<p>The induced changes in resource and kin competition by male killing endosymbionts are responsible for the disproportional increase in male emigration compared to that of females. The evolutionary mechanism underlying this sex-specific dispersal [##REF##10657181##48##] is different from the evolution of sex-indifferent dispersal [##UREF##19##42##,##UREF##20##43##], but it is evident that it is of particular relevance for the rescue of infected population (Bonte <italic>et al</italic>., submitted for publication). Such populations face the risk of a depletion of males and consequently local extinction in the absence of male immigration.</p>", "<p>Our sensitivity analysis with respect to the carrying capacity revealed that the modeling results are robust for larger <italic>K</italic>. Only when K is low, a significant change in extinction and curing probabilities were detected. Evidently, this is due to increased effects of stochasticity in smaller populations [##UREF##23##49##]. However, since our model reflects endosymbiont invasions in arthropod populations, altered dynamics at low <italic>K </italic>can be disregarded. Besides <italic>K</italic>, male limitation, with subsequent Allee effects on mating, decrease host metapopulation viability when the number of mating events for each male is limited [##REF##10438666##50##,##UREF##24##51##]. We did not model this implicitly, but models run for monogamous paring systems (compared to the polygynous system described here) indeed confirmed overall low (mostly zero) survival probabilities for invaded host metapopulations (Bonte <italic>et al</italic>., unpub. results).</p>", "<p>Evidently, the probability of endosymbionts extinction (the 'curing') is expected to depend on the initial infection rate. Sensitivity analysis showed that high initial infection rates (<italic>I </italic>= 0.5; <italic>I </italic>= 0.8) always led to metapopulation extinction under conditions favoring high dispersal in the host (low <italic>μ </italic>and high <italic>σ</italic>). However, initially high infection rates do not affect the phenomenon of metapopulation curing (only endosymbionts go extinct). In contrast, when initial infection rates were very low and non-evenly distributed only slight increases of parasite extinction rates were observed under conditions that disfavor high dispersal. The fate of male-killer infections also strongly depends on the local population size (<italic>K</italic>). When <italic>K </italic>was very low (<italic>K </italic>= 10), male killers always disappeared from the metapopulations. Entire metapopulations got extinct under environmental conditions that disfavored dispersal (<italic>μ </italic>&gt; 3, <italic>σ </italic>&lt; 2). Under conditions of low <italic>μ </italic>and high <italic>σ</italic>, metapopulation extinction rates always exceeded 0.56, because the remaining fraction got entirely cured by stochastic processes. In the latter, dispersal rates increased up to 15–25% due to the increasing importance of kin competition [##UREF##16##37##]. At the other extreme, when <italic>K </italic>was increased (K = 250, 500), only a slight decrease in overall extinction (respectively 0.07 (<italic>K </italic>= 250), 0.06 (<italic>K </italic>= 500), compared to 0.09 for <italic>K = 100</italic>) and curing rates were observed (respectively 0.16 (<italic>K </italic>= 250), 0.14 (<italic>K </italic>= 500), compared to 0.18 for <italic>K = 100</italic>), obviously due to an increase in population size. Because insect populations are expected to occur at high local population densities, we assume our modeling results therefore to be reliable with respect to the envisioned biological system.</p>", "<p>As demonstrated by our simulations, endosymbionts are only able to persist under intermediate levels of host dispersal. Even exceptional infection rates of up to 90% and associated skewed sex ratio's, may be stable under conditions that are characterized by low environmental stochasticity and low dispersal costs. Such stability does not require behavioral changes in mating system or fitness costs for infected individuals. For example, low environmental variation and low dispersal costs for butterflies in tropical forests [##REF##10905965##20##,##UREF##25##52##] could explain the high infection rates reported for these species. Accordingly, agrobiont species (experiencing high dispersal costs after reproduction in contemporary landscapes; e.g. [##UREF##26##53##]) show, on average, low to intermediate infection rates [##REF##10905965##20##]. These observations are thus in good agreement with our result that the spatial dynamics in host metapopulations can be important for the establishment of infection rates by male-killing endosymbionts. Our simulations also showed that strong among-population variation in infection rates may occur under ecological conditions that support the evolution of low to intermediate evolutionary stable dispersal rates in hosts. Relating recently observed among-population heterogeneity [##UREF##9##24##,##UREF##10##26##] in local infection rates to the spatial structure and environmental conditions of the entire metapopulation could consequently provide a more quantitative validation of our hypothesis. Our simulation experiments therefore add to recent theoretical work [##UREF##11##28##,##REF##10438666##50##,##UREF##24##51##,##UREF##27##54##] that highlights the crucial importance of spatial ecological dynamics for evolutionary host-parasite processes.</p>" ]

[ "<title>Conclusion</title>", "<p>The invasion of male killer endosymbionts is responsible for the evolution towards higher dispersal rates in their host. The resulting sex-specific dispersal rates in host metapopulations that are invaded by male-killing endosymbionts strongly determine the level of infection rates and related host-endosymbiont population dynamics. The influence of environmental conditions on host dispersal allows for the emergence of high but stable infection rates under a wide range of environmental conditions, which favor the evolution of intermediate host dispersal. In contrast, endosymbionts are predicted to carry high extinction risks under either low or high host dispersal activities. Under high dispersal, this is either due to fixation of the infection (and extinction of the host metapopulation) or due to accidental loss of the infection from host metapopulations at the brink of global extinction, which may, however, recover after the infection is lost. In contrast, low dispersal rates may lead to deterministic curing of the host population.</p>" ]

[ "<title>Background</title>", "<p>Male killing endosymbionts manipulate their arthropod host reproduction by only allowing female embryos to develop into infected females and killing all male offspring. Because of the reproductive manipulation, we expect them to have an effect on the evolution of host dispersal rates. In addition, male killing endosymbionts are expected to approach fixation when fitness of infected individuals is larger than that of uninfected ones and when transmission from mother to offspring is nearly perfect. They then vanish as the host population crashes. High observed infection rates and among-population variation in natural systems can consequently not be explained if defense mechanisms are absent and when transmission efficiency is perfect.</p>", "<title>Results</title>", "<p>By simulating the host-endosymbiont dynamics in an individual-based metapopulation model we show that male killing endosymbionts increase host dispersal rates. No fitness compensations were built into the model for male killing endosymbionts, but they spread as a group beneficial trait. Host and parasite populations face extinction under panmictic conditions, i.e. conditions that favor the evolution of high dispersal in hosts. On the other hand, deterministic 'curing' (only parasite goes extinct) can occur under conditions of low dispersal, e.g. under low environmental stochasticity and high dispersal mortality. However, high and stable infection rates can be maintained in metapopulations over a considerable spectrum of conditions favoring intermediate levels of dispersal in the host.</p>", "<title>Conclusion</title>", "<p>Male killing endosymbionts without explicit fitness compensation spread as a group selected trait into a metapopulation. Emergent feedbacks through increased evolutionary stable dispersal rates provide an alternative explanation for both, the high male-killing endosymbiont infection rates and the high among-population variation in local infection rates reported for some natural systems.</p>" ]

[ "<title>Authors' contributions</title>", "<p>The work presented here was carried out in collaboration between all authors. DB conceptualized the research questions, implemented the model, analyzed the data, interpreted the results and wrote the paper. TH and HJP designed an earlier version of the model, discussed analyses, interpretation, and presentation. All authors have contributed to, seen and approved the manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>DB is a postdoctoral fellow at the Fund for Scientific Research – Flanders (FWO), from which he received a mobility grant for a long-term stay at Würzburg University. HJP and TH are partially supported by a grant from the \"Deutsche Forschungsgemeinschaft\" (DFG PO233/3) and FWO grant G.0202.06. We are grateful to the three referees who provided comments that increased the quality of the manuscript.</p>" ]

[ "<fig id=\"F1\" position=\"float\"><label>Figure 1</label><caption><p><bold>Dispersal rates of males and females</bold>. Contour plot of average host emigration probability (males, A; females, B) in the metapopulation under infected (no extinction of host and/or endosymbiont) and uninfected conditions(males, C; females, D). The x-axis gives dispersal mortality (<italic>μ</italic>), the y-axis environmental variability (<italic>σ</italic>).</p></caption></fig>", "<fig id=\"F2\" position=\"float\"><label>Figure 2</label><caption><p><bold>Metapopulation and endosymbiont extinction</bold>. Effect of endosymbionts invasion on metapopulation extinction probability (A) and the probability that a surviving metapopulation gets infection-free (B).</p></caption></fig>", "<fig id=\"F3\" position=\"float\"><label>Figure 3</label><caption><p><bold>Infection rates and sex ratio</bold>. Average host infection rates (number of infected females/total population size; A) and sex-ratio (number of females/total population size; B) within host metapopulations under infected conditions (no extinction of host and/or endosymbiont).</p></caption></fig>", "<fig id=\"F4\" position=\"float\"><label>Figure 4</label><caption><p><bold>Among population variation</bold>. Variation in infection rates among local populations in non-extinct metapopulations. Arrows indicate the fraction of non-infected local populations. Histograms (based on 10 replicate simulations) are given for three simulation runs representative of conditions were metapopulations experience high probabilities of losing endosymbionts (A, <italic>μ </italic>= 0.4, <italic>σ </italic>= 0.5), usually show stable coexistence with, on average, high infection rates (B, <italic>μ </italic>= 0.3, <italic>σ </italic>= 2), and the risk of host/endosymbiont metapopulation extinction is high (C, <italic>μ </italic>= 0.1, <italic>σ </italic>= 4).</p></caption></fig>", "<fig id=\"F5\" position=\"float\"><label>Figure 5</label><caption><p><bold>Feedback mechanisms</bold>. Net changes in the number of empty patches (patch extinction; A), the number of infected patches (B) and the number of uninfected patches (C) in a metapopulation with stable infection rates, plotted over the number of respectively empty, infected and uninfected patches. Regression lines indicate areas where negative feedback regulation occur (<italic>μ </italic>= 0.3, <italic>σ </italic>= 2). Net changes are calculated as the absolute difference in the number of empty (A), infected (B) or uninfected (C) patches at time <italic>t+1 </italic>in relation to the actual number of patches at time <italic>t</italic>.</p></caption></fig>" ]

[ "<table-wrap id=\"T1\" position=\"float\"><label>Table 1</label><caption><p>Parameters of the model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Parameter</th><th align=\"left\">Description</th><th align=\"left\">Ranges tested</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"3\"><bold><italic>model analysis</italic></bold></td></tr><tr><td align=\"left\"><italic>K</italic></td><td align=\"left\">Carrying capacity local populations</td><td align=\"left\">100</td></tr><tr><td align=\"left\"><italic>I</italic></td><td align=\"left\">Initial infection rates</td><td align=\"left\">0, 0.1</td></tr><tr><td align=\"left\"><italic>λ</italic></td><td align=\"left\">mean offspring number</td><td align=\"left\">4</td></tr><tr><td align=\"left\"><italic>σ</italic></td><td align=\"left\">standard deviation in mean offspring number; reflects environmental stochasticity</td><td align=\"left\">0, 0.5,...,4.5</td></tr><tr><td align=\"left\"><italic>μ</italic></td><td align=\"left\">dispersal mortality</td><td align=\"left\">0.1, 0.15...,0.45</td></tr><tr><td align=\"left\" colspan=\"3\"><bold><italic>Sensitivity analysis</italic></bold></td></tr><tr><td align=\"left\"><italic>K</italic></td><td align=\"left\">Carrying capacity</td><td align=\"left\">10, 250, 500</td></tr><tr><td align=\"left\"><italic>I</italic></td><td align=\"left\">Initial infection rates</td><td align=\"left\">0.001, 0.01, 0.02, 0.50, 0.80</td></tr></tbody></table></table-wrap>" ]

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[ "<title>Conclusion</title>", "<p>Mitochondria long have been recognized for their role as powerhouse of the cell. Interest in mitochondria was greatly rekindled upon recognition of their central role in regulation of cell death. Many death stimuli converge on these organelles to cause release of apoptogenic factors. This mitochondrial response is also coupled to the interruption of energy production and a collapse of mitochondria ROS and Ca²⁺homeostasis. However, the latter processes may also be directly targeted by pro- and antiapoptotic signaling pathways (Figure ##FIG##0##1##) opening up possible novel options for therapeutic interference at an early stage, before through the release of second messenger like ROS the damage to cells and organs is amplified.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>The concept of a pre-emptive strike as a good means to prevent greater harm may be frequently over-stressed in daily life. However, biological systems in a homeostatic balance are prepared to withstand a certain degree of hostile fire by rather passive means. This also applies to the maintenance of cell survival, where a plethora of protective proteins provide safeguard against erroneous activation of death pathways. Apart from these mechanisms active processes are also essential for the maintenance of cellular homeostasis, commonly referred to as survival signaling. Frequently their targets may be mitochondrial, assuring organelle integrity, which is essential for continued energy production and survival. Transient or permanent failures in these cellular defense strategies result in pathophysiological conditions, which manifest themselves e.g. as cancer or ischemia/reperfusion-associated organ damage.</p>" ]

[ "<title>Review</title>", "<p>During times of peace cells are dependent on a balanced crosstalk with their surrounding environment. Survival and proper functioning not only require physical contact with their neighbors, but also depend on a plethora of soluble factors such as hormones or growth factors. The full spectrum of possible cell fates is governed by these mutual and highly dynamic interactions. In the extreme case a dissonance in this \"orchestra of life\" leads to cell death. However, in order for this to happen a variety of safeguard mechanisms have to fail and cells are normally sufficiently guarded against these threats.</p>", "<p>Subversion of intracellular control mechanisms is linked to many pathophysiological conditions. In particular, cancer cells are geared towards cellular autonomy, which is achieved through aberrant activation of intracellular signaling processes. As a consequence these cells are in a preemptive way programmed to withstand hostile conditions and to thrive in a growth and survival limiting environment. Thus cancer provided a useful model for the delineation of mechanisms used to counter potential assaults. Its analysis taught us that tumors in a unique way are equipped to withstand limitation in life supporting oxygen or nutrient supply. Many of the genetic defects found in tumors reside in signaling cascades or proteins, supporting the key role of aberrant signaling in this. However, protective mechanisms also can be triggered in a more rapid and transient fashion. During transplantation organs are temporarily deprived of oxygen, nutrients and growth factors (ischemia). A decrease in myocardial oxygen delivery initially results in decreased contractile activity and oxygen consumption, a phenomenon termed <italic>hibernating myocardium </italic>[##REF##9452449##1##]. Prolonged hypoxia may also reduce ATP demand by down-regulating protein synthesis [##REF##8790358##2##]. Restoration of blood flow (reperfusion) corrects these deficits but at the same time initiates a detrimental cascade, which in the end can lead to irreversible damage of the affected organ. During reperfusion organs also respond with the activation of intracellular signaling pathways. Some of these signaling activities are clearly linked to the cell death induction, while others may be involved in the elicitation of a protective response. Through repeated short ischemic intervals which do not cause irreversible damage (\"pre-conditioning\"), cells may actually learn to cope with conditions, which are normally life-threatening. Also this defense mechanism is operated by intracellular signaling pathways [##REF##17999631##3##]. Therefore, understanding the role of signaling in ischemia-reperfusion induced injury (IRI) holds the potential for the development of novel therapeutic strategies for its prevention, perhaps even at a time point before other events like the production of reactive oxygen species (ROS), the perturbation of Ca²⁺homeostasis or inflammatory responses occur, which will greatly amplify the damage. Mitochondria feature prominently in these processes as they are critical for the provision of energy and the assurance of cell survival. A coordinated cellular response will require crosstalk between mitochondria and their cellular environment. Cytoplasmic signaling pathways are increasingly recognized for their central role in relaying information to the mitochondria and in possibly controlling their function [##REF##15527752##4##]. In this review we will present a current view of mitochondrial form and function, before we discuss the dealings of mitochondria with the cellular environment. Finally we will use the example of ischemia/reperfusion-induced tissue damage to illustrate the cooperation of these players and to show up possible therapeutic implications.</p>", "<title>From form to function: Mitochondria shaping up for performance</title>", "<p>The classical view of mitochondria as bean-shaped organelles has changed dramatically over the last years. Earlier studies shed light on the complexity of their internal organization [##REF##10871882##5##], while most recently another feature of these organelles has attracted considerable interest, their highly dynamic behavior [##REF##17928812##6##]. Through fission and fusion mitochondrial morphology can change from small spheres or short rods to long tubules forming large network-like structures within the same cell. Another level of complexity is added through their high motility. While the highest velocity was found in neurons, mitochondrial movement could be shown in various other cell systems such as HL-1 cells, cultured fibroblasts, budding yeast, etc. [##REF##16306220##7##, ####REF##15556861##8##, ##REF##7615636##9##, ##REF##10559975##10##, ##REF##10066164##11####10066164##11##]. Mitochondria can be actively transported in cells and may have defined tissue-specific subcellular distributions. In neurons, for example, they are translocated to regions with high energy and Ca²⁺buffering demands, such as active growth cones, pre- and post-synaptic sites. In addition, they often pause at sites where no mitochondria are present, resulting in an uniform axonal mitochondrial distribution. Mitochondria with high membrane potential preferentially migrate in the anterograde direction, whereas mitochondria with low membrane potential move in the retrograde direction. Therefore active mitochondria appear at distal regions with high energy demands, while impaired mitochondria are returned to the cell soma, possibly for repair or mitophagy. In addition, signaling molecules such as nerve growth factor (NGF) influence mitochondrial recruitment and retention [##REF##15150321##12##].</p>", "<p>Several studies have suggested that controlling mitochondrial shape through fusion and fission is also crucial for maintaining the functional properties of mitochondria [##REF##17928812##6##]. The precise balance between these two opposing processes therefore might play a key role in mitochondrial and cellular function. More than ten years ago, the first molecular mediator of mitochondrial fusion was discovered in <italic>Drosophila melanogaster</italic>: Fusion factor <italic>fuzzy onions </italic>(Fzo), a mitochondrial outer membrane GTPase that is required for the fusion of mitochondria during spermatogenesis [##REF##9230308##13##]. The two human Fzo homologues Mitofusin (Mfn) 1 and 2 also control mitochondrial morphology [##REF##11950885##14##,##REF##12527753##15##]. As a subset of mitochondria in Mfn1-deficient cells was shown to lose their membrane potential, mitochondrial fusion seems to allow cooperation between mitochondria, thereby protecting mitochondria from respiratory dysfunction [##REF##12527753##15##]. Also Mfn2 ablation experiments have documented a reduced mitochondrial oxidation and membrane potential as well as a repression of nuclear-encoded subunits of OXPHOS complexes [##REF##15829499##16##]. In mammals, mitochondrial fission requires the recruitment of cytosolic dynamin-related protein (DRP1) [##REF##11514614##17##]. Post-translational modifications regulate its function in mitochondrial fission. The ubiquitin ligase of the mitochondrial outer membrane, termed membrane-associated RING-CH (MARCH)-V, a member of the transmembrane RING-finger protein family, has the ability to bind to Mfn2 and DRP1, to ubiquitinate DRP1 and to modify mitochondrial morphology. By regulating Mfn2 and Drp1 activities, MARCH-V controls mitochondrial morphology [##REF##16936636##18##].</p>", "<p>In addition, cellular stress influences mitochondrial fusion and fission: Thus DRP1 was also shown to be involved in apoptosis-associated mitochondrial fission. While under normal conditions DRP1 recycles between the cytoplasm and mitochondria, it shows a stable membrane association following the recruitment of BAX to the mitochondrial membrane but before the loss of mitochondrial membrane potential. During apoptosis, the biochemical properties of DRP1 are regulated via a BAX/BAK-dependent stimulation of small ubiquitin-like modifier-1 conjugation to DRP1 [##REF##17470634##19##]. Recent findings have demonstrated a key role of the proper regulation of mitochondrial dynamics for various cellular pathways, demonstrating also that defective mitochondrial behavior may affect human health. For example, several neurological diseases (e.g. Charcot-Marie-Tooth, CMT; autosomal dominant optic atrophy, DOA) are associated with mutations in proteins that control mitochondrial dynamics and morphology like mitofusin-2 and OPA1 [##REF##11017080##20##,##REF##15064763##21##].</p>", "<title>Breathing oxygen-producing ROS</title>", "<p>The change in earth's atmosphere from anoxic to our current conditions of approx. 21% oxygen had on the one hand catastrophic effects on unicellular anaerobic life forms but on the other hand paved the way for new forms of life which managed to tame this highly reactive and due to its oxidizing properties potentially life-threatening molecule and made a renegade of it changing fronts from life threatening to life supporting [##REF##18062771##22##]. The supply of ATP through oxidative phosphorylation, which couples the oxidation of metabolic substrates to the synthesis of ATP from ADP and inorganic phosphate takes place in the mitochondria, putative descendents of an ancient endosymbiotic event between an alpha-proteobacterium and an archean host [##REF##10066161##23##,##REF##16857720##24##]. Utilizing oxygen as the final electron acceptor in the aerobic metabolism of glucose as the primary source of energy increased the efficiency of ATP generation.</p>", "<p>The mitochondrial respiratory chain transfers electrons to molecular oxygen, permanently producing ROS as a by-product of oxidative phosphorylation. Depending on the conditions, a few percents of the oxygen consumed by mitochondria are reduced by a single free electron with formation of superoxide radical, which then can be converted to hydrogen peroxide (further mono-electron reduction of oxygen) by mitochondrial superoxide dismutase (SOD), which in turn can be scavenged by catalase reaction or converted to the very reactive hydroxyl radical in the presence of transition metals (e.g. Fe²⁺). Several reports have demonstrated that mitochondrial superoxide production is mostly a result of incomplete reduction of oxygen at sites of respiratory complexes I (NADH:ubiquinone oxidoreductase) and III (CoQ:cytochrome <italic>c </italic>oxidoreductase) which therefore can be considered as main sources for mitochondrial ROS [##REF##16054089##25##, ####REF##14625276##26##, ##REF##15262965##27##, ##REF##11948241##28##, ##REF##17555402##29####17555402##29##].</p>", "<title>Sensing cellular energy status</title>", "<p>Mitochondria are able to monitor their surrounding environment, including intracellular energy (ATP) levels, as well as oxygen, ROS, Ca²⁺and the presence or absence of growth factors [##REF##15527752##4##]. Moreover, mitochondria are well tailored to meet both the signaling and metabolic needs of the cell. It has been suggested that mitochondrial biogenesis (mitochondrial proliferation) and dynamics are strongly linked to the ability of mitochondria to sense energy status [##REF##16306220##7##,##REF##17609368##30##, ####REF##12444247##31##, ##REF##11701451##32##, ##REF##10066162##33####10066162##33##]. In muscles confronted with increased work load (training, endurance exercise) or pathological changes (mitochondrial diseases, genetic defects in respiratory complexes), the proliferation of mitochondria serves as an adaptational response to decreased energy levels [##REF##10066162##33##]. In other cells like neurons, energy sensing mechanisms may also serve for the directorial transport of mitochondria to the cellular regions of higher energy demands [##REF##16306220##7##]. One of the key enzymes for low-energy sensing is AMP activated protein kinase (AMPK) [##REF##16644800##34##]. AMPK is an evolutionarily conserved enzyme which is allosterically activated by AMP (marker of low energy status). In addition, AMPK is strongly regulated by changes in phosphorylation state by upstream kinases and phosphatases [##REF##16644800##34##, ####REF##16054096##35##, ##REF##12764152##36####12764152##36##]. This enzyme therefore is sensitive to increases in the cellular AMP/ATP ratio and can be activated by various metabolic stresses, such as ischemia, hypoxia, starvation (e.g. glucose deprivation), by metabolic inhibition (e.g. using analogs of energy substrates or simulated ischemia) or in response to increased exercise in muscles [##REF##12444247##31##,##REF##14729328##37##, ####REF##16443822##38##, ##REF##11069105##39##, ##REF##12824177##40####12824177##40##]. Stimuli for AMPK involve either processes that inhibit ATP production or accelerate ATP consumption. Active AMPK upregulates catabolic and suppresses anabolic pathways [##REF##16443822##38##,##REF##17705797##41##]. For example, AMPK may phosphorylate and thus inhibit enzymes of ATP consuming pathways like the formation of fatty acids, cholesterol and glycogen (e.g. acetyl-CoA-carboxylase, glycogen synthase, etc.), and also highly ATP consuming protein synthesis by eEF2K phosphorylation [##REF##12194824##42##]. Moreover, active AMPK blocks cell growth and proliferation by suppression of the target of rapamycin (mTOR) pathway [##REF##11997383##43##,##REF##12558800##44##] via direct phosphorylation of an upstream regulator of mTOR, tuberous sclerosis complex-2 (TSC2 or tuberin) [##REF##14651849##45##]. This type of downregulation of mTOR signaling seems to be dominant over the positive effects of growth factors or amino acids. More recent data suggest two inhibitory effects of AMPK on mTOR. Activated AMPK may phosphorylate TSC2 at a site different from AKT, promoting its Rheb-GAP activity, and additionally it may phosphorylate raptor (regulatory associated protein of mTOR), also resulting in mTOR inhibition [##REF##18439900##46##], leading to a suppression of protein synthesis and overall cellular ATP consumption. At the same time, AMPK activation in muscles could markedly stimulate glucose uptake by increased translocation of the glucose transporter GLUT4 to the plasma membrane [##REF##10426389##47##] via phosphorylation of a downstream target of AMPK – AS160, a Rab GTPase-activating protein [##REF##16804075##48##]. Besides, acute or chronic chemical activation of AMPK in muscles results also in elevated GLUT4 expression (with remarkable increase in GLUT4 mRNA levels) [##REF##10562646##49##,##REF##11509501##50##]. Therefore, through activation of both GLUT4 translocation and GLUT4 expression, activated AMPK stimulates glycolysis in muscles. In addition, activation of 6-phosphofructo-2 kinase (PFK) by AMPK also supports glycolytic ATP production. Furthermore, phosphorylation of acetyl-CoA carboxylase (ACC) by AMPK decreases malonyl-CoA levels [##REF##17008367##51##], reducing inhibition of carnitine palmitoyl-CoA acyltransferase-1 (the enzyme responsible for transport of fatty acids into mitochondria), stimulating utilization of fatty acids and helping thus better mitochondrial ATP production. AMPK activation therefore serves to defend against energy deficiency via activation of glucose transport and oxidation of fatty acids [##REF##16644800##34##,##REF##10871188##52##, ####REF##11334411##53##, ##REF##10444490##54####10444490##54##]. Growing evidence [##REF##17609368##30##,##REF##12444247##31##] demonstrates that AMPK is also a critical regulator involved in initiating mitochondrial biogenesis through activation of the peroxisome proliferator activated receptor γ coactivator 1α (PGC-1α) which is an important regulator of transcription of many genes involved in mitochondrial energy metabolism, mitochondrial physiology and oxidation of glucose and fatty acids [##REF##10412986##55##]. Notably, AMPK also interferes with mitochondrially produced ROS and reactive nitrogen species (RNS), as well as with their scavengers: like vitamin E, N-acetylcysteine, the SOD-mimetic MnTBAP, or α-Lipoic acid (powerful antioxidant and an essential cofactor for several mitochondrial enzymes) [##REF##12824177##40##,##REF##17157194##56##,##REF##15265871##57##].</p>", "<p>Metabolic dysregulation is commonly observed under conditions of metabolic stress, e.g. cancer, ischemia/reperfusion. In tumors it may be an important contributor to the transformation process. Thus the frequently described switch to glycolysis which also persists under aerobic conditions (\"Warburg effect\") may in part be caused by direct effects of cancer protein signaling on the expression/activity of glycolytic enzymes [##REF##10098401##58##, ####REF##18538731##59##, ##REF##9490722##60####9490722##60##]. The discovery of mutations in succinate dehydrogenase and fumarate hydratase, components of the tricarboxylic acid (TCA) cycle (also known as Krebs cycle), which connects cytosolic glucose metabolism to mitochondrial oxidative phosphorylation (OXPHOS), led to the demonstration of a tumor suppressor function for these proteins [##REF##16327764##61##]. When these genes are mutated, succinate or fumarate, respectively, accumulate in mitochondria and pass to the cytosol resulting in the inhibition of prolyl hydroxylases (PHDs) and consecutive stabilization of transcription factor hypoxia-inducible factor 1α (HIF1α) under normoxic conditions [##REF##16892081##62##] with important consequences for the expression of target genes required for tumor growth and metastasis. Finally, also mitochondrial DNA (mtDNA) may carry mutations which through impairment of OXPHOS, increased ROS production and increased proliferation contribute to tumor progression [##REF##16892079##63##].</p>", "<title>Controlling mitochondrial function by modulating intracellular signaling</title>", "<p>Ischemia and reperfusion cannot be avoided during organ transplantation and initiate a cascade of events, which results in tissue damage. While advances in immunosuppressive therapy, amelioration of surgical techniques and organ preservation have significantly improved success rates of solid organ transplantation, IRI remains a major problem requiring substantial follow up treatment [##REF##15541456##64##, ####REF##10383108##65##, ##REF##9721797##66####9721797##66##].</p>", "<p>Massive mitochondrial ROS production during reperfusion paralleled by the depletion of scavengers like superoxide dismutase (SOD), vitamins C and E etc. results in the deterioration of organ function or even organ loss [##REF##17430185##67##, ####REF##12646264##68##, ##REF##16827855##69####16827855##69##]. There is also evidence that crucial events leading to ROS production already occur during ischemia [##REF##18077608##70##]. Nevertheless, the major hit to the oxygen-deprived cell happens, paradoxically, during reperfusion. The reperfused cells experience an \"oxidative burst\" with mitochondria-derived superoxide radicals [##REF##11889418##71##,##REF##17599037##72##]. Mitochondria are especially sensitive to ROS induced damage and as a consequence disruption of oxidative phosphorylation can be observed culminating in significant reduction of ATP levels, excessive entry of Ca²⁺into mitochondria and loss of mitochondrial membrane potential [##REF##15355853##73##,##REF##16472163##74##], resulting in cytosolic release of apoptosis inducing factors, such as apoptosis inducing factor (AIF), cytochrome <italic>c </italic>and Smac/DIABLO [##REF##11413467##75##,##REF##12115719##76##].</p>", "<p>Attempts to limit ischemia/reperfusion-associated cellular damage have to take into account the important role of mitochondria in this process. Current strategies try to limit the extent of ROS damage by applying anti-oxidants. Much more desirable would be an approach, which avoids oxidative damage by preventing ROS production or scavenging oxygen radicals at the site of their production. First evidence for the control of mitochondrial events by cellular signaling pathways was provided by demonstrating their effect on the expression and function of anti-apoptotic proteins of the Bcl-2 or IAP family [##REF##14555207##77##]. Additional support came from the suggested localization of many diverse signaling molecules (kinases, transcription factors, etc.) to various sites in the mitochondria [##REF##15527752##4##,##REF##18240421##78##]. More difficult was the search for targets regulated by them due to experimental difficulties. Candidate processes controlled through signaling include protein and Ca²⁺trafficking, oxidative phosphorylation and production of reactive oxygen species. A critical event in cell death initiation is the translocation of the pro-apoptotic Bcl-2 protein BAX to the mitochondria [##REF##18314333##79##,##REF##18082600##80##]. Cessation of survival signals, which is a common stimulus for cell death induction, will result in the shut-down of signaling cascades, and in particular the kinases, which compose them. Since phosphorylation may both positively and negatively regulate protein function, signal interruption also will cause the generation of new signals. One of them originates from GSK-3, which upon activation will cause the phosphorylation-dependent ubiquitination and subsequent degradation of the survival protein Mcl-1, which normally negatively controls BAX, followed by its mitochondrial translocation [##REF##16543145##81##]. In our work we recently demonstrated that expression of oncogenic or wild type RAF prevented mitochondrial ROS production, Ca²⁺overload and apoptosis [##REF##18212057##82##]. Protein kinase A (PKA) has been implicated in the activation of the NADH-ubiquinone oxidoreductase activity of complex I resulting in reduced ROS production [##REF##16870178##83##,##REF##18455500##84##]. Decreased mitochondrial ROS levels were also observed in the heart of transgenic mice expressing the p38 MAPK activator MAPK kinase 6 (MKK6) [##REF##16766635##85##]. Also the tumor suppressor p53 can control ROS levels through its transcriptional target TIGAR [##REF##16839880##86##], leading to an increase in the levels of glutathione (GSH), which scavenges ROS. In contrast, increased mitochondrial ROS production has been described for SHC [##REF##16677103##87##,##REF##16051147##88##]. A fraction of p66 (SHC) exists within mitochondria, where it oxidizes cytochrome <italic>c </italic>to form hydrogen peroxide, which in turn induces mitochondrial permeability and apoptosis. Taken together these examples demonstrate that key mitochondrial processes can be subject to the regulation by signaling pathways, which normally respond to extrinsic stimuli (Figure ##FIG##0##1##). Many of the signaling molecules have attracted considerable interest in the past because of their role in diverse pathological settings including autoimmune diseases, inflammation or cancer. Various approaches have been developed to target them for therapeutic purposes including the development of small molecular weight inhibitors. This raises the possibility of planned pre-emptive intervention to also limit the extent of IRI.</p>", "<p>Production of mitochondrial ROS is not only restricted to IR but indeed may be an important intermediate in intrinsic and extrinsic (cell death receptor-dependent) pathways of cell death induction. Thus growth factor abrogation [##REF##18212057##82##,##REF##16870178##83##], death induction through activation of the TNF-α receptor [##REF##15766528##89##,##REF##17979836##90##] or genotoxic stress [##REF##16978905##91##,##REF##18208352##92##] all are linked to the induction of massive ROS production, which is essential for cell death.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>JT planned the review outline, drafted the final version. All the other authors equally contributed to the writing of the review.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors acknowledge the excellent secretarial assistance provided by Ruth Baldauf in the preparation of the manuscript. Financial support for this work has been provided over the last years by DFG, FWF, MFF (Medizinischer Forschungsfonds Tirol), the TWF (Tiroler Wissenschaftsfonds), Uniqa Versicherungen AG and the Tiroler Krebshilfe.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Mitochondrial rheostat of cell survival control</bold>. Key players in the regulation of mitochondrial function are depicted under four different states. Intracellular signaling is represented by bold arrows, filled light grey for survival or dark grey for pro-apoptotic signaling. Under normal conditions cells tolerate a certain level of stress before strong pro-apoptotic stimuli eventually perturb cellular homeostasis. A tumor cell no longer is in a state of equilibrium as ROS levels usually are high, survival signals are enhanced and extra-mitochondrial energy production may become predominant. During ischemia/hypoxia oxidative phosphorylation is disturbed leading to a decrease in ATP. Additionally, cells suffer from elevated ROS and Ca²⁺levels. During reperfusion/reoxygenation mitochondrial ROS and Ca²⁺levels peak and cell death may follow. Various intracellular signaling pathways are activated during this time and may positively or negatively control mitochondrial function. Eventually, a therapy that abolishes pro-apoptotic signals or elicits survival signaling may help to prevent or limit damage occurring under these conditions.</p></caption></fig>" ]

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{ "acronym": [], "definition": [] }

[ "<title>1. Background</title>", "<p>The basic mechanism underlying the functioning of DNA microarrays is that of hybridization. Hybridization is defined as the binding between complementary single-stranded nucleic acids. In the case of microarrays one strand is anchored at the surface and the second one is dissolved in solution, referred to as probe and target, respectively. The experimental technique of detecting hybridized probes relies on the fluorescence intensity measurement to infer the transcript abundance specific for a selected gene. The relationship between transcript abundance and intensity is affected by parasitic effects owing to the \"technical\" variability of repeated measurements and systematic biases which disturb the one-to-one relationship between the input and the output quantity of the measurement [##UREF##0##1##].</p>", "<p>The task of making estimates of the input quantity (transcript concentration) of a measurement from observations of its output (intensity) is called calibration. Calibration of microarray measurements thus aims at removing consistent and systematic sources of variations to allow mutual comparison of measurements acquired from different probes, arrays and experimental settings. Calibration is also called preprocessing because it usually constitutes the first step in the microarray analysis pipeline. It potentially influences the results of all subsequent steps of \"higher-level\" analyses as well as the biological interpretation of these results, and is therefore a crucial step in the processing of microarray data. The improvement of microarray calibration methods is an essential prerequisite for obtaining absolute expression estimates which in turn are required for the quantitative analysis of, e.g., transcriptional regulation.</p>", "<p>Most of the established preprocessing methods rely on algorithms of mainly empirical nature based on the simple assumption of a linear signal response on the transcript concentration in the sample [##UREF##1##2##, ####UREF##2##3##, ##UREF##3##4##, ##REF##11134512##5####11134512##5##]. In the last years numerous studies on the physical background of microarray hybridization are published with the perspective of developing improved analysis algorithms [##REF##12794640##6##, ####REF##12935175##7##, ##REF##12808153##8##, ##REF##17092029##9##, ##UREF##4##10##, ##REF##16723429##11##, ##REF##16646815##12####16646815##12##]. For example it has been shown that the probes saturate at higher transcript concentrations which gives rise to a non-linear relation between intensity and transcript concentration. Moreover, benchmark studies have indicated that the proper correction for non-specific background intensity contributions is presumably the most problematic preprocessing step with no satisfactory solution so far.</p>", "<p>The immediate aim of most of these papers and also of our previous work [##UREF##0##1##,##UREF##5##13##, ####UREF##6##14##, ##REF##15834006##15##, ##REF##16171364##16##, ##UREF##7##17##, ##UREF##8##18####8##18##], has been to study the physical (and chemical) processes responsible for converting concentrations of specific target RNA of known sequences to measured fluorescence intensities after hybridization. However, the ultimate, still not-achieved aim of these physical approaches has been to provide scientists with feasible calibration methods which estimate absolute specific target concentrations in the presence of a complex non-specific background from fluorescence intensity data.</p>", "<p>Proper calibration of microarray data includes several tasks: Firstly it requires the determination of the model describing the basic relationship between the probe intensity and the specific transcript concentration under consideration of relevant parasitic effects which should be straightened out.</p>", "<p>Secondly, the magnitude of these effects should be estimated using the intensity information of a given chip or of a series of chips, and, thirdly, one needs practicable algorithms which judge the quality of a particular hybridization and estimate the expression degree from the intensity values.</p>", "<p>Moreover, except MAS5 all popular preprocessing methods [##UREF##1##2##, ####UREF##2##3##, ##UREF##3##4##, ##REF##11134512##5####11134512##5##] rely on multichip-algorithms for calibration, i.e. they process a series of chips at once together to separate chip- and probe-level effects from each other. The obtained expression measures are consequently context-sensitive and require a minimum number of chips for appropriate data-processing (usually more than four). As a consequence the results are constricted to a particular series of chips, i.e. they depend on the particular selection of chips and require re-calculation upon adding or removing chips. The development of single chip calibration methods is therefore an important additional task to provide virtually context-insensitive expression measures which can be compared between chips and experimental series without reprocessing. This issue requires appropriate metrics for expression measures to enable direct comparison of data from different experiments in consistent units.</p>", "<p>This paper addresses these tasks and presents a new single-chip calibration method for microarrays based on a physical model of hybridization. Our so-called hook-method provides a graphical summary of the hybridization characteristics of each microarray which directly transforms into a sort of natural metrics for intensity calibration with the potential to estimate expression values on an absolute scale. This metrics uses mismatched probes on Affymetrix GeneChip arrays as internal reference for judging the hybridization of the perfect matched probes over the whole potential concentration range.</p>", "<p>In the first part of the paper we outline the calibration model and validate its relevance using single probe benchmark data. In the second part we apply the model to single chip data and describe the analysis algorithm step by step. Table ##TAB##0##1## summarizes the essential notations and symbols used in the paper. Examples which illustrate the performance of the method are presented in the accompanying publication [##REF##18759984##19##].</p>" ]

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[ "<title>4. Summary and Conclusion</title>", "<p>The improvement of microarray calibration methods in combination with the development of meaningful quality standards is an essential prerequisite for obtaining absolute expression estimates which in turn are required for the quantitative analysis of transcriptional regulation. In this publication we present a new method of microarray data analysis based on a physical model. This so-called hook method pre-processes the raw intensity data for further downstream analyses on one hand, and, on the other hand, provides chip characteristics with potential applications in hybridization quality control and array normalization.</p>", "<p>The method is based on the Langmuir-hybridization model which provides a physically adequate and computationally feasible approach for microarray intensity calibration with the potency to improve existing methods. Our hook-calibration method uses this model together with the positional-dependent nearest-neighbour affinity correction. It is based on the linear transformation of the intensities of PM and MM probes from one chip into Δ-vs-Σ coordinates, probe-set averaging and smoothing. Here, the MM probes serve as an internal reference subjected essentially to the same hybridization law as the PM, however with modified characteristics. Figure ##FIG##10##11## and Table ##TAB##1##2## summarize the essential steps of the algorithm together with the output characteristics provided by the method.</p>", "<p>The obtained hook-curve can be interpreted as a special representation of the binding isotherm where the explicit dependence of the probe intensities on the (usually unknown) transcript concentrations is replaced by the (experimentally available) relation between the PM- and the MM-probe intensities. It enables clear differentiation between different, well-defined regimes and it provides a set of chip summary characteristics which evaluate the performance of a given hybridization in terms simple parameters such as the mean non-specific background intensity, its saturation value, the mean PM/MM-sensitivity gain and the fraction of absent probes. The hook curve spans a natural metrics system for the expression estimates which reflects essential hybridization characteristics in terms of its geometric dimensions, width, height and \"start\"-coordinates.</p>", "<p>The obtained single chip characteristics in combination with the sensitivity corrected probe-intensity values provide expression estimates scaled in natural units given by the binding constants of the particular hybridization. This way the method corrects the raw intensities for the non-specific background hybridization in a sequence-specific manner, for the potential saturation of the probe-spots with bound transcripts and for the sequence-specific binding of specific transcripts.</p>", "<p>In the accompanying publication we illustrate the performance and potential applications in terms of quality control and expression analysis using a series of selected chip-types, hybridization conditions and benchmark experiments [##REF##18759984##19##].</p>", "<p>The beta-version of the hook-program can be downloaded from <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.izbi.de\"/>. The stand-alone JAVA program processes single-chips and chip-series in a batch-mode according to the scheme given in Figure ##FIG##10##11## and Table ##TAB##1##2##. Chip and probe-set related characteristics such as expression degrees, hook-curves and sensitivity profiles are exported in html- as well as in tabular form and jpg-graphics.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background:</title>", "<p>The improvement of microarray calibration methods is an essential prerequisite for quantitative expression analysis. This issue requires the formulation of an appropriate model describing the basic relationship between the probe intensity and the specific transcript concentration in a complex environment of competing interactions, the estimation of the magnitude these effects and their correction using the intensity information of a given chip and, finally the development of practicable algorithms which judge the quality of a particular hybridization and estimate the expression degree from the intensity values.</p>", "<title>Results:</title>", "<p>We present the so-called hook-calibration method which co-processes the log-difference (delta) and -sum (sigma) of the perfect match (PM) and mismatch (MM) probe-intensities. The MM probes are utilized as an internal reference which is subjected to the same hybridization law as the PM, however with modified characteristics. After sequence-specific affinity correction the method fits the Langmuir-adsorption model to the smoothed delta-versus-sigma plot. The geometrical dimensions of this so-called hook-curve characterize the particular hybridization in terms of simple geometric parameters which provide information about the mean non-specific background intensity, the saturation value, the mean PM/MM-sensitivity gain and the fraction of absent probes. This graphical summary spans a metrics system for expression estimates in natural units such as the mean binding constants and the occupancy of the probe spots. The method is single-chip based, i.e. it separately uses the intensities for each selected chip.</p>", "<title>Conclusion:</title>", "<p>The hook-method corrects the raw intensities for the non-specific background hybridization in a sequence-specific manner, for the potential saturation of the probe-spots with bound transcripts and for the sequence-specific binding of specific transcripts. The obtained chip characteristics in combination with the sensitivity corrected probe-intensity values provide expression estimates scaled in natural units which are given by the binding constants of the particular hybridization.</p>" ]

[ "<title>2. Calibration model for microarray data</title>", "<title>The competitive two-species Langmuir model of microarray hybridization</title>", "<p>We emphasize on Affymetrix GeneChip microarray data obtained after the chips have been hybridized, scanned and the images have been summarized into hundred-thousands of paired intensity values of perfect match (PM) and of mismatched (MM) probes. The intensities of probe \"p\" on chip \"c\" are well described using the Langmuir adsorption isotherm [##REF##16646815##12##,##UREF##6##14##,##REF##14747310##20##, ####REF##12655013##21##, ##UREF##9##22####9##22##],</p>", "<p></p>", "<p>Here the superscript denotes the probe-type (P = PM, MM). The indices \"p\" and \"c\" assign probe- and chip-specific parameters, respectively. The probe-index implies the chip specificity as well, i.e. p = p, c. This model predicts that the fraction of \"occupied\", i.e. dimerized oligonucleotides of a probe spot, Θ_p^P(also called surface probe coverage or occupancy), is directly related to the observed intensity, I_p^P* [##UREF##6##14##,##UREF##8##18##]. The proportionality constant, M_c, specifies the maximum intensity referring to complete occupancy, Θ_p^P= 1, if all oligonucleotides of the respective probe spot on the given chip are dimerized. The minimum intensity referring to the absence of bound transcripts, Θ_p^P= 0, gives rise to the \"optical\" background intensity, O_c. Throughout the paper we will consider only \"net\" intensities which have been corrected for the optical background before further analysis, , using, for example, the zone-algorithm provided by Affymetrix [##UREF##10##23##].</p>", "<p>The surface coverage changes as a hyperbolic function of the \"binding strength\", X_p^P, which additively decomposes into contributions due to specific and non-specific hybridization</p>", "<p></p>", "<p>Since the binding strengths follow the mass action law they are related to the concentration of specific and non-specific transcripts, [S]_pand [N]_c, respectively, and to the respective effective association constants of duplex formation, K_p^P,h(h = S, N) (see [##UREF##0##1##] for details),</p>", "<p></p>", "<p>The latter equation assumes that the large number of different non-specific RNA-fragments in the hybridization solution effectively acts like a single species with the common concentration [N]_cfor all probes of the chip [##REF##15834006##15##,##REF##16171364##16##]. Contrarily, the concentration of specific transcripts, [S]_p, refers to a particular probe sequence, i.e., it represents a \"single probe\"-property. Microarrays of the GeneChip-type use so-called probe sets of several probes (usually N_set= 11) for estimating the expression of each considered gene. One expects therefore that all probes of a set probe the same, common transcript concentration, i.e. [S]_set= [S]_pfor p ∈ set assuming that effects as alternative splicing have been appropriately considered during probe design.</p>", "<p>The competitive two-species Langmuir adsorption isotherm (Eq. (1)) considers the effects of non-specific \"background\" hybridization and of saturation at small and large concentrations of specific transcripts, respectively. The maximum intensity at saturation, M_c, depends on factors such as the number of oligonucleotides per probe spot (which in turn is related to the density of oligomers and to the spot size), the mean number of optical labels per bound target and the settings of the scanner. These factors affect the PM and MM nearly in the same fashion giving rise to virtually identical values of M_cat complete saturation of the probe spots under equilibrium conditions (X_p^P&gt;&gt; 1) [##REF##16171364##16##,##UREF##8##18##].</p>", "<p>Recent studies report significantly higher limiting intensity values of the PM, compared with that of the MM, i.e. M^PM&gt; M^MM[##UREF##9##22##]. They interpreted this result assuming a probe-dependent partial dissociation of the duplexes during the post-hybridization washing phase. Another, additional explanation might be the truncation of a considerable amount of the probe oligomers due to incomplete synthesis because this effect causes the asymptote-like flattening of the hybridization isotherms at intermediate and large transcript concentrations in a sequence-dependent manner [##UREF##0##1##,##REF##17092029##9##].</p>", "<p>We will apply in the following analysis the special-case of the common intensity asymptote for all probes of the chip according to Eq. (1). Possible consequences of deviations from this assumption for the data analysis will be addressed in a separate study.</p>", "<title>Matched and mismatched microarray probes</title>", "<p>The probes on expression microarrays of the GeneChip-type are usually designed in a pairwise fashion. Each probe pair consists of 25-meric PM- and MM-probes where the PM-sequence is assumed to perfectly match a 25-meric section of the target gene. The MM-sequence differs from that of the PM by a single complementary mismatch in the centre of the sequence. The different middle bases of both probes of one pair cause different base pairings in the respective probe/target-duplexes and thus different binding constants (see below and [##REF##16171364##16##]). Let us define the pairwise PM/MM ratio of the binding constants of specific and non-specific hybridization,</p>", "<p></p>", "<p>respectively, which specify the noted effect of different base-pairings formed by the PM and MM. For example, the binding strength of the complementary Watson-Crick (WC) base-pairings in the middle of the specific duplexes of the PM exceeds that of the specific duplexes of the MM which form a weaker self-complementary mismatch at this position [##REF##15834006##15##, ####REF##16171364##16##, ##UREF##7##17##, ##UREF##8##18####8##18##]. For the ratio of the specific binding constants one consequently obtains s_p&gt; 1. Contrarily, for the ratio of the non-specific binding constants one gets n_p&lt; 1 for purines (Adenine, Guanine) and n_p&gt; 1 for pyrimides (Thymine, Cytosine) in the middle of the PM sequence owing to the purine-pyrimidine asymmetry of Watson-Crick (WC) base-pair interactions in RNA/DNA duplexes [##UREF##5##13##,##REF##7545436##24##]. Hence, the parameters s_pand n_pspecify the PM/MM-affinity gain of a selected probe pair upon specific and non-specific binding, respectively. Both, PM and MM probes obey the hyperbolic adsorption isotherm, Eq. (1) [##UREF##8##18##]. With Eq. (4) one obtains for the binding strengths of the PM and MM probes</p>", "<p></p>", "<p>Eq. (5) scales the intensity of the PM and MM probes as a function of the relative hybridization degree,</p>", "<p></p>", "<p>This S/N-ratio, R, provides the specific binding strength of the PM in units of the non-specific one. It can serve as a relative measure of the expression degree because it is directly related to the concentration of specific transcripts, [S]_p. It scales the expression degree in a probe-specific fashion.</p>", "<p>Part a of Figure ##FIG##0##1## shows the courses of the intensities of a typical PM/MM pair as a function of the parameter R (see Eq. (6)). The PM intensity sigmoidally increases from its minimum value, I_p(R = 0), to I_p(R = ∞) = M_c, at small and large abscissa values, respectively. The respective probes referring to these limiting cases are either exclusively non-specifically hybridized or completely saturated with surface coverages of Θ_p^PM(0) = X_p^PM,N/(1 + X_p^PM,N) ≈ X_p^PM,Nand Θ_p^PM(∞) = 1, respectively. The concentration and S/N-ratio referring to the inflection point of the isotherm at half-way between these values are</p>", "<p></p>", "<p>respectively. They specify the condition at which 50% of the free probes available in the absence of specific transcripts become occupied. The approximations at the right-hand side of Eq. (7) refer to small X_p^PM,N&lt;&lt; 1.</p>", "<p>The MM intensity responds in a very similar fashion as that of the PM with increasing R (see part a of Figure ##FIG##0##1##). The limiting surface coverage of exclusively non-specifically hybridized MM probes at R = 0 is changed compared with that of the PM (see Eq. (4)), Θ_p^MM(0) = X_p^PM,N/(n_p+ X_p^PM,N) ≈ X_p^PM,N/n_p. The isotherm of the MM is clearly shifted to larger abscissa values in the intermediate R-range owing to the smaller binding strength for specific hybridization (s_p&gt; 1, see above). For the inflection point of the isotherm one obtains in analogy to Eq. (7)</p>", "<p></p>", "<p>which shows that the horizontal shift between the PM- and MM-isotherms is log(s_p) and log(s_p/n_p) in the log-scale of [S] and R, respectively.</p>", "<title>The delta- and sigma-transformations</title>", "<p>The MM probes were designed as reference for estimating the non-specific background contribution to the respective PM intensity [##UREF##1##2##,##REF##11134512##5##,##UREF##11##25##]. The \"simple\" subtraction of the MM-intensity from that of the PM however partly failed as correction method because both probes differently respond to non-specific and specific hybridization due to their complementary middle bases which, for example, gives rise to negative PM-MM intensity differences [##REF##15834006##15##].</p>", "<p>According to the Langmuir model, the behaviour of the PM and MM can be understood on the basis of the same hybridization rules where both probe types however differ with respect to their effective association constants for probe/target dimerization (see above). The intensities of the PM and MM are consequently expected to correlate in a well defined fashion. This mutual relation is determined by the mismatch design of the reference probe, the particular probe sequences and by the concentrations of specific and of non-specific RNA fragments in the sample solution used for hybridization on the particular chip [##UREF##8##18##].</p>", "<p>Let us empirically analyze the relation between the PM and MM signals in terms of two simple linear combinations of the log-intensities of a probe pair, namely their difference and average value,</p>", "<p></p>", "<p>(log ≡ log₁₀is the decadic logarithm). The intensity model predicts for this transformation (see Eqs. (1) and (5))</p>", "<p></p>", "<p>with the \"start\", \"linear\" and the \"saturation terms\"</p>", "<p></p>", "<p></p>", "<p></p>", "<p>respectively. The limiting values of Σ(R) and Δ(R) in the absence of specific transcripts (R = 0) are</p>", "<p></p>", "<p>In the limit of weak non-specific binding (X_p^P,N&lt;&lt; 1) the o-terms vanish and the limiting Δ- and Σ-coordinates are given by their start values. The probe-specific exponents in Eq. (10) are defined as</p>", "<p></p>", "<p>In summary, the hyperbolic intensity functions of the PM and MM can be transformed into Δ and Σ coordinates which are governed by essentially four parameters, the start values Δ_p^start≅ Δ_p(0) and Σ_p^start≅ Σ_p(0) and the exponents <italic>α</italic>_pand <italic>β</italic>_p. They were chosen to provide a simple geometrical interpretation of the Δ-vs-Σ trajectory in terms of its start-coordinates and its vertical and horizontal dimension with respect to the start values (see below and Figure ##FIG##0##1## and Figure ##FIG##1##2##).</p>", "<title>The hybridization regimes</title>", "<p>Part b and c of Figure ##FIG##0##1## show the transformed intensities taken from part a of the figure as a function of the parameter R = R_p^PM. The course of the log-difference, Δ_p(R), can be roughly divided into five regimes which reflect different hybridization characteristics of the PM and the MM probes with increasing degree of specific hybridization (see Figure ##FIG##0##1##, part b):</p>", "<p>(1) <bold>N-regime</bold>: In the non-specific-regime, at small values R → 0, both, the PM and MM nearly exclusively hybridize with non-specific transcripts. Saturation can be typically neglected in this range (B_p^P≈ 1, see Eqs. (10) and (11)). The limiting ordinate value for X_p^P,N&lt;&lt; 1 estimates the ratio of the binding constants referring to the respective pair of complementary middle bases in the PM and MM sequences, Δ_p(0) ≈ log n_p(see Eq. (4)). We will use the approximation of weak non-specific binding throughout the paper.</p>", "<p>(2) <bold>mix-regime</bold>: In the subsequent mixed-regime, both, specific and non-specific transcripts significantly contribute to the observed intensity of the probes. The log-difference Δ increases with increasing amount of specific transcripts. The positive slope of Δ_p(R) implies ∂Δ/∂R ~ (1-10^{-<italic>α</italic>}) &gt; 0, and thus <italic>α</italic>_p&gt; 0 or equivalently s_p&gt; n_p(see Eq. (12)). The increase of Δ_p(R) consequently reflects the simple fact that the specific binding constant of the PM exceeds that of the respective MM, i.e., K_p^PM,S&gt; K_p^MM,S, if one assumes K_p^PM,N≈ K_p^MM,N(see below and Eq. (4)).</p>", "<p>(3) <bold>S-regime</bold>: In the specific-regime the probes predominantly hybridize with specific transcripts. As a consequence, Δ_preaches a maximum at with the ordinate value</p>", "<p></p>", "<p>This rough approximation assumes Δ_p(0) &lt;&lt; 1 &lt;<italic>β</italic>_pand R_max&gt;&gt; 1. At conditions of weak saturation Eq. (13) simplifies with 0.5 (<italic>β</italic>_p- <italic>α</italic>_p) &gt;&gt; 1 into . At these conditions the height of the maximum directly provides the log-transformed PM/MM-ratio of the specific binding constants, <italic>α</italic>_p.</p>", "<p>(4) <bold>sat-regime</bold>: In the saturation-regime the probes become progressively saturated with bound transcripts (B_p^P&gt; 1). This effect first and foremost affects the PM due to their higher specific binding constant (see above). As a consequence Δ_pstarts to decrease.</p>", "<p>(5) <bold>as-regime</bold>: At very large expression degrees both, PM and MM reach their maximum intensity upon complete saturation. In this asymptotic-regime the trajectory reaches the abscissa for R → ∞, Δ_p(∞) ≈ 0 (see Eq. (10)).</p>", "<p>The respective log-sum of the intensities, Σ_p(R), is shown in part c of Figure ##FIG##0##1##. It varies in a similar, sigmoidal fashion as the individual log-intensities of the PM and MM (compare part a and c of Figure ##FIG##0##1##). Here the mix-, S- and sat-regimes merge into one region of increasing Σ whereas the N- and as-regimes provide the minimum and maximum values, and Σ_p(∞) = log M_c, respectively. With Eqs. (11) and (12) one obtains for the difference</p>", "<p></p>", "<p><italic>β</italic>_pspecifies the span between the maximum and minimum Σ-values. The Σ-coordinate of the maximum of Δ_p(R) at R = R_maxbecomes</p>", "<p></p>", "<p>Eqs. (15) and (14) provide , i.e., the maximum of Δ_{<italic>p</italic>}(<italic>R</italic>) roughly bisects the total range of the Σ-coordinate.</p>", "<title>The Δ-vs-Σ trajectory</title>", "<p>In the next step we plot the transformed intensities into Δ-vs-Σ coordinates (see Figure ##FIG##1##2##, part a). This presentation, also known as M-vs-A plot (difference-vs-sum), reflects the binding isotherms of a PM/MM-probe pair. The obtained Δ-vs-Σ trajectory shows a characteristic curved shape with start-, end- and maximum-points referring to the S/N-ratios R = 0, R = ∞ and R = R_max, respectively. They consequently define the N-, as- and S-hybridization regimes. The mix- and sat-regimes can be attributed to the increasing and decreasing parts of the Δ-vs-Σ trajectory, respectively.</p>", "<p>The parameters <italic>α</italic>_pand <italic>β</italic>_pdefine the height and the width of the obtained Δ-vs-Σ curve (see also Eqs. (13) and (14)). The Δ- and Σ-coordinates of the characteristic points depend on the PM/MM-ratios of the binding constants (see Eq. (4)), on the maximum intensity, Σ_p(∞) = logM_c, and on the mean intensity of the chemical background due to non-specific hybridization, Σ_p(0) ∝ log(I_p^PM(0)) + log(I_p^MM(0)). Hence, the Δ-vs-Σ trajectory links the observed probe intensities with essential hybridization characteristics in terms of simple geometric parameters.</p>", "<p>The horizontal scale of the Δ-vs-Σ trajectory</p>", "<p>In the Appendix A we show that the difference between the actual Σ-coordinate and its \"asymptotic-value\", Σ_p-Σ_p(∞), estimates the mean probe coverage of the PM and MM probes</p>", "<p></p>", "<p>whereas the difference between the Σ-coordinate and its \"start value\", Σ_p-Σ_p(0) characterizes the relation between the amount of specific and non-specific hybridization in terms of the fraction of specifically occupied binding sites of the respective probe spot</p>", "<p></p>", "<p>Eqs. (16) and (17) provide mean values averaged over the respective PM/MM-probe pair. The \"individual\" coverages of the PM and MM probes, Θ_p^PMand Θ_p^MM, and the respective fraction of specifically hybridized oligomers, x_p^PM,Sand x_p^MM,S, in addition depend on the relative Δ-coordinates Δ-Δ(∞) and Δ-Δ(0), respectively (see Eqs. (42) and (45) in the Appendix A).</p>", "<p>Part b of Figure ##FIG##1##2## shows the surface coverage and the fraction of specifically occupied oligomers for the Δ-vs-Σ trajectory plotted in part a of the figure. Note that x^{P, S}and Θ^Pexponentially scale with the coordinate differences Σ-Σ(0) and Σ-Σ(∞), respectively (see Eqs. (17) and (16), respectively).</p>", "<p>Consequently, the fraction of specifically occupied probes steeply increases in the raising part of the Δ-vs-Σ trajectory (mix-regime) whereas the probe coverage steeply increases in its decaying part (sat-regime). The contribution of non-specific hybridization and/or the effect of saturation of a particular probe can be essentially neglected if the distance of its Σ-coordinate from the start and/or end points exceeds unity. Particularly, one obtains &lt;x_p^S&gt; &gt; 0.9 for Σ-Σ(0) &gt; 1 and &lt; Θ_p&gt; &lt; 0.1 for Σ(∞)-Σ &lt; 1.</p>", "<p>The horizontal shift between the PM-and MM-curves in part b of Figure ##FIG##1##2## illustrates the \"delayed response\" of the MM with respect to the specific transcript concentration: The MM reach a certain ordinate-level of the surface coverage and of the fraction of specifically bound probes at larger abscissa values and thus at larger concentrations of specific transcript concentrations than the PM (see also Eqs. (7) and (8)).</p>", "<p>The fraction of specifically bound probes directly transforms into the mean S/N-ratio of the PM and MM (see Appendix A and also Eq. (6)),</p>", "<p></p>", "<p>For abscissa values Σ &lt; Σ(∞) -1, Eq. (18) simplifies into log(&lt;R&gt; + 1) ≈ Σ-Σ(0). Hence, the Σ-axis nearly linearly scales with the logarithm of the mean S/N-ratio. For the S/N-ratio of the PM, this equation modifies into (see Eq. (46) below), i.e., it depends in addition on the vertical coordinate of the Δ-vs-Σ trajectory.</p>", "<p>For intermediate abscissa values, Σ(0) + 1 &lt; Σ &lt; Σ(∞) -1, the occupancy of the probe spots (Eqs. (16) and (42)) provide an approximation of the binding strength of specific hybridization of the PM and MM probes (Θ_p^P≈ X_p^P,S, see also Eq. (1)) and of their mean</p>", "<p></p>", "<p>In summary, the position of a probe-point along the Σ-coordinate estimates the hybridization degree of the respective probe spot in terms of relative concentration measures characterizing either the S/N-ratio (Eq. (18)), the relative occupancy of the probe oligomers with specific transcripts (Eq. (17)), their overall degree of occupancy of (Eq. (16)) and the specific binding strength of the considered probe pair (Eq. (19)).</p>", "<p>The probe coverage (Eq. (16)) provides an additional interpretation of the horizontal dimensions of the Δ-vs-Σ trajectory: For the N-point one obtains with Σ = Σ(0) the coverage due to non-specific hybridization, , because (almost) exclusively non-specific transcripts bind to the probes. Note that this \"non-specific\" coverage is exponentially related to the \"width\"-exponent, <italic>β</italic>_p(see Eq. (14)), and thus to the horizontal distance between the N- and the as-points. The remaining, not-occupied and thus free oligomers serve as potential binding sites for specific targets, i.e., . The horizontal dimension of the Δ-vs-Σ trajectory consequently specifies the maximum amount of free probes available for specific binding at R = 0 and thus the measurement range of the probe spots for estimating the expression degree. The narrowing of the model curves reflects the diminishing capacity of the respective probes for specific transcript binding. Figure ##FIG##2##3## (part a) illustrates the narrowing of the Δ-vs-Σ trajectory upon increasing the non-specific background contribution. The special ideal case <italic>β </italic>= -∞ consequently refers to hybridization without non-specific background.</p>", "<title>The vertical scale of the Δ-vs-Σ trajectory</title>", "<p>The Δ-coordinate of a probe is directly related to the so-called discrimination score DS used by Affymetrix as a relative measure of the PM-MM intensity difference.</p>", "<p></p>", "<p>The discrimination score roughly estimates the fraction of the signal due to specific hybridization (see [##UREF##12##26##]). The approximation on the right hand side of Eq. (20) seems save for small values DS &lt;&lt; 1.</p>", "<p>The discrimination score serves as the basic parameter in the MAS5-algorithm to calculate the so-called detection call (DC) which judges the \"presence\" or \"absence\" of a gene. Hence, the vertical scale of the Δ-vs-Σ trajectory is related to the detection call: the higher the Δ_p-value of a probe the higher the probability of the presence of the respective specific transcript in the hybridization solution. We will discuss this point more in detail in the accompanying paper in connection with our alternative method for classifying the genes into present and absent ones (see below).</p>", "<p>The vertical scale of the Δ-vs-Σ trajectory admits an additional interpretation in terms of different strengths of the base pairings of the PM and MM probes. Particularly, the Δ-coordinates of the N- and the S-points estimate the ratio of the binding constants of the PM and MM upon specific and non-specific hybridization according to Eqs. (4), (11) and (13). We have previously shown that the log-ratio of the binding constants of the PM and MM probes can be interpreted in terms of the effective free energy difference for duplex formation with the respective targets [##REF##15834006##15##,##REF##16171364##16##,##UREF##8##18##]. For the MM-design used for GeneChip expression arrays it roughly refers to the effective free energy change upon replacement of the Watson Crick (WC) pairing in the middle position of the probe/target duplexes with the respective self complementary (SC) pairing in the specific duplexes and with the complementary WC-pairing in the non-specific duplexes, respectively, i.e.,</p>", "<p></p>", "<p>Here Δ<italic>ε</italic>₁₃^WC-SCdenotes the dimensionless free energy gain (given in units of the thermal energy, RT) upon replacements of the type B•b^c→ B^c•b^c(i.e. WC → SC) for the base B_p= A, T, G, C at sequence position 13 of the probe (for example, C•g → G•g; upper case letters refer to the DNA-probe; lower case letters refer to the bound RNA-fragment, b = a, u, g, c; the superscript \"c\" indicates the respective complement). Accordingly, Δ<italic>ε</italic>₁₃^WC-WCis the respective free energy change upon WC-reversals, B•b^c→ B^c•b (for example, C•g → G•c).</p>", "<p>Hence, the ordinate position of the starting point of the Δ-vs-Σ trajectory estimates the effective free energy change upon replacing the central base in complementary WC-pairings, i.e. Δ_p(0) ≈ -Δ<italic>ε</italic>^WC-WC(B_p) (see Eqs. (11) and (21)). The relative ordinate value of the maximum is related to the respective free energy change upon replacing the central WC-pairing in the specific PM-duplexes by the respective SC-pairing in the MM-duplexes, i.e. Δ_p(R_max) ≈ -Δ<italic>ε</italic>^WC-SC.</p>", "<p>Figure ##FIG##2##3## illustrates that the maximum height of the Δ-vs-Σ trajectory starts to decrease for relatively small widths referring to large strengths of non-specific hybridization (<italic>β</italic>_p&lt; 3) because saturation onsets almost in the mix-range. In such cases the observed vertical dimension of the trajectory potentially underestimates the height-parameter <italic>α</italic>_p(see Eq. (13)) which however can be obtained by appropriate curve fitting using Eq. (10) (see below).</p>", "<p>In summary, the Δ-vs-Σ trajectory spans a sort of natural or intrinsic metric system between distinctive points which characterizes the binding thermodynamics of the probes of the particular microarray. The horizontal dimension characterizes the measurement range of the respective probe whereas the vertical dimension reflects the free energy gain due to the change of the central base pairing in the respective duplexes of the PM and MM probes.</p>", "<title>Δ-vs-Σ trajectories of individual probes</title>", "<p>Each probe is characterized by its \"individual\" Δ-vs-Σ trajectory which describes the intensity change upon increasing content of S-transcripts in the range 0 ≤ R ≤ ∞. We used the Affymetrix HG-133 spiked-in data-set to study the R-dependence of selected probes <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.affymetrix.com/support/technical/sample_data/datasets.affx\"/>. This data set was generated by Affymetrix to calibrate the observed intensities on the basis of known transcript concentrations. Particularly, transcripts referring to 42 selected genes were titrated with increased concentration onto a series of chips using the Latin-squares design. The non-specific background was taken into account by adding a HeLa-cell line extract to all hybridizations which does not contain the spiked-in transcripts.</p>", "<p>Part a of Figure ##FIG##3##4## shows the trajectories of six selected probes together with fits by means of Eq. (10) (compare curves and symbols). The probe-labels 1 to 6 are chosen to increase with increasing number of C and decreasing number of A per probe sequence (see Figure ##FIG##3##4##). The observed intensities and thus also the trajectories are functions of the binding constants for DNA/RNA duplex formation, which in turn depend on the sequences of the 25 meric probes. For example, the binding affinity of C•g WC-pairings exceeds that of A•u pairs in the hybrid duplexes. In general, the probes with a higher amount of cytosines are therefore expected to bind the RNA fragments more strongly than probes with a higher amount of adenines. Equation (3) predicts for the increase of K_p^P,N(and of logX_p^PM,N, see Eq. (3)) the decrease of the horizontal dimensions, <italic>β</italic>_p, of the respective probe-trajectory.</p>", "<p>Indeed, the increase of the cytosine-content causes the narrowing of the trajectories by the shifting of their start-point, Σ_p(0), towards larger abscissa values at invariant Σ_p(∞) = const., which is assumed to be constant across all probes because of their common maximum binding capacity. Note that the width of the trajectories and thus the binding strength of the non-specific background varies over about two orders of magnitude, logX_p^PM,N≈ -4 to -2, for the six selected probes.</p>", "<p>The Δ-coordinates of the starting- and maximum-points of the selected probe-trajectories show considerable variation without obvious correlation to their sequence characteristics. We calculated the trajectories of all spiked-in probes (~500) using the results of our previous analysis of the hybridization isotherms (see refs. [##UREF##8##18##] and [##REF##16171364##16##] for details) to estimate the variance of the positions of their starting- and maximum-points. The boxplot in part b of Figure ##FIG##3##4## visualizes the center and the width of the distributions of the obtained Δ_p(0)- and Δ_p(R_max)-data in vertical and horizontal directions.</p>", "<p>The respective coordinates of the individual probe-trajectories depend mainly on the particular probe pairings of the middle bases in the non-specific and specific duplexes, respectively (see Eqs. (11) – (13) and (21)). To filter out the underlying sequence effects we calculated \"mean\" trajectories for all probe pairs with a certain middle base (see Figure ##FIG##3##4##, part b). These middle-base related mean trajectories are shifted each to another in vertical direction according to C ≈ T &gt; G ≈ A for the N-, and C &gt; G ≈ T &gt; A for the S-point, respectively. This systematic trend is in agreement with Eq. (21) which predicts that the vertical positions of the N- and S-points are functions of the middle base of the respective probe sequences. The observed relations reflect the purine-pyrimidine asymmetry of binding strength of complementary WC-pairings at the N-point (i.e., Δ<italic>ε</italic>₁₃^WC-WC(B) ≠ Δ<italic>ε</italic>₁₃^WC-WC(B^c)) and the higher stability of the WC-pairings compared with SC-mismatches at the S-point, Δ<italic>ε</italic>₁₃^WC-SC(B) (see Eq. (21)). Note that the specific binding constants of PM exceed that of the MM on the average by the factor of s ≈ 7 whereas for non-specific binding one obtains a mean ratio of n ≈ 1.2.</p>", "<p>The comparison of the middle-base related trajectories with the width of the N- and S-boxes indicates that the systematic effect due to the middle-base explains the variability of the Δ_p(0)- and Δ_p(R_max)-coordinates in the limits of their 25% and 75% quartiles. The consideration of the nearest neighbors of the middle base further broadens this range: For illustration we show the respective mean trajectories for the \"middle triples\" CCC and CGC which provide the strongest and weakest binding affinities among the 64 possible combinations of three adjacent bases, respectively (see [##UREF##8##18##] and [##UREF##5##13##]).</p>", "<p>In summary, the transformed intensity data of individual probes are well described by the Δ-vs-Σ trajectories predicted by the Langmuir-isotherms. The presented data illustrate the probe-specific variability of the Δ-vs-Σ trajectories due to sequence effects. The positions of the start- and maximum-points can be attributed to the differences between the PM and MM probe-sequences which affect the respective binding constants in a middle-base dependent fashion.</p>", "<title>3. The hook-algorithm for single-chip calibration</title>", "<p>The Δ-vs-Σ trajectories describe the behaviour of PM/MM-probe intensities as a function of the RNA-concentration on a relative scale. The analysis of probe-specific trajectories seems not applicable for probe data which are taken from a single chip because each probe pair refers exactly to only one concentration and thus to only one point along its \"individual\" Δ-vs-Σ trajectory. On the other hand, the large number of probes per chip (and the presence of considerable amounts of specific targets) lets us suggest that their hybridization degrees usually cover the whole potentially possible concentration range. Our idea is to characterize the performance of a particular hybridization experiment in terms of its mean Δ-vs-Σ trajectory averaged over all probes of one particular microarray in analogy to the \"individual\" Δ-vs-Σ trajectory of each single probe. The horizontal and vertical dimensions of this mean Δ-vs-Σ trajectory are expected to provide the hybridization metrics of the considered chip in terms of characteristic concentration measures (e.g. the mean level of non-specific background or the mean occupancy and saturation level of the probe spots) and of characteristic effective free energy differences due to the used mismatch-design of the probe pairs.</p>", "<title>The raw hook curve</title>", "<p>To construct the mean Δ-vs-Σ trajectory we plot the PM-MM log-intensity difference of all probe pairs of a particular chip, Δ_p, versus the set-averaged log intensity of the respective probe set, &lt;Σ&gt;_set, in a first step (see Eq. (9) and part a of Figure ##FIG##4##5##). Additional set-averaging of the log-difference, &lt;Δ&gt;_set, reduces the scatter width of the data points along the ordinate roughly by the factor of ~ √N_set~ 3 (see the yellow dots in Figure ##FIG##4##5##). In the next step we smoothed these data by calculating the moving average over a sliding window of N_mov≈ 100 subsequent probe sets along the abscissa to extract the mutual dependence between &lt;Δ&gt;_setand &lt;Σ&gt;_set. The resulting plot is called (raw-) hook-curve because of its typical shape (see part b of Figure ##FIG##4##5##). Each probe-set is characterized by its \"hook\"-coordinates, Σ^hook= &lt;Σ&gt;_p∈setand Δ^hook= &lt;&lt;Δ_p&gt;_p∈set&gt;_mov.</p>", "<p>The shape of the hook curve basically agrees with that of the Δ-vs-Σ trajectory (compare with Figure ##FIG##1##2##). We attribute the rising and decaying part and the maximum in-between to the mix-, sat- and S-regimes, respectively, which refer to the mean hybridization level of the respective probes on the chip. The hook-curve obviously does not reach the asymptotic as-regime with Δ(∞) ≈ 0. This result does not surprise because complete saturation is usually circumvented by reasonably chosen hybridization conditions. Otherwise the probes completely lose their sensitivity to detect changes of the transcript concentration [##UREF##6##14##].</p>", "<p>At small abscissa values the hook curve starts with a virtually horizontal part (slope(N) &lt; 0.1) which is separated from the subsequent mix-range (slope(mix) &gt; 0.6) by a distinct break-point. In the appendix we show that the observed initial tiny slope can be explained by the relative strong correlation between the intensities of non-specifically hybridized PM- and MM-probes in the absence of specific transcripts (<italic>ρ </italic>&gt; 0.7, see Eq. (49)) which in turn seems reasonable in view of the nearly equal sequences of both probe-types which suggest similar variations of the sequence-specific bindings strengths from probe pair to probe pair. On the other hand, for the mix-region the hybridization model predicts a considerably increased slope of slope(mix) ≈ 1.15·<italic>α</italic>_p≈ 0.9 &gt; slope(N) ≈ 0.8 (see Eqs. (47) and (49) with·<italic>α </italic>&gt; 0.8 and <italic>ρ </italic>&gt; 0.7, respectively). Hence, the break in the course of the hook-curve can be explained by the onset of specific hybridization for probes (and probe-sets) located on the right from this point.</p>", "<p>Accordingly, the break-point between the N- and mix-ranges was used to classify the probe-sets into two sub-ensembles: (i) \"absent\"-ones for Σ^hook&lt; Σ^break, which are assumed to hybridize predominantly non-specifically owing to the absence of specific transcripts in the hybridization solution (R = 0); and (ii) \"present\"-ones for Σ^hook&gt; Σ^break, which significantly hybridize specifically owing to the presence of specific transcripts (R &gt; 0).</p>", "<p>The exact position of the break point of a particular hook curve was estimated by a simple algorithm based on the joint least-squared fit of the Δ^hook-data to a linear function for Σ^hook&lt; Σ^break, and a quadratic function for Σ^hook&gt; Σ^break(see Figure ##FIG##4##5##). The algorithm systematically varies the position of the break, Σ^breakfinally returning the optimum value of Σ^breakwhich best fits the data.</p>", "<title>Sensitivity-corrected intensity-data and sensitivity profiles</title>", "<p>The intensity of a probe and thus also its (Δ, Σ)-coordinates depend on the concentration of RNA-transcripts and on the binding constants for specific and non-specific hybridization as well (see Eq. (5)). These constants are functions of the respective probe sequences giving rise to the scattering of the individual probe intensities over one-to-three orders of magnitude [##UREF##6##14##]. This variability is not related to changes of the transcript concentration, and thus it introduces considerable uncertainty if one aims at interpreting the (Σ_set^hook, Δ_set^hook)-coordinates of a probe in terms of its hybridization degree. In the next step we therefore correct the intensities for probe specific effect according to</p>", "<p></p>", "<p>where I^P_0,pdenotes the corrected intensity of probe p. The sequence-specific incremental contribution, <italic>δ</italic>A_p^P(P = PM, MM), the so-called sensitivity of the probe, additively splits into two terms due to specific and non-specific hybridization, <italic>δ</italic>A_p^P,Nand <italic>δ</italic>A_p^P,S, which are weighted by the fraction of non-specifically and specifically hybridized oligomers, and x_p^P,S= (1 - x_p^P,N) with logL_p^P(0) ≈ logI_p^P(0) = &lt;logI_p^P&gt;_p∈N+ <italic>δ</italic>A_p^P,Nand L_p^P= I_p^P/(1-I_p^P/M_c), respectively. The brackets &lt;...&gt;_p∈Ndenote averaging over all probes from the N-range of the hook curve.</p>", "<p>The intensity-correction according to Eq. (22) requires the knowledge of two sensitivity-values for each PM and each MM probe, <italic>δ</italic>A_p^P,Sand <italic>δ</italic>A_p^P,N(P = PM, MM), respectively. They were estimated using either the so-called single-nucleotide (SN, m = 1), the nearest neighbour (NN, m = 2) or the next to nearest neighbour (NNN, m = 3) model. This approach additively decomposes the increments <italic>δ</italic>A_p^P,hinto positional and sequence-dependent sensitivity terms, <italic>δε</italic>_k^P,h(b_m) (m = 1,2,3) referring either to single nucleotides (b₁= B), to adjacent duplets (b₂= BB') or triplets (b₃= BB'B\"; B,B',B\"' = A, T, G, C; see also [##UREF##13##27##]),</p>", "<p></p>", "<p>with <italic>δ</italic>_k(b_m, <italic>ξ</italic>^P_k,m) = 1 for b_m= <italic>ξ</italic>^P_k,mand <italic>δ</italic>_k(b_m, <italic>ξ</italic>^P_k,m) = 0, otherwise. Here <italic>ξ</italic>^P_k,mdenotes a subsequence of m consecutive bases starting at position k of the respective probe sequence. Each set of sensitivity terms consequently comprises 25 × 4 = 100, 24 × 16 = 384 and 23 × 64 = 1472 parameter values for the SN, NN and NNN models, respectively.</p>", "<p>Altogether, the intensity-correction requires four sets of such profiles, <italic>δε</italic>_k^P,h(b_m), referring to P = PM, MM and h = N, S, respectively. We used weighted multiple linear regression of the normalized intensity data taken from selected sub-ensembles of probe sets to estimate the required sensitivity-profiles (see Appendix C and [##UREF##8##18##]). These sub-ensembles were chosen to comprise probes which are predominantly hybridized with non-specific (p ∈ N) or specific (p ∈ S) transcripts for estimating <italic>δε</italic>_k^P,N(b_m) and <italic>δε</italic>_k^P,S(b_m), respectively. Probes of the former sub-ensemble are taken from the initial horizontal part of the hook curve which was assigned to the N-regime meeting the condition Σ_p^hook&lt; Σ^break(see Figure ##FIG##4##5##). The respective absent-probes are assumed to bind predominantly non-specific transcripts.</p>", "<p>The second sub-ensemble of predominantly specifically hybridized probes (p ∈ S) was selected according to the condition Σ_set^hook&gt; Σ^80%where Σ^80%defines a threshold referring to &lt;x^S&gt; &gt; 0.8, i.e. to probe spots with a fraction of specifically-hybridized oligomers of at minimum 80%. According to Eq. (17) the respective probes are selected to meet the \"horizontal distances\"-criterion with respect to the break-point (Σ^80%- Σ^break) &gt; -log(0.2) ≈ 0.7. The somewhat arbitrary choice of &lt;x^S&gt; &gt; 0.8 turned out to be not very crucial with respect to the quality of the obtained correction. On one hand the higher the value of &lt;x^S&gt; the smaller the residual contribution of non-specific hybridization in the selected sub-ensemble and the better the obtained sensitivity profiles characterize specific binding [##REF##16171364##16##]. On the other hand, the number of probe sets in the sub-ensemble decreases with increasing &lt;x^S&gt; giving rise to more noisy sensitivity profiles and thus to less precise correction terms [##REF##16171364##16##]. The chosen value of &lt;x^S&gt; &gt;0.8 provides a good compromise (see Figure ##FIG##4##5##).</p>", "<p>Typical SN- and NN-sensitivity profiles of the PM and MM referring to the N- and S-subsets are shown in Figure ##FIG##5##6##. Note their different shape, especially that of the S-profiles of the MM with the typical \"dent\" in the middle of the sequence. It is caused by the mismatched base pairing in the specific duplexes of the MM which give rise to changed interaction characteristics compared with WC-base pairings. We refer to our previous papers for the detailed discussion of the sensitivity profiles in terms of base-pair interactions in the respective probe-target duplexes [##REF##15834006##15##,##REF##16171364##16##,##UREF##8##18##]. In the present context it is important to discriminate between the four different sensitivity profiles to properly correct the intensity data for sequence specific effects.</p>", "<p>Importantly, for perfect selection of the N-subset one expects the same sensitivity profiles for the PM and MM probes, since the nonspecific background bears no particular relationship to any of both kinds of probes. The profiles shown in Figure ##FIG##5##6## confirm this prediction. The degree of similarity of the N-profiles of the PM and MM probes thus provides a criterion for the proper selection of the N-subsets.</p>", "<title>The corrected hook curve</title>", "<p>In the next step, the corrected intensity values were transformed into (Δ_0,p, Σ_0,p)-coordinates using the corrected intensities in Eq. (9). Subsequently the (Δ_0,p, Σ_0,p)-data were set-averaged and smoothed in the same fashion as described above for the non-corrected intensities to get the sensitivity-corrected version of the hook-curve with the coordinates (Σ₀^hook, Δ₀^hook).</p>", "<p>The sensitivity-correction reduces the scattering of the probe- and probe-set-level intensity data about the smoothed hook-curve (see Figure ##FIG##6##7##). With the N-, mix-, S- and sat-hybridization regimes it essentially shows the same features as the uncorrected hook curve. The break between the N- and mix-regimes was again used to classify the probe sets into absent and present ones. The sensitivity correction affects the (Σ₀^hook, Δ₀^hook)-coordinates of each probe set with possible consequences for its classification into absent and present ones. In a second iteration we therefore re-calculated the four sensitivity profiles on the basis of corrected hook-curve by applying the same criteria for probe selection as above, i.e., Σ₀^hook&lt; Σ₀^breakand Σ₀^hook&gt; Σ₀^80%for the N- and S-profiles, respectively. Typically the re-calculated sensitivity profiles only marginally change compared with the profiles which were obtained on the basis of the uncorrected hook curve indicating the relative robustness of the chosen classification criteria.</p>", "<p>The detailed comparison between both versions of the hook-curve reveals subtle differences especially of the initial N-regime: After correction it changes slope and, more importantly, considerably narrows in horizontal direction by roughly 50% (compare Figure ##FIG##6##7## and Figure ##FIG##4##5##). The steeper slope of the N-region after correction reflects the reduced cross correlation between the corrected PM- and MM-probe level data (see appendix B). Typically, the coefficient of correlation decreases from values <italic>ρ </italic>≈ 0.7–0.9 of the uncorrected data to <italic>ρ </italic>≈ 0.4–0.7 after correction which gives rise to the change of the slope by the factor of 1.5 – 3 (see Eq. (49)).</p>", "<p>The narrowing of the N-range results from the partial removal of sequence effects which, to a large degree, cause the variability of probe signals [##UREF##6##14##]. Ideally, the correction of the intensities for sequence specific effects is expected to shrink the N-region into one point referring to one and the same corrected background intensity for all probes of the chip (see Eqs. (11) and (3)). The residual width of the N-region reflects the deficiency of the method due to at least three, essentially undistinguishable effects: Firstly, the \"fit\"-error of the position-dependent sensitivity model which only incompletely corrects the intensity data for sequence effects caused, e.g. by the specific folding of probe or target and/or bulk dimerization between different targets [##UREF##0##1##]; secondly, the \"N-concentration\" error due the simple assumption to consider all non-specific transcripts as one effective species (Eq. (3)) and thirdly, the \"classification\" error of the simple break-criterion which imperfectly distinguishes between \"present\" and \"absent\" probes due to its limited specificity.</p>", "<title>Fit of the hybridization model</title>", "<p>The corrected hook curve manifests the mean hybridization characteristics of the probes on the particular chip in sensitivity-corrected (Σ₀^hook, Δ₀^hook)-coordinates. It shows essentially the same properties as the Σ-vs-Δ trajectory of a single probe except the N-regime. For quantitative analysis we fit the hybridization model introduced above (Eq. (10)) to the corrected hook data in the mix-, S-, sat- and as-ranges (i.e. at Σ₀^hook&gt; Σ₀^break, see Figure ##FIG##7##8##). The least-squares gradient descent algorithm searches for optimum values of <italic>α</italic>_c, <italic>β</italic>_cand Σ_c(0) ≈ Σ₀^breakand Δ_c(0) ≈ &lt;Σ₀^hook&gt;_p∈N. Note that the break position Σ₀^breakslightly deviates from the centre of the N-range &lt;Σ₀^hook&gt;_p∈Nbecause of the width of the N-regime (see Figure ##FIG##6##7##). We define the total width of the hook curve as .</p>", "<p>Note that the obtained model parameters are now chip-averaged mean values in contrast to the single probe properties used above. We therefore substitute the probe-index \"p\" by the chip-index \"c\". Particularly, one gets the mean PM/MM-ratios of the binding constants for specific and non-specific hybridization</p>", "<p></p>", "<p>respectively, and the mean binding strength for non-specific binding of the particular chip,</p>", "<p></p>", "<p>in analogy with Eqs. (4) and (11) – (12). Here the \"height\" and \"width\" parameters, <italic>α</italic>_cand <italic>β</italic>_c, characterize the vertical and horizontal dimensions of the corrected hook curve of chip \"c\" (see Figure ##FIG##6##7## and Figure ##FIG##7##8##) which in turn are related to the mean binding characteristics averaged over all probes of the chip, i.e., (P = PM, MM, h = N, S). The sensitivity-corrected S/N-ratio</p>", "<p></p>", "<p>scales the concentration ratio of specific and non-specific transcripts with the respective ratio of chip-averaged mean binding constants of the PM for specific and non-specific binding. Note that this scaling is common for all probes of the chip in contrast to the probe-specific scaling of R_p^PMin Eq. (6).</p>", "<p>In summary, the hook-curve analysis of the intensity data thus provides chip characteristics such as the mean contribution of the non-specific background, the asymptotic intensity maximum and the mean PM/MM-sensitivity gain, and, in addition, the expression degree on probe-set basis in terms of the S/N-ratio.</p>", "<title>Signal distributions</title>", "<p>Part a of Figure ##FIG##8##9## shows the probability-density distribution to find a probe pair a at a given position of the hook-abscissa, p(Σ₀^hook) = ΔN/(N_tot·ΔΣ^hook·) (here ΔN/N_totis the fraction of probe-pairs found per abscissa interval ΔΣ^hook). About 40% of the probes fall in the N-range in this example and thus are classified \"absent\". We separately plot the density distribution of these absent probes as a function of their corrected log-intensities (part b of Figure ##FIG##8##9##). The obtained PM- and MM-probe-level data are well described by normal distributions (P_p^N(x, <italic>σ</italic>_c) = N(<italic>μ</italic>_c, <italic>σ</italic>_c) with ) of with virtually the same width (<italic>σ</italic>^PM≈ <italic>σ</italic>^MM) and slightly shifted centres, .</p>", "<p>One obtains the coordinates of the centre of the N-region of the hook-curve (see also Eq. (11)),</p>", "<p></p>", "<p>The total distribution decays exponentially to a good approximation at Σ₀^hook&gt; Σ_c(0) in many cases (part a of Figure ##FIG##8##9##). Define the parameter , related to the S/N ratio R.</p>", "<p>The exponential behaviour is approximately preserved with respect to this parameter in the mixed and S ranges since from Eq. (18) (see part c of Figure ##FIG##8##9##). Note that r directly relates to the binding strength of specific hybridization in the relevant range of intermediate and large R-values, r ~ logR ~ log(X_set^PM,S). The initial value of the distribution at r = R = 0 provides the fraction of virtually absent probes, f^absent, whereas the area under the normalized distribution for r &gt; 0 consequently gives the fraction of present probes, f^present= (1 - f^absent).</p>", "<p>The distribution can be empirically approximated by an exponential decay function for r-values greater than a certain threshold r' (and R' &gt; R)</p>", "<p></p>", "<p>In the intermediate range the signal is approximated by a constant with f₂^present= 1 - (f^absent+ f₁^present) (f^present= f₁^present+ f₂^present) whereas for r = 0 one gets the fraction of absent probes. The decay constant <italic>λ</italic>_rdefines the r-range which decreases the probability of the specific signal by one order of magnitude. It thus defines a characteristic S/N-ratio (in logarithmic scale) of the chip which characterizes log-ratio of the mean specific and non-specific signals, or in other words, to which extend the specific signal exceeds the non-specific one. The S(pecific)/N(onspecific)-ratio thus can be also interpreted as a sort of S(ignal)/N(oise)-ratio of a given probe set. The value of the r-related decay constant <italic>λ</italic>_rslightly exceeds that of the hook-related distribution owing to the larger range covered by the PMonly S/N-ratio (<italic>λ</italic>_r= 1.0 versus <italic>λ </italic>= <italic>λ</italic>_Σ= 0.75; compare part c and a of Figure ##FIG##8##9##).</p>", "<p>An estimate of the mean decay constant can be obtained by simple averaging over the respective R-range</p>", "<p></p>", "<p>Note that the exponential decay in Eq. (28) is equivalent with the power law, 10^{-r/<italic>λ</italic>r}= (R+1)^{-1/<italic>λ</italic>r}, which has been shown to describe the probability distribution of expression values in a series of microarray experiments [##REF##12016055##28##, ####REF##12582260##29##, ##REF##16472022##30##, ##REF##15727680##31####15727680##31##]. This power-law function is known as the Zipf's law, observed in many natural and social phenomena. The presence of such power-law function in principle prevents an intrinsic cut off point between \"on\" genes and \"off\" genes. The analysis of expression data in terms of their probability distribution therefore is of basic importance for judging the expression level in terms of global characteristics. The hook-transformation provides such characteristics in terms of the signal distribution along the Σ^hookand/or r coordinates for the mix-, S- and sat-hybridization ranges.</p>", "<p>Let us now consider the S/N-ratio of a particular probe at two conditions: (i) with x = 0, referring to the non-specific binding strength in the centre of the normal background distribution, X_p^PM,N≈ 10^{<italic>μ</italic>}/M_c:; and (ii) with x ≠ 0, i.e. X_p^PM,N(x) ≈ 10^{<italic>μ</italic>+x}/M_cand .</p>", "<p>After transformation into logarithmic scale and combination of both situations we get log <italic>R</italic>(<italic>x</italic>) = log <italic>R</italic>_{<italic>p </italic>}- <italic>x </italic>and for R &gt; 1 to a good approximation <italic>r</italic>(<italic>x</italic>) ≈ <italic>r </italic>- <italic>x</italic>.</p>", "<p>Now we combine the virtually independent background and signal distributions into the joint probability density function</p>", "<p></p>", "<p>It refers to the logarithmic signal value r with the particular non-specific background contribution <italic>μ </italic>+ x. Integration over the whole possible backgound range provides the probability for detecting the signal r for probe p,</p>", "<p></p>", "<p>Note that the upper integration range is effectively restricted to x ≤ r because of p^S(r-x,<italic>λ</italic>) = 0 for x &gt; r (see Eq. (28)). Eqs. (30)–(31) define the convolution product of the background and specific-signal distributions. A similar approach was used in ref. [##REF##16472022##30##] and partly also in the RMA-algorithm [##REF##12582260##29##].</p>", "<title>De-saturation of the signal and convolution based expression estimates</title>", "<p>The hyperbolic intensity-response (Eq. (1)) can be linearized and transformed into the total binding strength using the asymptotic value M_c:</p>", "<p></p>", "<p>Figure ##FIG##9##10## re-plots the hook curve shown in Figure ##FIG##7##8## after linearization of the corrected intensities using Eq. (32). The sat-range now levels off into the asymptotic value <italic>α</italic>_c(compare with Figure ##FIG##7##8##). This \"de-saturated\" signal additively decomposes into contributions due to non-specific and specific hybridization (Eq. (2)). We now calculate the expression value as the weighted \"glog\"-mean of the specific signal,</p>", "<p></p>", "<p>Particularly, Eq. (33) corrects the linearized signal (Eq. (32)) for the probe-specific background contribution using the mean background of the chip and the probe-specific sensitivity for non-specific hybridization, (Eq. (23)). The use of the generalized logarithm, , for data transformation is advantageous in two respects: Firstly, it enables processing negative arguments which may appear due to data scattering and, secondly, it \"stabilizes\" the variance at small values of x provided that the transformation parameter c &gt; 0 is properly chosen [##REF##12169537##32##,##REF##12169536##33##].</p>", "<p>In Eq. (33) the glog-transformed data are averaged over the probability distribution representing the convolution product of the mutually independent probabilities of the non-specific Gaussian background and the specific expression signal (see previous section and [##REF##16472022##30##]). This approach assumes that the probability distribution of each individual transcript is the same as the mean distribution averaged over all transcripts. Alternatively one can use the un-weighted kernel with p^S= const. In this case Eq. (33) restricts the averaging to the background distribution.</p>", "<p>In the next step, the obtained values are corrected for the sequence effects according to using the positional-dependent sensitivity model and the Z_p^Pvalues instead of the log-intensities for parameterization (Eq. (50)). Then, the probe-level data are summarized for each probe set by calculating the Tukey-biweight median, [##UREF##11##25##], and finally by transforming them into linear scale to get the probe set-level expression degree, . Eq. (33) thus provides \"PMonly\" and \"MMonly\" estimates of the expression degree with P = PM and MM, respectively.</p>", "<p>Considering the fact that the MM intensity comprises information about the non-specific background one can correct the linearized intensity and background of the PM by subtracting that of the respective MM:</p>", "<p></p>", "<p>with and </p>", "<p>Eq. (34) uses the background distribution of the PM and the conditional expectation of the bivariate normal distribution for the argument of the MM-background which gives rise to an effectively shrunken integration variable, (here <italic>ρ</italic>_cis the coefficient of correlation, see appendix B). Note that this approach is to some degree similar to the GC-RMA algorithm [##UREF##14##34##] which however uses pseudo-MM representing subsets of PM-probes of the same GC-content as the considered PM. A second difference to Eq. (34) is that GC-RMA directly subtracts the (non-linear) MM-intensity without explicit consideration of the non-specific background.</p>", "<p>In this context we stress the fact that the non-specific background intensity is rather a variable contribution which progressively decreases with increasing amount of specific binding than a constant (see appendix A and the figure shown there). The background correction of the intensity (as realized, e.g. by GC-RMA) neglects this trend and therefore it is expected to over-correct the signal in the S- and as-hybridization ranges. As a consequence, this approach underestimates the expression degree due to two reasons: Firstly, this over-correction of the background and, secondly, the neglect of saturation. On the other hand, the linearized signal used here (Eq. (32)) corrects the intensity for saturation and, in addition, it contains a constant background level corrected by simple subtraction in Eqs. (33) and (34).</p>", "<p>The joint PM-MM- and especially the MMonly-expression measures are smaller than the PMonly estimates because of the smaller binding constants of the MM for specific binding. The former two measures can be scaled to values equivalent to the expression level of the PM according to (see also Eq. (24)),</p>", "<p></p>", "<p>and finally transformed into the \"set-averaged\" binding strength in analogy with Eq. (32)</p>", "<p></p>", "<p>Note that the PM-estimate exceeds the MM signal roughly by the factor s_c≈ 5 – 10 at comparable variance of the residual background distribution (see Figure ##FIG##8##9##, part b). For the coefficient of variation, CV ≈ <italic>σ</italic>/S, one gets roughly CV(PM) ≈ CV(PM-MM) &lt;&lt; CV(MM). The MM consequently are expected to provide considerably less accurate expression estimates compared with the respective PMonly and PM-MM values.</p>", "<p>Note that also the S/N-ratio (Eq. (26)) transforms into an alternative estimate of the specific binding strength of the PM (see Eq. (25) and (26)) with</p>", "<p></p>", "<p>Finally, the decay constant of the distribution of the specific signal relates to the logarithm of the S/N-ratio (see Eqs. (28) and (29)). One obtains the mean specific signal measured by the given chip as</p>", "<p></p>", "<p>The characteristic expression index (or exponent of specific binding) <italic>φ</italic>_ccomplements the respective exponents for non-specific hybridization <italic>β</italic>_cand the characteristic S/N-index <italic>λ</italic>_ras the basic chip summary-characteristics of specific and non-specific binding.</p>", "<title>Chip characteristics and expression estimates in natural units</title>", "<p>Eqs. (36) and (37) provide probe set-estimates of the specific binding strength as a measure of the expression degree,</p>", "<p></p>", "<p>which represents a dimensionless concentration measure in units of the mean specific binding constant of the chip. A value of S_set= 1 consequently defines the condition of half-coverage to a good approximation (see Eq. (7)). Analogously, the horizontal dimensions of the hook-curve provide the non-specific binding strength as a measure of the non-specific background in units of the respective binding constant (see Eq. (25)),</p>", "<p></p>", "<p>It specifies the mean occupancy of the probes in the absence of specific transcripts, Θ^PM(0) ≈ X_c^PM,N.</p>", "<p>Hence, the hook method measures both, the abundance of specific and non-specific transcripts in the hybridization solution in chip-related units such as the relative occupancy of the probe spots and the respective binding strengths.</p>", "<p>The specific and non-specific signals are combined into the S/N-ratio, R (Eq. (26)), which provides the expression degree in units of the non-specific background contribution in the particular chip experiment. The S/N-ratio is directly related to the hook-coordinates of a selected probe set and thus it can be roughly deduced by visual inspection of the particular hook curve (Eqs. (46) and (18)). Figure ##FIG##7##8## illustrates the relation between the intrinsic expression measures and the hook coordinates for a typical microarray hybridization. The point of half coverage (Θ^PM= 0.5, X^{PM, S}≈ 1) is found beyond the maximum in the sat-regime. Virtually no probe of the chosen chip meets this condition. Note that Θ^PMscales with the distance relative to the end point referring to R → ∞ (see above). Vice versa, the mean fraction of specifically hybridized oligomers, x^{PM, S}, scales with the distance relative to the N-point. It steeply increases in the mix-regime and reaches the conditions at which 50% of the bound transcripts belong to the specific ones, x^{PM, S}= 0.5, at relatively small abscissa-values. Hence, specific hybridization starts to dominate over non-specific one always at the beginning of the mix-range. The S-range near the maximum of the hook-curve refers to probes with a 50 – 100 fold excess of specific hybridization, R^PM≈ 50 – 100. The width of the hook of about <italic>β </italic>= 2.7 is equivalent with the background strength of N_c≈ 10^-2.7= 0.002 which in turn rescales the S/N-ratio into binding strengths, for example S_c= 0.1–0.2 for R = 50–100. These rough estimation shows that the maximum of the hook is equivalent with the occupancy of the PM-spots in the order of 10 – 25%.</p>", "<p>The mean binding constants, K_c^PM,Sand K_c^PM,Nand thus also the used measures of specific and non-specific hybridization depend on the particular probe and chip design (e.g., the length of the probe-oligonucleotides, their density and the type of the mismatches used for the MM probes). Consequently they are specific for the used chip type, on one hand. On the other hand, also the conditions of a particular hybridization affect the K_c^PM,hbecause their values depend on all processes affecting the binding reaction between the probe-oligonucleotides and the targets. For example, the composition of a particular sample will affect K_c^PM,Nand K_c^PM,Sas well, because both constants depend on the extent of target-dimerization which is a function of the concentrations of the reacting species in the hybridization solution [##UREF##0##1##].</p>", "<title>5. Appendix</title>", "<title>A. Concentration scales of the Δ-vs-Σ-trajectory: Derivation of Eqs. (16) – (18)</title>", "<p>The relative Σ- and Δ-coordinates of the log-transformed probe intensities with respect to its asymptotic value at R = ∞ directly rescale into the respective log-sum and -difference of the surface coverage of the PM and MM probes (see Eqs. (1) and (9))</p>", "<p></p>", "<p>One obtains Eq. (16) for the mean coverage of the PM and MM with Eq. (41) and the definition, ⟨Θ⟩ ≡ 10^ΣlogΘ. Rearrangement provides the surface coverage of the PM and MM probes as a function of the relative Σ- and Δ-coordinates,</p>", "<p></p>", "<p>The surface coverage splits into contributions due to non-specific and specific transcripts, Θ^{<italic>P </italic>}= Θ^{<italic>P,N </italic>}+ Θ^{<italic>P,S</italic>}, with (see Eq. (2)). Both contributions are functions of the composition of the hybridization solution expressed in terms of the S/N-ratio R (see Eq. (5)),</p>", "<p></p>", "<p>Eq. (43) shows that the specific coverage monotonously increases with the S/N-ratio whereas the non-specific \"background\" coverage remains virtually constant at R &lt; 1/X^{PM, N}for the PM (and at R &lt; (n/(s·X^{PM, N}) for the MM, see Figure ##FIG##11##12##). Specific transcripts of large binding strength progressively replace the bound non-specific fragments with further increasing values of R. As a consequence the non-specific coverage Θ^{P, N}drops and finally disappears for R → ∞.</p>", "<p>With Eq. (43) one can express the specific and non-specific coverage as follows</p>", "<p></p>", "<p>The ratio of the \"specific\" and the total coverage defines the fraction of specifically hybridized probe-oligomers, (see also Eqs. (43) and (44)). With Eqs. (44) and (42) one obtains,</p>", "<p></p>", "<p>and Eq. (17) for the mean fraction, &lt;x^S&gt;. Here we make use of and (see Eqs. (42) and (14)).</p>", "<p>Finally, with and Eq. (45) one obtains for P = PM, MM</p>", "<p></p>", "<p>and Eq. (18) for the respective average .</p>", "<title>B. The slope of the hook-curve in the mix- and the N-ranges</title>", "<p>The initial part of the hook curve roughly divides into two segments of different slope. We assume that the probes from probe-sets with abscissa positions to the left from the break, Σ^hook&lt; Σ^break, are predominantly hybridized with non-specific transcripts (N-range) whereas the probes from probe-sets with abscissa positions to the right from the break, Σ^break&lt; Σ^hook, in addition, bind a certain amount of specific transcripts (mix-range). The slope of the hook curve in this mix-range reflects the change of the hook coordinates with increasing concentration of specific transcripts. From Eq. (10) one gets after differentiation with respect to the S/N-ratio R in the limit of R → 0,</p>", "<p></p>", "<p>The initial slope of the mix range essentially depends on the \"height\"-parameter <italic>α</italic>_cand thus on the PM/MM-ratio of the specific binding constants (see Eqs. (13) and (4)).</p>", "<p>The slope of the hook-curve in the N-range can be rationalized in terms of cross-correlations between the non-specific background signals of the PM and MM probes referring to \"absent\" specific transcripts, i.e. R = 0. The variances of the hook-coordinates are given by</p>", "<p></p>", "<p>Here <italic>σ</italic>_PM², <italic>σ</italic>_MM²and <italic>σ</italic>_PM,MMdenote the variance and covariance of the set-averaged log-intensities of the PM and MM probes in the N-range. The formula for the correlation coefficient <italic>ρ </italic>assumes to a good approximation (see Figure ##FIG##8##9##).</p>", "<p>With Eq. (48) one obtains for the mean slope of the hook-curve in the N-range</p>", "<p></p>", "<p>Hence, a tiny slope near zero indicates strongly correlated PM and MM signals (<italic>ρ</italic>~1) whereas the increase of slope(N) reflects \"decoupling\" of PM and MM intensities.</p>", "<title>C. Fit of the position-dependent sensitivity profiles</title>", "<p>The sensitivity terms <italic>δε</italic>_k^P,h(b_m) in Eq. (23) were estimated using the so-called probe sensitivity [##UREF##6##14##],</p>", "<p></p>", "<p>which normalizes the log-intensities with respect to their log-mean over the probe set. Here the probe set was selected from the specific or non-specific sub-ensembles (h = N or S). P = PM, MM specifies the probe type. Insertion of Eq. (22) into (50) provides</p>", "<p></p>", "<p>Here f_k(b_m) is the probability to find the subsequence b_mat sequence position k within the probes of a probe set. The weighted least squares algorithm fits Y(theory) to Y(exp) by optimizing the coefficients <italic>δε</italic>_k^P,h(b_m) using single value decomposition [##UREF##15##35##].</p>", "<p>The NN model provides 16 profiles <italic>δε</italic>_k^P,h(BB') (k = 1...24) and the NNN model 64 profiles <italic>δε</italic>_k^P,h(BB'B\") (k = 1...23) per sub-ensemble (N or S) and probe type (PM or MM). To extract the basic trends for a qualitative discussion we reduce the number of data simply by transforming the NN- and NNN-profiles into single-base (SN)-profiles by appropriate averaging</p>", "<p></p>", "<title>D. Fit of the Langmuir model to the Δ-vs-Σ data</title>", "<p>Rearrangement of the parametric equation for the abscissa of the hook-data (Eq. (10)) provides a quadratic equation for the S/N-ratio with the non-negative solution</p>", "<p></p>", "<p>Equation (53) thus returns the S/N-ratio R for the Σ₀^hook-coordinate of a probe set and a given set of model-parameters {<italic>α</italic>_c, <italic>β</italic>_c, Σ_c(0), Δ_c(0)}. The parametric equation for the hook-ordinate (Eq. (10)) then provides an estimate of Δ₀(R) referring to the respective probe set. The fit-algorithm minimizes the sum of least squares between the calculated and measured Δ-values, , by adjusting the parameters <italic>α</italic>_c, <italic>β</italic>_cand Σ_c(0) using an iterative gradient method with linearly decreasing step size. The ordinate value of the start-point was set to the break between the N- and mix-range, (see above).</p>", "<p>We divide the Σ₀^hook-axis into i = 10 – 30 equally-spaced sampling points Σ₀^hook= Σ_iby averaging over the probe/probe set data within the respective sampling interval of width <italic>δ</italic>Σ, i.e., for all probes with which were used in Eq. (53) to calculate the respective S/N-ratios R_iand theoretical ordinate points Δ_i,0(R_i) using Eq. (10). The weighting factor, , considers the data-density, <italic>ρ</italic>(Σ_i), and variance, <italic>σ</italic>_Δ(Σ_i)², per interval. Both, <italic>ρ</italic>(Σ_i) and <italic>σ</italic>_Δ(Σ_i)², are given by decaying functions ([##REF##16472022##30##,##REF##12169537##32##]) which partly compensate each other to a good approximation. By default the weighting factor is therefore set to w_i= 1.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>Both authors invented the method. HB leads the project and wrote the paper. SP wrote the computer program for data analysis and helped to draft the paper. Both authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>HB thanks Conrad Burden from Australian National University in Canberra for useful discussions and advice. The work was supported by the Deutsche Forschungsgemeinschaft under grant no. BIZ 6/4. SP thanks the International Max Planck Research School for Molecular Cell Biology and Bioengineering (IMPRS-MCBB) Dresden for funding.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>PM- and MM-probe intensities (part a), their log-difference (part b) and -sum (part c) as a function of the specific target concentration (S/N-ratio). The curves are calculated using the Langmuir-model (Eq. (1)). The difference-plot reveals the hybridization regimes of non-specific (N), mixed (mix) and specific (S) hybridization, of saturation (sat) and the asymptotic (as) range. The parameters <italic>α </italic>and <italic>β </italic>used in Eq. (10) specify the data range spanned by the log-difference and -sum.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Δ-vs-Σ plot of the PM- and MM-isotherms shown in Figure 1 (part a, see Eq. (9)). The parameters <italic>α </italic>and <italic>β </italic>now specify the height and width of the Δ-vs-Σ trajectory of the PM/MM-probe pair. Part b shows the fraction of specific transcripts bound to PM- and MM-probes (x_S^P, P = PM, MM; and their log-mean, &lt;...&gt;) and the total fraction of occupied probe-oligomers (Θ^P, and of their mean). Note that the fraction of specific transcripts steeply increases in the mix-range whereas the occupancy mainly increases in the sat-range (see Eqs. (17) and (16), respectively).</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Part a: Δ-vs-Σ trajectories upon decreasing contribution of the non-specific background. The width of the curve, <italic>β</italic>, defines the logarithm of the binding strength of non-specific hybridization in the absence of specific transcripts (Eq. <bold>(12)</bold>). Part b shows two trajectories of different height. The PM/MM-gain parameter s defines the height in the absence of saturation. The narrowing of the trajectories decreases the maximum (see Eq. <bold>(13)</bold>).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Upper panel: Δ-vs-Σ trajectories of six selected probe-pairs taken from the HG-U133 spiked-in experiment (Affymetrx). The sequences of the PM-probes are shown in the insertion below. The probe-pairs are numbered with increasing C and decreasing A content of the respective PM-probe (see of insertion on the right). The symbols are the experimental data. The lines are calculated using Eq. <bold>(10)</bold>. Lower panel: Variability of the Δ-vs-Σ trajectories of all 498 spiked-in probes. The boxplot indicates the scattering of the start- and maximum-coordinates for R = 0 and R = R_max, respectively. The Δ-vs-Σ trajectories are averaged over all probe-pairs with the middle base A, T, G and C of the PM, respectively. The variability due to the middle base refers to the 75%/25% quantiles of the distribution of the individual probe trajectories. The consideration of the nearest neighbours in terms of the middle triple extends this range: only the trajectories with the largest and smallest maximum value (for middle triples CCC and CGC, respectively) are shown (see also ref. [##UREF##8##18##]).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p>Upper panel: Δ-vs-&lt;Σ&gt;_setplot of the intensity data of one complete chip taken from the HG-U133 spiked-in experiment (Affymetrix): Probe intensity data (black dots), probe-set log-averaged data (light dots) and moving average over ~100 probe-sets (line). The latter plot is enlarged in the lower panel: It is called (raw) hook curve because of its characteristic shape. The N-, mix-, S- and sat-hybridization regimes are indicated (compare with Figure 2). The breakpoint is used to classify the probesets into absent and present ones (see text).</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p>Positional dependent sensitivity profiles: The upper panel shows the single-nucleotide (SN) profiles for the PM and MM for non-specific and specific hybridization. The profiles are calculated using the intensity data shown in Figure 5 (Eq. <bold>(23)</bold>). The lower panel shows the NN-profiles of the PM for non-specific hybridization and the respective SN-profiles (lines) which are re-plotted from the upper panel (open symbols). Typically the values increase according to BA BT BG BC (with B = A, T, G, C; see arrows in the figure).</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p>The same as Figure 5 but for sensitivity-corrected intensity data (Eq.(22)). The upper panel shows the Δ-vs-&lt;Σ &gt;_setplot of the sensitivity-corrected intensity data of one chip taken from the HG-U133 spiked-in experiment (Affymetrix) The lower panel shows the (corrected) hook-curve.</p></caption></fig>", "<fig position=\"float\" id=\"F8\"><label>Figure 8</label><caption><p>Fit of the Langmuir-model (Eq. <bold>(10)</bold>) to the mix-, S- and sat-ranges of the corrected hook curve (see Figure 7). The lower panel illustrates the relation between the coordinate axes and intrinsic probe characteristics: The respective fraction of specifically hybridized PM-probes (Eq. <bold>(45)</bold>), their S/N-ratio (Eq. <bold>(46)</bold>) and occupancy (Eq. <bold>(43)</bold>). The arrows indicate the 50%-conditions at which the PM-probes on the average become equally hybridized with specific and non-specific transcripts (x^{PM, S}= 0.5) and at which 50% of the oligomers of the PM-probe spots become occupied (Θ^PM= 0.5). The third arrow points to the probes with a 100fold excess of specific hybridization.</p></caption></fig>", "<fig position=\"float\" id=\"F9\"><label>Figure 9</label><caption><p>Probe-density distribution of the hook-curve (part a), the log-intensity distributions of the PM- and MM-probes taken from the N-range of the hook (part b) and the distribution of the S/N-ratio showing the specific signal distribution for log(R+1) &gt; 0 (part c). About 40% of the probe pairs are absent according to the break-criterion. The distributions of their corrected intensities (bars) are well approximated by Gaussian functions (lines) with slightly shifted centres <italic>μ </italic>and nearly equal widths, <italic>σ </italic>(part b). Part c rescales the total distribution by using the argument r = log(R+1). The fraction of absent probes refers to intersection with the ordinate at r = 0 (40%). 60% of the probes are consequently called present with specific signals r &gt; 0. Their distribution follows an exponential decay for values r ≥ r' = 0.5 with the decay constant <italic>λ</italic>_r. In the intermediate range r' &lt; r &lt; 0 the signal is approximated by a constant (see Eq. <bold>(28)</bold>). The rescaling from Σ₀^hookto log(R+1) slightly increases the decay constant (compare part b and a).</p></caption></fig>", "<fig position=\"float\" id=\"F10\"><label>Figure 10</label><caption><p>„Desaturated” hook-curve: The corrected intensities (see <bold>Figure 7</bold>) are linearized using Eq. <bold>(32)</bold>, transformed into Δ and Σ coordinates (Eq. <bold>(9)</bold>) and smoothed. After \"linearization\" the sat-range of the hook levels off into the asymptote of height <italic>α </italic>(Eq. <bold>(24)</bold>) which defines the PM/MM-gain upon duplexing (compare with <bold>Figure 8</bold>). The fit neglects the saturation terms in Eq. <bold>(10)</bold>.</p></caption></fig>", "<fig position=\"float\" id=\"F11\"><label>Figure 11</label><caption><p>Schematic summary of the hook-method: The raw intensity data of one GeneChip microarray are plotted into the Δ = log(PM/MM)-vs-Σ = 1/2·log(PM·MM) coordinate system and smoothed to get the raw hook-curve. Then, probes from the N- and S-hybridization regimes are used to calculate four sets of position-dependent sensitivity profiles of the affinity model (non-specific and specific for the PM and MM each) which in turn are used to correct the intensities for sequence effects. The corrected intensities provide the corrected hook-curve. The mix-, S- and sat-ranges are fitted using the two-species Langmuir hybridization model. The dimensions of the hook, its width and height, provide hybridization characteristics of the chip which in turn are used to calculate probe-level expression measures.</p></caption></fig>", "<fig position=\"float\" id=\"F12\"><label>Figure 12</label><caption><p>Δ-vs-Σ trajectory (part a), the S/N ratios of the PM, MM and of their mean (Eqs. <bold>(46) </bold>and <bold>(18)</bold>, part b) and the fraction of occupied PM and MM probes (occupancy, Eq. <bold>(42)</bold>, part c). The total occupancy additively decomposes into the occupancy due to specific and non-specific hybridization (thin lines, see Eq. <bold>(43)</bold>). Note that the latter occupancy is not a constant but it depletes upon increasing total occupancy because specific binding progressively replaces non-specific one.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Notations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Superscripts</bold></td><td align=\"left\">Assigns main symbols to...</td></tr><tr><td align=\"left\">P = PM, MM</td><td align=\"left\">Probe type</td></tr><tr><td align=\"left\">h = N, S</td><td align=\"left\">Non-specific or specific hybridization</td></tr></thead><tbody><tr><td align=\"left\"><bold>Subscripts</bold></td><td align=\"left\">Assigns main symbols to...</td></tr><tr><td align=\"left\">p, c, set</td><td align=\"left\">Probe-, chip- or probe-set-level</td></tr><tr><td align=\"left\">0</td><td align=\"left\">Values after sequence correction</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Main symbols</bold></td><td/></tr><tr><td align=\"left\">, M_c, O_c</td><td align=\"left\">Probe intensity, maximum intensity upon saturation and optical background</td></tr><tr><td align=\"left\">, </td><td align=\"left\">Linearized (de-saturated) intensities</td></tr><tr><td align=\"left\">S_set, N_c</td><td align=\"left\">Specific and non-specific signals</td></tr><tr><td align=\"left\">, , </td><td align=\"left\">Probe occupancy: total and due to specific and non-specific hybridization</td></tr><tr><td align=\"left\">x_p^P,S, x_p^P,N</td><td align=\"left\">Fraction of specific and of non-specific transcripts among the total amount of bound transcripts</td></tr><tr><td align=\"left\">, , </td><td align=\"left\">Binding strength: total and due to specific and non-specific hybridization</td></tr><tr><td align=\"left\">[S]_p, [N]_c</td><td align=\"left\">Concentration of specific and non-specific transcript</td></tr><tr><td align=\"left\">, </td><td align=\"left\">Binding constants of a probe for specific and non-specific transcripts</td></tr><tr><td align=\"left\">s, n</td><td align=\"left\">PM/MM-sensitivity gain for specific and non-specific binding</td></tr><tr><td align=\"left\">R</td><td align=\"left\">S/N-ratio</td></tr><tr><td align=\"left\">Δ, Σ</td><td align=\"left\">Hook coordinates</td></tr><tr><td align=\"left\">Δ_start, Σ_start</td><td align=\"left\">Starting values of the hook coordinates</td></tr><tr><td align=\"left\">Δ(0), Σ(0)</td><td/></tr><tr><td align=\"left\">Δ(∞), Σ(∞)</td><td align=\"left\">End values of the hook coordinates</td></tr><tr><td align=\"left\"><italic>α</italic>, <italic>β</italic></td><td align=\"left\">Vertical and horizontal dimensions of the hook curve</td></tr><tr><td align=\"left\"><italic>DS</italic>_{<italic>p</italic>}</td><td align=\"left\">Discrimination score</td></tr><tr><td align=\"left\">(B_p)</td><td align=\"left\">Contribution of middle base B to the signal</td></tr><tr><td align=\"left\">(b_m)</td><td align=\"left\">Positional dependent sensitivity propfile; k is the start position of sequence motiv b_mwhich consists of m adjacent nucleotides</td></tr><tr><td align=\"left\"></td><td align=\"left\">Sequence specific contribution to the intensity</td></tr><tr><td align=\"left\"></td><td align=\"left\">Sensitivity</td></tr><tr><td align=\"left\">, </td><td align=\"left\">Density distributions of the non-specific and specific signals</td></tr><tr><td align=\"left\"><italic>μ</italic>^{<italic>P</italic>}, <italic>σ</italic>^{<italic>P</italic>}, <italic>ρ</italic></td><td align=\"left\">Mean value, standard deviation and coefficient of PM/MM-correlation of the normal distributions of the non-specific background signals</td></tr><tr><td align=\"left\"><italic>λ</italic>, <italic>λ</italic>_Σ</td><td align=\"left\">decay lengths of the exponential distribution (referring to the S/N-ratio and to the Σ-signal)</td></tr><tr><td align=\"left\"><italic>φ</italic>_{<italic>c</italic>}</td><td align=\"left\">Mean specific signal</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Operation</bold></td><td/></tr><tr><td align=\"left\">g log(x)</td><td align=\"left\">Generalized logarithm</td></tr><tr><td align=\"left\">&lt;...&gt;</td><td align=\"left\">Arithmetic mean</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Hook method: algorithm and output characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Step</bold></td><td align=\"left\"><bold>Output (chip and probe-set characteristics)</bold></td><td align=\"left\"><bold>Eq.</bold></td></tr></thead><tbody><tr><td align=\"left\">1) optical background correction using the Affymetrix zone-algorithm (see Ref. [##UREF##12##26##]).</td><td align=\"left\">Optical background (O, mean over all zones);<break/>the algorithm uses a scaled value with a scaling factor chosen between 0 and 1</td><td align=\"left\">(1)</td></tr><tr><td align=\"left\">2) Raw hook: Plot of the PM and MM probe intensity data into Δ-vs-Σ coordinates and smoothing over a sliding-window of ~100 probe sets. Classification into N- and S-probes using the breakpoint of the hook.</td><td align=\"left\">Raw hook curve</td><td align=\"left\">(9)</td></tr><tr><td align=\"left\">3) Parameterization of the positional dependent sensitivity-model separately for the PM and MM in the N and S-ranges and correction of the intensities for probe-specific sensitivities.</td><td align=\"left\">Sensitivity profiles (optional SN, NN or NNN models)</td><td align=\"left\">(22), (23); App. C</td></tr><tr><td align=\"left\">4) Corrected hook: re-iterate steps (2)–(3) with the corrected intensities to improve the sensitivity correction and the classification of the probes into absent and present ones</td><td align=\"left\">Corrected hook-curve<break/>Fraction of absent probes (%N), mean N-background level and width of the N-range</td><td align=\"left\">(27)</td></tr><tr><td align=\"left\">5) Fit of the hook-equation to the mix-, S-and sat-ranges of the corrected hook curve and analysis of the probe-level hook coordinates</td><td align=\"left\">Maximum intensity (M_c), mean non-specific background level (N_c^PM), dimensions of the hook (<italic>α</italic>_c, <italic>β</italic>_c), PM/MM-affinity gain (s_cand n_c), parameters of the normal background distribution (<italic>μ</italic>_c, <italic>σ</italic>_c, <italic>ρ</italic>_c) and of the signal distribution (<italic>λ</italic>), S/N-ratio (R), and occupancy (Θ) and fraction of specific binding (x^S)</td><td align=\"left\">(10), (12), (24) – (26), (29); App. D, App. A</td></tr><tr><td align=\"left\">6) Calculation of probe-set related expression estimates (alternatively PMonly or PM-MM) by the joint processing of the intensity data and selected chip characteristics which corrects for the non-specific background, sequence-specific sensitivity and saturation</td><td align=\"left\">Expression measures (L_set, S_set)</td><td align=\"left\">(33) – (36)</td></tr></tbody></table></table-wrap>" ]

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overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>≡</mml:mo><mml:msubsup><mml:mtext>R</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>S</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>N</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM7\"><label>(7)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M25\" name=\"1748-7188-3-12-i25\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>S</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mtext>p</mml:mtext><mml:mrow><mml:mn>50</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msup><mml:mtext>R</mml:mtext><mml:mrow><mml:mn>50</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM8\"><label>(8)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M26\" name=\"1748-7188-3-12-i26\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>S</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mtext>p</mml:mtext><mml:mrow><mml:mn>50</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo>⋅</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mo>;</mml:mo></mml:mtd><mml:mtd><mml:mrow><mml:msup><mml:mtext>R</mml:mtext><mml:mrow><mml:mn>50</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM9\"><label>(9)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M27\" name=\"1748-7188-3-12-i27\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>≡</mml:mo><mml:mi>Δ</mml:mi><mml:mi>log</mml:mi><mml:msub><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:mi>log</mml:mi><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>≡</mml:mo><mml:mi>Σ</mml:mi><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:mi>log</mml:mi><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM10\"><label>(10)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M28\" name=\"1748-7188-3-12-i28\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>Linear</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:mi>log</mml:mi><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mfrac></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo 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stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M29\" name=\"1748-7188-3-12-i29\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msubsup><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>M</mml:mtext><mml:mtext>c</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M30\" name=\"1748-7188-3-12-i30\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>Linear</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo>+</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo>⋅</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfrac></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msubsup><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>Linear</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>⋅</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>⋅</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M31\" name=\"1748-7188-3-12-i31\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msubsup><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>R</mml:mi><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM11\"><label>(11)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M32\" name=\"1748-7188-3-12-i32\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msubsup><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msub><mml:mtext>o</mml:mtext><mml:mi>Δ</mml:mi></mml:msub></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msubsup><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msub><mml:mtext>o</mml:mtext><mml:mi>Σ</mml:mi></mml:msub></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mtext>with</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mtext>o</mml:mtext><mml:mi>Δ</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>/</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mtext>o</mml:mtext><mml:mi>Σ</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>⋅</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>/</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM12\"><label>(12)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M33\" name=\"1748-7188-3-12-i33\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M34\" name=\"1748-7188-3-12-i34\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>=</mml:mo><mml:msub><mml:mtext>R</mml:mtext><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub><mml:mo>≈</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>0.5</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM13\"><label>(13)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M35\" name=\"1748-7188-3-12-i35\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>R</mml:mtext><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≈</mml:mo><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>+</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>0.5</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>0.5</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow><mml:mo>}</mml:mo></mml:mrow><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M36\" name=\"1748-7188-3-12-i36\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:msubsup><mml:mi>Δ</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>L</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>e</mml:mi><mml:mi>a</mml:mi><mml:mi>r</mml:mi></mml:mrow></mml:msubsup><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:msub><mml:mi>Δ</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>+</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>&gt;</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M37\" name=\"1748-7188-3-12-i37\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≈</mml:mo><mml:msubsup><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>start</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM14\"><label>(14)</label><italic>β</italic>_p≈ Σ_p(∞) - Σ_p(0) &gt; 0</disp-formula>", "<disp-formula id=\"bmcM15\"><label>(15)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M38\" name=\"1748-7188-3-12-i38\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mtext>R</mml:mtext><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M39\" name=\"1748-7188-3-12-i39\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mtext>R</mml:mtext><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≈</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>&gt;</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM16\"><label>(16)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M40\" name=\"1748-7188-3-12-i40\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msub><mml:mi>Θ</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>〉</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM17\"><label>(17)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M41\" name=\"1748-7188-3-12-i41\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msubsup><mml:mtext>x</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>S</mml:mtext></mml:msubsup></mml:mrow><mml:mo>〉</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mn>0</mml:mn><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM18\"><label>(18)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M42\" name=\"1748-7188-3-12-i42\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mtext>R</mml:mtext><mml:mo>〉</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mn>0</mml:mn><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M43\" name=\"1748-7188-3-12-i43\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:msubsup><mml:mtext>R</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≈</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM19\"><label>(19)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M44\" name=\"1748-7188-3-12-i44\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>≈</mml:mo><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mtd><mml:mtd><mml:mo>;</mml:mo></mml:mtd><mml:mtd><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>≈</mml:mo><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>S</mml:mtext></mml:msubsup><mml:mo>≡</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M45\" name=\"1748-7188-3-12-i45\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msubsup><mml:mi>Θ</mml:mi><mml:mtext>p</mml:mtext><mml:mtext>N</mml:mtext></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>〉</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>∞</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M46\" name=\"1748-7188-3-12-i46\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msubsup><mml:mi>Θ</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>free</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>R</mml:mtext><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>〉</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>p</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM20\"><label>(20)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M47\" name=\"1748-7188-3-12-i47\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mi>D</mml:mi><mml:msub><mml:mi>S</mml:mi><mml:mi>p</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>D</mml:mi><mml:msub><mml:mi>S</mml:mi><mml:mi>p</mml:mi></mml:msub></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mfrac><mml:mn>2</mml:mn><mml:mrow><mml:mi>ln</mml:mi><mml:mo>⁡</mml:mo><mml:mn>10</mml:mn></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mi>D</mml:mi><mml:msub><mml:mi>S</mml:mi><mml:mi>p</mml:mi></mml:msub></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>w</mml:mi><mml:mi>i</mml:mi><mml:mi>t</mml:mi><mml:mi>h</mml:mi></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>D</mml:mi><mml:msub><mml:mi>S</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mi>I</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msubsup><mml:mi>I</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mi>I</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>I</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM21\"><label>(21)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M48\" name=\"1748-7188-3-12-i48\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo>≈</mml:mo><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>WC</mml:mtext><mml:mo>−</mml:mo><mml:mtext>SC</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo>≈</mml:mo><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>WC</mml:mtext><mml:mo>−</mml:mo><mml:mtext>WC</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtext>with</mml:mtext></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mi>Δ</mml:mi><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>WC</mml:mtext><mml:mo>−</mml:mo><mml:mtext>SC</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msubsup><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>c</mml:mtext></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>Δ</mml:mi><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>WC</mml:mtext><mml:mo>−</mml:mo><mml:mtext>WC</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mn>13</mml:mn></mml:mrow><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msubsup><mml:mtext>B</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>c</mml:mtext></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM22\"><label>(22)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M49\" name=\"1748-7188-3-12-i49\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>I</mml:mtext><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mtext>p</mml:mtext></mml:mrow><mml:mtext>P</mml:mtext></mml:msubsup><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>P</mml:mtext></mml:msubsup><mml:mo>−</mml:mo><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>P</mml:mtext></mml:msubsup></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>with</mml:mtext></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>P</mml:mtext></mml:msubsup><mml:mo>=</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msubsup><mml:mtext>x</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mtext>x</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>⋅</mml:mo><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M50\" name=\"1748-7188-3-12-i50\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>x</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mi>min</mml:mi><mml:mo>⁡</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>/</mml:mo><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo>,</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM23\"><label>(23)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M51\" name=\"1748-7188-3-12-i51\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:munderover><mml:mo>∑</mml:mo><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mn>25</mml:mn><mml:mo>−</mml:mo><mml:mtext>m</mml:mtext><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:munderover><mml:mrow><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub></mml:mrow></mml:munder><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>δ</mml:mi><mml:msubsup><mml:mi>ε</mml:mi><mml:mtext>k</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:msub><mml:mi>δ</mml:mi><mml:mtext>k</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub><mml:mo>,</mml:mo><mml:msubsup><mml:mi>ξ</mml:mi><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>,</mml:mo><mml:mtext>m</mml:mtext></mml:mrow><mml:mtext>P</mml:mtext></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M52\" name=\"1748-7188-3-12-i52\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msubsup><mml:mi>Σ</mml:mi><mml:mn>0</mml:mn><mml:mrow><mml:mi>h</mml:mi><mml:mi>o</mml:mi><mml:mi>o</mml:mi><mml:mi>k</mml:mi></mml:mrow></mml:msubsup></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>p</mml:mi><mml:mo>∈</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM24\"><label>(24)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M53\" name=\"1748-7188-3-12-i53\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>c</mml:mtext></mml:msub><mml:mo>≡</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>c</mml:mtext></mml:msub><mml:mo>≡</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM25\"><label>(25)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M54\" name=\"1748-7188-3-12-i54\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>≈</mml:mo><mml:mo>−</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>c</mml:mtext></mml:msub><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M55\" name=\"1748-7188-3-12-i55\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo>≈</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mtext>chip</mml:mtext></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM26\"><label>(26)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M56\" name=\"1748-7188-3-12-i56\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>≡</mml:mo><mml:msubsup><mml:mtext>R</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>S</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>N</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M57\" name=\"1748-7188-3-12-i57\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>x</mml:mi><mml:mo>≡</mml:mo><mml:msub><mml:mi>x</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mi>I</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup><mml:mo>−</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>p</mml:mi><mml:mo>∈</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M58\" name=\"1748-7188-3-12-i58\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>μ</mml:mi><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>&gt;</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo>=</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mi>I</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>p</mml:mi><mml:mo>∈</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msub><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM27\"><label>(27)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M59\" name=\"1748-7188-3-12-i59\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msub><mml:mi>Σ</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>p</mml:mi><mml:mo>∈</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>p</mml:mi><mml:mo>∈</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msub><mml:mo>≡</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M60\" name=\"1748-7188-3-12-i60\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>r</mml:mi><mml:mo>≡</mml:mo><mml:mi>log</mml:mi><mml:msubsup><mml:mi>X</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:mrow><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msup><mml:mi>μ</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mi>log</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M61\" name=\"1748-7188-3-12-i61\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>r</mml:mi><mml:mo>≈</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msup><mml:mi>Σ</mml:mi><mml:mrow><mml:mi>h</mml:mi><mml:mi>o</mml:mi><mml:mi>o</mml:mi><mml:mi>k</mml:mi></mml:mrow></mml:msup><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msup><mml:mi>Δ</mml:mi><mml:mrow><mml:mi>h</mml:mi><mml:mi>o</mml:mi><mml:mi>o</mml:mi><mml:mi>k</mml:mi></mml:mrow></mml:msup><mml:mo>−</mml:mo><mml:msub><mml:mi>Δ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM28\"><label>(28)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M62\" name=\"1748-7188-3-12-i62\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>p</mml:mi><mml:mi>c</mml:mi><mml:mi>S</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>r</mml:mi><mml:mo>,</mml:mo><mml:mi>λ</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≈</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mn>1</mml:mn><mml:mrow><mml:mi>p</mml:mi><mml:mi>r</mml:mi><mml:mi>e</mml:mi><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msubsup><mml:mo>⋅</mml:mo><mml:mfrac><mml:mrow><mml:mi>ln</mml:mi><mml:mo>⁡</mml:mo><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:msub><mml:mi>λ</mml:mi><mml:mi>r</mml:mi></mml:msub></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:msup><mml:mi>r</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>/</mml:mo><mml:msub><mml:mi>λ</mml:mi><mml:mi>r</mml:mi></mml:msub></mml:mrow></mml:msup><mml:mo>;</mml:mo></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mi>r</mml:mi><mml:mo>&gt;</mml:mo><mml:msup><mml:mi>r</mml:mi><mml:mo>′</mml:mo></mml:msup></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mn>2</mml:mn><mml:mrow><mml:mi>p</mml:mi><mml:mi>r</mml:mi><mml:mi>e</mml:mi><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msubsup><mml:mo>/</mml:mo><mml:msup><mml:mi>r</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mo>;</mml:mo></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mn>0</mml:mn><mml:mo>&lt;</mml:mo><mml:mi>r</mml:mi><mml:mo>≤</mml:mo><mml:msup><mml:mi>r</mml:mi><mml:mo>′</mml:mo></mml:msup></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msup><mml:mi>f</mml:mi><mml:mrow><mml:mi>a</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msup><mml:mo>⋅</mml:mo><mml:mi>δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>r</mml:mi><mml:mo>,</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>;</mml:mo></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mi>r</mml:mi><mml:mo>≤</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mrow><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM29\"><label>(29)</label>⟨<italic>λ</italic>⟩ ≈ (⟨log(<italic>R </italic>+ 1)⟩_{<italic>R </italic>&gt; <italic>R</italic>'}·In 10)</disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M63\" name=\"1748-7188-3-12-i63\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mi>p</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>M</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>⋅</mml:mo><mml:msubsup><mml:mi>X</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msubsup><mml:mo>/</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mi>μ</mml:mi></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M64\" name=\"1748-7188-3-12-i64\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msub><mml:mi>M</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>⋅</mml:mo><mml:msubsup><mml:mi>X</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msubsup><mml:mo>/</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mi>x</mml:mi><mml:mo>+</mml:mo><mml:mi>μ</mml:mi></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM30\"><label>(30)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M65\" name=\"1748-7188-3-12-i65\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>p</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msubsup><mml:mi>p</mml:mi><mml:mi>p</mml:mi><mml:mi>N</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msup><mml:mi>σ</mml:mi><mml:mi>P</mml:mi></mml:msup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:msubsup><mml:mi>p</mml:mi><mml:mi>c</mml:mi><mml:mi>S</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>λ</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM31\"><label>(31)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M66\" name=\"1748-7188-3-12-i66\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>P</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>r</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:mrow><mml:msubsup><mml:mo>∫</mml:mo><mml:mrow><mml:mo>−</mml:mo><mml:mi>∞</mml:mi></mml:mrow><mml:mi>∞</mml:mi></mml:msubsup><mml:mrow><mml:msubsup><mml:mi>p</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:mi>d</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:mrow></mml:mstyle><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM32\"><label>(32)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M67\" name=\"1748-7188-3-12-i67\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>P</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mi>I</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msubsup><mml:mi>M</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msubsup><mml:mo>⋅</mml:mo><mml:msubsup><mml:mi>I</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msubsup><mml:mi>X</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup></mml:mrow><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM33\"><label>(33)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M68\" name=\"1748-7188-3-12-i68\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>Z</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:mrow><mml:msubsup><mml:mo>∫</mml:mo><mml:mrow><mml:mo>−</mml:mo><mml:mi>∞</mml:mi></mml:mrow><mml:mi>∞</mml:mi></mml:msubsup><mml:mrow><mml:msubsup><mml:mi>p</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:mi>g</mml:mi><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup><mml:mo>−</mml:mo><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>⋅</mml:mo><mml:mi>d</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:mrow></mml:mstyle><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M69\" name=\"1748-7188-3-12-i69\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mi>δ</mml:mi><mml:msubsup><mml:mi>A</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo>+</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M70\" name=\"1748-7188-3-12-i70\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>g</mml:mtext><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>x</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≡</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>x</mml:mtext><mml:mo>+</mml:mo><mml:msqrt><mml:mrow><mml:msup><mml:mtext>x</mml:mtext><mml:mn>2</mml:mn></mml:msup><mml:mo>+</mml:mo><mml:mtext>c</mml:mtext></mml:mrow></mml:msqrt><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M71\" name=\"1748-7188-3-12-i71\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>p</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M72\" name=\"1748-7188-3-12-i72\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>Z</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup><mml:mo>=</mml:mo><mml:msubsup><mml:mi>Z</mml:mi><mml:mi>p</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo>−</mml:mo><mml:mi>δ</mml:mi><mml:msubsup><mml:mi>A</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msubsup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M73\" name=\"1748-7188-3-12-i73\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>Z</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup><mml:mo>=</mml:mo><mml:mi>T</mml:mi><mml:mi>B</mml:mi><mml:msub><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msubsup><mml:mi>Z</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:mi>p</mml:mi><mml:mo>∈</mml:mo><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M74\" name=\"1748-7188-3-12-i74\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:mrow><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:msubsup><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:mrow><mml:mi>P</mml:mi></mml:msubsup></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM34\"><label>(34)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M75\" name=\"1748-7188-3-12-i75\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>Z</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>−</mml:mo><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:mrow><mml:msubsup><mml:mo>∫</mml:mo><mml:mrow><mml:mo>−</mml:mo><mml:mi>∞</mml:mi></mml:mrow><mml:mi>∞</mml:mi></mml:msubsup><mml:mrow><mml:msubsup><mml:mi>p</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>r</mml:mi><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:mi>g</mml:mi><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:msub><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mi>N</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>⋅</mml:mo><mml:mi>d</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:mrow></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M76\" name=\"1748-7188-3-12-i76\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>Δ</mml:mi><mml:msub><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msubsup><mml:mi>L</mml:mi><mml:mrow><mml:mn>0</mml:mn><mml:mo>,</mml:mo><mml:mi>p</mml:mi></mml:mrow><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M77\" name=\"1748-7188-3-12-i77\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>Δ</mml:mi><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mi>N</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mi>P</mml:mi></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:msubsup><mml:mi>L</mml:mi><mml:mi>p</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mi>x</mml:mi><mml:mo>⋅</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>ρ</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M78\" name=\"1748-7188-3-12-i78\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:mi>x</mml:mi><mml:mo>→</mml:mo><mml:msubsup><mml:mi>μ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msub><mml:mi>ρ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mi>x</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM35\"><label>(35)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M79\" name=\"1748-7188-3-12-i79\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mtext>L</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:msubsup><mml:mtext>L</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>≈</mml:mo><mml:msub><mml:mtext>s</mml:mtext><mml:mtext>c</mml:mtext></mml:msub><mml:mo>⋅</mml:mo><mml:msubsup><mml:mtext>L</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>≈</mml:mo><mml:msup><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msubsup><mml:mtext>s</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup><mml:mo>⋅</mml:mo><mml:msubsup><mml:mtext>L</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>−</mml:mo><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM36\"><label>(36)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M80\" name=\"1748-7188-3-12-i80\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mtext>S</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mtext>L</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mtext>M</mml:mtext><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM37\"><label>(37)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M81\" name=\"1748-7188-3-12-i81\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mtext>S</mml:mtext><mml:mrow><mml:mtext>set</mml:mtext></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mtext>R</mml:mtext><mml:mo>⋅</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mtext>R</mml:mtext><mml:mo>⋅</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>β</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mtext>n</mml:mtext><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM38\"><label>(38)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M82\" name=\"1748-7188-3-12-i82\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mi>S</mml:mi><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mi>c</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>φ</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:mrow></mml:msup></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>w</mml:mi><mml:mi>i</mml:mi><mml:mi>t</mml:mi><mml:mi>h</mml:mi></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msub><mml:mi>φ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>≡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>λ</mml:mi><mml:mi>r</mml:mi></mml:msub></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", 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xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M84\" name=\"1748-7188-3-12-i84\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mtext>N</mml:mtext><mml:mtext>c</mml:mtext></mml:msub><mml:mo>≡</mml:mo><mml:msubsup><mml:mtext>X</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mtext>N</mml:mtext><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mtext>c</mml:mtext></mml:msub><mml:mo>⋅</mml:mo><mml:msubsup><mml:mtext>K</mml:mtext><mml:mtext>c</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msubsup><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM41\"><label>(41)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M85\" name=\"1748-7188-3-12-i85\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mi>Σ</mml:mi><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mi>Θ</mml:mi><mml:mo>≡</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mrow><mml:mi>Δ</mml:mi><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mi>Θ</mml:mi><mml:mo>≡</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msup><mml:mo>−</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", 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overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>∞</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M87\" name=\"1748-7188-3-12-i87\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>h</mml:mi></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mi>X</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mo>,</mml:mo><mml:mi>h</mml:mi></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>X</mml:mi><mml:mi>P</mml:mi></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM43\"><label>(43)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M88\" name=\"1748-7188-3-12-i88\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mi>X</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>X</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo>⋅</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mi>R</mml:mi><mml:mo>⋅</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mi>X</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo>/</mml:mo><mml:mi>n</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>X</mml:mi><mml:mrow><mml:mi>P</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo>⋅</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>/</mml:mo><mml:mi>n</mml:mi><mml:mo>+</mml:mo><mml:mi>R</mml:mi><mml:mo>/</mml:mo><mml:mi>s</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mi>R</mml:mi><mml:mo>⋅</mml:mo><mml:mfrac><mml:mi>n</mml:mi><mml:mi>s</mml:mi></mml:mfrac><mml:mo>⋅</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mi>M</mml:mi><mml:mi>M</mml:mi><mml:mo>,</mml:mo><mml:mi>N</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>R</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM44\"><label>(44)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M89\" name=\"1748-7188-3-12-i89\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mtext>P</mml:mtext></mml:msup><mml:mo>−</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mtext>P</mml:mtext></mml:msup><mml:mo>−</mml:mo><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M90\" name=\"1748-7188-3-12-i90\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mtext>x</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup><mml:mo>≡</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mtext>P</mml:mtext></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM45\"><label>(45)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M91\" name=\"1748-7188-3-12-i91\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msup><mml:mtext>x</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mi>β</mml:mi><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mtext>n</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msup><mml:mtext>x</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mi>β</mml:mi><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mtext>n</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M92\" name=\"1748-7188-3-12-i92\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mi>β</mml:mi><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mtext>n</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M93\" name=\"1748-7188-3-12-i93\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mi>β</mml:mi><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mtext>n</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M94\" name=\"1748-7188-3-12-i94\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mtext>R</mml:mtext><mml:mtext>P</mml:mtext></mml:msup><mml:mo>≡</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:msup><mml:mi>Θ</mml:mi><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>N</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mfrac><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mtext>x</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mtext>x</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>S</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM46\"><label>(46)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M95\" name=\"1748-7188-3-12-i95\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mtext>R</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>∞</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>∞</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:msup><mml:mtext>R</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msup><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Σ</mml:mi><mml:mo>−</mml:mo><mml:mi>Σ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>∞</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Δ</mml:mi><mml:mo>−</mml:mo><mml:mi>Δ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>∞</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M96\" name=\"1748-7188-3-12-i96\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mtext>R</mml:mtext><mml:mo>〉</mml:mo></mml:mrow><mml:mo>≡</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>0.5</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mtext>R</mml:mtext><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mtext>R</mml:mtext><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM47\"><label>(47)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M97\" name=\"1748-7188-3-12-i97\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mrow><mml:mrow><mml:mrow><mml:mtext>slope</mml:mtext><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>mix</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mo>∂</mml:mo><mml:msup><mml:mi>Δ</mml:mi><mml:mrow><mml:mtext>hook</mml:mtext></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mo>∂</mml:mo><mml:mtext>R</mml:mtext></mml:mrow></mml:mfrac><mml:mo>⋅</mml:mo><mml:mfrac><mml:mrow><mml:mo>∂</mml:mo><mml:mtext>R</mml:mtext></mml:mrow><mml:mrow><mml:mo>∂</mml:mo><mml:msup><mml:mi>Σ</mml:mi><mml:mrow><mml:mtext>hook</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow><mml:mo>|</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>→</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo>≈</mml:mo><mml:mn>2</mml:mn><mml:mfrac><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mi>min</mml:mi><mml:mo>⁡</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>ln</mml:mi><mml:mo>⁡</mml:mo><mml:mn>10</mml:mn><mml:mo>⋅</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo>,</mml:mo><mml:mn>2</mml:mn><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM48\"><label>(48)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M98\" name=\"1748-7188-3-12-i98\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>Δ</mml:mi><mml:mn>2</mml:mn></mml:msubsup><mml:mo>=</mml:mo><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup><mml:mo>−</mml:mo><mml:mn>2</mml:mn><mml:mo>⋅</mml:mo><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>MM</mml:mtext></mml:mrow></mml:msub><mml:mo>≈</mml:mo><mml:mn>2</mml:mn><mml:mo>&lt;</mml:mo><mml:msup><mml:mi>σ</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>&gt;</mml:mo><mml:mo>⋅</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>ρ</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>Σ</mml:mi><mml:mn>1</mml:mn></mml:msubsup><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>4</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup><mml:mo>+</mml:mo><mml:mn>2</mml:mn><mml:mo>⋅</mml:mo><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>MM</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>≈</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mo>&lt;</mml:mo><mml:msup><mml:mi>σ</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>&gt;</mml:mo><mml:mo>⋅</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mi>ρ</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:mtext>with</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mo>&lt;</mml:mo><mml:msup><mml:mi>σ</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>&gt;</mml:mo><mml:mo>≡</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mtext>and</mml:mtext></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>ρ</mml:mi><mml:mo>≡</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>MM</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow></mml:msub><mml:mo>⋅</mml:mo><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>≈</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext><mml:mo>,</mml:mo><mml:mtext>MM</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:mo>&lt;</mml:mo><mml:msup><mml:mi>σ</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>&gt;</mml:mo></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M99\" name=\"1748-7188-3-12-i99\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mo>&lt;</mml:mo><mml:msup><mml:mi>σ</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>&gt;</mml:mo><mml:mo>≈</mml:mo><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>PM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup><mml:mo>≈</mml:mo><mml:msubsup><mml:mi>σ</mml:mi><mml:mrow><mml:mtext>MM</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msubsup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula id=\"bmcM49\"><label>(49)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M100\" name=\"1748-7188-3-12-i100\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>slope</mml:mtext><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>N</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>∝</mml:mo><mml:msqrt><mml:mrow><mml:mfrac><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>Δ</mml:mi><mml:mn>2</mml:mn></mml:msubsup></mml:mrow><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>Σ</mml:mi><mml:mn>2</mml:mn></mml:msubsup></mml:mrow></mml:mfrac></mml:mrow></mml:msqrt><mml:mo>=</mml:mo><mml:mn>2</mml:mn><mml:msqrt><mml:mrow><mml:mfrac><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>ρ</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mi>ρ</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mfrac></mml:mrow></mml:msqrt><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM50\"><label>(50)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M101\" name=\"1748-7188-3-12-i101\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mtext>Y</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>exp</mml:mi><mml:mo>⁡</mml:mo><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≡</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>P</mml:mtext></mml:msubsup><mml:mo>−</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:msubsup><mml:mtext>I</mml:mtext><mml:mtext>p</mml:mtext><mml:mtext>P</mml:mtext></mml:msubsup></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mtext>set</mml:mtext><mml:mo>∈</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msub><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM51\"><label>(51)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M102\" name=\"1748-7188-3-12-i102\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>Y</mml:mi><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>theory</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>≈</mml:mo><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msub><mml:mrow><mml:mrow><mml:mo>〈</mml:mo><mml:mrow><mml:mi>δ</mml:mi><mml:msubsup><mml:mtext>A</mml:mtext><mml:mtext>p</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup></mml:mrow><mml:mo>〉</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mtext>set</mml:mtext><mml:mo>∈</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:munderover><mml:mo>∑</mml:mo><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mn>25</mml:mn><mml:mo>−</mml:mo><mml:mtext>m</mml:mtext><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:munderover><mml:mrow><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub></mml:mrow></mml:munder><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>δ</mml:mi><mml:msubsup><mml:mi>ε</mml:mi><mml:mtext>k</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>⋅</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>δ</mml:mi><mml:mtext>k</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub><mml:mo>,</mml:mo><mml:msubsup><mml:mi>ξ</mml:mi><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>,</mml:mo><mml:mtext>m</mml:mtext></mml:mrow><mml:mtext>P</mml:mtext></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:msub><mml:mtext>f</mml:mtext><mml:mtext>k</mml:mtext></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mtext>b</mml:mtext><mml:mtext>m</mml:mtext></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:mstyle><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM52\"><label>(52)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M103\" name=\"1748-7188-3-12-i103\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msubsup><mml:mi>ε</mml:mi><mml:mtext>k</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>B</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:mo>=</mml:mo><mml:mtext>A</mml:mtext><mml:mo>,</mml:mo><mml:mtext>T</mml:mtext><mml:mo>,</mml:mo><mml:mtext>G</mml:mtext><mml:mo>,</mml:mo><mml:mtext>C</mml:mtext></mml:mrow></mml:munder><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:mtext>B</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>+</mml:mo><mml:msubsup><mml:mi>ε</mml:mi><mml:mtext>k</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>B</mml:mtext><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:msubsup><mml:mi>ε</mml:mi><mml:mtext>k</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>B</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>3</mml:mn></mml:mfrac><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:mo>=</mml:mo><mml:mtext>A</mml:mtext><mml:mo>,</mml:mo><mml:mtext>T</mml:mtext><mml:mo>,</mml:mo><mml:mtext>G</mml:mtext><mml:mo>,</mml:mo><mml:mtext>C</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:msup><mml:mtext>B</mml:mtext><mml:mo>″</mml:mo></mml:msup><mml:mo>=</mml:mo><mml:mtext>A</mml:mtext><mml:mo>,</mml:mo><mml:mtext>T</mml:mtext><mml:mo>,</mml:mo><mml:mtext>G</mml:mtext><mml:mo>,</mml:mo><mml:mtext>C</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:munder><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>ε</mml:mi><mml:mtext>k</mml:mtext><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>B</mml:mtext><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:msup><mml:mtext>B</mml:mtext><mml:mo>″</mml:mo></mml:msup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>+</mml:mo><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:mtext>B</mml:mtext><mml:msup><mml:mtext>B</mml:mtext><mml:mo>″</mml:mo></mml:msup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>+</mml:mo><mml:msubsup><mml:mi>ε</mml:mi><mml:mrow><mml:mtext>k</mml:mtext><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow><mml:mrow><mml:mtext>P</mml:mtext><mml:mo>,</mml:mo><mml:mtext>h</mml:mtext></mml:mrow></mml:msubsup><mml:mo stretchy=\"false\">(</mml:mo><mml:msup><mml:mtext>B</mml:mtext><mml:mo>′</mml:mo></mml:msup><mml:msup><mml:mtext>B</mml:mtext><mml:mo>″</mml:mo></mml:msup><mml:mtext>B</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM53\"><label>(53)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M104\" name=\"1748-7188-3-12-i104\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtext>R</mml:mtext><mml:mo>=</mml:mo><mml:mo>−</mml:mo><mml:mfrac><mml:mtext>p</mml:mtext><mml:mn>2</mml:mn></mml:mfrac><mml:mo>+</mml:mo><mml:msqrt><mml:mrow><mml:mfrac><mml:mrow><mml:msup><mml:mtext>p</mml:mtext><mml:mn>2</mml:mn></mml:msup></mml:mrow><mml:mn>4</mml:mn></mml:mfrac><mml:mo>+</mml:mo><mml:mtext>q</mml:mtext></mml:mrow></mml:msqrt><mml:mo>≥</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtext>p</mml:mtext><mml:mo>=</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>+</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>2</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>Σ</mml:mi><mml:mn>0</mml:mn><mml:mrow><mml:mtext>hook</mml:mtext></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn><mml:msub><mml:mi>β</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>+</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtext>q</mml:mtext><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>+</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>2</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>Σ</mml:mi><mml:mn>0</mml:mn><mml:mrow><mml:mtext>hook</mml:mtext></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:msub><mml:mi>Σ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn><mml:msub><mml:mi>β</mml:mi><mml:mtext>c</mml:mtext></mml:msub></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>β</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo>+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:mfrac><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:msub><mml:mi>Δ</mml:mi><mml:mtext>c</mml:mtext></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mn>0</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mtd></mml:mtr></mml:mtable><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M105\" name=\"1748-7188-3-12-i105\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>SSQ</mml:mtext><mml:mo>=</mml:mo><mml:mstyle 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[ "<title>Background</title>", "<p>There is currently a severe shortage of experienced nurses in Australia, as in many other developed countries. This is considered to be the result of both decreasing enrolments in nursing education, and poor retention rates of those in the nursing workforce. Retention rates are generally thought to have worsened over recent years. There is also concern over the ageing of the nursing workforce since this will cause critical shortages in the future as greater proportions of nurses reach retirement age.</p>", "<p>The Senate Select Committee on Nursing described workforce retention as an acute problem, and a key issue in ensuring adequate numbers in the future. The reasons given for nurses leaving the workforce include pay and conditions, increased workload, particularly in acute hospitals with higher complexity patients admitted for shorter stays, lack of childcare, and poor recognition of nurses' skills and knowledge [##UREF##0##1##]. There is a general perception that, as workloads have increased, nurses feel undervalued and increasingly stressed, retention rates fall further increasing workloads, leading to higher levels of stress and burnout, and a further decrease in retention. However, there is no readily available information on the number of nurses leaving the workforce.</p>", "<p>The Australian Institute of Health and Welfare reports the number of nurses employed in nursing, for all nurses and registered and enrolled nurses separately [##UREF##1##2##]. While this provides some indication of the size of a potential pool of trained nurses, it does not show retention rates, their changes over time, or whether they vary according to the type of job, the type of hospital, or type of nurse. A report by the National Nursing and Nursing Education Taskforce shows that nursing students are more likely to complete their course and to find employment in their field than other higher education programs. However, no data are available on attrition once in employment, and, as stated in the report, \"there is little good data that allows us to know what is actually occurring within nursing or to compare nursing to other careers\" [[##UREF##2##3##], p2].</p>", "<p>The issue of the public and private sector distribution of resources is of great interest to policy makers and to researchers. The growth in private hospitals over the last twenty years raises the possibility that the shortage of nurses in the public sector is, in large part, due to a shift of resources to the rapidly growing area of private health care. Understanding the allocation of the nursing workforce in the two sectors, and changes over time in this allocation is important in developing policies towards solving the nursing shortage.</p>", "<p>There is very little work in the economics literature on the nursing workforce in Australia. The reason for this is again the lack of appropriate data. Shah and Long use data from the Labour Force Survey (LFS) to predict the supply of nurses and other health care workers as well as shortages in these professions based on a forecast of the demand for health care [##UREF##3##4##]. Given the small sample of nurses in general surveys such as the LFS, the potential for detailed micro-econometric analysis based on these data is limited. In an earlier article, Doiron and Jones use NSW administrative data to analyze the relationship between hospital characteristics and nurse retention in 1996–97. Based on cross-section variation in the characteristics of nurses and the hospitals in which they work, this study finds that several hospital characteristics significantly affect the probability of retention. Characteristics which positively affect retention include hospital size, expenditures, emergency admissions and staffing levels. Factors which negatively affect retention include workloads, complexity (ANDRG weight), and greater usage of visiting medical officers. Surprisingly, no evidence of hospital specific effects over and above observed hospital characteristics was found [##UREF##4##5##].</p>", "<p>Nursing shortages are a concern in many countries and a significant number of studies on nursing labour supply have been conducted in recent years based on overseas data. Reviews of the literature are provided in Shields [##UREF##5##6##], and Antonazzo, Scott, Skatun and Elliott [##REF##12759916##7##].</p>", "<p>A larger body of work on the nursing shortage in Australia can be found in nursing journals and government reports [##REF##11256272##8##, ####UREF##6##9##, ##UREF##7##10##, ##UREF##8##11####8##11##]. Many of the issues and concerns over the present state of the nursing profession discussed above are drawn from these studies. The current article contributes to the area by providing more quantitative and evidence-based results on nursing retention over time. Specifically, we use administrative data on New South Wales (NSW) nurses to analyze trends over the period 1993–2000 in the nursing workforce: the aging of the population of workers, the attrition rates by age group and by premises, and the year to year movements across nursing jobs as well as in and out of nursing.</p>" ]

[ "<title>Methods</title>", "<title>Data</title>", "<p>All working nurses in NSW must be registered with the NSW Nurses Registration Board. We begin by using aggregate figures based on this information and published by NSW Health. These data allow us to construct a consistent data series on the size of the nursing workforce in NSW from 1986 to 2000. This is informative in establishing trends over time in the total supply of nurses in NSW.</p>", "<p>At the time of registration, those nurses renewing their registration (rather than registering for the first time) are given a labour force questionnaire which covers personal characteristics and, if working in NSW, information about the job including location, hours of work, and type of work. Unit record files based on the information collected by the NSW Nurses Registration Board from the registration renewal form and the labour force questionnaire have been provided to us in a de-identified form by the Australian Institute of Health and Welfare (AIHW) with NSW Health's permission. Each nurse is given a unique identifier (a random number unrelated to the nurses' registration number) permitting the linkage of individuals over time. The data span the years 1993–2000, excluding 1998.</p>", "<p>Estimates of the response rate to the labour force questionnaire suggest that the data represent between 85 and 90% of the total nursing workforce in NSW [##UREF##1##2##]. Hence we can follow the working history of a large sample of nurses over a fairly long panel. With these data, we can analyse retention and changes in retention by type of premises and nurse characteristic. We can also look at nurses who remain in nursing but who change type of premises from year to year. These data form the basis of all quantitative analyses reported below.</p>", "<title>Analysis</title>", "<p>Retention rates are calculated separately for different types of nurses and jobs, and for different time periods. To further quantify changes over time, separate retention probit regressions are estimated for 1994–95 and 1999–2000. Separate probit regressions are also estimated for RNs and enrolled nurses. Explanatory variables include controls for personal characteristics and proxies for human capital (sex, age, citizenship, post basic education, years since first registered as a nurse); job characteristics (hours of work, an indicator for the presence of a second job in nursing, field, activity, job classification, location of the job, and premises); and the local unemployment rate. There is no information on wages; however most nurses will be covered by award wages and hence, their wages will be determined in large part by their job classification. This analysis is useful in allowing us to separate out and quantify the contribution of these various characteristics to retention and to changes in retention over time. Finally, cohorts of nurses are followed over time in order to describe the profile of work experience by nurses.</p>" ]

[ "<title>Results</title>", "<title>General trends in the nursing workforce</title>", "<p>Figure ##FIG##0##1## presents trends in the employment of nurses in total and RNs only in NSW from 1986 to 2000. For comparison, the trend in total female employment in the State is also plotted. Figure ##FIG##0##1## shows that the growth rate in the total number of nurses has slowed in the 90s compared to 1986–1989. It has also slowed relative to the trend in total employment of women in the state. The trend in the employment of RNs follows closely that of the total nursing employment. RNs comprise between 80 and 85% of total nurses in the state and, despite the concerns that less skilled nurses are being increasingly used as substitutes for RNs, no definite trend is detected in the proportion of RNs to enrolled nurses over the period in question.</p>", "<title>Nurse retention by age</title>", "<p>We now make use of the detailed unit record data from the NRB. Table ##TAB##0##1## presents statistics on the average age of the workforce and the proportion of nurses in the younger age groups: less than 25 years of age and 25–29 years of age. A nurse is defined as working if he/she either a) answers the labour force question and indicates working in NSW or b) provides positive hours of work in nursing in NSW. With this definition, some nurses who are providing positive hours of unpaid work may be included as working, but it does provide consistent estimates over the period under study. More details are available from the authors.</p>", "<p>The third column shows an increase in the average age of working nurses over the period from just under 39 in 1993 to over 42 in the year 2000, a substantial increase in a relatively short period of time. A similar increase in the average age is found when considering RNs only.</p>", "<p>The next set of columns suggests that one cause of this aging is a substantial reduction in nurses in the youngest age group. The percentage of all working nurses in this age group falls from almost 7% in 1993 to less than 3% by the year 2000. There is in fact a large drop in the absolute number of both RNs and enrolled nurses less than 25 years of age from 1997 to 2000. Specifically, the number of working RNs (enrolled nurses) under 25 years of age went from 2004 (660) in 1997 to 1245 (410) in 1999 and 1216 (347) in 2000. This is the result of a decrease in the entry into nursing, bachelor degree non-overseas student commencements dropped from 11,274 in 1994 to 8,248 in 2000 [##REF##16929471##12##].</p>", "<p>The reduction in the under 25 cohort has started to feed into the next age group (25–29) and a continued drop in the numbers in this age group is expected in the next few years. Any trend to increase the proportion of mature age entrants to nursing will also affect the age profile of the workforce. Whether this will contribute to an aging of the workforce depends on the age distribution of this pool of entrants.</p>", "<p>In presenting evidence on retention, we focus on data for 1994–95 and 1999–2000. These years span most of the available period and the growth rates for 1994–95 and 1999–2000 in the microdata match very closely the official estimates published by NSW Health. Figures ##FIG##1##2## and ##FIG##2##3## plot retention rates by age group for RNs and enrolled nurses. Retention rates have been calculated as follows. For each year, all nurses working in NSW are identified and categorised by age group. Using the individual identifier, we see if the nurse is still working in NSW in the following year. If the answer is 'yes', the nurse is part of the retained group. This is true whether or not the nurse is still in the same job premises. For example, a nurse working in a public hospital in 1994 and working in a private nursing home in 1995 is considered as retained. This definition of retention is appropriate when analysing nurses' decisions to remain or leave nursing rather than the choice of staying in particular work premises.</p>", "<p>The overall retention rate for nurses in 1994–95 is 82.3%; hence 17.7% have stopped working in nursing in NSW in 1995 at least temporarily. The rate for RNs is higher than for enrolled nurses (83.6 versus 75.6%). Retention rates are lowest for the extreme age groups. This is not unique to nursing. The young are known to have high mobility rates across jobs and labour market states, and this is usually explained by job shopping and attempts to improve on the quality of the job match. Since most nurses are female, low retention rates in the child bearing years is also expected. The old are retiring from the labour force. For nurses in NSW, the highest retention rates are found for the 40–55 age groups.</p>", "<p>How do these rates compare with overseas nurses or with other occupations? According to Fritjers et al [##REF##16929471##12##], the turnover rate among nurses in the British National Health Service is approximately 10% while McCarty et al [##UREF##9##13##] report rates for the USA between 20% and 30%. There is sparse evidence of turnover by occupation generally but numbers involving teachers suggest similar attrition. For example, Clotfelter et al calculate year on year attrition rates amongst teachers in North Carolina at around 26% [##UREF##10##14##].</p>", "<p>The surprising fact shown in Figures ##FIG##1##2## and ##FIG##2##3## is that retention rates in NSW have not worsened over the period 1995–2000. On average and for most age groups, they have slightly improved. Overall, the rate increased from 82.3% to 83.3% with the largest increases found amongst the enrolled nurses and generally in the youngest age groups. These figures suggest that the aging of the nursing workforce originates from fewer entrants, particularly of school leavers, and a slight improvement in retention.</p>", "<title>Growth and retention by type of premises</title>", "<p>Table ##TAB##1##2## shows the distribution of nurses by broad categories of type of premises for 1994 and 2000. Growth rates are computed separately for public and private sectors. Overall there has been a slight increase in the proportion of all nurses working in the public sector from 72% in 1994 to 75% in 2000. The private sector overall does not show an increase in the employment of nurses over the period and the aggregate 10% rise in the nursing workforce is found in the total public sector employment growth.</p>", "<p>Table ##TAB##1##2## shows that private sector hospitals have grown much faster than public sector hospitals (33% compared to 11%) however employment in private hospitals is still very small compared to the public sector institutions. The areas of rapid growth are the public sector nursing homes and community health. In the private sector, growth in private nursing practices and doctor's rooms has also been rapid.</p>", "<p>Given the differences in employment growth across premises, one would have expected movements in retention probabilities over time. However, retention rates by age presented earlier suggest very stable retention probabilities over the analysis period. Are retention rates similar across premises? We turn to this question next.</p>", "<p>Table ##TAB##2##3## presents retention rates across three broad groups of premises for 1994–95 and 1999–2000. Retention rates are defined in the same manner as above; in particular the type of premises is that in which the nurse worked in the base year and nurses are treated as retained as long as they are working in the following year (in NSW) even if they have changed premises.</p>", "<p>Except for nursing homes, the retention rates in public sector premises are greater than in corresponding private premises. This holds for both time periods. Rates for nurses under 30 years of age show the same relative magnitudes in retention between public and private sectors. (Results are available from the authors.) The last set of columns in Table ##TAB##2##3## shows the differences in retention rates over time. In all cases, these differences are positive; i.e. there are improvements in retention across all major groups of premises. The largest increases in retention are found in nursing homes and generally amongst enrolled nurses.</p>", "<p>We do not find evidence of a problem with retention in nursing specific to public sector hospitals. Public sector hospitals have higher retention rates than other categories of premises except for private sector nursing homes. Furthermore, although the increase in retention in public hospitals has been slightly less compared to other premises, it has been positive. The stable aggregate retention rates shown earlier are a product of lessening differences in retention across sectors, and faster growth in the sectors with worse but more rapidly improving retention probabilities.</p>", "<p>Retention in specific types of premises (i.e. the proportion of nurses who remain employed in the same sector rather than in nursing as a whole) show similar patterns (details available from the authors.) The average probability of remaining in the public hospital sector (for those already working in a public hospital) is 76% in 1994–95 and 77% in 1999–2000; corresponding figures for the private sector hospitals are 67% and 70% respectively.</p>", "<p>Changes in predicted probabilities of retention are decomposed into components due to changes in coefficients and changes in the distribution of the characteristics. Table ##TAB##3##4## summarizes the results. (Detailed results are available from the authors.) The main result from the decomposition is that there are only minor differences in either the distributions of the explanatory factors or in the coefficients. Very few sets of coefficients are statistically different over the two years and in particular the coefficients on type of premises are not jointly significantly different. The greater age and level of experience of nurses in 1999 did tend to increase retention rates but lower unemployment rates and shifts in the field away from clinical work caused a reduction in retention. The net effect is very small. Overall there has been very little change over time in retention levels and retention functions of personal and job characteristics.</p>", "<title>Transition probabilities across types of premises</title>", "<p>We show in this section of the article that the stability in retention rates over time masks a substantial amount of movement by individuals from year to year across types of premises as well as in and out of nursing. We use the term 'churning' to describe this phenomenon. Using the long panel nature of the data we follow cohorts of nurses over time. In Table ##TAB##4##5##, four cohorts of RNs are chosen: a young cohort and a middle-aged cohort working in 1994 and cohorts in the same age groups working in 1997. In the top panel we follow the cohort of individuals who were working as RNs in 1994 and were aged 21–23 years at that time. This group numbers 1059. Most young nurses start their career in public sector hospitals and for the group represented in Table ##TAB##4##5##, we find that 70% were employed in public hospitals. One year later, 29.5% of the group are not working as nurses in NSW. Two years later the figure is 37%. The proportion not working then stays fairly stable at 37–43% up to year 2000 at which time the cohort is aged 27–29. If we follow the young cohort of working RNs in 1997 (the second panel in the table) we find even more concentration in the public hospitals. We also find a slightly increased proportion staying on as nurses (68 versus 63%); this is consistent with the results of improved retention presented above.</p>", "<p>In comparison, we present similar results for the older cohort aged 41–43 in 1994. The proportion not working in the following year (13%) is much lower than for the younger age group reflecting the increased retention rates for older nurses, though this will include mature recent entrants to the workforce as well as experienced nurses. Again comparing to the same age cohort in 1997, we find a slightly improved retention rate at the end of the period. In some sense, Table ##TAB##4##5## shows several of the results discussed previously, a stable profile of retention over time with a slight improvement in retention in nursing overall. Barring the youngest and oldest age groups, there is also a relatively stable retention profile over time by age cohorts.</p>", "<p>In order to show in more detail the underlying flows, we look at the full matrix of transition probabilities across premises. Table ##TAB##5##6## presents these figures for two of the cohorts described above; in each case we present the transition frequencies between 1999 and 2000. For example of the 452 RNs of cohort 1 who were working in public hospitals in 2000, 75% were also working in public hospitals in 1999, 2% were working in private hospitals, 1% were working in other public premises and 22% were not working. Of the 398 RNs not working in 2000, only 76% were not working in 1999.</p>", "<p>The table shows that many RNs move between working and not working in any single year and a substantial number also move between sectors of employment. There is less movement for the older cohorts but it is still considerable. We find similar results for other years covered by the panel. It is possible that these movements are the result of dissatisfaction with the current job and represent a search for better working conditions. In this case policy intervention could not only improve nurses' job satisfaction and retention but also reduce possibly inefficient search and job switches across type of premises and out of the nursing workforce.</p>", "<p>As an indication of the relative magnitude of movements between work and non-work and between type of premises for nursing, we calculate a mobility index from the transition information illustrated in Table ##TAB##5##6##. Using the Shorrocks [##UREF##11##15##] index of mobility, we find that mobility among the young cohort is 47% while the measure for older nurses is 45%. To give some idea of the importance of these values, Boeri and Flinn calculate values of 20% for occupational mobility among Italian women based on 9 occupational categories [##UREF##12##16##].</p>" ]

[ "<title>Discussion</title>", "<p>The profile of the NSW nursing workforce shows a substantial increase during the late 80s followed by a small trend upward in the 90s. The slow growth in the overall nursing workforce over the 90s can originate from a reduction in entry into nursing, a reduction in retention of nurses or an increasing tendency to retire early (reduced retention among higher age groups). It is important to recognise which of these forces is responsible for the relative slowdown in nursing employment as the recommended policy responses will differ. For example, increasing nurse intake from school leavers will have little impact if young nurses have high and increasing attrition rates. If increased attrition is concentrated in experienced nurses, then the appropriate policy response will focus on career paths and recognition for seniority and skill. Our evidence points to a problem in the entry of young nurses which is declining in the later years of the decade and which is too slow relative to demand.</p>", "<p>Although retention is often discussed as an area of concern when discussing the nursing workforce, little work has been done on documenting its movements over time [##UREF##0##1##,##UREF##6##9##,##UREF##7##10##,##UREF##13##17##]. While the aging of the nursing workforce has received more attention, the relationship between aging and retention is rarely considered [##UREF##1##2##]. In general a reduction in retention while maintaining the age profile of new entrants will lead to a lowering of the average age of the workforce. However if this is accompanied by a reduction in entry, or an increase in the proportion of older entrants, then it will lead to an increase of the average age of the workforce.</p>", "<p>The analysis presented above suggests that very little change has occurred over time in the retention rates in nursing. Furthermore, poor retention is not a problem particular to the public hospital sector. The finding of improved retention rates contradicts the widespread perception of a developing crisis in nursing retention. This implies that policies aimed at increasing the nursing positions in tertiary institutions may be more appropriate in the short term, as indeed is recommended by the National Review of Nursing Education [##UREF##7##10##].</p>", "<p>This does not necessarily mean that there is no role for policy intervention in trying to improve retention. But further improvements in retention may require more focussed attention to identify specific aspects of working conditions. Shields and Ward found that although pay rates were important in determining overall job satisfaction, other aspects of the working environment were extremely important in explaining satisfaction and intentions to leave nursing [##REF##11558644##18##]. The analysis of 'Magnet Hospitals' in the US carried out by Scott et al has shown that the attributes of nursing administration and leadership, nursing practice and nurse-doctor relationships are important in attracting and maintaining nursing staff [##REF##9921144##19##]. Finally, Buchanan et al found that the most frequent reason for nurses working less was a change in family and/or personal life; hence more attention is needed to understand and help manage family and other demands [##UREF##14##20##].</p>", "<p>In addition, churning in the younger age groups is an issue which is not well understood. As the nursing workforce is predominantly female, retention in nursing and job switching will be affected by child rearing responsibilities. What appears as an exit from the workforce in year to year transitions may in fact be a period spent caring for children followed by a return to the nursing workforce as children become more independent. Our results suggest that a substantial fraction of nurses who leave nursing return within a relatively short time frame (2 to 5 years). The administrative data unfortunately did not provide information on the nature of these periods away from nursing; in particular no information was available on whether the nurses were taking leave to sample other types of jobs or to raise children. As the National Nursing and Nursing Education Taskforce noted, there are many reasons why people change study, change jobs, and change careers but too few good studies that allow us to understand what drives these decisions [##UREF##2##3##].</p>" ]

[ "<title>Conclusion</title>", "<p>In this article, we investigate trends in the NSW nursing workforce over the the period 1993–2000 using administrative data collected by the NSW Nursing Registration Board and the Australian Institute of Health and Welfare. The dataset is longitudinal in that nurses can be linked across the years using a de-personalized identity number. This allows us to look at retention in nursing in NSW and to analyse retention probabilities by year, sector of work, age of the nurse and other personal and job characteristics.</p>", "<p>Overall, several findings are obtained.</p>", "<p>• Evidence of aging of the nursing workforce is found and this is caused by two reinforcing factors: a slower entry of young workers into the workforce and an increase in retention over time. The improved retention is found in most age groups, including the youngest group.</p>", "<p>• Employment growth has been faster in the public sector overall but this is due to rapid increases in community health and nursing homes. When restricting attention to hospitals, we find that growth has been faster in the private sector.</p>", "<p>• Retention is generally higher in public sector premises and is highest amongst nurses working in public hospitals.</p>", "<p>• Retention is surprisingly stable over time. Probit regressions explaining retention show very little change in either the distributions of characteristics or in the estimated coefficients. The greater age and level of experience of nurses did tend to increase retention rates over time but lower unemployment rates and shifts in the nursing fields away from clinical work caused a reduction in retention. The net effect is very small.</p>", "<p>• Net results based on stocks of nurses over time hide substantial flows from year to year across type of premises as well as in and out of employment in nursing. This is especially true for the younger age cohorts.</p>", "<p>Job vacancies in the health care industry in Australia grew from 4,000 to 11,900 during the period 1993–2000. This suggests that there was excess demand in the sector as a whole and that the shortages reflected a problem of lack of supply. From our analysis, it follows that an appropriate focus is increasing entry into nursing but that encouraging retention of graduating nurses in the nursing workforce is also important.</p>", "<p>Recent recommendations of the Productivity Commission addressing health workforce shortages stress the need for research to address recruitment, training, retention and re-entry, as well as exploring new roles for nurses and other health professionals and increasing flexibility in education and role definition [##UREF##15##21##]. Such research is also required to underpin further health service reforms including new models of service delivery and new methods of funding health services,. The data requirements to undertake comprehensive studies of nursing labour supply are substantial and we suggest that different types of data be collected: surveys of actual career choices by nurses as they move through and out of the nursing workforce and of stated preferences to explore the specific job factors which influence these decisions. Specialised questions on detailed working conditions are needed as well as questions regarding household-related decisions.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>There is a severe shortage of nurses in Australia. Policy makers and researchers are especially concerned that retention levels of nurses in the health workforce have worsened over the last decade. There are also concerns that rapidly growing private sector hospitals are attracting qualified nurses away from the public sector. To date no systematic analysis of trends in nursing retention rates over time has been conducted due to the lack of consistent panel data.</p>", "<title>Results</title>", "<p>A 1.4 percentage point improvement in retention has led to a 10% increase in the overall supply of nurses in NSW. There has also been a substantial aging of the workforce, due to greater retention and an increase in mature age entrants. The improvement in retention is found in all types of premises and is largest in nursing homes. There is a substantial amount of year to year movement in and out of the workforce and across premises. The shortage of nurses in public hospitals is due to a slowdown in entry rather than competition from the rapidly growing private sector hospitals.</p>", "<title>Policy Implications</title>", "<p>The finding of an improvement (rather than a worsening) in retention suggests that additional improvements may be difficult to achieve as further retention must involve individuals more and more dissatisfied with nursing relative to other opportunities. Hence policies targeting entry such as increased places in nursing programs and additional subsidies for training costs may be more effective in dealing with the workforce shortage. This is also the case for shortages in public sector hospitals as retention in nursing is found to be relatively high in this sector. However, the large amount of year to year movements across nursing jobs, especially among the younger nurses, also suggests that policies aimed at reducing job switches and increasing the number who return to nursing should also be pursued. More research is needed in understanding the relative importance of detailed working conditions and the problems associated with combining family responsibilities and nursing jobs.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>DD and GJ designed the study and carried out the analyses. JH contributed to the conceptualisation and study design. All authors contributed to the development of the manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This research was supported by NHMRC Program Grant 245202 and the NSW Department of Health. The project was made possible by the NSW Nurses Registration Board and the Australian Institute of Health and Welfare who provided us with the data. We are especially indebted to Kathy Southgate for her help. We wish to thank colleagues at CHERE for very useful advice and comments especially Elizabeth Savage, Rosalie Viney and Marion Haas. Also, we gratefully acknowledge contributions from participants at presentations at the Econometric Society Australasian meetings, the Australian Health Economics Society and the International Health Economics Association meetings and two anonymous referees. Finally our special thanks to Gabrielle Beith for her insights into the nursing profession and to Joanne Yeoh for research assistance.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Trends in Total Female Employment and Nursing, NSW(1990 = 100)</bold>. Source: Profile of the Nursing Workforce, NSW Department of Health, various issues.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Retention Rates by Age Group, RNs</bold>. Source: Profile of the Nursing Workforce, NSW Department of Health, various issues.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Retention Rates by Age Group, Enrolled Nurses</bold>. Source: Profile of the Nursing Workforce, NSW Department of Health, various issues.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Average age and proportion of nurses in young age groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"4\"><bold>Total working nurses</bold></td><td align=\"center\" colspan=\"4\"><bold>RNs only</bold></td></tr><tr><td/><td colspan=\"4\"><hr/></td><td colspan=\"4\"><hr/></td></tr><tr><td align=\"center\"><bold>Year</bold></td><td align=\"center\"><bold>Number working</bold></td><td align=\"center\"><bold>Average age</bold></td><td align=\"center\"><bold>% aged &lt;25</bold></td><td align=\"center\"><bold>% aged 25–29</bold></td><td align=\"center\"><bold>Number working</bold></td><td align=\"center\"><bold>Average age</bold></td><td align=\"center\"><bold>% aged &lt;25</bold></td><td align=\"center\"><bold>% aged 25–29</bold></td></tr></thead><tbody><tr><td align=\"center\">1993</td><td align=\"center\">40762</td><td align=\"center\">38.75</td><td align=\"center\">6.76</td><td align=\"center\">12.30</td><td align=\"center\">33200</td><td align=\"center\">39.45</td><td align=\"center\">6.30</td><td align=\"center\">11.12</td></tr><tr><td align=\"center\">1994</td><td align=\"center\">47946</td><td align=\"center\">39.35</td><td align=\"center\">4.99</td><td align=\"center\">10.66</td><td align=\"center\">40296</td><td align=\"center\">40.01</td><td align=\"center\">4.19</td><td align=\"center\">9.51</td></tr><tr><td align=\"center\">1995</td><td align=\"center\">50793</td><td align=\"center\">39.72</td><td align=\"center\">5.17</td><td align=\"center\">10.62</td><td align=\"center\">43116</td><td align=\"center\">40.29</td><td align=\"center\">4.44</td><td align=\"center\">9.85</td></tr><tr><td align=\"center\">1996</td><td align=\"center\">51497</td><td align=\"center\">40.08</td><td align=\"center\">4.95</td><td align=\"center\">10.72</td><td align=\"center\">44025</td><td align=\"center\">40.62</td><td align=\"center\">4.39</td><td align=\"center\">10.16</td></tr><tr><td align=\"center\">1997</td><td align=\"center\">53076</td><td align=\"center\">40.38</td><td align=\"center\">5.02</td><td align=\"center\">10.51</td><td align=\"center\">44735</td><td align=\"center\">40.91</td><td align=\"center\">4.48</td><td align=\"center\">10.08</td></tr><tr><td align=\"center\">1998</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"center\">1999</td><td align=\"center\">53376</td><td align=\"center\">41.80</td><td align=\"center\">3.10</td><td align=\"center\">9.67</td><td align=\"center\">45100</td><td align=\"center\">42.25</td><td align=\"center\">2.76</td><td align=\"center\">9.34</td></tr><tr><td align=\"center\">2000</td><td align=\"center\">54648</td><td align=\"center\">42.16</td><td align=\"center\">2.86</td><td align=\"center\">9.63</td><td align=\"center\">46249</td><td align=\"center\">42.54</td><td align=\"center\">2.63</td><td align=\"center\">9.47</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Growth of the NSW nursing workforce by premises</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"2\"><bold>1994</bold></td><td align=\"center\" colspan=\"2\"><bold>2000</bold></td><td align=\"center\" colspan=\"3\"><bold>Growth 2000-1994</bold></td></tr><tr><td/><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\"><bold>Premises</bold></td><td align=\"right\"><bold>Number working</bold></td><td align=\"center\"><bold>Prop. private</bold></td><td align=\"right\"><bold>Number working</bold></td><td align=\"center\"><bold>Prop. private</bold></td><td align=\"center\"><bold>Public 00/94</bold></td><td align=\"center\"><bold>Private 00/94</bold></td><td align=\"center\"><bold>Total 00/94</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>All nurses</bold></td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">hospital</td><td align=\"right\">30332</td><td align=\"center\">0.16</td><td align=\"right\">34816</td><td align=\"center\">0.18</td><td align=\"center\">1.11</td><td align=\"center\">1.33</td><td align=\"center\">1.15</td></tr><tr><td align=\"left\">nursing homes</td><td align=\"right\">8428</td><td align=\"center\">0.62</td><td align=\"right\">8485</td><td align=\"center\">0.45</td><td align=\"center\">1.46</td><td align=\"center\">0.73</td><td align=\"center\">1.01</td></tr><tr><td align=\"left\">community health</td><td align=\"right\">3100</td><td align=\"center\">0.00</td><td align=\"right\">4744</td><td align=\"center\">0.07</td><td align=\"center\">1.42</td><td/><td align=\"center\">1.53</td></tr><tr><td align=\"left\">develop. disability service</td><td align=\"right\">1446</td><td align=\"center\">0.00</td><td align=\"right\">1548</td><td align=\"center\">0.04</td><td align=\"center\">1.03</td><td/><td align=\"center\">1.07</td></tr><tr><td align=\"left\">doctor's room</td><td align=\"right\">1224</td><td align=\"center\">1.00</td><td align=\"right\">1497</td><td align=\"center\">1.00</td><td/><td align=\"center\">1.22</td><td align=\"center\">1.22</td></tr><tr><td align=\"left\">private nursing practice</td><td align=\"right\">425</td><td align=\"center\">1.00</td><td align=\"right\">517</td><td align=\"center\">1.00</td><td/><td align=\"center\">1.22</td><td align=\"center\">1.22</td></tr><tr><td align=\"left\">Other</td><td align=\"right\">5534</td><td align=\"center\">0.42</td><td align=\"right\">3753</td><td align=\"center\">0.34</td><td align=\"center\">0.76</td><td align=\"center\">0.56</td><td align=\"center\">0.68</td></tr><tr><td align=\"left\">Total</td><td align=\"right\">50489</td><td align=\"center\">0.28</td><td align=\"right\">55360</td><td align=\"center\">0.25</td><td align=\"center\">1.14</td><td align=\"center\">1.00</td><td align=\"center\">1.10</td></tr><tr><td align=\"left\"><bold>RNs</bold></td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">hospital</td><td align=\"right\">25225</td><td align=\"center\">0.16</td><td align=\"right\">29195</td><td align=\"center\">0.19</td><td align=\"center\">1.11</td><td align=\"center\">1.40</td><td align=\"center\">1.16</td></tr><tr><td align=\"left\">nursing homes</td><td align=\"right\">5878</td><td align=\"center\">0.68</td><td align=\"right\">6225</td><td align=\"center\">0.48</td><td align=\"center\">1.70</td><td align=\"center\">0.75</td><td align=\"center\">1.06</td></tr><tr><td align=\"left\">community health</td><td align=\"right\">2914</td><td align=\"center\">0.00</td><td align=\"right\">4355</td><td align=\"center\">0.07</td><td align=\"center\">1.40</td><td/><td align=\"center\">1.50</td></tr><tr><td align=\"left\">develop. disability service</td><td align=\"right\">1052</td><td align=\"center\">0.00</td><td align=\"right\">1116</td><td align=\"center\">0.04</td><td align=\"center\">1.02</td><td/><td align=\"center\">1.06</td></tr><tr><td align=\"left\">doctor's room</td><td align=\"right\">1089</td><td align=\"center\">1.00</td><td align=\"right\">1329</td><td align=\"center\">1.00</td><td/><td align=\"center\">1.22</td><td align=\"center\">1.22</td></tr><tr><td align=\"left\">private nursing practice</td><td align=\"right\">388</td><td align=\"center\">1.00</td><td align=\"right\">431</td><td align=\"center\">1.00</td><td/><td align=\"center\">1.11</td><td align=\"center\">1.11</td></tr><tr><td align=\"left\">Other</td><td align=\"right\">4655</td><td align=\"center\">0.42</td><td align=\"right\">3170</td><td align=\"center\">0.34</td><td align=\"center\">0.77</td><td align=\"center\">0.55</td><td align=\"center\">0.68</td></tr><tr><td align=\"left\">Total</td><td align=\"right\">41201</td><td align=\"center\">0.28</td><td align=\"right\">45821</td><td align=\"center\">0.25</td><td align=\"center\">1.14</td><td align=\"center\">1.03</td><td align=\"center\">1.11</td></tr><tr><td align=\"left\"><bold>Enrolled</bold></td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">hospital</td><td align=\"right\">5107</td><td align=\"center\">0.17</td><td align=\"right\">5621</td><td align=\"center\">0.17</td><td align=\"center\">1.11</td><td align=\"center\">1.04</td><td align=\"center\">1.10</td></tr><tr><td align=\"left\">nursing homes</td><td align=\"right\">2550</td><td align=\"center\">0.50</td><td align=\"right\">2260</td><td align=\"center\">0.39</td><td align=\"center\">1.10</td><td align=\"center\">0.68</td><td align=\"center\">0.89</td></tr><tr><td align=\"left\">community health</td><td align=\"right\">186</td><td align=\"center\">0.00</td><td align=\"right\">389</td><td align=\"center\">0.11</td><td align=\"center\">1.86</td><td/><td align=\"center\">2.09</td></tr><tr><td align=\"left\">develop. disability service</td><td align=\"right\">394</td><td align=\"center\">0.00</td><td align=\"right\">432</td><td align=\"center\">0.04</td><td align=\"center\">1.06</td><td/><td align=\"center\">1.10</td></tr><tr><td align=\"left\">doctor's room</td><td align=\"right\">135</td><td align=\"center\">1.00</td><td align=\"right\">168</td><td align=\"center\">1.00</td><td/><td align=\"center\">1.24</td><td align=\"center\">1.24</td></tr><tr><td align=\"left\">private nursing practice</td><td align=\"right\">37</td><td align=\"center\">1.00</td><td align=\"right\">86</td><td align=\"center\">1.00</td><td/><td align=\"center\">2.32</td><td align=\"center\">2.32</td></tr><tr><td align=\"left\">Other</td><td align=\"right\">879</td><td align=\"center\">0.38</td><td align=\"right\">583</td><td align=\"center\">0.34</td><td align=\"center\">0.71</td><td align=\"center\">0.59</td><td align=\"center\">0.66</td></tr><tr><td align=\"left\">Total</td><td align=\"right\">9288</td><td align=\"center\">0.29</td><td align=\"right\">9539</td><td align=\"center\">0.24</td><td align=\"center\">1.09</td><td align=\"center\">0.86</td><td align=\"center\">1.03</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Annual retention rates by sector and type of premises (%)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\"><bold>1994–95</bold></td><td align=\"center\" colspan=\"3\"><bold>1999–2000</bold></td><td align=\"center\" colspan=\"3\"><bold>99-94 differences</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\"><bold>Premises</bold></td><td align=\"center\"><bold>Public</bold></td><td align=\"center\"><bold>Private</bold></td><td align=\"center\"><bold>Total</bold></td><td align=\"center\"><bold>Public</bold></td><td align=\"center\"><bold>Private</bold></td><td align=\"center\"><bold>Total</bold></td><td align=\"center\"><bold>Public</bold></td><td align=\"center\"><bold>Private</bold></td><td align=\"center\"><bold>Total</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>All nurses</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">hospital</td><td align=\"center\">83.8</td><td align=\"center\">81.9</td><td align=\"center\">83.5</td><td align=\"center\">84.6</td><td align=\"center\">83.9</td><td align=\"center\">84.5</td><td align=\"center\">0.8</td><td align=\"center\">2.0</td><td align=\"center\">1.0</td></tr><tr><td align=\"left\">nursing homes</td><td align=\"center\">80.9</td><td align=\"center\">83.5</td><td align=\"center\">82.5</td><td align=\"center\">84.4</td><td align=\"center\">85.7</td><td align=\"center\">85.0</td><td align=\"center\">3.6</td><td align=\"center\">2.2</td><td align=\"center\">2.5</td></tr><tr><td align=\"left\">all other premises</td><td align=\"center\">82.1</td><td align=\"center\">77.9</td><td align=\"center\">80.7</td><td align=\"center\">83.3</td><td align=\"center\">80.2</td><td align=\"center\">82.4</td><td align=\"center\">1.2</td><td align=\"center\">2.3</td><td align=\"center\">1.7</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">83.2</td><td align=\"center\">81.3</td><td align=\"center\">82.7</td><td align=\"center\">84.3</td><td align=\"center\">83.4</td><td align=\"center\">84.1</td><td align=\"center\">1.1</td><td align=\"center\">2.1</td><td align=\"center\">1.4</td></tr><tr><td align=\"left\"><bold>RNs</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">hospital</td><td align=\"center\">84.6</td><td align=\"center\">83.6</td><td align=\"center\">84.5</td><td align=\"center\">85.2</td><td align=\"center\">84.6</td><td align=\"center\">85.1</td><td align=\"center\">0.6</td><td align=\"center\">1.0</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">nursing homes</td><td align=\"center\">83.4</td><td align=\"center\">85.5</td><td align=\"center\">84.8</td><td align=\"center\">85.9</td><td align=\"center\">86.2</td><td align=\"center\">86.0</td><td align=\"center\">2.5</td><td align=\"center\">0.7</td><td align=\"center\">1.2</td></tr><tr><td align=\"left\">all other premises</td><td align=\"center\">83.3</td><td align=\"center\">79.2</td><td align=\"center\">81.9</td><td align=\"center\">84.2</td><td align=\"center\">81.6</td><td align=\"center\">83.5</td><td align=\"center\">0.9</td><td align=\"center\">2.4</td><td align=\"center\">1.6</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">84.3</td><td align=\"center\">82.9</td><td align=\"center\">83.9</td><td align=\"center\">85.1</td><td align=\"center\">84.2</td><td align=\"center\">84.9</td><td align=\"center\">0.8</td><td align=\"center\">1.3</td><td align=\"center\">1.0</td></tr><tr><td align=\"left\"><bold>Enrolled</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">hospital</td><td align=\"center\">79.5</td><td align=\"center\">74.0</td><td align=\"center\">78.6</td><td align=\"center\">81.3</td><td align=\"center\">79.5</td><td align=\"center\">81.0</td><td align=\"center\">1.8</td><td align=\"center\">5.5</td><td align=\"center\">2.5</td></tr><tr><td align=\"left\">nursing homes</td><td align=\"center\">76.9</td><td align=\"center\">76.8</td><td align=\"center\">76.9</td><td align=\"center\">81.0</td><td align=\"center\">83.8</td><td align=\"center\">82.0</td><td align=\"center\">4.0</td><td align=\"center\">7.0</td><td align=\"center\">5.1</td></tr><tr><td align=\"left\">all other premises</td><td align=\"center\">74.7</td><td align=\"center\">69.2</td><td align=\"center\">72.9</td><td align=\"center\">77.9</td><td align=\"center\">72.3</td><td align=\"center\">76.2</td><td align=\"center\">3.2</td><td align=\"center\">3.1</td><td align=\"center\">3.3</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">78.2</td><td align=\"center\">74.4</td><td align=\"center\">77.1</td><td align=\"center\">80.7</td><td align=\"center\">79.3</td><td align=\"center\">80.4</td><td align=\"center\">2.5</td><td align=\"center\">4.9</td><td align=\"center\">3.3</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Decomposition of changes in retention rates over time</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\"><bold>RNs</bold></td><td align=\"center\" colspan=\"3\"><bold>Enrolled</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>1999</bold></td><td align=\"center\"><bold>1994</bold></td><td align=\"center\"><bold>Differ</bold>.</td><td align=\"center\"><bold>1999</bold></td><td align=\"center\"><bold>1994</bold></td><td align=\"center\"><bold>Differ</bold>.</td></tr></thead><tbody><tr><td align=\"left\">Sample Size</td><td align=\"center\">45084</td><td align=\"center\">41386</td><td/><td align=\"center\">9374</td><td align=\"center\">9095</td><td/></tr><tr><td align=\"left\">Observed mean retention probability</td><td align=\"center\">0.849</td><td align=\"center\">0.839</td><td align=\"center\">0.010</td><td align=\"center\">0.804</td><td align=\"center\">0.771</td><td align=\"center\">0.033</td></tr><tr><td align=\"left\">Predicted mean retention probability</td><td align=\"center\">0.849</td><td align=\"center\">0.839</td><td align=\"center\">0.010</td><td align=\"center\">0.804</td><td align=\"center\">0.771</td><td align=\"center\">0.033</td></tr><tr><td align=\"left\">Probability at mean characteristics:</td><td align=\"center\">0.857</td><td align=\"center\">0.848</td><td align=\"center\">0.009</td><td align=\"center\">0.813</td><td align=\"center\">0.781</td><td align=\"center\">0.031</td></tr><tr><td align=\"left\">Overall decomposition:</td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\" colspan=\"3\"> Contribution from differences in coefficients</td><td align=\"center\">0.006</td><td/><td/><td align=\"center\">0.030</td></tr><tr><td align=\"left\" colspan=\"3\"> Contribution from differences in mean characteristics</td><td align=\"center\">0.004</td><td/><td/><td align=\"center\">0.001</td></tr><tr><td align=\"left\">Total</td><td/><td/><td align=\"center\">0.009</td><td/><td/><td align=\"center\">0.031</td></tr><tr><td align=\"left\" colspan=\"3\">Contribution from individual characteristics:</td><td/><td/><td/><td/></tr><tr><td align=\"left\" colspan=\"3\"> Personal characteristics (age, citizenship, sex)</td><td align=\"center\">0.002</td><td/><td/><td align=\"center\">0.012</td></tr><tr><td align=\"left\" colspan=\"3\"> Human capital (post basic qualification, years registered)</td><td align=\"center\">0.005</td><td/><td/><td align=\"center\">0.005</td></tr><tr><td align=\"left\" colspan=\"3\"> Location of job (region, unemployment rates)</td><td align=\"center\">-0.003</td><td/><td/><td align=\"center\">-0.003</td></tr><tr><td align=\"left\" colspan=\"3\"> Hours of work (hours in main job, second job as nurse)</td><td align=\"center\">0.003</td><td/><td/><td align=\"center\">-0.001</td></tr><tr><td align=\"left\" colspan=\"3\"> Job characteristics (classification, field, activity, premises)</td><td align=\"center\">-0.004</td><td/><td/><td align=\"center\">-0.012</td></tr><tr><td align=\"left\">Total</td><td/><td/><td align=\"center\">0.004</td><td/><td/><td align=\"center\">0.001</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\" colspan=\"7\"><bold>Characteristics whose coefficients changed significantly between 1994 and 1999:</bold></td></tr><tr><td align=\"left\" colspan=\"7\">RNs: sex, hours in main job, job classification, field and activity.</td></tr><tr><td align=\"left\" colspan=\"7\">Enrolled: post-basic qualification and field</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Working history of cohorts of RNs, distribution by sector (%)</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td/><td align=\"center\" colspan=\"7\"><bold>Cohort 1: 21 – 23 years old in 1994 (aged 27 – 29 in 2000)</bold></td></tr><tr><td/><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\"><bold>Sector</bold></td><td align=\"right\"><bold>1994</bold></td><td align=\"right\"><bold>1995</bold></td><td align=\"right\"><bold>1996</bold></td><td align=\"right\"><bold>1997</bold></td><td align=\"right\"><bold>1998</bold></td><td align=\"right\"><bold>1999</bold></td><td align=\"right\"><bold>2000</bold></td></tr><tr><td align=\"left\">Public hospital</td><td align=\"right\">71</td><td align=\"right\">54</td><td align=\"right\">47</td><td align=\"right\">41</td><td/><td align=\"right\">40</td><td align=\"right\">43</td></tr><tr><td align=\"left\">Private hospital</td><td align=\"right\">7</td><td align=\"right\">6</td><td align=\"right\">6</td><td align=\"right\">7</td><td/><td align=\"right\">7</td><td align=\"right\">8</td></tr><tr><td align=\"left\">Public other</td><td align=\"right\">11</td><td align=\"right\">4</td><td align=\"right\">4</td><td align=\"right\">5</td><td/><td align=\"right\">5</td><td align=\"right\">6</td></tr><tr><td align=\"left\">Private other</td><td align=\"right\">10</td><td align=\"right\">6</td><td align=\"right\">5</td><td align=\"right\">4</td><td/><td align=\"right\">4</td><td align=\"right\">5</td></tr><tr><td align=\"left\">Missing premises</td><td align=\"right\">1</td><td align=\"right\">1</td><td align=\"right\">2</td><td align=\"right\">1</td><td/><td align=\"right\">1</td><td align=\"right\">1</td></tr><tr><td align=\"left\">Not working</td><td/><td align=\"right\">29</td><td align=\"right\">36</td><td align=\"right\">43</td><td/><td align=\"right\">43</td><td align=\"right\">37</td></tr><tr><td align=\"left\">Total</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">100</td><td/><td align=\"right\">100</td><td align=\"right\">100</td></tr><tr><td align=\"left\">No. observations</td><td align=\"right\">1059</td><td align=\"right\">1059</td><td align=\"right\">1059</td><td align=\"right\">1059</td><td/><td align=\"right\">1059</td><td align=\"right\">1059</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"center\" colspan=\"7\"><bold>Cohort 2: 21 – 23 years old in 1997 (aged 24 – 26 in 2000)</bold></td></tr><tr><td/><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\"><bold>Sector</bold></td><td align=\"right\"><bold>1997</bold></td><td align=\"right\"><bold>1998</bold></td><td align=\"right\"><bold>1999</bold></td><td align=\"right\"><bold>2000</bold></td><td/><td/><td/></tr><tr><td align=\"left\">Public hospital</td><td align=\"right\">80</td><td/><td align=\"right\">54</td><td align=\"right\">52</td><td/><td/><td/></tr><tr><td align=\"left\">Private hospital</td><td align=\"right\">11</td><td/><td align=\"right\">8</td><td align=\"right\">8</td><td/><td/><td/></tr><tr><td align=\"left\">Public other</td><td align=\"right\">5</td><td/><td align=\"right\">4</td><td align=\"right\">5</td><td/><td/><td/></tr><tr><td align=\"left\">Private other</td><td align=\"right\">3</td><td/><td align=\"right\">2</td><td align=\"right\">2</td><td/><td/><td/></tr><tr><td align=\"left\">Missing premises</td><td align=\"right\">1</td><td/><td align=\"right\">1</td><td align=\"right\">1</td><td/><td/><td/></tr><tr><td align=\"left\">Not working</td><td/><td/><td align=\"right\">31</td><td align=\"right\">32</td><td/><td/><td/></tr><tr><td align=\"left\">Total</td><td align=\"right\">100</td><td/><td align=\"right\">100</td><td align=\"right\">100</td><td/><td/><td/></tr><tr><td align=\"left\">No. observations</td><td align=\"right\">1270</td><td/><td align=\"right\">1270</td><td align=\"right\">1270</td><td/><td/><td/></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"center\" colspan=\"7\"><bold>Cohort 3: 41 – 43 years old in 1994 (aged 47 – 49 in 2000)</bold></td></tr><tr><td/><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\"><bold>Sector</bold></td><td align=\"right\"><bold>1994</bold></td><td align=\"right\"><bold>1995</bold></td><td align=\"right\"><bold>1996</bold></td><td align=\"right\"><bold>1997</bold></td><td align=\"right\"><bold>1998</bold></td><td align=\"right\"><bold>1999</bold></td><td align=\"right\"><bold>2000</bold></td></tr><tr><td align=\"left\">Public hospital</td><td align=\"right\">47</td><td align=\"right\">40</td><td align=\"right\">38</td><td align=\"right\">39</td><td/><td align=\"right\">37</td><td align=\"right\">36</td></tr><tr><td align=\"left\">Private hospital</td><td align=\"right\">9</td><td align=\"right\">9</td><td align=\"right\">9</td><td align=\"right\">8</td><td/><td align=\"right\">8</td><td align=\"right\">8</td></tr><tr><td align=\"left\">Public other</td><td align=\"right\">24</td><td align=\"right\">19</td><td align=\"right\">19</td><td align=\"right\">21</td><td/><td align=\"right\">21</td><td align=\"right\">21</td></tr><tr><td align=\"left\">Private other</td><td align=\"right\">19</td><td align=\"right\">17</td><td align=\"right\">14</td><td align=\"right\">12</td><td/><td align=\"right\">11</td><td align=\"right\">12</td></tr><tr><td align=\"left\">Missing premises</td><td align=\"right\">1</td><td align=\"right\">3</td><td align=\"right\">4</td><td align=\"right\">2</td><td/><td align=\"right\">2</td><td align=\"right\">2</td></tr><tr><td align=\"left\">Not working</td><td/><td align=\"right\">12</td><td align=\"right\">16</td><td align=\"right\">18</td><td/><td align=\"right\">21</td><td align=\"right\">21</td></tr><tr><td align=\"left\">Total</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">100</td><td/><td align=\"right\">100</td><td align=\"right\">100</td></tr><tr><td align=\"left\">No. observations</td><td align=\"right\">4221</td><td align=\"right\">4221</td><td align=\"right\">4221</td><td align=\"right\">4221</td><td/><td align=\"right\">4221</td><td align=\"right\">4221</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"center\" colspan=\"7\"><bold>Cohort 4: 41 – 43 years old in 1997 (aged 44 – 46 in 2000)</bold></td></tr><tr><td/><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\"><bold>Sector</bold></td><td align=\"right\"><bold>1997</bold></td><td align=\"right\"><bold>1998</bold></td><td align=\"right\"><bold>1999</bold></td><td align=\"right\"><bold>2000</bold></td><td/><td/><td/></tr><tr><td align=\"left\">Public hospital</td><td align=\"right\">49</td><td/><td align=\"right\">42</td><td align=\"right\">40</td><td/><td/><td/></tr><tr><td align=\"left\">Private hospital</td><td align=\"right\">11</td><td/><td align=\"right\">10</td><td align=\"right\">10</td><td/><td/><td/></tr><tr><td align=\"left\">Public other</td><td align=\"right\">22</td><td/><td align=\"right\">21</td><td align=\"right\">21</td><td/><td/><td/></tr><tr><td align=\"left\">Private other</td><td align=\"right\">15</td><td/><td align=\"right\">12</td><td align=\"right\">12</td><td/><td/><td/></tr><tr><td align=\"left\">Missing premises</td><td align=\"right\">3</td><td/><td align=\"right\">2</td><td align=\"right\">2</td><td/><td/><td/></tr><tr><td align=\"left\">Not working</td><td/><td/><td align=\"right\">13</td><td align=\"right\">15</td><td/><td/><td/></tr><tr><td align=\"left\">Total</td><td align=\"right\">100</td><td/><td align=\"right\">100</td><td align=\"right\">100</td><td/><td/><td/></tr><tr><td align=\"left\">No. observations</td><td align=\"right\">5232</td><td/><td align=\"right\">5232</td><td align=\"right\">5232</td><td/><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>1999–2000 transition frequencies for two cohorts of RNs (%)</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td/><td align=\"center\" colspan=\"8\"><bold>Sector in 1999</bold></td></tr><tr><td/><td align=\"center\" colspan=\"8\"><bold>Cohort 1: 21 – 23 years old in 1994 (aged 27 – 29 in 2000)</bold></td></tr><tr><td/><td colspan=\"8\"><hr/></td></tr><tr><td align=\"left\"><bold>Sector in 2000</bold></td><td align=\"center\"><bold>No. obs</bold>.</td><td align=\"center\"><bold>Public hospital</bold></td><td align=\"center\"><bold>Private hospital</bold></td><td align=\"center\"><bold>Public other</bold></td><td align=\"center\"><bold>Private other</bold></td><td align=\"center\"><bold>Missing premises</bold></td><td align=\"center\"><bold>Not working</bold></td><td align=\"center\"><bold>Total</bold></td></tr><tr><td align=\"left\">Public hospital</td><td align=\"center\">452</td><td align=\"center\">75</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">22</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Private hospital</td><td align=\"center\">83</td><td align=\"center\">10</td><td align=\"center\">62</td><td align=\"center\">1</td><td align=\"center\">4</td><td align=\"center\">0</td><td align=\"center\">23</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Public other</td><td align=\"center\">65</td><td align=\"center\">12</td><td align=\"center\">3</td><td align=\"center\">52</td><td align=\"center\">8</td><td align=\"center\">2</td><td align=\"center\">23</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Private other</td><td align=\"center\">50</td><td align=\"center\">12</td><td align=\"center\">4</td><td align=\"center\">4</td><td align=\"center\">56</td><td align=\"center\">4</td><td align=\"center\">20</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Missing premises</td><td align=\"center\">11</td><td align=\"center\">18</td><td align=\"center\">18</td><td align=\"center\">0</td><td align=\"center\">10</td><td align=\"center\">18</td><td align=\"center\">36</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Not working</td><td align=\"center\">398</td><td align=\"center\">15</td><td align=\"center\">3</td><td align=\"center\">3</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">76</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">1059</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"center\" colspan=\"8\"><bold>Cohort 3: 41 – 43 years old in 1997 (aged 44 – 47 in 2000)</bold></td></tr><tr><td/><td colspan=\"8\"><hr/></td></tr><tr><td align=\"left\"><bold>Sector in 2000</bold></td><td align=\"center\"><bold>No. obs</bold>.</td><td align=\"center\"><bold>Public hospital</bold></td><td align=\"center\"><bold>Private hospital</bold></td><td align=\"center\"><bold>Public other</bold></td><td align=\"center\"><bold>Private other</bold></td><td align=\"center\"><bold>Missing premises</bold></td><td align=\"center\"><bold>Not working</bold></td><td align=\"center\"><bold>Total</bold></td></tr><tr><td align=\"left\">Public hospital</td><td align=\"center\">2088</td><td align=\"center\">89</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">6</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Private hospital</td><td align=\"center\">510</td><td align=\"center\">8</td><td align=\"center\">78</td><td align=\"center\">3</td><td align=\"center\">4</td><td align=\"center\">1</td><td align=\"center\">6</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Public other</td><td align=\"center\">1092</td><td align=\"center\">8</td><td align=\"center\">1</td><td align=\"center\">70</td><td align=\"center\">12</td><td align=\"center\">1</td><td align=\"center\">8</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Private other</td><td align=\"center\">619</td><td align=\"center\">2</td><td align=\"center\">3</td><td align=\"center\">22</td><td align=\"center\">64</td><td align=\"center\">3</td><td align=\"center\">6</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Missing premises</td><td align=\"center\">124</td><td align=\"center\">15</td><td align=\"center\">2</td><td align=\"center\">26</td><td align=\"center\">19</td><td align=\"center\">22</td><td align=\"center\">16</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Not working</td><td align=\"center\">799</td><td align=\"center\">24</td><td align=\"center\">6</td><td align=\"center\">14</td><td align=\"center\">8</td><td align=\"center\">3</td><td align=\"center\">45</td><td align=\"center\">100</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">5232</td><td/><td/><td/><td/><td/><td/><td/></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Notes: The samples exclude nurses who do not report their age; this group forms less than 5% of the sample.</p></table-wrap-foot>", "<table-wrap-foot><p>Notes: Observations with missing premises are excluded. RNs working as enrolled nurses are included in the enrolled. Nursing homes include hostels and hospices. The other category includes: schools, day procedures, various companies, prisons and the defense forces.</p></table-wrap-foot>", "<table-wrap-foot><p>Notes: The retention rate is conditional on working as a nurse in NSW in the base years (1994 or 1999). Nurses working in the base year are defined as retained if they are still employed as a nurse in NSW in the following year. Nursing homes include hostels and hospices.</p></table-wrap-foot>", "<table-wrap-foot><p>Notes: Separate probits are estimated for 1999 and 1994 and for RNs and enrolled nurses. In both years the same explanatory variables are used and differences in the predicted retention probability is decomposed using a first order Taylor-series expansion.</p></table-wrap-foot>", "<table-wrap-foot><p>Notes: Four cohorts of working RNs in specified age groups and years are followed over time. The columns indicate the percentage distribution of the cohorts according to their work status and premises.</p></table-wrap-foot>", "<table-wrap-foot><p>Notes: These cohorts correspond to cohorts 1 and 3 from Table 5. The frequencies are in percentages and represent the distributions across the premises in 1999. For example, of the cohort 1 RNs working in public hospitals in 2000 (452 nurses), 75% were working in public hospitals in 1999, 22% were not working, 2% were working in private hospitals and so on.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1743-8462-5-19-1\"/>", "<graphic xlink:href=\"1743-8462-5-19-2\"/>", "<graphic xlink:href=\"1743-8462-5-19-3\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Metformin-induced hemolytic anemia has been reported in three patients, all of whom recovered when metformin was discontinued [##REF##9725923##1##, ####REF##10644400##2##, ##REF##12610074##3####12610074##3##]. We report the case of a patient with fulminant and fatal hemolysis that occurred shortly after metformin was started for the treatment of type 2 diabetes mellitus.</p>" ]

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[ "<title>Discussion</title>", "<p>The temporal relationship with metformin ingestion is strong in this case, with the patient noting symptoms within hours of the initiation of metformin. The 4-day course was rapid and fatal, characterized by massive hemolysis and shock. In the three previously reported cases of metformin-induced hemolytic anemia (Table ##TAB##1##2##), the time to onset of symptoms ranged from 9 to 14 days after starting metformin, and none resulted in massive hemolysis or death. Glucose-6-phosphate dehydrogenase (G6PD) levels and the results of the DAT were variable. In two of the three cases the hemolysis recurred with metformin rechallenge, which increases the likelihood of a causal relationship according to the Naranjo adverse drug reaction probability scale [##REF##7249508##4##].</p>", "<p>Other possible causes of fulminant hemolysis must be considered in this patient. The lack of schistocytes makes micro-angiopathic processes such as thrombotic thrombocytopenic purpura (TTP) or disseminated intravascular coagulation less likely. In addition, the absence of fever and the patient's normal platelet count reduce the likelihood of TTP. There are several case reports of ciprofloxacin-induced hemolysis [##REF##12911170##5##], but our patient had already developed anemia and hemoglobinuria suggestive of ongoing hemolysis before being started on ciprofloxacin in the emergency room. Another possibility is Evans syndrome, which is a DAT-positive hemolytic anemia and immune thrombocytopenia with no known underlying etiology. Evans syndrome causes chronic hemolytic anemia, which our patient did not have, and it is rarely fulminant. A third possibility is hemolytic anemia associated with acute hepatitis, most commonly hepatitis A, which has been described as a cause of fulminant and sometimes fatal hemolysis in patients with G6PD deficiency [##REF##11319332##6##,##REF##1111716##7##]. As hepatitis serologies and G6PD levels are not available for this patient, it is impossible to rule out acute hepatitis as the underlying cause of the hemolysis. However, at an office visit 4 days prior to admission, this patient had no prodromal signs or symptoms of hepatitis, and nothing in his travel or dietary history was suggestive of a risk for hepatitis A. In addition, hemolysis can cause a significant increase in AST and a more moderate increase in ALT owing to the release of these transaminases from the lysed RBCs [##REF##11106349##8##]. As there is more AST than ALT in RBCs, a high AST-to-ALT ratio would be expected in a case of hemolysis-induced transaminitis. The presence a high AST-to-ALT ratio in this case suggests that massive hemolysis could account for all of the transaminase abnormalities.</p>", "<p>The predictive value of a positive DAT for an immune etiology in a patient with hemolytic anemia is 83% [##UREF##0##9##]. DAT reactivity in our patient was 4+ to polyspecific, 4+ to IgG and negative to C3. The patient's serum reacted with all reagent RBCs tested by the indirect antiglobulin test. Adsorption of aliquots of serum with ZZAP-treated autologous RBCs failed to remove all reactivity (ZZAP is a papain and dithiothreitol reagent used to clear autoantibody from the patient's serum). Adsorption of aliquots of the patient's serum with R1R1, R2R2, and RBC samples revealed the presence of an autoantibody with 'e-like' specificity in the adsorbed serum. Serum antibody reactivity was consistent with a warm autoantibody (panagglutinin) and an antibody with 'e-like' specificity at anti-human globulin. These results could be consistent with either a warm autoimmune hemolytic anemia (WAIHA) or a drug-induced immune hemolytic anemia (DIIHA) with autoantibody formation (alpha-methyldopa type), which could explain the persistence of hemolysis in this case despite the discontinuation of metformin. Unlike DIIHAs involving neoantigen (immune complex) formation or drug adsorption onto the RBCs, hemolysis owing to drug-induced autoantibodies can persist for several days to months after the drug is stopped. The presence of an autoantibody directed to the Rh system ('e-like' specificity) can occur with WAIHA but is more commonly seen with DIIHA [##REF##11921020##10##]. The strength of the DAT reactivity does not necessarily argue for a warm autoantibody; Joshua et al. have shown that the DAT is strongly positive (at least 2+) in 75% of patients with drug-associated hemolysis [##REF##17381629##11##].</p>", "<p>The possible mechanism of metformin-induced hemolytic anemia discussed here is different from that proposed by Kashyap and Kashyap in their report [##REF##10644400##2##]. Their patient's DAT was positive for anti-C3 and negative for anti-IgG, which suggests the formation of an antibody against the erythrocyte-drug complex. In contrast, our patient's DAT was consistent with autoantibody formation. This is not necessarily a contradiction, since it has been shown that the same drug can cause many if not all of the mechanisms of DIIHA. In fact, one mechanism may simply be more pronounced and identifiable in a particular patient. Observations of DIIHA caused by third-generation cephalosporins support the notion of multiple mechanisms for the same drug [##UREF##1##12##].</p>", "<p>Unfortunately, stored samples of this patient's blood are not available to test for drug-dependent antibodies. Ultimately, we cannot be certain whether this patient had WAIHA or drug-induced hemolysis caused by an autoantibody. If he did have WAIHA, we are unable to find any clear precipitating cause for his catastrophic hemolysis other than the initiation of metformin.</p>" ]

[ "<title>Conclusion</title>", "<p>This patient developed fulminant and fatal Coombs-positive hemolytic anemia that was temporally related to the initiation of metformin treatment, in the absence of any other likely cause. The Naranjo probability score is 3 ('possible') for a metformin drug reaction, but in view of the fatal outcome we think it is important to make clinicians aware of the possibility of rare but severe hemolysis with metformin treatment.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Metformin is a widely prescribed biguanide antidiabetic drug that has been implicated as a cause of hemolytic anemia in three previous case reports. We report a case of rapidly fatal hemolysis that was temporally associated with the initiation of metformin treatment for diabetes. Clinicians need to be aware of this rare but potentially serious side effect of metformin.</p>", "<title>Case presentation</title>", "<p>A 56-year-old Caucasian man with type 2 diabetes mellitus was started on metformin to improve glycemic control. Shortly afterwards, he developed progressive fatigue, exertional dyspnea, cranberry-colored urine and jaundice. Laboratory studies showed severe hemolysis, with a drop in hemoglobin from 14.7 to 6.6 g/dl over 4 days, markedly elevated lactate dehydrogenase, bilirubin and reticulocyte counts, and a low haptoglobin level. A peripheral blood smear showed no schistocytes, and a direct Coombs test was positive for anti-IgG and negative for anti-C3. Despite corticosteroid treatment and transfusion of packed red blood cells, the patient developed increasing dyspnea, hypotension, further decline in hemoglobin to 3.3 g/dl, and fatal cardiorespiratory arrest 12 hours after admission.</p>", "<title>Conclusion</title>", "<p>The serologic findings in this case suggest an autoimmune hemolytic anemia, caused either by a drug-induced autoantibody or a warm autoantibody. Based on the temporal association with metformin and the lack of other clear precipitating causes, we propose that metformin-induced hemolysis with a drug-induced autoantibody is a strong possibility. This mechanism differs from a previously described case with a possible antibody to the erythrocyte-drug complex. It has been shown, however, that hemolysis may occur via multiple mechanisms from the same drug. Clinicians should consider the possibility of metformin-associated immune hemolytic anemia in patients with otherwise unexplained hemolysis.</p>" ]

[ "<title>Case presentation</title>", "<p>A 56-year-old Caucasian man with type 2 diabetes mellitus, hypothyroidism, idiopathic thrombocytopenic purpura status post splenectomy in 1979, and remote testicular cancer status post orchiectomy and radiation therapy in the 1970s was admitted with 2 days of progressive fatigue, exertional dyspnea, low back pain and cranberry-colored urine. He had been started on metformin 500 mg twice a day 4 days previously for type 2 diabetes but called in to his physician the following day with complaints of \"palpitation, heavy breathing, and tossing and turning last night\" after taking the metformin, which he declined to continue. Two days before admission he was seen at an outside emergency room with hematuria and anemia; he was diagnosed with a urinary tract infection and started on oral ciprofloxacin. His other medications were pantoprazole, levothyroxine and glyburide. On the day of admission, vital signs were temperature 37.1°C, pulse rate of 133 per minute, respiration rate of 32 breaths per minute, blood pressure of 155/84 and pulse oxygen 94% on 6 liters O₂. Physical examination was significant for respiratory distress, scleral icterus and generalized jaundice. There was no jugular venous distention and no enlarged thyroid gland or lymphadenopathy. His lungs were clear, heart sounds were distant, his abdomen was soft without masses or enlargement of organs, he had no rashes and no peripheral edema. Mild lumbar and thoracic spinous tenderness was noted; neurological examination revealed mild lethargy but otherwise normal mental status, with no focal findings. Laboratory studies (Table ##TAB##0##1##) were significant for hemoglobin of 6.6 g/dl, which had dropped from 14.7 g/dl 4 days before, total bilirubin 6.6 mg/dl (direct 2.7 mg/dl), reticulocyte count 3.51%, lactate dehydrogenase 4829 U/l, and haptoglobin less than 6 mg/dl, all consistent with severe hemolysis. The direct antiglobulin (Coombs) test (DAT) was positive for anti-IgG and negative for anti-C3. The peripheral blood smear on admission significantly showed no schistocytes; 4% immature granulocytes and 4% nucleated red blood cells (RBCs) were noted. Other significant findings included marked leukocytosis to 46.1 K/cmm, acute renal failure, elevation of troponin-I and marked transaminase elevations (aspartate aminotransferase (AST) 1711, alanine aminotransferase (ALT) 806) with normal international normalized ratio and alkaline phosphatase. Blood and urine cultures showed no growth. Despite treatment with corticosteroids and transfusion of packed RBCs, the patient became increasingly dyspneic and agitated, complained of abdominal pain and developed hypotension followed by cardiorespiratory arrest approximately 8 hours after admission. Over the next 4 hours he was treated following the advanced cardiac life support protocol for recurrent bouts of pulseless electrical activity and asystole, with worsening hyperkalemia and metabolic acidosis. Despite transfusion, hemoglobin was noted to have declined to 3.3 g/dl. The patient died approximately 12 hours after admission.</p>", "<title>Abbreviations</title>", "<p>ALT: alanine aminotransferase; AST: aspartate aminotransferase; DAT: direct antiglobulin test; DIIHA: drug-induced immune hemolytic anemia; G6PD: glucose-6-phosphate dehydrogenase; RBC: red blood cell; TTP: thrombotic thrombocytopenic purpura; WAIHA: warm autoimmune hemolytic anemia.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>CDP researched the case, analyzed the laboratory data and was chief author of the manuscript. TRH assisted with the analysis of the data, helped substantially with the discussion and contributed to the manuscript. SAA cared for the patient, assisted with the details of the case report, helped with the discussion and assisted in revising the manuscript. All authors read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient's next-of-kin for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors wish to thank Dr Suja Subramanyan for her help in procuring and interpreting the blood bank serology data of this patient.</p>" ]

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[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Laboratory test results</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Variable</td><td align=\"left\">11/21/2006</td><td align=\"left\">11/20/2006</td><td align=\"left\">11/16/2006</td><td align=\"left\">9/21/2006</td><td align=\"left\">Units</td></tr></thead><tbody><tr><td align=\"left\">Hemoglobin</td><td align=\"left\">3.3</td><td align=\"left\">6.6</td><td align=\"left\">14.7</td><td align=\"left\">-</td><td align=\"left\">g/dl</td></tr><tr><td align=\"left\">Hematocrit</td><td align=\"left\">10.2</td><td align=\"left\">19.5</td><td align=\"left\">43.3</td><td align=\"left\">-</td><td align=\"left\">%</td></tr><tr><td align=\"left\">Platelet</td><td align=\"left\">97</td><td align=\"left\">166</td><td align=\"left\">322</td><td align=\"left\">-</td><td align=\"left\">K/cmm</td></tr><tr><td align=\"left\">White blood cell</td><td align=\"left\">44.0</td><td align=\"left\">46.1</td><td align=\"left\">11.5</td><td align=\"left\">-</td><td align=\"left\">K/cmm</td></tr><tr><td align=\"left\">Glucose</td><td align=\"left\">-</td><td align=\"left\">277</td><td align=\"left\">-</td><td align=\"left\">220</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Blood urea nitrogen</td><td align=\"left\">-</td><td align=\"left\">38</td><td align=\"left\">-</td><td align=\"left\">22</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Creatinine</td><td align=\"left\">-</td><td align=\"left\">2.4</td><td align=\"left\">-</td><td align=\"left\">1.1</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Sodium</td><td align=\"left\">-</td><td align=\"left\">129</td><td align=\"left\">-</td><td align=\"left\">140</td><td align=\"left\">meq/l</td></tr><tr><td align=\"left\">Potassium</td><td align=\"left\">-</td><td align=\"left\">5.5</td><td align=\"left\">-</td><td align=\"left\">4.5</td><td align=\"left\">meq/l</td></tr><tr><td align=\"left\">Chloride</td><td align=\"left\">-</td><td align=\"left\">94</td><td align=\"left\">-</td><td align=\"left\">104</td><td align=\"left\">meq/l</td></tr><tr><td align=\"left\">CO₂</td><td align=\"left\">-</td><td align=\"left\">15</td><td align=\"left\">-</td><td align=\"left\">27</td><td align=\"left\">mmol/l</td></tr><tr><td align=\"left\">Calcium</td><td align=\"left\">-</td><td align=\"left\">8.7</td><td align=\"left\">-</td><td align=\"left\">9.2</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Lactate dehydrogenase</td><td align=\"left\">-</td><td align=\"left\">4829</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">U/l</td></tr><tr><td align=\"left\">Haptoglobin</td><td align=\"left\">-</td><td align=\"left\">&lt;6</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Fibrinogen</td><td align=\"left\">-</td><td align=\"left\">253</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Total bilirubin</td><td align=\"left\">-</td><td align=\"left\">6.9</td><td align=\"left\">-</td><td align=\"left\">0.8</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Direct bilirubin</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">0.1</td><td align=\"left\">mg/dl</td></tr><tr><td align=\"left\">Alkaline phosphatase</td><td align=\"left\">-</td><td align=\"left\">103</td><td align=\"left\">-</td><td align=\"left\">83</td><td align=\"left\">U/l</td></tr><tr><td align=\"left\">Alanine aminotransferase</td><td align=\"left\">-</td><td align=\"left\">806</td><td align=\"left\">-</td><td align=\"left\">38</td><td align=\"left\">U/l</td></tr><tr><td align=\"left\">Aspartate aminotransferase</td><td align=\"left\">-</td><td align=\"left\">1711</td><td align=\"left\">-</td><td align=\"left\">31</td><td align=\"left\">U/l</td></tr><tr><td align=\"left\">Creatine phosphokinase</td><td align=\"left\">-</td><td align=\"left\">597</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">U/l</td></tr><tr><td align=\"left\">Partial thromboplastin time</td><td align=\"left\">-</td><td align=\"left\">26.7</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">seconds</td></tr><tr><td align=\"left\">International normalized ratio</td><td align=\"left\">-</td><td align=\"left\">1.22</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">-</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Reported cases of metformin-induced hemolytic anemia</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Case report</td><td align=\"left\">Patient's age (years)</td><td align=\"left\">Gender</td><td align=\"left\">Time from starting metformin to onset of symptoms</td><td align=\"left\">Direct Coombs</td><td align=\"left\">G6PD level</td><td align=\"left\">Recurrence of hemolysis with metformin rechallenge</td><td align=\"left\">Outcome</td></tr></thead><tbody><tr><td align=\"left\">Lin et al. [##REF##9725923##1##]</td><td align=\"left\">46</td><td align=\"left\">Male</td><td align=\"left\">10 days</td><td align=\"left\">'Equivocal'</td><td align=\"left\">Normal</td><td align=\"left\">Yes</td><td align=\"left\">Recovery</td></tr><tr><td align=\"left\">Kashyap and Kashyap [##REF##10644400##2##]</td><td align=\"left\">51</td><td align=\"left\">Female</td><td align=\"left\">9 days</td><td align=\"left\">Positive (-IgG, +C3)</td><td align=\"left\">Normal</td><td align=\"left\">Yes</td><td align=\"left\">Recovery</td></tr><tr><td align=\"left\">Meir et al. [##REF##12610074##3##]</td><td align=\"left\">68</td><td align=\"left\">Female</td><td align=\"left\">14 days</td><td align=\"left\">Negative</td><td align=\"left\">Decreased</td><td align=\"left\">N/A</td><td align=\"left\">Recovery</td></tr><tr><td align=\"left\">Packer et al. (this study)</td><td align=\"left\">56</td><td align=\"left\">Male</td><td align=\"left\">1 to 2 days</td><td align=\"left\">Positive (+IgG, -C3)</td><td align=\"left\">N/A</td><td align=\"left\">N/A</td><td align=\"left\">Death</td></tr></tbody></table></table-wrap>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Testicular germ cell tumor metastasis to the upper gastrointestinal (GI) tract is uncommon (&lt;5%), and its likelihood is related to the histologic type of the primary neoplasm [##REF##11824886##1##]. Non-seminomatous germ cell tumors are much more likely to spread to the gastrointestinal (GI) tract than seminomas [##REF##3365676##2##]. In their series of 25 patients with GI tract involvement, Chait <italic>et al. </italic>reported the primary neoplasms to be combinations of embryonal carcinoma, teratoma, and choriocarcinoma [##UREF##0##3##]. The most commonly observed metastatic sites of the GI tract include the small intestine and duodenum [##REF##3365676##2##,##REF##987634##4##]. Different modes of spread have been observed, but direct extension from the retroperitoneal lymph nodes is more frequent than peritoneal seeding or hematogenous spread [##UREF##0##3##]. GI complaints such as intestinal obstruction, volvulus, intussusception, and hemorrhage resulting from metastatic testicular neoplasms are the most common manifestations of the disease [##REF##3365676##2##]. Although small bowel ulceration secondary to metastatic seminoma has been previously reported, it is very uncommon [##REF##11824886##1##,##REF##1498708##5##,##REF##15302504##6##]. We report a case of classic type seminoma tumor presenting primarily as perforation of the duodenum and acute abdomen.</p>" ]

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[ "<title>Discussion</title>", "<p>Involvement of the GI tract by metastatic seminoma is rare. When metastatic, only 5% of testicular germ cell tumors involve the bowel, and seminoma is the least commonly reported type of testicular neoplasm to do so [##REF##11824886##1##]. In an autopsy study by Johnson <italic>et al.</italic>, pure seminoma was the histologic type observed in only two of the 21 metastatic germ cell tumors identified in the GI tract [##REF##987634##4##]. Whereas the small bowel was the most common GI site of involvement in their study, the duodenum was only rarely involved. A series of 487 postmortem cases evaluated by Chait <italic>et al. </italic>did not document any purely seminomatous tumors metastasizing to the GI tract [##UREF##0##3##]. In a review article by Sweetenham <italic>et al.</italic>, three cases of seminoma metastatic to the duodenum and stomach were described, with severe upper abdominal and back pain having been the predominant symptoms in all patients [##REF##3365676##2##]. The involvement of the duodenum by metastatic testicular neoplasms has been attributed to the position of its second, third and fourth segments in the retroperitoneum where the lymphatic drainage of the testis is located [##REF##3365676##2##].</p>", "<p>A case of an ulcerating retroperitoneal seminoma mass communicating with the distal duodenum has been reported previously [##REF##1498708##5##]. However, the patient was cured successfully with several courses of chemotherapy and non-surgical management. The authors note that, although other cancers such as melanoma, kidney, and stomach are much more common than germ cell tumor (GCT) and more often metastasize to the small bowel, this diagnosis should be considered when an ulcerating small bowel mass is identified in a young man [##REF##1498708##5##].</p>" ]

[ "<title>Conclusion</title>", "<p>Although modern chemotherapeutic regimens have high success rates in the treatment of metastatic seminoma, some authors have proposed that patients with intestinal metastasis belong to a high-risk group [##UREF##0##3##,##REF##16184443##7##]. Early intervention with surgical resection of the involved segment of bowel is necessary when GI complications are encountered. This group of patients with intermediate or high-risk traditionally receive four cycles of bleomycin, etoposide, and cisplatin (BEP) with a known 30% to 40% failure of achieving a durable response [##REF##16184443##7##]. Unfortunately, in our patient with multiple complicating medical factors secondary to a late stage seminoma with bowel perforation, the chemotherapy was never initiated and the patient died.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Testicular neoplasms metastasizing to the retroperitoneum rarely involve the upper gastrointestinal tract. Gastrointestinal tract metastases usually present with complications including intestinal obstruction, gastrointestinal hemorrhage, and rarely ulceration of the bowel mucosa.</p>", "<title>Case presentation</title>", "<p>We describe an unusual case of duodenal perforation as the presenting manifestation of metastatic classic type seminoma in a 45-year-old man.</p>", "<title>Conclusion</title>", "<p>Germ cell tumor diagnosis should be considered when an ulcerating small bowel mass is identified in a young man.</p>" ]

[ "<title>Case presentation</title>", "<p>A 45-year-old man presented with acute respiratory failure, hypotension, rigid abdomen, and a hard, erythematous, and tender 14 cm right inguinoscrotal mass. Initial differential diagnoses included incarcerated hernia and testicular cancer. Further information regarding the mass could not be elicited due to the patient's altered mental status and critical condition requiring immediate intubation. Plain abdominal radiograph was unremarkable and chest radiograph revealed two large pulmonary nodules suspicious for malignancy. The patient's laboratory findings revealed elevated lactate of 7.7 mmol/liter (normal 0.5–2.2), amylase of 518 units/liter (normal 20–128), lipase of 157 units/liter (normal 6–32), a normal WBC of 5.5 with a slight left shift, and normal tumor markers (alpha-fetoprotein and beta-HCG). He underwent an emergency exploratory laparotomy due to suspicion of an incarcerated hernia and was found to have succus entericus throughout the peritoneal cavity and significant para-aortic lymphadenopathy invading the second and third portion of the duodenum.</p>", "<p>The perforated duodenal defect could not be repaired due to the extent of tumor infiltration. A controlled fistula was created with two separate red rubber catheters which were placed proximally and distally to the duodenal defect. A wedge tissue biopsy taken from the mass proved consistent with classic seminoma (Figure ##FIG##0##1##). The right scrotal mass was not explored during the initial operation due to the patient's critical condition in the operating room requiring postponement of surgery. On postoperative day three, a computed tomography (CT) scan was obtained and revealed extensive disease above and below the diaphragm (Figures ##FIG##1##2## and ##FIG##2##3##). The scrotal mass eventually began to invade through the scrotal skin and required resection 1 week after initial surgery (Figure ##FIG##3##4##). The final pathology revealed seminoma, classic type, and the final staging was consistent with T3, N3, M1b disease.</p>", "<p>The patient remained on respiratory support throughout his hospitalization and eventually succumbed to his disease 4 weeks later when his family declined further medical therapy. Treatment with chemotherapy was considered but not commenced due to the presence of the duodenal perforation and respiratory failure.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Consent</title>", "<p>Written informed consent could not be obtained since the patient is deceased and the next of kin were untraceable. We believe this case report contains a worthwhile clinical lesson which could not be as effectively made in any other way. We expect that the next of kin would not object to the publication since the patient remains anonymous.</p>", "<title>Authors' contributions</title>", "<p>Both authors contributed equally in preparing this document and were equally involved in care of the patient. RM was responsible for writing the introduction and case report itself, while RA contributed to the conclusion section and revision of the final document. Both authors were involved in creating CT and pathology images.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Hematoxylin and eosin stain of retroperitoneal mass biopsy consistent with classic seminoma. Magnification ×40.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Computed tomography scan demonstrating extensive metastatic disease of the mediastinum.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Computed tomography scan demonstrating extensive metastatic disease of the retroperitoneum.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Gross specimen of testicular mass invading through the scrotum.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1752-1947-2-294-1\"/>", "<graphic xlink:href=\"1752-1947-2-294-2\"/>", "<graphic xlink:href=\"1752-1947-2-294-3\"/>", "<graphic xlink:href=\"1752-1947-2-294-4\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Small round or oval objects that enter the stomach nearly always pass uneventfully through the gastrointestinal tract without requiring intervention. The retention of foreign objects within the duodenum is suggestive of partial obstruction, usually of congenital origin [##REF##1118573##1##, ####REF##2964775##2##, ##REF##5125285##3####5125285##3##]. We describe a child presenting with features of high intestinal obstruction where retention of such an object led to the discovery of congenital duodenal stenosis producing partial obstruction.</p>" ]

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[ "<title>Discussion</title>", "<p>Retention of elongated or pointed objects in the duodenum is a frequent problem. Long, sharp objects may perforate the duodenum and have been known to migrate widely in the abdomen. Early removal of such objects has been advised [##REF##11132474##4##,##REF##12024131##5##]. In addition, objects longer than 5 cm frequently fail to negotiate the C-curve and become impacted [##REF##12024131##5##, ####REF##5847723##6##, ##REF##934748##7####934748##7##] and hence should be removed using an endoscope if possible. For blunt objects, some authors have also recommended intervention if the foreign body remains in the same location for more than a week [##REF##11132474##4##,##REF##12024131##5##].</p>", "<p>Small round, oval, or cuboidal foreign objects nearly always pass through the gastrointestinal tract promptly, and stasis of such objects in the stomach or duodenum is extremely uncommon [##REF##1118573##1##]. The retention of such foreign objects within the duodenum suggests partial obstruction, usually of congenital origin. In otherwise normal children, duodenal stenosis, prolapsing duodenal diaphragm, and annular pancreas may cause retention of swallowed foreign objects [##REF##1118573##1##].</p>", "<p>There are a few reports of radio-opaque foreign objects retained at the site of congenital duodenal obstruction [##REF##1118573##1##, ####REF##2964775##2##, ##REF##5125285##3####5125285##3##]. Patients with duodenal stenosis alone or duodenal stenosis with annular pancreas may present with a variety of retained foreign materials in the stomach or proximal duodenum. Nuts, vegetable and fruit pits, and coins have been discovered at operation. Repeated abdominal roentgenograms should show that the foreign object is retained within the stomach or, more frequently, within the proximal duodenum. Upper gastrointestinal tract examination should confirm the presence of a duodenal anomaly. Duodenoduodenostomy or duodenojejunostomy should be performed after removal of the foreign object(s).</p>", "<p>However, in spite of the persistence of the radio-opaque foreign body on plain X-rays of the abdomen, the possibility of an obstructing anomaly in this child was never considered. He continued to suffer for about 15 months until he was seen by a pediatric surgeon. However, even at the tertiary center, initially the surgeon and radiologists were confused by the location of the radio-opaque shadow in his right lower quadrant and a diagnosis of small gut obstruction was made; this was attributed to the foreign body being impacted in the intestine. However, during a review of the radiograph, the double bubble sign was appreciated and duodenal obstruction was suspected. At surgery, an annular pancreas was detected and the foreign body was found to be lodged in the distended proximal duodenum.</p>", "<p>In adults, there are rare case reports of impaction by foreign bodies leading to detection of bowel stricture due to acquired diseases such as Crohn's disease [##REF##16407383##8##,##REF##17847697##9##]. However, in children with impaction or retention of foreign bodies, a congenital obstructing anomaly should always be kept in mind [##REF##1118573##1##, ####REF##2964775##2##, ##REF##5125285##3####5125285##3##]. The case reported here was not subjected to proper investigations pre-operatively. In cases of radio-opaque foreign bodies, it is quite easy to follow the passage of the object periodically by plain abdominal radiography; however, this has limitations in studying bowel obstructions from foreign bodies which are not radio-opaque. Plain abdominal radiography has a sensitivity of 86% in the diagnosis of high-grade bowel obstruction and this will demonstrate air fluid levels with dilated small bowel loops [##REF##12218815##10##,##REF##8956576##11##]; an intramural width of small intestine of 3 cm or less is considered abnormal. An abdominal CT scan is of great help in diagnosing and detecting the etiology of intestinal obstruction in 73–95% of cases [##REF##12218815##10##, ####REF##8956576##11##, ##REF##9129407##12####9129407##12##]. A CT scan may also be able to demonstrate the foreign body [##REF##16407383##8##]. Generally, laparotomy is performed for diagnosis and management in cases of impacted foreign bodies in the gut. However, with increasing expertise, laparoscopy can be equally effective with all of the other advantages of a minimal access approach. Hence, laparoscopy is now increasingly being employed for removal of ingested foreign bodies impacted in the gastrointestinal tract [##REF##17593464##13##,##REF##18097316##14##].</p>" ]

[ "<title>Conclusion</title>", "<p>The present case is reported to highlight the fact that retention or non-passage of a radio-opaque foreign body in a child should alert the treating doctors to the possibility of an obstructive congenital anomaly.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Small smooth objects that enter the gut nearly always pass uneventfully through the gastrointestinal tract. Retention of foreign objects may occur due to congenital obstructive anomaly of the gut.</p>", "<title>Case presentation</title>", "<p>We report here a child who presented with features of small gut obstruction which were attributed to a foreign body impacted in the intestine. At surgery, an annular pancreas was detected and the foreign body was found to be lodged in the distended proximal duodenum.</p>", "<title>Conclusion</title>", "<p>The reported case highlights the fact that an impacted radio-opaque foreign body in a child should warn the pediatrician to the possibility of an obstructive congenital anomaly.</p>" ]

[ "<title>Case presentation</title>", "<p>A 32-month-old boy presented with a history of intermittent vomiting over the previous 15 months. The vomitus was generally non-bilious but occasionally bilious. The parents also noticed intermittent distension of his abdomen which subsided after vomiting. The symptoms seemed to commence after the child had swallowed a metallic pendant which was coin-shaped and about 12 mm in diameter; at the time of swallowing, the child was about 17 months old. He underwent repeated plain upright radiographs of the abdomen to localize the foreign body and to determine whether it had been passed. However, these continued to detect the foreign body. The last plain radiograph (Figure ##FIG##0##1##) of his abdomen showed the foreign body to be located in the right lower quadrant and it was surmised that the intestinal obstruction was due to impaction of the foreign body in the region of the terminal ileum. The child's parents were therefore advised that their child needed to undergo surgery for relief of the obstruction. However, a review of the plain upright radiograph of the abdomen showed the presence of a 'double bubble sign', in addition to a few dilated loops of small bowel in the left upper quadrant. A pre-operative diagnosis of duodenal obstruction was made with the possibility of another obstructive lesion in the small bowel. The foreign body was presumed to be lodged somewhere in the ileal loops. The child was then subjected to exploratory laparotomy. During surgery, his stomach and proximal duodenum were found to be grossly dilated with thickening of their walls, and an annular pancreas was detected encircling the second part of the duodenum. In addition, there was a membrane with a small aperture in the duodenum. Surprisingly, the metallic pendant was found lodged in the duodenum along with lot of debris including berry seeds. The third part of the duodenum was mobilized and duodenoduodenostomy was performed without dividing the pancreas.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the parents of the child for publication of this case report and accompanying image. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>SPS assessed and interpreted the patient's gastrointestinal symptoms and the investigations. CM and OA carried out the radiological examination while PCS performed the surgery on the child. All were major contributors in writing the manuscript and all authors read and approved the final manuscript.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Plain radiograph of the abdomen showing the metallic foreign body in the right lower quadrant, the presence of a 'double bubble sign', and a few dilated loops of small bowel in the left upper quadrant.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1752-1947-2-293-1\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Atrial fibrillation (AF) is a common arrhythmia and its prevalence increases with age. It is usually associated with underlying heart disease, of almost any cause, complicated by heart failure and atrial enlargement. Most common underlying disorders are hypertensive heart disease, coronary artery disease, valvular heart disease, hyperthyroidism, and alcoholism. The majority of AF episodes were found to be triggered by atrial ectopic beats from muscle fibers extending from the left atrium into the pulmonary veins [##REF##10545432##1##]. Hence, radiofrequency catheter ablation of the pulmonary veins is effective for curing atrial fibrillation in selected cases, which may be complicated with atrioesophageal fistulas due to the proximity of the esophagus to the left atrium [##REF##12019377##2##].</p>", "<p>Esophageal cancer (EC) is a relatively rare malignancy in the United States with a poor prognosis. The majority of ECs are squamous cell carcinoma (SCC) and adenocarcinoma (AC). Dysphagia and weight loss are the two most common presenting symptoms. The majority of SCCs are located in the midportion of the esophagus where it is closely related to the posterior wall of the left atrium.</p>", "<p>AF was previously reported in patients with EC as a complication of total esophagectomy or photodynamic therapy [##REF##3277551##3##,##REF##9328978##4##]. This may be due to manipulation of the left atrium during the surgical procedure or deep penetration of light waves affecting the left atrium during the photodynamic therapy. Here, we will present a rare case, a patient with AF who was diagnosed with EC compressing the left atrium.</p>" ]

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[ "<title>Discussion</title>", "<p>To our knowledge, AF in association with EC was not reported previously except as a complication of esophagectomy and photodynamic therapy. In our case, direct mechanical compression of the left atrium by EC may have precipitated AF. On the other hand, AF might be related to the patient's HTN. In the Framingham study, the relative risk of AF in hypertensive patients with and without LVH was reported as 1.9 and 3.0, respectively [##REF##7062992##5##]. Therefore, the risk of AF is modestly increased due to HTN in our patient who had a structurally normal heart on echocardiogram. Thus, we hypothesize that EC may have precipitated AF by compressing on the left atrium.</p>", "<p>External compression of the left atrium was previously reported to precipitate AF. Upile <italic>et al</italic>. reported AF in a case with mega-esophagus due to achalasia in which AF was attributed to the external compression of the left atrium by food debris. AF had resolved after removal of food debris from the esophagus [##REF##17166260##6##]. AF was also reported in a case with intrapericardial lipoma compressing the left atrium [##REF##8154443##7##]. Similarly, swallowing may cause transient atrial tachyarrhythmias including AF, due to direct mechanical stimulation of the left atrium by the contents passing through the esophagus or activation of the autonomous nervous system [##REF##2436158##8##]. It was demonstrated experimentally that in patients with swallowing induced tachyarrhythmias, inflation of a balloon in the esophagus at the level of the left atrium precipitated the tachyarrhythmias until the balloon was deflated [##REF##5020876##9##]. In recent years, electrophysiological studies in patients with swallowing-induced tachyarrhythmias demonstrated ectopic atrial foci that were successfully treated with radiofrequency ablation [##REF##16876749##10##]. Likewise, AF in our patient may have arisen from an automatic focus in the posterior left atrium which may be more excitable with mechanical stimulation. However, electrophysiological studies were not performed since AF was short-lived and did not recur.</p>", "<p>The proximity of the esophagus to the left atrium may yield other unexpected complications. Atrial tachyarrhythmias may develop during esophagectomy and photodynamic therapy due to mechanical manipulation or thermal injury to the left atrium [##REF##3277551##3##,##REF##9328978##4##]. In reverse, atrioesophageal fistulas may develop during intraoperative or percutaneous catheter radioablation of pulmonary veins for treatment of atrial fibrillation [##REF##12019377##2##]. The diminutive distance between the esophagus and left atrium may contribute to the occurrence of this complication. Additionally, Oishi <italic>et al</italic>. recently reported a case with syncope upon swallowing caused by an esophageal hiatal hernia compressing the left atrium and impeding the blood flow to the left ventricle [##REF##14717723##11##].</p>" ]

[ "<title>Conclusion</title>", "<p>Esophageal cancer may precipitate AF by mechanical compression of the left atrium or pulmonary veins, triggering ectopic beats in susceptible patients. The proximity of the esophagus to the heart may be overlooked by physicians, but may have an important role in the pathogenesis of esophageal and heart disorders.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Atrial fibrillation was previously reported in patients with esophageal cancer as a complication of total esophagectomy or photodynamic therapy. Here, we propose that atrial fibrillation may also be caused by external compression of the left atrium by esophageal cancer.</p>", "<title>Case presentation</title>", "<p>We present a 58-year-old man who developed atrial fibrillation with rapid ventricular rate in the emergency room while being evaluated for dysphagia and weight loss. Atrial fibrillation lasted less than 12 hours and did not recur. Echocardiogram did not reveal any structural heart disease. A 10-cm, ulcerated mid-esophageal mass was seen during esophagogastroscopy. Microscopic examination showed squamous cell carcinoma. Computed tomography of the chest revealed esophageal thickening compressing the left atrium.</p>", "<title>Conclusion</title>", "<p>External compression of the left atrium was previously reported to provoke atrial fibrillation. Similarly, esophageal cancer may precipitate atrial fibrillation by mechanical compression of the left atrium or pulmonary veins, triggering ectopic beats in susceptible patients.</p>" ]

[ "<title>Case presentation</title>", "<p>A 58-year-old black man from the Caribbean was referred by his primary care physician for evaluation of dysphagia and weight loss. He reported a 2-month history of progressively worsening dysphagia with solids only and weight loss of 10 kg over a period of 2 months. He denied cough, regurgitation, hoarseness, palpitations, and dyspnea. Past medical history was significant for hypertension (HTN) for 5 years which had been treated with valsartan and hydrochlorothiazide. He denied any history of cardiovascular problems or arrhythmias. He quit smoking 7 years ago and denied drinking alcohol. There was no other significant medical, family or social history.</p>", "<p>Initial physical examination revealed regular heart rhythm with a rate of 81/minute. Abdominal and chest examinations were normal. Initial electrocardiogram (EKG) in the emergency room (ER) showed normal sinus rhythm with a rate of 68/minute and left ventricular hypertrophy (LVH). Chest X-ray revealed multiple nodules in both lung fields without cardiomegaly. Laboratory tests revealed mild normochromic, normocytic anemia with hemoglobin of 12.9 g/dl. Biochemical and coagulation studies were within normal limits. His serum potassium level was 4.2 mEq/liter.</p>", "<p>Four hours after presentation to ER, the admitting physician found the patient's heart rhythm to be irregular. A repeat EKG showed atrial fibrillation (Fig. ##FIG##0##1##) with a ventricular rate of 143/min. The patient was hemodynamically stable but was complaining of palpitations without dyspnea or chest pain. After 20 mg diltiazem had been administered intravenously, his ventricular rate dropped below 110/minute and the patient was started on metoprolol 25 mg twice daily orally. Troponin I level was below 0.04 ng/ml. Serum creatinine phosphokinase level was mildly elevated at 899 IU/liter with normal myoglobin (MB) fraction level. EKG performed after 12 hours revealed spontaneous reversion back to sinus rhythm.</p>", "<p>The next day, transthoracic echocardiography showed normal systolic and diastolic functions, and normal left atrium size without LVH. The patient underwent esophagogastroscopy which revealed a 10-cm, ulcerated mid-esophageal mass. The biopsy of the lesion showed infiltrating SCC. Computed tomography (CT) of the chest/abdomen/pelvis showed subcarinal lymphadenopathy and esophageal thickening compressing the left atrium (Fig. ##FIG##1##2##). Bronchoscopy revealed no abnormalities. Thyroid function tests, prostate specific antigen level, serum and urine protein electrophoreses were within normal limits.</p>", "<p>During 15 days of hospitalization, no arrhythmia was witnessed again and he did not complain of palpitations, chest pain or dyspnea. The patient was discharged to have chemoradiotherapy as an outpatient.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>UDB conceived of the report, treated the patient, gathered the data, searched the literature and drafted the manuscript. SB searched the literature and drafted the manuscript. AD treated the patient and conceived of the study. RRP and OIA treated the patient and helped to draft the manuscript. All authors read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Electrocardiogram showing atrial fibrillation with rapid ventricular rate.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Computed tomography of the chest demonstrating esophageal thickening (compound line) compressing the left atrium (dashed line).</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1752-1947-2-292-1\"/>", "<graphic xlink:href=\"1752-1947-2-292-2\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>In South Africa, adolescents are extremely vulnerable to HIV infection. Worldwide, about half of all new HIV infections among adults occur in people under the age of 25 [##UREF##0##1##]. Each day, 7000 people between the ages of 15 and 24 are infected with HIV worldwide, resulting in 2.6 million new infections per year, 1.7 million of which occur in Africa [##REF##15167292##2##]. Similarly, the highest rates of HIV infection in South Africa occur among young people [##UREF##1##3##]. A national household survey conducted in 2002 estimated that about 10% of 15–24 year old South Africans are living with HIV [##UREF##2##4##]. The prevalence rate was 4.8% among boys and 15.5% among girls of the same age group in a second national survey conducted in 2004 [##REF##16135907##5##]. While South African adolescents have widespread exposure to HIV prevention messages and knowledge of HIV aetiology [##REF##17327261##6##], perception of vulnerability to HIV remains low [##REF##16951647##7##,##REF##15812613##8##]. High levels of risky sexual behaviour among teens are exemplified by, for instance, a high teenage pregnancy rate. The 2004 survey estimated a pregnancy rate of 15.5% among 15–19 year old South African girls [##REF##16135907##5##]. In light of these behaviour challenges, an HIV vaccine will be an important tool for protecting adolescents and therefore testing promising candidate vaccines amongst adolescents is required.</p>", "<p>Over the last two decades, candidate HIV vaccines have been studied in safety and efficacy trials involving healthy adult volunteers, and more recently infants and pregnant women have been included in early phase studies [##REF##15167292##2##]. On the contrary, candidate vaccines have not been tested in adolescents. Currently, phase I/II vaccine trials are being carried out with the adult population in Soweto. The United States Food and Drug Administration (FDA), one of the regulatory bodies involved in oversight of clinical trials of HIV vaccines, stipulates that a drug cannot be licensed for use in a population in which it has not been tested. For this reason, lack of adolescent participation in HIV vaccine trials will only delay access of this age group to a vaccine once it is available [##REF##16327928##9##]. Willingness of adolescents to enrol in HIV vaccine clinical trials is therefore an important factor in planning such initiatives.</p>", "<p>Prior studies indicate that willingness to participate in future HIV vaccine trials is contingent on vaccine knowledge and to hypothetical trial attributes [##REF##9619811##10##,##REF##17275895##11##]. Men who have sex with men (MSM), whose baseline knowledge of HIV vaccines was very low, became unwilling to participate with increased knowledge. However, other findings have not borne out such a relationship, with one study suggesting that high levels of knowledge regarding HIV vaccines may lead to the increased likelihood of participation [##REF##16282079##12##], while another did not find a relationship between knowledge and willingness to participate [##REF##11464149##13##]. Willingness to participate in a hypothetical vaccine clinical trial may not reflect willingness to participate in an actual trial [##REF##9619811##10##,##REF##12473841##14##]. Some of the factors, identified among adults, that would discourage participation in HIV vaccine clinical trials include mistrust of medical research, social harms, and concerns regarding vaccine safety and vaccine-induced HIV seropositivity [##REF##9619811##10##,##REF##17275895##11##,##REF##11464149##13##]. Some of the perceived benefits of trial participation include risk reduction counselling, altruism, and possible protection from the vaccine.</p>", "<p>Other challenges inherent in adolescent clinical trial participation include many socio-legal and psychological considerations. In particular, adolescents may lack cognitive maturity to weigh the pros and cons of clinical trial participation [##REF##16533797##15##]. This is further complicated by the importance of peer pressure on decision making. Adolescent participation in clinical trials requires parental consent, potentially compromising the privacy and confidentiality of the participant. Another important consideration when planning adolescent participation in clinical trials is to build in flexibility that will accommodate the needs of the adolescents.</p>", "<p>To begin to understand adolescent attitudes to these complex issues, and inform our future work with adolescents in HIV vaccine trials, we undertook a formative study examining attitudes towards such trials, potential motivating factors and hypothetical willingness to participate, among Soweto youth. There are varied meanings of 'adolescent'; in this research we used the psychological sense of the intermediate time of development between childhood and maturity, rather than in a legal sense referring to a specific age, although examined responses in relation to the specific age, given age would be an eligibility criterion in trials.</p>" ]

[ "<title>Methods</title>", "<p>We undertook a study of attitudes to HIV vaccine trial participation among high school students in Soweto from August 2005 to February 2006. This study was approved by the University of the Witwatersrand Human Research Ethics Committee (protocol number MO50101). Approval was also provided by each school head teacher and the Gauteng Department of Education. Consultations were held with school governing bodies prior to initiation of the survey within each school.</p>", "<title>Participants</title>", "<p>A two-stage sampling procedure was used. The first stage sampling units were all 72 public high schools in Soweto. Ten schools were randomly selected. Based on our estimates of class numbers and response rates, we planned to enrol students at four schools; we oversampled from the first stage pool to provide for potential non-agreement to conduct the research at a selected school. The first four randomly chosen schools were approached regarding participation and all agreed. All pupils within the selected schools from whom parental consent and child assent could be obtained were eligible for participation.</p>", "<title>Measures</title>", "<p>A self-administered, facilitated questionnaire was administered to all participants [see Additional File ##SUPPL##0##1##]. The questionnaire explored general HIV knowledge, perception of adolescent risk, knowledge of vaccine concepts, willingness to participate in future vaccine trials, perceived personal and social harms and benefits associated with participation as well as barriers and facilitators to participating in future HIV vaccine trials.</p>", "<p>The measures administered were based and adapted from a similar survey conducted among high-risk populations in the United States [##REF##9619811##10##]. The items were adapted for comprehensibility and local idiomatic language use, and piloted prior to use in the school setting. The items had not been validated in prior work in South Africa, to our knowledge.</p>", "<title>Sample size</title>", "<p>The sample size was estimated based on an initial assumption that 20% of adolescents would be willing to enrol in an HIV vaccine trial. To compare the hypothesized value against an alternative proportion of 50%, with type 1 error rate of 0.05 and 90% power, we estimated that 23 respondents would be required within each stratum. We will therefore recruit a minimum of 25 children of each gender within each of three age strata: &lt; 13 years, 13 – 14 years, and 15 – 18 years. The minimum sample size for the questionnaire portion of this study will therefore be 150 participants.</p>" ]

[ "<title>Results</title>", "<p>277 school-going youth (mean age 16.2 years; range 10 – 25; 53.1% female) provided assent or consent to participate, and if under 18, we also obtained written consent from a parent. The response rate to the survey is not known. Not all data fields were adequately responded to, resulting in missing data for some items.</p>", "<title>Perceptions And Attitudes To Adolescent Sexuality And HIV Testing</title>", "<p>Of the 241 participants who responded to the question on HIV testing, 10% indicated that they have tested for HIV (Table ##TAB##0##1##). Of those who responded that they had not previously tested, almost half (46%) of the participants stated that a reason for not testing was that they believed that they were not at risk of HIV infection, while 44% stated the reason was that they were afraid to test for HIV. More than half of the participants believed that sexual debut in Soweto is as early as 9 years of age and 43% believed that 9 year olds were vulnerable to HIV infection. However, less than half of the participants believed that adults talk to children that age about HIV. The majority (57%) of participants believed that parents should give permission for their child's HIV test while most of the participants (84%) believed that parents should know the HIV status of their child.</p>", "<title>Trial Participation And Stigma</title>", "<p>HIV stigma did not appear to impact on willingness to participate in a future trial. Most respondents felt that potential discrimination, being avoided as a result of trial participation, being perceived as at high risk of HIV, or being thought to have AIDS would not influence their decision to participate in trials (Table ##TAB##1##2##).</p>", "<title>Willingness To Participate In Future HIV Vaccine Trials And Associated Factors</title>", "<p>Of the 240 responses to the willingness item, 84 (35%) indicated they were \"probably willing\" and 126 (52.5%) that they were \"definitely willing\" to join a study of a vaccine to prevent HIV. Combined, willingness to participate ('definitely' and 'probably') was 88.2% (95% confidence interval 84.1% – 92.3%, p &lt; 0.00001). There were no significant differences in willingness by gender, age, school grade, or institution. Factors that were rated as \"very important\" in determining willingness included receiving current information about HIV research [n = 201 (89%)], that they would be doing something to honour people who have HIV or AIDS or have died of AIDS [n = 168 (71%)], getting free counselling and testing every six months [n = 168 (71%)], that participants may receive some protection against HIV infection from the vaccine [n = 160 (71%)], and would feel more motivated to avoid risky behaviour [n = 134 (59%)] (Table ##TAB##2##3##).</p>" ]

[ "<title>Discussion</title>", "<p>Sexual debut in Soweto was perceived to be very early, exposing adolescents to HIV. Ten percent of the participants in this study reported having previously testing for HIV. This figure perhaps reflects the difficulties in accessing HIV testing for Soweto youth. Comparative figures for testing uptake in Soweto are not available; however, national surveys report rates of prior testing of 30.5% among people 15 years and older [##REF##17600972##16##]. Similar to other reports emanating from South Africa (6), youth in this believed that they were at risk of HIV acquisition. However, the proportion of participants who thought that they were not at risk is still high in light of the prevalence of HIV in young adults and the belief expressed that sexual debut is early. The high proportion of participants who believed that parents should give permission for the HIV testing and know the HIV status of their child indicates interdependence between parents and their children although this is not without problems. Parental involvement in adolescent trial participation will have to be thought out very carefully to balance the need for privacy and autonomous decision-making and the need to have adults oversee adolescent participation in vaccine clinical trials.</p>", "<p>Soweto school-going youth report high degrees of willingness to participate in future HIV vaccine trials. Participants indicated that access to regular counselling and testing, current information, and potential impact on motivation to reduce risk behaviour were very important for determining willingness to participate. Whether hypothetical willingness translates to participation will await data from adolescent HIV vaccine trials. In the same vein, consideration given to factors that may encourage or discourage participation in such trials may differ from a hypothetical to an actual trial. However, that being said, the enormousness of the HIV and AIDS epidemic in South Africa has fostered a culture of participation in HIV/AIDS-related initiatives. In this regard, HIV stigma may be a minor consideration in such decisions. Some recent data suggest that HIV stigma may no longer be a major influence in decisions relating to HIV and AIDS [##REF##17600972##16##]. Further, several international studies point out that willingness to participate in a hypothetical HIV vaccine study is strongly associated with being at high risk for HIV infection [##REF##9619811##10##,##REF##10048904##17##,##REF##9358105##18##].</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>To explore adolescent HIV risk perception, HIV vaccine knowledge, willingness to participate in future HIV vaccine clinical trials, and the factors that influence willingness to participate among high school students in Soweto, South Africa, we recruited school-going youth through randomly selected local high schools. All pupils within the selected schools from whom parental consent and child assent could be obtained were eligible for participation. A self-administered, facilitated questionnaire was completed by all participants.</p>", "<title>Findings</title>", "<p>Perception of adolescent HIV risk was high. Some misconceptions regarding vaccine research were common, particularly regarding placebo and potential eligibility criteria for prophylactic vaccine trials. Of 240 responses to the willingness item, 84 (35%) indicated they were \"probably willing\" and 126 (52.5%) that they were \"definitely willing to participate\". There were no significant differences in willingness by gender, age, school grade, or institution. Factors that were rated as \"very important\" in determining willingness included receiving current information about HIV research [n = 201 (88.9%)], doing something to honour people who have HIV or have died of AIDS [n = 168 (70.9%)], getting free counselling and testing [n = 167 (70.5)], that participants may receive some protection against HIV infection from the vaccine [n = 160 (70.2%)], and improving motivation to avoid risky behaviour [n = 134 (59%)].</p>", "<title>Conclusion</title>", "<p>Soweto school-going youth report high degrees of willingness to participate in HIV vaccine trials. This may be related to the high levels of adolescent HIV risk perception. Whether hypothetical willingness translates to participation will await data from adolescent HIV vaccine trials.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>GdB designed the study, analyzed the data, and drafted the manuscript. NS designed the study, carried out the field work, and helped draft the manuscript. GR participated in the study design and helped oversee the fieldwork. GG conceived of the study, participated in its coordination and helped to draft the manuscript. JM helped arrange funding. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The authors acknowledge the PHRU for funding; the Gauteng Department of Education for providing permission to work with schools; the principals and teachers, parents, and students of participating schools; and our adolescent community advisory board for ongoing informative discussions. The funder had no direct role in the study design, data collection, analysis or interpretation, writing of the manuscript, or decision to submit the manuscript for publication.</p>" ]

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[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Questions Exploring Perceptions And Attitudes To Adolescent Sexuality And HIV Testing</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\">n (%)</td></tr></thead><tbody><tr><td align=\"left\">I have tested for HIV</td><td align=\"left\">24 (10)</td></tr><tr><td align=\"left\">I do not think I am risk of HIV infection</td><td align=\"left\">110 (46)</td></tr><tr><td align=\"left\">I am afraid to get tested for HIV</td><td align=\"left\">107 (44)</td></tr><tr><td align=\"left\">My parents should know my HIV test results</td><td align=\"left\">198 (84)</td></tr><tr><td align=\"left\">Children age 9 are beginning to be sexually active</td><td align=\"left\">133 (56)</td></tr><tr><td align=\"left\">Adults talk to children between 9–10 about HIV</td><td align=\"left\">111 (47)</td></tr><tr><td align=\"left\">HIV is a threat to children from age 9</td><td align=\"left\">102 (43)</td></tr><tr><td align=\"left\">My parents should give permission for my HIV test</td><td align=\"left\">135 (57)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Questions Exploring Stigma Resulting From HIV Vaccine Trial Participation</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">How important is stigma in making decisions about trial participation?</td><td align=\"center\">Very n (%)</td><td align=\"center\">Somewhat n (%)</td><td align=\"center\">Slightly n (%)</td><td align=\"center\">Not at all n (%)</td></tr></thead><tbody><tr><td align=\"left\">I may be discriminated against at school if I volunteer</td><td align=\"center\">41 (18)</td><td align=\"center\">30 (13)</td><td align=\"center\">32 (14)</td><td align=\"center\">130 (56)</td></tr><tr><td align=\"left\">People may avoid me if I volunteer in a vaccine trial</td><td align=\"center\">40 (17)</td><td align=\"center\">25 (11)</td><td align=\"center\">41 (17)</td><td align=\"center\">132 (55)</td></tr><tr><td align=\"left\">People may think I have HIV or AIDS if I volunteer in a vaccine trial</td><td align=\"center\">26 (11)</td><td align=\"center\">37 (17)</td><td align=\"center\">37 (17)</td><td align=\"center\">136 (58)</td></tr><tr><td align=\"left\">People may think I am at high risk of HIV if I am in a study</td><td align=\"center\">44 (19)</td><td align=\"center\">32 (14)</td><td align=\"center\">38 (16)</td><td align=\"center\">117 (51)</td></tr><tr><td align=\"left\">People may not want to have sex with me if I am in a study</td><td align=\"center\">56 (23)</td><td align=\"center\">17 (7)</td><td align=\"center\">35 (15)</td><td align=\"center\">132 (55)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Factors Influencing Willingness To Participate In HIV Vaccine Trials</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">n (%) indicating factor was \"very important\" in relation to willingness</td></tr></thead><tbody><tr><td align=\"left\">I would get free counseling and HIV testing at least once every 6 months</td><td align=\"center\">167/237 (70.5)</td></tr><tr><td align=\"left\">I would get current information about HIV research</td><td align=\"center\">201/226 (88.9)</td></tr><tr><td align=\"left\">I may feel more motivated to avoid risky behavior</td><td align=\"center\">134/224 (59.8)</td></tr><tr><td align=\"left\">I would get a small amount of money each time I came for a visit</td><td align=\"center\">58/238 (24.4)</td></tr><tr><td align=\"left\">I may get some protection against HIV infection from the vaccine</td><td align=\"center\">160/228 (70.2)</td></tr><tr><td align=\"left\">I would be doing something to honor people who have HIV or have died of AIDS</td><td align=\"center\">168/237 (70.9)</td></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional File 1</title><p>Adolescent questionnaire v1 29 Dec 2004.pdf. Self-administered questionnaire utilized in this research.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>*Values may not add up to total number of participants as some fields had missing data.</p></table-wrap-foot>" ]

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[ "<media xlink:href=\"1756-0500-1-76-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>MIER1 is a newly described transcriptional regulator that functions in anterioposterior patterning in the <italic>Xenopus </italic>embryo [##REF##12927772##1##] and as an inhibitor of anchorage-independent growth of breast carcinoma cells [##REF##18665173##2##]. Two major protein isoforms, MIER1α and β, have been identified [##REF##12242014##3##] and structurally, these two isoforms share a number of domains with other transcriptional regulators, including ELM2 [##REF##10226007##4##], SANT [##REF##8882580##5##] and acid activation domains. At the molecular level, MIER1 can both activate and repress transcription. The former involves the N-terminal acidic activation domain [##REF##9325278##6##] while repression occurs by at least two distinct mechanisms: displacement of transcription factors, like Sp1, from their cognate binding sites [##REF##15117948##7##] and recruitment of the chromatin remodeling enzyme, HDAC1 through its ELM2 domain [##REF##12482978##8##]. Recently, studies have shown that the SANT domain also plays a crucial role in chromatin remodeling; in particular, this domain is required for efficient histone acetylation [##REF##15040448##9##]. In this report, we extended our investigation of MIER1 in chromatin remodeling by examining its ability to interact with CBP and regulate its HAT activity.</p>" ]

[ "<title>Methods</title>", "<p>The GST fusion and myc-tagged hmi-er1β (GenBank: <ext-link ext-link-type=\"gen\" xlink:href=\"NM_001077701\">NM_001077701</ext-link>) sequences were constructed using pGEX-4T-1 and pCS3+MT plasmids, respectively and their production has been described elsewhere [##REF##15117948##7##,##REF##12482978##8##]. The full-length mouse CBP (GenBank: NM_001025432<ext-link ext-link-type=\"gen\" xlink:href=\"NM_001025432\"/>) in pRc/RSV was a kind gift from Dr. Roland Kwok (University of Michigan). CBP _1–1096and CBP_1094–2441were constructed by PCR amplification of the full-length sequence using 5'-ggggatccatggccgagaacttgctggacg-3' (forward) with 5'-cgggatccctacataagtgcctggcgtagctcctcg-3' (reverse) and 5'-ggggatccgcacttatgccaactctagaag-3' (forward) with 5'-ccggatccctacaaaccctccacaaactttt-3' (reverse), respectively. The PCR products were digested with BamH1 and inserted into the BamH1 site of the pCMV-Tag2B vector (Stratagene). Anti-myc hybridoma supernatant was prepared from 9E10 cells (ATCC) [##REF##3915782##10##] grown in hybridoma serum-free media (Invitrogen, Inc.) supplemented with 1% OptiMab monoclonal antibody production enhancer (Invitrogen, Inc.). GST pull-down assays were performed as in [##REF##15117948##7##], using 0.35 μg of GST or equimolar amounts of GST fusion proteins and 100,000 cpm of ³⁵S-labeled <italic>in vitro </italic>translation products. Transient transfections were performed as in [##REF##12482978##8##]. HAT assays were performed as in [##REF##9685509##11##]; briefly, cell lysates were subjected to immunoprecipitation with the indicated antibody and the washed beads incubated with 100 nCi [¹⁴C]acetyl-CoA (51 mCi/mmol, Amersham), 30 μM H4 biotinylated peptide (Upstate Biotechnology Inc.) and 300 nM trichostatin A (Sigma) in HAT buffer [##REF##9685509##11##] for 45 min at 30°C. The supernatants were collected and incubated with streptavidin-agarose (Pierce) at 4°C for 20 min; the ¹⁴C incorporated into the bound H4 peptide was determined by liquid scintillation counting.</p>" ]

[ "<title>Results and discussion</title>", "<title>The N-terminal half of MIER1 interacts with the C-terminal half of CBP</title>", "<p>We investigated a possible interaction between MIER1β and CBP, using pull-down assays. ³⁵S-labelled flag-tagged CBP constructs (Figure ##FIG##0##1A##), synthesized <italic>in vitro</italic>, were incubated with a full-length GST-MIER1β fusion protein. CBP was detected in the pull-down with GST-MIER1β, but not with GST alone (Figure ##FIG##0##1B##). Furthermore, only the C-terminal half of CBP, consisting of the bromo-, HAT, C/H3 and glutamine-rich domains, interacted with MIER1β (Figure ##FIG##0##1B##). To determine which domain(s) of MIER1β were required for binding, two deletion mutants were constructed: one consisting of the N-terminal half, which includes the acidic activation and ELM2 domains, and a second consisting of the C-terminal half, which includes the SANT domain and beta-specific C-terminus (Figure ##FIG##0##1C##). As can be seen in Figure ##FIG##0##1D##, only the N-terminal half (amino acids 1–283) of MIER1 was able to bind CBP. Since this construct contains sequence that is common to both MIER1α and β, one would expect that MIER1α would also interact with CBP. Interestingly, this region does not include the SANT domain, a domain known to play an important role in the histone acetyltransferase (HAT) activity of several chromatin remodelling complexes [##REF##12419236##12##].</p>", "<title>Binding of MIER1 results in inhibition of CBP HAT activity</title>", "<p>To explore the functional consequence of MIER1-CBP interactions, we performed HAT assays on extracts from HEK293 cells co-transfected with flag-tagged CBP_1094–2441(flag-CBP) and myc-tagged full-length MIER1β (myc-mier1). Parallel samples were subjected to immunoprecipitation (IP) with the relevant antibody and the pellets assayed for interaction with MIER1β by Western blot or for HAT activity using ¹⁴C-labelled acetyl-CoA and a biotinylated histone 4 (H4) peptide. Acetylated H4 was recovered using streptavidin-agarose and the level of incorporation measured by liquid scintillation counting. Western blot analysis was used to confirm the expression of MIER1β (Fig. ##FIG##1##2A##, panel i) and CBP (Figure ##FIG##1##2A##, panel ii) in transfected cells.</p>", "<p>As expected, no HAT activity was detectable in immunoprecipitates from cells transfected with empty vector or <italic>mier1β </italic>(Figure ##FIG##1##2B##, lanes 2–3), however high levels of HAT activity were measured in those from cells expressing CBP alone (Fig. ##FIG##1##2B##, lane 4). When CBP was co-immunoprecipitated with MIER1β on the other hand, no detectable HAT activity was recovered in the pellet (Fig. ##FIG##1##2B##, lane 5). The presence of CBP in the co-IP was verified in a parallel sample subjected to Western blot analysis with anti-flag (Fig. ##FIG##1##2A##, panel iii, lane 3). These data show that when associated with MIER1β, CBP has no detectable HAT activity.</p>", "<title>MIER1 does not interfere with histone binding to CBP</title>", "<p>The inhibitory effect of MIER1β on CBP HAT activity could result from interference with histone binding or from a direct effect on the HAT catalytic domain. To test whether interaction with MIER1β interferes with CBP's ability to bind to histone, we measured the ability of CBP to interact with H4 peptide in the presence or absence of MIER1. <italic>In vitro </italic>translated ³⁵S-labelled CBP_1094–2441was incubated with biotinylated H4 peptide in the presence of a 400-fold molar excess of GST alone or GST-MIER1_1–283fusion protein; the complex was precipitated using streptavidin-agarose and analyzed by autoradiography. As can be seen in Figure ##FIG##2##3##, the level of CBP associated with H4 peptide in the presence of GST-MIER1 (lane 2) was the same as that in the presence of GST alone (lane 3), demonstrating that the interaction of CBP with H4 peptide was not affected by MIER1.</p>", "<p>Together, our data show that MIER1 physically interacts with CBP and inhibits its HAT activity; this inhibition is not the result of interference with histone binding but is possibly due to a direct effect on the HAT catalytic domain.</p>" ]

[ "<title>Results and discussion</title>", "<title>The N-terminal half of MIER1 interacts with the C-terminal half of CBP</title>", "<p>We investigated a possible interaction between MIER1β and CBP, using pull-down assays. ³⁵S-labelled flag-tagged CBP constructs (Figure ##FIG##0##1A##), synthesized <italic>in vitro</italic>, were incubated with a full-length GST-MIER1β fusion protein. CBP was detected in the pull-down with GST-MIER1β, but not with GST alone (Figure ##FIG##0##1B##). Furthermore, only the C-terminal half of CBP, consisting of the bromo-, HAT, C/H3 and glutamine-rich domains, interacted with MIER1β (Figure ##FIG##0##1B##). To determine which domain(s) of MIER1β were required for binding, two deletion mutants were constructed: one consisting of the N-terminal half, which includes the acidic activation and ELM2 domains, and a second consisting of the C-terminal half, which includes the SANT domain and beta-specific C-terminus (Figure ##FIG##0##1C##). As can be seen in Figure ##FIG##0##1D##, only the N-terminal half (amino acids 1–283) of MIER1 was able to bind CBP. Since this construct contains sequence that is common to both MIER1α and β, one would expect that MIER1α would also interact with CBP. Interestingly, this region does not include the SANT domain, a domain known to play an important role in the histone acetyltransferase (HAT) activity of several chromatin remodelling complexes [##REF##12419236##12##].</p>", "<title>Binding of MIER1 results in inhibition of CBP HAT activity</title>", "<p>To explore the functional consequence of MIER1-CBP interactions, we performed HAT assays on extracts from HEK293 cells co-transfected with flag-tagged CBP_1094–2441(flag-CBP) and myc-tagged full-length MIER1β (myc-mier1). Parallel samples were subjected to immunoprecipitation (IP) with the relevant antibody and the pellets assayed for interaction with MIER1β by Western blot or for HAT activity using ¹⁴C-labelled acetyl-CoA and a biotinylated histone 4 (H4) peptide. Acetylated H4 was recovered using streptavidin-agarose and the level of incorporation measured by liquid scintillation counting. Western blot analysis was used to confirm the expression of MIER1β (Fig. ##FIG##1##2A##, panel i) and CBP (Figure ##FIG##1##2A##, panel ii) in transfected cells.</p>", "<p>As expected, no HAT activity was detectable in immunoprecipitates from cells transfected with empty vector or <italic>mier1β </italic>(Figure ##FIG##1##2B##, lanes 2–3), however high levels of HAT activity were measured in those from cells expressing CBP alone (Fig. ##FIG##1##2B##, lane 4). When CBP was co-immunoprecipitated with MIER1β on the other hand, no detectable HAT activity was recovered in the pellet (Fig. ##FIG##1##2B##, lane 5). The presence of CBP in the co-IP was verified in a parallel sample subjected to Western blot analysis with anti-flag (Fig. ##FIG##1##2A##, panel iii, lane 3). These data show that when associated with MIER1β, CBP has no detectable HAT activity.</p>", "<title>MIER1 does not interfere with histone binding to CBP</title>", "<p>The inhibitory effect of MIER1β on CBP HAT activity could result from interference with histone binding or from a direct effect on the HAT catalytic domain. To test whether interaction with MIER1β interferes with CBP's ability to bind to histone, we measured the ability of CBP to interact with H4 peptide in the presence or absence of MIER1. <italic>In vitro </italic>translated ³⁵S-labelled CBP_1094–2441was incubated with biotinylated H4 peptide in the presence of a 400-fold molar excess of GST alone or GST-MIER1_1–283fusion protein; the complex was precipitated using streptavidin-agarose and analyzed by autoradiography. As can be seen in Figure ##FIG##2##3##, the level of CBP associated with H4 peptide in the presence of GST-MIER1 (lane 2) was the same as that in the presence of GST alone (lane 3), demonstrating that the interaction of CBP with H4 peptide was not affected by MIER1.</p>", "<p>Together, our data show that MIER1 physically interacts with CBP and inhibits its HAT activity; this inhibition is not the result of interference with histone binding but is possibly due to a direct effect on the HAT catalytic domain.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p><italic>Mier1 </italic>encodes a novel transcriptional regulator and was originally isolated as a fibroblast growth factor early response gene. Two major protein isoforms have been identified, MIER1α and β, which differ in their C-terminal sequence. Previously, we demonstrated that both isoforms recruit histone deacetylase 1 (HDAC1) to repress transcription. To further explore the role of MIER1 in chromatin remodeling, we investigated the functional interaction of MIER1 with the histone acetyltransferase (HAT), Creb-binding protein (CBP).</p>", "<title>Findings</title>", "<p>Using GST pull-down assays, we demonstrate that MIER1 interacts with CBP and that this interaction involves the N-terminal half (amino acids 1–283) of MIER1, which includes the acidic activation and ELM2 domains and the C-terminal half (amino acids 1094–2441) of CBP, which includes the bromo-, HAT, C/H3 and glutamine-rich domains. Functional analysis, using HEK293 cells, shows that the CBP bound to MIER1 <italic>in vivo </italic>has no detectable HAT activity. Histone 4 peptide binding assays demonstrate that this inhibition of HAT activity is not the result of interference with histone binding.</p>", "<title>Conclusion</title>", "<p>Our data indicate that an additional mechanism by which MIER1 could repress transcription involves the inhibition of histone acetyltransferase activity.</p>" ]

[ "<title>Abbreviations</title>", "<p>CBP: Creb-binding protein; GST: glutathione S-transferase; HAT: histone acetyltransferase; H4: histone 4.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>TMB performed the GST pull-downs and the HAT assays and participated in the interpretation of the data. CFM performed the histone binding assays and participated in the interpretation of the data. GDP participated in the design of the experiments and interpretation of the data. LLG participated in the design of the experiments and interpretation of the data, prepared the Figures and wrote the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported by a grant from the Canadian Institutes of Health Research to LLG and GDP. The authors thank Krista Butt for her expert technical assistance.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>MIER1 interacts with CBP</bold>. (A) Schematic illustrating the CBP protein sequence and its domains: NR = nuclear receptor interaction domain, C/H1 and C/H3 = cysteine/histidine rich regions, KIX = kinase-induced interacting domain, Br = bromodomain, HAT = histone acetyltransferase domain, QRD = glutamine-rich domain. (B) GST pull-down assays using CBP deletion mutants. <italic>In vitro </italic>translated, ³⁵S-labelled, full-length CBP (panel i), CBP_1–1096(panel ii) or CBP_1094–2441(panel iii) were incubated with 0.35 μg GST (lane 2) or an equimolar amount of GST-MIER1β fusion protein (lane 3). One twentieth of the labelled protein input is shown in lane 1. (C) Schematic illustrating the MIER1β sequence and its domains: acidic activation, ELM2 and SANT domains as well as the β-specific C-terminus. (D) GST-pull-down assays using MIER1β deletion mutants. <italic>In vitro </italic>translated, ³⁵S-labelled CBP_1094–2441was incubated with 0.35 μg of GST alone (lane 2) or equimolar amounts of GST fusions of full-length MIER1β (lane 1), the N-terminal half (lane 3) or C-terminal half (lane 4) of MIER1β. One twentieth of the labelled protein input is shown in lane 5. (E) Coomassie blue-stained gel showing the GST fusion proteins used in panel D.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>MIER1β inhibits CBP HAT activity</bold>. (A) Interaction between MIER1β and CBP_1094–2441expressed in HEK293 cells. Western blots of total extracts (panels i and ii) or anti-myc immunoprecipitates (panel iii) from nontransfected cells (lane 1) or cells co-transfected with plasmids encoding flag-tagged CBP_1094–2441and myc tag (lane 2) or myc-tagged MIER1β (lane 3). (B) HAT activity recovered from immunoprecipitates of nontransfected HEK293 cells (bar 1) or cells transfected with empty vectors (bar 2), myc-tagged <italic>mier1β </italic>(bar 3), flag-tagged <italic>cbp</italic>_1094–2441(bar 4) or flag-tagged <italic>cbp</italic>_1094–2441and myc-tagged <italic>mier1β </italic>(bar 5). In each sample, the total amount of DNA transfected was kept constant by including the appropriate amount of empty vector. HAT assays were performed as described in the M<sc>ETHODS</sc> and ¹⁴C-acetyl incorporation into H4 peptide was determined for each sample. Shown are the mean and standard deviation of four independent experiments.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>MIER1β does not interfere with H4 peptide binding by CBP</bold>. <italic>In vitro </italic>translated, ³⁵S-labelled CBP_1094–2441was incubated with 0.1 ug biotinylated H4 peptide (Upstate Biotechnology Inc.) in the absence (lane 1) or presence of a 400-fold molar excess of GST (lane 2) or GST-MIER1β fusion protein (lane 3).</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1756-0500-1-68-1\"/>", "<graphic xlink:href=\"1756-0500-1-68-2\"/>", "<graphic xlink:href=\"1756-0500-1-68-3\"/>" ]

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{ "acronym": [], "definition": [] }

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[ "<title>Methods</title>", "<title>Acquisition of blood samples</title>", "<p>The study was carried out according to the regulations of the local ethics committee and Austrian Law. After having obtained informed consent, peripheral blood samples were drawn from patients with newly diagnosed, locally advanced rectal cancer (n = 20), metastatic non-small cell lung cancer (NSCLC; n = 25) and from age-mached healthy volunteers (n = 30). Women during the active menstrual phase were excluded from the study. Patients' characteristics are summarized in table ##TAB##0##1##.</p>", "<title>Isolation of progenitor cells from cord blood</title>", "<p>Human umbilical cord blood samples (n = 10) were obtained at birth from full-term newborns. Blood samples were collected in heparinized tubes and stored at 8°C no longer than 12 h before flow cytometric analysis and mRNA extraction, respectively. MNC were isolated by Ficoll density gradient centrifugation (Lymphoprep^®, Nycomed, Norway). Progenitor cells were enriched by a two step immunomagnetic bead separation protocol by negative selection for CD45 and subsequent positive selection for CD34⁺(CD34 isolation kit, CD45 microbeads, Miltenyi Biotec). Progenitor cells were spiked into PBMNC of healthy volunteers at frequencies ranging from 0.001 to 1%.</p>", "<title>Generation of endothelial colony forming cells (ECFC) from peripheral blood</title>", "<p>Autologous ECFC cultures were generated as described previously [##REF##17053059##7##,##REF##16698211##13##]. Briefly, PBMNC from five healthy donors were isolated by Ficoll density gradient centrifugation, resuspended in EGM-2 medium (Cambrex) and placed into a six-well-plate coated with type I collagen (from kangaroo, Sigma-Aldrich). After 24 h, non-adherent cells were removed by changing the medium. Autologous ECFC were spiked into PBMNC of the corresponding donor at frequencies ranging from 0.001 to 1%.</p>", "<title>Flow cytometry</title>", "<p>Flow cytometric detection and enumeration of of CEC/CEP was carried out according to a recently published protocol [##REF##17446880##14##]. Except for the anti-CD34 antibody monoclonal antibodies were chosen exactly as suggested by the authors. In brief, after Fc-blocking (Fc-receptor blocking antibody, Miltenyi Biotec) PBMNC were incubated in triplicates with antibodies specific for CD31-FITC (BD Pharmingen), CD34-PC7 (Beckman Coulter), CD45 PerCP (BD Pharmingen), CD133-PE (Miltenyi Biotec) or VEGF-R2 (KDR)-PE (R&amp;D Systems). Appropriate fluorochrome-conjugated isotype-matched murine IgG antibodies (BD Pharmingen) were used as controls for each staining procedure. After incubation for 30 min at 4°C, cells were washed, resuspended in 300 mL PBS and analyzed in a Cytomics-FC-500 cytometer using the Cytomics RXP-Software (Beckman Coulter; figure ##FIG##1##2##). CEC were defined as CD31⁺/CD34⁺/CD45^-/CD133^-and CEP were defined as CD31⁺/CD34⁺/CD133⁺/CD45^-/lowcells. All experiments were carried out in triplicates with analysis of at least 5 × 10⁵cells per run.</p>", "<title>Quantitative PCR</title>", "<p>RNA was purified by cell lysis of 5 × 10⁵PBMNC and nucleic acid extraction using of the RNeasy Kit (Qiagen). Extracted total RNA was transcribed into cDNA with oligo-dT- und hexanukleotide-random-primers and the AMV-Reverse Transcriptase (all Promega). For qPCR analysis in the 20 ng of each cDNA were used in triplicates. 5 μL Sybr-green Mix (Bio-Rad), and 10 pMol of each primer were mixed to the cDNA sample. Primer sequences and PCR conditions are listed in table ##TAB##1##2##. Instead of determining the ubiquitously expressed CD31 gene we assessed gene expression of the more specific endothelial marker CD144. Analysis was carried out in a Bio-Rad iCycler using the iCycler Software (Bio-Rad). Efficiency of the used primer pairs was determined by logarithmic dilutions of a highly concentrated cDNA template. Relative quantification and statistical data analysis of triplicates per sample was done according to the delta-Ct method described by Pfaffl et al. [##REF##11328886##15##].</p>", "<title>External standards</title>", "<p>For absolute quantification CD34, CD133, KDR and CD144 cDNAs were subcloned by the use of the PCR-Script cloning kit (Stratagene). Plasmid copies were calculated as follows: amount (copies/μL) = 6 × 10²³(copies/mol) × concentration (g/μL)/MW (g/mol). Standard curves were generated by logarithmic dilutions of triplicates of the amplicon-containing plasmids in a complex matrix of COS-7 cDNA. These external standard curves were used to calculate copy numbers per μg total RNA in all PBMNC samples using the iCycler software (BioRad).</p>", "<title>Statistical analysis</title>", "<p>Statistical analysis was performed with the GraphPad Prism 5 software for Windows. All tests of statistical significance were two-sided. Student's t-test was used for the analysis of spiking experiments. Kruskal Wallis H test was applied to study differences between healthy controls, rectal cancer patients and NSCLC patients.</p>" ]

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[ "<title>Discussion</title>", "<p>Recently, CEC and CEP have been suggested as surrogate markers for angiogenesis and response to antiangiogenic therapy in cancer [##REF##16543470##10##]. Flow cytometric rare event analysis, currently the most commonly applied method for CEC/CEP assessment, is technically demanding due to a high level of \"background noise\", i.e. false positive events due to autofluorescence, cell clumps and non-specific staining of other cell types such as monocytes, lymphocytes, non-lysed erythrocytes, aggregated platelets [##REF##17252604##11##], dead cells or endothelial microparticles. Furthermore, technical aspects such as inadequate cleaning of the cytometer, blocking, washing and lysing procedures may impact the flow-cytometric analysis. Even with freshly drawn blood and standardized technical workup non-specific binding of fluorochrome-matched isotype controls may be observed in up to 0.5% of cells analyzed markedly exceeding the anticipated number of CEC and CEP within the PBMNC fraction (0.01% to 0.0001%) [##REF##15668988##12##]. As a result, CEC/CEP measurements are virtually not comparable between different laboratories posing a major obstacle for the interpretation of the data published in the literature.</p>", "<p>The detection limit of 0.001% CEC/CEP in PBMNC determined for qPCR in our spiking experiments is compatible with frequencies of CEC/CEP in humans reported in the literature [##REF##15711737##1##] and well above the values determined by 4-color flow cytometry (i.e., 0.01%).</p>", "<p>However, despite markedly improved sensitivity determined in our spiking experiments we found normal endothelial marker gene expression when we applied qPCR to samples from patients with newly diagnosed locally advanced rectal cancer. This may be due to the rather low tumor burden in this study cohort as overall angiogenic activity depends not only on the tumor type but also on tumor load. When we analysed blood samples from patients with a high tumor burden, i.e., metastatic NSCLC, we found significantly elevated gene expression levels of CD34 and KDR which may indicate an elevated number of CEC. Importantly, these markers are not specific for endothelial cells and might as well reflect circulating hematopoietic progenitors due to tumor-associated inflammatory stimuli, metastatic cells or platelet contamination. This represents the major limitation of the qPCR methodology as applied in our study: gene transcript quantification is carried out on total RNA derived from PBMNC. Thus and in contrast to flow cytometry, qPCR does not allow to identify distinct cell types through simultaneous assessment of multiple markers on one cell and the detection of CD34 and KDR gene expression alone in PBMNC is by no means proof for CEC/CEP. But currently there are no specific CEC/CEP markers available, crucial for a valid molecular detection assay. Enrichment procedures (e.g., immunomagnetic beads for CD146) are currently being studied to improve CEC detection limits achievable with flow cytometry. However, it remains to be determined whether these labor-intensive techniques can provide the purity and cell numbers required for proper flow cytometric CEC enumeration.</p>", "<p>In conclusion qPCR is more sensitive, but less specific than 4-channel flow cytometry for the detection of CEC/CEP. Nevertheless, both methods failed to reliably detect an increase of CEC/CEP in tumor patients. However, despite significant improved detection limits by qPCR a single marker expressed specifically in CEP/CEC is hitherto missing. Such a marker would be crucial to achieve high specificity and to discriminate these rare cells from other cell populations of the peripheral blood. Thus, transcriptome analysis of sorted and functionally tested CEC/CEP might lead to the discovery of novel markers that can be used in real-time PCR-based assays.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Circulating endothelial cells (CEC) and endothelial precursor cells (CEP) have been suggested as markers for angiogenesis in cancer. However, CEC/CEP represent a tiny and heterogeneous cell population, rendering a standardized monitoring in peripheral blood difficult. Thus, we investigated whether a PCR-based detection method of CEC/CEP might overcome the limitations of rare-event flow cytometry.</p>", "<title>Findings</title>", "<p>To test the sensitivity of both assays endothelial colony forming cell clones (ECFC) and cord blood derived CD45^-CD34⁺progenitor cells were spiked into peripheral blood mononuclear cells (PBMNC) of healthy volunteers. Samples were analyzed for the expression of CD45, CD31, CD34, KDR or CD133 by 4-color flow cytometry and for the expression of CD34, CD133, KDR and CD144 by qPCR. Applying flow cytometry, spiked ECFC and progenitor cells were detectable at frequencies ≥ 0.01%, whereas by qPCR a detection limit of 0.001% was achievable. Furthermore, PBMNC from healthy controls (n = 30), patients with locally advanced rectal cancer (n = 20) and metastatic non-small cell lung cancer (NSCLC, n = 25) were analyzed. No increase of CEC/CEP was detectable by flow cytometry. Furthermore, only CD34 and KDR gene expression was significantly elevated in patients with metastatic NSCLC. However, both markers are not specific for endothelial cells.</p>", "<title>Conclusion</title>", "<p>QPCR is more sensitive, but less specific than 4-channel flow cytometry for the detection of CEC/CEP cell types. However, both methods failed to reliably detect an increase of CEC/CEP in tumor patients. Thus, more specific CEC/CEP markers are needed to validate and improve the detection of these rare cell types by PCR-based assays.</p>" ]

[ "<title>Findings</title>", "<title>CEC a heterogenous and rare cell type of the peripheral blood</title>", "<p>CEC have been shown to contribute significantly to angiogenesis in ischemia, inflammation, wound healing and tumor progression [##REF##15711737##1##]. In cancer patients CEC measurement in peripheral blood has been proposed a non-invasive tool to assess tumor angiogenesis [##REF##11369666##2##] and monitor antiangiogenic therapies [##REF##15652744##3##] CEC comprise a heterogenous cell population consisting of endothelial cells shed from the vessel wall [##REF##15585655##4##], bone marrow-derived CEP [##REF##17036040##5##] and endothelial precursors originating from monocytic cells [##REF##12615796##6##] (figure ##FIG##0##1##). CEC are only a tiny subset of the mononuclear cell fraction of peripheral blood rendering their quantification a challenging task. Endothelial colony formation assays are labor-intensive, time-consuming, poorly standardised and may give rise preferentially to monocytic cells [##REF##17053059##7##]. Currently, the most common technique applied for CEC quantification is multicolor flow cytometry. Based on this method absolute numbers of CEC reported in the literature vary greatly ranging from 0 to 7.900 CEC/mL in peripheral blood of healthy controls and from 5 to 39.000 CEC/mL under pathological conditions [##REF##11369666##2##,##REF##16807650##8##]. Thus, there is an urgent need for more reliable and standardized methods for CEC quantification.</p>", "<p>In this study both methods, flow cytometry and qPCR, were evaluated to compare the ability to detect mature peripheral blood-derived endothelial colony forming cells (ECFC; CEC phenotype) and cord blood-derived progenitors (CEP phenotype) spiked into PBMNC of healthy volunteers.</p>", "<title>Phenotype analysis of cord blood progenitor cells and ECFC by flow cytometry</title>", "<p>At first, the phenotypes of cord blood derived progenitor cells and ECFC was determined by flow cytometry (figure ##FIG##1##2##). As expected, ECFC were CD45^-CD31⁺(figure ##FIG##1##2A##). Further subtyping revealed that cells were CD34^-KDR⁺. Moreover, cells were CD133^-and CD144⁺(data not shown). Due to the two-step isolation procedure cord blood progenitor cells displayed a CD45^-/lowCD34⁺phenotype (figure ##FIG##1##2B##). The majority of CD34⁺cells displayed a CD31⁺CD133^-phenotype corresponding to hematopoietic precursor cells. In accordance with previous reports only a small subset of cells displayed a CD31⁺CD133^lowphenotype (5–10% of the CD34+ cells)[##REF##10648408##9##]. Therefore, only few cord blood-derived progenitor cells were detectable in the CEP window during the subsequent spiking experiments. Moreover, progenitor cells were KDR^-and CD144^-(data not shown).</p>", "<title>Detection of progenitors spiked into peripheral blood samples</title>", "<p>In five independent experiments cord blood derived progenitors from different donors were spiked in triplicates into PBMNC from healthy volunteers at concentrations ranging from 0.001 to 1%. As depicted in figure ##FIG##2##3A##, flow cytometry allowed detection of progenitors with a CEP phenotype at concentrations ≥ 0.01% (mean: 4 cells/10⁶PBMNC vs 1 cell in unspiked controls, p = 0.017).</p>", "<p>Quantification of both CD34 and CD133 gene transcripts proved to be a reliable approach for detecting spiked progenitor cells in PBMNC samples with 10-fold greater sensitivity than flow cytometry. At a frequency of only 0.001% progenitor cells were detectable by a 3.9-fold increased gene expression for CD133 (SD 2.2) and a 3.4-fold increase for CD34 (SD 2.3) in comparison to unspiked controls (p = 0.03; figure ##FIG##2##3B##). Although linear, the increase of CD34 and CD133 gene transcripts was not proportional to the number of cells spiked, possibly due to technical reasons (e.g., cell clumping) or cell death as progenitor cells are more fragile compared to mature cells. Due to their low expression on progenitors as described above, CD144 and KDR gene expression was not analyzed.</p>", "<title>Detection of ECFC spiked into peripheral blood samples</title>", "<p>In five independent experiments freshly detached autologous ECFC were spiked into PBMNC samples of the respective donor at concentrations ranging from 0.001 to 1%. Using flow cytometry ECFC spiked into PBMNC samples were detectable at frequencies ≥ 0.01% (mean: 68 cells/10⁶PBMNC vs 20 cells in unspiked controls, p = 0.004; figure ##FIG##3##4A##).</p>", "<p>QPCR was at least 10-fold more sensitive than flow cytometry for ECFC detection. Indeed, at a frequency of 0.001% relative gene expression of KDR was increased 48.3-fold (SD 52.1; p = 0.027) and that of CD144 40.8-fold (SD 58.5; p = 0.04) compared to unspiked controls (figure ##FIG##3##4B##). Due to their low expression level on ECFC as described above, CD34 and CD133 gene transcripts were not determined in this setting.</p>", "<title>Detection of CEC/CEP in peripheral blood of cancer patients and healthy volunteers</title>", "<p>Applying 4-color flow cytometry no significant differences concerning CEC/CEP numbers were found between cancer patients and age-matched healthy controls (figure ##FIG##4##5A##). We then applied qPCR for quantifying gene transcripts of endothelial progenitor cell markers CD34, CD133 and endothelial cell markers KDR and CD144. Overall, gene transcripts for CD34 and CD144 were found abundantly expressed (i.e., &gt;100 copies/μg RNA) in the total study cohort whereas only very few KDR or CD133 gene transcripts were detectable (figure ##FIG##4##5B##). Subgroup analysis showed no influence of gender, age or tumor stage on any of the markers studied. No significant elevation of any of the endothelial marker gene transcripts determined was found in locally advanced rectal cancer patients. In contrast, in the cohort of patients with metastatic NSCLC a significantly increased CD34 and KDR gene expression was found (p = 0.028 and p = 0.002, respectively).</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>MS and GU designed and coordinated the study, provided funding, analyzed the data and wrote the manuscript. JK carried out cell isolation assays and cell culture. MZ and AA provided rectal cancer samples, corresponding clinical data and performed RNA isolation. MB carried out flow cytometric analyses and qPCR assays. EG and GG participated in the design of the study, critical discussion of study data and writing of the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported by the Fellinger Krebsforschungsverein (MS) and the Austrian Science Fund NFN-92 (GU, EG). The funding bodies had no role in study design, collection, analysis and interpretation of data, writing and submission of the manuscript.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Hypothetical model of the origin and immunophenotypic characteristics of distinct subpopulations of circulating endothelial cells in peripheral blood</bold>. Pluripotent stem cells reside in the stem cell niche of the bone marrow and can give rise to \"hemangioblasts\" that have the capacity to differentiate into hematopoietic progenitor cells (HPC) or endothelial progenitors (EPC). EPC differentiate into circulating endothelial precursors (CEP) and circulating endothelial cells (CEC). HPC differentiate into myeloid cells such as monocytes, that can transdifferentiate into myeloid EC. Moreover, mature EC shed from the vessel wall can enter the circulation. Various subsets of circulating endothelial cell types have been demonstrated to contribute to tumor angiogenesis.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Four-color flow cytometric analyses of endothelial cells within human mononuclear cells</bold>. <bold>A) </bold>Staining for CD31, CD34, CD45 and KDR of PBMNC allows the detection of mature circulating endothelial cells. Top row: PBMNC sample of a healthy donor; lower row: autologous ECFC spiked into PBMNC from the respective healthy donor. <bold>B </bold>Staining for CD31, CD34, CD45 and CD133 of PBMNC allows the detection of circulating endothelial and progenitor cells. Top row: PBMNC sample of a healthy donor; lower row: cord-blood derived progenitors spiked into PBMNC from a healthy donor. Of note, only a small subset of cells displayed a CD34+ CD133 phenotype.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Detection of progenitor cells spiked into peripheral blood samples</bold>. A) Four-channel flow cytometric analysis of cord blood derived progenitor cells spiked into PBMNC (n = 5). Progenitors were spiked at frequencies ranging from 0.001 to 1% into PBMNC of a healthy donor. (* p &lt; 0.05 compared to unspiked controls). B) Quantitative PCR analysis of CEP marker gene expression in peripheral blood samples containing cord blood derived progenitor cells spiked at varying frequencies (0.001–1%; five independent experiments). Expression of CD34 and CD133 was analyzed in all samples relative to unspiked PBMNC. (* p &lt; 0.05 compared to unspiked controls).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Detection of ECFC in peripheral blood samples</bold>. <bold>A) </bold>Four-channel flow cytometric analysis of autologous ECFC spiked into PBMNC of the respective donor (n = 5). ECFC were spiked at frequencies ranging from 0.001 to 1%. (* p &lt; 0.05 compared to unspiked controls). <bold>B) </bold>Quantitative PCR analysis of ECFC marker gene expression in peripheral blood samples containing ECFC spiked at varying frequencies (0.001–1%; five independent experiments involving five different healthy donors). Expression of KDR and CD144 was analyzed in all samples relative to unspiked PBMNC. (* p &lt; 0.05 compared to unspiked controls).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Quantification of CEC and CEP in cancer patients and healthy controls</bold>. The content of CEC and CEP was determined by flow cytometry and qPCR in peripheral blood of patients with newly-diagnosed rectal cancer patients (n = 20), metastatic NSCLC patients (n = 25) and healthy controls (n = 30). Statistics were performed using the Kruskal Wallis H test. (<bold>A</bold>) Applying flow cytometry no difference was found concerning CEC/CEP detection in the peripheral blood of cancer patients and healthy controls. (Note the logarithmic scale.) (<bold>B</bold>) In comparison to healthy controls gene expression of endothelial cell markers CD34 and KDR was significantly elevated in patients with metastatic NSCLC but not in patients with newly-diagnosed localized rectal cancer patients. (* p &lt; 0.05; bars indicate mean +/- SD).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Patient characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Parameters</td><td align=\"center\"><bold>No. of patients</bold></td></tr></thead><tbody><tr><td align=\"left\">Rectal cancer patients</td><td align=\"center\">20</td></tr><tr><td align=\"left\">UICC stage I</td><td align=\"center\">6 (30%)</td></tr><tr><td align=\"left\">UICC stage II</td><td align=\"center\">5 (25%)</td></tr><tr><td align=\"left\">UICC stage III</td><td align=\"center\">9 (45%)</td></tr><tr><td align=\"left\">median age (years)</td><td align=\"center\">64</td></tr><tr><td align=\"left\">female</td><td align=\"center\">6 (30%)</td></tr><tr><td align=\"left\">NSCLC patients</td><td align=\"center\">25</td></tr><tr><td align=\"left\"> UICC stage IV</td><td align=\"center\">25 (100%)</td></tr><tr><td align=\"left\"> median age (years)</td><td align=\"center\">65</td></tr><tr><td align=\"left\"> female</td><td align=\"center\">10 (40%)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Genes and primer sequences used for qPCR</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Gene</bold></td><td align=\"left\">Sequence</td><td align=\"left\">Tm</td><td align=\"left\">Assay range cycles</td><td align=\"left\">Primer efficiency</td></tr></thead><tbody><tr><td align=\"left\"><bold>EF1A </bold>(EEF1A1)</td><td align=\"left\">For: 5-cacacggctcacattgca<break/>Rev:5-cacgaacagcaaagcgacc</td><td align=\"left\">86</td><td align=\"left\">12–30</td><td align=\"left\">98%</td></tr><tr><td align=\"left\"><bold>CD34 </bold>(HPCA1)</td><td align=\"left\">For: 5-tccagagacaaccttgaagc<break/>Rev: 5-cttcttaaactccgcacagc</td><td align=\"left\">85</td><td align=\"left\">18–32</td><td align=\"left\">100%</td></tr><tr><td align=\"left\"><bold>CD133 </bold>(PROM1)</td><td align=\"left\">For: 5-ttgcggtaaaactggctaag<break/>Rev: 5-tgggcttgtcataacaggat</td><td align=\"left\">81</td><td align=\"left\">20–36</td><td align=\"left\">100%</td></tr><tr><td align=\"left\"><bold>KDR </bold>(VEGFR2)</td><td align=\"left\">For: 5-gtggggattgacttcaactg<break/>Rev: 5-tgtgctgttcttcttggtca</td><td align=\"left\">85</td><td align=\"left\">17–35</td><td align=\"left\">98%</td></tr><tr><td align=\"left\"><bold>CD144 </bold>(CDH5)</td><td align=\"left\">For: 5-ttcatgacgtgaacgacaac<break/>Rev: 5-tccaccacgatctcatacct</td><td align=\"left\">89</td><td align=\"left\">17–35</td><td align=\"left\">84%</td></tr></tbody></table></table-wrap>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Transient Ischemic attacks (TIA) represent an opportunity to prevent strokes. Although the risk factors, evaluation and secondary prevention of TIA and stroke are comparable, TIA is conventionally considered a less urgent manifestation and therefore receives leisurely intervention [##REF##16545749##1##,##REF##15975320##2##]. Whether an intervention can prevent the development of stroke in patients presenting with TIA, has been an area of significant debate and research. In the interim, given the natural history, proper care and management should be provided to all patients with TIA [##REF##7820345##3##,##REF##16912978##4##]. The EXPRESS study has shown that early initiation of existing treatments after TIA or minor stroke was associated with an 80% reduction in the risk of early recurrent stroke [##REF##17928046##5##].</p>", "<p>TIA has been described as a stroke that lasts less than 24 hours. The American TIA Working Group proposed a new definition which states that a transient ischemic attack is a brief episode of neurologic dysfunction, caused by local brain or retinal ischemia, with clinical symptoms typically lasting less than one hour, and without evidence of cerebral infarction[##REF##12829866##6##]. The early estimated risk of stroke after a TIA is 8–12% at seven days and 11–15% at one month [##REF##12829866##6##,##REF##14981172##7##]. A study from California done on the short term prognosis of transient ischemic attacks revealed that in a 90 day period after a TIA, one in nine patients had a stroke and half of all the strokes occurred in the first 2 days [##REF##11147987##8##].</p>", "<p>Stroke is the leading cause of sustained neurological disability in the world [##REF##17239805##9##]. Two thirds of all strokes now occur in the developing world. South Asia represents a quarter of the emerging world and harbors 20% of the global stroke population [##REF##17239805##9##]. Approximately 15% of ischemic strokes are preceded by a TIA [##REF##14981172##7##]. Thus TIA represents an intervention opportunity in those most at risk.</p>", "<p>In Pakistan, non communicable disease now accounts for 41% of total disease burden. The National Health Survey of Pakistan (NHSP) estimates that Hypertension – the single most preventable cause of stroke and TIA – affects one in three adults aged greater than 45, and 19% of the population aged 15 and above. The NHSP showed that DM is present in 35% of adults greater than 45 years of age [##REF##16151442##10##]. Coronary artery disease can cause cardio embolic stroke and is a surrogate for atherosclerosis in the cerebrovascular system: a population based cross sectional survey showed a prevalence of 1 in 4 middle aged adults with men and women at equal risk [##REF##16086922##11##]. The overall prevalence of obesity is 28% in women and 22% in men. The prevalence of tobacco use is 40% in men and 12% in women [##REF##17060656##12##]. Various other factors, like unhealthy dietary patterns, low socio-economic strata and genetic predisposition in certain population groups, have repeatedly been identified [##REF##17239805##9##,##REF##16157712##13##, ####REF##16765468##14##, ##REF##15368804##15##, ##REF##12870308##16####12870308##16##]. Adding to this, other challenges like the lack of knowledge of TIA symptomatology, diagnosis and awareness of its serious implication at the primary health care level, and where these patients may present to, make the awareness and proper management of TIA patients all the more important [##REF##12743226##17##,##REF##17903931##18##]. The presentation, natural history and prognosis of TIAs are not known for Pakistan, where the risk profile and population is very different from Caucasian cohorts.</p>", "<p>The objective of this study is to describe the base line characteristics, presentation and the current management of TIA events in daily clinical practice in a tertiary care hospital in a developing country. This information would help prevent stroke in those most at risk of developing this disease and will provide a comparison with findings from the Western countries.</p>" ]

[ "<title>Methods</title>", "<title>Study Design</title>", "<p>A retrospective chart review was conducted for inpatients who were admitted and diagnosed with TIA between January 2003 and December 2005 at the Aga Khan University (AKU), a teaching hospital in Karachi, Pakistan. Patients who were admitted and diagnosed with TIA, as defined by ICD 9 code, were included in this study. The definition of TIA was the sudden onset of neurologic deficit respecting a vascular territory with resolution of symptoms within 24 hours. The majority of TIAs actually resolve within 60 minutes, and most of these resolve within 30 minutes. Levy showed that the likelihood that symptoms will resolve completely within 24 hours is less than 15 percent if symptoms last more than 1 hour [##REF##3362360##19##]. In the emergency room, all patients who present with TIA are offered admission for 24 hours.</p>", "<p>These patients were diagnosed with TIA by the neurologist on service. The patients were evaluated in the emergency room and admitted in the hospital via the emergency room, or picked up as consultations from other in patient services e.g. TIA on internal medicine service. The neurologic consultant assigned the vascular diagnosis and the hospital coding service assigned the ICD 9 code number. 200 charts were selected after the approval of the Ethical Review Committee (AKU-ERC). 35 charts were either irretrievable or had incomplete data and hence, were excluded. Out of the remaining 165, seven were TIA mimics and not true cases of TIA, therefore these were excluded.</p>", "<title>Study Setting</title>", "<p>This is a hospital based survey conducted at the Aga Khan University Hospital (AKUH). AKUH is a tertiary care hospital in Karachi, Pakistan, with a total patient population of 334,393 outpatients and 32,500 inpatients yearly. Karachi is an urban city with a population of 20 million. This study population reflects the reported TIA rates of a non rural, multiethnic South Asian population in transition. During the study period (January 2003– December 2005) there were 1036 admissions for stroke. The stroke and TIA admissions came from all over the city, and from households that would be described as lower to middle class urban city dwellers. Thus this study is generalisable only as far as Asian \"population in transition\" (Omran's Theory of rural population being urbanized) [##REF##5155251##20##], which may be most at risk for non communicable disease. In the rural areas there are government run district health centers and the presentation and total numbers of TIAs are not known for Pakistan. There is also a lack of community based statistics.</p>", "<title>Data collection tool</title>", "<p>The main elements of the questionnaire, designed after a thorough review of literature, were the presenting symptoms, co-morbid illnesses, history of use of anticoagulants and antiplatelet agents, laboratory tests carried out, emergency room work up and the initial treatment, management in the stroke units and further follow-up of the patients to a minimum of three months with new stroke and its workup details. Risk factor definitions were</p>", "<p>a) Hypertension defined either as:</p>", "<p>1. Blood pressure &gt;140/90 mmHg or &gt;130/80 mmHg for diabetic patients (before stroke or at least one week after stroke), or</p>", "<p>2. Known hypertension and being treated with antihypertensives [##REF##14656957##21##].</p>", "<p>b) Overweight: BMI 25.0 – 29.9 kg/m²as defined by WHO [##UREF##0##22##]</p>", "<p>Obese: BMI ≥30.0 kg/m²as defined by WHO [##UREF##0##22##].</p>", "<p>c) Diabetes Mellitus as defined by any one of the following:</p>", "<p>1. Fasting plasma glucose level at or above 126 mg/dL (7.0 mmol/l)</p>", "<p>2. Plasma glucose at or above 200 mg/dL (11.1 mmol/l) 2 hours after a 75 gram oral glucose load as in a GTT.</p>", "<p>3. Random plasma glucose at or above 200 mg/dL (11.1 mmol/l)</p>", "<p>4. Known diabetic being treated with dietary modification, medication or both.</p>", "<p>d) Smoker: &gt;1 cigarette/day</p>", "<p>Ex-smoker: Stopped smoking ≥2 years ago</p>", "<p>e) Dyslipidemia defined as:</p>", "<p>1. Known case of dyslipidemia on treatment or TG &gt; 240 mg/dL</p>", "<p>2. Hypercholesterolemia: LDL &gt; 100 mg/dl [##UREF##1##23##].</p>", "<title>Data collection, analyses and follow up</title>", "<p>The data was collected by the sub-investigators and then entered and analyzed in SPSS 14.0. A qualified stroke neurologist classified the mechanism responsible for TIA according to the TOAST classification [##REF##7678184##24##].</p>", "<p>Descriptive statistics were run for age, delay in presentation, and duration of hospital stay, radiological data and laboratory tests. Cross-tabs were carried out and Chi-square tests were performed to find any association of delay in presentation, symptom at presentation, age and gender with management received, and for the comorbid illnesses, risk factors and initial treatment received by the TIA patients in the emergency room with recurrent TIA or new stroke development.</p>", "<p>All patients were given a 90 day follow up appointment in the outpatient clinic and telephone contact was established with the patients so as to remind them of their follow up appointments. Since all charts in the hospital for a single patient are linked (there are no separate inpatient and outpatient charts) it is possible to review follow up data as well.</p>" ]

[ "<title>Results</title>", "<p>Among 158 patients, 57.6% were male and 41.1% were female. The mean age of the patients was 60.23 ± 13.14 but the median age was 60, and the mode of the data for age was 58. The most common presenting symptom was motor impairment followed by speech difficulty. Table ##TAB##0##1## depicts the presenting symptoms of the patient population. The median for the delay in presentation to the hospital was 4 hours and the mean was 20 hours and 46 minutes.</p>", "<p>Table ##TAB##1##2## depicts the comorbid illnesses and risk factors of the patient population as well as a comparison with the sub group that developed new stroke.</p>", "<p>Table ##TAB##2##3## depicts the immediate management and interventions received by the patients.</p>", "<p>The most common type of TIA came out to be of undetermined and under investigated type (24.1%), followed sequentially by presumable cardioembolic (20.3%), large artery atherosclerosis (18.4%), probable lacunar warning syndrome (15.8%) and truly undetermined (1.3%).</p>", "<p>Out of the total 158 patients presenting with TIA, 9.5% developed stroke in the first year. Among them, 50% developed the stroke within 24 hours and 83.4% within 90 days following their initial TIA. All the strokes were diagnosed in hospital. These were all ischemic strokes. Although we did not look at ICH or SAH as predefined outcomes, these were not reported in the small number of outcome events that were studied.</p>", "<p>Significant associations were found between male gender and high LDL (p = 0.001), high triglycerides (p = 0.001) and positive history of smoking (p = 0.00). Increasing age was found to be associated with more sensory symptoms at presentation (p = 0.04). We found a significant association between the development of a new stroke after the initial TIA event with positive history of unstable angina (p = 0.00), high LDL, elevated triglycerides, low HDL (p = 0.01), time delay to presentation after onset of symptoms (p = 0.003) and with the length of hospital stay (p = 0.042). There was a positive association between speech symptoms at presentation and initial aspirin administration (p = 0.039). We found a negative association between initial treatment with clopidogrel and heparin, with new stroke (p = 0.021).</p>", "<p>We did not find any significant association between new stroke occurrence with administration of aspirin (p = 0.2) or statin (p = 1.0) as an initial treatment in the emergency room on presentation with TIA. This may be due to the small number of outcome events.</p>" ]

[ "<title>Discussion</title>", "<p>The high risk of stroke after a transient ischemic attack supports an approach involving rapid evaluation and initiation of treatment. Consensus guidelines on the management of TIA have been promulgated by the American Heart Association AHA and the National Stroke Association [##REF##7820345##3##]. With regard to finding the cause and diagnosis of TIA, our center has principally followed the AHA and NSA guidelines. We found that about 91% of the patients were diagnostically evaluated via at least one radiographic imaging modality. These diagnostic tests were done to identify or exclude etiologies of TIA requiring specific therapy, to assess modifiable risk factors, and to determine prognosis. Head MRI and CT were done in 53.2% and 27.2% of the cases respectively. The guidelines also recommend imaging the carotid arteries in all cases but in our study only 47.5% of patients underwent carotid imaging. The reason for the low number of carotid dopplers may be the perception held by the doctors that our population is different in terms of stroke causation. This perception is based on studies that suggest that Asians have more intracranial atherosclerosis [##REF##15769776##25##,##REF##15620858##26##]. The figures for neuroimaging are comparable with Western figures, as a national study on emergency department visits for TIA in the United States revealed that CT scan was performed on 56% patients and MRI on less than 5% of patients, though over the period of the study there was an increase in the trend to perform neuroimaging [##REF##16609106##27##]. Another study conducted in 4 regional stroke centers in Ontario revealed that diagnostic interventions were underutilized. CT scanning was performed in 58%, carotid Doppler ultrasonography in 44%, and MRI in 3% of patients [##REF##15051693##28##].</p>", "<p>Transient Ischemic attack, regarded as being the warning sign for stroke needs prompt evaluation and management [##REF##12829866##6##]. Majority of the patients in our study were provided robust evaluation but fewer received any immediate treatment, among which aspirin was the most common medicine administered. About 62.8% received immediate treatment, of which 44% got aspirin(27.2% of the total) while 19% got other anti-platelet medications. Statins and heparin constituted only a meager 12% together. The use of aspirin as an initial treatment is in accordance with the AHA guidelines. Aspirin use in the early phase after stroke or TIA reduces the risk of recurrence [##REF##15383482##29##]. However, we did not find any significant association between aspirin and the risk of stroke in our study. This may be because our sample size was very small with only 15 patients developing new stroke after the initial TIA. 39.2% of our patients received no immediate medical treatment which compares with the national study on emergency department TIA management in the United States in which 42% of patients received no immediate medical treatment [##REF##16609106##27##].</p>", "<p>It has been reported in several studies that age &gt; 60 yrs is a risk factor for stroke after TIA. The ABCD and California risk score systems have taken age &gt; 60 yr as a significant risk factor to predict future stroke after TIA [##REF##15993230##30##]. Our study did not find any association between age and stroke occurrence. Although the mean age of our patients was 60.23 ± 13.14, but the median age was 60 and the mode of the data for age was 58. This shows that in our region much younger population suffers from TIA and stroke. We attribute it to the dietary and genetic factors as previously described. This aspect should be further explored in terms of the factors behind this difference in the age at presentation.</p>", "<p>The most common risk factors prevalent in descending order of frequency were hypertension, hypercholesterolemia and diabetes respectively. This emphasizes the need to address these co-morbid illnesses for secondary prevention of stroke. Smoking has been found to be associated with stroke. In our study 20.9% were smokers but the documented counseling for smoking cessation was done in only 8.2% of the patients. This raises an important issue regarding prevention of stroke. We propose that all the smokers should be counseled for cessation in-hospital and on outpatient follow-up visits. Such an approach might help reduce the incidence of stroke among TIA patients that is attributable to smoking.</p>", "<p>Raised LDL and triglycerides were significantly associated with male gender (p = 0.001). In our study more male patients presented with TIA which is contrary to previous studies which identify female gender as a risk factor. The outcome of patients with TIA depends on a number of factors like the initial treatment received and comorbid illnesses. The delay in accessing hospital care and receiving treatment is also important. Our study showed that increased time delay of symptoms was associated with a prolonged hospital stay (p = 0.042) and increased incidence of stroke (p = 0.003).</p>", "<p>We were unable to deduce significant associations with risk factors and the occurrence of new stroke, probably because our sample size was small. We therefore recommend that further studies be carried out to find out various risk factors for stroke.</p>", "<p>In our study, 9.5% of TIA patients developed stroke, which is comparable to the international figure of 10.5% stroke conversion. Our study, also verified the findings in previous studies that the greatest risk of stroke after TIA is in the first 48 hours. 9.5% of our patients developed stroke and about 50% did so in the first 24 hours. There is significant underutilization of investigative modalities and the immediate medical management options for TIA. This adds to the preexisting lack of attention to preventive medicine. Data from Pakistan from the WHO_ PREMIS study that looked at patients that accessed primary care facilities – showed under utilization of prevention practices of quitting smoking, exercise, reduction of dietary salt intake and limited use of aspirin (83%), B Blockers (35%), ACEI (43%) and Statins (2.3%) [##REF##15769769##31##]. This study was limited to patients who visit outpatients facilities and are likely to differ from the general population in their health seeking behavior – the national situation regarding prevention is likely to be far worse than this sample.</p>", "<p>The stroke epidemic of the developing world disables individuals in their prime of life, and is mostly preventable [##REF##17239789##32##]. TIA represents an opportunity to intervene in those most at risk. 50% of the stroke conversions in our study occurred within the first 24 hours. A large percentage of these patients did not receive any immediate treatment. Hence a rapid evaluation is immensely important to prevent stroke and permanent neurologic sequelae in these patients and to thwart the expanding stroke morbidity and mortality in the developing world.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Transient ischemic attack (TIA) is described as a brief episode of neurological dysfunction caused by focal brain ischemia, with clinical symptoms typically lasting less than an hour, and without evidence of acute infarction. Recent studies depict TIA as a particularly unstable condition. Risk of stroke is greater than 10% in the first 90 days after an index TIA. The presentation, prognosis and intervention for TIA have not been reported in South-Asians in a developing country.</p>", "<title>Method</title>", "<p>A retrospective chart review was done for 158 patients who were admitted with the diagnosis of TIA, as defined by ICD 9 code 435, from January 2003 to December 2005 at the Aga Khan University Hospital, Karachi, Pakistan. The data was entered and analyzed in SPSS version 14.0.</p>", "<title>Findings</title>", "<p>Among 158 patients, 57.6% were male and 41.1% were female. The common presenting symptoms were motor symptoms (51.3%), speech impairment (43%), sensory impairment (34.8%) and loss of balance/vertigo (29.1%). The median delay in presenting to the hospital was 4 hours. Those with motor symptoms were found to present earlier. The study showed that only 60.8% of all the patients presenting with TIA received any immediate treatment out of which 44.7% received aspirin. Neuroimaging was used in 91.1% of the patients. Of all the TIA patients 9.1% converted to stroke with 50% doing so within the first 24 hours.</p>", "<title>Conclusion</title>", "<p>The natural history of TIA from this developing nation is comparable to international descriptions. A large percentage of patients are still not receiving any immediate treatment as recommended in available guidelines, even in a tertiary care hospital.</p>" ]

[ "<title>Authors' contributions</title>", "<p>AK conceived, designed the study and monitored its data quality, wrote manuscript and was involved in all stages of the study. FK, RR, SB, SJ collected data, drafted the manuscript and performed analysis. SZ assisted in formulating the final manuscript and performed exploratory analysis after review. All authors read and approved the final manuscript.</p>" ]

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[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Presenting symptoms of the patient cohort</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Presenting symptoms</bold></td><td align=\"left\"><bold>Frequency(%)</bold></td></tr></thead><tbody><tr><td align=\"left\">Motor symptoms</td><td align=\"left\">51.3</td></tr><tr><td align=\"left\">Sensory symptoms</td><td align=\"left\">34.8</td></tr><tr><td align=\"left\">Difficulty or loss of speech</td><td align=\"left\">43.0</td></tr><tr><td align=\"left\">Vertigo or loss of balance</td><td align=\"left\">29.1</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>A comparison of risk factors in TIA patients versus new stroke patients</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Characteristics</bold><break/></td><td align=\"left\"><bold>Frequency(%)</bold><break/><bold>TIA patients</bold></td><td align=\"left\"><bold>Frequency(%)</bold><break/><bold>New stroke patients</bold></td></tr></thead><tbody><tr><td align=\"left\">Hypertension</td><td align=\"left\">122(77.2)</td><td align=\"left\">12(80.0)</td></tr><tr><td align=\"left\">Diabetes</td><td align=\"left\">61(38.6)</td><td align=\"left\">4(26.7)</td></tr><tr><td align=\"left\">Stable angina</td><td align=\"left\">10(6.3)</td><td align=\"left\">2(13.3)</td></tr><tr><td align=\"left\">Unstable angina</td><td align=\"left\">9(5.7)</td><td align=\"left\">2(13.3)</td></tr><tr><td align=\"left\">Previous myocardial infarction</td><td align=\"left\">23(14.6)</td><td align=\"left\">0(0.0)</td></tr><tr><td align=\"left\">Congestive heart failure</td><td align=\"left\">5(3.2)</td><td align=\"left\">0(0.0)</td></tr><tr><td align=\"left\">Peripheral vascular disease</td><td align=\"left\">2(1.3)</td><td align=\"left\">5(33.3)</td></tr><tr><td align=\"left\">Hypercholesterolemia</td><td align=\"left\">72(45.6)</td><td align=\"left\">6(40.0)</td></tr><tr><td align=\"left\">Obesity</td><td align=\"left\">18(11.4)</td><td align=\"left\">1(6.7)</td></tr><tr><td align=\"left\">Coagulopathy</td><td align=\"left\">6(3.8)</td><td align=\"left\">1(6.7)</td></tr><tr><td align=\"left\">Atrial fibrillation</td><td align=\"left\">8(5.1)</td><td align=\"left\">1(6.7)</td></tr><tr><td align=\"left\">History of smoking</td><td align=\"left\">33(20.9)</td><td align=\"left\">3(20.0)</td></tr><tr><td align=\"left\">Prior use of at least one Medication (for any disease)</td><td align=\"left\">119(75.3)</td><td align=\"left\">13(86.7)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Immediate therapeutic and diagnostic interventions performed on the patient population</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Initial management</bold></td><td align=\"left\"><bold>Frequency(%)</bold></td></tr></thead><tbody><tr><td align=\"left\">Percentage receiving any form of initial treatment</td><td align=\"left\">60.8</td></tr><tr><td align=\"left\">No immediate treatment</td><td align=\"left\">39.2</td></tr><tr><td align=\"left\">Initial aspirin</td><td align=\"left\">27.2</td></tr><tr><td align=\"left\">Other antiplatelet (Clopidogrel and Persantin)</td><td align=\"left\">12.7</td></tr><tr><td align=\"left\">Statins</td><td align=\"left\">1.9</td></tr><tr><td align=\"left\">Heparin</td><td align=\"left\">6.3</td></tr><tr><td align=\"left\">Low molecular weight heparin</td><td align=\"left\">8.2</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Radiological diagnostic modalities</bold></td><td align=\"left\"><bold>Frequency(%)</bold></td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\">One or more radiological diagnostic modalities</td><td align=\"left\">91.1</td></tr><tr><td align=\"left\">MRI</td><td align=\"left\">53.2</td></tr><tr><td align=\"left\">Carotid dopplers</td><td align=\"left\">47.5</td></tr><tr><td align=\"left\">MRA</td><td align=\"left\">41.8</td></tr><tr><td align=\"left\">CT Scan</td><td align=\"left\">27.2</td></tr><tr><td align=\"left\">Echocardiography</td><td align=\"left\">57.6</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Initial counseling</bold></td><td align=\"left\"><bold>Frequency(%)</bold></td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\">Documented counseling for smoking cessation</td><td align=\"left\">8.2</td></tr></tbody></table></table-wrap>" ]

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[ "<title>Background</title>", "<p>Treatment of chronic sinusitis is a well-established procedure in traditional Chinese acupuncture, and acupuncture is commonly used to relieve sinusitis and nasal symptoms [##REF##10865572##1##, ####REF##11713120##2##, ##REF##16686397##3####16686397##3##]. The symptoms of chronic sinusitis are not easy to measure or quantify, and health-related quality of life (HRQoL) has recently gained increasing awareness as an outcome measure for interventions in chronic sinusitis [##REF##7711687##4##, ####REF##7715384##5##, ##REF##15867652##6####15867652##6##].</p>", "<p>Previous studies have reported a favourable effect of acupuncture in children and young adults with chronic maxillary sinusitis, compared with antibiotics and laser acupuncture [##REF##7183207##7##], and that acupuncture is effective in sinusitis or sinus pain [##REF##6145308##8##,##REF##16055451##9##]. Recently, we reported only a nonsignificant advantage of conventional treatment compared with acupucture on symptoms in a three-armed randomized study for CT-verified chronic sinusitis [##REF##15907672##10##]. The report focused on changes in symptoms, sinus soft tissue swelling on CT, and the two SF-36 component summary scales. However, in the study we also included a disease-specific outcome measure, the Chronic sinusitis survey (CSS), which was not validated in Norwegian at the time, but that might be more sensitive to change than the other HRQoL measures [##REF##7711687##4##].</p>", "<p>In the present study, we report the full HRQoL outcomes from this trial of conventional medical treatment, traditional Chinese acupuncture and minimal acupuncture at non-acupoints for CT-verified chronic sinusitis.</p>" ]

[ "<title>Methods</title>", "<title>Subjects, study design and interventions</title>", "<p>We included patients &gt;17 years of age with sinusitis symptoms for &gt;3 months and sinus swelling, fluid retention, or opacification on CT after screening &gt;500 patients with sinusitis. We excluded patients if they were pregnant, had previously had acupuncture treatment, had been operated on for chronic sinusitis, had polypous sinusitis or pansinusitis, or used medication that could influence the results of the study. In total, 66 patients were included between 1996 and 2000. We recruited patients from one ear-nose-throat practice and advertised the study in local newspapers and a magazine. One otorhino-laryngologist examined and included all patients. He allocated them to one of three groups according to a six-block randomization algorithm, by first assigning a patient number to each patient. He then phoned one of the acupuncturists to receive information about the group allocation for that particular patient [##REF##15907672##10##]. The groups were (1) conventional medical therapy, (2) traditional Chinese acupuncture (TCA), or (3) minimal acupuncture at non-acupoints (sham). No patients were included between February and September to avoid influence from seasonal allergies.</p>", "<p>All patients in the conventional medical therapy group used xylometazoline as local vasoconstrictor, and 0.9% sodium chloride solution locally for one week, and oral corticosteroids for 14 days. In addition, 14 patients used cefalexin 1500 mg daily for 10 days and six used azithromycin 500 mg for 7 days.</p>", "<p>Both acupuncture groups had 10 treatments with bilateral acupoints over 4 weeks, performed by the same experienced acupuncturists with 4–10 years of experience and with experience in the treatment of chronic sinusitis. The TCA group patients had individual TCM diagnoses and treatment using 1.0–1.5 cun needles (Ø 0.28 mm, length 25–40 mm). The needles were inserted to from 0.5 cun (facial/hand/feet area) to a maximum of 1.3 cun (arms/legs/trunk area) depth to achieve a good needle sensation, stimulated manually using reducing or reinforcing methods and left in the acupoints for 25 minutes [##REF##15907672##10##,##UREF##0##11##].</p>", "<p>In the sham treatment group, the patients were given minimal acupuncture at non-acupoints outside the meridians. One point was situated on each shoulder between LI 15 and TE 14, one on each thigh 3 cun above the midpoint of the patella, and two bilateral points were situated 2.5 cun lateral to the umbilicus. For the sham group, we used 0.5 cun needles (Ø 0.25 mm, length 13 mm) A shallow, superficial insertion of the needle (maximum depth 0.25 cun) and minimal needle sensation was emphasized. The needles were left in the points for 25 minutes[##REF##15907672##10##,##REF##10356376##12##]. We applied the same sham points during each treatment session. In all treatment groups, medication used for other indications remained unchanged.</p>", "<title>Outcome assessment</title>", "<p>The participants responded to a questionnaire in the physician's office at baseline and after 12 weeks, including the Chronic sinusitis survey and Short Form 36 questionnaires.</p>", "<title>Chronic sinusitis survey</title>", "<p>The Chronic sinusitis survey (CSS) is a 6-item duration-based, sinus-specific questionnaire with a symptom and a medication subscale for use in chronic sinusitis [##REF##7711687##4##,##REF##7715384##5##,##REF##9230316##13##]. Scores were reported on a 0–100 scale, where 100 represents minimal symtoms or medication use. The Norwegian version of the CSS has only recently been validated [##REF##16677392##14##].</p>", "<title>Short form 36</title>", "<p>The Short form 36 (SF-36) assesses eight dimensions of health status including physical functioning, role limitations due to physical problems, bodily pain, general health, vitality, social functioning, role limitations due to emotional problems, and mental health [##UREF##1##15##,##REF##8277801##16##]. The scales were scored from 0 (lowest level of functioning) to 100 (highest level of functioning). The SF-36 has been extensively validated [##UREF##1##15##,##REF##8277801##16##] and used in subjects with chronic rhinosinusitis [##REF##9230316##13##,##REF##10580223##17##, ####REF##10718411##18##, ##REF##11554654##19####11554654##19##]. We used the Norwegian standard SF-36 version 1.2 [##REF##9868748##20##].</p>", "<title>Statistical analysis</title>", "<p>Descriptive statistics are presented with means and SDs, or percentages. We compared changes in HRQoL from baseline to 12 weeks between groups using one-way analysis of variance with post-hoc Tukey's test because of multiple comparisons.</p>", "<p>The required sample size was initially estimated to two groups of 22 patients, to detect a group difference of 0.85 SD on a visual analog scale, with power 0.8 and a 5% confidence level. Before study start, the study protocol was adjusted to include a third arm with 22 patients [##REF##15907672##10##].</p>", "<p>We omitted pairwise comparisons of changes on the CSS medication effects and total scales involving the conventional treatment group, because medication was part of the protocol for this group.</p>", "<p>We chose a 5% confidence level, using two-sided tests. The Regional Committee for Medical Research Ethics and The Norwegian Data Inspectorate approved the study.</p>" ]

[ "<title>Results</title>", "<p>The intervention groups were reasonably balanced (Table ##TAB##0##1##). On baseline sinus CT, three patients in the conventional medicine group had opacification, six in the sham group, and eight in the TCA group. Only two patients in the TCA group had baseline fluid retention.</p>", "<p>The completion rate at 12 weeks was 17/25 in the TCA group, 15/19 in the sham group, and 17/21 in the conventional medicine group. Completers, who responded to the sinusitis symptoms scale of the CSS at baseline and after 12 weeks (n = 47), were somewhat older, had had chronic sinusitis longer, and had better baseline CSS and SF-36 scores on all subscales than dropouts (n = 18) after 12 weeks, although only the differences on the SF-36 General health (p = 0.03) and Social functioning scales (p = 0.04) were statistically significant. From baseline to 12 weeks, there was a trend to improvement on the CSS sinusitis symptoms scale in all three allocation groups, but there was no statistical difference in the changes between groups (Table ##TAB##1##2##).</p>", "<p>In the conventional treatment group all eight SF-36 scales improved over the 12-week period (Table ##TAB##1##2##). Only two comparisons of the improvements were statistically significant: conventional medicine vs. sham on the Role-physical scale and conventional medicine vs. TCA on the Mental health scale. There was no statistical difference between TCA and sham on any of the SF-36 scales (Table ##TAB##1##2##).</p>" ]

[ "<title>Discussion</title>", "<p>In this study of patients with CT-verified chronic sinusitis, there was a small improvement on the CSS sinusitis symptom scale in all three groups over 12 weeks. The improvement was largest for conventional treatment, however statistically not significantly different from the change in the two other allocation groups. On the eight SF-36 scales, there were only significant differences in favor of the conventional group on one scale compared with TCA and on one scale compared with sham.</p>", "<p>The short-term changes in the present report are in line with our previous report using CT soft tissue swelling, symptoms and summary scales of the SF-36 as outcomes [##REF##15907672##10##]. Comparison with other studies is difficult because of differences in criteria for establishing the diagnosis of sinusitis, patient selection, lack of feasible control groups, and use of different outcomes [##REF##7183207##7##]. There was some difference in the proportion of patients with opacification on sinus CT between the randomized groups. In this randomized study, this distribution was by chance. We have no reason to believe that this influenced the outcome of the study. Further, we cannot exclude that some of the patients may have had symptoms of perennial rhinitis, though we have no reason to believe that this contributed to a difference in outcome between the three groups.</p>", "<p>A strength of the present study is the randomized design and the blinding of the patients to the type of acupuncture given. We used validated instruments for HRQoL assessment; the disease-specific CSS and the well-known SF-36. The small sample size, and the three intervention groups, which required adjustment for multiple comparisons, limited the study power. It is possible that the study was underpowered, and that the differences in favor of the conventional treatment group would have been statistically significant in a larger study.</p>", "<p>We used minimal acupuncture at non-acupoints to emulate TCA, using a penetrating or invasive sham procedure on points that were considered inappropriate for treatment of sinusitis. The lack of standardization of treatments may represent a limitation of the study. The TCA was not standardized, but tailored to the individual patient according to the traditional Chinese medicine diagnosis. Similarly, the conventional medical therapy was not entirely standardized, although all patients had a common core of local therapy and oral corticosteroids.</p>", "<p>Because we included only patients with CT-verified chronic sinusitis, only 10–15% of the examined patients were eligible. CT-verified sinusitis is poorly associated with symptoms [##REF##11868929##21##, ####REF##12222944##22##, ##REF##10392233##23####10392233##23##]. Therefore, one should be cautious with generalization beyond patients with CT-verified sinus soft tissue swelling. In clinical practice the treatment of sinusitis is initiated without CT scan, and the diagnosis of chronic sinusitis typically implies having had sinusitis symptoms for &gt;3 months. Finally, our patients had longer duration of chronic sinusitis, with mean symptom duration &gt;9 years, and therefore may represent a therapy-resistant population.</p>" ]

[ "<title>Conclusion</title>", "<p>We conclude that in this single blind randomized trial, there was no clear evidence of short-term improvement of one treatment over another. However, there was a non-significant advantage of conventional therapy, but this should be reassessed in a larger trial and with less restrictive inclusion criteria. There was no difference in change in HRQoL between TCA and minimal acupuncture at non-acupoints.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Acupuncture is commonly used to treat chronic sinusitis, though there is little documentation on the effect. This study presents the health-related quality of life (HRQoL) outcomes in a trial comparing traditional Chinese acupuncture, sham acupuncture, and conventional treatment for chronic sinusitis.</p>", "<title>Findings</title>", "<p>In a three-armed single blind randomized controlled study, we recruited 65 patients with symptoms of sinusitis &gt;3 months and signs of sinusitis on computed tomography (CT). Patients were randomized to one of three study arms: (1) 2–4 weeks of medication with antibiotics, corticosteroids, 0.9% sodium chloride solution, and local decongestants (n = 21), (2) ten treatments with traditional Chinese acupuncture (n = 25), or (3) ten treatments with minimal acupuncture at non-acupoints (n = 19). Change in HRQoL was assessed over 12 weeks using the Chronic Sinusitis Survey (CSS) and Short form 36 (SF-36) questionnaires.</p>", "<p>In the study, we found only a non-significant difference on the CSS symptom scale between conventional medical therapy and traditional Chinese acupuncture. On the SF-36 scale role-physical the change was larger in the conventional group than in the sham group (p = 0.02), and on the mental health scale the change in the conventional therapy arm was larger than in the traditional Chinese acupuncture group (p = 0.03). There was no difference in effect on HRQoL on any scale between the sham and traditional Chinese acupuncture groups.</p>", "<title>Conclusion</title>", "<p>There was no clear evidence of the superiority of one treatment over another on short-term HRQoL outcomes, although there was a statistically non-significant advantage of conventional therapy in a few dimensions.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>KS, ER and PGL participated in the study design and prepared the protocol. ER organized the data collection and was one of the acupuncturists. KS and PGL cleaned the data and performed the data analysis. KS drafted and revised the paper. ER and PGL critically reviewed and commented on the paper. All authors approved the final version.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Thanks to Oddveig Birkeflet and Lars-Erik Søholt for their important contribution to data collection and to Gunvor Ruus and Gaute Mehl for assistance during the study.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Patient baseline characteristics and HRQoL scores according to allocation group, mean (SD)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Acupuncture</bold></td><td align=\"center\"><bold>Sham</bold></td><td align=\"center\"><bold>Conventional</bold></td></tr></thead><tbody><tr><td align=\"left\">n</td><td align=\"center\">23–25</td><td align=\"center\">17–19</td><td align=\"center\">19–21</td></tr><tr><td align=\"left\">Women, number (%)</td><td align=\"center\">11 (44)</td><td align=\"center\">9 (47)</td><td align=\"center\">13 (62)</td></tr><tr><td align=\"left\">Age</td><td align=\"center\">41 (14)</td><td align=\"center\">47 (14)</td><td align=\"center\">42 (13)</td></tr><tr><td align=\"left\">Duration of chronic sinusitis in years</td><td align=\"center\">7 (8)</td><td align=\"center\">12 (14)</td><td align=\"center\">10 (11)</td></tr><tr><td align=\"left\"><italic>Chronic sinusitis survey</italic>¹</td><td/><td/><td/></tr><tr><td align=\"left\">Sinusitis symptoms</td><td align=\"center\">48 (23)</td><td align=\"center\">40 (24)</td><td align=\"center\">33 (31)</td></tr><tr><td align=\"left\">Medication effects</td><td align=\"center\">84 (21)</td><td align=\"center\">85 (16)</td><td align=\"center\">82 (15)</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">65 (16)</td><td align=\"center\">62 (16)</td><td align=\"center\">58 (15)</td></tr><tr><td align=\"left\"><italic>Short form 36</italic>²</td><td/><td/><td/></tr><tr><td align=\"left\">Physical functioning</td><td align=\"center\">77 (25)</td><td align=\"center\">85 (15)</td><td align=\"center\">86 (15)</td></tr><tr><td align=\"left\">Role – physical</td><td align=\"center\">48 (41)</td><td align=\"center\">61 (40)</td><td align=\"center\">54 (41)</td></tr><tr><td align=\"left\">Bodily pain</td><td align=\"center\">57 (22)</td><td align=\"center\">61 (25)</td><td align=\"center\">60 (25)</td></tr><tr><td align=\"left\">General health</td><td align=\"center\">48 (21)</td><td align=\"center\">71 (17)</td><td align=\"center\">60 (25)</td></tr><tr><td align=\"left\">Vitality</td><td align=\"center\">42 (24)</td><td align=\"center\">51 (21)</td><td align=\"center\">49 (23)</td></tr><tr><td align=\"left\">Social functioning</td><td align=\"center\">67 (27)</td><td align=\"center\">72 (23)</td><td align=\"center\">69 (28)</td></tr><tr><td align=\"left\">Role – emotional</td><td align=\"center\">61 (38)</td><td align=\"center\">69 (34)</td><td align=\"center\">67 (42)</td></tr><tr><td align=\"left\">Mental health</td><td align=\"center\">75 (16)</td><td align=\"center\">78 (11)</td><td align=\"center\">69 (21)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Change in HRQoL scores from baseline to 12 weeks, mean (SD) unless otherwise stated</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td/><td align=\"center\" colspan=\"3\"><bold>Change score</bold></td><td align=\"center\" colspan=\"9\"><bold>Mean difference between change scores</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"9\"><hr/></td></tr><tr><td/><td align=\"left\"><bold>(1) Acupuncture</bold></td><td align=\"left\"><bold>(2) Sham</bold></td><td align=\"left\"><bold>(3) Conventional</bold></td><td align=\"right\"><bold>(1) – (2)</bold></td><td align=\"right\"><bold>(95%CI)</bold></td><td align=\"right\"><bold>p</bold>³</td><td align=\"right\"><bold>(3) – (2)</bold></td><td align=\"right\"><bold>(95%CI)</bold></td><td align=\"right\"><bold>p</bold>³</td><td align=\"right\"><bold>(3) – (1)</bold></td><td align=\"right\"><bold>(95%CI)</bold></td><td align=\"right\"><bold>p</bold>³</td></tr><tr><td/><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\"><italic>n</italic></td><td align=\"left\"><italic>15–18</italic></td><td align=\"left\"><italic>14–16</italic></td><td align=\"left\"><italic>16–17</italic></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><italic>Chronic sinusitis survey</italic>¹</td><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Sinusitis symptoms</td><td align=\"left\">11 (23)</td><td align=\"left\">8 (24)</td><td align=\"left\">32 (41)</td><td align=\"right\">3</td><td align=\"right\">(-24 to 31)</td><td align=\"right\">0.96</td><td align=\"right\">24</td><td align=\"right\">(-3 to 51)</td><td align=\"right\">0.09</td><td align=\"right\">24</td><td align=\"right\">(-3 to 52)</td><td align=\"right\">0.14</td></tr><tr><td align=\"left\">Medication effects</td><td align=\"left\">-0.5 (18)</td><td align=\"left\">8 (22)</td><td align=\"left\">-10 (21)</td><td align=\"right\">-9</td><td align=\"right\">(-26 to 9)</td><td align=\"right\">0.44</td><td/><td/><td align=\"right\">*</td><td/><td/><td align=\"right\">*</td></tr><tr><td align=\"left\">Total</td><td align=\"left\">6 (15)</td><td align=\"left\">7 (18)</td><td align=\"left\">10 (24)</td><td align=\"right\">-1</td><td align=\"right\">(-19 to 17)</td><td align=\"right\">0.99</td><td/><td/><td align=\"right\">*</td><td/><td/><td align=\"right\">*</td></tr><tr><td align=\"left\"><italic>Short Form 36</italic>²</td><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Physical functioning</td><td align=\"left\">1 (16)</td><td align=\"left\">0.5 (13)</td><td align=\"left\">6 (17)</td><td align=\"right\">1</td><td align=\"right\">(-12 to 14)</td><td align=\"right\">0.99</td><td align=\"right\">5</td><td align=\"right\">(-8 to 18)</td><td align=\"right\">0.58</td><td align=\"right\">5</td><td align=\"right\">(-8 to 17)</td><td align=\"right\">0.68</td></tr><tr><td align=\"left\">Role – physical</td><td align=\"left\">-3 (48)</td><td align=\"left\">-12 (39)</td><td align=\"left\">28 (36)</td><td align=\"right\">9</td><td align=\"right\">(-44 to 25)</td><td align=\"right\">0.8</td><td align=\"right\">40</td><td align=\"right\">(5 to 75)</td><td align=\"right\">0.02</td><td align=\"right\">31</td><td align=\"right\">(-3 to 65)</td><td align=\"right\">0.08</td></tr><tr><td align=\"left\">Bodily pain</td><td align=\"left\">2 (23)</td><td align=\"left\">5 (23)</td><td align=\"left\">16 (20)</td><td align=\"right\">-3</td><td align=\"right\">(-21 to 15)</td><td align=\"right\">0.92</td><td align=\"right\">11</td><td align=\"right\">(-7 to 29)</td><td align=\"right\">0.33</td><td align=\"right\">14</td><td align=\"right\">(-4 to 32)</td><td align=\"right\">0.16</td></tr><tr><td align=\"left\">General health</td><td align=\"left\">2 (22)</td><td align=\"left\">-4 (18)</td><td align=\"left\">10 (21)</td><td align=\"right\">6</td><td align=\"right\">(-11 to 23)</td><td align=\"right\">0.67</td><td align=\"right\">14</td><td align=\"right\">(-3 to 31)</td><td align=\"right\">0.13</td><td align=\"right\">8</td><td align=\"right\">(-9 to 25)</td><td align=\"right\">0.48</td></tr><tr><td align=\"left\">Vitality</td><td align=\"left\">-1 (20)</td><td align=\"left\">4 (16)</td><td align=\"left\">13 (31)</td><td align=\"right\">-5</td><td align=\"right\">(-25 to 14)</td><td align=\"right\">0.8</td><td align=\"right\">8</td><td align=\"right\">(-11 to 28)</td><td align=\"right\">0.56</td><td align=\"right\">13</td><td align=\"right\">(-6 to 33)</td><td align=\"right\">0.21</td></tr><tr><td align=\"left\">Social functioning</td><td align=\"left\">7 (15)</td><td align=\"left\">5 (22)</td><td align=\"left\">15 (23)</td><td align=\"right\">1</td><td align=\"right\">(-15 to 18)</td><td align=\"right\">0.98</td><td align=\"right\">9</td><td align=\"right\">(-8 to 26)</td><td align=\"right\">0.4</td><td align=\"right\">8</td><td align=\"right\">(-9 to 24)</td><td align=\"right\">0.5</td></tr><tr><td align=\"left\">Role – emotional</td><td align=\"left\">-4 (36)</td><td align=\"left\">7 (31)</td><td align=\"left\">24 (40)</td><td align=\"right\">-10</td><td align=\"right\">(-41 to 20)</td><td align=\"right\">0.69</td><td align=\"right\">17</td><td align=\"right\">(-14 to 48)</td><td align=\"right\">0.4</td><td align=\"right\">27</td><td align=\"right\">(-2 to 57)</td><td align=\"right\">0.08</td></tr><tr><td align=\"left\">Mental health</td><td align=\"left\">-3 (10)</td><td align=\"left\">0 (12)</td><td align=\"left\">10 (20)</td><td align=\"right\">-3</td><td align=\"right\">(-15 to 9)</td><td align=\"right\">0.82</td><td align=\"right\">10</td><td align=\"right\">(-2 to 22)</td><td align=\"right\">0.12</td><td align=\"right\">13</td><td align=\"right\">(1 to 25)</td><td align=\"right\">0.03</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>¹0 (maximal) to 100 (minimal symptoms/medication use) scale, ²0 (lowest) to-100 (highest level of functioning) scale</p></table-wrap-foot>", "<table-wrap-foot><p>Change = last value-first value; a negative change score represents reductions in symptoms; * omitted because of medication use in the conventional treatment arm; ¹0 (maximal) to 100 (minimal symptoms/medication use) scale, ²0 (lowest) to-100 (highest level of functioning) scale; ³after adjustment for multiple comparisons</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Brown algae (Phaeophyceae) are multi-cellular marine organisms that grow along temperate, tropical and polar coasts. Many of them are subject to frequent changes in their local environment, because they are uncovered at low tide, and are hence exposed to desiccation, and to variations in osmotic pressure due to rain or evaporation. In addition, pollution of the coasts, due to human activities, constitutes an additional source of abiotic stress, to which they must develop adaptive mechanisms. Expression analyses of genes involved in the perception of the stress, and in the establishment of the appropriate responses, provide a means to decipher the molecular mechanisms potentially involved in such adaptations. Despite the availability of medium scale cDNAs libraries for several different species of the brown algae (<italic>Laminaria, Sargassum</italic>, and <italic>Fucus</italic>), this task has been hindered by the lack of genome-scale resources. In 2004, Peters et al. [##UREF##0##1##] have compared a range of features in several species of Phaeophyceae and concluded that <italic>Ectocarpus siliculosus </italic>was the best candidate to consider for such developments. Recently, the genome of this alga has been sequenced, offering a unique opportunity to survey the expression of gene families in brown algae (Genoscope, J.M. Cock, unpublished data). <italic>E. siliculosus </italic>is a small filamentous alga, extensively studied over the last two centuries for its complex life cycle and its physiological features (reviewed in [##REF##18181960##2##]). The genome is currently being annotated, allowing the initiation of both large scale and targeted surveys of the <italic>Ectocarpus </italic>genes, such as microarrays or real-time RT-PCR respectively.</p>", "<p>Compared to high-throughput microarray techniques, real-time quantitative RT-PCR only allows assays of gene expression to be carried out at relatively low throughput (10–20 genes in 10–50 samples). Nonetheless, this technique has been adopted by a large community as a standard method for gene expression studies, because of its high reliability, and its rapidity of execution [##REF##15208338##3##,##REF##15956331##4##]. This technique is now widely used for a large number of animal and plant organisms, as well as for bacteria and viruses.</p>", "<p>A few years after the emergence of this technique, a need for a reliable normalisation method became insistent. Different methods of identifying normalisation genes, such as geNorm [##REF##12184808##5##], NormFinder [##REF##15289330##6##] and BestKeeper [##REF##15127793##7##], were then developed. This was followed by a wave of reports on the identification of the best normalisation genes from a broad range of species and specific tissues. These biological materials included human tissues [##REF##18042273##8##, ####REF##18096027##9##, ##REF##18226276##10####18226276##10##] and viruses [##REF##18053162##11##], as well as tissues from a variety of animals such as cow [##REF##17559642##12##], pig [##REF##17540017##13##], horse [##REF##16643647##14##], dolphin [##REF##16984641##15##], fishes [##REF##18230138##16##,##REF##16139890##17##], worm [##REF##18211699##18##] and others. In parallel, a similar extension of the use of this technique was observed in plant research, for rice [##REF##16690022##19##], poplar [##REF##15317655##20##], potato [##REF##16188960##21##], grapevine [##REF##17105665##22##], and for plant pathogens [##REF##17888160##23##].</p>", "<p>In the brown alga <italic>E. siliculosus</italic>, the expression level of 20 genes specific to the two generations in the life-cycle of this alga was recently reported in a mutant impaired in development [##REF##18339673##24##]. Additional developmental and physiological studies are underway, including studies aimed at assessing the resistance of this alga to environmental changes. Hence, the availability of a set of housekeeping genes for normalising the expression levels of genes of interest is a pre-requisite to any valuable conclusion, especially since this organism lives in a frequently changing environment.</p>", "<p>In this paper, we propose optimal normalisation genes for expression analyses in <italic>E. siliculosus</italic>. Thirteen housekeeping genes that have been reported to be good potential candidates in the previously cited literature, were chosen for this task. Their expression was examined by Q-RT-PCR in a diversity of algal samples corresponding to growth kinetic series, osmotic stress experiments, and chemical treatments. Namely, the candidate genes are involved in the synthesis and the dynamics of the cytoskeleton, in the synthesis, folding and degradation of proteins, and in the metabolism of carbon, all of these processes being known to be only moderately affected by the fluctuation of growth conditions.</p>" ]

[ "<title>Methods</title>", "<title>Culture conditions and treatments</title>", "<p><italic>E. siliculosus </italic>(Ectocarpales, Phaeophyceae) unialgal strain 32 (CCAP accession 1310/4, origin san Juna de Marcona, Peru) was cultivated in 10 L plastic flasks in a culture room at 14°C using filtered and autoclaved natural seawater enriched in Provasoli nutrients [##UREF##3##33##]. Light was provided by Philips daylight fluorescence tubes with a photon flux density of 40 μmol. m-².s^-1for 14 hours per day. Cultures were bubbled with filtered (0.22 μm) compressed air to avoid CO₂depletion. To conduct the chemical treatment experiments, algal tissues were transferred into Petri dishes containing artificial seawater enriched with Provasoli (ASW) for at least 18 h before treatments in order to acclimatize the cultures to the change of growth conditions. They were then treated with different chemicals for 3 and/or 6 h (see Table ##TAB##0##1##) during the light phase. The treatments were 10 mM H₂O₂(final concentration), 42 μg.L^-1Diuron, 55 μg.L^-1atrazine, 5 μM 13-HOTrE and 15(S)-HEPE. Algae were also incubated in 10 μM CuSO₄for 3 and 6 h. An equal volume of solvent (ASW or DMSO 1%) was used in each corresponding control treatment. Wounding was carried out by damaging the tissues with a razor blade. To perform saline stress and an additional H₂O₂treatment, tissues were transferred to ASW for one week before applying the stress. The NaCl concentration in control ASW was 450 mM, while it was 60 mM and 1.5 M in ASW used to submit the alga to hyposaline and hypersaline conditions respectively. In addition, H₂O₂was added at 1 mM final concentration to the control ASW for generating oxidative stress. Treatments were applied for 6 h before harvesting the tissues for RNA extraction. To collect samples through the diurnal cycle, algae were incubated in ASW and tissue harvested every 6 h during one day. The first sample was taken 30 min after the beginning of the light period. The summary of the culture conditions is presented in Table ##TAB##0##1##.</p>", "<p>Three biological replicates were obtained for each treatment and these were used for total RNA extraction.</p>", "<title>RNA extraction</title>", "<p>The protocol used for RNA extraction was based on the method developed by Apt et al. [##REF##7891659##34##] with some modifications. Frozen tissue was ground in liquid nitrogen and immediately incubated in the presence of extraction buffer (100 mM Tris-HCl pH 7.5, 2% CTAB, 1.5 M NaCl, 50 mM EDTA, 50 mM DTT). The sample was shaken at room temperature for 30 min, then one volume of chlorophorm:isoamylic alcohol (24:1, V/V) was added and the sample shaken again for 25 min. After centrifugation, the upper phase was transferred to a new tube and mixed with 0.3 V of absolute ethanol to precipitate the polysaccharides, and extracted with 1 V of chlorophorm. After centrifugation the upper phase was transferred to a fresh tube and RNA was precipitated by addition of 0.25 V of 12 M LiCl and β-mercapto-ethanol to 1% final concentration, overnight at -20°C. After centrifugation, the pellet was resuspended for DNAse treatment by an RNAse-free DNAse I (Turbo DNAse, Ambion) according to the manufacturer's instructions, in order to eliminate any residual genomic DNA from the preparation. An extraction was then carried out by adding Phenol-Chlorophorm (1:1, V/V). After centrifugation the upper phase was transferred to a fresh tube, and extracted with 1 V of chlorophorm:isoamylic alcohol (24:1, V/V) and centrifuged again. The upper phase was precipitated with 0.3 M NaAc pH 5.5 and 75% ice cold ethanol by incubating overnight at 20°C. After centrifugation, the supernatant was removed, and the pellet washed with 80% ethanol. After centrifugation and drying on ice, the pellet was resuspended in an appropriate volume of RNAse-free water.</p>", "<title>Quantification of RNAs and cDNA synthesis</title>", "<p>Nucleic acid concentrations were measured by the absorbance at OD₂₆₀using a NanoDrop ND-1000 spectrophotometer. The purity of the RNA samples was assessed by measuring the ratio OD₂₆₀/OD₂₈₀and OD₂₃₀/OD₂₆₀(see Additional file ##SUPPL##2##3##). RNA integrity was then verified on 1.5% agarose gel stained with ethidium bromide (see Additional file ##SUPPL##3##4##). From each RNA sample, 1.4 μg was reverse transcribed to cDNA using oligo(dT)_12–18and the Superscript™ First Strand synthesis for RT-PCR (Invitrogen) according to the manufacturer's instructions, and subsequently diluted with nuclease free water to 1 ng.μl^-1cDNA.</p>", "<title>Protocol for DNA extraction</title>", "<p>Frozen tissue was ground in liquid nitrogen and then in a wheaton potter with 15 ml of extraction buffer (100 mM Tris-HCl pH7.5; 1.5 M NaCl; 2% CTAB; 50 mM EDTA; 50 mM DTT) per g of wet tissue. The suspension was then mixed vigorously at room temperature for at least 30 min. Proteins were degraded with 25 units of proteinase K for 2 h at 55°C, and then extracted with chlorophorm/isoamyl alcohol for several minutes. Polysaccharides were precipitated with progressive addition of 0.2 – 0.3 V of ethanol, and then extracted with 1 V of chloroform after spinning at 10,000 g and 20°C for 20 min. Nucleic acids were recovered from the upper phase by addition of 0.25 V of 12 M LiCl and 1% of β-mercaptoethanol, incubation at -20°C overnight and spinning at 10,000 g and 4°C for 1 h. The supernatant was precipitated with 0.6 V isopropanol, 0.3 M NaAc pH 5.2, left at 4°C for 30 min, and then spun down for 30 min at 13,000 g. The pellet was then dissolved in 400 μl H₂O, and precipitated again with ethanol and NaAc. DNA was dissolved in 500 μl of TE (10 mM Tris-HCl pH 8.0; 1 mM EDTA), 5.4 M CsCl (density 1.66) and 250 μg.mL^-1of ethidium bromide. Spinning at 90,000 g for 24 h at room temperature allowed the recovery of a band containing ultrapure genomic DNA under UV. Ethidium bromide was extracted 4–5 times with TE-saturated butanol and CsCl eliminated by successive ethanol precipitations.</p>", "<title>Real-time PCR</title>", "<p>All the genes were quantified on the same lot of cDNAs, to minimize experimental variation that could be due to cDNA synthesis. For each gene, a pair of oligonucleotide sequences was designed in the 3' UTR of the genes when the sequence was known, or in the 3'coding sequence using Primer Express TM1.0 (PE Applied Biosystems, Foster City, CA, USA) (Table ##TAB##1##2##). The Q-PCR reactions were performed in a 96-well thermocycler (Biorad, Opticon) with SYBRgreen reaction mix from ABgene (AB-1162/B), for 15 min at 95°C, followed by 41 runs of 15 sec at 95°C and 1 min at 60°C. Each sample was technically duplicated. <italic>E. siliculosus </italic>genomic DNA was used as a quantification reference. A dilution series ranging from 37 to 48671 copies of the <italic>E. siliculosus </italic>genome was prepared and tested for each gene. The amplification efficiency was tested using this dilution series (Table ##TAB##1##2##). The specificity of amplification was checked with a dissociation curve obtained by heating the samples from 65°C to 95°C (Table ##TAB##1##2##). In addition to the DNAse-I treatments of RNAs, the absence of a genomic DNA contaminants was checked, by amplifying an intron sequence on the cDNAs. The number of copies of contaminant gDNA was subtracted from all other values, prior to any further analyses.</p>" ]

[ "<title>Results</title>", "<title>Treatments applied to <italic>E. siliculosus </italic>and choice of housekeeping genes</title>", "<p>Several different stresses were tested in this study. Chemical agents tested included H₂O₂, a reactive oxygen species produced by many organisms, including seaweeds, under conditions of abiotic and biotic stresses [##UREF##1##25##]. We also tested heavy metals such as copper, which are among the most significant pollution actors in marine environments worldwide. Diuron and atrazine are herbicides that inhibit photosynthesis by blocking the d1 protein of photosystem II [##REF##15276715##26##,##REF##11485216##27##]. Diuron is also an additive of antifouling paints, which prevent growth of organisms on ships' hulls. In addition pathogen or grazer attacks were mimicked by wounding <italic>E. siliculosus </italic>tissues with a razor blade. We also tested the effect of oxylipins. These are oxygenated derivatives of polyunsaturated fatty acids which play a major role in inflammatory processes, allergies, and, in a wide sense, defensive stress responses to infection, drugs, and xenobiotics [##REF##11729303##28##]. In land plants, C18 derived jasmonates play a pivotal role in defense induced mechanisms [##REF##12119169##29##]. In mammals, oxidation of the C20 arachidonic acid produces derivatives such as leukotriens and prostaglandins. As brown algae are able to produce oxylipins typical of both land plants and animals [##UREF##2##30##], their putative action on the induction of stress signalling pathways is of particular interest. Finally, as the metabolism and the physiology of brown algae are regulated to a large extent by diurnal rhythms, a time series of samples taken over a single day was also analysed.</p>", "<p>RNA was extracted from biological triplicates of algae that had received the above treatments resulting in a total of 63 samples for 21 different treatments (see Table ##TAB##0##1##, and Methods for details on concentration and timing). Single strand cDNA was synthesised simultaneously from each of the 63 extracts in order to minimize any variation during this step of the process. The abundance of the transcripts of 13 potential housekeeping genes was then assayed on these cDNAs. The genes tested included commonly used genes such as a ribosomal protein and translation initiation or elongation factors (eIF2A, eIF4E, EF1a, 26S ribosomal protein), cytoskeleton proteins (tubulin alpha, actin and actin-related proteins), and proteins involved in the protein degradation process (ubiquitin and ubiquitin-conjugating enzyme). In addition, cyclophylin, two actin-related proteins, a tubulin molecular motor (dynein) and an enzyme involved in the pentose phosphate pathway (glucose 6-phosphate dehydrogenase) were included in this study. The genes tested are listed in Table ##TAB##1##2##.</p>", "<title>Quantification and data analysis</title>", "<p>In order to assess whether the transcripts of these 13 genes remained at comparable levels in the different samples tested, we calculated the variation in the Ct value for each gene. Figure ##FIG##0##1A## shows that the transcripts of these genes exhibited different levels of abundance, with <italic>CYC </italic>being expressed at the lowest level, and <italic>UBQ </italic>being expressed the most strongly. Variation in transcript accumulation across the 21 culture conditions was not the same for all the genes tested. <italic>EF1a </italic>showed the weakest variation, while <italic>G6PD </italic>expression seemed to be strongly influenced by the treatments, its range of expression level exceeding 10 Ct (Figure ##FIG##0##1B##).</p>", "<p>In order to test the robustness of these data, we performed the geNorm pairwise analysis, which was first described by Vandesompele et al. [##REF##12184808##5##], and has since been widely used to evaluate the stability of expression of genes from many organisms. The results of this analysis (Figure ##FIG##1##2##) were slightly different from those obtained with the Ct value calculation. The two calculation methods identified the same least and most stably expressed genes (<italic>G6PD </italic>and <italic>CYC </italic>were the least stable, and <italic>TUA, EF1a </italic>and <italic>Dyn </italic>were the most stable), but the intermediate genes were ordered differently. This was particularly striking for <italic>ARP2.1 </italic>and <italic>UBCE</italic>, which the geNorm analysis indicated were the most stably expressed genes, and which the Ct value analysis indicated to be among the least stably expressed. In order to test whether averaging the biological triplicates had an effect on the final result, we performed the geNorm analysis using the transcript abundances measured in the 63 individual cDNA samples, as previously described [##REF##16166256##31##]. This analysis identified the same genes as having either highly variable (<italic>CYC, G6PD </italic>and <italic>ACT</italic>) or very stable (<italic>ARP2.1, UBCE, TUA</italic>, <italic>EF1a </italic>and <italic>Dyn</italic>) transcript abundances, but the order of the six remaining genes was again different (data not shown). Thus, averaging the biological replicates modified the results of the analysis for the intermediate genes, but not for the most and the least stable genes. A one-way ANOVA test showed that for most of the genes considered individually, the variance between the different culture conditions is significantly higher than the variance between the biological replicates for a given condition (see Additional file ##SUPPL##0##1##). Therefore, averaging on the three biological replicates should not introduce any significant distortion.</p>", "<p>NormFinder is another approach that has been used to assess the stability of expression of housekeeping genes [##REF##15289330##6##]. When NormFinder was applied to the data obtained in this study, it indicated that the genes with the most stable levels of transcript abundance were <italic>TUA, ARP2.1, EF1a </italic>and <italic>Dyn </italic>(Table ##TAB##2##3##). These were almost the same genes as the ones identified by geNorm, with the exception that <italic>Dyn </italic>performed better than <italic>UBCE</italic>. Therefore, there was a very good correlation between the results obtained from geNorm and NormFinder, despite the fact that the methods of calculation are fundamentally different.</p>", "<p>In order to test whether the normalisation genes identified above were also the best choices for specific conditions, we performed expression stability measurements on distinct series of treatments <italic>i.e. </italic>osmotic stresses, chemical treatments and diurnal rhythm. Figure ##FIG##2##3## shows that with both the geNorm and NormFinder calculation methods (A and B) the optimal choice of normalisation gene depended on the type of experiments. Thus, although <italic>EF1a </italic>remained among the most stable genes, variations in the identity of the other very stable genes were observed depending on the treatment. This was particularly striking for the <italic>ACT </italic>gene, the abundance of its transcript showing a high level of variability following all the treatments except osmotic stresses. The transcript of the <italic>TUA </italic>gene varied significantly in abundance in the diurnal sample series (see Additional file ##SUPPL##1##2##), but remained at a stable level in the abiotic stress treatments. Note that <italic>CYC </italic>and <italic>G6PD</italic>, which showed the greatest variability in transcript abundance in the global analyses, were also highly variable in each of the different classes of experiment.</p>", "<p>To calculate the number of normalisation genes necessary to obtain the normalisation factor we determined, using geNorm, the pairwise variation between sets of normalisation factors obtained when using two, three or more genes for normalisation. Figure ##FIG##3##4## shows that the normalisation factors are only modified slightly when a third (or more) gene is added (pairwise variation of 0.13 for 3 genes). Vandesompele et al. [##REF##12184808##5##] recommended that additional normalisation genes be included if the pairwise variation between the normalisation factors is higher than 0.15. According to geNorm, measuring the expression levels of <italic>ARP2.1 </italic>and <italic>UBCE </italic>is sufficient to normalise the expression of genes of interest in these samples.</p>" ]

[ "<title>Discussion</title>", "<p>In this study, the three methods used to identify the best normalisation genes were concordant, as previously reported in other studies [##REF##18226276##10##]. Comparison of the three methods indicates that <italic>EF1a </italic>is the most reliable gene to normalise gene expression in experiments aiming at quantitatively measuring the transcriptional response to abiotic stresses and chemical treatments. The V pairwise analysis shows that two genes are sufficient for a proper expression normalisation. The choice of the second gene, however, will depend on the type of experiment that is being carried out. For osmotic stresses and chemical treatments, <italic>TUA </italic>can be used reliably, while for the diurnal cycle <italic>ARP2.2 </italic>is more relevant.</p>", "<p>As a brown alga, <italic>E. siliculosus </italic>is member of the kingdom of the Heterokonta, which is phylogenetically very distant from animals and land plants [##REF##12805537##32##]. Interestingly, and despite this evolutionary distance, a consensus seems to emerge from similar analyses performed in organisms belonging to distant lineages. The gene coding for the elongation factor of protein translation <italic>EF1a </italic>was shown to be the best reference genes in salmon [##REF##16139890##17##] and in several plants such as in rice [##REF##16690022##19##], grapevine [##REF##17105665##22##] and potato [##REF##16188960##21##]. The alpha tubulin encoding gene was also reported to be one of the best reference genes for horse tissues [##REF##17540017##13##] and in poplar [##REF##16690022##19##]. On the other hand, actin genes have been very often reported as exhibiting highly variable levels of expression in both human and animals tissues [##REF##18226276##10##,##REF##17559642##12##,##REF##18230138##16##, ####REF##16139890##17##, ##REF##18211699##18####18211699##18##], and in plants [##REF##16690022##19##]. In this study, we have shown that this is also true for <italic>E. siliculosus</italic>.</p>", "<p>Despite the fact that ubiquitin and related enzymes (UBCE) are not commonly used as normalisation genes, in this study, they were found to be quite suitable. Interestingly, Czechowski et al. [##REF##16166256##31##] showed, using microarray analysis, that genes of the ubiquitin complex, comprising an ubiquitin conjugating enzyme such as UBCE, and several E3-ubiquitin protein ligases, were very stably expressed. They also pointed out that genes with fairly low levels of expression such as <italic>UBCE </italic>may be of particular interest for normalising expression levels of genes that are expressed at moderate to low levels, such as transcription factors. This latter example illustrates how microarray analyses may be useful to find additional normalisation genes, which can be then tested by Q-PCR for their suitability.</p>" ]

[ "<title>Conclusion</title>", "<p><italic>E. siliculosus </italic>is recognised as the genomic and genetic model of brown macroalgae [##UREF##0##1##,##REF##18181960##2##]. As the genome sequence is currently in the phase of expert annotation, the community interested in <italic>E. siliculosus </italic>is likely to grow in the near future. The results presented in this paper pave the way for further studies on different aspects of <italic>E. siliculosus </italic>biology including development/morphogenesis and abiotic/biotic stress responses. In addition, they will be helpful for comparison with results from microarray hybridizations, which are currently in progress.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Brown algae are plant multi-cellular organisms occupying most of the world coasts and are essential actors in the constitution of ecological niches at the shoreline. <italic>Ectocarpus siliculosus </italic>is an emerging model for brown algal research. Its genome has been sequenced, and several tools are being developed to perform analyses at different levels of cell organization, including transcriptomic expression analyses. Several topics, including physiological responses to osmotic stress and to exposure to contaminants and solvents are being studied in order to better understand the adaptive capacity of brown algae to pollution and environmental changes. A series of genes that can be used to normalise expression analyses is required for these studies.</p>", "<title>Results</title>", "<p>We monitored the expression of 13 genes under 21 different culture conditions. These included genes encoding proteins and factors involved in protein translation (ribosomal protein 26S, EF1alpha, IF2A, IF4E) and protein degradation (ubiquitin, ubiquitin conjugating enzyme) or folding (cyclophilin), and proteins involved in both the structure of the cytoskeleton (tubulin alpha, actin, actin-related proteins) and its trafficking function (dynein), as well as a protein implicated in carbon metabolism (glucose 6-phosphate dehydrogenase). The stability of their expression level was assessed using the Ct range, and by applying both the geNorm and the Normfinder principles of calculation.</p>", "<title>Conclusion</title>", "<p>Comparisons of the data obtained with the three methods of calculation indicated that EF1alpha (EF1a) was the best reference gene for normalisation. The normalisation factor should be calculated with at least two genes, alpha tubulin, ubiquitin-conjugating enzyme or actin-related proteins being good partners of EF1a. Our results exclude actin as a good normalisation gene, and, in this, are in agreement with previous studies in other organisms.</p>" ]

[ "<title>Abbreviations</title>", "<p>13-HOTrE: 13-hydroxyoctadecatrienoic acid; 15(S)-HEPE: 15-hydroxyeicosapentaenoic acid; ACT: actin; ARP2: actin-related protein 2/3; ASW: artificial sea water; CYC: cyclophilin; DMSO: dimethyl sulfoxide Dyn: dynein; EF1a: translation elongation factor alpha; G6PD: glucose 6-phosphate dehydrogenase; IF2A: translation initiation factor 2 A; IF4E: translation initiation factor 4E; R26S: ribososomal protein 26S; TUA: tubulin alpha; UBCE: ubiquitin conjugating enzyme; UBQ: ubiquitin.</p>", "<title>Authors' contributions</title>", "<p>P-O dF, SR and SD extracted the RNAs. SR provided <italic>Ectocarpus </italic>genomic DNA. TT tested the quality of the RNAs and performed the cDNA synthesis. MC gave access to the <italic>E. siliculosus </italic>genomic resources. BC chose the housekeeping genes, found homologues in the <italic>Ectocarpus </italic>databases and designed the oligonucleotides for Q-PCR. ALB and SD carried out the Q-PCR experiments. Analyses of the data were performed equally by ALB, SD, TT &amp; BC. The MS was written by TT and BC, and approved by all the authors.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Julia Morales (Station Biologique de Roscoff) for her help concerning the identification of the IF2A and EFI4 genes, and Bernard Billoud (Atelier de Bioinformatique de l'Université Pierre et Marie Curie Paris-6) for his assistance with statistical analyses. ALB and P-O dF are granted by the French Ministère de l'Enseignement Supérieur et de la Recherche. SD has received funding from the European community's Sixth Framework Programme (ESTeam n° contract MESTCT 2005-020737).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Expression level of 13 housekeeping genes</bold>. A: The range of the expression level of the 13 genes over the 21 culture conditions is expressed in Ct values. The black diamond represents the arithmetic mean. B: Variations observed in the range of Ct values.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Global ranking of the 13 housekeeping genes using geNorm analysis</bold>. The M value was calculated with the geNorm software [##REF##12184808##5##]. Low values of M indicate that a gene is expressed very stably.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Ranking of the 13 housekeeping genes over the three different series of culture conditions</bold>. Both geNorm (A) and Normfinder (B) were used to order the housekeeping genes according to three axes, corresponding to the three series of culture conditions/treatments. The position of each gene in the 3-D graph indicates its suitability as a reference gene. The front bottom position corresponds to the most stable gene, the far top position to the most regulated gene. Note the different scales on the axes.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Determination of the optimal number of control genes for normalisation</bold>. The pairwise variation V of the normalisation factors was calculated for the 21 different culture conditions for the 13 housekeeping genes with the geNorm software [##REF##12184808##5##].</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Culture conditions and duration. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Type of treatment</td><td align=\"left\">Final concentration</td><td align=\"left\">Duration</td></tr></thead><tbody><tr><td align=\"left\">Diurnal cycle</td><td/><td align=\"left\">0 h</td></tr><tr><td align=\"left\">Diurnal cycle</td><td/><td align=\"left\">6 h</td></tr><tr><td align=\"left\">Diurnal cycle</td><td/><td align=\"left\">12 h</td></tr><tr><td align=\"left\">Diurnal cycle</td><td/><td align=\"left\">18 h</td></tr><tr><td align=\"left\">Diurnal cycle</td><td/><td align=\"left\">24 h</td></tr><tr><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\">ASW</td><td align=\"left\">450 mM NaCl</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">DMSO</td><td align=\"left\">1% (V:V)</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">H₂O₂</td><td align=\"left\">10 mM</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">CuSO₄</td><td align=\"left\">10 μM</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">Atrazine</td><td align=\"left\">55 μg. L^-1</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">13-HOtrE</td><td align=\"left\">5 μM</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">15-HEPE</td><td align=\"left\">5 μM</td><td align=\"left\">3 h</td></tr><tr><td align=\"left\">ASW</td><td align=\"left\">450 mM NaCl</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">Ethanol</td><td align=\"left\">0.2% (V:V)</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">CuSO₄</td><td align=\"left\">10 μM</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">Diuron</td><td align=\"left\">42 μg.L^-1</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">Wounding</td><td/><td align=\"left\">6 h</td></tr><tr><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\">ASW</td><td align=\"left\">450 mM NaCl</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">Hyposaline</td><td align=\"left\">60 mM</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">Hypersaline</td><td align=\"left\">1,5 M</td><td align=\"left\">6 h</td></tr><tr><td align=\"left\">H₂O₂</td><td align=\"left\">1 mM</td><td align=\"left\">6 h</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Candidate housekeeping genes tested in this study.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Gene symbol</bold></td><td align=\"left\"><bold>Homologous to</bold></td><td align=\"left\"><bold>Description of trace archive</bold></td><td align=\"left\"><bold>Accession number</bold></td><td align=\"left\"><bold>Oligonucleotides – Forward – Reverse</bold></td><td align=\"left\"><bold>E (%)</bold></td><td align=\"left\"><bold>R2</bold></td><td align=\"left\"><bold>Tm product</bold></td><td align=\"left\"><bold>PCR product length (bp)</bold></td></tr></thead><tbody><tr><td align=\"center\">ACT</td><td align=\"left\">Actin</td><td align=\"left\">KY0AIB94YO18AHM1</td><td align=\"left\">1927036313</td><td align=\"left\">CCCAGATCATGTTCGAGACGTT<break/>CACGCCGTCACCCGAGTC</td><td align=\"left\">91</td><td align=\"left\">1.000</td><td align=\"left\">87.80</td><td align=\"left\">119</td></tr><tr><td align=\"center\">ARP2.1</td><td align=\"left\">p34-arc subunit of the actin-related protein complex ARP2/3</td><td align=\"left\">KY0AFIPA38YJ23RM1</td><td align=\"left\">1927195696</td><td align=\"left\">GAAGGAGTTCTGCCGGGAAG<break/>ACAAAGCAGCAACGCAGAGA</td><td align=\"left\">98</td><td align=\"left\">0.994</td><td align=\"left\">84.50</td><td align=\"left\">121</td></tr><tr><td align=\"center\">ARP2.2</td><td align=\"left\">ARP2 subunit of the actin-related protein complex ARP2/3</td><td align=\"left\">KY0AIB269YJ02AHM1</td><td align=\"left\">1929831232</td><td align=\"left\">GAAGAAGTTCAAGCTCAACATCGA<break/>CCGCACCCCCAATGAAA</td><td align=\"left\">104</td><td align=\"left\">0.998</td><td align=\"left\">80.90</td><td align=\"left\">68</td></tr><tr><td align=\"center\">CYC</td><td align=\"left\">Cyclophilin</td><td align=\"left\">KY0ADB29YF06FM1</td><td align=\"left\">1291599781</td><td align=\"left\">AGACGGCGGTGCAAGTAGG<break/>GTGAGTCACGGCTGCTTTTATG</td><td align=\"left\">92</td><td align=\"left\">0.997</td><td align=\"left\">84.80</td><td align=\"left\">101</td></tr><tr><td align=\"center\">Dyn</td><td align=\"left\">Dynein light chain protein</td><td align=\"left\">KY0AEB344YP09RM1</td><td align=\"left\">1306215256</td><td align=\"left\">GGAACAAAGCATGGTGACAACA<break/>CGCGTGCCTATCCAAGCT</td><td align=\"left\">100</td><td align=\"left\">0.999</td><td align=\"left\">81.20</td><td align=\"left\">65</td></tr><tr><td align=\"center\">EF1alpha</td><td align=\"left\">Translation elongation factor 1 alpha</td><td align=\"left\">KY0AEC342YI10RM1</td><td align=\"left\">1291335619</td><td align=\"left\">GCAAGGGCCTCAGCTCTG<break/>ACAAGCCGTCTGGGTATATGTTAGC</td><td align=\"left\">92</td><td align=\"left\">0.997</td><td align=\"left\">81.50</td><td align=\"left\">160</td></tr><tr><td align=\"center\">G6PD</td><td align=\"left\">Glucose 6 phosphate dehydrogenase</td><td align=\"left\">KY0AEF243YN02RM1</td><td align=\"left\">1299896231</td><td align=\"left\">GTGAGGATGTTCAGGTCCCAG<break/>GTGGAAGACCCGGTGAGGT</td><td align=\"left\">90</td><td align=\"left\">0.996</td><td align=\"left\">84.50</td><td align=\"left\">101</td></tr><tr><td align=\"center\">IF2A</td><td align=\"left\">Translation initiation factor eIF2 alpha</td><td align=\"left\">KY0AIB251YB11AHM1</td><td align=\"left\">1918199315</td><td align=\"left\">GCGGTACGTGATGGACACC<break/>CCCCCGACTCGATGATCTTT</td><td align=\"left\">94</td><td align=\"left\">0.991</td><td align=\"left\">84.80</td><td align=\"left\">101</td></tr><tr><td align=\"center\">IF4E</td><td align=\"left\">Translation intiation factor eIF4E</td><td align=\"left\">KY0ADA42YE14FM1</td><td align=\"left\">1291478318</td><td align=\"left\">TCGCGATTCGAGGTTTGAGTA<break/>CAAACGCTGCGGCAGC</td><td align=\"left\">100</td><td align=\"left\">0.991</td><td align=\"left\">82.40</td><td align=\"left\">71</td></tr><tr><td align=\"center\">R26S</td><td align=\"left\">Ribosomal protein 26S</td><td align=\"left\">KY0AEC624YL15RM1</td><td align=\"left\">1300144654</td><td align=\"left\">GCTAGGCTTGCGTTTGTGTG<break/>GGCGAGACAGAAAGATTCCG</td><td align=\"left\">93</td><td align=\"left\">0.995</td><td align=\"left\">85.40</td><td align=\"left\">101</td></tr><tr><td align=\"center\">TUA</td><td align=\"left\">Alpha tubulin</td><td align=\"left\">KY0AEC614YE14RM1</td><td align=\"left\">1299935912</td><td align=\"left\">TTTGAGGAGTTTCGTCGGAGAT<break/>CACACAGCGCAAAACGGC</td><td align=\"left\">92</td><td align=\"left\">0.999</td><td align=\"left\">83</td><td align=\"left\">140</td></tr><tr><td align=\"center\">UBCE</td><td align=\"left\">Ubiquitin conjugating enzyme</td><td align=\"left\">KY0AFIPA87YJ24RM1</td><td align=\"left\">1917772478</td><td align=\"left\">AACAATGGCCTTTGCGAAAA<break/>GCGTACGTCTTGAAGCCCAG</td><td align=\"left\">95</td><td align=\"left\">0.997</td><td align=\"left\">84.50</td><td align=\"left\">101</td></tr><tr><td align=\"center\">UBQ</td><td align=\"left\">Ubiquitin C</td><td align=\"left\">KY0AEC576YH18FM1</td><td align=\"left\">1306241438</td><td align=\"left\">CAACGCCCATGATTGTTCAC<break/>GATTATTCCCATCCACGGCA</td><td align=\"left\">100</td><td align=\"left\">0.997</td><td align=\"left\">82.70</td><td align=\"left\">101</td></tr><tr><td align=\"center\">mN</td><td align=\"left\">Intron amplification</td><td align=\"left\">KY0AEF302YN21FM1</td><td align=\"left\">1306150449</td><td align=\"left\">TCATTTTTCATGTGGAGGTCTCTG<break/>GCCAAACAAACAACAACCCTC</td><td align=\"left\">83</td><td align=\"left\">0.981</td><td align=\"left\">84.80</td><td align=\"left\">93</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Normfinder analysis of the expression stability of the 13 genes. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Gene name</td><td align=\"left\">Stability value</td></tr></thead><tbody><tr><td align=\"left\">TUA</td><td align=\"left\">0.099</td></tr><tr><td align=\"left\">ARP2.1</td><td align=\"left\">0.182</td></tr><tr><td align=\"left\">EF1a</td><td align=\"left\">0.220</td></tr><tr><td align=\"left\">Dyn</td><td align=\"left\">0.227</td></tr><tr><td align=\"left\">UBCE</td><td align=\"left\">0.240</td></tr><tr><td align=\"left\">UBQ</td><td align=\"left\">0.401</td></tr><tr><td align=\"left\">IF4E</td><td align=\"left\">0.403</td></tr><tr><td align=\"left\">IF2A</td><td align=\"left\">0.406</td></tr><tr><td align=\"left\">ARP 2.2</td><td align=\"left\">0.422</td></tr><tr><td align=\"left\">R26S</td><td align=\"left\">0.479</td></tr><tr><td align=\"left\">ACT</td><td align=\"left\">0.558</td></tr><tr><td align=\"left\">G6PD</td><td align=\"left\">0.655</td></tr><tr><td align=\"left\">CYC</td><td align=\"left\">1.964</td></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>One-way ANOVA test for the significance of the biological triplicate averaging. An ANOVA was performed on the three biological replicates of all the data, with the groups corresponding to the different treatments. The resulting p-values are shown in the table.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Gene expression during the diurnal cycle.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Quantification and quality of the RNAs used in this study.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>RNA extracts considered in this study. From the 83 RNAs run on the gel, the ones used for the cDNA synthesis are labelled in red. Between 400 to 900 ng of RNA were loaded on the gel.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>Treatments were applied under light (see Material and Methods for details). ASW: artificial sea water; DMSO: dimethyl sulfoxide; 13-HOTrE: 13-hydroxyoctadecatrienoic acid; 15(S)-HEPE: 15-hydroxyeicosapentaenoic acid.</p></table-wrap-foot>", "<table-wrap-foot><p>The identity of the sequences (gene name, function) is indicated in the left part of the table. The trace corresponds to trace archive at NCBI <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/Traces/trace.cgi?cmd=retrieve&amp;val=species_code%3D%22ECTOCARPUS+SILICULOSUS%22\"/>. Parameters on the corresponding amplified product (oligonucleotides, amplicon Tm and size, reaction efficiency and reliability) are indicated in the right part.</p></table-wrap-foot>", "<table-wrap-foot><p>The stability of expression of the 13 genes was calculated using the Normfinder method designed by Andersen et al.[##REF##15289330##6##]</p></table-wrap-foot>" ]

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[ "<title>Background</title>", "<p>Recent statistics by UNAIDS suggest that 2.5 million (Range: 1.8–4.1 million) people were newly infected with HIV in 2007. About 15.4 million (Range: 13.9–16.6 million) women were living with HIV [##UREF##0##1##]. The disproportionately higher number of infections among women requires a commitment to address the urgent need for HIV prevention tools. Microbicides are products that are currently in development for use by women with or without their partners' knowledge in order to reduce the growing rates of new infections among women. The microbicide research community spans across a multidisciplinary team of basic and clinical scientists, social and behavioural experts together with committed members of community and advocacy groups who are dedicated to finding a women initiated HIV prevention option.</p>", "<p>In February 2008, the Microbicide 2008 (M2008) conference was held in the Asian Sub-continent for first time. Held in New Delhi India, the conference attracted over 1000 delegates from the USA, Europe, Asia, Australia, South America and Africa. This was an important meeting, given the recent developments in the field with several large scale efficacy trials having disappointing outcomes [##REF##17631387##2##, ####UREF##1##3##, ##UREF##2##4####2##4##].</p>", "<p>We report on the proceedings of the Microbicides 2008 International conference, with respect to outcomes and discussions from Track A (basic science), Track B (clinical science), Track C (social and behavioural science) and Track D (community and advocacy).</p>", "<title>Track A – Basic science and preclinical development</title>", "<title>Gustavo F. Doncel</title>", "<p>Within Track A speakers updated a wide variety of topics ranging from HIV entry in cervicovaginal epithelium to delivery of microbicides by controlled-release devices. In order to facilitate their description, the highlighted presentations have been divided into four areas: sexual transmission of HIV; emerging candidates; biomarkers, models and preclinical evaluation; and formulation and delivery systems.</p>", "<title>Sexual transmission of HIV</title>", "<p>In his plenary lecture, Tom Hope showed that using cervical explants, photoactivable green fluorescent protein-labeled virus and high-resolution confocal microscopy, HIV was seen to penetrate intact epithelium, predominantly through the interstitium. Although some virions reached the innermost layers of the epithelium, most of them were concentrated in the first 40 microns. This distance was enough to put the virus in contact with cellular targets such as Langerhan's cells and intraepithelial lymphocytes. Similar in vivo experiments in macaques support the conclusion that HIV is able to penetrate the genital mucosa through an apparently intact squamous stratified epithelial layer. Derived from this conclusion is the fact that vaginal pathologies, progestogenic hormones or microbicides that decrease the thickness of the epithelium will increase the chances of HIV to meet its target cells. The increased number of monkeys vaginally infected with SIV/SHIV when pre-treated with DMPA clearly supports this contention. An inflammatory reaction recruiting target cells to the epithelium or the partial de-epithelialization and disruption of epithelial permeability caused by surfactants like nonoxynol-9 would have the same effect.</p>", "<title>Emerging microbicide candidates</title>", "<p>In his contribution to the \"Drug Discovery\" symposium, Martin Springer indicated that there was a significant attrition of candidate compounds from discovery to phase III clinical trials. Contrary to popular belief, most of this attrition is due to lack of sufficient efficacy. A plenary lecture by Charles Kelly provided an update of current and emerging microbicides. The most promising microbicide candidates in the pipeline belong to the mechanistic categories of reverse transcriptase inhibitors (RTIs), entry inhibitors (EIs) and integrase inhibitors (INIs). Within the RTIs, the most advanced compounds are tenofovir, dapirivine, UC-781 and MIV-150. Among EIs, there are CCR5 blockers (e.g., Maraviroc, RANTES analogs, M-167), gp-120 blockers (e.g., BMS-793), fusion inhibitors (e.g., T-1249) and a CD4 downmodulator (CADA). Two new fully recombinant RANTES analogs (peptides) were shown to prevent systemic viremia in 100% (5/5) of the monkeys challenged intravaginally with 300 TCID₅₀SHIV SF162P [##UREF##3##5##]. Mohammed Saifuddin reported a similar outcome for cellulose sulfate (CS) using a low-dose multiple-challenge X4/R5 SHIV model. Although most of the CS treated animals showed HIV positive proviral DNA and HIV-specific T cell responses, none of them seroconverted, showed systemic viremia (vRNA) or produced culturable virus.</p>", "<p>In a symposium on \"New Approaches\", Robert Buckheit outlined the significance of pyrimidinediones, a new series of small molecules with anti-HIV activity in the subnanomolar range and a dual mechanism of action inhibiting RT and cell entry.</p>", "<p>Combination microbicides were cited as a logical next step in microbicide development. Their advantages, as discussed in a symposium on \"Combination Microbicides\", include wider antiviral spectrum, higher genetic barrier to resistance, higher potency, and broader cell/tissue coverage. Combinations of RTIs such as tenofovir with TMC-120 or UC-781 are being explored and developed. Studies from different labs have shown that these combinations display synergistic activity (CI ~ 0.7) and are more potent and more active against resistant virus than their single ingredients alone [##UREF##4##6##,##UREF##5##7##].</p>", "<p>Speaking on the induction of resistance, John Mellors stated that in spite of the valid concern about compounds generating and being susceptible to resistant viruses, product development emphasis should be put on potency and efficacy of single-active and combination microbicides. The impact of viral resistance in the context of microbicide use is significantly lower than that of resistance generated by antiviral therapy and is even smaller in the presence of reduced number of infections due the use of an effective microbicide.</p>", "<p>Various delivery systems and dosage forms for combination microbicides are currently in development, as described by Patrick Kiser, with gels and two types of intravaginal rings being the most advanced systems. In addition to developmental challenges, combination microbicides also face an unexplored regulatory pathway.</p>", "<title>Biomarkers, models and microbicide preclinical evaluation</title>", "<p>In a panel discussion, Gustavo Doncel proposed a new preclinical testing algorithm for the rational selection of microbicide candidates. Three main parameters, efficacy, safety and pharmacokinetics and pharmacodynamics (PK/PD), are to be assessed sequentially in vitro, ex vivo (explants) and in vivo (animals). The need to incorporate environmental factors (e.g., pH, seminal plasma, cervicovaginal secretions and microflora) in these studies was highlighted by Raina Fichorova, Ken Rosenthal, and Radiana Trifonova in two symposia and one oral presentation [##UREF##6##8##], respectively. Improvements and development of new animal models were reported. Dorothy Patton [##UREF##7##9##] and Cecilia Cheng-Meyer described the use of single- and multiple-dose non-human primate models of HIV vaginal transmission to assess microbicide safety and efficacy (roundtable discussion on \"Critical gaps in microbicide development\"). Furthermore, cell-associated transmission of SIV is being optimized in a single-dose model by Roger Le Grand and colleagues.</p>", "<p>A new humanized mouse model based on transplantation of human fetal bone marrow, liver and thymus into a SCID/NOD mouse has been shown by Victor Garcia and colleagues to be a suitable model for intravaginal HIV infection [##REF##18198941##10##]. If validated for microbicide testing, this model will be useful in early assessments of compound efficacy.</p>", "<p>Epithelial integrity, permeability and overall barrier function must be evaluated in vitro, and, if possible, in vivo, when determining the profile of a compound in regard to cervicovaginal safety. Betsy Herold proposed that inflammatory mediators, immune innate factors and antimicrobial activity also be critical endpoints of preclinical safety evaluation.</p>", "<p>Given the results of recent microbicide clinical effectiveness trials, both Gustavo Doncel and Marla Keller cited the importance of considering evaluating the potential of compounds and formulations to increase or enhance susceptibility to infection. In vitro and animal models already in existence or in development to assess this property [##REF##18434407##11##] were described during a roundtable discussion by Marla Keller. For the most part they consist of pre-exposing tissues or animals (e.g., mice or monkeys) to repeated doses of microbicides before challenging them with a suboptimal infectious dose of virus in the absence of microbicide.</p>", "<p>In the panel discussion on \"Criteria to enable criticial selection of microbicides\", Joe Romano emphasized that pharmacokinetic and, whenever possible, pharmacodynamic studies, both in vitro and in vivo, are crucial to understand how microbicides work at the tissue/cell level. Innovative methodology is being developed to assess these parameters, both clinically and preclinically.</p>", "<p>The overall conclusion of the panel was that the rational selection of microbicide candidates for further clinical testing is a complex, iterative, evolving process that may be improved by harmonizing/standardizing a minimum set of assays and models, while preserving the ability of scientists to innovate. With the addition of new, more predictive biomarkers and models of safety and efficacy, a final Go/No Go decision should be based on a comprehensive preclinical package, rather than on a single \"gatekeeper\" assay or model.</p>", "<title>Microbicide formulations and delivery systems</title>", "<p>Formulations can \"make or break\" a microbicide product. For instance, in his plenary lecture Charles Lacey pointed out that a gel containing high concentrations of glycerol produced unacceptable adverse events in a phase I clinical trial. The hyperosmolarity of a product has been blamed for significant negative effects on mucosal tissue, especially that of the rectum [##UREF##8##12##]. Formulation properties can also be used to enhance the antiviral activity of microbicides [##UREF##9##13##]. Research and development of new delivery systems and dosage forms for vaginal and rectal microbicides is ongoing. Intravaginal rings were described as especially suitable for long-term controlled-release of hydrophobic compounds in two different symposia by Karl Malcolm and Patrick Kiser. Quick-dissolve thin films and tablets are also being investigated and developed to deliver microbicides, as described by Lisa Rohan and Sanjay Garg, respectively, in the symposium on \"Dosage Forms for Microbicides.\"</p>", "<p>Although more research is needed to determine the acceptability of different dosage forms, it is clear that cultural differences exist that may affect adherence to product use. Since the type and characteristics of formulations and delivery systems influence preclinical testing, clinical trial design and, ultimately, user acceptability, formulations and delivery systems should be designed taking all these parameters into consideration. Furthermore, they should be characterized and established as early as possible in the product development process.</p>", "<title>Track B – Clinical science</title>", "<title>Sanjay Mehendale</title>", "<p>Within this track there were two plenary sessions, one with Sharon Hillier providing an update on clinical trials of microbicide effectiveness and a second with Charles Lacey providing an overview of how product characteristics and delivery mechanisms may influence clinical trial design. Sharon Hillier provided an overview of current and future research products and some of the challenges we face in the conduct of clinical trials. The new generation of ARV-containing products were introduced with some information on planned trials.</p>", "<p>General sessions were grouped into themes of 1) Update on clinical trials 2) statistics, power and design of clinical trials 3) studies in men 4) findings from early phases of clinical trials 5) impact of other prevention trials 6) clinical safety studies of vaginal microbicides and 7) lessons learnt from cohort studies. In addition there were cross track sessions on \"when clinical trials end: challenges and lessons learned\", and \"standards of care\". The sessions reported here have been divided into seven areas: Current status and findings from phase III trials: products in the advanced stage of evaluation; early safety trials; methodological issues in the design and implementation of clinical trials; impact of other HIV prevention trials; clinical safety studies; and when clinical trials end: challenges, experiences and lessons learned; and a short report on cross track sessions.</p>", "<title>Current status and findings from phase III trials: Products in the advanced stage of evaluation</title>", "<title>HPTN 035</title>", "<p>HPTN 035 is a trial funded by the NIH to assess the effectiveness of PRO 2000 and BufferGel in preventing HIV infection in a cohort of women from South Africa, Malawi, Zimbabwe and Zambia. A total of 3200 women have been enrolled and are due to complete the study by August 2008. The study is designed to have two microbicide arms and two control arms (placebo and condom only). The results are expected in early 2009 [##UREF##10##14##].</p>", "<title>MDP 301</title>", "<p>The microbicide development program (MDP) is a collaboration between scientists in the UK (Imperial college and Clinical trials Unit of the Medical Research Council) and scientists from Uganda, Tanzania, Zambia and South Africa. The trial is being conducted in Africa [##UREF##11##15##]. The trial was initially testing two concentrations of PRO 2000 (0.5% and 2%) against a placebo. However in early February, the data and safety monitoring committee (DSMC) reviewed the data to find that the 2% PRO 2000 had very little chance of showing effectiveness. The 2% arm of the study was subsequently dropped. The study continues to enrol women on the 0.5% and placebo arms of the study and is expected to complete enrolment in August 2008. The results are expected in late 2009. Henry Luwugge reported that gel use appeared to be high irrespective of condom use [##UREF##12##16##]. Given the recent failures of products with similar modes of action, it is encouraging that to date major safety concerns have not been raised through several interim analysis in both the above ongoing trials.</p>", "<title>Carraguard™</title>", "<p>A plenary presentation by Elof Johannson provided the results of the Carraguard™ trial. Carraguard™, a sea weed extract, was the Population Council's lead microbicide product. A large phase III clinical trial involving 6202 women was conducted at 3 sites in South Africa; Durban, Shoshuguwe (Pretoria) and Cape Town. The results showed that although Carraguard™ was safe, it was not effective in preventing HIV transmission. The results were extremely disappointing [##UREF##13##17##].</p>", "<p>The report of a sub study presented by Marlena Gehret to assess the association between male circumcision and partner sero-conversion was studied in 4579 women with a single partner [##UREF##14##18##]. Women with partners who were circumcised were more likely to have a lower HIV incidence. Thesla Palanee reported that incidence of STI among participants of Carraguard™ trial showed a high prevalence of <italic>C. trachomatis </italic>(CT) and <italic>T. vaginalis </italic>(TV) infection [##UREF##15##19##]. The prevalence rates varied across the three African sites. At follow-up, decreasing trends in the incidence of STI was observed. This could be due to counseling, improved health seeking behavior and STI treatment. Risk factors associated with HIV incidence included number of partners, and being positive for CT, TV and bacterial vaginosis (BV).</p>", "<p>Results of another study of the impact of behavioural change on STI incidence by Felicity Gopolang showed that there was a reduction in the number of sex acts, number of partners and increase in condom use [##UREF##16##20##]. However, the observed behavioral change had no impact on the overall STI incidence rate. Adherence to product use was measured through the use of biomarkers, self-report and a combination of both methods. Nearly 96% of the 6005 women self-reported adherence to the product. Gel used during vaginal sex was 57%, condom use 64%, both gel and condom use 62%; women reported having sex 2.5 times per week and applicator insertion 0.9 times per week. Analysis of self-reported condom use and microscopy for sperms in vaginal swabs (wet mount and TV In pouch) showed detectable spermatozoa among that reporting condom use in 62.5%. This study indicated that information given by women on condom use may not be reliable.</p>", "<title>CAPRISA 004</title>", "<p>In addition to trials of current generation of microbicides, an update was provided on the first proof of concept ARV-based microbicide trial being conducted in South Africa. CAPRISA 004 is a two arm study comparing a coitally dependent dose of 1% tenofovir against a placebo. Enrollment is scheduled to be completed by July and results expected in 2010 [##UREF##17##21##].</p>", "<title>Savvy</title>", "<p>The vaginal microbicide Savvy was evaluated in a Phase III Nigerian trial which required the use of pre-loaded single use gel applicators and a placebo, and enrolled 2142 women. The trial was terminated early at 75% completion level. High pregnancy rates were observed across both study arms. There was no evidence of the effectiveness of the product in preventing HIV infection. Paul Feldblum concluded that more conservative HIV incidence estimations should be employed and more effective family planning measures should be advocated among the trial participants [##UREF##18##22##].</p>", "<title>Early safety trials</title>", "<title>HPTN 059</title>", "<p>Sharon Hillier presented some very encouraging results of the safety and coitally dependent use of 1% tenofovir over six months [##UREF##19##23##]. The HPTN 059 trial also tested the safety and acceptability of 1% Tenofovir gel and was conducted in India and two US sites [##UREF##20##24##]. Soma Das reported 96% retention over 6 months and 80–85% product adherence. Preliminary results indicate that the safety profile of the product was excellent and toxicity end points were comparable in product and placebo arms. There were no significant sexually transmitted infection (STI) acquisitions. Daily gel use was close to 20% and over 75% with sex. Some tenofovir was detectable in blood in 75% of those who had used gel in the past 24 hours. Strategies such as locator forms, participant tracking database, telephonic contacts, home visits, clinic diary and follow-up schedule chart were used to facilitate retention. Male involvement and proper scheduling helped in achieving remarkably high retention rate in this study.</p>", "<p>In a study presented by Jill Schwartz, two 1% tenofovir gel dosing regimens are currently being evaluated in pharmacokinetic studies on samples collected by cytobrush and biopsies from the posterior fornix. Advanced assays are being used for local and systemic compartment evaluations.</p>", "<title>Dapivirine vaginal gel (Gel-002)</title>", "<p>Gel-002 with active ingredient Dapivirine recently underwent safety and tolerability testing in studies in Rwanda, South Africa and Tanzania. This NNRTI was tested in a gel form to assess its safety and acceptability. Shanique Smythe presented the data from this 3 dose study requiring 42 days' product use. The product was shown to be safe and well-tolerated, possibly warranting further investigation of the gel [##UREF##21##25##]. Annalene Nel presented the results of a South African phase I pharmacokinetic study of Gel-002 among 18 women in 3 groups. Low systemic levels of the product were detected up to 24 hours after exposure [##UREF##22##26##].</p>", "<title>Cellulose acetate phthalate (CAP 13% gel)</title>", "<p>Charles Lacey presented a Phase I study of this hyper-osmolar vaginal gel in 10 women which was stopped following unacceptable adverse events. A continuous, heavy and watery discharge was noted in half of the women participating in the study [##UREF##23##27##].</p>", "<title>Vivagel</title>", "<p>Vivagel (SPL7013 Gel), a product with anti-HIV and anti-herpes properties, was initially tested in macaque models and subsequently in two studies in men and women. Clare Price and Maureen Momanyi reported findings from Vivagel studies. Safety after penile application of 2 mg of product for 7 days showed no genital irritation, genital pruritus, penile dryness or scrotal tingling and the results were similar in circumcised and uncircumcised men. The product was found to be safe and well tolerated. The acceptability was good and there was no evidence of systemic absorption [##UREF##24##28##,##UREF##25##29##].</p>", "<title>Special cross track sessions: Key-note addresses, symposia and panel discussions</title>", "<p>Within track B three symposia were organized on \"Rectal Microbicides\", \"Moving Microbicides into susceptible populations\" (discussed under track D) and \"Microbicides and HIV positive women\" (discussed under track D) and two key-note addresses on \"Methodological issues in design and implementation of clinical trials\". Additionally, two panel discussions were conducted on the \"Impact of other HIV prevention trials\" and \"Clinical safety studies\". The major observations during these sessions are summarized below.</p>", "<title>Studies on rectal exposures of microbicides</title>", "<p>An ex-vivo challenge study of the safety of the rectal microbicide UC-781 on explants has been completed and the data is still blinded. A subsequent interim report of the safety study at 50% completion was presented by Peter Anton [##UREF##26##30##]. Interim data from 36 rectally-exposed men and women at UCLA, USA indicated that the product was safe and well-tolerated. Product adherence was good and no Grade III or IV adverse reactions were observed. Even at 75% study completion results remain unchanged. The study employed a vaginal applicator for rectal use. Further research needs to be conducted on the design and acceptability of the vaginal applicator for rectal use. Mucosal immunity studies following two weekly applications for 6 weeks indicated no changes in the mucosal and cytokine profiles of the three groups over time.</p>", "<title>Methodological issues in the design and implementation of clinical trials</title>", "<p>Doug Taylor gave a very informative talk on statistical power. He expressed the challenges we face in assessing trial outcomes on factors that impact on power. There are several factors that contribute to the power of the study to show efficacy. These include high retention rates, adherence to product use, women taken off the product due to pregnancy and high incidence rates. He expressed the importance of conducting effectiveness trials over efficacy trials. To overcome the challenges of high incidence of pregnancy and its impact on power, new generation of products will be tested for safety during pregnancy.</p>", "<p>Zeda Rosenberg discussed the challenges in doing phase III studies with enough power when a product is believed to be effective in preventing HIV transmission. She explained that the current trials do not measure efficacy, but it is inferred that a woman has become infected after unknown number of sex acts. She stressed that effectiveness trials are more important because they measure both efficacy as well as adherence. It is being increasingly felt that alternative study designs should be employed for the fast tracking of microbicide development and testing. The best among the next generation products must be selected for safety evaluation and should be evaluated early for futility after employing measures to improve adherence. They should be powered for licensure. Alternate studies of superior design will allow for improved ways of measuring adherence and reductions of risk taking behaviour, and at the same time test the effectiveness of the product in HIV prevention.</p>", "<title>Impact of other HIV prevention trials</title>", "<p>Globally the agenda of HIV prevention research includes behavioral change, circumcision, diaphragm use, pre-exposure prophylaxis and STI control. We have learned that adherence significantly impacts the outcomes of trials. Trials have also had setbacks due to unexpected fewer number of study end-points resulting from low HIV incidence. According to Lut van Damme and colleagues, lower than expected HIV incidence rates highlight the importance of site preparatory studies and newer technologies to estimate HIV incidence.</p>", "<title>HSV-2 suppressive therapy for HIV prevention</title>", "<p>The HPTN 039 study, conducted by Connie Celum, explored whether HSV-2 suppression by Acyclovir could reduce the risk of HIV acquisition [##UREF##27##31##]. Although the precise reasons why this trial failed to show the desired result in Africa are unknown, the lack of adherence to Acyclovir prophylaxis may appear to be one of the reasons. This is the second trial of Acyclovir which failed to show effectiveness in preventing HIV. A trial conducted in Tanzania showed similar results [##REF##18337596##32##].</p>", "<title>Male circumcision</title>", "<p>Cate Hankins presented the outcome of the three trials on male circumcision in the prevention of HIV. The results showed the male circumcision provided up to 60% protection against female to male transmission of HIV. The current challenges were to roll out male circumcision as an HIV prevention option in developing countries.</p>", "<title>Vaginal diaphragm for the prevention of HIV</title>", "<p>MIRA (Methods of Improving reproductive Health in Africa) was a trial conducted to assess the effectiveness of the vaginal diaphragm in the prevention of HIV. The trial was completed in early 2007 and the results reported in July of the same year [##REF##17631387##2##]. The study was conducted at 3 sites in Southern Africa; Zimbabwe and South Africa (Johannesburg and Durban). The study showed that the vaginal diaphragm did not provide any added benefit when used in addition to the current prevention package of male condoms, risk reduction counseling and treatment for STI. Kelly Blanchard presented an overview of the trial and the results [##UREF##28##33##].</p>", "<title>Clinical safety studies</title>", "<p>Clinical safety studies evaluate integrity of epithelium, effects on the penis, vaginal microflora, pregnancy and impact on body function due to systemic absorption or inflammatory response. Symptoms and colposcopy do not necessarily indicate safety and recent outcomes of trials suggest that there is a need to identify markers for general toxicity at an early stage of clinical trials. It is essential to establish safety both in HIV negative and positive women. The possibility of extension of the product in endocervix and uterus warrants some method like Magnetic Resonance Imaging (MRI) for its safety evaluation, which might increase the cost of a trial substantially. Jonathan Weber emphasized the urgent need for long-term safety assessment and strategies to avoid products going into large scale trials and then showing increased safety concerns.</p>", "<title>Cross track sessions</title>", "<title>Standard of Care</title>", "<p>In a cross track session on standard of care, Kathy Shapiro presented the results of a mapping exercise by the Global Campaign for Microbicides. Key conclusions from this study were that clinical trial sites are providing better quality (access, affordability, skills of providers) of services. Also there are a range of standards of care being offered at sites depending on public sector services in the area. She outlined recommendations that came out of the exercise and subsequent meetings; urging that communities should be engaged in decisions about how to manage trial standard of care; future trials should consider co-locating with existing local care facilities and use the opportunity to improve the services provided, improve the quality of care and build the capacity of health care providers; trial sites should also improve their referral systems and facilitate women's access to care at referral facilities; and as much as possible to also establish formal agreements with referral sites to avoid the unnecessary repetition of tests and other procedures.</p>", "<title>When clinical trials end: Challenges, experiences and lessons learned</title>", "<p>Three speakers in this session, Lut Van Damme, Gita Ramjee and Manju Chatani provided their perspectives on the impact of the unexpected closure of clinical trials mainly due to safety concerns. Lut Van Damme provided an overview of the challenges faced by sponsors during the closure of Cellulose Sulphate trial in early 2007. Key lessons learned were the need for communication, and visiting trial sites immediately. She stressed that one is never prepared emotionally and practically for sudden closure of trials.</p>", "<p>Manju Chatani's contribution to a panel discussion outlined a number of lessons learned from the advocates' perspective after the closure and premature end of microbicide trials. These include; the need to strengthen communication strategies in the microbicides field, the need to select effective community speakers and inform them routinely on developments and be informed from them as well and the need to conduct ongoing media training for these spokesperson. A key lesson is to work closely with media agencies on an ongoing basis – so that media is well-versed with protocols of microbicides research and is an effective partner. There is a value in scenario planning in anticipation of different possible results. These experiences have led to advocates having increased access to researchers and information, and as a result there is more coordination and collaboration among these stakeholders.</p>", "<p>The MMCI completed a case study of lessons learned during the unexpected closures of the Cellulose Sulfate trial and the inflammatory press coverage that followed in South Africa. The case study analyzes the handling of the crisis in light of conflicting pressures at the international, local, and trial site level. It highlights the particular challenges of ensuring that relevant stakeholders and trial participants are informed of the findings before they are released to the media.</p>", "<p>Gita Ramjee gave her perspective as an investigator at trial sites. Many of the sites employ skilled staff to conduct clinical trials. When trials end either prematurely or due to natural completion, it is difficult to sustain trial staff if no other products are available to go into large scale trials. This poses a huge challenge for trial sites. Unexpected closures have been challenging due to sensationalist articles in the media that impact on HIV prevention efforts. Effective communication and scenario planning of trial outcomes need to be in place well in advance of the trial outcomes. She stressed the involvement of the community in the dissemination of results and preparation of results in local language. All speakers stressed the importance of communication and collaboration with various disciplines prior to release of the results.</p>", "<p>In addition to the cross track sessions there were special symposia on microbicides and HIV positive women. The symposium presenters were Wafaa EL Sader and Anna Forbes. Both presenters stressed the importance of involving HIV positive women in HIV prevention efforts. The second symposium was on moving microbicide research to vulnerable populations. Richard Beigi presented on the need for involving pregnant women in clinical trials to assess the safety of products. Ian McGowan stressed the importance of involving men who have sex with men and development of rectal microbicides. Kathy Slack highlighted the growing incidence of HIV in adolescents and the need to involve adolescents in clinical trials of microbicides and other prevention technologies.</p>", "<title>Track C – Behavioural and social science</title>", "<title>Elizabeth E. Tolley</title>", "<p>The social science Track C program featured a wide range of research topics and methodological approaches. Seven abstract-driven sessions and three invited presentations addressed issues pertaining to adherence; behavioural and social science methods and tools; acceptability; community involvement; partner roles; vulnerable populations; and future access.</p>", "<title>Cultural influence</title>", "<p>In his plenary talk, Ravi Varma described the ways that culture influences men's and women's risk through gender roles and relationships – and will ultimately determine whether, with whom and how gels may be used. Some men's first sexual encounters were with other men; many men who engage in sex with other men are married. Men's perception of risk from such behaviours was low – especially if one was the \"penetrator\". Men who engaged in extramarital sex (whether with other women or men) were six times more likely to report wife abuse than those who did not. Yet, gender norms perpetuate women's submission to coercive sex in marriage and prevent frank discussions about sexuality and risk. Varma concluded that while the introduction of microbicides may act as a catalyst, more encompassing gender transformative strategies were needed to reduce men's and women's risk of HIV in India. Indeed, the association between microbicide introduction and gender norm transformation arose in South Africa as well, where Fern Terris-Prestholt found a preference for promotion of microbicides as a means to empower women and/or prevent HIV – rather than a method to enhance sexual pleasure, in a survey of 1017 women in three townships in Johannesburg, South Africa [##UREF##29##34##].</p>", "<p>Several studies reminded us that the cultural context of microbicide use may vary across countries and for different groups within a population. This included access to partially effective microbicides and its impact on vulnerability of sex workers [##UREF##30##35##], types of products, frequency and timing of use [##UREF##31##36##] and modelling studies to ascertain impact of microbicide introduction [##UREF##32##37##].</p>", "<title>Communities</title>", "<p>Communities are not homogenous. Multiple stakeholders, including civil society groups [##UREF##33##38##], healthcare providers [##UREF##34##39##], clinical trial staff [##UREF##35##40##] and trial participants influence trial acceptability through their understanding and expectations of clinical trials. One important factor influencing successful trial implementation is community perception of the quality and types of HIV-related treatment, care and support to be provided to those who screen out of the trial or sero-convert, their families or the broader community. Community involvement and partnership is critical to initiation and completion of trials to ensure such concerns are adequately addressed. The benefit of such involvement was evident in premature closure of the Cellulose Sulphate trial [##UREF##36##41##], where intensive counselling, community education and on-going informed consent processes led to relatively positive community reactions despite a spate of negative and inaccurate publicity about closure. While there are cultural differences, trial sites have to develop novel strategies to explain the understanding of trial methodologies such as randomization and placebo [##UREF##37##42##,##UREF##35##40##]. This requires ongoing improvement of the informed consent process and understanding. In addition it was pointed out that communities should have a sense of ownership for successful community involvement. New trials will implement comprehensive socio-behavioural and community preparedness activities to allow for community partnerships [##UREF##33##38##,##UREF##38##43##].</p>", "<title>Trials and clinic settings</title>", "<p>The clinical trial setting itself is likely to influence individuals' risk behaviours; several studies examined changes in trial participants' behaviours post randomization. Among 2140 women randomized to the diaphragm arm of the MIRA trial, just over 22% reported using diaphragms instead of condoms at all visits, and over 60% reported doing so at some visits [##REF##17631387##2##,##UREF##28##33##]. Women who consistently reported substituting the diaphragm for condoms (versus never report this behaviour) were more likely to be engaged in sex work, report domestic violence or sex with a drunken partner, believe that diaphragms protect against HIV/STIs, and are less likely to know that condoms can be used with diaphragms.</p>", "<p>While Ariane Van der Straten's study identified the potential for therapeutic misconception and condom migration, Adelaide Mzimela's and Elizabeth Tolley's studies found that trial participation may, in fact, lead to higher use of condoms [##UREF##39##44##,##UREF##40##45##].</p>", "<title>Partners</title>", "<p>Women's ability to negotiate trial participation with intimate partners may determine who enrolls in trials and how well they are able to adhere to gel and other trial requirements. Anna Dladla-Qwabe examined the relationship between consistent gel adherence and disclosure to partners of study participation/gel use in a study of 263 women in Hlabisa, South Africa participating in the HPTN 035 trial [##UREF##41##46##]. She noted that women reporting consistent gel use were more likely to have disclosed both their study participation and their use of gel to partners than women who reported inconsistent use. Local behavioural investigators at several MDP trial sites examined the role of men in gel use. Disclosure to gel use was reported by many participants in several trials and, in general, men supported women's use of the product. Lubrication provided by the gel increased sexual pleasure hence the products were acceptable [##UREF##42##47##, ####UREF##43##48##, ##UREF##44##49##, ##UREF##45##50##, ##UREF##46##51####46##51##].</p>", "<p>On the other hand Petina Musara examined covert use of microbicides in a sub-study of HPTN 035 in Zimbabwe [##UREF##47##52##]. Women reported a motivation to use microbicides clandestinely when they suspected a partner to be unfaithful; when he was unwilling to use condoms; or when he was HIV positive. However, requirements for timing and insertion of gel, as well as difficulties of storage limited covert use. Community leaders also expressed negative opinions about covert use, further constraining this approach.</p>", "<title>Participants</title>", "<p>Several Track C presentations identified individual-level factors as influencing acceptability and use of microbicides. These included perceptions of product attributes, perception of risk and efficacy to communicate with a partner about risk and/or negotiate risk reduction behaviours. For example, in PRO 2000/5 study of 3157 women, Jessica Dhookie noted very few reports of difficulty with insertion (&gt; 1%) – all reported in week 4 follow-up only [##UREF##45##50##]. Alex Carballo-Diéguez examined the acceptability of rectal microbicide vehicle-related attributes in a cross-over trial of 77 HIV-negative cohort of men having sex with men [##UREF##48##53##]. Men and their partners were significantly more likely to prefer gel over suppositories, reporting that gel was associated with greater sexual satisfaction and resulted in less leakage, bloating or other side effects than did suppositories. In a cross-sectional U.S.-based study called the Phoenix Project, Kate Morrow found that a person's attitudes and characterizations of risk were influenced by specific partner contexts and that willingness to use a microbicide was affected by both those individual and relationship elements [##UREF##49##54##]. In India, Elizabeth Tolley found somewhat similar measures of risk perception and partner context, as well as product attitudes and perception of protection efficacy, to predict consistency of condom use among clinical trial participants, but only product attitudes to predict gel use [##UREF##40##45##].</p>", "<p>While several presentations focused on the individual, couple-related or other factors that might explain participants' level of adherence in trials, only one presentation focused on approaches to optimizing participants' adherence within trials. Approaches include motivational interviewing to assist individual participants in identifying and pre-empting situations that could lead to non-adherence of gel [##UREF##50##55##].</p>", "<title>Inside the body</title>", "<p>Finally, in her keynote address, Kate Morrow described her collaboration with basic scientists. As they work to optimize microbicide gel deployment, her aim is to adequately measure individual perceptions' of deployment (or other product properties) and link them to biophysical characteristics – so that such characteristics can be assessed by the user. Such a linkage would enable product developers to more rationally select formulations that have a greater chance of success – because participants may be more adherent.</p>", "<title>Cross-cutting themes</title>", "<p>An important cross-cutting theme for the Microbicide 2008 Track C program was the need for social scientists to pay more attention to measurement. Topics pertaining to measurement included 1) the development and use of psychometric scales; 2) triangulation of information through mixed method approaches; and 3) assessment of different data collection strategies. In her keynote address, Geraldine Barrett described her work to develop a more valid and reliable measure of unplanned pregnancy for use in the United Kingdom. Barrett relied on a two step process, first using qualitative methods to identify and define key factors associated with women's attitudes towards a recent pregnancy; and then the use of quantitative methods to develop a six item psychometric scale that more accurately captures the range of positions women might have towards pregnancy. Kate Morrow used a similar process of qualitative research and psychometric scale development to behavioural tools that better assess women's perception of how microbicide products perform within the body.</p>", "<p>In addition to improving measures for specific concepts through psychometric scale development, Robert Pool provided examples of how the use of multiple data collection methods could improve understanding and ultimately the accuracy of data on adherence [##UREF##51##56##]. Ana Ventuneac described the advantages and shortcomings of three data collection strategies: 1) interactive voice response systems; 2) web-based and computer assisted self-interviews; and 3) use of hand-held devices [##UREF##52##57##]. Such approaches can increase privacy and frequency of data collection, thereby decreasing social desirability and recall biases that lead to inaccurate reporting.</p>", "<p>A second cross-cutting theme was the challenge of implementing behavioural and social science research in microbicide trials and the need for greater collaboration and networking within these disciplines [##UREF##53##58##].</p>", "<title>Track D – Policy, advocacy and community</title>", "<title>Kim Dickson</title>", "<p>Track D highlighted the issues of policy, advocacy and community relating to microbicides research, development, access and introduction. The Track D presentations and discussions revolved around the key themes of community involvement; managing stakeholders expectations; modelling the impact of microbicides introduction; engaging a broader audience in microbicides advocacy; and other key issues.</p>", "<title>Community involvement</title>", "<p>A keynote talk by Mangala Patil on defining the community and the importance of partnerships for HIV research emphasized how the community advisory board (CAB) has an important role to play to be the bridge between trial participants, the broader community in the region, and researchers, scientists and clinicians. Another key role of the CAB was to communicate effectively to dispel misconceptions or myths that participants or the trial community might have.</p>", "<p>The presentations on community involvement highlighted how community engagement has become more sophisticated with more innovative strategies being employed. These strategies included the use toll free lines, homes visits and peer educators. They outlined how civil society engagement helps microbicide trials in many ways, including: helping research to avoid pitfalls, maintaining accountability between researchers and community, mobilizing new public resources, facilitating open and fair communication between different stakeholders thereby increasing accountability and increasing trust in the communities. The presentations reinforced the importance of assessing the needs of the community and involving them in all stages of research.</p>", "<p>Although advocates continue to request for early community engagement in the protocol development process, including the concept development stage many researchers feel this is difficult. Morenike Ukpong presented new strategies to involve community at all levels [##UREF##54##59##].</p>", "<p>A presentation by Majorie Nakimuli [##UREF##55##60##] outlined the effectiveness of peer leaders in Uganda from the Makere/Mulago/CONRAD Center project in the mobilization, recruitment and retention of participants. These peer leaders worked alongside the CAB and belonged to the community where trial participants were from. They were crucial in mobilizing the community through training and leadership [##UREF##56##61##].</p>", "<p>Anna Forbes explained the process the Global Campaign for Microbicides spearheaded to identify seven key gaps in civil society involvement throughout the microbicide research and development and post-development process and make recommendations for seven key priority actions for how funders, researchers, governments, and civil society working together could address each of these gaps [##UREF##57##62##]. The Microbicide Development Strategy (MDS) also proposes a funding mechanism to donor agencies to provide a window to key civil society organizations working on microbicides research, advocacy and development.</p>", "<title>Managing stakeholder expectations of trial results</title>", "<p>Presentations in these sessions emphasized the importance of preparing for communications and unexpected results and the need to understand how to frame data to meet the needs of different audiences including advocates, policy makers, providers, participants and communities.</p>", "<p>A presentation from the Microbicides Media Initiative (MMCI) by Deborah Baron emphasized that developing clear, concise and consistent messages on interpreting trial results has become a top priority for the microbicides field whether studies are halted prematurely or finish on schedule [##UREF##58##63##]. The Microbicides Media and Communication Initiative (MMCI) was launched in 2005 to help the wider microbicide field anticipate and respond proactively to the communications challenges posed by large-scale trials in Africa and Asia. Since then, the MMCI has become a forum for communications staff, researchers and advocates to share expertise, resources and ideas across institutions and networks.</p>", "<title>Modelling the impact of microbicides introduction</title>", "<p>Charlotte Watts used mathematical modelling to explore the relationship between 'efficacy' and 'effectiveness' measures [##UREF##59##64##]. Phase III microbicide trials provide the strongest evidence about HIV impact. For coitally dependent products, inevitably the measure of trial effectiveness will be lower than the per sex act protection provided, with greater differences for lower consistency use. Estimates of contraceptive efficacy come from prospective observational studies comparing users with non-users. Non-user dependent methods are &gt; 96% effective, with rates less than 80% being viewed as inadequate. Estimates of condom HIV efficacy come from comparisons of infection rates among discordant couples with different reported levels of condom use, with meta analysis suggesting that consistent use reduces cumulative risk by 87%, and inconsistent use by 60%. The 90% – 95% condom efficacy term refers to per sex act reduction in risk, and is derived from modelling. Impact of microbicides is different on: risk per sex act, on individual risk if used overtime, on HIV incidence in a controlled trial setting and on population HIV incidence following widespread provision. The presentation concluded that the findings highlight the need for clarity in the way in which the terms 'efficacy' and 'effectiveness' are used across fields, and for care when communicating and interpreting trial results and that we need to find better ways of communicating the results to different stakeholders.</p>", "<p>An keynote presentation by Sally Blower on modelling the use of rectal microbicides in 'bathouses' concluded that moderately effective rectal microbicides (50% efficacy) with moderate use (30% use) could have substantial impact on HIV prevention in these bathouses. Blower highlighted the impact of anti retroviral based (ARV) based microbicides derived from modelling studies. She concluded that microbicides are important empowerment tools for women but paradoxically ARV based-microbicides could benefit men more than women in terms of infection prevented and infections prevented per resistant cases, especially if the microbicide was 'high-risk' (in terms of the possibility for acquiring resistance).</p>", "<title>Engaging a broader audience in microbicides advocacy</title>", "<p>Presentations in these sessions focused on the issues of rectal microbicides advocacy reaching young women and addressing the issues of HIV positive women.</p>", "<title>Rectal microbicides</title>", "<p>A comprehensive advocacy approach, spanning science, policy and the community, is needed to bring safe, acceptable and effective rectal microbicides to market. James Pickett of the International Rectal Microbicides Working Group expressed that data consistently reveal that men and women around the world engage in receptive anal intercourse, often without the use of a condom [##UREF##60##65##]. He stressed that the development of a rectal microbicide, which could provide some protection from HIV transmission during anal intercourse, is hampered by biological and scientific challenges, socio-cultural and political barriers such as stigma, denial and homophobia, and a lack of adequate resources necessary for the development of a robust pipeline of rectal microbicide candidates. He called for rectal safety studies on all viable vaginal microbicides and stressed that testing of additional commercial lubricants for rectal safety be encouraged and regulatory bodies and policies should be supportive too. Nesha Haniff presented her experiences of rectal microbicides advocacy through the work of Jamaica Aids Support for Life [##UREF##61##66##].</p>", "<title>Moving microbicides into susceptible populations</title>", "<title>Adolescents</title>", "<p>The topic of adolescents was covered in both track B and D. Martha Brady highlighted the gap in policy and programmes to build the social and health platform for the adolescents (10–19 years), youth (15–24 years), especially young girls [##UREF##62##67##]. Conventional \"youth programs\" and \"adolescent sexual reproductive health\" programs do not reach the majority of vulnerable adolescent girls, who remain overlooked and underserved. Any effort to reach adolescents girls and young women with a microbicide product would need to address the heterogeneity of this potential user group: they have diverse needs and situations they deal with. Targeted messages and a range of protection strategies and services for a diverse group of girls will be needed.</p>", "<title>Microbicides and HIV positive women</title>", "<p>Sean Philpott, Louise Binder [##UREF##63##68##] and a roundtable panel of HIV positive women, researchers and advocates stressed the need to involve HIV positive women in microbicides research. They mentioned that as microbicides are being developed, HIV-positive women are raising numerous issues related to safety, trial design and ethics, which require consideration and implementation in current trials and future research. The roundtable discussions outlined how research with HIV positive women and engagement of HIV positive women in advocacy has increased. The discussions emphasized that communication channels to keep HIV positive women's groups apprised of new developments on microbicides research should be developed.</p>", "<title>Other key issues</title>", "<p>Helen Rees's insightful key note on lessons from experience with other reproductive health technologies stressed that introduction of new products and widespread access and use take a long time; it took more than 30 years for the tampon to gain widespread acceptability and use. Lessons drawn from the introduction of the Lippes Loop and Norplant have taught us to carefully evaluate service capability, the technology and consumer acceptability before introducing new technologies. Rees summarised key lessons from product introduction as; price; political context; distribution channel; marketing and targeting of advertising.</p>", "<p>Panel sessions were held to discuss issues key issues including; 'Confronting the evidence' and planning for introduction and access. The 'evidence' discussion concluded that the level 'evidence' needed differs depending on the 'perceived' acceptability of the intervention, the researcher and complexity of implementation. Participants and communities need to be consulted about what evidence is acceptable and informed of new findings. The 'access and introduction' session revealed that; sponsors and trialists are working together and thinking about access after Phase III trials and are including cost, distribution and manufacturing in contracts to access their products for trials.</p>", "<title>Satellite sessions and workshops</title>", "<p>In addition to the full scientific programme, there were several satellite sessions. The NIH held a grantsmanship workshop for young investigators which included sessions on the components of a successful grant application, electronic submission tips, funding opportunities for international investigators and opportunities for collaboration.</p>", "<p>There was a workshop for junior social scientists organized by the Office for AIDS Research (OAR) which covered a wide range of pertinent topics related to social science research within a clinical trial setting.</p>", "<p>A pre-conference workshop on 'Health Advocacy\" was co-hosted by AMAG, GCM, INN, NCHI and PWN. The workshop aimed to provide a status report on microbicide science and advocacy including the history of the field, a snapshot of the current status of the field, and discussion on some of the issues that participants were likely to raise.</p>", "<p>The Alliance of Microbicide Development had a workshop on industrializing microbicides which covered a wide range of topics such as toxicology guidelines, manufacturing chemical and biological microbicides, intellectual property considerations and regulatory issues.</p>", "<p>A symposium on rectal microbicides was co-hosted by AMFAR, UCLA AIDS Institute and the University of Pittsburgh. The objective was to provide an overview of recent advances in rectal microbicide development, improvement in applicator design and an update on advocacy directed towards increasing funding for rectal microbicide research.</p>", "<p>Finally, there was a workshop on ARV and ARV resistance hosted by NIH/OAR. Given the importance of the topic with recent advances in microbicide and PreP (Pre-exposure Prophylaxis) trials, this workshop covered an overview of the microbicide pipeline, description of ARV resistance and the impact of potential resistance on participants, and some of the key challenges in ARV-based microbicide clinical trials.</p>" ]

[ "<title>Methodological issues in the design and implementation of clinical trials</title>", "<p>Doug Taylor gave a very informative talk on statistical power. He expressed the challenges we face in assessing trial outcomes on factors that impact on power. There are several factors that contribute to the power of the study to show efficacy. These include high retention rates, adherence to product use, women taken off the product due to pregnancy and high incidence rates. He expressed the importance of conducting effectiveness trials over efficacy trials. To overcome the challenges of high incidence of pregnancy and its impact on power, new generation of products will be tested for safety during pregnancy.</p>", "<p>Zeda Rosenberg discussed the challenges in doing phase III studies with enough power when a product is believed to be effective in preventing HIV transmission. She explained that the current trials do not measure efficacy, but it is inferred that a woman has become infected after unknown number of sex acts. She stressed that effectiveness trials are more important because they measure both efficacy as well as adherence. It is being increasingly felt that alternative study designs should be employed for the fast tracking of microbicide development and testing. The best among the next generation products must be selected for safety evaluation and should be evaluated early for futility after employing measures to improve adherence. They should be powered for licensure. Alternate studies of superior design will allow for improved ways of measuring adherence and reductions of risk taking behaviour, and at the same time test the effectiveness of the product in HIV prevention.</p>" ]

[ "<title>Managing stakeholder expectations of trial results</title>", "<p>Presentations in these sessions emphasized the importance of preparing for communications and unexpected results and the need to understand how to frame data to meet the needs of different audiences including advocates, policy makers, providers, participants and communities.</p>", "<p>A presentation from the Microbicides Media Initiative (MMCI) by Deborah Baron emphasized that developing clear, concise and consistent messages on interpreting trial results has become a top priority for the microbicides field whether studies are halted prematurely or finish on schedule [##UREF##58##63##]. The Microbicides Media and Communication Initiative (MMCI) was launched in 2005 to help the wider microbicide field anticipate and respond proactively to the communications challenges posed by large-scale trials in Africa and Asia. Since then, the MMCI has become a forum for communications staff, researchers and advocates to share expertise, resources and ideas across institutions and networks.</p>" ]

[ "<title>Special cross track sessions: Key-note addresses, symposia and panel discussions</title>", "<p>Within track B three symposia were organized on \"Rectal Microbicides\", \"Moving Microbicides into susceptible populations\" (discussed under track D) and \"Microbicides and HIV positive women\" (discussed under track D) and two key-note addresses on \"Methodological issues in design and implementation of clinical trials\". Additionally, two panel discussions were conducted on the \"Impact of other HIV prevention trials\" and \"Clinical safety studies\". The major observations during these sessions are summarized below.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Recently revised statistics show the number of individuals living with HIV at over 33 million worldwide, with 68% being in sub-Saharan Africa. Current HIV prevention methods, such as condom use, monogamy and abstinence, are not always feasible. The need for improved HIV preventative technologies remains urgent. Of these, microbicides represent a promising female-initiated preventative method. Microbicides are designed to be applied vaginally to prevent HIV and STI acquisition. Research is also being undertaken to assess the safety of the product during rectal application.</p>", "<p>The biannual Microbicides conference took place in New Delhi, India from 24–27 February 2008. The conference was open to delegates from the scientific and medical fields, as well as communities and advocates. In addition to microbicide research and development, the conference afforded the opportunity for the discussion of key issues such as ethics, acceptability, access, and community involvement.</p>", "<p>In this conference report we provide brief summaries of recent advancements made and challenges experienced in microbicide research and development, including updates on basic and clinical science, social and behavioural science, and community mobilisation and advocacy activities pertaining to clinical trials.</p>" ]

[ "<title>Summary</title>", "<p>The Microbicides 2008 Conference in New Delhi was a resounding success. Despite the recent set backs in the HIV prevention field, with many products showing lack of effectiveness in preventing HIV, the scientists at the conference showed progress in the field of basic science. Valuable lessons learned from previous trials across all disciplines from basic and social sciences, as well as community involvement and advocacy, have greatly improved our understanding of the complexity of conducting HIV prevention research in a resource poor setting. Scientists reaffirmed their commitment to a continued search for a women-initiated HIV prevention option. The next meeting, planned for 2010, will be held in Pittsburgh, USA. The conference will be chaired by Sharon Hillier, Ian McGowan, and Gita Ramjee.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>GR co-chaired the Microbicides 2008 conference, invited author contributions for the various track summaries, provided summaries of general sessions and workshops, and edited this manuscript. Summaries of conference tracks A, B, C, and D, where written by GFD, SM, EET, and KD, respectively. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We would like to acknowledge the enormous time, effort and dedication of the conference chairs Nomita Chandhiok, Badri Saxena and Gita Ramjee for co-chairing this conference, the conference track chairs for track A: Gustavo Doncel, Robin Shattock and CP Puri, track B: Sanjay Mehendale, Roshini Govinden and Sharon Hillier; track C: Elizabeth Tolley, Neetha Morar and Will Stones and track D: Kim Dickson, Kelly Blanchard and Radium Bhattacharya, the scientific advisory committee, who provided guidance on the development of the program and the numerous plenary and session speakers for their invaluable contribution to the conference agenda and all the participants from around the globe who attended this conference and made it a resounding success. We also thank Yoshan Moodley for his assistance in preparing this manuscript.</p>" ]

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[ "<title>Background</title>", "<p>Gastrointestinal cancer, including cancers of the oesophagus, stomach, small intestine, colon, rectum and liver etc, is a major medical and economic burden worldwide. Although the incidence and mortality of gastrointestinal cancer has been gradually decreasing for decades, some common types of gastrointestinal cancer are steadily in the top five leading cause of new cancer cases and deaths, such as gastric cancer, colon and rectal cancer[##REF##15761078##1##]. Multiple factors have been proposed to play important roles in human carcinogenesis, however, the exact mechanism of gastrointestinal cancer development still remains unclear.</p>", "<p>Mammalian cells contain three functional <italic>RAS </italic>proto-oncogenes, known as <italic>H-RAS</italic>, <italic>K-RAS</italic>, and <italic>N-RAS</italic>, which encode small GTP-binding proteins in terms of p21^rass. The RAS proteins are GTPases that bind to GTP and GDP nucleotides[##REF##9696882##2##]. The switch between their inactive (GDP-bound) and active (GTP-bound) forms, together with their ability to bind to target proteins, provides the mechanism for the downstream transmission of the cellular signals. Their natural role is to relay extracellularly derived signals to a number of pathways controlling cellular proliferation and differentiation[##REF##12118316##3##]. <italic>RAS </italic>genes have been elucidated as major participants in the development and progression of a series of human tumours, such as gastrointestinal cancer, lung cancer and breast cancer. It was reported that just one point mutation occurring in codon12, 13 or 61 could result in continuous stimulation of cell proliferation or, alternatively, a 5- to 50-fold amplification of the wild type gene[##REF##12115718##4##]. As a result, the codon12, 13 and 61 are also called mutation hotpots. Numerous epidemiological studies on pancreatic, gastric, colorectal and non-small cell lung cancer evaluate the potential role of these mutation hotspots, but the results are still conflicting up to now [##REF##2199031##5##, ####REF##1671796##6##, ##REF##10806811##7##, ##REF##11605075##8####11605075##8##].</p>", "<p>Besides the mutation hotspots of <italic>H-RAS </italic>mentioned above, another single nucleotide polymorphism at <italic>H-RAS </italic>cDNA position 81 T→C (rs12628), primarily found by Taparowsky et al in 1982[##REF##7177195##9##], was shown to be associated with the risk of human cancers as well. Johne's research indicated that the individuals harbouring the homozygous C-genotype of the <italic>H-RAS </italic>T81C were at an increased risk of bladder cancer [##REF##12540507##10##]. More recently, it was demonstrated that the variant C allele of this genetic polymorphism could increase the risk of oral carcinoma, particularly in male population[##REF##16488657##11##]. However, the number of studies conducted to examine the <italic>H-RAS </italic>T81C polymorphism is not sufficient; moreover, the results of them are controversial yet. Especially, there is a lack of investigation on gastrointestinal cancer, such as gastric, colon and rectal cancer.</p>", "<p>Therefore, in the present research, we hypothesize that the <italic>H-RAS </italic>T81C polymorphism may have an effect on the <italic>H-RAS </italic>expression and activity, and ultimately may play a role in modulating the susceptibility to gastrointestinal cancer. In order to verify our hypothesis, a population based case-control study was conducted to investigate the association between the <italic>H-RAS </italic>T81C genotypes and the risk of gastrointestinal cancer in Chinese population. In addition, a meta-analysis was performed to estimate the risk of <italic>H-RAS </italic>T81C polymorphism for cancers.</p>" ]

[ "<title>Methods</title>", "<title>Study subjects</title>", "<p>This population-base case-control study included 296 gastrointestinal cancer patients and 448 healthy controls, and the details of the study population had been described previously[##REF##16724991##12##,##REF##17603900##13##]. In brief, the registry information of this population was initially collected for a cohort study on colorectal cancer in 1989 in Jiashan County, Zhejiang Province, China. Meanwhile a cancer surveillance and registry system covering the whole county was established for reporting new cancer patients of colorectal cancer and all other kinds of cancers. There were no age, gender, or stage restrictions, but patients with other malignant disease in their medical history were excluded. 296 eligible patients with histologically confirmed gastric cancer, colon cancer or rectal cancer reported by the cancer registry system were included as cases in the study. Gastric cancer patients consisted of 64 males and 26 females from 45 to 78 years old, while colon and rectal cancer patients consisted of 105 males and 101 females from 35 to 81 years old. Simultaneously, 448 population controls who did not have a history of cancer were selected randomly and recruited from all permanent residents listed in the cancer registry system during the same period. All the participants were ethnic Han Chinese residents in Jiashan County.</p>", "<p>At the beginning of investigation, written informed consent was obtained from each participant, and then they were face-to-face interviewed by professionally trained interviewers using a structured questionnaire, including demographic characteristics, personal habits (cigarette smoking, alcohol drinking, etc) and health factors (family history of cancer at any site including all first- and second-degree relatives of both genders, medical and dietary history, etc). Individuals who smoked ≥1 cigarette per day for over 1 year were defined as smokers, and those consumed ≥1 alcohol drinks per day for over 3 months were considered as drinkers. In addition, a 2 ml venous blood sample was drawn from each subject with the permission and saved in vacuum tube containing sodium citrate anticoagulation. This study was performed with the approval of the Medical Ethical Committee of Zhejiang University School of Medicine. The blood samples were stored at -60°C ultra low temperature freezers for DNA isolation.</p>", "<title><italic>H-RAS </italic>T81C genotyping</title>", "<p>The genomic DNA was extracted from peripheral blood samples using modified salting-out procedure as previously reported[##REF##16302208##14##]. The DNA concentration and purity was measured using BioPhotometer (Eppendorf, Hamburg, Germany) at 260 nm.</p>", "<p>For determination of the <italic>H-RAS </italic>genetic polymorphism 81 T→C, Polymerase Chain Reaction – Restriction Fragment Length Polymorphism (PCR-RFLP) assay was performed at the Molecular Epidemiology Laboratory in the Zhejiang University School of Medicine. The sequence of the oligonucleotide primers and the conditions for PCR amplification were reported elsewhere[##REF##12540507##10##]. A 200 bp DNA segment was amplified using forward primer 5'-CTTGGCAGGTGGGGCAGGAGA-3' and reverse primer 5'-GGCACCTGGACGGCGGCGCTAG-3'. The PCR mixture (20 μl) contained 2 μl of 10 × PCR buffer, 2 μl of deoxyribonucleotide triphosphates (dNTPs, 2 mM each), 1.6 μl MgCl₂(25 mM each), 0.2 μl of each primer (10 μM each), 0.5 μl genomic DNA (~50 ng) and 0.5 Unit of <italic>Taq </italic>DNA polymerase (Sangon, Shanghai, China). After 5 min of initial denaturation at 94°C in PTC-200 thermal cycler (BioRad, USA), the prepared PCR mixtures were subjected to 35 cycles of denaturation for 30 s at 94°C, annealing for 30 s at 50°C and extension for 30 s at 72°C. A final extension period of 5 min at 72°C was performed to completed the reaction. Subsequently, 6 μl of amplified product was added with 1 μl of 10× digestion buffer containing 3 units DraIII (New England Biolabs, Schwalbach, Germany). After 6 hours digestion at 37°C, the products were separated by electrophoresis on a 2% agarose gel stained with ethidium bromide and observed on an ultraviolet fluorescence imaging system. The CC homozygote with DraIII restriction site was cut into fragments of 145 bp and 55 bp, while the 81TT homozygote presented a single fragment of 200 bp. About 10% of the samples were selected randomly to be identified repeatedly for accuracy, and the results were 100% concordant. The genotype assay described above was done with case/control status blinded to the laboratory technician.</p>", "<title>Statistical analysis</title>", "<p>Pearson's χ²test was used for comparing the distributions of the demographic characteristics, personal habits such as cigarette smoking and alcohol drinking etc, and the distribution of <italic>H-RAS </italic>T81C allele types and genotypes between cases and controls. Hardy-Weinberg equilibrium was tested by a goodness-of-fit χ²test to compare the observed genotype frequencies within the case-control groups to the anticipated genotype frequencies calculated from the observed allele frequencies. Unconditional logistic regression analysis was performed to calculate the odds ratios (ORs) with 95% confidence intervals (95% CIs) for estimating the association between certain genotype and cancers with adjustment for potential confounding factors, including age (as a continuous variable), gender, smoking, drinking and family history of cancer (as dichotomous variables). <italic>H-RAS </italic>T81C polymorphism was analyzed as dichotomized variable using TT genotype as the reference category. Stratified analyses were used to explore potential gene-environment interactions. A <italic>p </italic>value of less than 0.05 indicated statistical significance. In the meta-analysis, raw data for genotype frequencies, without adjustment, were used for calculation of the estimates of OR. The extent of heterogeneity was examined by the Cochran's χ²test. The statistical analyses were performed with Statistical Analysis System software version 8.0 (SAS Institute, Cary, NC) and the meta-analysis was carried out using RevMan software version 4.2.</p>" ]

[ "<title>Results</title>", "<p>The demographic characteristics and personal habits of the study subjects were summarized in Table ##TAB##0##1##. There was no significant difference in gender, age, family history of cancer, smoking and drinking status among colon cancers, rectal cancers and healthy controls. Otherwise, the age, gender and smoking status were significantly different between gastric cancers and controls.</p>", "<p>The observed genotype distributions of <italic>H-RAS </italic>T81C among cases and controls were shown in Table ##TAB##0##1## as well. In healthy controls, the frequencies of TT, TC and CC genotypes were 79.24%, 19.87% and 0.89%, which did not deviate from the Hardy-Weinberg equilibrium (χ²= 0.375, p = 0.541), while those frequencies were 53.33%, 44.44% and 2.22% in gastric cancer patients, respectively. The frequency of C allele observed in gastric cancers was about 24.44% which was significantly higher than that in controls 10.83% (χ²= 24.413, p &lt; 0.0001). Meanwhile, the frequencies of C allele in colon cancer and rectal cancer, 12.90% and 12.39% respectively, were also higher than that in controls. However, no significant difference in genotype or allele distribution was found among colon cancer, rectal cancer and controls (data not shown).</p>", "<p>Furthermore, crude ORs and adjusted ORs were calculated to evaluate the risk of gastrointestinal cancer. Compared with TT genotype, the TC genotype was significantly associated with a increased risk of gastric cancer (crude OR = 3.32, 95%CI = 2.06–5.37, p &lt; 0.0001), and the CC genotype with more risk, crude OR was 3.69, but it was not statistically significant, this may be due to limited number of CC genotype carriers. The same results were observed after adjustment (shown in Table ##TAB##1##2##). In contrast, the TC genotype was not significantly increased in colon cancer and rectal cancer patients. Since <italic>H-RAS </italic>is one of proto-oncogene, mutation of which could confer a dominant negative phenotype, and the frequency of the CC genotype is very low (&lt;0.05), further analysis was performed by combining TC and CC genotypes compared against TT genotype. As a result, a statistically significant risk with adjusted OR of 3.65 (95%CI, 2.22–6.00, p &lt; 0.0001) was found in gastric cancer, while no significant association of <italic>H-RAS </italic>T81C polymorphism with colon cancer and rectal cancer was observed. In addition, the effect of <italic>H-RAS </italic>T81C polymorphism was further examined by stratification of age, gender, family history, smoking and drinking status. However, no significant gene-environment interaction in relation to gastric cancer, colon cancer and rectal cancer was found (data not shown).</p>", "<p>Three other studies on <italic>H-RAS </italic>T81C polymorphism and cancer risk were available in the literature including bladder, thyroid and oral cancer patients. Because of the small sample size of these studies, we carried out a meta-analysis to obtain an overall assessment of the effects of the <italic>H-RAS </italic>T81C polymorphism on human cancers, which was examined according to <italic>H-RAS </italic>genotype in all published studies and in our patients. As presented in Fig. ##FIG##0##1##, the test for heterogeneity was not significant (χ²= 9.87, p = 0.02), suggesting that the random effect model could be used to assess the odds ratio. The pooled odds ratio was 1.38 (95% CI, 1.01–1.98), which was significant.</p>" ]

[ "<title>Discussion</title>", "<p>A multi-factorial model of human carcinogenesis is currently accepted, according to which different dietary and non-dietary factors, including genetic susceptibility, are involved at different stages in the cancer process[##REF##12589864##15##]. <italic>RAS </italic>gene, serving as molecular switches in pivotal processes governing cellular growth and differentiation, have been found to be amplified and over expressed in gastric carcinomas[##REF##11092455##16##,##REF##12204060##17##]. Several molecular alternations in <italic>RAS </italic>gene have been identified such as minisatellites and mutations, however, research on the single nucleotide polymorphism in <italic>RAS </italic>gene was rare [##REF##12115538##18##, ####REF##11807778##19##, ##REF##12668612##20####12668612##20##]. In the present study, analyses of the polymorphism of <italic>H-RAS </italic>T81C in gastrointestinal cancer patients were carried out compared with healthy controls. The frequency of C allele in the Chinese healthy population was 10.83%, which was lower than that in Johne's study (26.42% in Germany)[##REF##12540507##10##] and Sathyan's study (20.00% in India)[##REF##16488657##11##]. This observation indicates that the distribution of <italic>H-RAS </italic>T81C polymorphism seems to be genetically different in various ethnics. In the aforementioned study, they reported that <italic>H-RAS </italic>81CC homozygous genotype showed 2-fold risk of bladder cancer and oral cancer. In this study, a statistically significant increased risk for gastric cancer was observed in the TC and CC genotypes combination compared to the TT genotype, and the adjusted OR achieved 3.65, which indicated that <italic>H-RAS </italic>T81C polymorphism is a strongly susceptibility factor for the development of gastric cancer. On the other hand, we did not find any association of <italic>H-RAS </italic>T81C polymorphism with colon cancer and rectal cancer, which derived from the same population.</p>", "<p>However, this epidemiological study could not provide the mechanism by which <italic>H-RAS </italic>T81C polymorphism modifies risk of different kinds of cancer. Although <italic>RAS </italic>gene is ubiquitously expressed, the mRNA analysis reveals different tissue expression levels suggesting that <italic>RAS </italic>family members probably are expressed in a tissue specificity fashion[##REF##12118316##3##]. <italic>K-RAS </italic>is mostly expressed in the pancreas, colorectal and non-small cell lung cancer, while <italic>H-RAS </italic>is common in squamous cell carcinomas, bladder carcinomas and renal cancers. <italic>K-RAS </italic>mutations have been found in 15%–68% of sporadic colorectal cancer[##REF##16699851##21##]. Keller et al. reported that endogenous K-RAS resulted in the most dramatic effect of the <italic>RAS </italic>isoforms (K &gt; H or N) in human colorectal cancer cells[##REF##17133351##22##]. However, <italic>K-RAS </italic>mutations are rarely observed in gastric cancer[##REF##12204060##17##,##REF##10430398##23##,##REF##10833479##24##] and increased expression of the <italic>H-RAS </italic>oncogene product was found in gastric cancer[##REF##2434216##25##,##REF##3315826##26##]. Consistent with the tissue specificity hypothesis, our finding suggested that the <italic>H-RAS </italic>gene played a more important role in gastric cancer than in colorectal cancer. Although this polymorphism does not lead to the alternation of RAS protein structure, it affects the cancer susceptibility possibly through linkage disequilibrium with other potential functional variant of <italic>H-RAS</italic>. One of the linkage candidate is a region of variable tandem repeats about 1 kb downstream exon4, with a possible transcriptional enhancer activity[##REF##1598201##27##]. Another associated polymorphic site is hexanucleotide repeat located about 80 bp upstream of the 5'-end of exon1[##REF##11376808##28##]. Recently, it is reported that <italic>H-RAS </italic>T81C might be serve as a marker of other polymorphisms in intron D2 of <italic>H-RAS </italic>that would act as regulators of IDX inclusion[##REF##16532025##29##]. As it was not examined in the present study, it would be interesting to conduct more studies on the linkage of <italic>H-RAS </italic>T81C polymorphism with the other candidate polymorphic sites in order to reveal the underlying mechanism.</p>", "<p>It has been suggested that sample size is always an issue of concern in the case-control analysis and statistical power of the analysis would generally increase with increasing size of sample[##REF##15955593##30##]. We only recruited 296 survival cases and the sample size might not be large enough to detect the low penetrance effect of the genes, especially for the SNPs with low frequency. Therefore, we pooled all published data together with ours, and then performed a meta-analysis to examine the association between the <italic>H-RAS </italic>T81C polymorphism and the cancer risk. Overall, the C allele carriers, including TC genotype and CC genotype carriers, have a 38% increased risk of cancer. It is reasonable to believe that the variant of <italic>H-RAS </italic>gene could be associated with cancer risk, and it will be of interest in test if this genetic polymorphism is associated with increased risk of other malignant tumors.</p>", "<p>Another limitation should be addressed in this study. <italic>Helicobacter pylori </italic>infection has been defined as a crucial risk factor for gastric cancer by numerous intensive researches, which lead to an improved understanding of the etiology and pathogenesis [##REF##11556297##31##]. Unfortunately, information of <italic>Helicobacter pylori </italic>infection in our study is not available, as a result of that we can not analyze the interaction between <italic>H-RAS </italic>polymorphism and <italic>Hp </italic>infection status.</p>" ]

[ "<title>Conclusion</title>", "<p>In summary, this study provides the evidences that the polymorphism of <italic>H-RAS </italic>T81C may be a risk factor for the development of gastric cancer in a Chinese population. Because this is the first study to report the significant association between <italic>H-RAS </italic>T81C polymorphism and gastric cancer susceptibility, additional studies with large sample size and detailed <italic>Hp </italic>infection information on gastric cancer are warranted in different ethnic populations to confirm our findings.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Gastrointestinal cancer, such as gastric, colon and rectal cancer, is a major medical and economic burden worldwide. However, the exact mechanism of gastrointestinal cancer development still remains unclear. <italic>RAS </italic>genes have been elucidated as major participants in the development and progression of a series of human tumours and the single nucleotide polymorphism at <italic>H-RAS </italic>cDNA position 81 was demonstrated to contribute to the risks of bladder, oral and thyroid carcinoma. Therefore, we hypothesized that this polymorphisms in <italic>H-RAS </italic>could influence susceptibility to gastrointestinal cancer as well, and we conducted this study to test the hypothesis in Chinese population.</p>", "<title>Methods</title>", "<p>A population based case-control study, including 296 cases with gastrointestinal cancer and 448 healthy controls selected from a Chinese population was conducted. <italic>H-RAS </italic>T81C polymorphism was genotyped by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) assay.</p>", "<title>Results</title>", "<p>In the healthy controls, the TT, TC and CC genotypes frequencies of <italic>H-RAS </italic>T81C polymorphism, were 79.24%, 19.87% and 0.89%, respectively, and the C allele frequency was 10.83%. Compared with TT genotype, the TC genotype was significantly associated with an increased risk of gastric cancer (adjusted OR = 3.67, 95%CI = 2.21–6.08), while the CC genotype showed an increased risk as well (adjusted OR = 3.29, 95%CI = 0.54–19.86), but it was not statistically significant. In contrast, the frequency of TC genotype was not significantly increased in colon cancer and rectal cancer patients. Further analysis was performed by combining TC and CC genotypes compared against TT genotype. As a result, a statistically significant risk with adjusted OR of 3.65 (95%CI, 2.22–6.00) was found in gastric cancer, while no significant association of <italic>H-RAS </italic>T81C polymorphism with colon cancer and rectal cancer was observed.</p>", "<title>Conclusion</title>", "<p>These findings indicate, for the first time, that there is an <italic>H-RAS </italic>T81C polymorphism existing in Chinese population, and this SNP might be a low penetrance gene predisposition factor for gastric cancer.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>YZ participated in the design of the study, SNP genotyping, and drafted the manuscript. MJ, BL participated in SNP genotyping and performed the statistical analysis. XM, KY and QL participated in data collection. KC conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2407/8/256/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>This study was supported by the grant from National Natural Science Foundation of China (NSFC 30471492) and Zhejiang Natural Science Foundation (ZJNSF R205319).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Meta-analysis of H-RAS T81C polymorphism for all cancers.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Distribution of selected characteristics in the study subjects</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"4\"><bold>Cases</bold><break/><bold>No.(%)</bold></td><td align=\"center\"><bold>Controls</bold><break/><bold>No.(%)</bold></td></tr><tr><td/><td colspan=\"4\"><hr/></td><td/></tr><tr><td/><td align=\"center\"><bold>Gastrointestinal cancer</bold></td><td align=\"center\"><bold>Gastric cancer</bold></td><td align=\"center\"><bold>Colon cancer</bold></td><td align=\"center\"><bold>Rectal cancer</bold></td><td/></tr></thead><tbody><tr><td align=\"left\">No. of subjects</td><td align=\"center\">296</td><td align=\"center\">90</td><td align=\"center\">93</td><td align=\"center\">103</td><td align=\"center\">448</td></tr><tr><td align=\"left\">Gender</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Male</td><td align=\"center\">169(57.09)</td><td align=\"center\">64(71.11)</td><td align=\"center\">48(51.61)</td><td align=\"center\">57(50.44)</td><td align=\"center\">223(49.78)</td></tr><tr><td align=\"left\"> Female</td><td align=\"center\">127(42.91)</td><td align=\"center\">26(28. 89)</td><td align=\"center\">45(48.39)</td><td align=\"center\">56(49.56)</td><td align=\"center\">225(50.22)</td></tr><tr><td align=\"left\">Age</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Mean ± SD</td><td align=\"center\">61.76 ± 9.92</td><td align=\"center\">64.68 ± 9.01</td><td align=\"center\">61.59 ± 8.87</td><td align=\"center\">59.57 ± 10.89</td><td align=\"center\">60.67 ± 10.92</td></tr><tr><td align=\"left\">Smoking</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> No</td><td align=\"center\">156(52.70)</td><td align=\"center\">33(36.67)</td><td align=\"center\">53(56.99)</td><td align=\"center\">70(61.95)</td><td align=\"center\">269(60.04)</td></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">140(47.30)</td><td align=\"center\">57(63.33)</td><td align=\"center\">40(43.01)</td><td align=\"center\">43(38.05)</td><td align=\"center\">179(39.96)</td></tr><tr><td align=\"left\">Drinking</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> No</td><td align=\"center\">202(68.24)</td><td align=\"center\">56(62.22)</td><td align=\"center\">65(69.89)</td><td align=\"center\">81(71.68)</td><td align=\"center\">322(71.88)</td></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">94(31.76)</td><td align=\"center\">34(37.78)</td><td align=\"center\">28(30.11)</td><td align=\"center\">32(28.32)</td><td align=\"center\">126(28.13)</td></tr><tr><td align=\"left\">Family history</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> No</td><td align=\"center\">212(71.62)</td><td align=\"center\">68(75.56)</td><td align=\"center\">68(73.12)</td><td align=\"center\">76(67.26)</td><td align=\"center\">338(75.45)</td></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">84(28.38)</td><td align=\"center\">22(24.44)</td><td align=\"center\">25(26.88)</td><td align=\"center\">37(32.74)</td><td align=\"center\">110(24.55)</td></tr><tr><td align=\"left\"><italic>H-RAS </italic>T81C</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> TT</td><td align=\"center\">204(68.92)</td><td align=\"center\">48(53.33)</td><td align=\"center\">71(76.34)</td><td align=\"center\">85(75.22)</td><td align=\"center\">355(79.24)</td></tr><tr><td align=\"left\"> TC</td><td align=\"center\">88(29.73)</td><td align=\"center\">40(44.44)</td><td align=\"center\">20(21.51)</td><td align=\"center\">28(24.78)</td><td align=\"center\">89(19.87)</td></tr><tr><td align=\"left\"> CC</td><td align=\"center\">4(1.35)</td><td align=\"center\">2(2.22)</td><td align=\"center\">2(2.15)</td><td align=\"center\">0(0.00)</td><td align=\"center\">4(0.89)</td></tr><tr><td align=\"left\">Allele frequencies</td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> T</td><td align=\"center\">496(83.78)</td><td align=\"center\">136(75.56)</td><td align=\"center\">162(87.10)</td><td align=\"center\">198(87.61)</td><td align=\"center\">799(89.17)</td></tr><tr><td align=\"left\"> C</td><td align=\"center\">96(16.22)</td><td align=\"center\">44(24.44)</td><td align=\"center\">24(12.90)</td><td align=\"center\">28(12.39)</td><td align=\"center\">97(10.83)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>H-RAS T81C polymorphism and gastrointestinal cancer risk</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Genotype</bold></td><td align=\"center\" colspan=\"2\"><bold>Gastrointestinal cancer</bold></td><td align=\"center\" colspan=\"2\"><bold>Gastric cancer</bold></td><td align=\"center\" colspan=\"2\"><bold>Colon cancer</bold></td><td align=\"center\" colspan=\"2\"><bold>Rectal cancer</bold></td></tr><tr><td/><td colspan=\"8\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>Crude OR</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Adjusted OR*</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Crude OR</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Adjusted OR</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Crude OR</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Adjusted OR</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Crude OR</bold><break/><bold>(95%CI)</bold></td><td align=\"center\"><bold>Adjusted OR</bold><break/><bold>(95%CI)</bold></td></tr></thead><tbody><tr><td align=\"center\">TT</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td><td align=\"center\">1.00</td></tr><tr><td align=\"center\">TC</td><td align=\"center\">1.72(1.22, 2.42)</td><td align=\"center\">1.74(1.23, 2.46)</td><td align=\"center\">3.32(2.06, 5.37)</td><td align=\"center\">3.67(2.21, 6.08)</td><td align=\"center\">1.12(0.65, 1.94)</td><td align=\"center\">1.15(0.66, 1.99)</td><td align=\"center\">1.26(0.76, 2.04)</td><td align=\"center\">1.25(0.77, 2.04)</td></tr><tr><td align=\"center\">CC</td><td align=\"center\">1.74(0.43, 7.03)</td><td align=\"center\">1.66(0.41, 6.77)</td><td align=\"center\">3.69(0.66, 20.73)</td><td align=\"center\">3.29(0.54, 19.86)</td><td align=\"center\">2.50(0.45, 13.91)</td><td align=\"center\">2.57(0.46, 14.46)</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"center\">TC+CC</td><td align=\"center\">1.72(1.23, 2.41)</td><td align=\"center\">1.74(1.24, 2.44)</td><td align=\"center\">3.34(2.08, 5.36)</td><td align=\"center\">3.65(2.22, 6.00)</td><td align=\"center\">1.18(0.70, 2.01)</td><td align=\"center\">1.20(0.71, 2.06)</td><td align=\"center\">1.26(0.76, 2.04)</td><td align=\"center\">1.25(0.77, 2.04)</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p><bold>*</bold>OR adjusted for age, gender, family history, status of cigarette smoking and alcohol drinking</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2407-8-256-1\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The functional role of DNA methylation includes maintaining the stability of chromosomes, silencing repetitive sequences, arresting the deleterious effects of integrated foreign DNA and controlling gene expression [##REF##16136652##1##]. Genome-wide loss of the methyl group at 5-methyl cytosines (hypomethylation) leads to the destabilization of the DNA [##REF##15948710##2##]. Global DNA hypomethylation has been observed to be one of the earliest molecular abnormalities described in human neoplasia [##REF##15489135##3##,##REF##14732866##4##]. This biological phenomenon could be exploited to gain an insight into the mechanism of action of DNA methylation to determine how it plays a role not only in disease but also in aging, diet and efficacy of drugs.</p>", "<p>Several technologies have been developed to measure the methyl content of the genome. In general the techniques have been focused around the use of methodologies that can quantitate the 5-methyl cytosines using reversed-phase high performance liquid chromatography (RP-HPLC), two dimensional thin layer chromatography (2D-TLC), high performance liquid chromatography-mass spectrometry (HPLC-MS), high performance capillary electrophoresis (HPCE) and liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) [##REF##7003544##5##, ####REF##3963364##6##, ##REF##2745598##7##, ##REF##12179987##8##, ##REF##15649046##9##, ##REF##12527791##10####12527791##10##]. These approaches represent the gold standards of measuring global DNA methylation but lack the capacity for high-throughput sample handling, require expensive equipment to analyze the material and involve highly specialized skill sets. Other approaches that have been developed to quantitate the global 5-methyl cytosines include radio-labeling the CpG sites using M.SssI methyltransferase, methyl-C antibody, pyrosequencing and methyl sensitive restriction enzymes [##REF##8323540##11##, ####REF##11131565##12##, ##REF##14973332##13##, ##REF##10471374##14##, ##REF##12202260##15##, ##REF##17998810##16##, ##REF##16624287##17####16624287##17##]. We have developed an approach that has been adapted from a method that uses methyl sensitive restriction enzymes. These enzymes have been used to define the methylation status of both the whole genome and specific regions using a host of technologies [##REF##10471374##14##, ####REF##12202260##15##, ##REF##17998810##16##, ##REF##16624287##17####16624287##17##]. In this paper we present <italic>CpG</italic>lobal, a non-radioactive, non-PCR, high-throughput approach to measure global DNA methylation. It describes how <italic>CpG</italic>lobal is performed in a microtiter plate, which enables multiple samples to be analyzed simultaneously. Furthermore, this paper illustrates how the assay utilizes biotinylated nucleotides to provide a highly accurate and reproducible method that can measure global DNA methylation using only 100 ng of genomic DNA per reaction. In addition, we demonstrate that <italic>CpG</italic>lobal is an excellent alternative to HPCE, one of the gold standard technologies.</p>", "<p><italic>CpG</italic>lobal has been employed to study the role of global DNA methylation in lung cancer to understand further the biology of this disease. It is the world's most common fatal cancer with an overall survival rate of 15% over 5 years [##REF##12502432##18##]. This dismal outcome can be attributed to the natural history of the disease where in its early stages it is asymptomatic and in the latter stages patients present with non-specific symptoms [##REF##17088104##19##]. In order to gain further insight into the natural history of this disease we measured global DNA methylation in a set of lung cancer cell lines that represented all the stages of this disorder as well as in 20 paired normal/tumor from patients diagnosed with Non-small cell lung cancer (NSCLC). The resultant data showed that there was an increase in hypomethylation observed with tumor progression as well as in the normal part of the lung from cancer patients.</p>" ]

[ "<title>Methods</title>", "<title>Measurement of Global DNA Methylation</title>", "<p>To quantitate the amount of DNA methylation in any genome 100 ng of a sample was aliquoted nine times into a 96 well white Microfluor 2 plate (Thermo Electron, Waltham, MA). The genomic DNA in the first three wells was digested with 5 units of a methyl-sensitive restriction enzyme such as HpaII (New England BioLabs, Beverly, MA), the DNA in the second three wells was digested with 5 units of the methyl-insensitive restriction enzyme MspI (New England BioLabs, Beverly, MA) to normalize the data when calculating the Global DNA Methylation Index (GDMI), and the third set of triplicates was for buffer only (NEBuffer1 – New England BioLabs, Beverly, MA). All reactions were performed in a total volume of 30 μl. Prior to incubation the 96 well microtiter plate was sealed with Adhesive PCR Foil (ABgene Inc., Rochester, NY) using an ALPS 300™ (ABgene Inc., Rochester, NY), spun briefly and placed in an air incubator for 3 hours at 37°C. After incubation, the plate was spun briefly and the Adhesive PCR Foil removed. The digestion of DNA was followed by an end-fill reaction where 20 μl of biotinylation buffer containing Biotin-11-dCTP and Biotin-11-dGTP (Perkin Elmer, Boston, MA) and Sequenase (USB Corporation, Clevland, OH) in 40 mM Tris-HCl, pH 7.5, 20 mM Tris-HCl, 50 mM NaCl) was added. The final concentration of biotinylated dCTP and dGTP and Sequenase used per well was 0.1 μM and 0.1 units respectively. The plate was sealed, spun briefly and placed into an air incubator for 30 minutes at 37°C. After the incubation period the plate was spun briefly, the Adhesive PCR Foil removed and 100 μl of Reacti-Bind™ DNA Coating Solution (Pierce, Rockford, IL) was added to each well. After mixing, the plate was once again sealed and placed on an orbital platform shaker (Lab-Line Instruments Inc., Melrose Park, IL) and shaken at 150 RPM at room temperature overnight. The solution in the wells was removed and the wells were washed 4 times with TBS (10 mM Tris-HCL pH 8.0, 150 mM NaCl). The biotin was detected using HRP Neutravidin (Pierce, Rockford, IL) and the DNA Detector kit (KPL, Gaithersburg, MD). Briefly, 200 μl of the Detector Block Solution (KPL, Gaithersburg, MD) was added to each well and the plate was incubated for 30 minutes at room temperature. After removal of the Detector Block Solution, 150 μl of Detector Block Solution containing 0.5 μg/ml (1:2000 dilution) of HRP Neutravidin was added to each well and the plate was incubated at room temperature for 30 minutes. The Detector Block/HRP Neutravidin solution was removed and the wells washed 5 times with 1xBiotin wash solution (KPL, Gaithersburg, MD). After the final wash 150 μl of LumiGlo^®chemiluminescence substrate (KPL, Gaithersburg, MD) was added to each well. After 2 minutes the luminescence emitted from each well was quantitated by a Wallac Envision 2100 multilabel reader (Perkin Elmer, Boston, MA).</p>", "<title>Generation of fully methylated lambda DNA</title>", "<p>To determine the analytical sensitivity of <italic>CpG</italic>lobal the entire genome of Lambda DNA was methylated using M.SssI (New England BioLabs, Beverly, MA), a bacterial CpG methylase, which methylated all the cytosine residues that resided within a CpG dyad. Fifty micrograms of lambda genomic DNA was methylated with M.SssI for 4 hours at 37°C. The salt and enzyme were removed from the methylated lambda DNA using QIAEX II (Qiagen, Valencia, CA). To determine whether the lambda DNA was fully methylated 1 μg of the product was aliquoted and digested with MspI (methyl insensitive restriction enzyme) and another microgram with HpaII (a methyl sensitive restriction enzyme). The digested products were analyzed by gel electrophoresis. No fragments were observed in the HpaII digested lane. The expected size bands were measured in the MspI digested lane.</p>", "<title>Linearity of CpGlobal using lambda DNA</title>", "<p>To determine the efficiency of digestion and end-fill reactions for an amount of lambda genomic DNA, we used the methyl-insensitive restriction enzyme MspI (CCGG) for which there were 328 restriction sites in the genome. The genomic DNA was aliquoted six times into a 96 well microtiter Microfluor 2 White plate. One set of triplicates were digested with MspI (New England BioLabs, Beverely, MA), the second set was treated with buffer only (NEBuffer2 – New England Biolabs, Beverely, MA). A range of DNA concentrations (25 ng, 12.5 ng, 6.25 ng, 3.12 ng) were assayed to determine the linearity of <italic>CpG</italic>lobal. The assay and the quantitation of the chemiluminescence were performed as described above. The net luminescence per DNA concentration was plotted and 25 ng of lambda DNA was determined to provide the appropriate signal to noise level for the next set of experiments.</p>", "<title>Accuracy of CpGlobal using lambda DNA</title>", "<p>To ascertain the accuracy of <italic>CpG</italic>lobal and determine the best methyl-sensitive restriction enzyme that could be applied to this assay, a series of mixtures with increasing ratios of unmethylated to methylated Lambda DNA was generated. The series of mixtures increased by 5% such that the range of methylated to unmethylated produced a broad spectrum of DNA methylation densities that varied from 100% to 0% methylated. Once the mixtures were generated, 25 ng of each DNA mix was aliquoted nine times into a 96 well microtiter Microfluor 2 White plate. To quantitate the amount of methylated Lambda DNA in each mixture the first three aliquots were digested with 5 units of a methyl-sensitive restriction enzyme (AciI, BstUI HpaII, HinP1I, HypCH4IV) (New England BioLabs, Beverely, MA), the second three aliquots were digested with 5 units of the methyl-insensitive restriction enzyme MspI (New England BioLabs, Beverely, MA) and the third three aliquots were mixed with buffer only. The following NEB buffers (New England Biolabs, Beverely, MA) were used for different enzymes: NEBuffer1 (HpaII, MspI, HpyCH4IV), NEBuffer2 (BstUI and HinP1I) and NEBuffer3 (AciI). The assay and the quantitation of the chemiluminescence were performed as described above except for BstUI. This enzyme is a blunt end cutter and instead of using Sequenase during the end-fill reaction 0.1 units Klenow (New England BioLabs, Beverely, MA) was used in its stead. Here, the 3'-5'exonuclease activity of the Klenow was utilized to chew back into the blunt end-fragment and then the 5'-3'exonuclease activity would incorporate the biotinylated nucleotides.</p>", "<title>Quantitative Range of CpGlobal using human genomic DNA</title>", "<p>The linear range of the <italic>CpG</italic>lobal assay for human genomic DNA was determined by measuring global DNA methylation in human male genomic DNA isolated from whole blood (Novagen, San Diego, CA). A range of DNA concentrations (100 ng, 50 ng, 25 ng, 12.5 ng, 6.25 ng and 3.125 ng) were assayed to determine the linearity of <italic>CpG</italic>lobal. One set of triplicates were digested with HpaII (New England BioLabs, Beverely, MA), the second set with MspI (New England BioLabs, Beverely, MA) and the third set was treated with buffer only (NEBuffer1 – New England Biolabs, Beverely, MA). The assay and the quantitation of the chemiluminescence were performed as described above.</p>", "<title>Cell Culture and DNA Isolation</title>", "<p>All cell lines were purchased from ATCC (Manassas, VA) and were grown according to the manufacturer's recommendations. The cell lines that were used to compare the <italic>CpG</italic>lobal with High Performance Capillary Electrophoresis (HPCE) were SW48 (CCL-231), LoVo (CCL-229), HT-29 (HTB-38) and NCI-H69 (HTB-119D). Assessment of the global DNA methylation was performed on Non-Small Cell Lung Cancer tumor cell lines from various stages of lung cancer. These included a normal lung NL20 (CRL-2503), Stage I NCI-H1703 (CRL-5889), Stage II NCI-H522 (CRL-5810), Stage IIIa NCI-H1993 (CRL-5909), Stage IIIb NCI-H1944 (CRL5907) and Stage IV metastatic liver NCI-H1755 (CRL-5892). All cells were grown in 75 cm²cell culture flasks (Corning Incorporated, Corning, NY) in 5% CO₂at 37°C. Cells were harvested when they had reached 90% confluency. DNA was isolated using the Blood and Cell Culture DNA Midi Kit (Qiagen, Valencia, CA). The purity and concentration of the DNA was measured using a DU650 spectrophotometer (Beckman Coulter, Fullerton, CA). The quality of the DNA was determined by loading 200 ng on a 1% agarose gel to inspect for any degradation.</p>", "<title>Lung Tissue samples</title>", "<p>Twenty fresh frozen tissues samples, including lung tumors and areas of non involved lung, were obtained from a repository of biological specimens through the lung cancer Specialized Program of Research Excellence (SPORE) at the Vanderbilt Ingram Cancer Center. For each specimen, a quality control of the tissue specimen was obtained from hematoxylin and eosin stained tissue section on adjacent tissue and reviewed by a pathologist prior to analysis. De-identified clinical data elements were shared in compliance of the health insurance portability and accountability regulations. This study was approved by the local Institutional Review Board of both institutions.</p>", "<title>Normal lung DNA</title>", "<p>Normal lung DNA from young male accident victims was purchased from BioChain Institute, Inc., Hayward, CA.</p>", "<title>DNA isolation</title>", "<p>Approximately 0.1 gm lung tissue from biopsies of paired tumor and normal tissue from NSCLC patients was frozen in liquid nitrogen. The tissue was pulverized to a fine powder using a freezer mill 6750 (SPEX SamplePrep, Metuchen, NJ) according to the manufacturer's recommendations. DNA was prepared using the Blood and Cell Culture DNA midi kit (Qiagen, Chatsworth, CA). The DNA was checked for concentration and purity by reading the absorbance at 260 and 280 nM and was further tested for intactness by running 100 ng on a 1% agarose gel.</p>", "<title>Linear Regression Analysis</title>", "<p>Linear regression analyss was performed using EXCEL Analysis ToolPak Regression Analysis. In each case presented single predictor variable was used. R square, Adjusted R square, intercept, coefficient, standard error and F significance were generated by standard Summary Report. Residual Plots and LineFit Plots were used to check for the linearity of the regression.</p>", "<title>Calculation of Global DNA Methylation Index (GDMI)</title>", "<p>To determine the net luminescence, the average value for the no enzyme control was subtracted from the individual enzyme values. To calculate the global DNA methylation index (GDMI), the individual net luminescence values for the methylation sensitive enzyme were divided by the average Msp I net luminescence. All calculations were performed in Microsoft Excel.</p>", "<title>Statistical Analysis</title>", "<p>Both means and medians were calculated when comparing group differences among Normal Non-Disease, Normal Disease and Tumor samples. Only medians were used when the distributions of continuous variables were significantly skewed by small sample sizes such as different histopathological groups. Due to the potential compromise of parametric assumption, non-parametric Wilcoxon/Kruskal-Wallis tests were applied to evaluate the statistical significances for all analysis. P-value &lt;= 0.05 was considered as statistically significant and p-value &gt; 0.05 and &lt;= 0.10 was regarded as border-line significant. All analyses were conducted using JMP5.1 (SAS Institute, Inc., Cary, NC).</p>" ]

[ "<title>Results</title>", "<title>Design of CpGlobal</title>", "<p><italic>CpG</italic>lobal was designed to incorporate several key features: easy to use, did not require radioactivity or PCR, functioned in a 96-well microtiter plate and utilized equipment that most laboratories possessed. The design was adapted from a method that utilizes methyl-sensitive restriction enzymes [##REF##10471374##14##], which when applied to genomic DNA would produce a set of digested fragments that could be quantitated and translated into an amount of DNA methylation present in the genome. We have modified the approach by performing all the steps in one 96 well microtiter plate. Therefore, once the genomic DNA from a sample was aliquoted into the well of the microtiter plate it remained in that location through the four stages of treatment: digestion, end-fill with biotinylated nucleotides, attachment to the surface of the well and chemiluminescence. The methyl-insensitive restriction enzyme MspI, the isoschizomer of HpaII, was used in the design to normalize the data collected from the methyl-sensitive restriction enzymes. This step aided in the removal of any intrinsic variations introduced through slight differences in DNA concentrations, and digestion and end-fill reactions. As such a global DNA methylation index (GDMI) was calculated. The arrangement of the DNA in the 96 well microtiter plate was designed so that up to 10 samples per plate could be analyzed (Figure ##FIG##0##1##). The final step in the assay was the measurement of luminescence through the use of a luminometer. The end-product was an assay designed for an operator to easily manage the measurement of global DNA methylation in multiple samples, without the need for radioactivity, PCR and expensive equipment.</p>", "<title>Accuracy of CpGlobal</title>", "<p>Based on the design of the assay we began with the application of <italic>CpG</italic>lobal on Lambda DNA with the aim to determine which methyl-sensitive restriction enzyme was the best indicator in measuring global DNA methylation. Two species of lambda DNA were created: one that was unmethylated and the other that was <italic>in vitro </italic>methylated using M.SssI, a CpG methylase. Five 4 base pair methyl-sensitive restriction enzymes, AciI (CCGC), BstUI (CGCG), HpaII (CCGG), HinP1I (GCGC) and HypCH4IV (ACGT), were chosen based on their frequency within the Lambda genome and the core recognition sequence site. These enzymes were used to digest a series of Lambda DNA mixtures, which consisted of 21 points that extended from 100% to 0% methylated in 5% intervals. GDMI was generated for each 5% increment, which was compared against the theoretical methylation level. A linear regression analysis was performed for each methyl-sensitive restriction enzyme (Table ##TAB##0##1##). We observed a highly significant correlation of GDMI with the theoretical methylation levels using HinP1I, HpaII and HypCH4IV. Thus, under these conditions the use of any one of these three methyl-sensitive restriction enzymes would be an effective indicator for global DNA methylation.</p>", "<title>Application of CpGlobal in human genomic DNA</title>", "<p>In order to quantitate global DNA methylation in the human genome it was essential that the assay operates within the linear range. In particular, it was important to determine if the performance of a methyl-sensitive and the methyl-insensitive restriction enzyme was linear with DNA concentration as the net luminescence generated from the assay would be used to calculate the GDMI. Subsequently, <italic>CpG</italic>lobal was applied to human genomic DNA isolated from whole blood. Using a two-fold serial dilution that ranged from 100 ng to 3.125 ng, the DNA for each concentration was digested in triplicate with HpaII, MspI and treated with buffer only. The net luminescence from each experiment was plotted against DNA concentration (Figure ##FIG##1##2a##). The results demonstrated a linear regression that correlated highly with DNA concentration and net luminescence (R²HpaII = 0.982, R²MspI = 0.999). The GDMI was calculated for human whole blood DNA and was plotted against DNA concentration. The GDMI was moderately consistent with DNA concentration (Figure ##FIG##1##2b##). We chose to use 100 ng of human genomic DNA in all the following experiments because the signal to background ratio was at least &gt; 10 fold.</p>", "<title>Comparison of CpGlobal with High-performance capillary elecrophoresis (HPCE)</title>", "<p>HPCE is viewed as one of the gold standard technologies when measuring the global genomic content of 5-methylcytosine [##REF##12179987##8##]. We applied <italic>CpG</italic>lobal to calculate the GDMI from a selection of cancer cell lines to determine whether a strong correlation existed between these two technologies. We measured the global DNA methylation in four cancer cell lines (SW48, LoVo, HT-29 and H69), which varied in methyl content from high to low as determined by HPCE. HpaII and MspI were utilized on 100 ng of cell line genomic DNA to calculate the GDMI. The HPCE results, extracted from the publication by Paz et al [##REF##12615730##20##] were compared with the calculated GDMIs from the four cell lines. The <italic>CpG</italic>lobal results presented with a good linear fit when compared to the HPCE data. In addition, we observed that the number of unmethylated HpaII sites had an inverse linear relationship with the total number of methylated cytosines (data not shown).</p>", "<p>The linear fit for this correlation was calculated:</p>", "<p>HPCE = -6.2 × GDMI + 7.18</p>", "<p>Adjusted R²= 0.77</p>", "<p>Residual error = 0.36.</p>", "<p>Considering that the HPCE data were taken from a publication to create the correlation, these results demonstrated that <italic>CpG</italic>lobal could be utilized as an alternative technique to one of the gold standard technologies.</p>", "<title>Application of CpGlobal to lung cancer lines</title>", "<p>We directed the assay toward measuring the association of global DNA methylation with the natural history of lung cancer. Lung cancer is measured in 5 stages, which range from 0 to IV [##REF##15013719##21##]. We measured the GDMI, using the HpaII methyl-sensitive restriction enzyme, in epithelial cell lines that represented the full extent of the disease: Normal lung, Stage I, Stage II, Stage IIIa, Stage IIIb and Stage IV metastatic liver. The results indicated that there was an increase in global DNA hypomethylation that was associated with the progressive development of the tumor (Figure ##FIG##2##3##). The greatest loss of methylation was observed in the Stage IIIb cell line and the least was measured in the Stage I. Compared with the normal epithelial cell line, this represented a loss of 5-methylcytosines that ranged from 10%, in an early stage tumor, to 50% in a late stage cancer. These data demonstrated the quantitative capacity of <italic>CpG</italic>lobal to measure changes in global DNA methylation in a cancer as it progresses from early to late stage and metastasis.</p>", "<title>Global DNA methylation levels in normal tissue and lung cancer</title>", "<p>We measured the GDMI using <italic>CpG</italic>lobal in lung DNA from 20 patients diagnosed with Non Small Cell Lung Cancer (NSCLC) (Table ##TAB##1##2##) and 12 normal individuals to ascertain whether global DNA hypomethylation is a prominent phenomenon in this disease. DNA from three types of lung tissues was analyzed: Normal Non-Disease from normal individuals, Normal Disease (pathological and histological defined normal) paired with Tumor from each cancer patient. The GDMI was measured in the lung DNAs using the methyl-sensitive restriction enzymes HinP1I, HpaII and HypCH4IV. A general trend was observed when the median GDMI was calculated for all three methyl-sensitive enzymes (Table ##TAB##2##3a##); an increase in the median GDMI was measured with lowest levels detected in the Normal Non-Diseased and the highest in the Tumors (median GDMI – Normal Non-Disease &lt; Normal Disease &lt; Tumor). Nonparametric Wilcoxon/Kruskal-Wallis test was performed on the median GDMI data to determine whether the observed trend was statistically significant (Table ##TAB##2##3b##). The greatest difference in GDMI was between the Normal Non-Disease and Tumor (p &lt; 0.054–0.004), which was observed in all three methyl-sensitive enzymes. However, only HinP1I and HpaII were able to detect a GDMI difference between the paired Normal Disease and Tumor (p = 0.064 and p = 0.068 respectively). Out of the three methyl-sensitive enzymes only HpaII was observed to distinguish between the Normal Non-Disease and Normal Disease with statistical significance (p = 0.039). These results suggested that the histological and pathological defined normal part of the lung from a cancer patient had altered global DNA methylation levels.</p>", "<title>Distinguishing Properties of CpGlobal in Lung Cancer</title>", "<p>To investigate further the changes in global DNA methylation in lung cancer we separated the major histopathologic characteristics assigned to the cancer patient samples into three groups (Stage – 1A and 1B, grade of differentiation – well and non-well and tumor size – T1 and T2) and searched for any association of the GDMI with these characteristics in the Normal Disease and Tumor samples. Nonparametric Wilcoxon/Kruskal-Wallis test was performed using the median GDMI data, which was measured in the Normal Disease and Tumor samples. No statistically significant changes were observed in global DNA methylation from the Normal Disease tissue samples for any methyl-sensitive restriction enzyme when compared against the three groups. However, the median GDMI from the Tumor tissue samples was significantly associated with all three histopathologic characteristics. In particular this was observed for HinP1I (Stage 1A versus 1B), HypCH4IV and HpaII (well versus non-well differentiated) and HinP1I and HpaII (T1 versus T2) (Table ##TAB##3##4##). When the analysis was performed using the ratio of median GDMI Tumor/median GDMI Normal Disease the statistical significance was improved for some methyl-sensitive restriction enzymes and made worse for others when compared against the three histopathologic characteristics (Table ##TAB##3##4##). These analyses indicated that global DNA hypomethylation remained a persistent observation in lung tissue from patients diagnosed with NSCLC. Furthermore, <italic>CpG</italic>lobal could clearly distinguish a difference in the Tumor samples between Stage 1A and 1B, tumor size T1 and T2, and well differentiated and non-well differentiated tissue.</p>" ]

[ "<title>Discussion</title>", "<p>To actively study the role of global DNA methylation in the context of disease requires complex and expensive equipment and skill sets that compliment the technology. We have designed and developed a technique, <italic>CpG</italic>lobal, which is easy-to-use, cost-effective and used skill sets and equipment that were present in most molecular biology laboratories. The assay did not require radioactivity or involve PCR. We found that <italic>CpG</italic>lobal correlated significantly with HPCE, which was one of the gold standard technologies used to measure global DNA methylation. Considering that the HPCE global DNA methylation data was retrieved from a publication [##REF##12615730##20##], where the cell culture conditions may not have been similar to our standards, these results exemplified the quality of <italic>CpG</italic>lobal to measure the methyl content of a genome.</p>", "<p>The use of certain methyl-sensitive restriction enzymes in this assay provided <italic>CpG</italic>lobal with a level of accuracy and reproducibility in the measurement of global DNA methylation. The methyl-sensitive enzymes that worked consistently were HpaII and HinP1I. While the performance of HypCH4IV was not as effective in our assay as the other two methyl-sensitive restriction enzymes, the recognition sequence ACGT made it unique compared to HpaII and HinP1I, which were CpG rich sites. Therefore, such a mixture of methyl sensitive restriction sites allowed a greater assessment of the genome's global methyl content.</p>", "<p>The application of <italic>CpG</italic>lobal in a 96 well microtiter plate enabled multiple samples to be analyzed at once. We routinely assayed each sample in triplicate. As such 10 samples were measured at a time. Yet, by performing the assay in duplicate up to 16 samples could be incorporated into the 96 well microtiter format. In addition, we have extended the use of the assay to function in a 384 well microtiter plate, which shared the same characteristics as the 96 well format (data not shown). Here, up to 64 samples could be analyzed at once. However, the application of robotics to dispense the liquids would be more practical in this format. While the data presented in this paper were obtained from the assay where 100 ng of genomic DNA per well was used, the results showed that using as little as 3 ng could be utilized. However, we have observed that the signal to background ratio diminishes as less DNA is used (data not shown).</p>", "<p>The ability to access high quality tissue to perform these experiments was one of the limiting factors. While the tissue that was obtained from patients with lung cancer was highly defined and scored by experts that are knowledgeable in the histology and pathology of lung cancer, the normal tissue was obtained from car crash victims. To acquire detailed information regarding normal tissue is often difficult and limited. The variability in the tissue from accident victims can cause irreproducibility in global DNA methylation data. This may be reflected in the time and cause of death. In addition, it may explain why the median GDMI data from the Normal Non-Disease tissue were slightly higher than expected. The importance of collecting high quality tissue from normal individuals outside of blood is an on-going issue. A well-defined normal tissue bank, where sex and age matched samples could be obtained, which could go hand-in-hand with patient material, would be invaluable for diagnostic studies that seek the ability to use tissue beyond blood. An additional factor, which may have influenced the data, could be the purity of the tumor from the matched patient material. While the tumor was matched with normal it was not micro-dissected and so heterogeneity could have been an issue. Nevertheless, while the median GDMI for the tumor tissue was greater that the matched Normal Disease it was not as high as expected and this may have been attributed to heterogeneity. Given the difficulties faced in this study in acquiring truly well defined tissue, the data still remained convincing and strongly suggested <italic>CpG</italic>lobal was able to clearly discern differences in global DNA methylation from Normal Non-Disease and Normal Disease clinical samples.</p>", "<p>The application of <italic>CpG</italic>lobal in a disease environment provided an opportunity to ascertain the value of the technology as a research tool. In particular, how global DNA hypomethylation contributed to the instability of the genome and in the transformation of a cell from normal to disease. Genome-wide loss in methylation has been observed as one of the earliest known molecular abnormalities in human neoplasias [##REF##15489135##3##]. This would suggest that a better understanding of this biological phenomenon may provide an insight into the evolution of cancer [##REF##14732866##4##]. In that regard, we have applied <italic>CpG</italic>lobal to lung cancer to delve deeper into understanding the natural history of this disease. Through the use of samples from patients diagnosed with NSCLC, two major observations from these studies were construed. The first, demonstrated that there was a statistically significant loss of global DNA methylation as the tumor progressed from Stage 1A to 1B (p = 0.08–0.006). At this early stage in the disease the only other characteristics for a pathologist to stage the lung cancer is size and grade of differentiation of the tumor. Both of these were associated with global DNA hypomethylation (p = 0.04 and p = 0.04 – 0.01 respectively). The second suggested that the histological and pathological defined normal part of the lung had incurred a loss in global DNA methylation that was statistically significant when compared with normal individuals (p = 0.039). Considering the small sample size in this study, and that by histopathologic standards the non tumor lung tissue from the cancer patients were graded as normal, global DNA hypomethylation appears to be a measurable change. Also, several studies have observed global DNA hypomethylation in other normal disease tissues such as colon, breast and ovary [##REF##15539937##22##, ####REF##15231656##23##, ##REF##14534800##24####14534800##24##]. In addition, this phenomenon was determined to be a whole tissue circumstance rather than a cell-by-cell event [##REF##14534800##24##, ####REF##8039116##25##, ##REF##11358850##26####11358850##26##]. It is plausible to speculate that a tissue-wide loss in global DNA methylation suggests that the entire lung is in a pre-neoplasia state. Continued global DNA hypomethylation could be one of the key factors in driving the cells to become malignant. However, how much global DNA hypomethylation is required before malignant transformation occurs would require a longitudinal prospective study to be performed.</p>", "<p>Exploiting these global DNA methylation changes may be of value in screening asymptomatic individuals who are at risk in developing lung cancer. An initial practical application would be to measure the global DNA methylation levels of a large sample set that contained prospective patient material. One type of sample set that could be used is from a prospective nested case control study such as the one that was utilized to measure the methylation status of the promoters from 14 genes in proximal sputum samples. Here, methyl sensitive PCR (MSP) was the technique applied to these samples. The results showed that this technique could detect changes 18 months prior to diagnosis with a 64% sensitivity and specificity [##REF##16540689##27##]. Application of <italic>CpG</italic>lobal to this type of material may improve the result through combining the results of both global DNA methylation and region specific analysis using MSP. Furthermore, it may provide information as to the association of global DNA methylation and the natural history of the disease before the presence of any clinical symptoms.</p>" ]

[ "<title>Conclusion</title>", "<p><italic>CpG</italic>lobal is an easy-to-use technique to study the biological role of global DNA methylation in the cell. The technique can be used in almost any practical laboratory without the need for expensive equipment or highly specialized skill sets. In addition, <italic>CpG</italic>lobal can be utilized as a research tool to investigate the epigenetic phenomenon in disease, aging, diet, efficacy of drugs and in any other vertebrate or invertebrate genome where methylation is employed. The application of <italic>CpG</italic>lobal to measure the changes in global DNA methylation in lung cancer has demonstrated that there exists a distinguishing difference between Normal Non-Disease and Normal Disease tissue. Such a change should be examined further and exploited to understand the functional role of this epigenetic phenomenon with the potential aim of providing a diagnostic for asymptomatic individuals who are at risk of developing lung cancer.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Genome-wide changes in DNA methylation are an epigenetic phenomenon that can lead to the development of disease. The study of global DNA methylation utilizes technology that requires both expensive equipment and highly specialized skill sets.</p>", "<title>Methods</title>", "<p>We have designed and developed an assay, <italic>CpG</italic>lobal, which is easy-to-use, does not utilize PCR, radioactivity and expensive equipment. <italic>CpG</italic>lobal utilizes methyl-sensitive restriction enzymes, HRP Neutravidin to detect the biotinylated nucleotides incorporated in an end-fill reaction and a luminometer to measure the chemiluminescence. The assay shows high accuracy and reproducibility in measuring global DNA methylation. Furthermore, <italic>CpG</italic>lobal correlates significantly with High Performance Capillary Electrophoresis (HPCE), a gold standard technology. We have applied the technology to understand the role of global DNA methylation in the natural history of lung cancer. World-wide, it is the leading cause of death attributed to any cancer. The survival rate is 15% over 5 years due to the lack of any clinical symptoms until the disease has progressed to a stage where cure is limited.</p>", "<title>Results</title>", "<p>Through the use of cell lines and paired normal/tumor samples from patients with non-small cell lung cancer (NSCLC) we show that global DNA hypomethylation is highly associated with the progression of the tumor. In addition, the results provide the first indication that the normal part of the lung from a cancer patient has already experienced a loss of methylation compared to a normal individual.</p>", "<title>Conclusion</title>", "<p>By detecting these changes in global DNA methylation, <italic>CpG</italic>lobal may have a role as a barometer for the onset and development of lung cancer.</p>" ]

[ "<title>Abbreviations</title>", "<p>GDMI: global DNA methylation index; HPCE: high performance capillary electrophoresis; NSCLC: Non small cell lung cancer.</p>", "<title>Competing interests</title>", "<p>The authors AA, HH, HW, SM and RGDM are co-inventors on a patent entitled \"Diagnosing Diseases by Detecting DNA Methylation Changes\" (United States Patent Application 20070292866). RGDM was a full time employee of AmberGen from 2005 to 2007 and is now a full time employee of Invitrogen Corporation. RGDM holds no stock or shares in AmberGen Incorporated but holds shares in Invitrogen Corporation. The article-processing charge was paid for by AmberGen Incorporated. There are no other financial or non-financial competing interests to declare that pertain to this manuscript.</p>", "<title>Authors' contributions</title>", "<p>AA, KIB and HG designed and performed the initial experiments with <italic>CpG</italic>lobal. ZL and SM isolated the DNA from the lung cancer cell lines and from the normal and tumor patient lung samples. AA performed all the experiments using <italic>CpG</italic>lobal to measure the global DNA methylation in the cell lines and patient lung samples. HH and HW performed the statistical analysis. JO was responsible for providing interpretation of the chemistry behind <italic>CpG</italic>lobal. HH and RGDM were responsible for the overall conception of <italic>CpG</italic>lobal. HH, PPM and RGDM were responsible the conception of the study and contributed to the preparation of this manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2407/8/222/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors dedicate this publication to Dr. Paul B. Wolfe, Program Director for the National Institute of General Medical Sciences, for his support, encouragement and enthusiasm toward the research presented in this paper.</p>", "<p>All the authors and the research described in this paper were fully supported by a grant from the National Institute of General Medical Sciences (R44 GM069291)</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Schematic showing design of <italic>CpG</italic>lobal.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Assessment of <italic>CpG</italic>lobal using human genomic DNA isolated from whole blood</bold>. A) Linearity of CpGlobal for different amounts of lymphocyte DNA. Twofold serial dilutions of genomic DNA from 100 ng down to 3.12 ng digested with HpaII or MspI. Net Luminescence of the no enzyme control is subtracted from the net luminescence of HpaII and MspI and plotted versus concentration of DNA. The points fit with a linear regression (HpaII R²= 0.982 and Msp I R²= 0.999). B) Net HpaII luminescence was divided by net MspI luminescence to get global DNA methylation index (GDMI) and plotted versus DNA concentration.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Measurement of global DNA methylation in a set of lung cancer cell lines that represents the various stages of the disease</bold>. 100 ng genomic DNA was digested with HpaII and MspI and the GDMI calculated: Lane 1, NL20 (normal lung); lane 2, NCI-H1703 (Stage 1 NSCLC); lane 3, NCI-H522 (Stage 2 NSCLC); lane 4, NCI-H1993 (stage 3A NSCLC); lane 5, NCI-H1944 (Stage 3B NSCLC); lane 6, NCI-H1755 (Stage 4 NSCLC).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Linear regression analysis to determine which methyl-sensitive restriction enzymes were effective in <italic>CpG</italic>lobal.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Enzyme</bold></td><td align=\"center\"><bold>Theoretical Regression</bold></td><td align=\"center\"><bold>Actual Regression</bold></td><td align=\"center\"><bold>Adjusted R Square</bold></td><td align=\"center\"><bold>Standard Error</bold></td><td align=\"center\"><bold>F significance</bold></td></tr></thead><tbody><tr><td align=\"center\">AciI</td><td align=\"center\">y = 1.57-1.57x</td><td align=\"center\">y = 0.45-0.46x</td><td align=\"center\">0.86</td><td align=\"center\">0.06</td><td align=\"center\">1.11E-09</td></tr><tr><td align=\"center\">BstUI</td><td align=\"center\">y = 0.48-0.48x</td><td align=\"center\">y = 0.09-0.11x</td><td align=\"center\">0.87</td><td align=\"center\">0.01</td><td align=\"center\">4.39E-10</td></tr><tr><td align=\"center\">HinP1I</td><td align=\"center\">y = 0.66-0.66x</td><td align=\"center\">y = 0.95-0.89x</td><td align=\"center\">0.97</td><td align=\"center\">0.05</td><td align=\"center\">1.24E-15</td></tr><tr><td align=\"center\">HpaII</td><td align=\"center\">y = 1.00-1.00x</td><td align=\"center\">y = 0.94-0.95x</td><td align=\"center\">0.96</td><td align=\"center\">0.06</td><td align=\"center\">4.46E-15</td></tr><tr><td align=\"center\">HpyCH4IV</td><td align=\"center\">y = 0.44-0.44x</td><td align=\"center\">y = 0.74-0.73x</td><td align=\"center\">0.97</td><td align=\"center\">0.04</td><td align=\"center\">7.67E-17</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Patient information</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td/><td/><td align=\"center\" colspan=\"4\"><bold>Pathology</bold></td><td/></tr><tr><td/><td/><td/><td/><td colspan=\"4\"><hr/></td><td/></tr><tr><td align=\"center\"><bold>Patient ID</bold></td><td align=\"center\"><bold>Age</bold></td><td align=\"center\"><bold>Race</bold></td><td align=\"center\"><bold>Gender</bold></td><td align=\"center\"><bold>Tumor</bold></td><td align=\"center\"><bold>Lymph Node</bold></td><td align=\"center\"><bold>Metastasis</bold></td><td align=\"center\"><bold>Stage</bold></td><td align=\"center\"><bold>Differentiation</bold></td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">64</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">Mx</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">2</td><td align=\"center\">59</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">3</td><td align=\"center\">85</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">4</td><td align=\"center\">62</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">Mx</td><td align=\"center\">Stage IA</td><td align=\"center\">Well Diff</td></tr><tr><td align=\"center\">5</td><td align=\"center\">62</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T1</td><td align=\"center\">N1</td><td align=\"center\">Mx</td><td align=\"center\">Stage IIB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">6</td><td align=\"center\">53</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">M1</td><td align=\"center\">Stage IA</td><td align=\"center\">N/A</td></tr><tr><td align=\"center\">7</td><td align=\"center\">68</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">Mx</td><td align=\"center\">Stage IA</td><td align=\"center\">Well Diff</td></tr><tr><td align=\"center\">8</td><td align=\"center\">60</td><td align=\"center\">Black</td><td align=\"center\">Female</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">9</td><td align=\"center\">54</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">Mx</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">10</td><td align=\"center\">77</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">11</td><td align=\"center\">71</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T1</td><td align=\"center\">N2</td><td align=\"center\">M1</td><td align=\"center\">Stage IIIA</td><td align=\"center\">Well Diff</td></tr><tr><td align=\"center\">12</td><td align=\"center\">47</td><td align=\"center\">Black</td><td align=\"center\">Female</td><td align=\"center\">T3</td><td align=\"center\">N/A</td><td align=\"center\">N/A</td><td align=\"center\">Stage IIIA</td><td align=\"center\">N/A</td></tr><tr><td align=\"center\">13</td><td align=\"center\">57</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T4</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">14</td><td align=\"center\">65</td><td align=\"center\">White</td><td align=\"center\">Female</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">15</td><td align=\"center\">77</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">16</td><td align=\"center\">82</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T1</td><td align=\"center\">N0</td><td align=\"center\">Mx</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">17</td><td align=\"center\">85</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">Mx</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">18</td><td align=\"center\">52</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">19</td><td align=\"center\">63</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IA</td><td align=\"center\">Non-well Diff</td></tr><tr><td align=\"center\">20</td><td align=\"center\">56</td><td align=\"center\">White</td><td align=\"center\">Male</td><td align=\"center\">T2</td><td align=\"center\">N0</td><td align=\"center\">M0</td><td align=\"center\">Stage IB</td><td align=\"center\">Non-well Diff</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Median GDMI of normal non-disease, normal disease and the paired tumors for different methyl-sensitive restriction enzymes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>A</bold></td><td/><td/><td/></tr></thead><tbody><tr><td align=\"left\" colspan=\"4\"><bold>Median GDMI of normal non-disease, normal disease and the paired tumors for different methyl-sensitive restriction enzymes.</bold></td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold>Sample Type</bold></td><td align=\"left\"><bold>HinP1 I</bold></td><td align=\"left\"><bold>HpyCH4 IV</bold></td><td align=\"left\"><bold>Hpa II</bold></td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">Normal Non-Disease</td><td align=\"left\">0.163</td><td align=\"left\">0.304</td><td align=\"left\">0.293</td></tr><tr><td align=\"left\">Normal Disease</td><td align=\"left\">0.197</td><td align=\"left\">0.368</td><td align=\"left\">0.321</td></tr><tr><td align=\"left\">Tumor</td><td align=\"left\">0.216</td><td align=\"left\">0.427</td><td align=\"left\">0.379</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold>B</bold></td><td/><td/><td/></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\" colspan=\"4\"><bold>Non-parametric tests of normal disease versus paired tumor, normal non-disease versus normal disease, and normal non-disease versus tumor for each of the methyl-sensitive restriction enzymes.</bold></td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold>Comparisons</bold></td><td align=\"left\"><bold>HinP1 I</bold></td><td align=\"left\"><bold>HpyCH4 IV</bold></td><td align=\"left\"><bold>Hpa II</bold></td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">Normal Disease vs Tumor</td><td align=\"left\"><bold>0.068*</bold></td><td align=\"left\">0.201</td><td align=\"left\"><bold>0.064*</bold></td></tr><tr><td align=\"left\">Normal Non-Disease vs Normal Disease</td><td align=\"left\">0.483</td><td align=\"left\">0.129</td><td align=\"left\"><bold>0.039**</bold></td></tr><tr><td align=\"left\">Normal Non-Disease vs Tumor</td><td align=\"left\"><bold>0.005**</bold></td><td align=\"left\">0.054*</td><td align=\"left\"><bold>0.004**</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Median GDMI stratified by different histopathologic characteristics for normal disease, tumor, and their ratios.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Characteristics</bold></td><td align=\"center\"><bold>Enzymes</bold></td><td align=\"center\" colspan=\"2\"><bold>Normal Disease</bold></td><td align=\"left\"><bold>p-value</bold></td><td align=\"center\" colspan=\"2\"><bold>Tumor</bold></td><td align=\"left\"><bold>p-value</bold></td><td align=\"center\" colspan=\"2\"><bold>Tumor/Normal Disease</bold></td><td align=\"left\"><bold>p-value</bold></td></tr><tr><td colspan=\"2\"/><td colspan=\"2\"><hr/></td><td/><td colspan=\"2\"><hr/></td><td/><td colspan=\"2\"><hr/></td><td/></tr><tr><td/><td/><td align=\"center\" colspan=\"2\"><bold>(Median)</bold></td><td/><td align=\"center\" colspan=\"2\"><bold>(Median)</bold></td><td/><td align=\"center\" colspan=\"2\"><bold>(Median)</bold></td><td/></tr></thead><tbody><tr><td align=\"center\"><bold>Stage</bold></td><td/><td align=\"center\">Stage IA <break/>(n = 10)</td><td align=\"center\">Stage IB <break/>(n = 7)</td><td/><td align=\"center\">Stage IA <break/>(n = 10)</td><td align=\"center\">Stage IB <break/>(n = 7)</td><td/><td align=\"center\">Stage IA <break/>(n = 10)</td><td align=\"center\">Stage IB <break/>(n = 7)</td><td/></tr><tr><td/><td align=\"center\">HinP1I</td><td align=\"center\">0.20</td><td align=\"center\">0.15</td><td align=\"left\">0.22</td><td align=\"center\">0.18</td><td align=\"center\">0.26</td><td align=\"left\"><bold>0.005**</bold></td><td align=\"center\">0.92</td><td align=\"center\">1.74</td><td align=\"left\"><bold>0.006**</bold></td></tr><tr><td/><td align=\"center\">HypCH4IV</td><td align=\"center\">0.37</td><td align=\"center\">0.37</td><td align=\"left\">0.92</td><td align=\"center\">0.39</td><td align=\"center\">0.43</td><td align=\"left\">0.59</td><td align=\"center\">1.05</td><td align=\"center\">1.33</td><td align=\"left\"><bold>0.08*</bold></td></tr><tr><td/><td align=\"center\">HpaII</td><td align=\"center\">0.31</td><td align=\"center\">0.32</td><td align=\"left\">0.49</td><td align=\"center\">0.35</td><td align=\"center\">0.44</td><td align=\"left\">0.13</td><td align=\"center\">1.20</td><td align=\"center\">1.32</td><td align=\"left\">0.19</td></tr><tr><td colspan=\"11\"><hr/></td></tr><tr><td align=\"center\"><bold>Grade of Differentiation</bold></td><td/><td align=\"center\">Well Diff <break/>(n = 3)</td><td align=\"center\">Nonwell Diff <break/>(n = 15)</td><td/><td align=\"center\">Well Diff <break/>(n = 3)</td><td align=\"center\">Nonwell Diff <break/>(n = 15)</td><td/><td align=\"center\">Well Diff <break/>(n = 3)</td><td align=\"center\">Nonwell Diff <break/>(n = 15)</td><td/></tr><tr><td/><td align=\"center\">HinP1I</td><td align=\"center\">0.20</td><td align=\"center\">0.20</td><td align=\"left\">0.31</td><td align=\"center\">0.19</td><td align=\"center\">0.25</td><td align=\"left\">0.17</td><td align=\"center\">1.11</td><td align=\"center\">1.21</td><td align=\"left\">0.86</td></tr><tr><td/><td align=\"center\">HypCH4IV</td><td align=\"center\">0.37</td><td align=\"center\">0.37</td><td align=\"left\">0.77</td><td align=\"center\">0.29</td><td align=\"center\">0.44</td><td align=\"left\"><bold>0.10*</bold></td><td align=\"center\">0.79</td><td align=\"center\">1.14</td><td align=\"left\"><bold>0.04**</bold></td></tr><tr><td/><td align=\"center\">HpaII</td><td align=\"center\">0.31</td><td align=\"center\">0.32</td><td align=\"left\">0.68</td><td align=\"center\">0.28</td><td align=\"center\">0.41</td><td align=\"left\"><bold>0.01**</bold></td><td align=\"center\">0.82</td><td align=\"center\">1.33</td><td align=\"left\"><bold>0.01**</bold></td></tr><tr><td colspan=\"11\"><hr/></td></tr><tr><td align=\"center\"><bold>Tumor Size</bold></td><td/><td align=\"center\">T1<break/>(n = 10)</td><td align=\"center\">T2<break/>(n = 8)</td><td/><td align=\"center\">T1<break/>(n = 10)</td><td align=\"center\">T2<break/>(n = 8)</td><td/><td align=\"center\">T1<break/>(n = 10)</td><td align=\"center\">T2<break/>(n = 8)</td><td/></tr><tr><td/><td align=\"center\">HinP1I</td><td align=\"center\">0.20</td><td align=\"center\">0.16</td><td align=\"left\">0.66</td><td align=\"center\">0.18</td><td align=\"center\">0.25</td><td align=\"left\"><bold>0.04**</bold></td><td align=\"center\">0.99</td><td align=\"center\">1.47</td><td align=\"left\"><bold>0.04**</bold></td></tr><tr><td/><td align=\"center\">HypCH4IV</td><td align=\"center\">0.37</td><td align=\"center\">0.35</td><td align=\"left\">0.59</td><td align=\"center\">0.39</td><td align=\"center\">0.42</td><td align=\"left\">0.70</td><td align=\"center\">1.01</td><td align=\"center\">1.15</td><td align=\"left\">0.12</td></tr><tr><td/><td align=\"center\">HpaII</td><td align=\"center\">0.32</td><td align=\"center\">0.32</td><td align=\"left\">0.62</td><td align=\"center\">0.32</td><td align=\"center\">0.43</td><td align=\"left\"><bold>0.08*</bold></td><td align=\"center\">1.14</td><td align=\"center\">1.31</td><td align=\"left\">0.17</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Theoretical regression formulas were calculated based on the number of recognition sites in lambda DNA for each of the methyl-sensitive restriction enzymes-AciI: 516, BstUI: 157, HinP1I: 215, HpaII and the isoschizomer MspI: 328, and HpyCH4IV: 143. The Actual regression formulae were calculated based on the regression analysis using the theoretical methylation level as a predictor for the results from <italic>CpG</italic>lobal.</p></table-wrap-foot>", "<table-wrap-foot><p>Numbers in bold with asterisks indicate statistical significance of Wilcoxon/Kruskal-Wallis tests with threshold of p &lt;= 0.05 (**) or p &lt;= 0.10 (*).</p></table-wrap-foot>", "<table-wrap-foot><p>Numbers in bold with asterisks indicate statistical significance of non-parametric Wilcoxon/Kruskal-Wallis tests with a threshold of p &lt;= 0.05 (**) or p &lt;= 0.10 (*).</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2407-8-222-1\"/>", "<graphic xlink:href=\"1471-2407-8-222-2\"/>", "<graphic xlink:href=\"1471-2407-8-222-3\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Invasive cervical cancer (ICC) is one of the leading causes of cancer-related death in women in developing countries. According to the WHO, the age-adjusted incidence rate of ICC in Brazil is 23.4 per 100,000 women [##UREF##0##1##], making it the second most common cancer in Brazilian women. The major risk factor is persistent infection with oncogenic types of human papillomavirus (HPV) with the contribution of additional co-factors such as smoking and oral contraceptive use. A strong association exists between persistent HPV infections and risk of squamous intraepithelial lesions (SIL), particularly for HPV types 16 and 18 [##REF##11754676##2##]. HPV DNA sequences are found in 2% to 44% of sexually-active asymptomatic women [##REF##16406226##3##], but virtually all cervical carcinomas contain DNA of the high-risk types [##REF##10451482##4##]. However, HPV infection is necessary but not sufficient to cause the development of ICC.</p>", "<p>HPV-16 is the most common type found in ICC and in healthy women. Investigations of HPV-16 sequence variability worldwide suggest that the virus evolved along five major phylogenetic branches that largely reflect the ethnicity of the human host populations [##REF##8411343##5##]. Studies from different populations described that non European variants, mainly from the Asian-American branch, are associated with higher risks of HPV persistence and CIN development [##REF##11086127##6##], as well as ICC [##REF##11535707##7##]. Different biological and biochemical properties have already been attributed to naturally occurring variants of HPV-16 [##REF##8794343##8##, ####REF##15140991##9##, ##REF##17854024##10##, ##REF##16519914##11####16519914##11##], and a differential risk for HPV persistence and ICC was also associated with some HPV-16 variants [##REF##8900368##12##,##REF##9485042##13##].</p>", "<p>The increased rate of HPV related diseases in patients with cellular immunodeficiency suggests an important role of the immune response in the control of HPV infection [##REF##16219398##14##]. Due to the crucial function of HLA class II molecules on antigen presentation to CD4 T cells, as well as the high polymorphism of HLA genes, many studies investigated associations between HLA class II alleles and HPV associated diseases [[##REF##1876187##15##, ####REF##1351625##16##, ##REF##7861462##17####7861462##17##], for review see [##REF##14644340##18##]].</p>", "<p>A decreased risk of ICC was observed in carriers of <italic>DQB1*05 </italic>in our previous case-control study conducted in a Northeastern Brazilian population [##REF##11097225##19##], and similar associations were found in studies conducted in the British population [##REF##10755413##20##,##REF##8782644##21##]. Positive associations with <italic>HLA-DRB1*15</italic>-<italic>DQB1*0602 </italic>were reported in Brazilian [##REF##11097225##19##], British [##REF##10755413##20##] and Swedish women [##REF##8945607##22##], as well as Hispanics from New Mexico [##REF##8162070##23##]. However, this haplotype was inversely associated with HPV-16 high-grade SIL (HSIL) in a study performed in United States [##REF##9829713##24##]. The conflicting data concerning some of HLA associations among different populations may be influenced by HPV-16 variability, because variants can be immunologically distinct, since some sequence changes occur in potential HLA class II and I epitopes.</p>", "<p>Previous studies were conducted to investigate the association between HPV-16 variants and HLA class II polymorphism in different populations. In Japanese women, <italic>DRB1*1501 </italic>and <italic>DQB1*0602 </italic>alleles are associated with ICC positive for HPV-16 prototype [##REF##12918070##25##]. A study done with Swedish, Italian and Czech women revealed a trend for a positive association between carriers of <italic>DRB1*04</italic>-<italic>DQB1*03 </italic>haplotypes and ICC positive for E6 83V variants [##REF##11745467##26##]. The same amino acid substitution was associated with HLA-DRB1*07 [##REF##9754647##27##] and <italic>DR4</italic>-<italic>DQ3 </italic>[##REF##15929080##28##] in Dutch and Swedish populations, respectively. Conversely, no associations were found in a British study [##REF##10755413##20##].</p>", "<p>To investigate if the association pattern between HLA class II genes and ICC is dependent on the distribution of HPV-16 variants, we evaluated the HPV-16 variability in 107 patients enrolled in a case-control study [##REF##11097225##19##], previously analyzed for <italic>HLA-DRB1</italic>, <italic>DQB1 </italic>and <italic>DQA1 </italic>polymorphisms.</p>" ]

[ "<title>Methods</title>", "<title>Samples</title>", "<p>The 107 HPV-16 positive cases and 257 controls included in the present study were selected from an epidemiological study of ICC and HPV infection previously conducted in Brazil, whose details have been presented elsewhere [##REF##7658069##29##,##REF##11097225##19##]. Cases were women with histopathological confirmation of squamous ICC admitted for diagnosis and treatment at the Napoleão Laureano Hospital, in João Pessoa, Brazil, between 1986 and 1990. Controls were women with normal or inflammatory Pap smears selected from a citywide opportunistic screening program carried out at the same hospital. Written informed consent was obtained from all patients and controls, and ethical review committee of the Hospital Napoleão Laureano and of the Hospital do Cancer A C Camargo/Fundação Antonio Prudente approved the study. Risk factor information was obtained through a standardized interview carried out by a trained nurse using a structured questionnaire. Ethnicity was identified by the nurse according to previously designated categories (white, mulatto and black). A cervical cell specimen was collected from each control using a cytobrush, and tumor biopsies were obtained from all cases. Clinical specimens were prepared and submitted to cytological or histological examination, and the remaining cells and tissues were stored at -20°C and shipped in dry ice to the Ludwig Institute for Cancer Research (São Paulo, Brazil) to DNA extraction. Aliquots of the purified DNA were used for HPV detection and typing, characterization of HPV-16 variants as well as for HLA typing.</p>", "<title>HPV typing</title>", "<p>DNA extraction and HPV detection and typing were performed by standard techniques [##REF##7658069##29##]. Briefly, DNA samples from cases and controls were submitted to PCR-based amplification of a 450 bp segment in the L1 viral gene with MY09 and MY11 primers [##UREF##1##30##]. PCR products were dot blotted in a Nylon membrane and hybridized with individual ³²P-labeled oligonucleotide probes specific for HPV types 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 45, 51–59, 66, 68, 70, 71, 72, 81, 82, 83 and 89 [##REF##1845912##31##,##REF##8235926##32##].</p>", "<title>Characterization of HPV-16 variants</title>", "<p>HPV-16 variants were characterized for <italic>E6 </italic>and <italic>L1 </italic>genes by nested PCR, followed by hybridization with oligonucleotide probes [##REF##8968874##33##]. The probes sequences and washing temperatures were as described by before [##REF##8968874##33##], except the <italic>E6 </italic>350G and 403A, washed at 47°C. The hybridization pattern of each sample with all the probes allows the classification of variants into European (E), Asian-American (AA), African-1 (Af-1) and African-2 (Af-2) branches, and two additional subclasses within E and AA branches [##REF##7494284##34##]. Variant designation was done according to previous report [##REF##9032384##35##].</p>", "<p>Some specimens were further characterized by sequencing analysis of viral gene fragments. L1 PCR products were cloned using the Sure Clone ligation kit (Amersham Pharmacia, New Jersey, USA) and transformed into <italic>E. coli</italic>, strain DH5α. E6 PCR products cloning were done with TOPO TA Cloning kit (Invitrogen, Carlsbad, USA) and transformed into TOP10 Chemically competent <italic>E.coli </italic>(Invitrogen, Carlsbad, USA). Clones were screened by PCR with plasmid specific primers, and these PCR products were sequenced using Big-Dye Terminator (Applied Biosystems, Foster City, USA) and one of the primers used in the PCR. Sequences were analyzed in an ABI3100 sequencer (Applied Biosystems, Foster City, USA). To identify infections by multiple variants, five clones from each transformation were selected for sequencing analysis. Samples were classified as positive for multiple infections only if clones from different HPV-16 branches were identified in one gene fragment and confirmed in the other (<italic>E6 </italic>and <italic>L1</italic>).</p>", "<title>HLA typing</title>", "<p>All the 257 controls and the 112 HPV-16 positive cases used in this study had been previously typed for HLA class II genes [##REF##11097225##19##]. Typing was done by PCR-amplification of the 2^ndexon of <italic>HLA-DQA1</italic>, <italic>DQB1 </italic>and <italic>DRB1 </italic>genes, followed by hybridization with sequence-specific oligonucleotide probes [##UREF##2##36##].</p>", "<title>Statistical analysis</title>", "<p>To evaluate the differences in the distribution of HLA group frequencies between cases carrying each HPV-16 variant and controls, odds ratios (OR) and respective 95% confidence intervals (95% CI) were calculated. Crude and age- and ethnicity-adjusted ORs were computed by unconditional logistic regression, using SPSS statistical software (version 11.0). In our previous study [##REF##11097225##19##] other variables (level of education, income, consumption of alcoholic beverages other than beer or sugar cane distillates) were also controlled for because of their association with ethnicity. In the interest of precision, however, as similar estimates were obtained using models based on both sets of confounders we used only adjustment for age and ethnicity. All the associations that were analyzed are reported.</p>" ]

[ "<title>Results</title>", "<p>HPV-16 variants from E, AA, Af-1 and Af-2 branches were identified in 107 cases out of 112 HPV-16 positive ICC cases, because five samples were not included in variant analysis due to PCR failure or disagreement between variant identity in E6 and L1 genes. Although we detected 36 HPV positive samples in the control group [##REF##11097225##19##], only 12 were HPV-16 positive. Due to this small number of carriers, we did not characterize HPV-16 variability in the control group. The frequency of cases harboring AA variants was similar to the frequency of cases with E variants, while a low proportion of African variants was observed, being 8 of Af-2 branch, and only one Af-1 variant (Table ##TAB##0##1##). We identified double infections by variants from different branches in 15 cases, 13 of which were carriers of AA and European prototype (E-P) variants, one positive for E-P and Af-2, and the other one carrying AA and Af-2 variants. Only one case harbored two different HPV-16 variants of the same branch, the European. The AAa variant, which belongs to the AA branch, was the most frequent HPV-16 variant in this series. From the same branch, we identified one NA-1 variant. The second most common variant was the E-P, from the E branch. We also identified an E-6994A, an E-G131T and 4 E-350G variants.</p>", "<p>In our previous case-control study performed with these samples, we have reported that <italic>DRB1*15 </italic>and the <italic>DRB1*1503</italic>-<italic>DQB1*0602 </italic>haplotype were positively associated with ICC. On the other hand, <italic>DRB1*0101 </italic>and <italic>DQB1*05 </italic>were inversely associated with this disease [##REF##11097225##19##]. As HPV-16 was the most common type found in those samples, we extended the type-specific analysis and the most relevant results are shown in Table ##TAB##1##2##.</p>", "<p>To perform the analysis of HLA distribution we first excluded 33 cases that contained HPV types other than 16, and then excluded 5 cases that were positive for more than one HPV-16 variant, as the influence of one variant in immune response to another is not clear. We therefore evaluated the HLA distribution in 69 cases, which were positive for HPV-16 only and had a single variant infection, and 257 controls. HPV-16 variants distribution in these cases is also shown in Table ##TAB##0##1##.</p>", "<p>The comparison of <italic>HLA-DQA1</italic>, <italic>DQB1 </italic>and <italic>DRB1 </italic>alleles' distribution between controls and cases, which were stratified according to major variants E-P and AA found in this sample, is presented on Table ##TAB##2##3##. We observed that the proportion of <italic>HLA-DQA1*0101/04 </italic>carriers was lower in cases positive for AA variants than in controls (Table ##TAB##2##3##). Due to linkage disequilibrium, this allele is commonly found in haplotypes with <italic>DQB1*05 </italic>and <italic>DRB1*01 </italic>alleles. As expected, an inverse association between <italic>HLA-DQB1*05 </italic>and <italic>DQB1*0501 </italic>carriers was also observed with AA variant cases (Table ##TAB##2##3##). Interestingly, the allele <italic>DRB1*1302 </italic>was not found among AA positive cases (p = 0.03, Fisher exact test), although its frequency was not statistically different between controls and ICC cases positive for E variants (Table ##TAB##2##3##).</p>", "<p>A higher frequency of <italic>HLA-DQA1*0102 </italic>was found in cases positive for E variants (adjusted OR = 2.32, 95% CI: 0.96–5.62; Table ##TAB##2##3##; p = 0.06) than in controls, but not in those associated with AA variants (Table ##TAB##2##3##). Although the <italic>DQA1*0102 </italic>allele can be found in different <italic>DRB1-DQB1 </italic>haplotypes, we found it mainly with <italic>DRB1*15 </italic>and <italic>DQB1*0602 </italic>alleles. The association with <italic>DRB1*15 </italic>was comparable between European variants (OR = 2.99; 95% CI: 1.13–7.86; p = 0.03) and AA variants (OR = 2.34; 95% CI: 1.00–5.46, p = 0.05) (Table ##TAB##2##3##). In both European and AA groups, the <italic>DRB1*1503 </italic>allele had the highest OR values (adjusted OR = 3.75; 95% CI: 0.99–12.42; p = 0.05 and OR = 2.62; 95% CI: 0.83–8.27; p = 0.10, respectively). <italic>DRB1*15 </italic>alleles are found in linkage disequilibrium with <italic>DQB1*0602</italic>. However, it is worth noting that this allele was found, in most cases, in linkage with <italic>DRB1*15</italic>, whereas in the controls, a larger proportion of <italic>DQB1*0602 </italic>was found in linkage with <italic>DRB1*11 </italic>alleles.</p>", "<p>The only statistically significant result in the comparison of <italic>HLA-DRB1-DQB1 </italic>haplotypes in the stratified analysis was an association between <italic>DRB1*15</italic>-<italic>DQB1*0602 </italic>and E-variant cases (p = 0.02, Table ##TAB##2##3##). Similar to the trends observed for the distribution of alleles, we found a lower frequency of the <italic>DRB1*0102</italic>-<italic>DQB1*0501 </italic>haplotype in patients carrying AA variants (adjusted OR = 0.18; 95% CI: 0.02–1.44; Table ##TAB##2##3##; p = 0.11) than in E carriers (adjusted OR = 2.18; CI: 0.75–6.29; Table ##TAB##2##3##, p = 0.15).</p>", "<p>Although the number of African variants was too small to allow any stratified analysis, it is of relevance that 4 of the 8 Af-2 cases were carriers of <italic>DRB1*07-DQB1*02 </italic>haplotype (in the control group, this haplotype was identified in 47 of the 257 controls).</p>", "<p>To verify if T to G substitution at 350 nucleotide position in the <italic>E6 </italic>viral oncogene could interfere in HLA association with ICC, we stratified cases according to this polymorphism and results of this analysis are on Table ##TAB##3##4##. The E6 83V group was composed of cases harbouring AA and the E-350G variants, while other E variants and Af variants formed the 83L group. Despite the observed inverse association between <italic>DQB1*05 </italic>and 83V cases (OR = 0.37; 95% CI: 0.15–0.89; Table ##TAB##3##4##, p = 0.03), the proportion of <italic>DQB1*05 </italic>carriers in 83L cases was not different from controls. Similar tendencies were also verified for the <italic>DQB1*0501 </italic>allele. We also found an inverse association between <italic>DRB1*04 </italic>and ICC cases positive for 83L E6 variants (adjusted OR = 0.27; 95% CI: 0.08–0.96; Table ##TAB##3##4##, p = 0.04), which was not observed for patients carrying 83V E6 variants.</p>", "<p>The frequency of <italic>DQA1*0102 </italic>carriers was higher in cases carrying 83L E6 variants (OR = 2.24; 95% CI: 0.99–5.09, p = 0.05) than in controls (Table ##TAB##3##4##). Increased risks were also seen for <italic>DRB1*15 </italic>alleles, particularly <italic>DRB1*1503</italic>. However, statistical significance was only unequivocal for cases with 83L variants (OR = 3.87, 95% CI: 1.20–12.52, p = 0.02). The analysis of haplotypes revealed a positive association between <italic>DRB1*15</italic>-<italic>DQB1*0602 </italic>and <italic>DRB1*1503</italic>-<italic>DQB1*0602 </italic>(OR = 2.86; 95% CI: 1.14–7.16, p = 0.02 and OR = 3.87; 95% CI: 1.20–12.52, p = 0.02 respectively; Table ##TAB##3##4##) with 83L carriers. Similar trends were found for 83V variants but they did not reach statistical significance. Despite the low frequency of the <italic>DRB1*09012</italic>-<italic>DQB1*0201/02 </italic>haplotype in this sample, it was positively associated with ICC carrying 83L variants (Table ##TAB##3##4##).</p>" ]

[ "<title>Discussion</title>", "<p>In this report we analyzed the interplay between HPV-16 variants and <italic>HLA-DQA1, DQB1 </italic>and <italic>DRB1 </italic>variability on the susceptibility to ICC in Brazilian women. We found similar frequencies of European (prototype) and AA HPV-16 variants in our group of cases and a lower proportion of African variants in samples from cervical cancer patients. In agreement with a previous study by our team of a different Brazilian population [##REF##11086127##6##], the major European variant found in these samples was the prototype. Non-European variants are associated with greater risk of cervical lesions than European ones but results have not been uniform across populations. Some studies were conducted in European populations [##REF##10755413##20##,##REF##9754647##27##,##REF##9807995##37##] and conflicting results were observed, probably due to the predominance of lower risk European variants in those populations [##REF##12445662##38##]. The relatively high proportion of AA variants in our cases agrees with our previous observation in asymptomatic Brazilian women that indicate that these variants are associated with higher risks of HPV persistence and CIN development [##REF##11086127##6##]. A case-control study done in Mexico also revealed a higher ICC risk among women carrying AA than E variants [##REF##11535707##7##]. Data obtained from such admixtured populations in the Americas show a reproducible pattern of risk associated with non-European variants of HPV-16 [##REF##12445662##38##]. The diverse distribution of HPV variants between cases and controls from several populations can reflect differences in their oncogenic potential. It has been suggested that differences in the LCR sequence might play a role in HPV-induced tumorigenesis, because nucleotide changes can alter promoter activity of the viral genome [##REF##10900036##39##,##REF##15688288##40##]. On the other hand, variations in coding regions, such as in E6 gene sequences could also explain this diverse oncogenic potential of variants through differential protein activity [##REF##8794343##8##, ####REF##15140991##9##, ##REF##17854024##10##, ##REF##16519914##11####16519914##11##].</p>", "<p>Several studies investigated the role of HLA class II genes and alleles in HPV related diseases. Positive associations with <italic>DRB1*15</italic>-<italic>DQB1*06 </italic>haplotype and inverse associations with <italic>HLA-DRB1*13 </italic>allele were described in different populations, including Brazilians [##REF##11097225##19##], Americans/Hispanics [##REF##8162070##23##] and Europeans [##REF##10755413##20##,##REF##8945607##22##]. In some of these studies, associations with cases harboring HPV-16 have been suggested: <italic>DRB1*0407</italic>-<italic>DQB1*0302 </italic>haplotype was positively associated with HPV-16 positive cases in Hispanic women [##REF##8162070##23##]. Likewise, we have previously reported an association of <italic>DRB1*1503 </italic>with HPV positive ICC, with higher OR values when only HPV-16 cases were considered [##REF##11097225##19##], but in this report we found similar results when compared women harboring E and AA variants. Since associations involving <italic>DR*15 </italic>alleles were observed in many populations [##REF##10755413##20##,##REF##8945607##22##,##REF##8162070##23##,##REF##7861462##41##, ####REF##10363725##42##, ##REF##11519043##43####11519043##43##], with different HPV variants, it is reasonable to speculate an effect of this allele on cervical disease independently of HPV-16 variants distribution.</p>", "<p>On the other hand, stratification of cases according to HPV-16 variants allowed us to find that trends of inverse associations between HPV-16 cases with <italic>DQA1*0101/04 </italic>and <italic>DQB1*05 </italic>[##REF##11097225##19##] are due to AA variants. Previous studies involving populations with few AA variants [##REF##11745467##26##, ####REF##9754647##27##, ##REF##15929080##28####15929080##28##] did not report the association of AA cases with <italic>DQB1*05</italic>. Due to the high prevalence of E variants in these studies, they took into consideration mostly single nucleotide polymorphisms, as in the <italic>E6 </italic>gene, which generates variants designated L83V (T to G substitution at 350 nucleotide position). This substitution was associated with and increased risk for HPV persistence and ICC [##REF##8900368##12##].</p>", "<p>Inverse associations of cervical cancer with <italic>DRB1*13 </italic>group were found in Costa Rica [##REF##11679920##44##] and Hispanic women from USA [##REF##8162070##23##]; as well as Swedish [##REF##8945607##22##]; French [##REF##8682580##45##] and Dutch [##REF##10363725##42##] populations. A trend for negative association was observed in American women [##REF##9829713##24##], similar to what we observed previously between <italic>DRB1*1302 </italic>and ICC cases [##REF##11097225##19##]. In our present study, the comparison of <italic>DRB1*1302 </italic>frequency between controls and European variants cases did not reveals any association, but, interestingly, this allele was not found in ICC cases positive for AA variants, suggesting a protective role of this allele to cases carrying AA variants.</p>", "<p>We found a lower proportion of women carrying DR4 in 83L cases than in controls, and a similar trend was observed in the <italic>DRB1*04</italic>-<italic>DQB1*0302 </italic>haplotype comparison (data not shown). Interestingly, in a Swedish population, the frequency of <italic>DR*04</italic>-<italic>DQ*03 </italic>haplotype was higher in cases with 83V variant than in controls [##REF##15929080##28##]; and similar trends were also described for Italian, Czech and other Swedish populations [##REF##11745467##26##]. A study conducted in the British population revealed that HPV-16 E2 variants, which also present the E6 350G (83V), occurred more frequently in individuals with HLA-<italic>DRB1*0401</italic>-<italic>DQB1*0301 </italic>and <italic>DRB1*1101</italic>-<italic>DQB1*0301 </italic>haplotypes [##REF##9398041##46##].</p>", "<p>The influence of HPV-16 variants in HLA distribution in ICC cases suggests that variants can differ in their immunogenic potential. Although there are few studies and most of them restricted to small sample sizes, which limits the interpretation of some findings, it is possible that the associations can reflect alterations in the binding of viral epitopes to HLA molecules. The <italic>DR4 </italic>alleles found here are in linkage disequilibrium with <italic>DQ3 </italic>and it was already detected that a substitution of a residue in a HSV peptide impaired its binding to DQ3.2 molecule (allele <italic>DQB1*0302</italic>), but this altered peptide become able to bind to DQ3.1 and DQ3.3 molecules (<italic>DQB1*0301 </italic>and <italic>*0303 </italic>alleles, respectively) [##REF##8690906##47##]. Functional consequences of alterations in viral proteins were demonstrated in animal models, and a single residue change in E6 protein of cottontail rabbit papillomavirus progressor strain led to high frequencies of spontaneous regressions in inbred rabbits [##REF##12414922##48##]. Variations in E6 protein from AA and E variants differ in peptide positions (14H, 83V) that are encompassed by the epitopes described earlier [##REF##9293919##49##,##REF##12566307##50##], but further evaluation is warranted to elucidate a possible role of these substitutions in immune response.</p>", "<p>In our previous report, we did not detect many differences when comparing HPV negative and positive controls [##REF##11097225##19##]. However, HPV detection was performed in a single point in time. In our longitudinal study, different haplotypes were associated with HPV infections and/or persistence [##REF##12134251##51##], but this study was conducted in a population of a different region in Brazil, which could reflect differences in HLA distribution. Bontkes et al. 1998 [##REF##9754647##27##] suggest that immunogenetic factors associated with disease progression are different from those associated with susceptibility to HPV-16 infection. However, Beskow <italic>et al</italic>., 2002 [##REF##12237892##52##] found a strong correlation between long-term infection and high viral load and between short-term infection and low viral load. They described that carriers of <italic>DRB1*1501</italic>-<italic>DQB1*0602 </italic>haplotype, had higher HPV-16 viral load than non-carriers [##REF##12237892##52##] and that carriers of protective alleles (<italic>DRB1*1301 </italic>and <italic>DQB1*0603</italic>) have lower HPV-18/45 load compared to non carriers [##REF##15906352##53##]. These results suggest an interaction between viral (as HPV types, variants and viral load) and host factors, and it is possible that HLA polymorphism may affect the immune reaction to the virus and indirectly play a role in the susceptibility to HPV-related lesions.</p>" ]

[ "<title>Conclusion</title>", "<p>Taken together our data suggest that HPV-16 variability influences the association between HLA polymorphism and ICC risk. Studies to elucidate its influence in immune responses to HPV, and its role in viral clearance or progression of HPV-related diseases are warranted.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Persistent infection with oncogenic types of human papillomavirus (HPV) is the major risk factor for invasive cervical cancer (ICC), and non-European variants of HPV-16 are associated with an increased risk of persistence and ICC. HLA class II polymorphisms are also associated with genetic susceptibility to ICC. Our aim is to verify if these associations are influenced by HPV-16 variability.</p>", "<title>Methods</title>", "<p>We characterized HPV-16 variants by PCR in 107 ICC cases, which were typed for <italic>HLA-DQA1</italic>, <italic>DRB1 </italic>and <italic>DQB1 </italic>genes and compared to 257 controls. We measured the magnitude of associations by logistic regression analysis.</p>", "<title>Results</title>", "<p>European (E), Asian-American (AA) and African (Af) variants were identified. Here we show that inverse association between <italic>DQB1*05 </italic>(adjusted odds ratio [OR] = 0.66; 95% confidence interval [CI]: 0.39–1.12]) and HPV-16 positive ICC in our previous report was mostly attributable to AA variant carriers (OR = 0.27; 95%CI: 0.10–0.75). We observed similar proportions of <italic>HLA DRB1*1302 </italic>carriers in E-P positive cases and controls, but interestingly, this allele was not found in AA cases (p = 0.03, Fisher exact test). A positive association with <italic>DRB1*15 </italic>was observed in both groups of women harboring either E (OR = 2.99; 95% CI: 1.13–7.86) or AA variants (OR = 2.34; 95% CI: 1.00–5.46). There was an inverse association between <italic>DRB1*04 </italic>and ICC among women with HPV-16 carrying the 350T [83L] single nucleotide polymorphism in the <italic>E6 </italic>gene (OR = 0.27; 95% CI: 0.08–0.96). An inverse association between <italic>DQB1*05 </italic>and cases carrying 350G (83V) variants was also found (OR = 0.37; 95% CI: 0.15–0.89).</p>", "<title>Conclusion</title>", "<p>Our results suggest that the association between HLA polymorphism and risk of ICC might be influenced by the distribution of HPV-16 variants.</p>" ]

[ "<title>Abbreviations</title>", "<p>CI: confidence intervals; HLA: human leukocyte antigen; HPV: human papillomavirus; OR: odds ratio; ICC: invasive cervical carcinoma; PCR: polymerase chain reaction; E: European variants of HPV-16; AA: Asian-American variants of HPV-16; Af-2: African-2 variants of HPV-16.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>PSAS carried out the HPV-16 variants typing, participated HLA typing and drafted the manuscript. PCM carried out the HLA typing and participated in study design. KBR performed the statistical analysis. MLP–E coordinated the HLA typing and participated in study design. ELF and LLV participated in the study design and supervised the study. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2407/8/246/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Drs J Simões, M Farias, C Seixas, L Araujo, I Arruda, P Honorato and F Honorato (Hospital Napoleão Laureano, João Pessoa, Brazil) for subject accrual and A Silva for specimens collection of asymptomatic women and conducting the interviews; MC Costa e AV Novello Neto for HPV typing; AC Salim and E Monteiro for sequencing.</p>", "<p>This work was supported by the CNPq, FAPESP and the Ludwig Institute for Cancer Research.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Distribution of HPV-16 variants in cervical biopsies from HPV-16 positive ICC cases</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Branch</td><td align=\"left\">Variants</td><td align=\"center\" colspan=\"4\">E6 substitutions^a</td><td align=\"center\">All HPV-16 cases</td><td align=\"center\">HPV-16 exclusively^d</td></tr><tr><td/><td/><td colspan=\"4\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td></tr><tr><td/><td/><td align=\"center\">10</td><td align=\"center\">14</td><td align=\"center\">78</td><td align=\"center\">83</td><td align=\"center\">Carriers (%)^bn = 107^c</td><td align=\"center\">Carriers (%) n = 69</td></tr></thead><tbody><tr><td align=\"left\">E</td><td/><td/><td/><td/><td/><td align=\"center\">54 (50.5)</td><td align=\"center\">28 (40.6)</td></tr><tr><td/><td align=\"left\">E-P</td><td align=\"center\">A</td><td align=\"center\">Q</td><td align=\"center\">H</td><td align=\"center\">L</td><td align=\"center\"><italic>49 (45.8)</italic></td><td align=\"center\"><italic>23 (33.3)</italic></td></tr><tr><td/><td align=\"left\"><italic>E-350G</italic></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">V</td><td align=\"center\"><italic>4</italic></td><td align=\"center\"><italic>3</italic></td></tr><tr><td/><td align=\"left\"><italic>E-6994 A</italic></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\"><italic>1</italic></td><td align=\"center\"><italic>1</italic></td></tr><tr><td/><td align=\"left\"><italic>E-G131T</italic></td><td align=\"center\">G</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\"><italic>1</italic></td><td align=\"center\"><italic>1</italic></td></tr><tr><td align=\"left\">AA</td><td/><td/><td/><td/><td/><td align=\"center\">59 (55.1)</td><td/></tr><tr><td/><td align=\"left\">AAa</td><td align=\"center\">-</td><td align=\"center\">H</td><td align=\"center\">Y</td><td align=\"center\">V</td><td align=\"center\"><italic>58 (54.2)</italic></td><td align=\"center\"><italic>37 (53.6)</italic></td></tr><tr><td/><td align=\"left\">NA-1</td><td align=\"center\">-</td><td align=\"center\">H</td><td align=\"center\">Y</td><td align=\"center\">V</td><td align=\"center\"><italic>1</italic></td><td align=\"center\"><italic>0</italic></td></tr><tr><td align=\"left\">Af-1</td><td align=\"left\">Af-1</td><td align=\"center\">T</td><td align=\"center\">D</td><td align=\"center\">Y</td><td align=\"center\">-</td><td align=\"center\">1</td><td align=\"center\">0</td></tr><tr><td align=\"left\">Af-2</td><td align=\"left\">Af-2</td><td align=\"center\">I</td><td align=\"center\">D</td><td align=\"center\">Y</td><td align=\"center\">-</td><td align=\"center\">8 (7.5)</td><td align=\"center\">4 (5.7)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>ORs and 95% CIs for HPV-16 positive ICC according to HLA.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Controls<break/>(n = 257)</td><td align=\"center\" colspan=\"4\">HPV-16 Cases<break/>(n = 112)</td></tr><tr><td/><td colspan=\"1\"><hr/></td><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">HLA</td><td/><td/><td align=\"center\">Crude</td><td align=\"center\" colspan=\"2\">Adjusted^d</td></tr><tr><td/><td/><td/><td colspan=\"1\"><hr/></td><td colspan=\"2\"><hr/></td></tr><tr><td/><td align=\"center\">C/N^a</td><td align=\"center\">C/N</td><td align=\"center\">OR^b</td><td align=\"center\">OR</td><td align=\"center\">CI^c</td></tr></thead><tbody><tr><td align=\"left\"><italic>DQA1</italic></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">  *0102</td><td align=\"center\">80/177</td><td align=\"center\">39/73</td><td align=\"center\">1.18</td><td align=\"center\">1.22</td><td align=\"center\">0.73–2.04</td></tr><tr><td align=\"left\"><italic>DQB1</italic></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">  *0501</td><td align=\"center\">71/186</td><td align=\"center\">25/87</td><td align=\"center\">0.75</td><td align=\"center\">0.72</td><td align=\"center\">0.40–1.27</td></tr><tr><td align=\"left\"> *06</td><td align=\"center\">87/170</td><td align=\"center\">46/66</td><td align=\"center\">1.36</td><td align=\"center\">1.32</td><td align=\"center\">0.80–2.17</td></tr><tr><td align=\"left\">  *0602</td><td align=\"center\">44/213</td><td align=\"center\">30/82</td><td align=\"center\">1.77</td><td align=\"center\">1.59</td><td align=\"center\">0.89–2.83</td></tr><tr><td align=\"left\"><italic>DRB1</italic></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> *01</td><td align=\"center\">52/205</td><td align=\"center\">22/90</td><td align=\"center\">0.96</td><td align=\"center\">0.89</td><td align=\"center\">0.49–1.64</td></tr><tr><td align=\"left\">  *0102</td><td align=\"center\">29/228</td><td align=\"center\">12/100</td><td align=\"center\">0.94</td><td align=\"center\">0.83</td><td align=\"center\">0.38–1.79</td></tr><tr><td align=\"left\"> *04</td><td align=\"center\">74/183</td><td align=\"center\">23/89</td><td align=\"center\">0.64</td><td align=\"center\">0.67</td><td align=\"center\">0.38–1.19</td></tr><tr><td align=\"left\"> *13</td><td align=\"center\">61/196</td><td align=\"center\">19/93</td><td align=\"center\">0.66</td><td align=\"center\">0.78</td><td align=\"center\">0.42–1.45</td></tr><tr><td align=\"left\">  *1302</td><td align=\"center\">27/230</td><td align=\"center\">4/108</td><td align=\"center\">0.32</td><td align=\"center\">0.43</td><td align=\"center\">0.14–1.32</td></tr><tr><td align=\"left\"><italic>DRB1-DQB1 haplotypes</italic></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> 0102–0501</td><td align=\"center\">29/228</td><td align=\"center\">12/100</td><td align=\"center\">0.94</td><td align=\"center\">0.59</td><td align=\"center\">0.23–1.51</td></tr><tr><td align=\"left\"> 15-0602</td><td align=\"center\">33/224</td><td align=\"center\">28/84</td><td align=\"center\">2.26</td><td align=\"center\">2.12</td><td align=\"center\">1.15–3.93</td></tr><tr><td align=\"left\"> 1503-0602</td><td align=\"center\">14/243</td><td align=\"center\">15/97</td><td align=\"center\">2.68</td><td align=\"center\">2.77</td><td align=\"center\">1.20–6.39</td></tr><tr><td align=\"left\"> 08041-0301</td><td align=\"center\">5/252</td><td align=\"center\">3/109</td><td align=\"center\">1.39</td><td align=\"center\">0.88</td><td align=\"center\">0.14–5.47</td></tr><tr><td align=\"left\"> 09012-0201/02</td><td align=\"center\">3/254</td><td align=\"center\">3/109</td><td align=\"center\">2.33</td><td align=\"center\">3.02</td><td align=\"center\">0.56–16.29</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>ORs and 95% CIs for ICC HPV-16EP or AA positive according to HLA.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Controls</td><td align=\"center\" colspan=\"3\">AA Cases</td><td align=\"center\" colspan=\"3\">EP Cases</td></tr><tr><td/><td colspan=\"1\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\">HLA</td><td align=\"center\">C/N</td><td align=\"center\">C/N</td><td align=\"center\">Crude</td><td align=\"center\">Adjusted</td><td align=\"center\">C/N</td><td align=\"center\">Crude</td><td align=\"center\">Adjusted</td></tr><tr><td/><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td></tr><tr><td/><td align=\"center\">Controls</td><td align=\"center\">Cases</td><td align=\"center\">OR</td><td align=\"center\">OR (95% CI)</td><td align=\"center\">Cases</td><td align=\"center\">OR</td><td align=\"center\">OR (95% CI)</td></tr><tr><td/><td align=\"center\">n = 257</td><td align=\"center\">n = 37</td><td/><td/><td align=\"center\">n = 24</td><td/><td/></tr></thead><tbody><tr><td align=\"left\">DQA1</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">  *0101/04</td><td align=\"center\">79/178</td><td align=\"center\">5/32</td><td align=\"center\">0.35</td><td align=\"center\">0.34(0.12–0.93)</td><td align=\"center\">9/15</td><td align=\"center\">1.35</td><td align=\"center\">1.31 (0.53–3.25)</td></tr><tr><td align=\"left\">  *0102</td><td align=\"center\">80/177</td><td align=\"center\">10/27</td><td align=\"center\">0.82</td><td align=\"center\">0.82(0.37–1.83)</td><td align=\"center\">12/12</td><td align=\"center\">2.21</td><td align=\"center\">2.32 (0.96–5.62)</td></tr><tr><td align=\"left\">DQB1</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">  *0301</td><td align=\"center\">78/179</td><td align=\"center\">9/28</td><td align=\"center\">0.74</td><td align=\"center\">0.74(0.32–1.70)</td><td align=\"center\">8/16</td><td align=\"center\">1.15</td><td align=\"center\">1.08 (0.42–2.75)</td></tr><tr><td align=\"left\"> *05</td><td align=\"center\">95/162</td><td align=\"center\">5/32</td><td align=\"center\">0.27</td><td align=\"center\">0.27(0.10–0.75)</td><td align=\"center\">10/14</td><td align=\"center\">1.22</td><td align=\"center\">1.29 (0.53–3.14)</td></tr><tr><td align=\"left\">  *0501</td><td align=\"center\">71/186</td><td align=\"center\">4/33</td><td align=\"center\">0.32</td><td align=\"center\">0.30 (0.10–0.92)</td><td align=\"center\">9/15</td><td align=\"center\">1.57</td><td align=\"center\">1.56 (0.63–3.89)</td></tr><tr><td align=\"left\"> *06</td><td align=\"center\">87/170</td><td align=\"center\">16/21</td><td align=\"center\">1.49</td><td align=\"center\">1.49 (0.72–3.08)</td><td align=\"center\">12/12</td><td align=\"center\">1.95</td><td align=\"center\">2.02 (0.84–4.88)</td></tr><tr><td align=\"left\">  *0602</td><td align=\"center\">44/213</td><td align=\"center\">9/28</td><td align=\"center\">1.56</td><td align=\"center\">1.45 (0.62–3.39)</td><td align=\"center\">8/16</td><td align=\"center\">2.42</td><td align=\"center\">2.13 (0.83–5.50)</td></tr><tr><td align=\"left\">DRB1</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> *01</td><td align=\"center\">52/205</td><td align=\"center\">4/33</td><td align=\"center\">0.48</td><td align=\"center\">0.45 (0.15–1.37)</td><td align=\"center\">7/17</td><td align=\"center\">1.62</td><td align=\"center\">1.51 (0.57–4.03)</td></tr><tr><td align=\"left\">  *0102</td><td align=\"center\">29/228</td><td align=\"center\">1/36</td><td align=\"center\">0.22</td><td align=\"center\">0.18 (0.02–1.44)</td><td align=\"center\">6/18</td><td align=\"center\">2.62</td><td align=\"center\">2.18 (0.75–6.29)</td></tr><tr><td align=\"left\"> *04</td><td align=\"center\">74/183</td><td align=\"center\">10/27</td><td align=\"center\">0.92</td><td align=\"center\">0.94 (0.42–2.09)</td><td align=\"center\">3/21</td><td align=\"center\">0.35</td><td align=\"center\">0.34 (0.10–1.21)</td></tr><tr><td align=\"left\"> *13</td><td align=\"center\">61/196</td><td align=\"center\">9/28</td><td align=\"center\">1.03</td><td align=\"center\">1.21 (0.52–2.78)</td><td align=\"center\">5/19</td><td align=\"center\">0.85</td><td align=\"center\">1.09 (0.37–3.16)</td></tr><tr><td align=\"left\">  *1302</td><td align=\"center\">27/230</td><td align=\"center\">0/37</td><td align=\"center\">0.00</td><td/><td align=\"center\">3/21</td><td align=\"center\">1.22</td><td align=\"center\">1.62 (0.42–6.16)</td></tr><tr><td align=\"left\"> *15</td><td align=\"center\">34/223</td><td align=\"center\">10/27</td><td align=\"center\">2.43</td><td align=\"center\">2.34 (1.00–5.46)</td><td align=\"center\">8/16</td><td align=\"center\">3.28</td><td align=\"center\">2.99 (1.13–7.86)</td></tr><tr><td align=\"left\">  *1503</td><td align=\"center\">14/243</td><td align=\"center\">5/32</td><td align=\"center\">2.71</td><td align=\"center\">2.62 (0.83–8.27)</td><td align=\"center\">4/20</td><td align=\"center\">3.47</td><td align=\"center\">3.75 (0.99–12.42)</td></tr><tr><td align=\"left\"><italic>DRB1-DQB1 haplotypes</italic></td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> 0102-0501</td><td align=\"center\">29/228</td><td align=\"center\">1/36</td><td align=\"center\">0.22</td><td align=\"center\">0.18 (0.02–1.44)</td><td align=\"center\">6/18</td><td align=\"center\">2.62</td><td align=\"center\">2.18 (0.75–6.29)</td></tr><tr><td align=\"left\"> 15-0602</td><td align=\"center\">33/224</td><td align=\"center\">8/29</td><td align=\"center\">1.87</td><td align=\"center\">1.84 (0.75–4.53)</td><td align=\"center\">8/16</td><td align=\"center\">3.39</td><td align=\"center\">3.08 (1.17–8.14)</td></tr><tr><td align=\"left\"> 1503-0602</td><td align=\"center\">14/243</td><td align=\"center\">5/32</td><td align=\"center\">2.71</td><td align=\"center\">2.62 (0.83–8.27)</td><td align=\"center\">4/20</td><td align=\"center\">3.47</td><td align=\"center\">3.50 (0.99–12.42)</td></tr><tr><td align=\"left\"> 08041-0301</td><td align=\"center\">5/252</td><td align=\"center\">0/27</td><td/><td/><td align=\"center\">2/22</td><td align=\"center\">4.58</td><td align=\"center\">3.59 (0.48–27.13)</td></tr><tr><td align=\"left\"> 09012-0201/02</td><td align=\"center\">3/254</td><td align=\"center\">1/36</td><td align=\"center\">2.35</td><td align=\"center\">2.62 (0.25–27.79)</td><td align=\"center\">1/23</td><td align=\"center\">3.68</td><td align=\"center\">5.00 (0.47–53.36)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>ORs and 95% CIs for HPV-16/E6-83V or E6-83L positive ICC according to HLA</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Controls</td><td align=\"center\" colspan=\"3\">E6 83V Cases</td><td align=\"center\" colspan=\"3\">E6 83L Cases</td></tr><tr><td/><td colspan=\"1\"><hr/></td><td colspan=\"3\"><hr/></td><td colspan=\"3\"><hr/></td></tr><tr><td align=\"left\">HLA</td><td align=\"center\">C/N</td><td align=\"center\">C/N</td><td align=\"center\">Crude</td><td align=\"center\">Adjusted</td><td align=\"center\">C/N</td><td align=\"center\">Crude</td><td align=\"center\">Adjusted</td></tr><tr><td/><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td><td colspan=\"1\"><hr/></td></tr><tr><td/><td align=\"center\">Controls</td><td align=\"center\">Cases</td><td align=\"center\">OR</td><td align=\"center\">OR (95% CI)</td><td align=\"center\">Cases</td><td align=\"center\">OR</td><td align=\"center\">OR (95% CI)</td></tr><tr><td/><td align=\"center\">n = 257</td><td align=\"center\">n = 40</td><td/><td/><td align=\"center\">n = 29</td><td/><td/></tr></thead><tbody><tr><td align=\"left\">DQA1</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">  *0101/04</td><td align=\"center\">79/178</td><td align=\"center\">7/33</td><td align=\"center\">0.48</td><td align=\"center\">0.46 (0.19–1.11)</td><td align=\"center\">10/19</td><td align=\"center\">1.19</td><td align=\"center\">1.13 (0.48–2.64)</td></tr><tr><td align=\"left\">  *0102</td><td align=\"center\">80/177</td><td align=\"center\">10/30</td><td align=\"center\">0.74</td><td align=\"center\">0.74 (0.33–1.63)</td><td align=\"center\">14/15</td><td align=\"center\">2.07</td><td align=\"center\">2.24 (0.99–5.09)</td></tr><tr><td align=\"left\">DQB1</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">  *0301</td><td align=\"center\">78/179</td><td align=\"center\">11/29</td><td align=\"center\">0.87</td><td align=\"center\">0.88 (0.40–1.90)</td><td align=\"center\">11/18</td><td align=\"center\">1.40</td><td align=\"center\">1.29 (0.56–3.00)</td></tr><tr><td align=\"left\"> *05</td><td align=\"center\">95/162</td><td align=\"center\">7/33</td><td align=\"center\">0.36</td><td align=\"center\">0.37 (0.15–0.89)</td><td align=\"center\">11/18</td><td align=\"center\">1.04</td><td align=\"center\">1.08 (0.47–2.49)</td></tr><tr><td align=\"left\">  *0501</td><td align=\"center\">71/186</td><td align=\"center\">6/34</td><td align=\"center\">0.46</td><td align=\"center\">0.44 (0.17–1.14)</td><td align=\"center\">9/20</td><td align=\"center\">1.18</td><td align=\"center\">1.17 (0.48–2.81)</td></tr><tr><td align=\"left\"> *06</td><td align=\"center\">87/170</td><td align=\"center\">16/24</td><td align=\"center\">1.30</td><td align=\"center\">1.29 (0.64–2.63)</td><td align=\"center\">14/15</td><td align=\"center\">1.82</td><td align=\"center\">1.93 (0.85–4.35)</td></tr><tr><td align=\"left\">  *0602</td><td align=\"center\">44/213</td><td align=\"center\">9/31</td><td align=\"center\">1.41</td><td align=\"center\">1.31 (0.56–3.03)</td><td align=\"center\">10/19</td><td align=\"center\">2.55</td><td align=\"center\">2.33 (0.97–5.57)</td></tr><tr><td align=\"left\">DRB1</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> *01</td><td align=\"center\">52/205</td><td align=\"center\">6/34</td><td align=\"center\">0.70</td><td align=\"center\">0.65 (0.25–1.09)</td><td align=\"center\">8/21</td><td align=\"center\">1.50</td><td align=\"center\">1.35 (0.54–3.39)</td></tr><tr><td align=\"left\">  *0102</td><td align=\"center\">29/228</td><td align=\"center\">2/38</td><td align=\"center\">0.41</td><td align=\"center\">0.36 (0.08–1.66)</td><td align=\"center\">6/23</td><td align=\"center\">2.05</td><td align=\"center\">1.70 (0.60–4.82)</td></tr><tr><td align=\"left\"> *04</td><td align=\"center\">74/183</td><td align=\"center\">12/28</td><td align=\"center\">1.06</td><td align=\"center\">1.11 (0.52–2.37)</td><td align=\"center\">3/26</td><td align=\"center\">0.29</td><td align=\"center\">0.27 (0.08–0.96)</td></tr><tr><td align=\"left\"> *13</td><td align=\"center\">61/196</td><td align=\"center\">9/31</td><td align=\"center\">0.93</td><td align=\"center\">1.08 (0.47–2.47)</td><td align=\"center\">5/24</td><td align=\"center\">0.67</td><td align=\"center\">0.86(0.30–2.43)</td></tr><tr><td align=\"left\">  *1302</td><td align=\"center\">27/230</td><td align=\"center\">0/40</td><td align=\"center\">0.00</td><td/><td align=\"center\">3/26</td><td align=\"center\">0.98</td><td align=\"center\">1.32 (0.35–4.94)</td></tr><tr><td align=\"left\"> *15</td><td align=\"center\">34/223</td><td align=\"center\">10/30</td><td align=\"center\">2.19</td><td align=\"center\">2.10 (0.91–4.86)</td><td align=\"center\">9/20</td><td align=\"center\">2.95</td><td align=\"center\">2.78 (1.11–6.92)</td></tr><tr><td align=\"left\">  *1503</td><td align=\"center\">14/243</td><td align=\"center\">5/35</td><td align=\"center\">2.48</td><td align=\"center\">2.40 (0.77–7.51)</td><td align=\"center\">5/24</td><td align=\"center\">3.62</td><td align=\"center\">3.87 (1.20–12.52)</td></tr><tr><td align=\"left\"><italic>DRB1-DQB1 haplotypes</italic></td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> 0102-0501</td><td align=\"center\">29/228</td><td align=\"center\">2/38</td><td align=\"center\">0.41</td><td align=\"center\">0.36 (0.08–1.66)</td><td align=\"center\">6/23</td><td align=\"center\">2.05</td><td align=\"center\">1.70 (0.60–4.82)</td></tr><tr><td align=\"left\"> 15-0602</td><td align=\"center\">33/224</td><td align=\"center\">8/32</td><td align=\"center\">1.70</td><td align=\"center\">1.67 (0.68–4.07)</td><td align=\"center\">9/20</td><td align=\"center\">3.06</td><td align=\"center\">2.86 (1.14–7.16)</td></tr><tr><td align=\"left\"> 1503-0602</td><td align=\"center\">14/243</td><td align=\"center\">5/35</td><td align=\"center\">2.48</td><td align=\"center\">2.40 (0.77–7.51)</td><td align=\"center\">5/24</td><td align=\"center\">3.62</td><td align=\"center\">3.87 (1.20–12.52)</td></tr><tr><td align=\"left\"> 08041-0301</td><td align=\"center\">5/252</td><td align=\"center\">0/40</td><td/><td/><td align=\"center\">3/26</td><td align=\"center\">5.82</td><td align=\"center\">4.10 (0.68–24.81)</td></tr><tr><td align=\"left\"> 09012-0201/02</td><td align=\"center\">3/254</td><td align=\"center\">1/39</td><td align=\"center\">2.18</td><td align=\"center\">2.37 (0.22–25.12)</td><td align=\"center\">2/27</td><td align=\"center\">6.27</td><td align=\"center\">9.36 (1.38–63.25)</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>a) -: Residue identical to the E-P;</p><p>b) Percentages are shown only for variant branches and for the most common variant groups;</p><p>c) The total number of HPV-16 variants exceeds 107 because we included cases with infection by more than one variant;</p><p>d) Co-infections with other types excluded.</p></table-wrap-foot>", "<table-wrap-foot><p>a) C/N: Carriers/Non carriers;</p><p>b) OR: Odds Ratio;</p><p>c) CI: Confidence Interval;</p><p>d) Adjusted for age and ethnic group.</p></table-wrap-foot>" ]

[]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p><italic>Anopheles gambiae </italic>sensu stricto (s.s.) is the most important vector of human malaria in Africa, causing 90% of the fatalcases worldwide [##REF##15331814##1##]. It is believed that the differentiation of this very synanthropic and anthropophilic species within the <italic>A. gambiae </italic>complex is very recent, having taken place a few thousand years ago, as a result of expansion of human activities, which provided mosquitoes with new opportunities for breeding, eventually creating a worsening in malaria transmission in sub-Saharan Africa [##REF##10697869##2##].</p>", "<p>Chromosomal and molecular evidence from West Africa suggests that <italic>A. gambiae </italic>s.s. is currently undergoing incipient speciation leading to a segregation by reproductive isolation of (at least) two \"molecular forms\" provisionally named M and S [##REF##11240632##3##, ####REF##12364623##4##, ##REF##15894192##5##, ##REF##17257119##6####17257119##6##]. These forms have a largely overlapping range west of the Great Rift Valley, although their relative frequencies are very different on a micro-geographic scale, probably due to adaptation to differentiated larval habitats [##REF##12364784##7##, ####REF##16465741##8##, ##REF##16524787##9##, ##REF##18187801##10####18187801##10##]. Due to common background of shared ancestral polymorphisms and to the still ongoing (although limited) gene flow, M and S forms are characterized by an overall very low degree of genetic differentiation, which has been shown to be mostly restricted to three unlinked regions of their genome. Two are adjacent to the centromere of 2L and X chromosomes and the other is in a small portion of the 2R chromosome (\"genomic islands of speciation\" [##REF##16076241##11##,##REF##17636041##12##]). Although the overall picture suggests that we are observing speciation at its very early stages, the taxonomic status of <italic>A. gambiae </italic>s.s. molecular forms has not yet been established, nor has consensus been reached on whether or not they should be considered as entities on independent evolutionary trajectories, i.e. either as polymorphic components of a single species, or as emerging species. This issue is of great interest not only from an evolutionary point of view, but also because it has important implications both for malaria epidemiology and for the optimization of vector-based control strategies.</p>", "<p>One major constraint to progress toward a solution of this debate is represented by difficulties in finding molecular markers with different/contrasting evolutionary dynamics, which would allow to get a better understanding of the strength of the reproductive barrier between molecular forms. In fact, so far, M and S forms are characterized by form-specific single nucleotide polymorphisms (SNPs) in the spacer regions of ribosomal DNA (rDNA) [##REF##11240633##13##, ####REF##11240634##14##, ##REF##18093002##15####18093002##15##] and their population genetics has been analysed mostly by microsatellite approach, which present important intrinsic (e.g. low differentiation between M and S and homoplasy) and technical (e.g. need of sequencing facilities) drawbacks, which have limited their exploitation [##REF##9826688##16##, ####REF##12721225##17##, ##REF##11553812##18##, ##REF##18043756##19####18043756##19##].</p>", "<p>Recently, the analysis of the insertion patterns of transposable elements (TEs) (i.e. mobile genetic units capable of replicating and spreading in the host genome) has been successfully applied to support genetic differentiation between <italic>A. gambiae </italic>molecular forms [##REF##15894192##5##,##REF##16033429##20##, ####REF##17217356##21##, ##REF##18414665##22####18414665##22##]. Among TEs, Short INterspersed Elements (SINEs) have been extensively used as phylogenetic and population genetic markers in primate taxa [##REF##11988762##23##] and, preliminary, in <italic>A. gambiae </italic>[##REF##15894192##5##,##REF##16033429##20##]. SINEs are 100–500 bp long non-autonomous retrotransposons occurring in large copy numbers in eukaryotic genomes [##UREF##0##24##, ####REF##8668192##25##, ##REF##12368238##26##, ##REF##16093701##27####16093701##27##], that need to recruit enzymes encoded by Long INterspersed Elements (LINEs) to mobilize after transcription via RNA polymerase III [##REF##12419252##28##,##REF##12897783##29##]. They present unique features absent in most other TEs, which make them particularly useful for phylogenetic and population genetic studies: i) they can be considered 'homoplasy-free characters' because the chance of independent insertions/excisions into/from the same site is remote; therefore, the ancestral state is represented by the absence of the element at a locus and shared insertions at that locus are identical by descent [##REF##11988762##23##,##REF##10655034##30##]; ii) since they are short, they can be amplified even from low-quality genomic DNA and insertion polymorphisms at individual genomic locations can be easily and rapidly assayed by PCR [##REF##17181718##31##]; iii) polymorphic SINEs are believed to be recently inserted and, thus, can help illuminate recent evolutionary events and resolve complexities in the population genetics structure [##REF##10655034##30##, ####REF##17181718##31##, ##REF##10468541##32##, ##REF##12116442##33##, ##REF##16701320##34####16701320##34##].</p>", "<p><italic>SINE200 </italic>is a ~200 bp element that is highly repetitive (&gt;3,000 copies) and widespread in the <italic>A. gambiae </italic>s.s. genome [##REF##12364791##35##]. Here we report the structure of this element and the results of a large scale analysis aimed to highlight different patterns of <italic>SINE200 </italic>insertion polymorphism between <italic>A. gambiae </italic>molecular forms at loci inside the speciation islands and propose the exploitation of these elements as novel molecular markers for the identification and/or population genetic analysis of M and S forms.</p>" ]

[ "<title>Materials and methods</title>", "<title><italic>Anopheles gambiae </italic>samples</title>", "<p>The study was carried out on <italic>A. gambiae </italic>s.s. M- and S-form adults collected between 1998 and 2006 in 11 African Countries (Figure ##FIG##0##1##, Table ##TAB##0##1##). Ten specimens of other species of <italic>A. gambiae </italic>complex, i.e. <italic>A. arabiensis </italic>from Senegal and Zimbabwe [##REF##15894192##5##,##REF##18498608##36##], <italic>A. melas </italic>from Angola [##REF##18187801##10##] and <italic>A. quadriannulatus </italic>A from Zimbabwe [##REF##18498608##36##] were also analysed.</p>", "<p>A cross between females of the GA-CAM (a M-form colony originated from field gravid females collected in Cameroon) and males of the GA-BF-5.7 colonies (a S-form colony originated from a single field gravid female collected in Burkina Faso) was performed and parental individuals and F1 hybrid females were analysed.</p>", "<title>Construction of <italic>SINE200 </italic>consensus sequence and copy number determination</title>", "<p><italic>SINE200 </italic>was first reported as part of the <italic>A. gambiae </italic>genome annotation [##REF##12364791##35##]. Ninety-two <italic>SINE200 </italic>copies, which are 150 bp or longer, were randomly selected from the PEST genome (version P3, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.vectorbase.org\"/>). Alignment was performed using ClustalX with gap open penalty = 10, gap extension penalty = 0.05 [##REF##9396791##37##]. The alignment was used as input for the program Consensus <ext-link ext-link-type=\"uri\" xlink:href=\"http://coot.embl.de/Alignment//consensus.html\"/> and a <italic>SINE200 </italic>consensus sequence was created using majority rule. At three positions, where there was no simple majority base, manual inspection allowed us to assign ambiguous bases (e.g., W for A or T). The <italic>A. gambiae </italic>genome database was then searched by BLAST using the above mentioned consensus as a query and the e-value cutoff was set at e-10. BLAST hits shorter than 150 bp were not counted.</p>", "<title>Analysis of <italic>SINE200 </italic>insertion polymorphisms</title>", "<p>Genomic DNA was extracted with various standard procedures, and specimens were identified to species and molecular forms by PCR-RFLP [##REF##12510902##38##,##REF##15210999##39##]. <italic>SINE200 </italic>elements were located <italic>in silico </italic>by BLASTN searches on the genome sequence of the <italic>A. gambiae </italic>PEST genome using the obtained <italic>SINE200 </italic>consensus sequence as a query. Thirteen <italic>SINE200 </italic>insertions lying within the <italic>A. gambiae </italic>molecular form speciation islands (<italic>sensu </italic>Turner [##REF##16076241##11##]) on X, 2L and 2R chromosomes, and characterized by the presence of 500 bp flanking regions showing a single hit in the genome, were selected. Primers were designed to amplify across the element using Primer 3 software [##REF##10547847##40##]. The selected loci were named '<italic>S200' </italic>followed by the abbreviation of the chromosomal arm (2L, 2R, X), by a number/letter corresponding to the chromosomal location on the cytogenetic map [##REF##12364623##4##] and by an additional number aimed to distinguish primer sets positioned on the same chromosome division. Genes annotated within a 20 Kb genome sequence including <italic>SINE200 </italic>insertions for each locus were retrieved from the PEST genome ver. Agam P3 Feb. 2006 (Table ##TAB##1##2##).</p>", "<p>PCR reactions were carried out in a 25 μl reaction which contained 1 pmol of each primer, 0.2 mM of each dNTP, 1.5 mM MgCl2, 2.5 U Taq polymerase, and 0.5 μl of template DNA extracted from a single mosquito. Thermocycler conditions were 94°C for 10 min followed by thirty-five cycles of 94°C for 30 s, 54°C for 30 s and 72°C for 1 min., with a final elongation at 72°C for 10 min, and a 4°C hold. The resulting products were analysed on 1.5% agarose gels stained with ethidium bromide, with low and high molecular weight bands corresponding to fragments containing or lacking the targeted <italic>SINE200</italic>, respectively.</p>", "<p>PCR products representing 'filled' and 'empty' sites of <italic>S200 </italic>X6.1 locus on X chromosome were sequenced on both strands using ABI Big Dye Terminator v.2 chemistry and an ABI Prism 3700 DNA Analyser. Multiple alignments were performed using ClustalX [##REF##9396791##37##]. All sequences were deposited in GenBank under accession numbers <ext-link ext-link-type=\"gen\" xlink:href=\"EU881868\">EU881868</ext-link>–<ext-link ext-link-type=\"gen\" xlink:href=\"EU881887\">EU881887</ext-link>.</p>", "<p>Indices of polymorphism (i.e. <italic>SINE200 </italic>insertion frequency and heterozygosity) and differentiation (<italic>Fst</italic>) at polymorphic loci were computed using <italic>Fstat </italic>2.9.3.2 [##UREF##1##41##]. Significance was tested with Bonferroni-adjusted <italic>P</italic>-values, using the randomization approach implemented in <italic>Fstat</italic>.</p>" ]

[ "<title>Results</title>", "<title>Structural features and chromosomal density of <italic>SINE200 </italic>in the <italic>A. gambiae </italic>genome</title>", "<p><italic>SINE200 </italic>is a previously discovered <italic>SINE </italic>family of the <italic>A. gambiae </italic>genome [##REF##12364791##35##]. Here we further characterized <italic>SINE200 </italic>by constructing a consensus sequence on the basis of 92 <italic>SINE200 </italic>copies that are 150 bp or longer, which is a small sample of all <italic>SINE200 </italic>copies (Figure ##FIG##1##2##). Analysis of the consensus sequence suggests that <italic>SINE200 </italic>has a typical structure, with a tRNA-related sequence at its 5' end, a conserved tRNA-unrelated sequence, and a simple repeat at its 3' end. Approximately 70 bp of the 5' end of the <italic>SINE200 </italic>consensus is 94% identical to the 5' end of a tRNA-Pseudo gene (AGAP000459). Sequences similar to the conserved A and B motifs for the polymerase III promoter were also found. Using the consensus sequence as a query, we showed that there are approximately 3,200 ubiquitous copies of <italic>SINE200 </italic>that are 150 bp or longer, and their density along the five chromosome arms ranges from 9.9 copies per Mbp (2R) to 12.9 copies per Mbp (X) (y##TAB##2##3##).</p>", "<title>Analysis of <italic>SINE200 </italic>insertion polymorphism</title>", "<p>The approach utilized was to design specific primers pair in the flanking regions of <italic>SINE200 </italic>insertions within M and S <italic>A. gambiae </italic>speciation islands, where a higher degree of form-specific genetic differentiation was expected. Although <italic>SINE200 </italic>are present in several copies also in the target regions, the selection of the loci has been more complicated than expected, mainly due to abundance of repetitive sequences in heterochromatic regions in centromeric areas of <italic>A. gambiae </italic>genome [##REF##12364791##35##]. Eventually, 13 primer pairs were initially designed. Among these, 5 did not successfully amplified the targeted <italic>SINE </italic>insertions, as they did not yield bands or provided aspecific PCR products, and the analysis was therefore focused on the remaining 8 loci. Table ##TAB##1##2## reports chromosomal location and annotated genes retrieved in the neighbouring genome areas of the 8 successfully amplified <italic>SINE </italic>loci. Each of these loci was initially scored for <italic>SINE200 </italic>insertion polymorphism by PCR-amplifying 15 M-form and 15 S-form specimens from either Burkina Faso and Cameroon and 15 S-form from Mali. <italic>SINE200 </italic>element insertions were found fixed in both forms in all five loci on the 2L speciation island, polymorphic in two loci positioned on 2R (i.e. <italic>S200 </italic>2R12D) and X (i.e. <italic>S200 </italic>X6.1) chromosomes, respectively, whereas a second <italic>SINE200 </italic>on centromeric area of X chromosome (<italic>S200 </italic>X6.2) was absent in all individuals analysed. <italic>SINE200 </italic>insertions were absent in all eight loci in the other analysed species of the <italic>A. gambiae </italic>complex (i.e. <italic>A. arabiensis</italic>, <italic>A. melas </italic>and <italic>A. quadriannulatus </italic>A).</p>", "<p>The two polymorphic loci positioned on X and 2R chromosomes, were further studied by analysing additional 111 M-form and 200 S-form specimens (Table ##TAB##0##1##). In the case of <italic>S200 </italic>2R12D locus, all S-form specimens resulted homozygotes for the insertion, except for few individuals from Mali (allele frequency [AF] = 0.97) and Senegal (AF = 0.98), while intermediate levels of polymorphisms were shown in M-form (AF = 0.38–0.53), resulting in an overall high degree of genetic differentiation between molecular forms (<italic>F</italic>st = 0.46 P &lt; 0.001). Moreover, preliminary results show intra-form differentiation between west (i.e. Burkina Faso, Nigeria and Benin) and west-central (i.e. Cameroon and Angola) M-subsamples (Fst = 0.46 P &lt; 0.001), while no significant variation was found within each subsample. On the other hand, no intra-form differentiation at the same locus was recorded in the S-form sample within the same range of distribution.</p>", "<p>Remarkable differences among molecular forms were found at locus <italic>S200 </italic>X6.1 (Table ##TAB##0##1##): in all samples the insertion was fixed in M-form individuals, from which a single PCR product of 479 bp was amplified, and absent in S-form specimens, from which a 249 bp product was obtained (Figure ##FIG##2##3##). As expected, laboratory-reared specimens of both molecular forms analysed (N = 60) showed the same pattern of insertion at <italic>S200 </italic>X6.1 locus. Moreover, the analysis of M/S hybrids resulting from laboratory crosses produced consistent results, yielding both PCR-bands from all hybrid M/S specimens analysed (N = 15) (Figure ##FIG##2##3##). The absence of <italic>SINE200 </italic>at this locus was confirmed in all the other <italic>A. gambiae </italic>s.l. member species analysed. Interestingly, the PCR product obtained from <italic>A. arabiensis </italic>was represented by a 223 bp band, due to a 26 bp deletion in the <italic>S200 </italic>X6.1 flanking region. In addition, the alignment of <italic>S200 </italic>X6.1 flanking regions sequences showed (Figure ##FIG##3##4##): i) fixed mutations at 3 positions in the alignment (positions 16, 74, 359) differentiating both <italic>A. gambiae </italic>s.s. molecular forms from <italic>A. arabiensis</italic>, <italic>A. melas </italic>and <italic>A. quadriannulatus</italic>; ii) mutations in two positions (pos. 17, 69) differentiating the M-form from all the other taxa analysed; iii) a very high conservation in the sequence of the element was found in all M individuals analysed.</p>" ]

[ "<title>Discussion</title>", "<p>The analysis of the consensus sequence of <italic>SINE200 </italic>indicates that it is a typical tRNA-related SINE element. In fact, it has a tRNA-related region at the 5' end with the A and B boxes found in polymerase III promoters. It also has a variable number of the AAG tandem repeat at the 3' end, which is also typical for tRNA-related SINEs [##REF##10368954##42##]. The middle of <italic>SINE200 </italic>is a conserved sequence that is not related to tRNA sequences, as already described for other eukaryotic <italic>SINE </italic>elements [##REF##11141194##43##].</p>", "<p>Eight <italic>SINE200 </italic>loci within <italic>A. gambiae </italic>s.s. speciation islands were analysed, as follows: i) two on the X-chromosome, one of which (i.e. <italic>S200 </italic>X6.2) was absent in all specimens tested, while the other (i.e. <italic>S200 </italic>X6.1) was fixed in the M-form and absent in the S-form samples; ii) one on 2R (i.e. <italic>S200 </italic>2R12D), which was found polymorphic in both molecular forms; and iii) five on 2L, which were all fixed in both forms. The observed high frequency of fixation of the insertions in centromeric areas probably reflects a common behaviour of transposable elements, which tend to accumulate in regions of reduced recombination [##REF##15219154##44##], as also suggested for other retrotrasposon classes in the <italic>A. gambiae </italic>genome [##REF##17217356##21##].</p>", "<p>The observed differences in the allelic frequencies at <italic>S200 </italic>2R12D locus highlight a significant reduction of gene-flow between the two molecular forms. This represents an additional evidence in support of the relevance of this small chromosomal region in the speciation process ongoing within <italic>A. gambiae </italic>s.s., as proposed by Turner <italic>et al </italic>[##REF##16076241##11##]. Interestingly, <italic>S200 </italic>2R12D lies in close proximity (about 20 Kb) to an odour receptor gene (i.e. GPR-OR38), which has been suggested to be likely related to reproductive isolation between molecular forms [##REF##17636041##12##]. Moreover, a similar level of differentiation was observed within M-form, suggesting a subdivision between western and western-central M-populations (Figure ##FIG##0##1##). This sub-structuring observed within the M-form is consistent with recent evidence from a wide microsatellite analysis carried out on the same M-form populations [##UREF##2##45##] and with previous observations by Slotman <italic>et al </italic>[##REF##17257119##6##], who suggests that M populations from Mali and Cameroon may no longer be considered a \"single entity\". It should be noted, however, that <italic>S200 </italic>2R12D locus lies within 2Rb chromosomal inversion, which is shared by M and S forms and shows different frequencies in various eco-geographic areas [##REF##12364623##4##,##REF##15894192##5##]. It is thus possible that the spread of this element in natural populations is affected by 2Rb inversion polymorphism, although preliminary data show that <italic>S200 </italic>2R12D insertion is not exclusive of one of the two alternative chromosomal arrangements (i.e. 2R+^band 2Rb). Further studies on larger karyotyped samples are ongoing to evaluate a possible association between the 2Rb inversion and the element insertion.</p>", "<p>As it is recognized that <italic>SINE</italic>s do not excide from a genome after their insertion [##REF##11988762##23##,##REF##10655034##30##] and since all <italic>SINE200 </italic>loci analysed were found to be specific of <italic>A. gambiae </italic>s.s., the analysed insertions likely occurred after divergence of this species from the other members of the <italic>A. gambiae </italic>complex. Moreover, <italic>S200 </italic>X6.1 was found to be exclusive of and highly conserved in the M-form and, therefore, probably recently integrated in its genome after divergence of molecular forms within the chromosome-X speciation island. This locus lies in proximity of CYP4G16, a gene of the cytochrome P450 family which has been indicated as a candidate gene in the incipient speciation process ongoing within <italic>A. gambiae </italic>s.s. [##REF##16076241##11##].</p>", "<p>In addition to the above cited indications in favour of a possible fruitful exploitation of <italic>SINE200 </italic>in the study of the sub-structuring of <italic>A. gambiae</italic>, the exclusive presence of <italic>S200 </italic>X6.1 in the M-form allows to propose a novel straightforward approach to distinguish <italic>A. gambiae </italic>s.s. molecular forms. In fact, all methods developed so far for their identification are based on point mutations in IGS region of rDNA, which is formed by several tandem arrays known to be subjected to concerted evolution. Thus, possible diagnostic problems, in particular in the interpretation of hybrid M/S patterns, may arise from incomplete homogenization of the arrays through concerted evolution and/or mixtures of M and S IGS-sequences among the arrays of single chromatids, due to recombination between copies on the X and Y chromosomes [##REF##18093002##15##]. The <italic>S200 </italic>X6.1 locus, on the other hand, although located only about 1 Mb from IGS-region, does not show these constraints, being present in a single copy on the X-chromosome. Moreover, it is important to highlight that PCR-RFLP [##REF##12510902##38##,##REF##15210999##39##], and IMP-PCR [##REF##11240633##13##,##REF##17177993##46##] methods currently used for M and S identification are based on the recognition of single/few mutation(s), and thus subjected to homoplasy. On the other hand, the PCR diagnostic approach here proposed is based on the specific and irreversible insertion of a 230 bp element in the M-form (and its absence in S-form), thus allowing an unambiguous, simple and straightforward recognition of M and S forms (Figure ##FIG##2##3##). It is also interesting to note that, although the S-form amplicon is identical to those of <italic>A. melas </italic>and <italic>A. quadriannulatus</italic>, the 26 bp deletion reported for <italic>A. arabiensis </italic>allows to propose the use of the novel approach to discriminate <italic>A. gambiae </italic>from <italic>A. arabiensis </italic>specimens without preliminary species identification in large areas of sub-saharan Africa where <italic>A. gambiae </italic>molecular forms and <italic>A. arabiensis </italic>are the only species of the complex present.</p>" ]

[ "<title>Conclusion</title>", "<p>The approach utilized opens new perspectives in the studies of <italic>A. gambiae </italic>molecular forms. Further analyses on <italic>SINE200 </italic>loci mapping in different areas of <italic>A. gambiae </italic>genome are ongoing based on preliminary selection by a genome-wide TE-display approach of form-specific or polymorphic loci, to eventually provide additional, new efficient co-dominant markers for the analysis of genetic differentiation between M and S-forms.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>SINEs (Short INterspersed Elements) are homoplasy-free and co-dominant genetic markers which are considered to represent useful tools for population genetic studies, and could help clarifying the speciation processes ongoing within the major malaria vector in Africa, <italic>Anopheles gambiae </italic>s.s. Here, we report the results of the analysis of the insertion polymorphism of a nearly 200 bp-long SINE (<italic>SINE200</italic>) within genome areas of high differentiation (i.e. \"speciation islands\") of M and S <italic>A. gambiae </italic>molecular forms.</p>", "<title>Methods</title>", "<p>A <italic>SINE</italic>-PCR approach was carried out on thirteen <italic>SINE200 </italic>insertions in M and S females collected along the whole range of distribution of <italic>A. gambiae </italic>s.s. in sub-Saharan Africa. Ten specimens each for <italic>Anopheles arabiensis</italic>, <italic>Anopheles melas, Anopheles quadriannulatus </italic>A and 15 M/S hybrids from laboratory crosses were also analysed.</p>", "<title>Results</title>", "<p>Eight loci were successfully amplified and were found to be specific for <italic>A. gambiae </italic>s.s.: 5 on 2L chromosome and one on X chromosome resulted monomorphic, while two loci positioned respectively on 2R (i.e. <italic>S200 </italic>2R12D) and X (i.e. <italic>S200 </italic>X6.1) chromosomes were found to be polymorphic. <italic>S200 </italic>2R12D was homozygote for the insertion in most S-form samples, while intermediate levels of polymorphism were shown in M-form, resulting in an overall high degree of genetic differentiation between molecular forms (Fst = 0.46 p &lt; 0.001) and within M-form (Fst = 0.46 p &lt; 0.001). The insertion of <italic>S200 </italic>X6.1 was found to be fixed in all M- and absent in all S-specimens. This led to develop a novel easy-to-use PCR approach to straightforwardly identify <italic>A. gambiae </italic>molecular forms. This novel approach allows to overcome the constraints associated with markers on the rDNA region commonly used for M and S identification. In fact, it is based on a single copy and irreversible <italic>SINE200 </italic>insertion and, thus, is not subjected to peculiar evolutionary patterns affecting rDNA markers, e.g. incomplete homogenization of the arrays through concerted evolution and/or mixtures of M and S IGS-sequences among the arrays of single chromatids.</p>", "<title>Conclusion</title>", "<p>The approach utilized allowed to develop new easy-to-use co-dominant markers for the analysis of genetic differentiation between M and S-forms and opens new perspectives in the study of the speciation process ongoing within <italic>A. gambiae</italic>.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>FS and EM carried out the molecular processing, participated in the analysis and interpretation of data, and in the drafting of the manuscript; YQ contributed to the molecular processing; FS collected part of the samples and to the drafting of the manuscript; ZT proposed the study and contributed to the set-up of the experimental approach, data analysis and drafting of the manuscript; AdT conceived and coordinated the study and wrote the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We are grateful to all scientists and entomology teams who provided samples utilized in this study; we especially thank K. Adasi, M. Akogbeto, T. Baldet, G. Carrara, C. Costantini, P.J. Cani, C. Curtis, I. Dia, J. Dossou-yovo, N. Elissa, F. Fortes, A. Mendjibe, YT. Touré, W. Takken, S. Torr and G. Vale for help with sample collections. We also thank JMC. Ribeiro for help with bioinformatic analyses of <italic>SINE200 </italic>and V. Petrarca and J. Pinto for useful discussion on data and manuscript. The project was funded by NIH-grant AI42121 to ZT. EM was supported by Compagnia di San Paolo (Torino, Italy) in the context of the Italian Malaria Network.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Insertion frequencies at <italic>S200 </italic>2R12D locus in <italic>Anopheles gambiae </italic>M-form and S-form samples</bold>. Numbers below the pie-charts refer to the sampling sites as listed in Table 1.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Consensus sequence of <italic>SINE200 </italic>in <italic>Anopheles gambiae </italic>s.s</bold>. <italic>SINE200 </italic>has a typical structure, with a tRNA-related sequence at its 5' end, a conserved tRNA-unrelated sequence, and simple repeats ('A' tail or tandem repeats) at its 3' end. The 5' end of the consensus (gray underlined) is 94% identical to the 5' end of a tRNA-Pseudo gene (AGAP000459). Sequences similar to the conserved A and B motifs for the polymerase III promoter are boxed. D:A/G/T; K:G/T; W: A/T.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Diagnostic PCR based on <italic>S200 </italic>X6.1 in <italic>Anopheles gambiae </italic>s.l</bold>. PCR results from locus <italic>S200 </italic>X6.1 indicating the presence (+) or absence (-) of the insertion in females of <italic>Anopheles gambiae </italic>species complex. QD = <italic>A. quadriannulatus </italic>A; ML = <italic>A. melas</italic>; AR = <italic>A. arabiensis</italic>; S = <italic>A. gambiae </italic>S-form; M = <italic>A. gambiae </italic>M-form; M/S = M/S hybrids from laboratory crosses; n.c. = negative control. Ladder = 100 bp (BIOLINE HyperLadder IV).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Sequence alignment of <italic>S200 </italic>X6.1 and flanking regions in the <italic>Anopheles gambiae </italic>s.l</bold>. Nucleotide substitutions at each position are indicated with the appropriate nucleotide. Deletions are denoted by dashes (-). The nucleotide deletion of 26 bp in the flanking region of <italic>S200 </italic>X6.1 for <italic>A. arabiensis </italic>corresponds to positions 82–107. Deletion at positions 124–353 corresponds to the absence of the <italic>S200 </italic>X6.1 element in <italic>A. gambiae </italic>S form, <italic>A. quadriannulatus </italic>A, <italic>A. arabiensis </italic>and <italic>A. melas</italic>. Target site duplications (TSDs) are underlined.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Insertion polymorphisms at loci <italic>S200 </italic>X6.1 and <italic>S200 </italic>2R12D in <italic>Anopheles gambiae </italic>molecular forms. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\"><bold>Country</bold></td><td align=\"left\"><bold>Site</bold></td><td align=\"left\"><bold>Form</bold></td><td align=\"left\"><bold>N</bold></td><td align=\"left\" colspan=\"2\"><bold><italic>S200 </italic>X6.1</bold></td><td align=\"left\" colspan=\"2\"><bold><italic>S200 </italic>2R12D</bold></td></tr><tr><td/><td/><td/><td/><td/><td colspan=\"4\"><hr/></td></tr><tr><td/><td/><td/><td/><td/><td align=\"left\"><bold>H</bold></td><td align=\"left\"><bold>AF</bold></td><td align=\"left\"><bold>H</bold></td><td align=\"left\"><bold>AF</bold></td></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">The Gambia</td><td align=\"left\">Maccarthy Island</td><td align=\"left\">M</td><td align=\"left\">15</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.40</td><td align=\"left\">0.53</td></tr><tr><td align=\"left\">2</td><td align=\"left\">Senegal</td><td align=\"left\">Kedougou</td><td align=\"left\">S</td><td align=\"left\">19</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.05</td><td align=\"left\">0.97</td></tr><tr><td align=\"left\">3</td><td align=\"left\">Mali</td><td align=\"left\">Banambani</td><td align=\"left\">S</td><td align=\"left\">32</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.98</td></tr><tr><td/><td/><td/><td align=\"left\">M</td><td align=\"left\">3</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.33</td><td align=\"left\">0.50</td></tr><tr><td align=\"left\">4</td><td align=\"left\">Ghana</td><td align=\"left\">Accra area</td><td align=\"left\">S</td><td align=\"left\">28</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td align=\"left\">5</td><td align=\"left\">Burkina Faso</td><td align=\"left\">Bobo Dioulasso</td><td align=\"left\">S</td><td align=\"left\">27</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td/><td/><td/><td align=\"left\">M</td><td align=\"left\">30</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.33</td><td align=\"left\">0.53</td></tr><tr><td align=\"left\">6</td><td align=\"left\">Ivory Coast</td><td align=\"left\">Buakè area</td><td align=\"left\">S</td><td align=\"left\">20</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td align=\"left\">7</td><td align=\"left\">Benin</td><td align=\"left\">Dassa area</td><td align=\"left\">M</td><td align=\"left\">33</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.24</td><td align=\"left\">0.41</td></tr><tr><td align=\"left\">8</td><td align=\"left\">Nigeria</td><td align=\"left\">Kobape, Olugbo</td><td align=\"left\">S</td><td align=\"left\">20</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td/><td/><td/><td align=\"left\">M</td><td align=\"left\">14</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.21</td><td align=\"left\">0.39</td></tr><tr><td align=\"left\">9</td><td align=\"left\">Cameroon</td><td align=\"left\">Mangoum</td><td align=\"left\">S</td><td align=\"left\">30</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td/><td/><td align=\"left\">Kribi</td><td align=\"left\">M</td><td align=\"left\">30</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td align=\"left\">10</td><td align=\"left\">Angola</td><td align=\"left\">Cabinda</td><td align=\"left\">S</td><td align=\"left\">43</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td/><td/><td align=\"left\">Luanda area</td><td align=\"left\">M</td><td align=\"left\">16</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr><tr><td align=\"left\">11</td><td align=\"left\">Tanzania</td><td align=\"left\">Nyakariro, Kwagole</td><td align=\"left\">S</td><td align=\"left\">26</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">0.00</td><td align=\"left\">1.00</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p><italic>SINE200 </italic>primer list. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Locus</bold></td><td align=\"left\"><bold><italic>SINE200 </italic>coordinate</bold></td><td align=\"left\"><bold>Primer pair (forward/reverse)</bold></td><td align=\"center\"><bold>Product size (bp)</bold></td><td align=\"left\"><bold>Annotated genes (in 20 Kb)</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold><italic>S200 </italic>X6.1</bold></td><td align=\"left\">Chromosome X:</td><td align=\"left\">5'-TCGCCTTAGACCTTGCGTTA-3'</td><td align=\"center\">479</td><td align=\"left\">AGAP001076</td></tr><tr><td/><td align=\"left\">22951445–22951671</td><td align=\"left\">5'-CGCTTCAAGAATTCGAGATAC-3'</td><td/><td align=\"left\">(CYP4G16 gene)</td></tr><tr><td align=\"left\"><bold><italic>S200 </italic>X6.2</bold></td><td align=\"left\">Chromosome X:</td><td align=\"left\">5'-TCGGGCCAATATAACACAC-3'</td><td align=\"center\">588</td><td align=\"left\">AGAP001094</td></tr><tr><td/><td align=\"left\">24225524–24225731</td><td align=\"left\">5'-AGGCGCCATGTACGTAACC-3'</td><td/><td/></tr><tr><td align=\"left\"><bold><italic>S200 </italic>2L20A.1</bold></td><td align=\"left\">Chromosome 2L:</td><td align=\"left\">5'-TGCCCTGTTCAAGATTTCAT-3'</td><td align=\"center\">564</td><td align=\"left\">none</td></tr><tr><td/><td align=\"left\">641051–641259</td><td align=\"left\">5'-GGTCACTCACGCATACCGTCT-3'</td><td/><td/></tr><tr><td align=\"left\"><bold><italic>S200 </italic>2L20A.2</bold></td><td align=\"left\">Chromosome 2L:</td><td align=\"left\">5'-ACGCCAGACGGTTTCATATC-3'</td><td align=\"center\">611</td><td align=\"left\">none</td></tr><tr><td/><td align=\"left\">977287–977497</td><td align=\"left\">5'-CCTATCTTTAATTTATATTCGC-3'</td><td/><td/></tr><tr><td align=\"left\"><bold><italic>S200 </italic>2L20B.1</bold></td><td align=\"left\">Chromosome 2L:</td><td align=\"left\">5'-AACCTTACAATACACAAGAAC-3'</td><td align=\"center\">495</td><td align=\"left\">AGAP004725</td></tr><tr><td/><td align=\"left\">2796669–2796889</td><td align=\"left\">5'-CAGGAAAACGACTACTCGAAC-3'</td><td/><td align=\"left\">AGAP004726</td></tr><tr><td align=\"left\"><bold><italic>S200 </italic>2L20B.2</bold></td><td align=\"left\">Chromosome 2L:</td><td align=\"left\">5'-CGCGTTGATTAATAATCCCAC-3'</td><td align=\"center\">483</td><td align=\"left\">none</td></tr><tr><td/><td align=\"left\">1191908–1192118</td><td align=\"left\">5'-CCAGTCTCTGGACATGCTG-3'</td><td/><td/></tr><tr><td align=\"left\"><bold><italic>S200 </italic>2L20B.3</bold></td><td align=\"left\">Chromosome 2L:</td><td align=\"left\">5'-TTATCTGCGCGTGAGTGG-3'</td><td align=\"center\">515</td><td align=\"left\">Intron of AGAP004691</td></tr><tr><td/><td align=\"left\">1276754–1276921</td><td align=\"left\">5'-ATACCGCCTAAACGCATG-3'</td><td/><td align=\"left\">(LIM gene)</td></tr><tr><td align=\"left\"><bold><italic>S200 </italic>2R12D</bold></td><td align=\"left\">Chromosome 2R:</td><td align=\"left\">5'-AGAATGAATTGTATGGAACAGG-3'</td><td align=\"center\">535</td><td align=\"left\">AGAP002640</td></tr><tr><td/><td align=\"left\">24868905–24869106</td><td align=\"left\">5'-CTATTAAATGTGTCTCGCTCG-3'</td><td/><td align=\"left\">(GPR-OR38 gene)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p><italic>SINE200 </italic>copy number and density on different chromosomes in <italic>Anopheles gambiae </italic>s.s. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Chromosome Arm</bold></td><td align=\"center\"><bold>Length (Mbp)</bold></td><td align=\"center\"><bold><italic>SINE200 </italic>Copy No.</bold></td><td align=\"center\"><bold>SINE200 Density (per Mbp)</bold></td></tr></thead><tbody><tr><td align=\"left\">X</td><td align=\"center\">24,393</td><td align=\"center\">314</td><td align=\"center\">12,9</td></tr><tr><td align=\"left\">2L</td><td align=\"center\">49,364</td><td align=\"center\">520</td><td align=\"center\">10,5</td></tr><tr><td align=\"left\">2R</td><td align=\"center\">61,545</td><td align=\"center\">610</td><td align=\"center\">9,9</td></tr><tr><td align=\"left\">3L</td><td align=\"center\">41,963</td><td align=\"center\">529</td><td align=\"center\">12,6</td></tr><tr><td align=\"left\">3R</td><td align=\"center\">53,201</td><td align=\"center\">626</td><td align=\"center\">11,8</td></tr><tr><td align=\"left\">UNKNOWN</td><td align=\"center\">ND</td><td align=\"center\">615</td><td align=\"center\">ND</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Sampling sites, number of specimens of <italic>A. gambiae </italic>molecular form analysed (N), heterozygosity (H) and allele frequency (AF). Sampling sites are listed from west to east and numbered as in Figure 1 (for information on the samples and sampling sites see della Torre <italic>et al </italic>[##REF##15894192##5##]).</p></table-wrap-foot>", "<table-wrap-foot><p><italic>SINE200 </italic>locus names, chromosomal locations and coordinates, PCR primers, 'filled' PCR product sizes and annotated genes within 20 Kb including the <italic>SINE200 </italic>loci investigated are indicated by Ensemble Gene ID, gene names are in brackets.</p></table-wrap-foot>", "<table-wrap-foot><p>Copy number was determined by BLAST analysis using <italic>SINE200 </italic>consensus as query. The e-value cutoff is e-10. Only copies &gt;150 bp are counted. ND = not determined.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1475-2875-7-163-1\"/>", "<graphic xlink:href=\"1475-2875-7-163-2\"/>", "<graphic xlink:href=\"1475-2875-7-163-3\"/>", "<graphic xlink:href=\"1475-2875-7-163-4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p><italic>Plasmodium vivax </italic>has the widest geographic range of the four parasites responsible for malaria in man. Historically, its range has extended as far north as Finland and northern China, and as far south as northern Australia and South Africa [##REF##12364370##1##]. Concerted malaria control initiatives in countries in temperate zones have today confined <italic>P. vivax </italic>mainly to the tropics, where its range overlaps that of the most important malaria parasite in terms of public health, <italic>Plasmodium falciparum</italic>. Thus, the two parasites co-exist in large parts of the tropical and semi-tropical world, except, strikingly, in large parts of western and central Africa, where <italic>P. vivax </italic>appears to be almost completely absent [##REF##16798089##2##]. This situation is apparently caused by the high prevalence of the Duffy negative phenotype in the local populations, which confers complete protection against <italic>P. vivax </italic>malaria [##REF##778616##3##]. The Duffy antigen/receptor for chemokines (DARC) is a transmembrane glycoprotein that is present on epithelial cells [##REF##9058825##4##], endothelial cells [##REF##8083383##5##], and erythrocytes. It is utilized by <italic>P. vivax </italic>parasites as the receptor for attachment to the red cell surface [##REF##1145213##6##]. Duffy negative individuals are homozygous for a DARC allele, <italic>FY*B</italic>^{<italic>null</italic>}, which carries a single nucleotide mutation which impairs promoter activity by disrupting a binding site for the h-GATA-1 erythroid transcription factor [##REF##7663520##7##]. This results in the loss of DARC expression on erythrocytes, but does not affect expression in epithelial or endothelial cells. Individuals who are homozygous for this allele thus express no DARC protein on the red cell surface and are completely protected from the erythrocytic cycle of <italic>P. vivax</italic>. The Duffy negative phenotype occurs in over 95% of the population of west and central Africa, but is extremely rare outside Africa and the Arabian peninsula [##UREF##0##8##].</p>", "<title>Present day prevalence of <italic>P. vivax </italic>in Africa</title>", "<p>Although <italic>P. vivax </italic>is known to be present in parts of northern, eastern and southern Africa, with some areas reporting a prevalence of around 20% of all malaria infections [##REF##11425182##9##], it is extremely rare in west and central Africa. In fact, there are very few cases of <italic>P. vivax </italic>in the indigenous population at all, with the exception of the island of Sao Tome, which is known to harbour all four human malaria parasites [##REF##9698266##10##]. It is possible that the lack of \"local\" <italic>P. vivax </italic>reported from these areas is due to the fact that its perceived absence precludes its identification. So ingrained may be the notion of the absence of <italic>P. vivax </italic>from west and central Africa that many surveys of parasite species composition from these areas do not include assays for the identification of the parasite [##REF##16094461##11##], and many microscopists automatically designate any parasite associated with Schüffner's dotted erythrocytes as <italic>P. ovale </italic>[##UREF##1##12##]. There are, however, sporadic reports of its presence. One report from Equatorial Guinea describes the discovery of four cases of <italic>P. vivax </italic>in children of mixed race parentage [##REF##10072133##13##], and another describes a mild infection of <italic>P. vivax </italic>in a Duffy negative woman from the Democratic Republic of Congo [##REF##3907539##14##]. These rare accounts are supported by more extensive reports detailing <italic>P. vivax </italic>infections in non-African travellers returning from these areas. For example, an analysis of 618 imported <italic>P. vivax </italic>cases diagnosed in European clinics between 1999 and 2003, found that 17% of travellers had contracted the parasite in west and central Africa [##REF##15003128##15##]. Furthermore, between 1995 and 1998 there were 73 reports of <italic>P. vivax </italic>imported into France from this region [##REF##11230828##16##]. Imported malaria surveys from the USA report a similar pattern, with data from 2004 revealing that 65% of <italic>P. vivax </italic>imported into the USA from Africa in that year (n = 67) originated in countries in west and central regions [##UREF##2##17##]. As some of these reports [##REF##15003128##15##,##UREF##2##17##] rely on microscopy for identification of parasite species, it may be argued that confusion between <italic>P. ovale </italic>and <italic>P. vivax </italic>may lead to a degree of misdiagnosis. However, there are an increasing number of reports that identify parasite species with molecular techniques [##REF##11230828##16##,##REF##16014856##18##], which are much less prone to misidentification of species. Given these data, it seems certain that transmission of <italic>P. vivax </italic>does occur in west and central Africa. However, it remains unclear how transmission is maintained in populations where the Duffy negative phenotype is almost at fixation.</p>", "<p>In 1985, Van Ros described the presence of <italic>P. vivax </italic>in a Duffy negative individual [##REF##3907539##14##] from the Democratic Republic of Congo. Recently, two new reports have also described this intriguing situation. One, from western Kenya, describes the presence of <italic>P. vivax </italic>circumsporozoite protein in 0.65% of mosquitoes from an area of high Duffy negativity [##REF##17038676##19##]. More recently, Cavasini <italic>et al </italic>[##UREF##3##20##] reported clear evidence of <italic>P. vivax </italic>infections in two Duffy negative individuals in Brazil. It has been proposed that the parasite may be in the process of evolving mechanisms which allow the infection of Duffy negative individuals [##REF##17360237##21##]. Such findings highlight the need for a clear investigation of the prevalence and population dynamics of <italic>P. vivax </italic>in west and central Africa, using accurate molecular species typing methods.</p>", "<p>In order to assess the current prevalence of <italic>P. vivax </italic>in west and central Africa, PCR species typing of 2,588 samples from nine different countries throughout the continent was carried out.</p>" ]

[ "<title>Methods</title>", "<title>Blood sample collection and parasite DNA extraction</title>", "<p>A total of 2,588 blood samples collated from various surveys undertaken in nine African countries (Figure ##FIG##0##1##) between 1998 and 2006 were analysed by PCR for the presence of each of the four human malaria parasites, <italic>P. falciparum</italic>, <italic>P. vivax</italic>, <italic>P. malariae </italic>and <italic>P. ovale</italic>. The original sample collections were predominantly carried out as part of unrelated investigations and the methodology of individual collection varies. Table ##TAB##0##1## outlines the details of these collections. In all cases, ethical clearance for sampling was obtained from the relevant ethical committees (for samples collected specifically for this study, details are given in the following paragraphs).</p>", "<title>Samples from Burkina Faso</title>", "<p>In 2002, samples were collected from asymptomatic children under 10 years old by Active Case Detection (ACD) in two villages (Bassy and Zanga) 60 Km east of Ouagadougou, the capital of Burkina Faso at the end of the transmission season [##REF##16420718##22##]. DNA was extracted by the use of TRIZOL^®reagent [##REF##16420718##22##]. 108 <italic>P. falciparum </italic>positive samples (by PCR), were used in this study.</p>", "<title>Samples from Angola, Mozambique, Rwanda, and the Democratic Republic of Sao Tome &amp; Principe (DRSTP)</title>", "<p>Blood samples were collected by Passive Case Detection (PCD) at clinics in the following countries: DRSTP, February 2004, at the Centro Policlínico de Saúde de Água Grande, São Tomé (all ages)[##REF##16420686##23##]; Angola, 2003–2004 at the Hospital Pediatrico de Luanda (1–5 year olds)[##REF##16597338##24##]; Mozambique from July to October 2004 at the Hospital Central de Maputo (1–5 year olds)[##REF##17378942##25##]; Rwanda, November to December 2003, at the Rukara Health Centre (1–60 years old)[##REF##16337665##26##]. Only samples identified by thick and thin smear microscopy as <italic>P. falciparum </italic>single species infections were available for analysis. Blood samples were spotted onto Whatman^®n°4 (n°3 in the case of Rwanda) filter paper and parasite genomic DNA was obtained by boiling in Chelex-100 [##REF##9893748##27##] and subsequent ethanol precipitation.</p>", "<title>Samples from Gabon</title>", "<p>206 samples were collected specifically for this study. Samples were collected in and around Lambarene, Departement du Moyen Ogooué at five different locations (Hôpital Albert Schweitzer, Hôpital General de Lambaréné, Dispensaire d'Isaac, Adouma and PK48, a village 48 kilometres from Lambaréné). 100–200 μl of venous blood was applied to Whatman^®FTA^®Classic Filter paper cards (Whatman^®, USA) and left to air dry. Whatman^®FTA^®filter cards deactivate viral DNA/RNA and preserve human and parasite DNA for downstream analyses. DNA extractions were carried out according to the manufacturer's instructions. Briefly, a disc of 1.2 mm in diameter was punched from the centre of each dried blood spotted card and washed three times with Whatman^®FTA^®Purification Reagent, and twice with TE buffer. This treated disc was then used directly in subsequent PCR analyses. Ethical clearance for sampling in Gabon was obtained from the ethical committee of the International Foundation of the Albert-Schweitzer Hospital and Edinburgh University. Prior to sampling each patient was informed about the study, consent was obtained (in the case of children parents/guardians gave informed consent) and medical follow-up was provided if needed.</p>", "<title>Samples from the Republic of Congo</title>", "<p>359 samples were collected by passive case detection from two health centres (Madibou and Tenrikyo) within Brazzaville, the capital of the Republic of Congo, in 2005. No age restrictions were applied to sampled individuals. These samples were collected on Whatman^®FTA^®filter paper, and processed as previously described. A further 492 samples were collected in 2006 by PCD from three separate locations within the Republic of Congo, 150 from Pointe-Noire, on the west coast of the country, a further 201 from the Tenrikyo health centre in Brazzaville, and 141 from Gamboma, a town in the east. These samples were collected on Whatman^®31ETCHR filter paper, and DNA extraction was performed using the EZ1 BioRobot™ (QIAGEN, Hilden, Germany) according to the manufacturer's instructions. Ethical approval for this collection was obtained from the ethical committee at Osaka University, and sampling was authorized by the administrative authority of the Ministry for Research and Ministry for Health in the Republic of Congo. Informed consent was obtained from individual patients, and antimalarial treatment was provided when appropriate.</p>", "<title>Samples from Kenya</title>", "<p>722 samples were collected in 1998 by active case detection in the Kisii district of Kenya. All age groups were sampled. Blood was collected by finger-prick on Whatman^®31ETCHR filter paper, and DNA extracted by boiling in Chelex-100 [##REF##9893748##27##] and subsequent ethanol precipitation. Ethical clearance for this collection was obtained from the Ministries of Health and Education in Kenya.</p>", "<title>Samples from Ghana</title>", "<p>352 samples were collected by ACD from 0–15 year old children in four villages near Winneba, a western coastal region of the country. Finger-prick blood was collected on Whatman^®31ETCHR filter paper, and DNA extraction was performed using the EZ1 BioRobot™. This study was approved by the Ministry of Health/Ghana Health Service.</p>", "<title>Species typing PCR</title>", "<p>DNA extracted from all samples was subjected to <italic>Plasmodium </italic>species typing PCR based on the nested PCR technique developed by Snounou <italic>et al </italic>[##REF##8264734##28##] with some modifications. Oligonucleotide primers were identical to those previously described [##REF##8264734##28##] but the PCR conditions were modified as follows: For the first round of PCR, 1 μl of extracted DNA was added to 14.85 μl of dH₂0, 1.75 μl of each primer (rPLU5 and rPLU6 at 5 uM), 2.5 μl of AmpliTaq Gold^®10× PCR Buffer II, 2 μl of 25 mM MgCl₂solution, 1 μl of dNTP mixture (2.5 mM each) and 0.15 μl of AmpliTaq Gold^®in a 25 μl reaction. The following cycling conditions were applied using a GeneAmp^®PCR 9700 thermocycler (Applied Biosystems, USA): 95°C for 10 min, 30 cycles of 57°C for 1 min, 72°C for 1 min, 94°C for 1 min and a final extension step of 72°C for 4 min. 1 μl of the resulting PCR product was used for the second round of PCR, with an identical reaction mix to that described for the first round (using pairs of species specific primers FAL-1 and FAL-2, VIV-1 and VIV-2, MAL-1 and MAL-2, and OVA-1 and OVA-2), and with the following cycle conditions: 95°C for 10 min, 32 cycles of 94°C for 1 min, 65°C for 1 min, and a final extension step of 65°C for 5 min. The resulting PCR products were visualized on 2% agarose gels, with the presence or absence of a band with each species primer pair indicative of the presence or absence of that species in the initial sample.</p>", "<title>Sensitivity of species diagnosis PCR</title>", "<p>Prior to commencement of PCR analysis of field samples, a pilot experiment was carried out to assess the sensitivity of the PCR conditions detailed above. This protocol consistently detected the presence of <italic>P. vivax </italic>in a dilution of genomic DNA that theoretically contained one copy of the parasite genome per μl (data not shown). Due to variation in DNA extraction technique between sample collections, a consistent volume of blood corresponding to the 1 μl of extracted genomic DNA used in the PCR cannot be given. However, it is estimated that no less than 0.5 μl of initial blood sample was used in each reaction. Therefore, the PCR detection method used in this investigation should detect <italic>P. vivax </italic>parasites in infections of as low as two parasites per μl of blood. Furthermore, microscopic evaluation of parasite presence was available for all samples, and these correlated well with PCR results. Although the very rare occurrence of a microscopically positive sample being found to be PCR negative did occur, the vast majority of discrepancies between microscopy and PCR diagnosis involved species misdiagnosis by microscopy, and the detection of parasite infections by PCR in microscopically negative samples, as is expected due to the greater sensitivity of the PCR technique.</p>", "<title>Duffy status profiling</title>", "<p>An FY* allele-specific PCR [##REF##9531948##29##] was used to determine the Duffy status of the individual from Sao Tome infected with <italic>P. vivax</italic>. Product amplification took place in a 50 μl volume reaction containing 5 μl of 10× PCR buffer, 4 μl of 25 mM MgCl2, 0.1 mM of each dNTP, 2 μl of the two 5 μM allele specific primers, 1 μl of the 5 μM control primers and 6 units of AmpliTaq Gold^®DNA polymerase (Applied Biosystems, USA). Amplification conditions were as follows; denaturation and activation of the AmpliTaqGold DNA polymerase at 96°C for 8 min, then 10 cycles of 94° for 20 s and 69°C for 1 min, leading to 25 cycles of 94°C for 20 s, 64°C for 30 s and 72°C for 1 min, followed by 5 cycles of 94°C for 20 s, 62°C for 30 s and 72°C for 1 min. Amplification of a 411 bp fragment of the ABO gene acted as the internal control for each reaction.</p>" ]

[ "<title>Results and discussion</title>", "<title>Prevalence of <italic>P. vivax </italic>in sub-Saharan Africa</title>", "<p>1,711 samples were positive for <italic>P. falciparum </italic>(1,526 single species infections, 51 with <italic>P. ovale</italic>, 129 with <italic>P. malariae</italic>, one with <italic>P. vivax </italic>and four with both <italic>P. malariae </italic>and <italic>P. ovale</italic>), 67 for <italic>P. ovale </italic>(12 single infections, 51 mixed with <italic>P. falciparum</italic>, and four triple infections with <italic>P. falciparum </italic>and <italic>P. malariae</italic>) 147 for <italic>P. malariae </italic>(14 single infections, 129 mixed with <italic>P. falciparum</italic>, and four triple infections with <italic>P. ovale </italic>and <italic>P. falciparum</italic>) and one for <italic>P. vivax </italic>(mixed infection with <italic>P. falciparum</italic>) (Table ##TAB##1##2##). The only <italic>P. vivax </italic>infected sample came from a Duffy positive individual from Sao Tome, an island off the west coast of Africa. No <italic>P. vivax </italic>from any other location within the continent was detected, confirming the scarcity of this parasite in Africa. When excluding samples from Rwanda, Mozambique, Angola and Sao Tome (self-selected as patients identified by microscopy with a mixed infection were excluded), <italic>P. malariae </italic>infections represented 8.5% of all malaria infections, and <italic>P. ovale </italic>3.9%. The prevalence of both parasites varies greatly by country.</p>", "<title>Scarcity of <italic>P. vivax</italic></title>", "<p>The prevalence of <italic>P. vivax </italic>in Africa is very low; no evidence for its presence in over 2,500 samples from nine African countries was found, with the exception of the island of Sao Tome, from which the parasite had previously been reported [##REF##9698266##10##]. These results, combined with the sporadic reports of the transmission of <italic>P. vivax </italic>in indigenous populations [##REF##9698266##10##,##REF##10072133##13##,##REF##17038676##19##] and the continued identification of imported cases originating in west and central Africa [##REF##15003128##15##,##UREF##2##17##] indicate that a very low prevalence of <italic>P. vivax </italic>is sufficient to maintain transmission. It is conceivable that in areas with very high entomological inoculation rates (EIR), such as in many areas of west and central Africa [##REF##17311470##30##], even very low numbers of Duffy positive individuals may allow the continued transmission of <italic>P. vivax</italic>.</p>", "<p>That low numbers of Duffy positive individuals in west and central Africa are sufficient to maintain transmission on <italic>P. vivax</italic>, is not surprising considering the very high basic reproduction number of malaria in this region. The basic reproductive number of a pathogen, R₀, is defined as the number of new infections arising from an infected individual introduced into a naïve population. When R₀&gt; 1, transmission is maintained in a population, but when R₀&lt; 1, transmission is interrupted and the pathogen cannot persist. A recent report showed that R₀for <italic>P. falciparum </italic>malaria transmission in Africa ranges from below one to nearly 11,000 with a median value of 86, depending on geographical location [##REF##17311470##30##]. Given that both <italic>P. falciparum </italic>and <italic>P. vivax </italic>are vectored by the same mosquito species, the only factor that that differentiates R₀for both species in a given population is the human host's susceptibility to infection. In order for transmission to be blocked, the proportion of completely immune individuals (<italic>p</italic>) required in a population is given by the formula <italic>p </italic>&gt; 1 - 1/R₀. Thus, in areas where Duffy negativity is present in a population at a prevalence of up to 99%, as it is in many parts of west and Central Africa [##UREF##0##8##], then <italic>P. vivax </italic>transmission can be expected to occur when R₀(for <italic>P. falciparum</italic>) &gt; 100, an entirely realistic value for many areas. It is entirely conceivable therefore, that <italic>P. vivax </italic>transmission occurs in populations in which there are a very high proportion Duffy negative individuals, given the very high <italic>P. falciparum </italic>R₀values associated with west and central Africa.</p>", "<p>A number of researchers have recently suggested that <italic>P. vivax </italic>may be in the process of evolving mechanisms [##REF##17360237##21##] that enable it to infect Duffy positive individuals. Given the extremely high EIRs and transmission dynamics of malaria parasites in sub-Saharan Africa, this scenario would appear highly unlikely given the extremely low incidences of the parasite reported here. Any <italic>P. vivax </italic>parasite that acquired the ability to infect Duffy negative individuals may be expected to rapidly spread throughout sub-Saharan Africa, and would be readily detectable in the population.</p>", "<title>Discrepancy between <italic>P. vivax </italic>rates in travellers and localpopulations</title>", "<p>Surveillance of malaria cases imported into the USA between 2001 and 2005 [##REF##17557074##31##, ####REF##12875252##32##, ##REF##15123983##33##, ##REF##15931154##34##, ##REF##16723971##35####16723971##35##], reveals that 32 cases of <italic>P. vivax </italic>originated in four west and central African countries for which we also have species prevalence data from the local populations. In the same time period, there were 545 cases of imported <italic>P. falciparum </italic>from the same countries. This gives a ratio of 100:6 <italic>P. falciparum </italic>to <italic>P. vivax </italic>infections in these areas, a surprisingly high rate, especially considering that <italic>P. malariae </italic>and <italic>P. ovale </italic>are represented at ratios of 100:6 and 100:5 respectively (comparable with those of the local populations, see Table ##TAB##2##3##). How does one account, then, for the discrepancy between the imported <italic>P. vivax </italic>data, and the extremely low prevalence in the native population reported here?</p>", "<p>It is possible that the geographical distribution of <italic>P. vivax </italic>within Africa is patchy, with sporadic areas of transmission scattered throughout the continent, possibly associated with human populations in which the Duffy negative phenotype is present at a lower frequency than elsewhere (such as on the island of Sao Tome). Travellers may preferentially visit areas of west and central Africa where there is a relatively high frequency of Duffy positive individuals in the local population (<italic>e.g</italic>. migrant workers and non-African expatriates) and where <italic>P. vivax </italic>is more likely to be transmitted.</p>", "<p>Another factor that may contribute to this discrepancy is the higher transmissibility of <italic>P. vivax </italic>relative to other malaria parasites, and in particular relative to <italic>P. falciparum</italic>, under adverse conditions [##REF##11425182##9##]. This has the consequence that there should be higher proportion of <italic>P. vivax </italic>relative to <italic>P. falciparum </italic>in the vector mosquitoes than there is in the corresponding human population. Consequently travellers, who are a probe of the infection rates in the local mosquitoes, can be expected to, and indeed do have (Carter and Mendis, unpublished analysis), higher proportions of <italic>P. vivax </italic>than are found in the endemic human populations amongst whom the travellers have briefly resided. This may explain the recent findings of Ryan et al [##REF##17038676##19##], who report the presence of <italic>P. vivax </italic>in 0.65% of mosquitoes from an area of western Kenya with a high proportion of Duffy negativity in the local population. However, even an extremely small percentage of Duffy positive individuals in this population may be expected to support such a rate in mosquitoes.</p>", "<p>The use of prophylactic anti-malaria drugs among travellers may also contribute to this phenomenon. Mefloquine is the recommended prophylactic drug for travellers to west and central Africa from the USA [##REF##17557074##31##], and whilst effective against the blood stages of all malaria parasites, it does not affect the dormant hypnozoite stages of <italic>P. vivax</italic>, and will therefore not protect against relapses after cessation of drug use. This is also true of <italic>P. ovale</italic>, which is also capable of producing hypnozoites, and may explain the slightly higher rate of this parasite in returning travellers compared to the local populations (Table ##TAB##2##3##).</p>", "<p>It is also probable that a small proportion of imported cases may be <italic>P. ovale </italic>infections rather than <italic>P. vivax</italic>, as is often difficult to distinguish the two species by microscopy [##REF##15003128##15##]. As previously mentioned, there are an increasing number of reports detailing imported African <italic>P. vivax </italic>diagnosed by accurate molecular typing techniques [##REF##11230828##16##,##REF##16014856##18##].</p>", "<p>In conclusion, the present study indicates that the prevalence of <italic>P. vivax </italic>in local populations in sub-Saharan Africa is very low, despite the frequent identification of this parasite in travellers. <italic>P. vivax </italic>malaria, therefore, does not constitute a health risk to the indigenous populations of west and central Africa, though Duffy positive individuals, including non-African travellers to the area, may be at risk.</p>" ]

[ "<title>Results and discussion</title>", "<title>Prevalence of <italic>P. vivax </italic>in sub-Saharan Africa</title>", "<p>1,711 samples were positive for <italic>P. falciparum </italic>(1,526 single species infections, 51 with <italic>P. ovale</italic>, 129 with <italic>P. malariae</italic>, one with <italic>P. vivax </italic>and four with both <italic>P. malariae </italic>and <italic>P. ovale</italic>), 67 for <italic>P. ovale </italic>(12 single infections, 51 mixed with <italic>P. falciparum</italic>, and four triple infections with <italic>P. falciparum </italic>and <italic>P. malariae</italic>) 147 for <italic>P. malariae </italic>(14 single infections, 129 mixed with <italic>P. falciparum</italic>, and four triple infections with <italic>P. ovale </italic>and <italic>P. falciparum</italic>) and one for <italic>P. vivax </italic>(mixed infection with <italic>P. falciparum</italic>) (Table ##TAB##1##2##). The only <italic>P. vivax </italic>infected sample came from a Duffy positive individual from Sao Tome, an island off the west coast of Africa. No <italic>P. vivax </italic>from any other location within the continent was detected, confirming the scarcity of this parasite in Africa. When excluding samples from Rwanda, Mozambique, Angola and Sao Tome (self-selected as patients identified by microscopy with a mixed infection were excluded), <italic>P. malariae </italic>infections represented 8.5% of all malaria infections, and <italic>P. ovale </italic>3.9%. The prevalence of both parasites varies greatly by country.</p>", "<title>Scarcity of <italic>P. vivax</italic></title>", "<p>The prevalence of <italic>P. vivax </italic>in Africa is very low; no evidence for its presence in over 2,500 samples from nine African countries was found, with the exception of the island of Sao Tome, from which the parasite had previously been reported [##REF##9698266##10##]. These results, combined with the sporadic reports of the transmission of <italic>P. vivax </italic>in indigenous populations [##REF##9698266##10##,##REF##10072133##13##,##REF##17038676##19##] and the continued identification of imported cases originating in west and central Africa [##REF##15003128##15##,##UREF##2##17##] indicate that a very low prevalence of <italic>P. vivax </italic>is sufficient to maintain transmission. It is conceivable that in areas with very high entomological inoculation rates (EIR), such as in many areas of west and central Africa [##REF##17311470##30##], even very low numbers of Duffy positive individuals may allow the continued transmission of <italic>P. vivax</italic>.</p>", "<p>That low numbers of Duffy positive individuals in west and central Africa are sufficient to maintain transmission on <italic>P. vivax</italic>, is not surprising considering the very high basic reproduction number of malaria in this region. The basic reproductive number of a pathogen, R₀, is defined as the number of new infections arising from an infected individual introduced into a naïve population. When R₀&gt; 1, transmission is maintained in a population, but when R₀&lt; 1, transmission is interrupted and the pathogen cannot persist. A recent report showed that R₀for <italic>P. falciparum </italic>malaria transmission in Africa ranges from below one to nearly 11,000 with a median value of 86, depending on geographical location [##REF##17311470##30##]. Given that both <italic>P. falciparum </italic>and <italic>P. vivax </italic>are vectored by the same mosquito species, the only factor that that differentiates R₀for both species in a given population is the human host's susceptibility to infection. In order for transmission to be blocked, the proportion of completely immune individuals (<italic>p</italic>) required in a population is given by the formula <italic>p </italic>&gt; 1 - 1/R₀. Thus, in areas where Duffy negativity is present in a population at a prevalence of up to 99%, as it is in many parts of west and Central Africa [##UREF##0##8##], then <italic>P. vivax </italic>transmission can be expected to occur when R₀(for <italic>P. falciparum</italic>) &gt; 100, an entirely realistic value for many areas. It is entirely conceivable therefore, that <italic>P. vivax </italic>transmission occurs in populations in which there are a very high proportion Duffy negative individuals, given the very high <italic>P. falciparum </italic>R₀values associated with west and central Africa.</p>", "<p>A number of researchers have recently suggested that <italic>P. vivax </italic>may be in the process of evolving mechanisms [##REF##17360237##21##] that enable it to infect Duffy positive individuals. Given the extremely high EIRs and transmission dynamics of malaria parasites in sub-Saharan Africa, this scenario would appear highly unlikely given the extremely low incidences of the parasite reported here. Any <italic>P. vivax </italic>parasite that acquired the ability to infect Duffy negative individuals may be expected to rapidly spread throughout sub-Saharan Africa, and would be readily detectable in the population.</p>", "<title>Discrepancy between <italic>P. vivax </italic>rates in travellers and localpopulations</title>", "<p>Surveillance of malaria cases imported into the USA between 2001 and 2005 [##REF##17557074##31##, ####REF##12875252##32##, ##REF##15123983##33##, ##REF##15931154##34##, ##REF##16723971##35####16723971##35##], reveals that 32 cases of <italic>P. vivax </italic>originated in four west and central African countries for which we also have species prevalence data from the local populations. In the same time period, there were 545 cases of imported <italic>P. falciparum </italic>from the same countries. This gives a ratio of 100:6 <italic>P. falciparum </italic>to <italic>P. vivax </italic>infections in these areas, a surprisingly high rate, especially considering that <italic>P. malariae </italic>and <italic>P. ovale </italic>are represented at ratios of 100:6 and 100:5 respectively (comparable with those of the local populations, see Table ##TAB##2##3##). How does one account, then, for the discrepancy between the imported <italic>P. vivax </italic>data, and the extremely low prevalence in the native population reported here?</p>", "<p>It is possible that the geographical distribution of <italic>P. vivax </italic>within Africa is patchy, with sporadic areas of transmission scattered throughout the continent, possibly associated with human populations in which the Duffy negative phenotype is present at a lower frequency than elsewhere (such as on the island of Sao Tome). Travellers may preferentially visit areas of west and central Africa where there is a relatively high frequency of Duffy positive individuals in the local population (<italic>e.g</italic>. migrant workers and non-African expatriates) and where <italic>P. vivax </italic>is more likely to be transmitted.</p>", "<p>Another factor that may contribute to this discrepancy is the higher transmissibility of <italic>P. vivax </italic>relative to other malaria parasites, and in particular relative to <italic>P. falciparum</italic>, under adverse conditions [##REF##11425182##9##]. This has the consequence that there should be higher proportion of <italic>P. vivax </italic>relative to <italic>P. falciparum </italic>in the vector mosquitoes than there is in the corresponding human population. Consequently travellers, who are a probe of the infection rates in the local mosquitoes, can be expected to, and indeed do have (Carter and Mendis, unpublished analysis), higher proportions of <italic>P. vivax </italic>than are found in the endemic human populations amongst whom the travellers have briefly resided. This may explain the recent findings of Ryan et al [##REF##17038676##19##], who report the presence of <italic>P. vivax </italic>in 0.65% of mosquitoes from an area of western Kenya with a high proportion of Duffy negativity in the local population. However, even an extremely small percentage of Duffy positive individuals in this population may be expected to support such a rate in mosquitoes.</p>", "<p>The use of prophylactic anti-malaria drugs among travellers may also contribute to this phenomenon. Mefloquine is the recommended prophylactic drug for travellers to west and central Africa from the USA [##REF##17557074##31##], and whilst effective against the blood stages of all malaria parasites, it does not affect the dormant hypnozoite stages of <italic>P. vivax</italic>, and will therefore not protect against relapses after cessation of drug use. This is also true of <italic>P. ovale</italic>, which is also capable of producing hypnozoites, and may explain the slightly higher rate of this parasite in returning travellers compared to the local populations (Table ##TAB##2##3##).</p>", "<p>It is also probable that a small proportion of imported cases may be <italic>P. ovale </italic>infections rather than <italic>P. vivax</italic>, as is often difficult to distinguish the two species by microscopy [##REF##15003128##15##]. As previously mentioned, there are an increasing number of reports detailing imported African <italic>P. vivax </italic>diagnosed by accurate molecular typing techniques [##REF##11230828##16##,##REF##16014856##18##].</p>", "<p>In conclusion, the present study indicates that the prevalence of <italic>P. vivax </italic>in local populations in sub-Saharan Africa is very low, despite the frequent identification of this parasite in travellers. <italic>P. vivax </italic>malaria, therefore, does not constitute a health risk to the indigenous populations of west and central Africa, though Duffy positive individuals, including non-African travellers to the area, may be at risk.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p><italic>Plasmodium vivax </italic>is estimated to affect 75 million people annually. It is reportedly absent, however, from west and central Africa due to the high prevalence of the Duffy negative phenotype in the indigenous populations. Despite this, non-African travellers consistently return to their own countries with <italic>P. vivax </italic>malaria after visiting this region. An attempt was made, therefore, to detect the presence of <italic>P. vivax </italic>parasites in blood samples collected from the indigenous populations of west and central Africa.</p>", "<title>Methods</title>", "<p>Parasite species typing (for all four human malaria parasites) was carried out by PCR on 2,588 blood samples collected from individuals from nine African malaria-endemic countries.</p>", "<title>Results</title>", "<p>Most infections (98.5%) were <italic>Plasmodium falciparum</italic>, <italic>Plasmodium malariae </italic>was identified in 8.5% of all infections, and <italic>Plasmodium ovale </italic>in 3.9%. The prevalence of both parasites varied greatly by country. Only one case of <italic>P. vivax </italic>was detected from Sao Tome, an island off the west coast of Africa, confirming the scarcity of this parasite in Africa.</p>", "<title>Conclusion</title>", "<p>The prevalence of <italic>P. vivax </italic>in local populations in sub-Saharan Africa is very low, despite the frequent identification of this parasite in non-African travellers.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>RCu, RCa and KT conceived the study and participated in its design and coordination. RCu wrote the manuscript. MN, FN, HU, RCa, UdA, AK and KT helped to draft the manuscript. RCu, HU, TM, HE and NT performed molecular parasite typing. MN coordinated and carried out sample collection in the Republic of Congo, HU and FN in Gabon, GP in Burkina Faso, HT, CK and UdA in Rwanda, PC and VdR in Sao Tome, Angola, and Mozambique, and TM, AK and TK in Ghana and Kenya. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This study was supported by Grant-in-Aid for Scientific Research on Priority Areas from The Japanese Ministry of Education, Culture, Sports, Science and Technology (18073013) and Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (17–05495, 18390131, 18GS03140013). We are grateful for a travel award to HU from the John Scaife Fund, Edinburgh. We thank Dr. Rikard Dryselius for helpful discussion, and Dr. Naoko Sakihama for technical assistance.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Details of sample collections.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Collection area</bold></td><td align=\"center\"><bold>Number</bold></td><td align=\"center\"><bold>Sampling year</bold></td><td align=\"center\"><bold>Sampling method (ACD/PCD)*</bold></td><td align=\"center\"><bold>Age</bold></td><td align=\"center\"><bold>Reference</bold></td></tr></thead><tbody><tr><td align=\"center\">Burkina Faso¹</td><td align=\"center\">108</td><td align=\"center\">2002</td><td align=\"center\">ACD</td><td align=\"center\">&lt; 10</td><td align=\"center\">22</td></tr><tr><td align=\"center\">Republic of Congo</td><td align=\"center\">851</td><td align=\"center\">2005–2006</td><td align=\"center\">PCD (clinic)</td><td align=\"center\">all ages</td><td align=\"center\">This study</td></tr><tr><td align=\"center\">Gabon</td><td align=\"center\">206</td><td align=\"center\">2005</td><td align=\"center\">PCD (clinic)</td><td align=\"center\">all ages</td><td align=\"center\">This study</td></tr><tr><td align=\"center\">Ghana¹</td><td align=\"center\">352</td><td align=\"center\">2004</td><td align=\"center\">ACD</td><td align=\"center\">&lt; 15</td><td align=\"center\">This study</td></tr><tr><td align=\"center\">Kenya</td><td align=\"center\">722</td><td align=\"center\">1998</td><td align=\"center\">ACD</td><td align=\"center\">All ages</td><td align=\"center\">This study</td></tr><tr><td align=\"center\">Sao Tome^1,2</td><td align=\"center\">70</td><td align=\"center\">2004</td><td align=\"center\">PCD (clinic)</td><td align=\"center\">All ages</td><td align=\"center\">23</td></tr><tr><td align=\"center\">Angola^1,2</td><td align=\"center\">90</td><td align=\"center\">2003–2004</td><td align=\"center\">PCD (clinic)</td><td align=\"center\">1–5</td><td align=\"center\">24</td></tr><tr><td align=\"center\">Mozambique^1,2</td><td align=\"center\">90</td><td align=\"center\">2004</td><td align=\"center\">PCD (clinic)</td><td align=\"center\">1–5</td><td align=\"center\">25</td></tr><tr><td align=\"center\">Rwanda^1,2</td><td align=\"center\">99</td><td align=\"center\">2003</td><td align=\"center\">PCD (clinic)</td><td align=\"center\">All ages</td><td align=\"center\">26</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Total</td><td align=\"center\">2588</td><td/><td/><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Species composition of isolates analysed by PCR (%)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Collection area</bold></td><td align=\"center\"><bold>Number</bold></td><td align=\"center\"><bold><italic>P. falciparum</italic></bold></td><td align=\"center\"><bold><italic>P. ovale</italic></bold></td><td align=\"center\"><bold><italic>P. malariae</italic></bold></td><td align=\"center\"><bold><italic>P. vivax</italic></bold></td></tr></thead><tbody><tr><td align=\"center\">Burkina Faso¹</td><td align=\"center\">108</td><td align=\"center\">108 (100)</td><td align=\"center\">6 (5.5)</td><td align=\"center\">8 (7.4)</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Congo</td><td align=\"center\">851</td><td align=\"center\">341 (40.1)</td><td align=\"center\">11 (1.3)</td><td align=\"center\">8 (0.9)</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Gabon</td><td align=\"center\">206</td><td align=\"center\">102 (49.5)</td><td align=\"center\">4 (1.9)</td><td align=\"center\">1 (0.5)</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Ghana¹</td><td align=\"center\">352</td><td align=\"center\">352 (100)</td><td align=\"center\">8 (2.3)</td><td align=\"center\">45 (12.8)</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Kenya</td><td align=\"center\">722</td><td align=\"center\">459 (63.6)</td><td align=\"center\">35 (4.8)</td><td align=\"center\">84 (11.6)</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Angola^1,2</td><td align=\"center\">90</td><td align=\"center\">90 (100)</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Mozambique^1,2</td><td align=\"center\">90</td><td align=\"center\">90 (100)</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Rwanda^1,2</td><td align=\"center\">99</td><td align=\"center\">99 (100)</td><td align=\"center\">2 (2)</td><td align=\"center\">1 (1)</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Sao Tome^1,2</td><td align=\"center\">70</td><td align=\"center\">70 (100)</td><td align=\"center\">1 (1.4)</td><td align=\"center\">0</td><td align=\"center\">1 (1.4)</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\"><italic>Total</italic></td><td align=\"center\"><italic>2588</italic></td><td align=\"center\"><italic>1711</italic></td><td align=\"center\"><italic>67</italic></td><td align=\"center\"><italic>147</italic></td><td align=\"center\"><italic>1</italic></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Parasite species prevalence of traveler's malaria imported into the USA (2001-2005) from Burkina Faso, Gabon, Republic of Congo / Democratic Republic of Congo and Ghana compared to that of the local populations.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Species</bold></td><td align=\"center\" colspan=\"2\"><bold>Total number</bold></td><td align=\"center\" colspan=\"2\"><bold>Species prevalence (per 100 <italic>P. falciparum </italic>cases)</bold></td></tr></thead><tbody><tr><td/><td align=\"center\">Imported to the USA¹</td><td align=\"center\">Local population²</td><td align=\"center\">Imported to the USA¹</td><td align=\"center\">Local population²</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>P. falciparum</italic></td><td align=\"center\">545</td><td align=\"center\">903</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"left\"><italic>P. vivax</italic></td><td align=\"center\">32</td><td align=\"center\">0</td><td align=\"center\"><bold>5.9</bold></td><td align=\"center\"><bold>0</bold></td></tr><tr><td align=\"left\"><italic>P. malariae</italic></td><td align=\"center\">34</td><td align=\"center\">62</td><td align=\"center\">6.2</td><td align=\"center\">6.9</td></tr><tr><td align=\"left\"><italic>P. ovale</italic></td><td align=\"center\">26</td><td align=\"center\">29</td><td align=\"center\">4.8</td><td align=\"center\">3.2</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>¹Only <italic>P. falciparum </italic>positive samples were available for analysis</p><p>²Only <italic>P. falciparum </italic>single species infections (diagnosed by microscopy) were analysed</p><p>*ACD; active case detection, PCD; passive case detection</p></table-wrap-foot>", "<table-wrap-foot><p>¹Only <italic>P. falciparum </italic>positive samples were available for analysis</p><p>²Only <italic>P. falciparum </italic>single species infections (diagnosed by microscopy) were analysed</p></table-wrap-foot>", "<table-wrap-foot><p>¹2001–2005, data from [##UREF##2##17##,##REF##17557074##31##, ####REF##12875252##32##, ##REF##15123983##33##, ##REF##15931154##34##, ##REF##16723971##35####16723971##35##]</p><p>²data from the current survey</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1475-2875-7-174-1\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Thousands of cases of malaria occur each year in the mountainous and forested provinces of south-central Vietnam [##UREF##0##1##,##UREF##1##2##]. Whilst few of these cases are fatal, the ensuing morbidity may have an economic impact on the population. The burden of malaria can be felt both in terms of the direct costs of seeking treatment as well as the indirect costs of reduced household productivity [##REF##11044273##3##, ####REF##12753643##4##, ##REF##12219157##5##, ##REF##1460697##6####1460697##6##]. Between 2004 and 2006, the National Institute of Malariology, Parasitology and Entomology of Vietnam, in collaboration with the Institute of Tropical Medicine in Belgium and with the financial support of the Belgium Cooperation and the UBS Optimus Foundation, piloted a cluster-based randomized trial to evaluate the efficacy of long-lasting insecticidal hammocks (LLIH) for the control of forest malaria in the province of Ninh Thuan. Ten intervention clusters received free LLIHs and were followed over two years, together with 10 control clusters (total 20,000 inhabitants), using bi-annual malariometric surveys and passive case detection. The latter was carried out at Commune Health Centres (CHC) and at the homes of village health workers (VHW) who were trained in the use of rapid diagnostic tests and malaria treatment. An ancillary health economic study was set up to evaluate the cost-effectiveness of this new intervention. This paper presents an estimation of the economic costs of a malaria episode to households in this area. The full economic cost and relative cost-effectiveness of LLIHs will be addressed in a subsequent paper.</p>" ]

[ "<title>Methods</title>", "<title>Study area and population</title>", "<p>The study was carried out in two districts (Bac Ai and Ninh Son) in the northwest of Ninh Thuan Province. The area is inhabited primarily by the Raglay ethnic minority, a largely self-sustaining farming community. Malaria transmission in this area is perennial with two peaks, at the beginning and end of the rainy season (May and November) [##UREF##2##7##]. Over the past few decades, the Vietnamese government has tried to relocate the Raglay community away from the forests and into purpose-built villages containing basic infrastructure. However, Raglays, a traditionally nomadic minority, continue to frequent the forest for cultivation and various other daily activities, and thus are continuously exposed to forest-dwelling mosquitoes.</p>", "<p>Ill patients have the option of seeking care from the VHW who can do a rapid diagnostic test (Paramax 3^®, Zephyr Biomedicals, India) and, if positive, treat patients or refer them to the CHC. Alternatively, patients can go for treatment directly to the CHC where antimalarial drugs are provided free by the government due to the poverty in the area. In another study, the treatment seeking patterns for malaria within this population were estimated to be 60% at the VHW, 38% at the CHC and 2% at other facilities [##UREF##3##8##]. Severe malaria cases are referred to the district or provincial hospital, where care is also free to the patient. The study area covers 30 villages (each with a VHW working from home) which make up 10 official communes (each with a CHC), two District Health Centres (DHC), and one district hospital.</p>", "<title>Methodology</title>", "<p>Data on direct and indirect costs of malaria to the household were collected by health workers using an exit survey and a household survey. The surveys were piloted for two months and then carried out between October 2004 and March 2006. Supervision for both surveys was provided by members of the provincial and national Malaria Control Programme, who also conducted refresher sessions regarding quality of responses and met regularly with data collectors to ensure that study guidelines were adequately followed.</p>", "<p>Patients for the exit survey were identified at the CHC after having tested positive for malaria (using a rapid diagnostic test that detects all four human malaria species). Only patients with a positive test were asked to take part. Patients were asked about all direct costs they incurred, including all expenditures associated with seeking treatment as well as all non-medical costs such as transport costs. Household visits took place two to four weeks after the initial interview at the CHC. The household survey included further questions regarding cost of any initial or follow-up treatment for malaria, productive activities, household assets, and workdays missed due to malaria. All patients included in the study were given an individual code number to maintain confidentiality.</p>", "<p>Direct costs were calculated per patient per facility and then complemented by actual (non-trial) local treatment-seeking probabilities at each level in order to estimate the probability-weighted mean direct cost per episode within the community. The availability of free government-sponsored malaria treatment was confirmed both in the survey and through informal discussions with patients, providers and provincial health staff.</p>", "<p>Indirect costs refer to the productivity lost within the household due to illness. Following the broad interpretation of the human capital approach [##REF##10175982##9##], these costs include: reduced paid production due to the individual's disease, reduced unpaid production due to the individual's disease, and indirect costs accrued by the family for taking care of the individual during their illness. The productivity loss within the household translates to an income loss that can be calculated using various microeconomic tools. Output-based approaches value the product forgone within the loss of time until the person is replaced or recovers [##UREF##4##10##]. They attach zero value to unpaid housework (primarily due to the difficulty of making accurate estimates of its output). Opportunity cost approaches use average wages paid to local workers as proxies for the value of work of unpaid workers[##REF##10175982##9##]. As the main profession in the study area was subsistence farming, formally-paid wages were not available to act as proxies for unpaid work. An output-based approach was therefore chosen to measure productivity loss due to malaria. In using this approach, income and production were taken to be expressions of the same quantity: the value-added of productive persons or their contribution to overall wealth [##REF##9353652##11##]. All agricultural work was considered to contribute to income whether the products were eventually sold or consumed within the household.</p>", "<p>It was judged that questions concerning loss of productivity due to illness would not attract accurate responses. Therefore, the household survey collected data on yearly household production (of livestock and agricultural produce) which was valued using the price of each item on the local market and taken to be a proxy for yearly income. Responses about local prices of agricultural produce and livestock varied little (average 22% deviation from the mean) so they were considered sufficiently accurate. These values were then complemented by evidence on productive days per year, work time, division of work within the family, and likelihood of being replaced when ill, in order to calculate the average daily household income per person.</p>", "<p>Anthropological investigation associated with the study previously found that men and women work the same hours and with the same intensity in the fields and that children over the age of 10 are fully contributing members of the household. Their contribution to output was therefore given equal value. This investigation also found that this community works approximately six days per week throughout the rainy season, which corresponds to approximately half the year. Assuming that these families work only four days per week during the dry season when there is less to cultivate, the average number of household productive workdays per year is 261. Workday equivalents for working time lost were calculated assuming responses expressed in days equalled one workday and responses expressed in hours and minutes equalled a fraction of a 12-hour workday. Given the stated average number of workdays lost for the patient and carer, the average income loss per malaria episode could then be calculated per household.</p>", "<p>Indirect and direct costs were combined to estimate the total cost incurred by the household per episode. Costs were converted from Vietnamese Dong (VND) to US dollars (USD) using the average inter-bank exchange rate for the period in which the study was conducted (15,989 VND per USD) [##UREF##5##12##]. Data entry, cleaning, and analysis were done with Epi-Info6 and Microsoft Excel. Sensitivity analysis was carried out to account for uncertainty surrounding some of the data and to test results given differing conditions and assumptions. Individual data values considered uncertain were replaced with alternate values in order to observe the level of change in the study results.</p>" ]

[ "<title>Results</title>", "<title>Characteristics of study respondents</title>", "<p>For the household survey, 251 patients were interviewed, with a sex ratio male to female of 1.67. The median age was 16, ranging from 1 to 68 years old and was similar among men (16.5 [range 1–68] and women (15 [range 1–60]). Seventy-five patients (30%) were children under the age of 10 who are considered here to be too young to contribute significantly to household production. This proportion was the same as in the general population [##UREF##2##7##] and slightly lower than the symptomatic population of which under 10s made up 36% of the population. Ninety-four percent of households sold agricultural products, 89% sold animals, and 3% worked for the public authority. Thirteen percent claimed to also do other unspecified work. Salaried workers had an annual average salary of 5,232,000 VND or 327 USD (range 63 to 438 USD). Seventy-two percent of patients had a radio in their household, 58% a television, 80% a bicycle, and 36% a motorbike.</p>", "<title>Direct costs of a malaria episode to the household</title>", "<p>Direct costs associated with seeking treatment are reported in Table ##TAB##0##1##. Forty percent of the patients (n = 99) attended the CHC by bicycle, another 33% by motorbike (n = 84), and 27% (n = 67) on foot. Overall, patients incurred an average travel cost of 1,750 VND or 0.11 USD when seeking care at the commune level. Eight (3.2%) patients visited the CHC twice, but only four were treated for malaria during the first visit. Four (1.6%) patients in the study initially sought care from the VHW (prior to going to the CHC), paying a mean of 15,500 VND or 0.97 USD for treatment (range 0.38 to 1.63). It was not determined whether treatment costs were for consultation or drugs other than antimalarials. The mean travel cost for those visiting the VHW was 1,250 VND or 0.08 USD. Eight (3.2%) patients sought further treatment after attending the CHC: four went to hospital, three went to a private health clinic (possibly meaning a traditional healer) and one went to a pharmacy/drug seller. They paid an average of 3,000 VND or 0.19 USD for treatment with an average travel cost of 15,312 VND or 0.96 USD. If these direct costs are applied to the actual treatment-seeking patterns for malaria in the community, where 60% of visits take place at the VHW, 38% at the CHC and 2% at other facilities[##UREF##3##8##], patients can be estimated to incur a direct cost of 0.69 USD (Table ##TAB##0##1##).</p>", "<title>Indirect costs of a malaria episode to the household</title>", "<p>Time loss due to treatment seeking. Average travel time was 14 minutes to the home of the VHW, 25 minutes to the CHC, and 38 minutes to other facilities (hospital, private clinic, pharmacy/drug seller). Average time spent at the health facility was 25 minutes at the VHW's home, 2 hours and 52 minutes at the CHC, and 1.77 workdays at other facilities. It was assumed that time lost from seeking treatment was included in the patient's response for the total duration of illness. If time lost for treatment-seeking of the survey population is applied to the actual treatment-seeking patterns of the community, patients, on average, lose the equivalent of 0.14 workdays in seeking treatment. Details of the time loss due to seeking treatment are reported as workday equivalents in Table ##TAB##1##2##.</p>", "<p>Patients were accompanied by an average of 1.11 household members (range:1–2). The household member stayed with the patient the entire duration of the visit and therefore could not replace the patient in the field during this time.</p>", "<title>Time loss due to illness</title>", "<p>The average malaria episode was found to last approximately 5 days (range: 1–10 days) – a duration over which most patients ceased all work. For those few who did work while ill, the vast majority stated that they were not able to perform at a normal level. Almost all patients received care from another household member. The caretaker was usually from the same household as the patient and ceased to work for most of the time the patient was ill.</p>", "<title>Productivity and income loss</title>", "<p>The surveys, together with numerous informal discussions with community members, suggested farming to be the primary economic activity in the area (see Table ##TAB##2##3## for details). Livestock reared and sold in the area included primarily chickens, cows, and pigs. Households grew a mean of 3.1 million VND or 194 USD worth of agricultural produce per year of which they sold 2.4 million VND or 152 USD worth (79%). Households reared an average of 14 million VND or 869 USD worth of livestock per year of which they sold 3.4 million VND or 210 USD (24%). Revenue from the sales could be spent on goods the household itself did not produce. Interviews with village elders suggested that the larger livestock were sold when households struggled to find cash for meeting immediate needs like seeking health care. 50% of households reared one or more cows and 3% reared one or more buffaloes. Total yearly production per household – including both what was sold and what was consumed – was estimated to be 1063 USD.</p>", "<p>A loss of five full household productive workdays as a result of malaria (approximately 2% of the estimated 261 total household productive days) would result in a loss of approximately 325,629 VND or 20.37 USD in income. This is 2% of the value of yearly production. However, not all productive members of the household are incapacitated during an episode of malaria. It was assumed, based on local information, that each household had an average of three fully productive person equivalents (individuals between the ages of 10 and 65). As caretakers were found to be productively inactive for the duration of illness, two productive person equivalents were considered inactive in the case of malaria in a productive person and one productive person equivalent was considered inactive in the case of a non-productive person (aged 0 through 9 or over 65) with malaria. It can be assumed that these days are productive days as malaria usually coincides with the rainy season which is also an agriculturally productive season. An episode of malaria amongst productive members of the household is therefore estimated to represent a loss of two-thirds of this income (217,086 VND or 13.58 USD) and an episode amongst non-productive members is estimated to represent a loss of one-third of this income (108,543 VND or 6.79 USD). The mean weighted by age for all symptomatic cases in the study area was 177,501 VND, or 11.10 USD.</p>", "<title>Sensitivity analysis</title>", "<p>Sensitivity analysis was conducted on the duration of illness using the ranges provided in patient responses. At the low end, a one-day episode would result in a loss of 2.22 USD in revenue per age weighted episode. At the high end, a 10-day episode would result in a loss of 22.20 USD in revenue per age weighted episode.</p>", "<p>The number of productive household members was also subject to sensitivity analysis to see how smaller or larger households might fare differently. A household with only two productive members would incur a loss of income of 16.65 USD per age weighted episode. A household with 4 productive members would incur a loss of income of 8.33 USD per age weighted episode.</p>", "<p>A sensitivity analysis was also conducted on travel costs. If the new VHW programme were to be cancelled and the CHC were the first level of care for those who currently go to the VHW, the average cost of travel would increase by approximately 15%. However, other costs which this study did not accurately calculate would likely increase significantly (see Discussion).</p>", "<p>This study has examined the economic burden (proportion of household income lost directly or indirectly due to illness) caused by malaria. Depending on the context, burden is thought to be catastrophic when households are forced to cut their consumption of other minimum needs, sell productive assets, accrue large debt, or become impoverished [##REF##15331831##13##]. It has been suggested that this occurs when the burden exceeds 10% of annual household income [##REF##12112492##14##]. In this study, the burden of one episode of malaria is estimated to be 1.04% of annual household income on average. This is calculated using number of productive days lost out of total productive days so it does not change according to household assets. However, it must be emphasized that this estimated loss in income is per episode. If there are several episodes per household per year the burden on the household could be substantially more. Previous studies carried out in the nearby province of Binh Thuan estimated the entomological inoculation rate to be approximately 1 infective bite per person per year and the incidence of all malaria infections to be 0.44 per person/year[##REF##11791965##15##,##REF##14993619##16##]. Therefore, if there were to be on average between 0.5 to 1 malaria episode per person per year, then a family of five with two children under 10 would incur a cost of 27.15 to 54.31 USD or 3 to 5% of annual income.</p>" ]

[ "<title>Discussion</title>", "<title>Impact on the household</title>", "<p>Direct costs per episode were estimated to be 0.69 USD, and indirect costs 11.10 USD, making a total of 11.79 USD. Thus the impact of malaria on the household was mainly in terms of the indirect costs (measured as an assumed reduction in output) imposed on an already small income. Mean annual household income was estimated to be worth 1063 USD, which is equivalent to approximately 4.25 cows on the local market. The approximate total loss of 11.79 USD per household per episode of malaria should be seen in the light of this yearly income; for a household with no large saleable assets (cows or buffalo), the absolute burden of illness would be far more significant than for those with these assets.</p>", "<p>Findings from a different study that was conducted on data from all provinces in Vietnam suggested that a 60% average reduction in malaria nationwide was associated with a 1.8% increase in annual household consumption. This translated to a mean 12.60 USD (1998 prices or 15.10 USD in 2005 prices). It is difficult to directly compare these findings with this study's findings due to the particular epidemiological and economic conditions of the south-central part of the country, as well as the different methods used. The nationwide study included households that did not experience any episodes of malaria, which could generally suggest that the estimated loss from malaria in this study, which only included households that experienced malaria episodes, may be low. However, the direct costs in Ninh Thuan province, where this study was conducted, are highly subsidized by government and therefore not comparable to a country-wide sample. A study from Sri Lanka estimated the loss of annual household income due to malaria to be 6% using wage rates[##REF##9230799##17##] compared to this study's estimate of 3 to 5% loss using productivity losses.</p>", "<p>Informal interviews conducted in this study revealed that households in Ninh Thuan sold productive assets such as a cow when under financial strain. It is difficult to estimate how many of the sales reported in the study took place under catastrophic conditions and what proportion of household income was lost to require the selling of these assets. Nor is it known what market conditions were like, and whether sales due to the need to obtain cash were at times when market prices were depressed (which might, for example, be the case if illness requiring sale of assets was concentrated at certain times of the year). It can, however, be inferred that those with large livestock to sell had a much easier time meeting emergency cash needs in times of illness.</p>", "<p>Productivity loss was measured in terms of annual output potentially lost from missing a given number of productive workdays due to illness. However, there may be compensating mechanisms (such as to adjustments to worker responsibilities) that allow a household to make up for the missing days of work by the patient and carer. Studies suggest that compensation mechanisms exist in most formal work environments[##REF##15497201##18##]. In a family setting, the taking of responsibility for patient or carer duties may seem even more likely. However, patient responses indicated that they needed almost full-time care from another household member when they were ill and, given that the 12-hour workday in Ninh Thuan is followed by household chores, there is little slack time for taking up additional work.</p>", "<p>Responses to the surveys gave estimates for the cost of seeking care at each level of the health system. However, they did not represent the real distribution of malaria patients amongst the levels of care as all patients in the study had to attend the CHC in order to be identified for the study. In reality it is believed that 60% of malaria patients are treated by the VHW, 38% are treated at the CHC, and 2% seek care elsewhere [##UREF##3##8##].</p>", "<p>Ideally more data from this study would have come from the level of the VHW, but the study design was constrained by the need to identify confirmed malaria cases and by the relatively small weekly load of malaria patients. These considerations meant that patients needed to be identified at a health facility, and health workers used as data collectors. Poor education levels amongst VHW were thought likely to affect their ability to carry out lengthy surveys, so the CHC was chosen as the point at which patients were selected. VHW patients were identified only if they also attended the CHC at some point. In reality there may be differences between those who sought care at the CHC and those who sought care from the VHW, however no significant differences were detected in this study: for example, both duration of illness and time off work were similar. As the CHC was the first and only point of call for most study patients, the data presented here are less robust with respect to costs associated with VHW care.</p>", "<p>If the pilot CHW programme is ended and the CHC returns to being the first point of access for malaria care, this study estimated that this would increase overall average travel costs by 15%. However, it is likely that, in the absence of VHWs, more patients would seek care from alternative sources such as local drug sellers or traditional healers. As seen in study responses, treatment seeking outside the public services does carry a significant direct cost. Accurate estimates of the magnitude of this cost to the household could not be made with the data from this study as they did not capture patients who lacked village-level services.</p>", "<title>Reliability of data</title>", "<p>The data for the economic analysis came primarily from a survey. Responses regarding assets may have omitted some assets grown (or raised in the case of livestock) on plots cultivated in the forest. Cultivating plots in the forest may not be illegal in itself, however, much secrecy surrounds any discussion on forest activities due to the illegal cutting and removal of wood from government-owned parts of the forest. Answering survey questionnaires is likely to appear extremely formal to the study population, with answers likely to be adapted to suit the perceived desires of government. When possible, informal discussions were used to complement survey data.</p>", "<p>There may be some economic activity that was not captured in this study. For example, it is likely that the purchase of some drugs from shops will be missed as it is illegal for drug sellers to sell antimalarial drugs. This direct cost is likely to be small in a poor area like Ninh Thuan where drugs are free to the patient in the public health services. It is also possible that informal payment may not have been reported given that it is known to be illegal. This could have a significant effect on the study results.</p>", "<p>Malaria challenges the productivity of this population year upon year, with the effect likely to be cumulative. The level of productivity that was calculated in this study to estimate income loss was the level of normal productivity minus the productivity loss estimated to result from an episode of malaria. This level of normal productivity is likely to be lower than it would be if malaria were not affecting household members year upon year. This means that the estimated total cost of 11.79 USD per episode is effectively underestimated and, conversely, that the gains that could be reaped in preventing malaria, over time, would be greater per episode.</p>" ]

[ "<title>Conclusion</title>", "<p>As in other parts of the world, malaria appears to impose a non-negligible economic burden on the household. Amongst farmers of the Raglay ethnic minority in Ninh Thuan, a south-central Vietnamese province with endemic forest malaria, this burden appears to be borne primarily in the form of indirect costs associated with decreased productivity. This loss is estimated to be approximately 11.10 USD per malaria episode. Due to take-up of government provision of services, direct costs remained low (0.69 USD), making up only 6% of the total. The total cost of illness was estimated at 11.79 USD per episode, a substantial burden for the poorest households in the community or for households experiencing multiple episodes.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Each year, several thousand cases of malaria occur in south-central Vietnam. Evidence from elsewhere suggests that malaria can have an economic impact on the household as the illness prevents households from completing their normal, physically demanding, productive duties such as tending crops and animals. The economic impact of malaria on households was explored within the Raglay ethnic minority living in the montainous and forested area of south-central Vietnam (Ninh Thuan Province).</p>", "<title>Methods</title>", "<p>Two-hundred fifty-one malaria patients were identified and interviewed in an exit survey at Community Health Centres. The same patient sample was then re-interviewed in a household survey two to four weeks later. Survey data were complemented by approximately 40 informal discussions with health workers, vendors, patients, and community leaders.</p>", "<title>Results</title>", "<p>Each episode of malaria was estimated to cost the patient's household an average of 11.79 USD (2005 prices), direct costs for travel and treatment representing 6% of the total while the remainder was loss in annual income.</p>", "<title>Conclusion</title>", "<p>Whilst government provision of malaria treatment keeps the direct costs relatively low, the overall loss in income due to illness can still be significant given the poverty amongst this population, especially when multiple cases of malaria occur annually within the same household.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>CMM designed the surveys, survey methodology, and helped in the initial training of health workers to conduct the surveys. NDT, NXX, LXH, PVK, AE, AJM and UA all contributed to survey design. NDT, NXX, LXH, LKT, PVK helped with logistics at both national and provincial level. NDT, NXX, and PVK trained health workers and supervised survey conduction. AE and NDT provided coordination between provincial, national, and international members of the research team. AJM supervised the study.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank the Belgium Cooperation for their support for this project.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Mean direct costs (USD) per malaria episode</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\">Travel*</td><td align=\"left\">Treatment*</td><td align=\"left\">Proportion of actual (non-trial) visits**</td></tr></thead><tbody><tr><td align=\"left\">Health facility (% of trial population attendance)</td><td/><td/><td/></tr><tr><td align=\"left\">Village Health Worker (1.6%)</td><td align=\"left\">0.08</td><td align=\"left\">0.97</td><td align=\"left\">60%</td></tr><tr><td align=\"left\">Community Health Centre (100%)</td><td align=\"left\">0.11</td><td align=\"left\">0.00</td><td align=\"left\">38%</td></tr><tr><td align=\"left\">Other treatment facility – hospital, private clinic, dispensary (3.2%)</td><td align=\"left\">0.96</td><td align=\"left\">0.19</td><td align=\"left\">2%</td></tr><tr><td align=\"left\">Mean total direct costs per episode under non-trial conditions</td><td/><td/><td align=\"left\">0.69 USD</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Mean time loss (workday equivalents) from treatment-seeking per malaria episode</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Health facility (% of trial population attendance)</td><td align=\"left\">Travel*</td><td align=\"left\">Treatment*</td><td align=\"left\">Proportion of actual (non-trial) visits **</td></tr></thead><tbody><tr><td align=\"left\">Village Health Worker (1.6%)</td><td align=\"left\">0.02</td><td align=\"left\">0.03</td><td align=\"left\">60%</td></tr><tr><td align=\"left\">Community Health Centre (100%)</td><td align=\"left\">0.03</td><td align=\"left\">0.16</td><td align=\"left\">38%</td></tr><tr><td align=\"left\">Secondary treatment – hospital, private clinic, dispensary (3.2%)</td><td align=\"left\">0.05</td><td align=\"left\">0.77</td><td align=\"left\">2%</td></tr><tr><td align=\"left\" colspan=\"3\">Mean workday equivalents lost per episode under non-trial conditions</td><td align=\"left\">0.14</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Mean annual agricultural and livestock assets and sales per household</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Crop</bold></td><td align=\"left\"><bold>Mean household production/year (kg)</bold></td><td align=\"left\"><bold>Proportion sold/year</bold></td><td align=\"left\"><bold>Local value </bold><bold>(USD per kg)</bold></td><td align=\"left\"><bold>Total value produced (USD)</bold></td><td align=\"left\"><bold>Total value sold </bold><bold>(USD)</bold></td></tr></thead><tbody><tr><td align=\"left\">Rice</td><td align=\"left\">435</td><td align=\"left\">64%</td><td align=\"left\">0.13</td><td align=\"left\">59.09</td><td align=\"left\">35.21</td></tr><tr><td align=\"left\">Maize</td><td align=\"left\">586</td><td align=\"left\">86%</td><td align=\"left\">0.10</td><td align=\"left\">55.76</td><td align=\"left\">47.98</td></tr><tr><td align=\"left\">Cashews</td><td align=\"left\">102</td><td align=\"left\">98%</td><td align=\"left\">0.60</td><td align=\"left\">61.62</td><td align=\"left\">60.41</td></tr><tr><td align=\"left\">Cassava</td><td align=\"left\">442</td><td align=\"left\">40%</td><td align=\"left\">0.05</td><td align=\"left\">21.45</td><td align=\"left\">8.64</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td/><td/><td/><td align=\"left\"><bold>193.83</bold></td><td align=\"left\"><bold>152.23</bold></td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\"><bold>Livestock</bold></td><td align=\"left\"><bold>Mean owned/household</bold></td><td align=\"left\"><bold>Sold/year</bold></td><td align=\"left\"><bold>Local value </bold><bold>(USD per unit)</bold></td><td align=\"left\"><bold>Total value owned (USD)</bold></td><td align=\"left\"><bold>Total value sold (USD)</bold></td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\">Chicken</td><td align=\"left\">8.3</td><td align=\"left\">3.30</td><td align=\"left\">2.13</td><td align=\"left\">17.65</td><td align=\"left\">7.02</td></tr><tr><td align=\"left\">Cow</td><td align=\"left\">3.0</td><td align=\"left\">0.70</td><td align=\"left\">250.17</td><td align=\"left\">750.52</td><td align=\"left\">175.12</td></tr><tr><td align=\"left\">Buffalo</td><td align=\"left\">0.2</td><td align=\"left\">0.04</td><td align=\"left\">250.17</td><td align=\"left\">50.03</td><td align=\"left\">10.01</td></tr><tr><td align=\"left\">Pig</td><td align=\"left\">1.8</td><td align=\"left\">0.70</td><td align=\"left\">24.27</td><td align=\"left\">43.68</td><td align=\"left\">16.99</td></tr><tr><td align=\"left\">Duck</td><td align=\"left\">0.5</td><td align=\"left\">0.10</td><td align=\"left\">1.94</td><td align=\"left\">0.97</td><td align=\"left\">0.19</td></tr><tr><td align=\"left\">Goat</td><td align=\"left\">0.1</td><td align=\"left\">0.02</td><td align=\"left\">45.34</td><td align=\"left\">4.53</td><td align=\"left\">0.91</td></tr><tr><td align=\"left\">Dog</td><td align=\"left\">0.2</td><td align=\"left\">0.02</td><td align=\"left\">9.38</td><td align=\"left\">1.88</td><td align=\"left\">0.19</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td/><td/><td/><td align=\"left\"><bold>869.26</bold></td><td align=\"left\"><bold>210.42</bold></td></tr></tbody></table></table-wrap>" ]

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[]

[ "<table-wrap-foot><p>*Data from survey of patients attending CHC</p><p>** Data from large passive case detection study [8]</p></table-wrap-foot>", "<table-wrap-foot><p>*Data from survey of patients attending CHC</p><p>** Data from large passive case detection study [8]</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Hepatitis C virus infection is hyper-endemic among injection drug user (IDU) populations [##REF##12558341##1##,##REF##9596383##2##], and evidence also suggests that excess HCV infection occurs in non-injection drug users (NIDUs) who administer heroin, cocaine, or amphetamine by other routes, such as inhalation or smoking [##UREF##0##3##,##REF##16102381##4##]. HCV is a significant cause of morbidity and mortality in IDUs [##REF##12407596##5##,##REF##7623656##6##], and a leading cause of death among IDUs co-infected with HIV [##REF##16338020##7##,##REF##16327326##8##].</p>", "<p>Once the hepatitis C virus was identified in 1989, the availability of serologic testing for HCV antibody (anti-HCV) led to a large number of studies of anti-HCV prevalence in IDUs during the 1990s. Four qualitative reviews of HCV epidemiology in IDUs were published by 2002; each summarized between 20 and 100 studies [##REF##12558341##1##,##REF##9596383##2##,##UREF##1##9##,##REF##12010503##10##]. These reviews noted relatively high incidences, ranging between 6 and 40 seroconversions per 100 person-years (PY) of follow-up; the median incidence rates across the four reviews were 9, 12, 16, and 16/100 PY. Anti-HCV prevalence varied substantially, between 30 and 90%. Some of this variation was clearly related to time at risk, with a fairly consistent and relatively linear relationship between number of years injecting and increasing anti-HCV prevalence [##REF##16251818##11##]. Geographic variability was also noted in these reviews, for example, higher mean HCV prevalence was found in studies of North American IDUs (82%), as compared to European (67%) or Australian/New Zealand IDUs (59%) [##UREF##1##9##]. Study year was also related to HCV prevalence, with the gradual emergence of reports of low-prevalence IDU samples in the literature. Altogether, research suggested that HCV infection varied in IDU populations in relation to characteristics of person, place and time, and that insights into HCV prevention might be obtained via a systematic, quantitative review of available studies.</p>", "<p>Fewer studies of HCV epidemiology have been conducted among NIDUs than among IDUs, and the etiology of HCV transmission in this population is not as well-understood, although some believe that exposure to HCV-positive blood occurs as a result of the shared use of pipes or straws to administer the drug [##REF##14986874##12##]. Excess HCV in NIDUs has been shown in a number of studies, with HCV prevalence reported between 1 and 35% [##REF##17174481##13##], compared to 1.8% anti-HCV prevalence in the general population [##UREF##2##14##]. Very few NIDU studies have closely examined route of HCV exposure, principally because they used a cross-sectional design, thus weakening the interpretation of a causal link between risk factors and incident infection. Consistency in findings across studies, or consistency in explanation for variation across studies, may support an underlying causal relation between these forms of drug use and HCV.</p>", "<p>A recent qualitative review showed that studies of strategies to prevent HCV infection in IDUs had inconsistent results, with few examples of interventions that reduce HCV transmission. Moreover, the majority of studies had small sample sizes [##REF##16251818##11##]. Most HCV prevention efforts thus far have used strategies shown to decrease HIV transmission in drug users, including drug treatment, voluntary counseling and testing, and needle exchange programs. It appears that their effect on HCV infection may be attenuated by several factors, particularly that HCV is more highly prevalent than HIV in IDU populations so that the probability of injecting with an HCV-infectious IDU is greater than injection with an HIV-positive injector. Additionally, there are many more materials used to inject or prepare drugs that may transmit HCV infection in the injection setting. Specifically, the shared use of syringes has been demonstrated to transmit HIV and HCV, but other equipment used to prepare drugs for injection (drug cookers and filtration cotton) may also transmit HCV [##REF##9703523##15##, ####REF##11189822##16##, ##REF##11914192##17##, ##REF##11431749##18####11431749##18##]. Nonetheless, despite the lack of evidence showing an individual-level effect of various prevention strategies on risk of HCV infection, declining HCV prevalence has been observed in settings where comprehensive HIV prevention for drug users is widely available (such as large-scale syringe exchange and access to drug treatment) [##REF##11450866##19##,##REF##11189821##20##]. Altogether, the published literature suggested that a synthesis of research on the epidemiology and prevention of HCV in drug user populations was needed to examine etiologic factors and drug or sexual practices that may reduce risk of HCV transmission, and to identify gaps in the literature.</p>", "<p>This article describes the scientific scope of this systematic research synthesis study, the criteria used to select reports to include in the study, the methodology used to identify and code relevant reports, the system employed to assure accuracy and consistency in all phases of the project, and a summary of the study sample. Other phases of the research synthesis study are also described. Finally, our protocol for evaluating indicators of study quality and the studies in our sample are summarized.</p>", "<title>Scope of the project</title>", "<p>We undertook the task of systematically reviewing all studies describing the epidemiology of hepatitis C in drug-user populations to address questions regarding factors that are associated with variability in HCV transmission. The scope of this study, \"Synthesis: A meta-analysis of HCV epidemiology and prevention in drug users\" (the HCV Synthesis Project) encompasses published and unpublished reports from the US and abroad describing the epidemiology of HCV infection (incidence and prevalence), the molecular epidemiology of HCV genotypes, and the co-occurrence of HIV, HCV and other hepatitis virus infections in drug users. Measures of association between HCV prevalence and incidence and factors such as risk behavior and participation in prevention programming are also collected. The population of interest includes injection drug users, and non-injection drug users of heroin, cocaine and amphetamine, because these groups of individuals have been identified as having a biologically plausible risk of exposure to HCV via drug use, including percutaneous exposure (via injection drug use) and mucous membrane exposure to HCV-positive blood via sharing of straws or pipes used to administer drugs (non-injection drug use). Data from IDU and NIDU studies are analyzed separately, as they differ substantially in the likelihood of HCV infection, and because their drug-related risk factors are quite dissimilar. In addition, a higher proportion of HCV infections in NIDUs vs. IDUs may be attributable to sexual rather than drug-related exposures, because there is less evidence to support specific drug-related transmission among NIDUs [##REF##12064440##22##].</p>", "<p>Another goal of the meta-analysis is to examine the influence of study methodology on study findings, particularly because the descriptive epidemiology of HCV may be strongly influenced by sampling methods, and because study design may affect associations between various characteristics and HCV infection. Since HCV antibody testing is a recent development (1989), it is possible to carry out a relatively complete synthesis covering approximately 18 years (1989–2006) of research studies that have reported incidence, prevalence and measures of association with HCV infection in drug users. Consistent with the fundamental goals of meta-analysis, the purpose of this study is to generate summary data, describe variation in HCV epidemiology, resolve inconsistencies in findings, and identify areas of future research.</p>" ]

[ "<title>Methods</title>", "<title>Search strategy</title>", "<p>Automated searches of published literature were carried out on electronic databases (MEDLINE, PsychInfo, ERIC, Dissertation Abstracts, Sociological Abstracts, and Current Contents) using the following search terms: (hepatitis C OR HCV) AND (intravenous drug abuse OR intravenous drug use OR drug misuse OR drug addict OR injecting drug use OR drug abuse OR IDU) AND (prevention OR risk factor OR epidemiology OR prevalence OR incidence OR seroprevalence OR seroincidence OR genotype OR co-infect* OR coinfect*). We performed searches in these electronic databases at six month intervals.</p>", "<p>Manual search methods included the retrieval of sources cited by seminal articles about HCV in drug-user populations, and hand searching of journals. We compiled a list of scientific journals that have either published articles on HCV epidemiology and prevention, or might conceivably publish such articles based on a history of publishing articles in a similar field (HIV epidemiology, for example). Internet searches of government websites (including local, state and national public health websites in the US; provincial, national and ministry of health websites in other countries; and websites for international health or drug control organizations) were carried out to locate government reports and unpublished surveillance estimates.</p>", "<p>Books of abstracts and proceedings from scientific conferences related to hepatitis, HIV, infectious diseases and harm reduction were also searched for eligible reports, using both the index of key words and by reading through the abstracts of presentations. The NIH CRISP database was also used to identify ongoing or recently completed studies relevant to our meta-analysis; names of investigators identified in CRISP were periodically entered into the electronic databases to identify publications that might conceivably report on measures of interest. Consultants to the study were enlisted to submit reports from their own studies or from other studies they had learned about through professional contacts at conferences or other meetings; these consultants included investigators who were carrying out research related to HCV in drug users in the US, Europe, Asia, Africa, the Middle East and Australia/New Zealand.</p>", "<title>Study selection</title>", "<p>Throughout this description of study methods, we use the term data report to refer to published and unpublished articles, manuscripts, personal communication, dissertations, abstracts, conference presentations and book chapters that are reviewed for inclusion in the study sample. Data reports available through the end of 2006 were included in the search; study retrieval and coding began in August, 2004.</p>", "<p>To be included in our study, data reports must have included in their sample individuals who could conceivably have acquired HCV infection via administration of an illegal drug, i.e., injection drug users, or non-injection drug users who snort, sniff or smoke heroin, cocaine, amphetamines or other drugs using straws or pipes. Marijuana smokers were not included in the study as there are no epidemiologic data to indicate excess HCV in marijuana smokers. Similarly, those who administered amphetamines or other illicit drugs orally (i.e., took pills) were also excluded as there is no biologically plausible route of HCV transmission associated with this practice.</p>", "<p>Only those reports from which we could abstract estimates of HCV prevalence, incidence, measures of association, HIV/HCV co-infection or HCV genotype distributions for drug users were included. Further, reports must have given separate estimates for IDUs and NIDUs, as these rates were expected to vary greatly between these two risk groups. Thus, studies that aggregated IDUs and NIDUs in estimates of prevalence, incidence or measures of association were not included in this review. HCV status must have been determined by serologic testing of either sera or saliva; studies that used self-reported HCV antibody status, or those that tested for HCV RNA without reporting the results of anti-HCV testing were excluded.</p>", "<p>Each data report could have one or more of the following types of studies associated with it: HCV prevalence studies, HCV incidence studies, HCV genotype studies or studies of HCV co-infection with HIV or other hepatitis viruses. Within a single report, each of these types of studies could appear and be counted as an individual study by our definition. A report was also defined as having multiple studies when epidemiologic estimates were given for subgroups of individuals distinguished by different methodology (e.g., enrollment criteria, sampling location or sampling method) or were reported as separate samples with different demographic characteristics or inclusion criteria. For example, a study in IDUs that spanned five years, and presented all their data (sample demographics and HCV prevalence) for each year of data collection was counted as five prevalence studies. Separating the data into individual studies permitted the collection of sample characteristics or methodological features associated with the subset of subjects being examined.</p>", "<title>Screening</title>", "<p>A pilot study was carried out to test and develop procedures for screening titles and abstracts to identify data reports that would be eligible to be retrieved, and to estimate an expected sample size (the number of data reports that would provide data to address the aims). In October 2003, we conducted a Medline search using the keywords mentioned above; this search retrieved 1324 articles. Abstracts we obtained from a 5% random sample of these articles (n = 63) and three study staff (the PI, a co-investigator and a research assistant) independently pre-screened each title and abstract. Of necessity, the criteria for screening were broad so as to reduce the likelihood of missing relevant studies, but it was also desirable that screening have relatively high specificity to avoid retrieving a large number of irrelevant studies.</p>", "<p>The screening criteria were: 1) sample included IDU or NIDU, and 2) study reported any parameters of epidemiology (incidence or prevalence of HCV-antibody or HCV-genotype), HIV/HCV co-infection, or measures of association. For this pilot, studies must also have been written in English. Initially, there was 80% agreement as to whether the article should be retrieved. Screening criteria were discussed and revised to reach consensus in their application.</p>", "<p>Beginning in August 2004, we followed the process developed in the pilot study to screen abstracts to determine whether a report was eligible in terms of its sample and the data it provided. For the reports whose abstracts deemed them potentially eligible, the full text was reviewed to determine whether it truly met our inclusion criteria. Each abstract or report was screened for eligibility by both a senior research assistant and the project director. Screening sought to eliminate studies that were clearly unrelated to the scope of the project. In cases where it could not be definitively determined whether a report was eligible based on reading the abstract, the full text article was retrieved and reviewed for eligibility. When the full text of an article was not available in English, Spanish, or Italian, the English-language Medline abstract of the article was used for coding.</p>", "<p>It was common to find multiple HCV-related reports originating from a single large research project such as ALIVE, VIDUS, CIDUS, RAVEN and many others [##REF##12615611##23##, ####REF##16251819##24##, ##REF##9927214##25##, ##REF##11189822##26##, ##REF##12198668##27##, ##REF##15167294##28##, ##REF##11599327##29##, ##UREF##3##30####3##30##]. Thus, several methods were used to identify duplicate or overlapping reports (for example, recording study names and searching our reference manager database for other reports by the same author or set of authors). These potentially-overlapping reports were identified but retained in the database, as some reports included analyses of different sets of factors or subsets of the study sample. Duplicate estimates of the same parameters for the same datasets will be excluded prior to each data analysis project. (Figure ##FIG##0##1## shows a decision tree of our study selection and screening process.)</p>", "<title>Coding</title>", "<p>The coding was carried out by senior research assistants who had graduate training in research methodology, and received additional training in HCV epidemiology, drug use and meta-analytic methods. The content and structure of the coding form was developed by reviewing those used in other meta-analyses, for example, the CDC Prevention Research Synthesis Project [##REF##12107357##31##] and the Self-Report/Biological Measures database of Drug Use [##UREF##4##32##] The coding form included items such as the type of study or studies included in the body of the report (prevalence, incidence, co-infection or genotype study), study methods (design, inclusion criteria, recruitment method, recruitment locations, method of determining IDU/NIDU status, specimen type, and HCV test method), and demographics and other characteristics of the sample such as duration of drug use, type of drugs used, and frequency of use.</p>", "<p>We collected all data related to HCV prevalence and incidence, i.e., all numerators and denominators, including both numbers and proportions of subjects and numbers of person-years, to allow us to combine data from separate studies in subsequent analyses. Anti-HCV prevalence and incidence estimates, relative risks and odds ratios (both crude and adjusted, with their 95% confidence intervals) were also collected in relation to sample characteristics. Simple calculations were made when necessary, and any approximations which were recorded (such as numbers estimated from reading a figure) were marked as such.</p>", "<p>In some cases, the statistics recorded were simple measures of overall HCV prevalence or incidence for the entire eligible sample, while in other cases prevalence or incidence measures were reported within highly restricted subgroups defined by a number of variables such as age, gender, race and type of drug used. The coding form was structured so that we could abstract both simple and complicated overall estimates and sub-group comparisons, and therefore accommodate varying degrees of complexity in the data.</p>", "<p>Thus, the coding form included fields for a number of pre-defined categories of gender, race/ethnicity, drug use, and risk behavior categories such as receptive and distributive syringe sharing, the shared use of drug preparation equipment (e.g., drug cooker, filtration cotton and rinse water), the use of a syringe to divide drugs, giving or receiving injections, injection in prison or jail, and participation in prevention activities such as drug treatment or syringe exchange programs. Sexual risk behavior data was also collected, for example, number of sexual partners, unprotected sex, commercial sex work and having an IDU sex partner. For each of these risk categories describing behavior, we recorded the referent time period used. There were also fields included in the coding form intended to capture relevant data that did not conform to our preset categories.</p>", "<p>We did not record measures such as odds ratios comparing HCV prevalence or incidence in IDUs to that among NIDUs or non-drug users, as there is clear evidence that injection drug use is a highly potent risk behavior for HCV acquisition, and comparisons among such populations would not contribute new knowledge to our understanding of HCV epidemiology.</p>", "<title>Quality assurance methods</title>", "<p>A number of strategies were used in the course of this study to ensure reliable, valid and consistent coding of data. For example, each data report coded by a research assistant was subsequently reviewed for accuracy and completeness by the Project Director and the Principal Investigator. The coders made any necessary changes to the coding before the report was considered complete. Any differences of opinion among the study group members were settled by discussion at a weekly study meeting convened for this purpose. A study manual was developed to guide coding and to record special cases and their resolution.</p>", "<title>Backcoding</title>", "<p>Once a significant portion of the published data had been coded (October 2005), the research assistants conducted a data-coding reliability sub-study. A 10% sample of eligible coded reports was selected and re-coded by a different coder and all discrepancies in coding were noted and summarized. This project was undertaken to establish whether (1) any changes in coding rules had occurred over the course of the study, (2) there were any systematic differences between coders or (3) there were any specific items that may have been inconsistently coded. This reliability project revealed that two items (recruitment method and recruitment location) were inconsistently coded. Our review of the text of the reports revealed that variation between coders was principally due to a lack of clarity in the presentation of this information across a significant number of reports. Coding rules for these two variables were discussed and re-defined, and these items were back-coded for all articles.</p>", "<title>Contacting Authors</title>", "<p>When the text or abstract of an article or conference presentation indicated that measures of interest to our study had been collected but were not reported, we contacted authors to request the information. These requests were limited to simple descriptive data such as separate estimates of HCV prevalence or incidence for IDUs vs. NIDUs, or to ask for the numerator or denominator used to estimate incidence or prevalence. We did not ask for additional analyses of data. Authors were contacted only if the report had been published or presented less than five years before the coding date. Overall, we contacted just over 100 authors, and 42% of authors we contacted sent a reply to the request for data. Of those who replied, 70% provided data that could be included as part of the meta-analysis.</p>", "<title>Unpublished data</title>", "<p>We also searched subject indexes of conference proceedings (abstracts) on paper, CD-ROM or various websites. The conferences included were annual meetings of the American Association for the Study of Liver Diseases, the Society for Epidemiologic Research, the American Public Health Association, the International AIDS Society, the National Harm Reduction Conference, the International Conference on the Reduction of Drug Related Harm, the College on Problems of Drug Dependence, International Society for Infectious Diseases, and the American Sociological Association. Investigators from the study also attended a number of these conferences and collected copies of presentations and other unpublished reports. These abstracts were screened and the data were coded by the same process we used for published abstracts and articles.</p>", "<p>Substantial effort was devoted to ascertaining whether the data in the unpublished literature duplicated any reports that had been previously coded. This step involved cross-checking of authors of unpublished studies against our database and in PubMed. When matches were found, the unpublished literature was compared to the published report to identify whether they overlapped in terms of location, number of subjects, and year of data collection. Approximately half of the conference abstracts that appeared to be codeable were subsequently eliminated because there was a published article with overlapping data.</p>", "<title>Study quality measures</title>", "<p>We followed the recommendation of the MOOSE group [##REF##10789670##21##] that meta-analyses of observational studies evaluate certain elements of each included study indicative of their quality. Thus, we devised a number of 'quality' items to assess whether each study's design and implementation was clearly explained and appropriate for the claims made in the reports. Our scale rated several study factors likely to affect findings of HCV prevalence, incidence and co-infection in drug user populations, including the rigor with which the investigators handled the problem of misclassification with respect to route of drug administration. Additionally, the quality scale assessed some aspects of the overall design and methodology of the studies, such as sample size, reporting of demographics, presence of inclusion or exclusion criteria, participation rate, adjustment for confounding, and consistency in reporting data. Sources of bias in study methods have been demonstrated to account for heterogeneity in results in meta-analyses [##REF##10789670##21##].</p>", "<p>An initial list of quality criteria was developed by the research team to assess NIDU studies included in a paper published by our group [##REF##17174481##13##]. The quality criteria for the IDU sample were modeled on the NIDU quality scale. A detailed description of the NIDU quality scale can be found in Scheinmann et al. [##REF##17174481##13##]. For the complete list of quality items used for evaluating IDU studies, see Table ##TAB##0##1##.</p>", "<p>To determine whether the items in our quality scale were internally consistent we performed Cronbach's alpha reliability analyses using two-thirds of the data from the HCV Synthesis Study. The 19-item scale had an alpha value of 0.73, reflecting adequate scale coherence. Removal of items with low item-total correlations did not improve the alpha. The distribution of the quality scale scores was bimodal. Quality was then recoded dichotomously by splitting between the modes.</p>" ]

[ "<title>Results</title>", "<p>Overall, the HCV Synthesis Project has identified 2384 reports through the electronic search terms. Of those, 948 (40%) reports appeared to be eligible for coding. In most cases of ineligible reports, it was immediately apparent that the reports were review articles, were not reporting any original data, or did not report any data on either IDUs or NIDUs. 319 reports were initially classified as codeable, but were disqualified upon closer review. The main reasons for disqualification were 1) no HCV prevalence or incidence data (n = 71); 2) drug user prevalence data aggregated, i.e., IDU and NIDU estimates were not disaggregated or distinguished from non-drug users (n = 64); 3) sample selection based on HCV status (n = 56); 4) results based on HCV-RNA testing alone (n = 9); and 5) self-reported HCV status was basis for prevalence estimates and no lab testing was performed (n = 26). Other reasons for disqualification of reports were that no drug users were included in the report; data were incomplete for coding; the article included only a mathematical model; or the article was a review and did not include original data.</p>", "<p>Thus, 629 codeable reports containing HCV prevalence rates, incidence rates and/or genotype distribution in injecting or non-injecting drug user populations published between January 1989 and December 2006 were identified. Each report contained one of more of the following types of information: prevalence rates, incidence rates, genotype distributions and/or coinfection information. Of the 629 eligible reports (some of which included more than one of the following types of statistics), 520 reported HCV prevalence statistics, 62 reported incidence statistics, and 118 reported genotype distribution. Further, 345 also reported co-infection with HIV, HBV or HAV.</p>", "<p>Of note, a given report (e.g., a published article) may contain more than one study if it provides separate data for samples collected in different locations, time periods and/or with different demographic data. Therefore, one report may contain multiple studies, of either the same type (two prevalence studies, for example) or different types (a prevalence study and an incidence study, for example). We have 794 studies overall, consisting of 599 prevalence studies, 72 incidence studies and 123 genotype studies.</p>", "<p>Fewer than 10% of the reports included data on individuals meeting our definition of NIDUs. More than 95% of all eligible reports were identified through Medline searches. (Note that these numbers of reports do not eliminate overlapping reports from single studies.)</p>", "<p>As shown in figure ##FIG##1##2##, the number of publications reporting HCV prevalence in IDUs rose from 1–11 reports per year from 1989 to 1991, to 19–22 reports per year from 1992–1997, 33 reports in 1998, and between 27–52 reports per year after 1998.</p>", "<p>The number of seroincidence reports in IDUs has risen more slowly and typically remained below seven per year, although in 2004 there were ten seroincidence reports. The number of HCV genotype studies among IDUs has ranged between 4 and 16 per year since 1994. The number of reports of HCV prevalence in NIDU samples per year has fluctuated between zero and ten. Genotype and seroincidence in NIDUs are rarely reported, with no more than one report in any given year (data not shown).</p>", "<p>The majority of reports collected data from western Europe (41%), North America (26%), Asia (11%) and Australia/New Zealand (10%). We also identified reports which collected data from Eastern Europe (5%), South America (4%), the Middle East (2%) and the Caribbean (0.3%). For a listing of the distribution of reports in the synthesis sample by country, see Table ##TAB##1##2##.</p>" ]

[ "<title>Discussion</title>", "<p>Electronic searches of the published literature retrieved a substantial number of reports on the epidemiology of HCV infection in drug users. The fact that nearly all eligible reports were discovered via Medline searches suggests that study data are relatively accessible for a meta-analysis. Our search of the unpublished data has so far retrieved relatively few additional reports. This is much higher than the 50% expected hit-rate using electronic databases [##REF##10789670##21##]. Thus, exclusion of pertinent data due to publication bias or other types of systematic omissions from our study sample are unlikely to be of sufficient magnitude to substantially bias our findings. Funnel plots and other methods will be used to systematically examine publication bias (to judge whether studies with small samples and low HCV prevalence are missing from the literature).</p>", "<p>The number of studies and reports related to HCV in injection drug users has been increasing over time, particularly since 1995. Cross-sectional prevalence studies make up the majority of reports we identified; these will be useful in terms of identifying characteristics of person, place and time associated with extreme rates of HCV prevalence. Because cross-sectional surveys are commonly used to characterize the epidemiology of HCV and other conditions in local drug user populations, understanding whether sampling methodology is associated with prevalence will help guide inferences regarding these data. The number of seroincidence reports has grown over recent years, and this relatively large sample (n = 62) should permit greater exploration of sources of variability in seroconversion rates. Synthesis of co-infection studies reporting HCV, HBV and HIV infection rates will provide insight into the joint occurrence of these infections and factors associated with similarities in their epidemiology in drug users. Co-infection data and HCV genotype information will be relevant to health care planning, particularly the treatment of HIV/HCV co-infection and HCV mono-infection in drug users.</p>", "<p>The scope and aims of the HCV Synthesis Project differ from typical meta-analyses which seek to combine effect sizes arising from studies of interventions or treatments. Nonetheless, we adapted standard approaches to meta-analysis [##UREF##5##33##] to synthesize parameters of epidemiology. The challenges we encountered in collecting and coding these data include lack of standard reporting of risk factor data, overlapping publication of data, and missing details on study methodology. One notable finding from our summary of the HCV Synthesis Project data is that future research reports can enhance their contributions to our understanding of HCV epidmiology by clearly defining their drug user participants with respect to type of drug and route of administration, and by analyzing and reporting data separately in injection and non-injection users of drugs. (Figure ##FIG##2##3## summarizes recommendations for future research on HCV among drug user populations.)</p>", "<p>Had more studies disaggregated IDU and NIDU data, our sample of NIDU studies would have potentially doubled (provided that the NIDU sample fit our definition of non injection drug users who sniff, snort, or smoke hard drugs). Unfortunately, a large number of studies that were ineligible for this reason were from developing countries for which HCV data are scarce. The use of standard reporting methods, as promulgated by MOOSE [##REF##10789670##21##], would enable data to be combined across a larger set of studies; this is especially important for HCV seroconversion studies which suffer from small sample sizes and low power to examine risk factors. MOOSE developed recommendations for meta-analyses of observational studies of interventions and etiologic factors. In general, we have followed their recommendations adapted to our specific research questions and the field of drug use related research. For example, we did use broad inclusion criteria which has yielded a large sample size.</p>", "<p>Despite the fact that meta-analysis is traditionally used to combine results from randomized studies, such as randomized control trials, the use of meta-analysis to combine results from observational studies is becoming widespread because of the many issues in public health which cannot be studied without the use of observational designs. In order to apply meta-analytic techniques to sets of observational studies, it is necessary to develop homogeneous subsets, so that confounding factors do not overly influence the meta-analytic results [##UREF##6##35##]. Heterogeneous sets of studies may be systematically described and sources of confounding or bias can be elucidated.</p>" ]

[ "<title>Conclusion</title>", "<p>Overall, we believe it will be essential to use meta-analysis to address outstanding questions regarding HCV prevention. Because individual studies have failed to find evidence of specific protective factors for HCV in drug users (especially IDUs) and the etiology of HCV transmission in NIDUs remains somewhat vague, meta-analysis may prove to be highly useful in addressing endemic HCV in drug users. For instance, combining data across seroconversion studies would substantially increase the ability to detect consistent and statistically significant risk factors. Additionally, identifying in more detail the relationship between HCV prevalence and incidence and number of years injecting is essential for honing and targeting prevention efforts [##REF##9462324##34##].</p>", "<p>For the HCV Synthesis Project, the data set is complete and data analysis is in process. A report on HCV in NIDUs is published [##REF##17174481##13##]; a preliminary analysis of the relationship of gender, duration and age to HCV in IDUs is in press [##REF##9462324##34##]; and a report on the relationship of racial and ethnic status to HCV in IDUs is in preparation. Future analyses in preparation will focus on complex questions of variability in HCV prevalence and incidence in injection drug users. It is anticipated that this study will help to summarize the state of HCV knowledge, identify new research questions or those that need additional confirmation, and may point towards promising HCV prevention strategies.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The hepatitis C virus (HCV) is hyper-endemic in injecting drug users. There is also excess HCV among non-injection drug users who smoke, snort, or sniff heroin, cocaine, crack, or methamphetamine.</p>", "<title>Methods</title>", "<p>To summarize the research literature on HCV in drug users and identify gaps in knowledge, we conducted a synthesis of the relevant research carried out between 1989 and 2006. Using rigorous search methods, we identified and extracted data from published and unpublished reports of HCV among drug users. We designed a quality assurance system to ensure accuracy and consistency in all phases of the project. We also created a set of items to assess study design quality in each of the reports we included.</p>", "<title>Results</title>", "<p>We identified 629 reports containing HCV prevalence rates, incidence rates and/or genotype distribution among injecting or non-injecting drug user populations published between January 1989 and December 2006. The majority of reports were from Western Europe (41%), North America (26%), Asia (11%) and Australia/New Zealand (10%). We also identified reports from Eastern Europe, South America, the Middle East, and the Caribbean. The number of publications reporting HCV rates in drug users increased dramatically between 1989 and 2006 to 27–52 reports per year after 1998.</p>", "<title>Conclusion</title>", "<p>The data collection and quality assurance phases of the HCV Synthesis Project have been completed. Recommendations for future research on HCV in drug users have come out of our data collection phase. Future research reports can enhance their contributions to our understanding of HCV etiology by clearly defining their drug user participants with respect to type of drug and route of administration. Further, the use of standard reporting methods for risk factors would enable data to be combined across a larger set of studies; this is especially important for HCV seroconversion studies which suffer from small sample sizes and low power to examine risk factors.</p>" ]

[ "<title>Abbreviations</title>", "<p>The following abbreviations are used in the body of the text: HCV: Hepatitis C Virus; IDU: Injection Drug User; NIDU: Non Injection Drug User; MOOSE: Meta-analysis of Observational Studies in Epidemiology study group; PY: Person Years; HIV: Human Immunodeficiency Virus; HBV: Hepatitis B Virus; HAV: Hepatitis A Virus.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>HH designed the meta-analysis described here, with consultation from DDJ, SS, and PF. HH wrote the first draft of this manuscript. RKS subsequently revised and completed the manuscript. CLW, RS, and DDJ contributed to and revised this manuscript. SS and PF made revisions to the manuscript. EP conducted the statistical analyses for the quality scoring process. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2288/8/62/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>This research was funded by NIDA Grant Number R01 DA018609. NIDA had no role in study design; in the collection, analysis or interpretation of the data; nor in the writing or submission of the manuscript. The authors would like to thank colleagues at the Center for Drug Use and HIV Research for their support and assistance.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>HCV Meta-Analysis Project Phases.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Number of reports per year describing HCV prevalence, incidence or genotype distribution in injection drug users in the HCV Synthesis Project.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Recommendations for future research on HCV in drug-user populations.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Quality Measure</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Quality/rigor/relevance of IDU data in studies included in HCV meta-analysis</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Type of study</bold></td></tr><tr><td/></tr><tr><td align=\"left\"><bold>Issues related to studying IDUs</bold></td></tr><tr><td align=\"left\">Was one of the stated aims to study the disease in IDUs or drug users (literature indicates interest to study HCV in IDUs)?</td></tr><tr><td align=\"left\">Sample composition (1 = non-drug users and drug users; 2 = NIDUs and IDUs; 3 = mostly IDUs; 4 = only IDUs)</td></tr><tr><td align=\"left\">Was there a method for minimizing misclassification bias (e.g., track marks or multiple interview questions)?</td></tr><tr><td/></tr><tr><td align=\"left\"><bold>Methodological issues</bold></td></tr><tr><td align=\"left\">Were dates of data collection given?</td></tr><tr><td align=\"left\">Were the selection criteria for the sample well defined and explained?</td></tr><tr><td/></tr><tr><td align=\"left\">Were details of recruitment methods given?</td></tr><tr><td align=\"left\">Were details of recruitment location given?</td></tr><tr><td align=\"left\">Were there any incentives offered to the participants?</td></tr><tr><td align=\"left\">Were participation rates given for the IDU sample?</td></tr><tr><td align=\"left\">What was the participation rate?</td></tr><tr><td align=\"left\">Did data collection methods change during the study (e.g., recruitment method; face-to-face interviewing vs. self-administered questionnaire; testing method; etc)</td></tr><tr><td align=\"left\">Were the statistical methods used stated (for contrasts and/or measures of association)?</td></tr><tr><td align=\"left\">What was the IDU sample size tested for HCV prevalence (denominator)?</td></tr><tr><td align=\"left\">Were the number of subjects and percentages consistent?</td></tr><tr><td align=\"left\">Were age characteristics given for the IDU sample?</td></tr><tr><td align=\"left\">Were gender characteristics given for the IDU sample?</td></tr><tr><td align=\"left\">Were race/ethnic characteristics given for the IDU sample?</td></tr><tr><td align=\"left\">Were duration of injection data given for the IDU sample?</td></tr><tr><td/></tr><tr><td align=\"left\"><bold>Issues related to IDU-specific behaviors/characteristics</bold></td></tr><tr><td align=\"left\">Were there univariate analyses of prevalence?</td></tr><tr><td align=\"left\">Were there multivariate analyses of prevalence?</td></tr><tr><td align=\"left\">Was HIV prevalence given?</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Number of Reports per Country</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\" colspan=\"3\">Geographical Location of Studies in HCV Synthesis Project</td></tr><tr><td align=\"left\">Country</td><td align=\"right\">Number of Reports</td><td align=\"right\">Percentage</td></tr></thead><tbody><tr><td align=\"left\">Argentina</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">Australia</td><td align=\"right\">56</td><td align=\"right\">8.9%</td></tr><tr><td align=\"left\">Austria</td><td align=\"right\">8</td><td align=\"right\">1.3%</td></tr><tr><td align=\"left\">Bangladesh</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">Belgium</td><td align=\"right\">7</td><td align=\"right\">1.1%</td></tr><tr><td align=\"left\">Bosnia and Herzegovina</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Brazil</td><td align=\"right\">20</td><td align=\"right\">3.2%</td></tr><tr><td align=\"left\">Bulgaria</td><td align=\"right\">2</td><td align=\"right\">0.3%</td></tr><tr><td align=\"left\">Canada</td><td align=\"right\">22</td><td align=\"right\">3.5%</td></tr><tr><td align=\"left\">China</td><td align=\"right\">17</td><td align=\"right\">2.7%</td></tr><tr><td align=\"left\">Croatia</td><td align=\"right\">2</td><td align=\"right\">0.3%</td></tr><tr><td align=\"left\">Czech Republic</td><td align=\"right\">5</td><td align=\"right\">0.8%</td></tr><tr><td align=\"left\">Denmark</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Egypt</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">England</td><td align=\"right\">20</td><td align=\"right\">3.2%</td></tr><tr><td align=\"left\">Estonia</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Finland</td><td align=\"right\">2</td><td align=\"right\">0.3%</td></tr><tr><td align=\"left\">France</td><td align=\"right\">22</td><td align=\"right\">3.5%</td></tr><tr><td align=\"left\">Georgia</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Germany</td><td align=\"right\">19</td><td align=\"right\">3.0%</td></tr><tr><td align=\"left\">Greece</td><td align=\"right\">9</td><td align=\"right\">1.4%</td></tr><tr><td align=\"left\">Haiti</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Hong Kong</td><td align=\"right\">2</td><td align=\"right\">0.3%</td></tr><tr><td align=\"left\">Hungary</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Iceland</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">India</td><td align=\"right\">7</td><td align=\"right\">1.1%</td></tr><tr><td align=\"left\">Iran</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Ireland</td><td align=\"right\">13</td><td align=\"right\">2.1%</td></tr><tr><td align=\"left\">Israel</td><td align=\"right\">2</td><td align=\"right\">0.3%</td></tr><tr><td align=\"left\">*Italy</td><td align=\"right\">47</td><td align=\"right\">7.5%</td></tr><tr><td align=\"left\">Japan</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">Lebanon</td><td align=\"right\">2</td><td align=\"right\">0.3%</td></tr><tr><td align=\"left\">Malaysia</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">Martinique</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Mexico</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Multiple</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Nepal</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">New Zealand</td><td align=\"right\">8</td><td align=\"right\">1.3%</td></tr><tr><td align=\"left\">Norway</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">Pakistan</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Philippines</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Poland</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Portugal</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Russia</td><td align=\"right\">11</td><td align=\"right\">1.8%</td></tr><tr><td align=\"left\">Saudi Arabia</td><td align=\"right\">4</td><td align=\"right\">0.6%</td></tr><tr><td align=\"left\">Scotland</td><td align=\"right\">20</td><td align=\"right\">3.2%</td></tr><tr><td align=\"left\">Slovenia</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">*Spain</td><td align=\"right\">46</td><td align=\"right\">7.3%</td></tr><tr><td align=\"left\">Sweden</td><td align=\"right\">12</td><td align=\"right\">1.9%</td></tr><tr><td align=\"left\">Switzerland</td><td align=\"right\">7</td><td align=\"right\">1.1%</td></tr><tr><td align=\"left\">Syria</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr><tr><td align=\"left\">Taiwan</td><td align=\"right\">9</td><td align=\"right\">1.4%</td></tr><tr><td align=\"left\">Thailand</td><td align=\"right\">13</td><td align=\"right\">2.1%</td></tr><tr><td align=\"left\">The Netherlands</td><td align=\"right\">10</td><td align=\"right\">1.6%</td></tr><tr><td align=\"left\">UK</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">USA</td><td align=\"right\">139</td><td align=\"right\">22.2%</td></tr><tr><td align=\"left\">Uzbekistan</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Vietnam</td><td align=\"right\">3</td><td align=\"right\">0.5%</td></tr><tr><td align=\"left\">Wales</td><td align=\"right\">1</td><td align=\"right\">0.2%</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>* Since we coded articles in Spanish and Italian, as well as English language articles, reports from Italy and Spain may be over-represented in comparison to reports from other countries outside the US.</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Data that are highly reliable and complete are essential to unbiased, high-quality research studies [##REF##3201042##1##,##REF##7261636##2##]. While poor statistical analyses can be run again, \"...a badly designed study with inferior data is beyond the redemption of the most sophisticated statistical technique\" [##REF##11126691##3##]. Prospective data collection gives researchers control over the quality of their data. Mistakes and omissions are likely to occur, however, regardless of how well-designed the study and how careful the study personnel [##REF##3201042##1##,##REF##7261636##2##]. Thus, it is essential that researchers develop and implement procedures to minimize data loss, identify concerns soon after data are collected, and detect and correct errors [##REF##3201042##1##,##REF##7261636##2##,##REF##3802845##4##,##UREF##0##5##]. \"No study is better than the quality of the data\" [##REF##8775751##6##].</p>", "<p>If detection of data errors is delayed, they become more difficult to correct [##REF##3802845##4##,##REF##8775751##6##,##REF##3755669##7##]. Possible sources of error occur throughout a study, and include deviations from the study protocol; inaccurate equipment; poorly designed forms; illegible, inaccurate, or incomplete data recording; errors or omissions in data transfer; inadequate training; intentional fraud; undocumented changes; programming errors; and misuse of statistical software [##REF##7789140##8##]. It is therefore essential that data quality control–the detection, review and correction of errors in data that have been collected–begins in the design stage of prospective studies and continues throughout data collection [##REF##7261636##2##,##UREF##0##5##, ####REF##8775751##6##, ##REF##3755669##7##, ##REF##7789140##8####7789140##8##]. The ability to give regular and rapid feedback to investigators and data collectors highlights preventable problems in the data collection process and prevents deterioration in data quality [##REF##3201042##1##,##REF##7789144##9##].</p>", "<p>In this paper we present the data management system used in a large prospective project conducted at two centers. The principles that guided our process could apply to virtually any project. While there are now sophisticated systems available for data management, most are quite expensive. Pilot studies and preliminary investigations are often unfunded, and must rely on existing resources.</p>" ]

[ "<title>Methods</title>", "<title>Study setting</title>", "<p>The Missouri Lower Respiratory Infection (LRI) Project was a large prospective cohort study of outcomes (mortality and functional change) of nursing home residents who developed an LRI [##REF##11712938##10##,##REF##11711008##11##]. The protocol was approved by institutional review boards at two medical centers, several independent hospitals, and two nursing home ethical review panels. Conducted in central Missouri and the St. Louis area, the study enrolled subjects from August 1995 through September 1998, and data collection continued for an additional three months.</p>", "<p>Our institutional review board helped develop an appropriate strategy for enrolling participants. We contacted attending physicians in all facilities that had agreed to participate in the study. Physicians either declined to participate, or agreed to have trained study nurses provide timely, comprehensive evaluations of their residents who developed an illness consistent with an LRI. Physicians could <italic>a priori </italic>exclude any resident from evaluation. The study nurse recorded initial data and quickly communicated findings to the resident's physician, usually by facsimile transmission. Treatment decisions were left to the attending physician. Because these detailed evaluations were authorized by attending physicians who received clinical information and made treatment decisions accordingly, evaluations were considered part of appropriate care. For this reason, institutional review boards allowed a simplified consent process consisting of a simple refusal or acceptance of the clinical evaluation by the resident or a family member.</p>", "<p>Study enrollment was a two-step process [##REF##11712938##10##]. Criteria for evaluating, excluding, and enrolling residents are shown in Table ##TAB##0##1##. First, after eliminating residents with exclusion reasons, eligible patients with illness signs and symptoms compatible with an LRI were evaluated. Based on the evaluation and chest radiograph results, residents who met the LRI definition (Table ##TAB##0##1##) were enrolled. We refer the reader to Mehr et al. [##REF##11712938##10##] for further details regarding evaluation and enrollment. Residents could be enrolled multiple times, providing that they were well and off antibiotics for at least seven days following the previous episode. In the analysis, we used general estimating equations to adjust for individuals being represented in the data more than once.</p>", "<p>Evaluation information was subsequently abstracted from medical records without recording personal identifiers on the abstraction forms. Other data were obtained by medical record abstraction and follow-up visits with surviving residents. Data were also collected on costs of care and potential quality-of-care indicators for facilities. Using these data, we have conducted analyses that consider several outcomes, including mortality, functional status, indicators of radiographic diagnosis of pneumonia, and costs of care. Figure ##FIG##0##1## shows a flowchart of the project's organizational activities.</p>", "<title>Data Collection</title>", "<p>All study nurses were trained with a standard protocol. To verify examination procedures, portions of evaluations were performed by different nurses (with the resident's permission) and compared immediately following the second evaluation. Additionally, the principal investigator or the co-investigator overseeing the St. Louis site shadowed each study nurse to observe evaluation skills and provided immediate feedback.</p>", "<p>Starting with creating our data forms, we employed many standard data management procedures to minimize missing and erroneous data (Table ##TAB##1##2##). For example, we designed data forms with multiple choices and check boxes whenever possible to avoid problems with interpreting handwriting, data abstractors used a specific code to indicate that items were blank and not inadvertently omitted, and the fields for continuous variables (e.g., temperature, white blood cell count) on our forms included an appropriate number of digits, decimal points (where appropriate), and clearly labeled measurement units.</p>", "<p>All forms were pre-tested by investigators and research assistants. This resulted in dropping some data elements that were judged too time-consuming to find in the medical records (for example, date of the latest pneumococcal vaccine, which could require searching several years of charts for some residents). Each form included the study title, the form title, space for the subject's identification number, and a footer with the version number and date. We were fortunate to have a full-time research assistant who had extensive experience with chart abstraction. She initially trained all of the other research assistants by visiting facilities and going through the abstraction forms item-by-item. Subsequently, research assistants from each site (central Missouri and St. Louis) developed a manual that captured all of this information. We used conference calls to facilitate this process. The manual included an overview of the study forms, information on requesting and examining medical records, a decision matrix on what information to record for each type of resident (e.g. enrolled vs. evaluated but not enrolled), detailed instructions for locating and abstracting each form's data elements, Current Procedural Terminology (CPT) codes to be recorded for the economic analysis, medication lists and codes, copies of each form, and common abbreviations and medical shorthand.</p>", "<p>Initially, we did not appreciate the complexity of our data management needs. Within a few months, we defined clear rules on which personnel were responsible for each data management task and how each task was to be completed. Early in the study, 51 evaluations were selected for complete re-abstraction by another research assistant. Abstractors compared these forms to determine where differences occurred, further standardized their methods, and reconciled any errors that were made.</p>", "<p>All computerized data were stored on a secure network that limited access to authorized individuals and required a password for entry. Paper forms were stored in locked cabinets when not in use. We used a relational database to track enrollment, follow-up evaluations, and receipt and location (e.g., at data entry) of all forms. To ensure confidentiality, each resident was assigned a study identification number that was included on all forms in lieu of personal identifiers. After data cleaning was completed, resident names and social security numbers were completely expunged from the tracking database, as required by our IRB. All files on our computer network were backed up regularly; approximately quarterly, files were copied and stored at an offsite location so they could be recreated in case of a major system failure.</p>", "<p>We used twenty different forms for data collection. This necessitated substantial data quality control over an extended period of time, and precluded data entry by project staff. After visual inspection for legibility and completeness, forms were sent to an on-campus data entry facility in batches of manageable size as they became available. Data cleaning was a two-step process involving data entry followed by detailed examination of the data for potential errors. To reduce typographical errors, forms were double-entered and verified; after one data entry operator entered a form, a second operator entered the same form and resolved typographical differences, if necessary. To facilitate identification and processing, we printed forms on differently colored paper. We then used SAS software, Version 6.1 of the SAS System for Windows [##UREF##1##12##] to read data batches, check for errors, correct errors, and compile batches of entered data into data sets for analysis. These procedures are summarized below. Detailed descriptions of these procedures, including input statements used for data entry and management using SAS software, are available in additional file ##SUPPL##0##1##.</p>", "<p>Initial screening and enrollment forms were entered in the tracking database within a week of a resident's evaluation. The tracking database checked for internal consistency (e.g., residents who met enrollment criteria were enrolled). These data were checked and corrected before follow-up assessments. The database was also used to print out lists of individuals who should receive 30- or 90-day follow-up evaluations, lists of individuals whose records were available for abstraction, and lists of missing or inconsistent data. We used weekly meetings to distribute these lists, collect incoming forms, and discuss any problems that arose. These weekly meetings provided regular discussions of problems and solutions that were critical to the data management process. We kept minutes of all meetings. In addition to weekly project meetings, staff involved with data collection regularly met with the data manager and principal investigator. We also kept a log of issues that resulted in procedural changes. One entry reads, \"If we don't know whether a medication was given in capsule or tablet form, specify tablet. (10/26/95).\" Batches of forms were sent to data entry approximately monthly throughout the project. The turnaround time for data entry was typically two to four weeks.</p>", "<title>Data Entry and Cleaning</title>", "<p>Prior to submitting forms for data entry, forms were visually inspected for completeness and legibility. Errors found at this stage were corrected by drawing a single horizontal line through the erroneous value, printing the correct value above or next to the original, initialing and dating the change, and adding an explanatory note when appropriate. We followed the same procedure to correct data following entry, with the exception that a specific SAS command was created for each edit. The erroneous data were never obscured, thus maintaining a clear audit trail of all changes. For each study form, we developed a data dictionary that contained several elements, including the name, description, type, allowable values (range), and maximum field width for each variable. This helped data entry personnel set up a series of data entry formats that ensured output of high quality data files. Any questions about form legibility or out-of-range responses were flagged by data entry personnel for later resolution.</p>", "<p>We established several rules to ensure accountability and data quality. Except for data entry, completed forms never left the office. The original electronic files we received from data entry were never altered. We copied each file and worked with the copies, never the originals. Each batch was given a name that identified the type of form and included a sequential number identifying the data entry batch. For example, the raw data files for participant evaluation forms for the Columbia site were named EVALCL01.DAT through EVALCL35.DAT, as there were 35 batches of entered forms. This allowed us to use simple macro variable names to refer to the batches in our SAS software programs. Figure ##FIG##1##2## shows a flow chart of the computational tasks.</p>", "<p>Entered data were returned to us as flat text files. Because changes must be made at specific row and column locations, directly editing a large text file can be quite difficult, particularly when each observation extends over hundreds of columns and several rows. A change made to the wrong location may be particularly difficult to find and correct. For this reason, and also to preserve the original data, the entered data files were never altered, but used to create analyzable SAS data sets. For each batch of forms, the input program read the text file, reported potential anomalies, and created a SAS data set. Each variable was given a label that included the form and a brief description of the variable. To facilitate naming almost 2,900 variables, 2–3 characters that identified forms were often used at the beginning of variable names, and variable labels included the source form as well. For example, variables names for the evaluation form usually started with EV, while those for the 90-day (quarterly) evaluation started with Q90.</p>", "<p>The input program was primarily devoted to statements that checked the entered data for potential errors. Our strategies for checking data quality include range and consistency checks and checking for missing data. Developing boundaries for out-of-range values required a collaborative effort between the data manager and the clinician-investigators. We focused staff efforts on the highest priority data, recognizing that some missing data would simply take too much time to recover. For example, for our main outcome measure (mortality), we performed a death certificate search for the three residents who were lost to follow-up, and had no missing data. Similarly, we placed a high priority on determining activities of daily living status and body mass index. We defined high priority items as those required for determining study eligibility (e.g., vital signs, respiratory signs and symptoms, recent change in status, age, time in facility, etc.), outcomes (e.g., mortality, ADL status, health care use for the economic analysis), and variables that were considered likely covariates or confounders based on our previous work and literature review (e.g., laboratory tests, chest x-ray results, body mass index, cognitive status, comorbid diagnoses, etc.).</p>", "<p>All editing programs were tested to make sure they detected anomalous values and did not report in-range data as anomalous using a dummy dataset containing known errors. We also made comparisons across different forms to check whether they were collected in the proper sequence, whether variables such as date of birth and gender were consistent across multiple forms, whether forms were entered more than once, and whether forms indicated as entered in the management database matched the entered data files.</p>", "<p>All code for editing data was stored in separate files of SAS statements for each form and batch. We could thus locate the edit commands for an individual without difficulty, and the commands were easily corrected if necessary. As these files of edit commands were changed, the original text file was re-read, the edits applied, and a new SAS data set was saved. In addition to writing on paper forms, comment statements were sometimes included in the files of edit statements to provide information on why data values were changed or added. This helped preserve the \"audit trail\" of edits, an important process for maintaining data integrity.</p>", "<p>Data were checked and edited as soon as possible after entry to help ensure that information was still available. After making repeat requests for some irretrievable information, we developed a computerized database of potential problems and their resolutions. This provided further documentation of all data changes and helped avoid sending staff out repeatedly to investigate the same issues.</p>", "<title>Creating data sets for analysis</title>", "<p>Once the edits for each batch were complete, we appended data from each batch to a master file. Rather than waiting until all data were entered, we created interim datasets to check for consistency across datasets, check for duplicate forms, and compare entered forms with the tracking database to see if the two sources matched. Statistical analysis highlighted more potential problems, making necessary another (abbreviated) round of checking and editing. After editing was complete, we calculated the error rate for each batch with the following formula:</p>", "<p></p>", "<p>Similarly, we summed errors and forms over all batches to derive an error rate for each type of form.</p>" ]

[ "<title>Results</title>", "<p>Facility nurses reported 4,959 illness episodes; after applying evaluation and exclusion criteria (Table ##TAB##0##1##), 2,592 episodes were eligible for evaluation. Physicians excluded 56 individuals from evaluation <italic>a priori</italic>, and residents or family members refused evaluation for 86 illness episodes of residents who were otherwise eligible. Of the 2,592 evaluations, 1,406 LRI episodes met the study definition and were enrolled, representing a total of 1,044 individuals (due to multiple enrollments). Over the course of the study, data collection resulted in 20,500 completed forms, with a combined total of 2,899 variables. The forms were entered in 418 batches, each of which was processed as described above. Early in the study, the long text (memo) fields in the project tracking database became corrupted, necessitating re-entry of some enrollment forms. Data were regularly backed up and stored offsite after this point.</p>", "<p>Data entry, review, and correction continued throughout the study. Approximately 2/3rds of data abstraction was completed within 4 months of evaluation, with 90% completion within 6 months. Due to the time involved in logging in forms, visually inspecting forms, waiting for sufficient forms to compose a batch, preparing data entry batches, and entering and verifying data, half of the data were entered within 6 months of evaluation, with 90% complete within 9 months. Due to regular meetings between study nurses, research assistants, the principal investigator, and the data manager, we encountered very few potential errors that could not be resolved. One facility closed after study enrollment ended, and all medical records were sent to a storage facility that we could not access. Because it was unclear at the time how and whether we could gain access to the data, we decided to accept the data on the small number of records involved \"as is\" (only 3 of the facility's residents were enrolled in the last quarter of the study).</p>", "<p>Despite extensive field testing of forms, we inadvertently omitted including some variables on the initial versions provided to research assistants. This resulted in adding three short forms, two of which were concerned with economic data. For early episodes for which abstraction was already complete, research assistants had to re-access medical records to make up for these omissions. Missing data were common, particularly when nurses had several ill residents to evaluate and searching the chart for the most recent height and weight, for example, was too time consuming. Many missing items were subsequently recovered in the data cleaning process. Items on which we placed a high priority, such as activities of daily living status and body mass index, had very little missing data in the final data sets (&lt; 1%). Laboratory results had the highest proportion of missing data (&gt;10%) [##REF##11712938##10##], because tests were not always ordered and performed. An example of an error flagged by our program is a height value of 52. Height was supposed to be measured in inches, but occasionally, as in this case, feet and inches (or even centimeters) were recorded on the form. This individual was actually 5 feet and 2 inches tall, and the value was edited accordingly. An example of a non-error that was flagged for testing is a blood urea nitrogen value of 236. The normal range is 7–25 mg/dL, and we flagged values over 75 for checking against the lab report. According to the lab report, this was the resident's actual value.</p>", "<p>Unfortunately, we did not record the specific reason for each edit (e.g., originally missing, flagged as out of range, or flagged as being inconsistent with other variables), making it impossible to determine absolute counts of all potential error sources. We did compare the raw data to the edited data for two types of forms, and discovered that most (&gt;75%) of edits were due to missing data that were subsequently recovered. Edits to correct data entry errors were rare (&lt;10 total for the entire study), probably because both data entry personnel must make the exact same error for this to occur. Visual inspection of forms primarily highlighted glaring problems such as skipped pages or photocopies that were illegible or cropped.</p>", "<p>Each form had a different error rate, varying from 0.21% to 3.6% of all fields on each form. All but two forms had error rates under 1%. The form with the highest error rate, the hospital bill abstraction form, involved the complex process of placing all of the itemized charges on each bill into the proper cost category. One person abstracted all bills, followed by an item-by-item check by a second individual. The sheer number of items on bills for long hospital stays made the process difficult and prone to different interpretations.</p>", "<p>Comparison across batches uncovered 493 duplicate or erroneous forms that were subsequently deleted or replaced. This most commonly occurred with data that were collected at baseline, 30, and 90 days. Multiple enrollments potentially overlapped, and research assistants sometimes abstracted the wrong episode's follow-up form.</p>", "<p>Initially, we planned to devote 20% of a full-time position to data management. This proved totally inadequate; handling forms, tracking data entry, writing SAS code, producing follow-up and error reports, and applying the appropriate edits occupied approximately 1.5 FTEs. Fortunately, we had the flexibility to adapt to the unanticipated time requirements. The most time-consuming single programming task was developing the commands that checked the data for potential errors. For a large form such as the resident evaluation, error checking statements were hundreds of lines long and could take two to three days to develop. Four full-time research assistants completed data abstraction. Querying project nurses and reviewing medical charts to resolve potential errors was also time- and labor-intensive. We did not perform time studies to determine what proportion of nursing staff time was devoted to checking data, but we feel that 10% is a reasonable estimate. Such activities must be built into the project budget to ensure successfully completing data collection.</p>" ]

[ "<title>Discussion</title>", "<p>Data management should be planned well in advance of data collection and continue throughout a study. We used several methods to maintain data quality for over three years of data collection in the Missouri LRI Study. Regardless of whether data collection involves a small number of paper forms, direct entry into an electronic database, a sophisticated data management program, or dozens of forms over years of data collection, common principles apply.</p>", "<p>We thought carefully about the variables we would need for analyses, but unfortunately omitted a few, requiring research assistants to re-abstract some medical records. To avoid such re-work, we recommend developing mock tables for planned publications and filling them in with variables from the data collection instruments to make sure there are no missing data elements [##UREF##2##13##,##REF##4005011##14##]. Despite regular network backups, we lost some data due to file corruption; the recommendation to back up files regularly [##UREF##0##5##] should be followed. In addition to backing up data, we recommend storing copies of data files at an offsite location to avoid problems that could arise from a major system failure [##REF##3802845##4##,##UREF##3##15##].</p>", "<p>While several sources recommend visually inspecting forms for legibility and completeness prior to data entry [##REF##3802845##4##,##REF##3755669##7##,##REF##9805727##16##,##REF##11728622##17##], we found that this was primarily useful for discovering major errors such as missing pages and poor copies. Visual inspection is likely more useful for studies with small numbers of forms. In contrast, we found that the recommendation to double-enter and verify all data [##REF##11126691##3##, ####REF##3802845##4##, ##UREF##0##5##, ##REF##8775751##6####8775751##6##,##REF##7789144##9##,##REF##9805727##16##] led to data files with very few typographical errors. For each study form, we gave each variable a short descriptive name, and developed a data dictionary containing several elements, including the name, description, type, allowable outcomes (range), and maximum field width for each variable [##REF##3802845##4##, ####UREF##0##5##, ##REF##8775751##6####8775751##6##,##UREF##3##15##,##REF##11898018##18##]. The shared data dictionary facilitated communication, collaboration, and analysis.</p>", "<p>Despite careful planning, training, and pre-testing, some of our data files contained missing or erroneous data. We developed SAS programs to check all entered data for missing values and potential errors. <italic>Cody's Data Cleaning Techniques Using SAS Software </italic>[##UREF##4##19##] contains many suggestions for developing such programs. It is important to keep in mind that unlikely values are sometimes correct [##REF##3201042##1##,##REF##7789140##8##], and that data cleaning programs can only check for potential errors. This process is quite time consuming, but it is crucial to the overall quality of the resultant data.</p>", "<p>We would have preferred a rapid turnaround time [##UREF##0##5##,##REF##7789140##8##] between evaluation and data entry (90% completion by 9 months), but the sheer volume of the workload and budget constraints left little room for improvement. This highlights the tendency to underestimate time requirements for data management. Hogg [##REF##1867992##20##] recommends carefully estimating the time and effort required for a task, and then doubling the figure to give a more realistic estimate. However, careful planning can not anticipate all problems, and flexibility to modify procedures will be needed to minimize the impact of unexpected problems [##REF##11898018##18##].</p>", "<p>The procedures described above can be incorporated into a comprehensive data management system that, if followed, will lead to high quality data for analysis. In the Missouri LRI study, missing data were minimized, and we discovered very few inconsistencies or other data problems once analysis commenced. The first author has also applied these data management procedures to other prospective cohort studies [##REF##12676592##21##,##REF##12817824##22##]. A limitation is that there is no way to know what we missed. In-range values could have been incorrect but never checked. It seems unlikely, however, that such potential errors would all be in one particular direction, thus biasing analyses. Replacing paper forms with electronic, on-site data entry could be used to minimize missing data, but was not feasible at the time. Galliher and colleagues [##REF##18332408##23##] compared data collection on paper forms and handheld computers. For the data forms that were returned, errors of omission were much more common with the paper forms (3.5% missing items compared with 0.4% with computerized collection). They experienced technical problems with the handheld computers, however, and reported that some were stolen or lost, leading to completely missing forms. They suggested that tablet computers or data submission to a secure web site might be less prone to these types of losses.</p>" ]

[ "<title>Conclusion</title>", "<p>Ensuring reliable and complete data is essential to the integrity of the study. Regardless of the system used for data collection and management, rigorous application of several key principles will help ensure high quality data and facilitate analysis and interpretation of analytic results. Careful planning for data management at the beginning of a study will facilitate smooth study operation, and help keep analysis and writing on track.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Maintaining data quality and integrity is important for research studies involving prospective data collection. Data must be entered, erroneous or missing data must be identified and corrected if possible, and an audit trail created.</p>", "<title>Methods</title>", "<p>Using as an example a large prospective study, the Missouri Lower Respiratory Infection (LRI) Project, we present an approach to data management predominantly using SAS software. The Missouri LRI Project was a prospective cohort study of nursing home residents who developed an LRI. Subjects were enrolled, data collected, and follow-ups occurred for over three years. Data were collected on twenty different forms. Forms were inspected visually and sent off-site for data entry. SAS software was used to read the entered data files, check for potential errors, apply corrections to data sets, and combine batches into analytic data sets. The data management procedures are described.</p>", "<title>Results</title>", "<p>Study data collection resulted in over 20,000 completed forms. Data management was successful, resulting in clean, internally consistent data sets for analysis. The amount of time required for data management was substantially underestimated.</p>", "<title>Conclusion</title>", "<p>Data management for prospective studies should be planned well in advance of data collection. An ongoing process with data entered and checked as they become available allows timely recovery of errors and missing data.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>RK participated in the design of the study, coordinated data collection, conceived of and applied the data management strategy, participated in data analysis and interpretation, and drafted the manuscript. DM conceived of the study, and oversaw its design, coordination, and analysis. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2288/8/61/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The Missouri LRI Project was supported by grant HS08551 from the Agency for Healthcare Research and Quality and DR Mehr's Robert Wood Johnson Foundation Generalist Physician Faculty Scholars award. RL Kruse was supported by Institutional National Research Service Award number PE10038 from the Health Resources and Services Administration.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Flowchart of organizational tasks (Note: some tasks such as obtaining IRB approval, obtaining facility participation, and interacting with attending physicians are not included).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Overview of data editing process.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Criteria for evaluating, excluding, and enrolling residents in the Missouri LRI Project.</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">Residents eligible for <underline>evaluation</underline> met one or more of the following three criteria:</td></tr><tr><td align=\"left\"> 1. Two or more new lower respiratory symptoms (e.g., cough, shortness of breath, cyanosis)</td></tr><tr><td align=\"left\"> 2. One new respiratory symptom and at least one sign of an acute change in condition (e.g., fever, decreased alertness, new or increased confusion)</td></tr><tr><td align=\"left\"> 3. At least one sign of an acute change in condition and no evidence of stroke, gastroenteritis, urine infection, constipation/fecal impaction, or an adverse drug reaction</td></tr><tr><td align=\"left\">Residents were <underline>excluded</underline> from evaluation if they met one or more of the following criteria:</td></tr><tr><td align=\"left\"> 1. Did not meet evaluation criteria (above)</td></tr><tr><td align=\"left\"> 2. Resident or a family member declined evaluation, or resident's physician excluded them from the protocol</td></tr><tr><td align=\"left\"> 3. Resident's physician was not signed on to the protocol</td></tr><tr><td align=\"left\"> 4. Resident was not well and off antibiotics for at least seven days following a prior LRI</td></tr><tr><td align=\"left\"> 5. Resident was not at least 60 years of age</td></tr><tr><td align=\"left\"> 6. Resident had less than one month life expectancy, resident was a hospice patient, or resident had AIDS</td></tr><tr><td align=\"left\"> 7. Resident had a \"no antibiotics\" order in effect</td></tr><tr><td align=\"left\"> 8. Illness episode was missed</td></tr><tr><td align=\"left\"> 9. Resident had not been in facility for at least 14 days</td></tr><tr><td align=\"left\">The six <underline>enrollment criteria</underline> were</td></tr><tr><td align=\"left\"> 1. New or increased cough</td></tr><tr><td align=\"left\"> 2. New or increased sputum production</td></tr><tr><td align=\"left\"> 3. Fever</td></tr><tr><td align=\"left\"> 4. Pleuritic chest pain</td></tr><tr><td align=\"left\"> 5. New or increased physical findings on chest examination (rales, rhonchi, wheezes, or bronchial breathing)</td></tr><tr><td align=\"left\"> 6. One or more indications of change in status or breathing difficulty (new or increased shortness of breath, respiratory rate &gt; 25, and worsening mental or functional status)</td></tr><tr><td align=\"left\">Residents were enrolled if, after evaluation, they met three or more of the above enrollment criteria, or they met two criteria and had chest x-ray findings positive for pneumonia. We further required that residents with congestive heart failure or chronic obstructive pulmonary disease had either a fever or a chest x-ray that was positive for pneumonia to avoid confusing an acute exacerbation of their condition with an LRI.</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Data management principles.*</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">General</td></tr><tr><td align=\"left\"> □ Carefully plan data management well ahead of data collection [##REF##7261636##2##,##UREF##0##5##, ####REF##8775751##6##, ##REF##3755669##7##, ##REF##7789140##8####7789140##8##].</td></tr><tr><td align=\"left\"> □ Check for problems early, while it is still possible to correct them [##UREF##0##5##,##REF##7789140##8##].</td></tr><tr><td align=\"left\"> □ Provide staff with appropriate training [##REF##11126691##3##,##REF##7789140##8##,##UREF##3##15##].</td></tr><tr><td align=\"left\"> □ Provide clear lines of authority and responsibility [##REF##11898018##18##].</td></tr><tr><td align=\"left\">Data collection instruments</td></tr><tr><td align=\"left\"> □ Pre-test all data collection instruments [##REF##8775751##6##,##REF##11898018##18##].</td></tr><tr><td align=\"left\"> □ Include the version number and date on each form [##REF##11728622##17##].</td></tr><tr><td align=\"left\"> □ Label measurement units on data collection forms [##REF##11728622##17##].</td></tr><tr><td align=\"left\"> □ Develop mock tables for results and fill them in with elements from data collection forms to ensure you are collecting all the variables you need [##UREF##2##13##,##REF##4005011##14##].</td></tr><tr><td align=\"left\"> □ Focus efforts on the variables needed for the primary analyses [##UREF##0##5##,##REF##7789140##8##].</td></tr><tr><td align=\"left\"> □ Develop a detailed procedural manual for data collection [##REF##7789140##8##,##UREF##3##15##,##REF##11898018##18##,##REF##7789142##24##]; keep a log of all decisions that alter procedures.</td></tr><tr><td align=\"left\"> □ Use a specific code to indicate data elements that are intentionally blank [##REF##3802845##4##].</td></tr><tr><td align=\"left\">Data security, entry and cleaning</td></tr><tr><td align=\"left\"> □ Double-enter and verify all data [##REF##11126691##3##, ####REF##3802845##4##, ##UREF##0##5##, ##REF##8775751##6####8775751##6##,##REF##7789144##9##,##REF##9805727##16##].</td></tr><tr><td align=\"left\"> □ Develop a data dictionary, including allowable and in-range responses [##REF##3802845##4##, ####UREF##0##5##, ##REF##8775751##6####8775751##6##,##UREF##3##15##,##REF##11898018##18##].</td></tr><tr><td align=\"left\"> □ Store both paper forms and computerized data securely [##UREF##3##15##,##REF##7789142##24##].</td></tr><tr><td align=\"left\"> □ Back up computerized data files regularly [##UREF##0##5##], keeping offsite copies to safeguard against a system failure [##REF##3802845##4##,##UREF##3##15##].</td></tr><tr><td align=\"left\"> □ Thoroughly check data for missing or potentially erroneous items [##REF##3201042##1##, ####REF##7261636##2##, ##REF##11126691##3####11126691##3##,##UREF##0##5##,##REF##7789140##8##,##REF##7789144##9##,##REF##11728622##17##]. Strategies for data checking include range and consistency checks [##REF##3201042##1##, ####REF##7261636##2##, ##REF##11126691##3####11126691##3##,##UREF##0##5##,##REF##7789140##8##,##REF##7789144##9##,##REF##11728622##17##], checking for missing data [##REF##11126691##3##,##UREF##0##5##,##REF##7789144##9##,##REF##11728622##17##], between-form consistency checks [##REF##7261636##2##,##UREF##0##5##,##REF##7789140##8##,##REF##7789144##9##,##REF##11728622##17##], comparing forms to check whether they were collected in the proper sequence, whether forms were entered more than once [##REF##9805727##16##], and whether entered forms matched up with the management database [##REF##3802845##4##].</td></tr><tr><td align=\"left\"> □ Never obscure or destroy original data; maintain a clear audit trail of all changes to the data [##REF##7261636##2##,##UREF##0##5##,##REF##7789140##8##,##REF##7789144##9##,##UREF##3##15##,##REF##11728622##17##].</td></tr></tbody></table></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p><bold>Prospective data management detailed methods</bold>. An additional file is provided that contains methods in more detail, including examples of SAS code and output.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>*Additional regulations that apply to data integrity and security have been enacted since the time of our study. The Health Insurance Portability and Accountability Act (HIPAA) [##REF##11343353##25##] addresses the security and privacy of health data, and 21CFR Part 11 [##UREF##5##26##] specifically addresses the reliability of electronic records.</p></table-wrap-foot>" ]

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[ "<media xlink:href=\"1471-2288-8-61-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The <italic>ERBB2 </italic>(<italic>Her-2/neu</italic>) oncogene is amplified and over-expressed in 25% of invasive breast carcinomas [##REF##2470152##1##, ####REF##9797688##2##, ##UREF##0##3##, ##REF##7607564##4####7607564##4##]. In general, <italic>ERBB2 </italic>amplification confers an unfavorable prognosis, although its significance is less than that of the traditional prognostic factors – stage and grade. Also, it seems that the prognosis and response to therapy varies considerably within the spectrum of <italic>ERBB2</italic>-amplified breast carcinomas (BC), indicating that they are biologically heterogeneous. The first targeted anti-neoplastic agent, Trastuzumab (Herceptin©), a monoclonal antibody to ERBB2, produces a response in approximately 15% of heavily pretreated patients with metastatic BC as a single agent [##REF##10561337##5##] and in combination with chemotherapy improved the overall survival of patients with metastatic BC by 5 months [##REF##11248153##6##]. It has recently been shown to decrease the risk of BC recurrence by about 50% in patients with <italic>ERBB2 </italic>amplified tumors in the adjuvant setting [##REF##16236737##7##]. Unfortunately, only a fraction of patients with <italic>ERBB2</italic>-amplified breast carcinomas respond to Trastuzumab, further evidence for heterogeneity among these tumors.</p>", "<p>The <italic>ERBB2 </italic>oncogene is located at the 17q12 chromosomal locus. Many genes located close to <italic>ERBB2 </italic>on 17q12-q21 are known or suspected to play a role in carcinogenesis, and specifically, in breast carcinogenesis. Previous studies demonstrated that the negative effect on the prognosis of BC attributed to <italic>ERBB2 </italic>amplification could, in fact, be due to co-amplification of the region adjacent but telomeric to <italic>ERBB2 </italic>[##REF##14578197##8##]. One of the genes located in this region is <italic>Topoisomerase IIA </italic>(<italic>TOP2A</italic>). It has been demonstrated that amplification of <italic>ERBB2 </italic>in BC cell lines and in primary breast tumors is associated with simultaneous amplification or deletion of the <italic>TOP2A </italic>gene [##REF##12006526##9##, ####REF##14499010##10##, ##REF##15486187##11##, ##REF##15628907##12##, ##REF##15068318##13##, ##REF##12755489##14####12755489##14##]. Also, it has been shown that in BC, amplification of <italic>ERBB2 </italic>correlates with overexpression of <italic>TOP2A </italic>[##REF##10824926##15##], but it cannot predict it [##REF##15486187##11##]. Some authors argue that ERBB2 and TOP2A overexpression could be independent prognostic factors of poor survival in BC [##UREF##1##16##].</p>", "<p>Topoisomerases are nuclear enzymes that modulate the topology of DNA by modifying the tertiary structure of the double helix. TOP2A is a 170-kD protein that binds to DNA, forming the cleavable complex, which allows intertwined replicated DNA strands to physically separate at the end of mitosis [##UREF##2##17##]. TOP2A is more highly expressed in rapidly proliferating cells, and expression is limited to the S to G2/M phases of cell cycle. TOP2A is a molecular target for some important anticancer drugs, including anthracyclines, which are the key chemotherapeutic agents in the treatment of BC. Anthracyclines stabilize the TOP2A cleavable complex and inhibit TOP2A catalytic activity (ibid). Therefore, it has been suggested that the empiric observation that <italic>ERBB2</italic>-amplified BCs respond relatively well to anthracycline-based chemotherapy [##REF##15980993##18##, ####REF##14654958##19##, ##REF##16137437##20##, ##REF##15994142##21##, ##REF##12560435##22##, ##REF##11905798##23####11905798##23##] is due to co-amplification of <italic>TOP2A </italic>[##REF##12628842##24##, ####REF##11948114##25##, ##REF##17260090##26##, ##REF##15887027##27##, ##REF##18574145##28####18574145##28##]. These data suggest that co-amplification of at least one of the genes adjacent to <italic>ERBB2 </italic>can play a role in the response to a specific chemotherapeutic agent widely used in the treatment of BC. The significance of amplification or deletion of other genes adjacent to <italic>ERBB2 </italic>remains to be determined. <italic>TOP2A </italic>aberrations (amplification or deletions) occur in less than 10% of <italic>ERBB2 </italic>non-amplified breast tumors [##REF##15891995##29##]. This indicates that <italic>ERBB2 </italic>amplification could be the primary genetic event involving chromosome 17q in breast carcinogenesis and the <italic>TOP2A </italic>alterations are secondary events.</p>", "<p>We showed previously that amplification of <italic>ERBB2 </italic>and nearby genes appears to form a single amplicon of variable size, without intervening normal or deleted segments [##REF##15034864##30##], consistent with the break-fusion-bridge model for gene amplification [##REF##15034864##30##,##REF##10469452##31##], where recurrent double-stranded DNA breaks occur at vulnerable sites which become starting points for further amplifications or telomeric deletions. We systematically analyzed the amplification patterns of the region telomeric to <italic>ERBB2</italic>, using a series of fluorescence <italic>in-situ </italic>hybridization (FISH) probe sets. We determined that there are significant variations of the amplicon size, and that <italic>TOP2A </italic>can be amplified, normal or deleted. Here we conducted a retrospective study to determine whether the amplicon pattern, including amplification or deletion of <italic>TOP2A </italic>correlates with clinico-pathologic characteristics of breast tumors, markers of proliferation, and the clinical outcome of patients with <italic>ERBB2</italic>-amplified BC.</p>" ]

[ "<title>Materials and methods</title>", "<title>Hybridization Probes</title>", "<p>The probes have been described in detail previously [##REF##15034864##30##]. Single clones used for FISH probes were the following: <italic>291U </italic>(RP11 BAC 283i23), <italic>291P </italic>(RP5 PAC 1152A16), <italic>291F </italic>(CITB BAC 428H21), <italic>291Z.2 </italic>(RP11 BAC 58o9), <italic>291Z.6 </italic>(Genome Systems P1 # 611), <italic>291Z.7 </italic>(RP11 BAC 89A22), and <italic>291Z.8 </italic>(RP1 PAC 1028K7). The single clones lie within a contig beginning about 69 kb telomeric of the Vysis LSI^®<italic>HER-2 </italic>probe and extending for approximately 889 kb toward the 17q telomere (see Figure ##FIG##0##1##) Each <italic>in situ </italic>hybridization included 3 FISH probes directly labeled with different fluorophores: a peri-centromeric alpha satellite probe for chromosome 17 (Vysis^®SpectrumAqua™ CEP^®17; Abbott Molecular Inc, Des Plaines, IL), a probe for <italic>ERBB2 </italic>(Vysis SpectrumGreen™ LSI^®HER-2, Abbott Molecular) and one of 7 single-clone probes telomeric to <italic>ERBB2 </italic>labeled with SpectrumOrange™.</p>", "<title>Specimens</title>", "<p>Fifty-four specimens from patients with invasive BC and 9 patients with ductal carcinoma <italic>in situ</italic>, without documented coexisting invasion, were obtained from the archives of the Pathology Department at Rush University Medical Center (Chicago, IL). They comprised left-over diagnostic material from patients seen between 1998 and 2003. There was sufficient archival material available for all of the patients included to ensure that the study did not exhaust the diagnostic tumor tissue. <italic>ERBB2 </italic>amplification was verified for all patients as part of this study, by use of the PathVysion^®FISH panel (Abbott Molecular). Paraffin blocks were sectioned at 5 μm thickness and mounted onto SuperFrost Plus^®positively charged slides (ThermoShandon, Pittsburgh, PA).</p>", "<title>Patients</title>", "<p>Patients with <italic>ERBB2</italic>-amplified BC treated at Rush University Medical Center, Chicago, Illinois, between 1997 and 2004 were considered for the study. The study was approved by the Rush Institutional Review Board. Only patients for whom adequate archival pre-therapy tumor tissue and adequate clinical follow-up data were available were eligible for the study. The median follow up for the patients in this study was 31 months. The diagnosis of invasive BC in the archival material was confirmed by histological evaluation before further analysis. The clinical outcome data was obtained by chart review. No patients in this study received adjuvant Trastuzumab because they were treated before the approval of Trastuzumab for the adjuvant treatment of BC.</p>", "<title><italic>In Situ </italic>Hybridization</title>", "<p>The procedure has been described in detail previously [##REF##15034864##30##]. Briefly, the specimens were prepared by immersion of the slides in Vysis Pretreatment Solution (Abbott Molecular) at 80°C for 10 minutes. The slides were then immersed in a solution of 4 mg pepsin (2500–3000 U/mg), rinsed in water, and dehydrated in 70%, 85%, and 100% ethanol. The slides were hybridized with the 3-color FISH probe solutions in a HYBrite™ automated co-denaturation oven (Abbott Molecular) and then immersed in 73°C 2 × SSC/0.3% NP40 for 2 minutes for removal of nonspecifically bound probe.</p>", "<title>Enumeration of FISH signals</title>", "<p>Typically, 30–90 cells were enumerated in each specimen. The FISH slides were evaluated under a Zeiss Axioscope epi-fluorescence microscope (Carl Zeiss, Thornwood, NY). Only nuclei with morphology characteristic of malignant cells were counted. The mean number of signals per cell was calculated by totaling the number of signals from each cell and dividing by the number of cells counted. Mean <italic>ERBB2 </italic>and mapping probe signals per cell were divided by the mean <italic>CEP17 </italic>signals per cell to provide the ratio of <italic>ERBB2</italic>-to-chromosome 17 signals and mapping probe-to-chromosome 17 signals. A lower ratio cutoff of 0.75 and an upper ratio cutoff of 2.00 were selected for deletion and amplification, respectively [##REF##15034864##30##].</p>", "<title>Immunohistochemistry</title>", "<p>In preparation for antibody staining, paraffin sections (5 microns, freshly cut) were deparaffinized and rehydrated using standard technique. A microwave antigen retrieval method was then carried out in citrate buffer. The tissue was stained using a Ventana ES Histo-stainer (Ventana Medical Systems, Tucson, AZ), using supplied diaminobenzidine and avidin-biotin conjugate immunoperoxidase chemistry. Sections were stained for TOP2A with the JH2.7 monoclonal antibody from Lab Vision Corp. (Fremont, CA) at a dilution of 1:100 and MIB1 with the Ki-S5 antibody (Dakcytomation, Carpeneria, CA), dilution 1:50. A single block from the pre-therapy biopsy was selected for analysis for each patient on the basis of having the greatest area of well-preserved tumor. Immunostaining frequency of all tumor cells on each slide was scored subjectively on a scale of 0 to 4 (actual cell counting was not performed) without knowledge of clinical patient data, as previously described [##REF##10443844##49##]. Less than 1% positive tumor cells were scored as 0, 1–10% as 1, 11–35% rated 2, 36 – 70% rated 3 and over 70% rated 4 on the scale. Tumor cell staining intensity was also scored on a scale of 0 to 4, but was found to be so closely related to frequency that it was not further considered in this study. Only nuclear staining was considered for TOP2A.</p>", "<title>Statistical analysis</title>", "<p>Fisher's exact tests and Chi-square tests were used to measure the significance of the association between pairs of categorical variables such as those between the amplicon class, patient descriptors, molecular variables and the clinical outcome of evidence of disease. Permutation based exact p-value were used for these tests since they are more appropriate for small sample size. Specimens were divided into 4 categories based on the FISH data as explained below. Immunohistochemical expression was divided into three categories: overexpressed (frequency 3+ and 4+), expressed (frequency 1+ and 2+) and undetected (frequency 0).</p>", "<p>Time to recurrence and overall survival were measured as months from the start of treatment to the time of tumor recurrence, death or last follow-up. Survival curves were estimated by the Kaplan-Meier method and are compared by the log-rank test. Due to the relatively small sample sizes, exact permutation based p-values, available in the R statistical software, are reported for the log-rank test. Age adjusted time to recurrence and time to survival are analyzed using the Cox proportional hazards regression. SAS version 9.0 and the R statistical software were used in the data analysis. All reported p-values are two-sided.</p>" ]

[ "<title>Results</title>", "<title>Chromosome 17q gene copy abnormality patterns in <italic>ERBB2</italic>-amplified BCs</title>", "<p>We showed previously that BCs with <italic>ERBB2 </italic>amplification have variable amplification and deletion of genes telomeric to <italic>ERBB2 </italic>[##REF##15034864##30##]. This was demonstrated with the Vysis <italic>ERBB2 </italic>probe and 7 other FISH probes covering an adjacent 889 kb telomeric region (Figure ##FIG##0##1##). The amplified region (amplicon) may extend to or even beyond the <italic>TOP2A </italic>gene, contained within the <italic>291F</italic>, <italic>291Z.6</italic>, <italic>291Z.2 </italic>probes, and appears to be continuous in 90% of cases studied, without intervening regions of normal copy number or deletion. If deleted segments are present, they begin just telomeric to the amplified segment, and almost always involve the <italic>TOP2A </italic>gene. In this study, the status of the <italic>291Z.2 </italic>probe was used to assess the copy number of the <italic>TOP2A </italic>gene because: 1) the gene is more centrally located within the <italic>291Z.2 </italic>sequence, as opposed to the 291F probe for which <italic>TOP2A </italic>is located near its telomeric end (furthest from <italic>ERRB2</italic>), and 2) <italic>291Z.2 </italic>targets a larger region than <italic>291Z.6</italic>, thereby providing a brighter signal that would be more accurately visualized in poorer quality specimens. The disadvantage of the <italic>TOP2A </italic>sequence lying near the terminus furthest from <italic>ERBB2 </italic>in the <italic>291F </italic>targeted region is that amplicons can terminate just centromeric to <italic>TOP2A </italic>but still contain the majority of the <italic>291F </italic>sequence, producing <italic>291F </italic>signals bright enough to be counted as amplified, and misrepresenting the <italic>TOP2A </italic>gene status.</p>", "<p>Here, we have classified the17q gene copy abnormalities of 63 BC, including 9 cases with only DCIS, all with amplification of <italic>ERBB2 </italic>by FISH, into 4 categories of similar frequency, to permit comparison with other tumor attributes and clinical outcome:</p>", "<p><bold>Class I</bold>: <italic>ERBB2 </italic>and <italic>TOP2A </italic>both amplified (25.4% of total);</p>", "<p><bold>Class II</bold>: Only <italic>ERBB2 </italic>amplified (no other mapping probe loci amplified), <italic>TOP2A </italic>normal (23.8% of total),</p>", "<p><bold>Class III</bold>: <italic>ERBB2 </italic>and neighboring mapping loci amplified, <italic>TOP2A </italic>normal (25.4% of total),</p>", "<p><bold>Class IV</bold>: <italic>ERBB2 </italic>amplified but <italic>TOP2A </italic>deleted (25.4% of total).</p>", "<title>Associations between Amplicon Class, clinical and pathologic characteristics of breast tumors</title>", "<p>Tests for association of Amplicon Class and accepted descriptors of breast carcinoma for all 63 patients are summarized in Table ##TAB##0##1##. No significant associations between Amplicon Class and presence of invasion, histological type, grade, stage, patient age, or hormone receptor status were found.</p>", "<title>Associations between <italic>TOP2A </italic>gene copy number, protein expression, and cell proliferation</title>", "<p>We studied nuclear TOP2A expression by immunohistochemistry (IHC) to determine whether it paralleled the gene copy (FISH) studies. A comparison of the frequency of expression by tumor cell nuclei versus Amplicon Class did not show a significant association (p = 0.50), data not shown. Similarly, comparing TOP2A expression frequency versus the <italic>TOP2A </italic>gene categorized as amplified, normal or deleted, did not show a significant association (p = 0.38), data not shown.</p>", "<p>TOP2A expression level has been reported to reflect the proliferation rate of tumors [##UREF##2##17##], and some authors have suggested that associations between TOP2A expression and/or gene amplification and the biological behavior of tumors occur on this basis (<italic>ibid</italic>). Here, we observed that TOP2A expression did show a modest association with expression of MIB1, a standard IHC assay for cell proliferation, correlation coefficient 0.54 (Figure ##FIG##1##2##).</p>", "<p>The presence or absence of <italic>TOP2A </italic>amplification was not associated with the frequency of MIB1 expression (p = 0.79), nor was Amplicon Class associated with MIB1 frequency (p = 0.58).</p>", "<title>Association of BC clinical outcome with Amplicon Class and <italic>TOP2A </italic>gene copy number</title>", "<p>The analysis of the clinical outcome data by chart review were obtained for 34 patients who presented with Stage I–III invasive BC and who had at least 18 months of clinical follow-up. The 9 patients with only DCIS were excluded from this analysis. Twenty-one other patients were also excluded, most often because follow-up was unobtainable, or they presented with Stage IV disease. Twenty patients received anthracycline-based therapy in the adjuvant setting and 3 in the neoadjuvant setting. The remainder never received anthracycline therapy, Table ##TAB##1##2##</p>", "<p>The Amplicon Class IV, with <italic>TOP2A </italic>deletion, had 67% (6/9) cases with unfavorable outcome, whereas the other three classes combined had only 12% (3/25) unfavorable outcomes. The association of <italic>TOP2A </italic>deletion with unfavorable outcome was strongly significant (p value = 0.004 from Fisher's exact test), whereas <italic>TOP2A </italic>amplification (Class I) did not confer a better outcome than normal <italic>TOP2A </italic>copy number (Class II and III). In contrast, no association was found between clinical outcome categories and expression of TOP2A (p = 0.66) or expression of MIB1 (p = 0.695). Clinical outcome categories were also not associated with tumor grade (p = 0.69), stage (p = 0.25), ER status (p = 0.78), PR status (p = 0.54, or patient age (p = 0.78). Five of the 9 unfavorable outcomes occurred in patients who had never received anthracycline therapy.</p>", "<p>The Kaplan-Meier estimates of time to tumor recurrence for patients with <italic>TOP2A </italic>deletion versus others are shown (Figure ##FIG##2##3##). 56% of cases are estimated to recur by 18 months in the <italic>TOP2A </italic>deleted group, whereas only 8% are estimated to recur in the other patients. The difference in time to recurrence between these two groups is strongly statistically significant (p-value = 0.0002 from a log-rank test). Since the sample sizes are small, we also obtained the permutations based p-value of the log-rank test using the ExactRankTests package of the R statistical software, this latter p-value = 0.0006.</p>", "<p>The Kaplan-Meier survival estimates of the <italic>TOP2A </italic>deletion group versus others are shown in Fig ##FIG##3##4## (Figure ##FIG##3##4##). 44% (4/9) patients died during the follow-up in the <italic>TOP2A </italic>deletion group whereas 12% (3/25) died in the other group. The difference in survival between these two groups is statistically significant (p-value = 0.04 from a log-rank test and = 0.03 from the exact permutation based approach).</p>", "<p>Due to the limited sample size, we considered multivariate analysis with <italic>TOP2A </italic>deletion and one additional covariate at a time. <italic>TOP2A </italic>deletion had significantly increased hazard of recurrence (HR = 8.6, p-value = 0.002) than the other group in a Cox proportional hazards regression analysis which also included age as a covariate. <italic>TOP2A </italic>deletion also had significantly increased hazard of recurrence after adjustment by grade (HR = 9.5, p-value = 0.002) and after adjustment by ER status (HR = 9.2, p-value = 0.002). The effect of <italic>TOP2A </italic>deletion on survival was marginally significant (HR = 5.2, p-value = 0.06) after adjustment by age. The effect of age, grade and ER were not at all significant in either one of these analyses.</p>", "<p>Thus, we found that Amplicon Class with <italic>TOP2A </italic>deletion in <italic>ERBB2</italic>-amplified BC was associated with shorter time to tumor recurrence and significantly higher risk of cancer recurrence independent of other covariates.</p>" ]

[ "<title>Discussion</title>", "<p>This paper is the first attempt to relate the characteristics of the highly variable <italic>ERBB2-TOP2A </italic>amplicon in BC, categorized into clearly defined Amplicon Classes, to the phenotype of the tumors. The Amplicon Classes were not associated with the commonly used descriptors of breast neoplasia. Specifically there was no evidence that Amplicon Class was associated with the ability of tumor cells to invade normal tissue, since the Class distribution was similar in invasive carcinoma and DCIS. Amplicon Class also seemed not to vary with stage at presentation, or hormone receptor status. These observations suggest that Amplicon Class may be independent of the most useful classical prognostic markers.</p>", "<p><italic>TOP2A </italic>deletion emerged as a strong predictor of unfavorable outcome and shorter disease-free survival, whereas no significant association with <italic>TOP2A </italic>amplification was found. This is not inconsistent with our previous study of local tumor response in locally advanced BC, most of which did not have <italic>ERBB2 </italic>amplification, and all of which were treated with neoadjuvant anthracycline-based therapy [##REF##11948114##25##]. <italic>TOP2A </italic>amplification was associated with tumor response in this study, but the patients and the end point were quite different than the present study. Comparing Amplicon Class II with Amplicon Class III, amplification of genes between <italic>ERBB2 </italic>and <italic>TOP2A </italic>was also not associated with outcome or time to recurrence in this study. We also assessed TOP2A expression by IHC, but we did not find a significant association with clinical outcome or time to recurrence. <italic>TOP2A </italic>deletion was not associated with significantly reduced expression of TOP2A. This raises the possibility that <italic>TOP2A </italic>deletion may be a marker for another genetic event, most likely involving a nearby gene, whose altered expression confers an adverse prognosis. In fact, the 291Z.2 probe contains all or part of at least 3 genes in addition to <italic>TOP2A </italic>(Figure ##FIG##0##1##). Identifying the significant gene will require studying more patients with <italic>TOP2A </italic>deletion at higher resolution. It is not possible to link the adverse prognostic significance of <italic>TOP2A </italic>deletion to anthracycline resistance in this group of patients, since 5 of the 9 patients with adverse outcomes did not receive anthracyclines. Given the existing evidence on the higher likelihood of <italic>TOP2A </italic>amplified tumors to respond to anthracyclines, this observation may indicate that <italic>TOP2A </italic>deletion is an unfavorable prognostic marker independent of chemotherapy, but the small number of patients does not allow drawing any definitive conclusion. The association between clinical outcome and anthracycline therapy (received vs. not received) was not significant (p = 0.4 from Fisher's exact test).</p>", "<p>This study of Amplicon Class versus clinical outcome is based upon a small number of highly selected (<italic>ERBB2</italic>-amplified) BC patients with relatively short follow-up. These factors probably account for several unexpected findings in this study. Among all factors considered only <italic>TOP2A </italic>deletion was associated with survival. We have not observed the correlation between survival and stage, presumably because the follow-up was too short. The fact that all of the tumors had <italic>ERBB2 </italic>amplification may have obscured the association of other established prognostic factors, such as ER and PR with outcome. Nevertheless, the study is significant because it demonstrates that the recently recognized molecular heterogeneity of the <italic>ERBB2 </italic>amplification event may have clinical significance, although this finding requires confirmation in a larger group of patients. It has been assumed that the adverse effect of <italic>ERBB2 </italic>amplification is mediated largely or entirely via associated overexpression of the ERBB2 oncogene, but associated copy abnormalities in nearby genes may also be involved [##REF##11719455##32##].</p>", "<p>TOP2A has been studied in BC by other investigators, primarily because it is a marker of proliferation and a target for anthracyclines [##REF##12915875##33##, ####REF##15331926##34##, ##REF##14728934##35####14728934##35##]. However, the information on the prognostic role of TOP2A is limited and the use of anthracyclines could be a confounding factor to assess it. Moreover, in previous studies [##REF##10824926##15##,##UREF##3##36##] the prognostic role of TOP2A in BC was frequently studied by correlating its expression by IHC with the clinical outcome. More recent studies showed that TOP2A expression measured by is cell cycle-dependent and thus, indicates the number of proliferating cells rather than nuclear <italic>TOP2A </italic>status in a given tissue. Furthermore, cell proliferation potentially can be a source of bias in measuring TOP2A protein [##REF##10702400##37##]. Since anthracyclines interact with TOP2A in the nucleus, it is important to determine TOP2A expression in the nucleus which can be done most accurately by determining <italic>TOP2A </italic>copy number as a surrogate marker. To illustrate this point Burgess <italic>et al</italic>. utilized RNA interference to knockdown <italic>TOP2A </italic>gene in the nucleus of lymphoma cells which resulted in increased resistance to an anthracycline, doxorubicin, but has not affected cell proliferation [##REF##18574145##28##]. Our results confirmed that TOP2A expression in BC cells by IHC is associated with proliferation (MIB-1), but neither marker was associated with outcome in this group of patients. The association between <italic>TOP2A </italic>deletion and adverse outcome in these patients appears, therefore, to be unrelated to the cell proliferation rate.</p>", "<p>A number of retrospective analyses of tissue specimens from earlier adjuvant clinical trials with anthracycline and non-anthracycline chemotherapy regimens have been recently published [##REF##12006526##9##,##REF##14654958##19##,##REF##15887027##27##,##REF##16234514##38##,##REF##16682728##39##]. The body of literature supports the idea that <italic>TOP2A </italic>status predicts the response to anthracyclines in BC and it is possible that clinical benefit from anthracyclines is limited to patients with <italic>ERBB2 </italic>and <italic>TOP2A </italic>amplified tumors. However, the prognostic and predictive value of <italic>TOP2A </italic>deletion remains controversial. The occurrence of <italic>TOP2A </italic>deletion in BC has been well documented previously, primarily in tumors with <italic>ERBB2 </italic>amplification [##REF##10469452##31##,##REF##10702400##37##,##REF##14632728##40##,##REF##16502015##41##]. In the study of Hicks <italic>et al</italic>. [##REF##15891995##29##] 50% of <italic>ERBB2</italic>-amplified breast tumors had <italic>TOP2A </italic>co-amplification and 16% had monoallelic deletion of <italic>TOP2A</italic>. In <italic>ERBB2 </italic>non-amplifed tumors, <italic>TOP2A </italic>was never amplified and in 5% of the tumors there were monoallelic deletions of both <italic>ERBB2 </italic>and <italic>TOP2A </italic>genes (<italic>ibid</italic>). In one published analysis of a large collection of primary breast tumor samples, <italic>TOP2A </italic>alterations were reported in 23% of all tumors, regardless of their <italic>ERBB2 </italic>status: 12% had <italic>TOP2A </italic>amplification and 11% had <italic>TOP2A </italic>deletion [##REF##16234514##38##]. In this study both <italic>TOP2A </italic>amplification and deletion were associated with improved recurrence-free and overall survival if treated with anthracycline-based chemotherapy as opposed to a non-anthracycline regimen.</p>", "<p>Our data confirm the results of the recently published retrospective analysis of tissue samples from the large adjuvant clinical trial [##REF##18465341##42##] which have demonstrated that <italic>TOP2A </italic>aberrations, including both <italic>TOP2A </italic>amplifications and deletions, are significantly associated with shorter recurrence free and overall survival. A clear benefit from adjuvant anthracyclines was identified in women with <italic>TOP2A </italic>amplifications [##REF##16234514##38##,##REF##15891995##29##,##REF##18465341##42##] and a non-significant trend for improved survival was observed in women with <italic>TOP2A </italic>deletions [##REF##18465341##42##]. Thus, the <italic>TOP2A </italic>deletion in BC seems to confer a poor prognosis, but more studies are needed to elucidate the responsiveness of these tumors to anthracyclines.</p>", "<p>Trastuzumab may be synergistic, additive or antagonistic in combinations with different chemotherapeutic agents. With the recent approval of Trastuzumab for the adjuvant treatment of BC and expanding its use, the importance of exploring molecular markers in the vicinity <italic>of ERBB2 </italic>is increased [##REF##16507275##43##,##REF##16236738##44##]. Slamon <italic>et al</italic>. [##REF##2470152##1##] recently illustrated this point with the preliminary analysis of the BCIRG 006 clinical trial data [##UREF##4##45##]. These results suggest that patients with co-amplification of <italic>TOP2A </italic>comprise the subset of patients who benefit from anthracyclines in the adjuvant setting. Therefore, patients without <italic>TOP2A </italic>co-amplification may be better treated with combinations of non-anthracycline drugs with Trastuzumab, which would decrease the risk of cardiotoxicity. In fact, we recently reported that <italic>ERBB2 </italic>amplicons that did not extend to the <italic>291Z.2 </italic>(<italic>TOP2A</italic>) locus (Class II + Class III amplicons) were associated with improved response to trastuzumab relative to amplicons that included the <italic>291Z.2 </italic>locus (Class I amplicons) [##REF##17243161##46##]. Although the combination of Trastuzumab and anthracyclines may seem to be very powerful against <italic>ERBB2 </italic>and <italic>TOP2A </italic>amplified BC, this combination is cardiotoxic. It would seem reasonable to search for new non-cardiotoxic inhibitors of TOP2A to combine with Trastuzumab. One of these agents, suberoylanilide hydroxamic acid (SAHA), is currently in clinical trials [##REF##14612526##47##,##REF##15108350##48##].</p>" ]

[ "<title>Conclusion</title>", "<p>The <italic>TOP2A </italic>deletion is associated with increased risk of BC recurrence and death from breast cancer in patient with <italic>ERBB2 </italic>amplified BC. Clarification of the mechanism of this association will require additional study.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Amplification of the <italic>ERBB2 </italic>(<italic>Her-2/neu</italic>) oncogene, which occurs in approximately 25% of breast carcinomas, is a known negative prognostic factor. Available data indicate that a variable number of nearby genes on chromosome 17q may be co-amplified or deleted, forming a continuous amplicon of variable size. In approximately 25% of these patients, the amplicon extends to the gene for <italic>topoisomerase II alpha </italic>(<italic>TOP2A</italic>), a target for anthracyclines. We sought to understand the significance of these associated genomic changes for breast cancer prognosis and predicting response to therapy.</p>", "<title>Methods and patients</title>", "<p>Archival tissue samples from 63 breast cancer patients with <italic>ERBB2 </italic>amplification, stages 0–IV, were previously analyzed with FISH probes for genes located near <italic>ERBB2</italic>. In the present study, the clinical outcome data were determined for all patients presenting at stages I–III for whom adequate clinical follow up was available.</p>", "<title>Results</title>", "<p>Four amplicon patterns (Classes) were identified. These were significantly associated with the clinical outcome, specifically, recurrence of breast cancer. The Amplicon class IV with deleted <italic>TOP2A </italic>had 67% (6/9) cases with recurrence, whereas the other three classes combined had only 12% (3/25) cases (p-value = 0.004) at the time of last follow-up. <italic>TOP2A </italic>deletion was also significantly associated with time to recurrence (p-value = 0.0002). After adjusting for age in Cox regression analysis, the association between <italic>TOP2A </italic>deletion and time to recurrence remains strongly significant (p-value = 0.002) whereas the association with survival is marginally significant (p-value = 0.06).</p>", "<title>Conclusion</title>", "<p><italic>TOP2A </italic>deletion is associated with poor prognosis in <italic>ERBB2</italic>-amplified breast carcinomas. Clarification of the mechanism of this association will require additional study.</p>" ]

[ "<title>List of Abbreviations</title>", "<p>BC: Breast carcinoma; TOP2A: Topoisomerase II alpha; FISH: Fluorescence <italic>In-Situ </italic>Hybridization; NED: No evidence of disease; AWD: Alive with recurrent breast cancer; DOD: Died of breast cancer; DNED: Dead with no evidence of disease at least 24 months after diagnosis; ER: Estrogen receptor; PR: Progesterone receptor; IHC: Immunohistochemistry.</p>", "<title>Competing interests</title>", "<p>Larry E. Morrison and Kris Jacobson are employees of Abbott Molecular Inc. John S. Coon has received research funding from the same company.</p>", "<title>Authors' contributions</title>", "<p>LU helped to plan the study and wrote the manuscript. BT and RR gathered and interpreted clinical data. LM and KJ performed the FISH analysis and interpreted the data. AZ and SB performed statistical analysis and helped to format and interpret the data. JC helped to plan the study and contributed significantly to writing the manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Susan S. Jewell, PhD for her valuable assistance in preparing the Diagram with the location of FISH probes and selected genes on chromosome 17.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Diagram showing location of FISH probes and selected genes on chromosome 17</bold>. The locations of the 6 mapping probes and LSI^®Her2 probe pictured in Figure 1 are based on the probe sequences in the May 2006 assembly of the human genome browser on the University of California, Santa Clara web site <ext-link ext-link-type=\"uri\" xlink:href=\"http://genome.ucsc.edu/\"/>.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Association between frequency of expression of TOP2A and MIB1 in breast carcinoma cells.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Time to recurrence for patients with stage I–III invasive breast cancer by Amplicon Class.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Survival for patients with stage I–III invasive breast cancer by Amplicon Class.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Clinical and pathologic characteristics of breast tumors by Amplicon class</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\" colspan=\"2\"><bold>Tumor Properties</bold></td><td align=\"left\" colspan=\"4\"><bold>Amplicon Class, number of patients</bold></td><td/></tr></thead><tbody><tr><td/><td/><td align=\"left\"><bold>Class I</bold></td><td align=\"left\"><bold>Class II</bold></td><td align=\"left\"><bold>Class III</bold></td><td align=\"left\"><bold>Class IV</bold></td><td align=\"left\"><bold>p-value</bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\">Invasion</td><td align=\"left\">present</td><td align=\"left\">14</td><td align=\"left\">12</td><td align=\"left\">14</td><td align=\"left\">14</td><td align=\"left\">0.913</td></tr><tr><td/><td align=\"left\">DCIS only</td><td align=\"left\">2</td><td align=\"left\">3</td><td align=\"left\">2</td><td align=\"left\">2</td><td/></tr><tr><td align=\"left\">Type (invasive)</td><td align=\"left\">Ductal</td><td align=\"left\">12</td><td align=\"left\">12</td><td align=\"left\">14</td><td align=\"left\">14</td><td align=\"left\">0.115</td></tr><tr><td/><td align=\"left\">Lobular</td><td align=\"left\">2</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td/></tr><tr><td align=\"left\">Grade (invasive)</td><td align=\"left\">II</td><td align=\"left\">5</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">4</td><td align=\"left\">0.146</td></tr><tr><td/><td align=\"left\">III</td><td align=\"left\">9</td><td align=\"left\">10</td><td align=\"left\">13</td><td align=\"left\">10</td><td/></tr><tr><td align=\"left\">Clinical Stage</td><td align=\"left\">I</td><td align=\"left\">5</td><td align=\"left\">6</td><td align=\"left\">6</td><td align=\"left\">4</td><td align=\"left\">0.336</td></tr><tr><td/><td align=\"left\">II</td><td align=\"left\">4</td><td align=\"left\">5</td><td align=\"left\">5</td><td align=\"left\">5</td><td/></tr><tr><td/><td align=\"left\">III</td><td align=\"left\">2</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">5</td><td/></tr><tr><td/><td align=\"left\">IV</td><td align=\"left\">3</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">0</td><td/></tr><tr><td align=\"left\">Age</td><td align=\"left\">under 50</td><td align=\"left\">6</td><td align=\"left\">6</td><td align=\"left\">7</td><td align=\"left\">9</td><td align=\"left\">0.720</td></tr><tr><td/><td align=\"left\">over 50</td><td align=\"left\">10</td><td align=\"left\">9</td><td align=\"left\">9</td><td align=\"left\">7</td><td/></tr><tr><td align=\"left\">Hormone receptors</td><td align=\"left\">ER+/PR+</td><td align=\"left\">4</td><td align=\"left\">3</td><td align=\"left\">3</td><td align=\"left\">3</td><td align=\"left\">0.710</td></tr><tr><td/><td align=\"left\">ER+/PR-</td><td align=\"left\">4</td><td align=\"left\">2</td><td align=\"left\">5</td><td align=\"left\">3</td><td/></tr><tr><td/><td align=\"left\">ER-/PR+</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">0</td><td/></tr><tr><td/><td align=\"left\">ER-/Pr-</td><td align=\"left\">4</td><td align=\"left\">6</td><td align=\"left\">6</td><td align=\"left\">8</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Clinical outcome is associated with Amplicon Class for patients with stage I–III invasive breast cancer</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Amplicon Class</bold></td><td align=\"center\" colspan=\"2\">Clinical outcome and number of patients (Total N = 33)</td></tr><tr><td/><td colspan=\"2\"><hr/></td></tr><tr><td/><td align=\"left\">NED or DNED</td><td align=\"left\">AWD or DOD</td></tr></thead><tbody><tr><td align=\"left\"><bold>Class I</bold></td><td align=\"left\">6 (4)</td><td align=\"left\">2 (0)</td></tr><tr><td align=\"left\"><bold>Class II</bold></td><td align=\"left\">6 (5)</td><td align=\"left\">1 (0)</td></tr><tr><td align=\"left\"><bold>Class III</bold></td><td align=\"left\">9 (9)</td><td align=\"left\">0</td></tr><tr><td align=\"left\"><bold>Class IV</bold></td><td align=\"left\">3 (1)</td><td align=\"left\">6 (4)</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p><bold>NED</bold>: alive with no evidence of disease. <bold>DNED</bold>: died with no evidence of disease at least 24 months after diagnosis. <bold>AWD</bold>: Alive with breast cancer. <bold>DOD</bold>: died of breast cancer. NED and DNED were categorized as favorable outcome, and DOD and AWD as unfavorable for this analysis. Numbers in parentheses refer to the number of patients who received anthracycline-based therapy. The association between Amplicon class and clinical outcome is strongly significant, permutation based exact p-value = 0.007 from a chi-square test.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1756-8722-1-12-1\"/>", "<graphic xlink:href=\"1756-8722-1-12-2\"/>", "<graphic xlink:href=\"1756-8722-1-12-3\"/>", "<graphic xlink:href=\"1756-8722-1-12-4\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p><italic>Staphylococcus aureus </italic>is one of the most significant human pathogens responsible for nosocomial and community acquired infections. It can cause a range of infectious disease from mild conditions, such as soft tissue infections, to severe life-threatening debiliation, such as endocarditis [##REF##15646406##1##]. Despite the recent staphylococci infections, they are persisting as an important hospital and community pathogen [##UREF##0##2##]. Methicillin resistance has become a major concern to the medical community due to the fact that they have an extraordinary ability to adapt rapidly to antibiotic stress [##UREF##1##3##]. Among hospital isolates the frequency of methicillin resistant <italic>S. aureus </italic>(MRSA) is very high [##REF##16449952##4##]. There is need to have new chemicals for treatment of staphylococci infections.</p>", "<p>The sulfonamides have, for many years, being widely studied for their chemotherapeutic activity. Their important role as antibacterial, antimalarial and antileprotic agents is well recognized [##UREF##2##5##,##REF##9280367##6##]. Recently, certain sulfonamides have been reported as showing interesting the antibacterial properties of sulfonamides have been extensively studied by Quantitive Structure-activity Relationship&amp;Molecular Modeling (QSAR) method. [##UREF##3##7##]. Antimicrobial therapy for infections with <italic>S. aureus </italic>often includes sulfonamides which are use to cure nosocomial infections [##REF##15646406##1##]. Sulfonamides are still an alternative option in order to cure methicillin resistant <italic>S. aureus </italic>(MRSA) staphylococci infections. Although the sulfonamide therapy has been reduced, owing to development of more effective antimicrobial agents and to the gradual increase in the resistance of bacterial species, clinical treatment with sulfonamides has undergone a revival by the combination sulfomethoxazole and trimethoprim.</p>", "<p>Considering this background, the objective of this study some sulfonamides derivatives were tested in terms of antimicrobial activity with the purpose of revealing possible leading compounds for development of new antimicrobial agents against methicillin resistant <italic>S. aureus </italic>(MRSA) and methicillin sensitive <italic>S. aureus </italic>MSSA.</p>" ]

[ "<title>Methods</title>", "<title>Preparation of the sulfonamides</title>", "<p>General procedure for preparation of the sulfonamides is as follows [##UREF##4##8##]. For a typical run; 0.06 mol substituted aniline was dissolved in 30 ml benzene. 0.06 mol <italic>p</italic>-toluenesulfonylchloride in 20 ml benzene was added into the solution. 0.06 mol dry pyridine was added into 20 ml benzene slowly and it was refluxed for 4 h, so the solvent was removed and a solid was obtained. The solid was dissolved in 10% (w/II) NaOH solution and extracted with CHCl₃. Aqueous solution was acidified with HCl to obtain raw sulfonamide. Recrystallization of ethanol-water mixture from raw sulfonamide resulted in corresponding sulfonamide in pure form [##UREF##5##9##]. Some physical and spectral data of the synthesized sulfonamides were summarized below:</p>", "<p><bold><italic>N- </italic>(2-<italic>Hydroxy</italic>-4-<italic>nitro-phenyl</italic>)-4-<italic>methyl-benzenesulfonamide </italic>(I) </bold>m.p. 181–182°C. ¹H NMR (acetone-<italic>d</italic>₆), <italic>δ</italic>(ppm) 2.23 (s,3H), 3.37 (s,1H), 7.34 (d,2H), 7.63 (d,2H), 7.71 (dd,1H), 7.82 (d,2H), 8.65 (s,1H), 10.99 (s,1H); IR (KBr) 3608 (OH), 3270 (NH), 3079 (Ar-H), 2920, 1596, 1525 (NO₂asym.), 1446, 1402, (SO₂asym.), 1336 (NO₂sym.), 1270, 1162, 1128 (SO₂sym.) cm^-1[##UREF##1##3##].</p>", "<p><bold><italic>N</italic>-(2-<italic>Hydroxy</italic>-5-<italic>nitro-phenyl</italic>)-4-<italic>methyl-benzenesulfonamide </italic>(II) </bold>m.p. 208–209°C. ¹H NMR (acetone-<italic>d</italic>₆), <italic>δ </italic>(ppm) 2.32 (s,3H), 3.60 (broad,1H,-NH), 6.97 (d,1H), 7.31 (d,2H), 7.75 (d,2H), 7.87 (dd,1H), 8.33 (d,1H), 8.55 (broad,1H,-OH); IR (KBr) 3407 (OH), 3280 (NH), 3085 (Ar-H), 2930, 1596, 1523 (NO₂asym.), 1454, (SO₂asym.), 1342 (NO₂sym.), 1164 (SO₂sym.) cm^-1[##REF##16449952##4##].</p>", "<p><bold><italic>N</italic>-(5-<italic>Chloro</italic>-2-<italic>hydroxy-phenyl</italic>)-4-<italic>methyl-benzenesulfonamide </italic>(III) </bold>m.p. 189–190°C. ¹H NMR (acetone-<italic>d</italic>₆), <italic>δ </italic>(ppm) 2.35 (s,3H), 3.55 (broad,1H,-NH), 6.79 (d,1H), 6.92 (dd,1H), 7.31 (d,2H), 7.36 (d,1H), 7.71 (d,2H), 8.62 (broad,1H,-OH); IR (KBr) 3450 (OH), 3259 (NH), 3080, 2930, 1602, 1504, 1440, 1384, 1319 (SO₂asym.), 1216, 1170 (SO₂sym.) cm^-1[##UREF##1##3##].</p>", "<p><bold><italic>N</italic>-(2-<italic>Hydroxy</italic>-5-<italic>methyl-phenyl</italic>)-4-<italic>methyl-benzenesulfonamide </italic>(IV)) </bold>m.p. 142–143°C. ¹H NMR (acetone-d₆), <italic>δ </italic>(ppm) 2.14 (s,3H), 2.33 (s,3H), 3.47 (broad,1H,-NH), 6.67 (d,1H), 6.74 (dd,1H), 7.13 (s,1H), 7.27 (d,2H), 7.67 (d,2H), 8.46 (broad,1H,-OH); IR (KBr) 3370 (OH), 3247 (NH), 3039, 2917, 1596, 1517, 1446, 1390, 1321 (SO₂asym.), 1290, 1245, 1187, 1162, 1112 (SO₂sym.) cm^-1[##UREF##1##3##].</p>", "<title>Bacterial strains and inoculums preparation</title>", "<p>As a preliminary screening for antimicrobial activity of 4 sulfonamides were tested against 30 meticillin resistant (MRSA) and 20 susceptible (MSSA) clinical isolates of <italic>Staphylococcus aureus </italic>provided by Ondokuz Mayis University, Medical School Department of Microbiology and Infectious disease. MRSA isolates were determined by oxacillin test. The commonly used method in routine laboratory practice for the detection of methicillin resistance is oxacillin disc diffusion. All the clinical isolates were isolated from patients in the hospital. Each <italic>Staphylococcus aureus </italic>isolates were cultured in nutrient broth before the antimicrobial activity test performed. Each isolate was checked for its purity and several colonies were emulsified into 50 ml nutrient broth (LabM). The inoculated flasks were incubated at 37C for 18 h on a rotary shaker at 150 rpm (GFL 3032). Reference strain of <italic>Staphylococcus aureus </italic>ATCC 29213 was used as control strain reference strain in order to monitor the antimicrobial disc susceptibility test [##UREF##6##10##].</p>", "<title>Antimicrobial activity Screening</title>", "<p>Antimicrobial studies were performed according to agar disc diffusion method [##UREF##7##11##]. To obtain more significant information as to the antibacterial potency of sulfonamides derivatives compound I, II, III, and IV against <italic>Staphylococcus aureus</italic>, subcultures were carried out and minimal bactericidal concentration were determined. The following test conditions were applied; all the compounds were dissolved in dimethylsulfoxid (DMSO, Merck). Sensitest agar (Oxoid) plates were prepared and dried at 35–36°C for about 30 min in an incubator. Test strains were spreaded on solid sensitest agar surface by using sterile swap. Spreaded inoculums were 3.5 × 10⁵colony forming unit/ml^-1(0.5 McFarland standards, Biomeriux Colorimeter). At the same time, absorbent paper discs were placed on agar surface (5 mm for compounds and 6 mm for antibiotics)and impregnated with known concentrations which determined previously by MIC tests (500 μg for each disc). Oxacillin 1 μg (Oxoid) and Trimetoprim-Sulfametaksazol 23.75 μg were also used for all test microorganisms as positive control. Blank test showed that DMSO in the preparations of the test solutions does not affect the test organisms. They were inverted and allowed to incubate at 37°C. The inhibition zone around the disc was calculated edge to edge zone of confluent growth which is usually corresponds to the sharpest edge of the zone and to be measured diameter in millimeter. All tests were repeated tree times and average data taken as final result.</p>" ]

[ "<title>Results and discussion</title>", "<p>Methicillin-resistant staphylococci are resistant to all other penicillin, carbapenems, cephems and beta-lactam, beta-lactam inhibitor combinations [##UREF##7##11##]. Consequently these antibiotics should not be used for treating of methicillin-resistant staphylococci infections. Moreover, recently several studies have shown that the methicillin-resistant staphylococci have started to gain resistance to some other widely used antibiotics (quinolone, macrolide group antibiotics, amino glycosides, tetracycline, trimetoprim sulphamethoxazole (SXT), clindamicin, chloramphenicol as well [##REF##10838776##12##, ####REF##12741734##13##, ##UREF##8##14##, ##REF##15379145##15####15379145##15##]. The resistance increase trimetoprim-sulphametoxazole, which is an alternative medicine in the treatment of methicillin-resistant staphylococci infections, is recently received attention. Previously, trimetoprim-sulphametoxazole resistance has been shown to be 10–53% in Turkey while it was reportedly higher (47–79%) in European countries [##UREF##9##16##]. Trimetoprim-sulphamethoxazole is used for the treatment of staphylococci infections. SXT has still maintain its' an alternative antibiotic potential for the treatment of MRSA and MSSA infections [##REF##15646406##1##]. In addition, sulphametizol, sulphamethaxozole or sulphisoxazole have been using for the treatment of <italic>E. coli </italic>urinary infection as a single antibiotics [##REF##15646406##1##].</p>", "<p>In this study, the in vitro antibacterial activity properties of the compounds tested on clinical isolates of 30 MRSA and 20 MSSA <italic>S. aureus </italic>by using new sulfonamide derivative compounds namely <italic>N</italic>-(2-Hydroxy-4-nitro-phenyl)-4-methyl-benzenesulfonamide(I), N-(2-Hydroxy-5-nitro-phenyl)-4-methyl-benzenesulfonamide, N-(5-Chloro-2-hydroxy-phenyl)-4-methyl-benzenesulfonamide(III&gt;), N-(2-Hydroxy-5-methyl-phenyl)-4-methyl-benzenesulfonamide(IV). Some of the sulfonamides were found to be effective on <italic>S. aureus </italic>among the others. The strongest inhibition was detected by the effect of (N-(2-Hydroxy-4-nitro-phenyl)-4-metil-benzensulfonamide) (<bold>I</bold>). The similar results were obtained in previous studies against <italic>Nocardia </italic>species by the treatment of the same sulfonamide compound (Isik and Özdemir-Koçak, article in press in Microb. Res.)</p>", "<p>First of all, we tried to find out (Minimal Inhibitory Concentrations) MIC values of sulfonamides derivatives against <italic>S. aureus </italic>isolates. The rate of MIC values showed alterations from 32 to 512 μg for 50 isolates. All data are given in Table ##TAB##0##1## indicated that MIC values was not the same for all isolates i.e. showed variations in terms of resistance. It was given in the literature that treatment of some infections 300 μg sulfafurazol and sulfisoxazole ST are applied to patients [##UREF##6##10##]. After determining the minimum and maximum MIC values, suitable concentration was selected for all isolates in order to proper comparison. It means, MIC values given in table ##TAB##0##1## showed that sulfonamide derivatives I and II given here area potential antibacterial substances. It was also reported that I, and II numbered substances showed strong antibacterial activity against <italic>Staphylococcus aureus </italic>ATTCC 43300 and some other gram positive bacteria [##UREF##10##17##]. Here tested compounds I, II, and III showed antibacterial activity against reference strain <italic>S. aureus </italic>ATTCC 29213 and their concentration were 32, 64 and 128 μg respectively. Compound I was found as a strongest antibacterial agent against <italic>S. aureus </italic>according to MIC values. The MIC values showed some alterations according to <italic>S. aureus </italic>strains given in Table ##TAB##0##1##.</p>", "<p>Secondly, antimicrobial activity of compounds was tested according to disc diffusion method on the base of MIC values. 500 μg concentrations were chosen as a suitable concentration which showed an effect to all <italic>S. aureus </italic>isolates. All data related to inhibition zones against <italic>S. aureus </italic>were given in Table ##TAB##1##2##. As regard to results the strongest inhibition was observed in case of compound I. In general, the ratio of inhibition caused by Compound I, II and III were 84%, 50% and 36% respectively (Table ##TAB##2##3##).</p>", "<p>Early and recent researchers have suggested that sulfonamides are useful for the treatment of some staphylococci infections, especially against urinary infections [##REF##15646406##1##]. In this study, some sulfonamides derivatives were tested in terms of antimicrobial activity with the purpose of revealing possible leading compounds for the development of new antimicrobial agents. Outcome of the study showed that sulfonamide derivatives I and II have proved to be effective enough, which is comparable with previous studies [##UREF##10##17##]. It was reported that, sulfonamide <bold>I </bold>and <bold>II </bold>showed the highest inhibitory effect on gram positive bacteria i.e. <italic>S. aureus, N. asteroides, N. farcinia and B. subtilis</italic>. On the contrary, they did not lead to significant inhibitory effect on gram negative bacteria and also yeast and mould namely <italic>E. coli, P. aeruginosa, E. cloaceae</italic>, a yeast <italic>C. albicans </italic>and a mould <italic>A. niger </italic>[##UREF##10##17##].</p>", "<p>Many attempts have been made to relate the antibacterial behavior of sulfonamides with molecular structure [##REF##9280367##6##]. It was shown here that antimicrobial activities of the sulfonamides were increased when introducing electron withdrawing groups into the benzene ring of the compounds (Table ##TAB##1##2##). The compound I has NO₂group in para position according to the sulfonamide group which showed the strongest effect on the <italic>S. aureus</italic>. Ionization is important factor on antimicrobial effect of sulfonamides due to increasing solubility. The behaviors of o-substituted acids are often anomalous [##UREF##11##18##]. Their strength is sometimes found to be much greater than expected due to direct interaction between the adjacent groups. For example, <italic>o</italic>-hydroxybenzoic acid is 10 times stronger than <italic>p</italic>-hydroxybenzoic acid. In the case of the sulfonamides, possibly the OH group in the <italic>ortho </italic>position stabilize the developing negative charge on the nitrogen through intramolecular hydrogen bonding, and in this way the ionization increases. As can be seen in table ##TAB##1##2## the compound I is more effective against the bacteria possibly due to increasing ionization of N-H group which is enhanced by p-NO₂group. OH group in ortho position is also supports ionization by involving intramolecular hydrogen bonding.</p>", "<p>Introducing NO₂group to meta position (compound II) reduces antimicrobial activity in general this is because of lesser effect of this position on N-H group. Chlorine substituted sulfonamide III has a weaker antimicrobial activity than NO₂substituted ones due to less electron withdrawing ability of the chlorine. This is also supported by the results obtained by compound IV which has CH₃group in meta position. Methyl group donates electron to the benzene ring therefore reduces the ionization dramatically of the compound. The correlation of antimicrobial activity with chemical facts of the current study are also in line with biological activity results [##REF##15158781##19##].</p>", "<p>Antimicrobial activities of the sulfonamides depend on substituent and their position in the benzene ring. While electron releasing group decreases, electron withdrawing groups enhanced the activity of the sulfonamides against <italic>S. aureus </italic>isolates. Although sulfonamide-based therapy is generally effective, optimal treatment could be guided by antimicrobial susceptibility testing of isolates. Moreover, experimental data show that compound I may also be considered as a broad spectral effective sulfonamide at 128 μg (78% in total isolates) against MRSA and MSSA <italic>S. aureus </italic>isolates. Although 30 out of 50 <italic>S. aureus </italic>isolates showed resistance to oxacillin antibiotic, 21 of them were susceptible mainly to compound I and II.</p>" ]

[ "<title>Results and discussion</title>", "<p>Methicillin-resistant staphylococci are resistant to all other penicillin, carbapenems, cephems and beta-lactam, beta-lactam inhibitor combinations [##UREF##7##11##]. Consequently these antibiotics should not be used for treating of methicillin-resistant staphylococci infections. Moreover, recently several studies have shown that the methicillin-resistant staphylococci have started to gain resistance to some other widely used antibiotics (quinolone, macrolide group antibiotics, amino glycosides, tetracycline, trimetoprim sulphamethoxazole (SXT), clindamicin, chloramphenicol as well [##REF##10838776##12##, ####REF##12741734##13##, ##UREF##8##14##, ##REF##15379145##15####15379145##15##]. The resistance increase trimetoprim-sulphametoxazole, which is an alternative medicine in the treatment of methicillin-resistant staphylococci infections, is recently received attention. Previously, trimetoprim-sulphametoxazole resistance has been shown to be 10–53% in Turkey while it was reportedly higher (47–79%) in European countries [##UREF##9##16##]. Trimetoprim-sulphamethoxazole is used for the treatment of staphylococci infections. SXT has still maintain its' an alternative antibiotic potential for the treatment of MRSA and MSSA infections [##REF##15646406##1##]. In addition, sulphametizol, sulphamethaxozole or sulphisoxazole have been using for the treatment of <italic>E. coli </italic>urinary infection as a single antibiotics [##REF##15646406##1##].</p>", "<p>In this study, the in vitro antibacterial activity properties of the compounds tested on clinical isolates of 30 MRSA and 20 MSSA <italic>S. aureus </italic>by using new sulfonamide derivative compounds namely <italic>N</italic>-(2-Hydroxy-4-nitro-phenyl)-4-methyl-benzenesulfonamide(I), N-(2-Hydroxy-5-nitro-phenyl)-4-methyl-benzenesulfonamide, N-(5-Chloro-2-hydroxy-phenyl)-4-methyl-benzenesulfonamide(III&gt;), N-(2-Hydroxy-5-methyl-phenyl)-4-methyl-benzenesulfonamide(IV). Some of the sulfonamides were found to be effective on <italic>S. aureus </italic>among the others. The strongest inhibition was detected by the effect of (N-(2-Hydroxy-4-nitro-phenyl)-4-metil-benzensulfonamide) (<bold>I</bold>). The similar results were obtained in previous studies against <italic>Nocardia </italic>species by the treatment of the same sulfonamide compound (Isik and Özdemir-Koçak, article in press in Microb. Res.)</p>", "<p>First of all, we tried to find out (Minimal Inhibitory Concentrations) MIC values of sulfonamides derivatives against <italic>S. aureus </italic>isolates. The rate of MIC values showed alterations from 32 to 512 μg for 50 isolates. All data are given in Table ##TAB##0##1## indicated that MIC values was not the same for all isolates i.e. showed variations in terms of resistance. It was given in the literature that treatment of some infections 300 μg sulfafurazol and sulfisoxazole ST are applied to patients [##UREF##6##10##]. After determining the minimum and maximum MIC values, suitable concentration was selected for all isolates in order to proper comparison. It means, MIC values given in table ##TAB##0##1## showed that sulfonamide derivatives I and II given here area potential antibacterial substances. It was also reported that I, and II numbered substances showed strong antibacterial activity against <italic>Staphylococcus aureus </italic>ATTCC 43300 and some other gram positive bacteria [##UREF##10##17##]. Here tested compounds I, II, and III showed antibacterial activity against reference strain <italic>S. aureus </italic>ATTCC 29213 and their concentration were 32, 64 and 128 μg respectively. Compound I was found as a strongest antibacterial agent against <italic>S. aureus </italic>according to MIC values. The MIC values showed some alterations according to <italic>S. aureus </italic>strains given in Table ##TAB##0##1##.</p>", "<p>Secondly, antimicrobial activity of compounds was tested according to disc diffusion method on the base of MIC values. 500 μg concentrations were chosen as a suitable concentration which showed an effect to all <italic>S. aureus </italic>isolates. All data related to inhibition zones against <italic>S. aureus </italic>were given in Table ##TAB##1##2##. As regard to results the strongest inhibition was observed in case of compound I. In general, the ratio of inhibition caused by Compound I, II and III were 84%, 50% and 36% respectively (Table ##TAB##2##3##).</p>", "<p>Early and recent researchers have suggested that sulfonamides are useful for the treatment of some staphylococci infections, especially against urinary infections [##REF##15646406##1##]. In this study, some sulfonamides derivatives were tested in terms of antimicrobial activity with the purpose of revealing possible leading compounds for the development of new antimicrobial agents. Outcome of the study showed that sulfonamide derivatives I and II have proved to be effective enough, which is comparable with previous studies [##UREF##10##17##]. It was reported that, sulfonamide <bold>I </bold>and <bold>II </bold>showed the highest inhibitory effect on gram positive bacteria i.e. <italic>S. aureus, N. asteroides, N. farcinia and B. subtilis</italic>. On the contrary, they did not lead to significant inhibitory effect on gram negative bacteria and also yeast and mould namely <italic>E. coli, P. aeruginosa, E. cloaceae</italic>, a yeast <italic>C. albicans </italic>and a mould <italic>A. niger </italic>[##UREF##10##17##].</p>", "<p>Many attempts have been made to relate the antibacterial behavior of sulfonamides with molecular structure [##REF##9280367##6##]. It was shown here that antimicrobial activities of the sulfonamides were increased when introducing electron withdrawing groups into the benzene ring of the compounds (Table ##TAB##1##2##). The compound I has NO₂group in para position according to the sulfonamide group which showed the strongest effect on the <italic>S. aureus</italic>. Ionization is important factor on antimicrobial effect of sulfonamides due to increasing solubility. The behaviors of o-substituted acids are often anomalous [##UREF##11##18##]. Their strength is sometimes found to be much greater than expected due to direct interaction between the adjacent groups. For example, <italic>o</italic>-hydroxybenzoic acid is 10 times stronger than <italic>p</italic>-hydroxybenzoic acid. In the case of the sulfonamides, possibly the OH group in the <italic>ortho </italic>position stabilize the developing negative charge on the nitrogen through intramolecular hydrogen bonding, and in this way the ionization increases. As can be seen in table ##TAB##1##2## the compound I is more effective against the bacteria possibly due to increasing ionization of N-H group which is enhanced by p-NO₂group. OH group in ortho position is also supports ionization by involving intramolecular hydrogen bonding.</p>", "<p>Introducing NO₂group to meta position (compound II) reduces antimicrobial activity in general this is because of lesser effect of this position on N-H group. Chlorine substituted sulfonamide III has a weaker antimicrobial activity than NO₂substituted ones due to less electron withdrawing ability of the chlorine. This is also supported by the results obtained by compound IV which has CH₃group in meta position. Methyl group donates electron to the benzene ring therefore reduces the ionization dramatically of the compound. The correlation of antimicrobial activity with chemical facts of the current study are also in line with biological activity results [##REF##15158781##19##].</p>", "<p>Antimicrobial activities of the sulfonamides depend on substituent and their position in the benzene ring. While electron releasing group decreases, electron withdrawing groups enhanced the activity of the sulfonamides against <italic>S. aureus </italic>isolates. Although sulfonamide-based therapy is generally effective, optimal treatment could be guided by antimicrobial susceptibility testing of isolates. Moreover, experimental data show that compound I may also be considered as a broad spectral effective sulfonamide at 128 μg (78% in total isolates) against MRSA and MSSA <italic>S. aureus </italic>isolates. Although 30 out of 50 <italic>S. aureus </italic>isolates showed resistance to oxacillin antibiotic, 21 of them were susceptible mainly to compound I and II.</p>" ]

[ "<title>Conclusion</title>", "<p>Sulfonamides are still an alternative option in order to cure MRSA staphylococci infections. However, increasing resistance against sulfonamides is a serious problem recently that has been taken attention. Therefore, there is need to have new chemicals for treatment of staphylococci and other bacterial infections. Outcome of the study has two noteworthy features. This study may help to suggest an alternative possible leading compound for development of new antimicrobial agents against MRSA and MSSA resistant <italic>S. aureus</italic>. It was also shown here that that clinical isolates of 50 <italic>S. aureus </italic>have various resistance patterns against to four sulfonamide derivatives. It may also be emphasized here that in vitro antimicrobial susceptibility testing results for <italic>S. aureus </italic>species need standardization with further studies and it should also have a correlation with in vivo therapeutic response experiments</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p><italic>Staphylococcus aureus </italic>is a non-motile, gram positive, non-sporforming, facultative anaerobic microorganism. It is one of the important bacteria as a potential pathogen specifically for nosocomial infections. The sulfonamide derivative medicines are preferred to cure infection caused by <italic>S. aureus </italic>due to methicillin resistance.</p>", "<title>Methods</title>", "<p>Antimicrobial activity of four sulfonamide derivatives have been investigated against 50 clinical isolates of <italic>S. aureus </italic>and tested by using MIC and disc diffusion methods. 50 clinical isolate which collected from specimens of patients who are given medical treatment in Ondokuz Mayis University Medical School Hospital. A control strain of <italic>S. aureus </italic>ATCC 29213 was also tested.</p>", "<title>Results</title>", "<p>The strongest inhibition was observed in the cases of <bold>I </bold>[<italic>N</italic>-(2-hydroxy-4-nitro-phenyl)-4-methyl-benzensulfonamid], and <bold>II </bold>[<italic>N</italic>-(2-hydroxy-5-nitro-phenyl)-4-methyl-benzensulfonamid] against <italic>S. aureus</italic>. Compound <bold>I </bold>[<italic>N</italic>-(2-hydroxy-4-nitro-phenyl)-4-methyl-benzensulfonamid] showed higher effect on 21 <italic>S. aureus </italic>MRSAisolates than oxacillin antibiotic. Introducing an electron withdrawing on the ring increased the antimicrobial activity remarkably.</p>", "<title>Conclusion</title>", "<p>This study may help to suggest an alternative possible leading compound for development of new antimicrobial agents against MRSA and MSSA resistant <italic>S. aureus</italic>. It was also shown here that that clinical isolates of 50 <italic>S. aureus </italic>have various resistance patterns against to four sulfonamide derivatives. It may also be emphasized here that in vitro antimicrobial susceptibility testing results for <italic>S. aureus </italic>need standardization with further studies and it should also have a correlation with in vivo therapeutic response experiments.</p>" ]

[ "<title>Abbreviations</title>", "<p>MRSA: methicillin resistant <italic>S. aureus</italic>; MSSA: methicillin susceptible <italic>S. aureus</italic>; SXT: trimetoprim sulphamethoxazole; DMSO: dimethylsulfoxid</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>All authors have read and approved the final manuscript. RÖ participated in the analysis of the data and coordinated and drafted the manuscript. YG carried out the antimicrobial activity tests and the data analysis. YB participate the production of sulfonamide derivatives and approving the final manuscript.</p>" ]

[]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>MIC values of sulfonamides derivatives I, II, and III against total 50 <italic>S. aureus </italic>clinical isolates (data given as percentage). </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"2\"><bold>Compound I</bold></td><td align=\"left\"><bold>Compound II</bold></td><td align=\"left\"><bold>Compound III</bold></td></tr></thead><tbody><tr><td align=\"left\">MICs (μg)</td><td align=\"center\">Number of susceptible Isolates (%)</td><td align=\"center\">Number of susceptible Isolates (%)</td><td align=\"center\">Number of susceptible Isolates (%)</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">32</td><td align=\"center\">3 (6)</td><td align=\"center\">0 (0)</td><td align=\"center\">0 (0)</td></tr><tr><td align=\"left\"><bold>64</bold></td><td align=\"center\">14(28)</td><td align=\"center\">6 (12)</td><td align=\"center\">0 (0)</td></tr><tr><td align=\"left\"><bold>128</bold></td><td align=\"center\">19 (38)</td><td align=\"center\">39 (78)</td><td align=\"center\">18 (36)</td></tr><tr><td align=\"left\"><bold>256</bold></td><td align=\"center\">12 (24)</td><td align=\"center\">5 (10)</td><td align=\"center\">22 (44)</td></tr><tr><td align=\"left\"><bold>512</bold></td><td align=\"center\">2 (4)</td><td align=\"center\">0 (0)</td><td align=\"center\">10 (20)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Measured inhibition zone in diameter (mm) of sulfonamide derivatives (I-IV) (500 μg) against clinical isolates of <italic>Staphylococcus aureus</italic>.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>S. aureus Isolation Number</bold></td><td align=\"center\"><bold>Compound II</bold></td><td align=\"center\"><bold>Compound II</bold></td><td align=\"center\"><bold>Compound III</bold></td><td align=\"center\"><bold>Compound IV</bold></td><td align=\"center\"><bold>OX (mm)</bold></td><td align=\"center\"><bold>SXT (mm)</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>SAY01(MRSA)</bold></td><td align=\"center\">20</td><td align=\"center\">14</td><td align=\"center\">5</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">24</td></tr><tr><td align=\"left\"><bold>SAY02(MRSA)</bold></td><td align=\"center\">22</td><td align=\"center\">15</td><td align=\"center\">11</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">25,5</td></tr><tr><td align=\"left\"><bold>SAY03(MRSA)</bold></td><td align=\"center\">26</td><td align=\"center\">17</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">28,5</td></tr><tr><td align=\"left\"><bold>SAY04(MSSA)</bold></td><td align=\"center\">19</td><td align=\"center\">17</td><td align=\"center\">13</td><td align=\"center\">0</td><td align=\"center\">13,5</td><td align=\"center\">28,5</td></tr><tr><td align=\"left\"><bold>SAY05(MSSA)</bold></td><td align=\"center\">23</td><td align=\"center\">18</td><td align=\"center\">16</td><td align=\"center\">0</td><td align=\"center\">13,5</td><td align=\"center\">28</td></tr><tr><td align=\"left\"><bold>SAY06(MRSA)</bold></td><td align=\"center\">23</td><td align=\"center\">18</td><td align=\"center\">10</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">26</td></tr><tr><td align=\"left\"><bold>SAY07(MRSA)</bold></td><td align=\"center\">25</td><td align=\"center\">18</td><td align=\"center\">19</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">25</td></tr><tr><td align=\"left\"><bold>SAY08(MRSA)</bold></td><td align=\"center\">26</td><td align=\"center\">19</td><td align=\"center\">13</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">26</td></tr><tr><td align=\"left\"><bold>SAY09(MRSA)</bold></td><td align=\"center\">19</td><td align=\"center\">16</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">24</td></tr><tr><td align=\"left\"><bold>SAY10(MRSA)</bold></td><td align=\"center\">25</td><td align=\"center\">17</td><td align=\"center\">11</td><td align=\"center\">7</td><td align=\"center\">0</td><td align=\"center\">23</td></tr><tr><td align=\"left\"><bold>SAY11(MRSA)</bold></td><td align=\"center\">25</td><td align=\"center\">13</td><td align=\"center\">11</td><td align=\"center\">9</td><td align=\"center\">0</td><td align=\"center\">27</td></tr><tr><td align=\"left\"><bold>SAY12(MRSA)</bold></td><td align=\"center\">29</td><td align=\"center\">19</td><td align=\"center\">11</td><td align=\"center\">9</td><td align=\"center\">0</td><td align=\"center\">25,5</td></tr><tr><td align=\"left\"><bold>SAY13(MRSA)</bold></td><td align=\"center\">13</td><td align=\"center\">14</td><td align=\"center\">10</td><td align=\"center\">9</td><td align=\"center\">0</td><td align=\"center\">25</td></tr><tr><td align=\"left\"><bold>SAY14(MRSA)</bold></td><td align=\"center\">23</td><td align=\"center\">17</td><td align=\"center\">15</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">25</td></tr><tr><td align=\"left\"><bold>SAY15(MRSA)</bold></td><td align=\"center\">21</td><td align=\"center\">14</td><td align=\"center\">14</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">26,5</td></tr><tr><td align=\"left\"><bold>SAY16(MRSA)</bold></td><td align=\"center\">25</td><td align=\"center\">18</td><td align=\"center\">13</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">27</td></tr><tr><td align=\"left\"><bold>SAY17(MSSA)</bold></td><td align=\"center\">21</td><td align=\"center\">18</td><td align=\"center\">15</td><td align=\"center\">0</td><td align=\"center\">21</td><td align=\"center\">28,5</td></tr><tr><td align=\"left\"><bold>SAY18(MRSA)</bold></td><td align=\"center\">25</td><td align=\"center\">16</td><td align=\"center\">13</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">23,5</td></tr><tr><td align=\"left\"><bold>SAY19(MSSA)</bold></td><td align=\"center\">21</td><td align=\"center\">16</td><td align=\"center\">16</td><td align=\"center\">0</td><td align=\"center\">18,5</td><td align=\"center\">27</td></tr><tr><td align=\"left\"><bold>SAY20(MRSA)</bold></td><td align=\"center\">26</td><td align=\"center\">15</td><td align=\"center\">15</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">25</td></tr><tr><td align=\"left\"><bold>SAY21(MSSA)</bold></td><td align=\"center\">19</td><td align=\"center\">14</td><td align=\"center\">13</td><td align=\"center\">0</td><td align=\"center\">17,5</td><td align=\"center\">30,5</td></tr><tr><td align=\"left\"><bold>SAY22(MRSA)</bold></td><td align=\"center\">23</td><td align=\"center\">14</td><td align=\"center\">15</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">27</td></tr><tr><td align=\"left\"><bold>SAY23(MSSA)</bold></td><td align=\"center\">20</td><td align=\"center\">16</td><td align=\"center\">13</td><td align=\"center\">9</td><td align=\"center\">20,5</td><td align=\"center\">28</td></tr><tr><td align=\"left\"><bold>SAY24(MSSA)</bold></td><td align=\"center\">14</td><td align=\"center\">15</td><td align=\"center\">14</td><td align=\"center\">0</td><td align=\"center\">17,5</td><td align=\"center\">30</td></tr><tr><td align=\"left\"><bold>SAY25(MSSA)</bold></td><td align=\"center\">12</td><td align=\"center\">20</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">26</td><td align=\"center\">31</td></tr><tr><td align=\"left\"><bold><italic>S. aureus </italic></bold>ATCC 29213</td><td align=\"center\">26</td><td align=\"center\">17</td><td align=\"center\">12</td><td align=\"center\">10</td><td align=\"center\">20</td><td align=\"center\">31</td></tr><tr><td align=\"left\"><bold>SAY26(MSSA)</bold></td><td align=\"center\">28</td><td align=\"center\">25</td><td align=\"center\">15</td><td align=\"center\">0</td><td align=\"center\">23</td><td align=\"center\">32,5</td></tr><tr><td align=\"left\"><bold>SAY27(MSSA)</bold></td><td align=\"center\">19</td><td align=\"center\">11</td><td align=\"center\">14</td><td align=\"center\">9</td><td align=\"center\">18</td><td align=\"center\">28</td></tr><tr><td align=\"left\"><bold>SAY28(MRSA)</bold></td><td align=\"center\">28</td><td align=\"center\">19</td><td align=\"center\">11</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">26,5</td></tr><tr><td align=\"left\"><bold>SAY29(MRSA)</bold></td><td align=\"center\">18</td><td align=\"center\">17</td><td align=\"center\">10</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">26,5</td></tr><tr><td align=\"left\"><bold>SAY30(MRSA)</bold></td><td align=\"center\">20</td><td align=\"center\">13</td><td align=\"center\">12</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">23,5</td></tr><tr><td align=\"left\"><bold>SAY31(MRSA)</bold></td><td align=\"center\">26</td><td align=\"center\">20</td><td align=\"center\">14</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">26</td></tr><tr><td align=\"left\"><bold>SAY32(MSSA)</bold></td><td align=\"center\">21</td><td align=\"center\">15</td><td align=\"center\">14</td><td align=\"center\">10</td><td align=\"center\">19</td><td align=\"center\">26,5</td></tr><tr><td align=\"left\"><bold>SAY33(MSSA)</bold></td><td align=\"center\">18</td><td align=\"center\">12</td><td align=\"center\">14</td><td align=\"center\">11</td><td align=\"center\">19</td><td align=\"center\">28</td></tr><tr><td align=\"left\"><bold>SAY34(MRSA)</bold></td><td align=\"center\">16</td><td align=\"center\">18</td><td align=\"center\">10</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">23,5</td></tr><tr><td align=\"left\"><bold>SAY35(MSSA)</bold></td><td align=\"center\">20</td><td align=\"center\">22</td><td align=\"center\">14</td><td align=\"center\">0</td><td align=\"center\">17</td><td align=\"center\">30</td></tr><tr><td align=\"left\"><bold>SAY36(MSSA)</bold></td><td align=\"center\">25</td><td align=\"center\">16</td><td align=\"center\">16</td><td align=\"center\">9</td><td align=\"center\">20,5</td><td align=\"center\">30</td></tr><tr><td align=\"left\"><bold>SAY37(MRSA)</bold></td><td align=\"center\">13</td><td align=\"center\">15</td><td align=\"center\">11</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">22</td></tr><tr><td align=\"left\"><bold>SAY38(MRSA)</bold></td><td align=\"center\">27</td><td align=\"center\">17</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">25</td></tr><tr><td align=\"left\"><bold>SAY39(MRSA)</bold></td><td align=\"center\">15</td><td align=\"center\">14</td><td align=\"center\">10</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">25,5</td></tr><tr><td align=\"left\"><bold>SAY40(MSSA)</bold></td><td align=\"center\">18</td><td align=\"center\">16</td><td align=\"center\">11</td><td align=\"center\">0</td><td align=\"center\">18</td><td align=\"center\">25,5</td></tr><tr><td align=\"left\"><bold>SAY41(MSSA)</bold></td><td align=\"center\">27</td><td align=\"center\">19</td><td align=\"center\">10</td><td align=\"center\">11</td><td align=\"center\">13</td><td align=\"center\">25,5</td></tr><tr><td align=\"left\"><bold>SAY42(MSSA)</bold></td><td align=\"center\">18</td><td align=\"center\">17</td><td align=\"center\">14</td><td align=\"center\">8</td><td align=\"center\">22,5</td><td align=\"center\">30</td></tr><tr><td align=\"left\"><bold>SAY43(MRSA)</bold></td><td align=\"center\">21</td><td align=\"center\">11</td><td align=\"center\">14</td><td align=\"center\">9</td><td align=\"center\">0</td><td align=\"center\">28</td></tr><tr><td align=\"left\"><bold>SAY44(MRSA)</bold></td><td align=\"center\">21</td><td align=\"center\">16</td><td align=\"center\">11</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">27,5</td></tr><tr><td align=\"left\"><bold>SAY45(MSSA)</bold></td><td align=\"center\">17</td><td align=\"center\">18</td><td align=\"center\">11</td><td align=\"center\">0</td><td align=\"center\">18,5</td><td align=\"center\">30</td></tr><tr><td align=\"left\"><bold>SAY46(MSSA)</bold></td><td align=\"center\">14</td><td align=\"center\">11</td><td align=\"center\">12</td><td align=\"center\">0</td><td align=\"center\">14,5</td><td align=\"center\">21,5</td></tr><tr><td align=\"left\"><bold>SAY47(MRSA)</bold></td><td align=\"center\">22</td><td align=\"center\">13</td><td align=\"center\">12</td><td align=\"center\">8</td><td align=\"center\">0</td><td align=\"center\">26,5</td></tr><tr><td align=\"left\"><bold>SAY48(MRSA)</bold></td><td align=\"center\">14</td><td align=\"center\">18</td><td align=\"center\">11</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">25,5</td></tr><tr><td align=\"left\"><bold>SAY49(MRSA)</bold></td><td align=\"center\">18</td><td align=\"center\">17</td><td align=\"center\">12</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">27</td></tr><tr><td align=\"left\"><bold>SAY50(MSSA)</bold></td><td align=\"center\">21</td><td align=\"center\">22</td><td align=\"center\">12</td><td align=\"center\">0</td><td align=\"center\">20</td><td align=\"center\">31</td></tr><tr><td align=\"left\"><bold><italic>S. aureus </italic></bold>ATCC 29213</td><td align=\"center\">26</td><td align=\"center\">17</td><td align=\"center\">12</td><td align=\"center\">10</td><td align=\"center\">20</td><td align=\"center\">31</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Susceptibility percentage and median zone diameter (mm) of <italic>Staphylococcus aureus </italic>isolates against sulfonamide derivatives and some antimicrobials determined by disc diffusion method.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"2\">Antimicrobials<break/></td><td align=\"center\" colspan=\"3\">Inhibition zone diameter <break/>(mm)^a</td><td align=\"left\" colspan=\"2\">Zone diameter (mm)<break/></td><td align=\"left\" colspan=\"3\">Tested <italic>S. aureus </italic>clinical isolates<break/></td></tr></thead><tbody><tr><td align=\"center\" colspan=\"10\">Susceptibility range (%) (n = 50)^b</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">Name</td><td align=\"center\">Concentration (μg)</td><td align=\"center\">R</td><td align=\"center\">I</td><td align=\"center\">S</td><td align=\"left\">Range</td><td align=\"left\">Median</td><td align=\"left\">R</td><td align=\"left\">I</td><td align=\"left\">S^c</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"left\">Oxacillin</td><td align=\"left\">1 μg</td><td align=\"center\">≤10</td><td align=\"center\">11–12</td><td align=\"center\">≥13</td><td align=\"left\">0–23</td><td align=\"left\">11.5</td><td align=\"left\">30(60)</td><td align=\"left\">0</td><td align=\"left\">20(40)</td></tr><tr><td align=\"left\">Trimetoprim (SXT)</td><td align=\"left\">25 μg</td><td align=\"center\">≤10</td><td align=\"center\">11–15</td><td align=\"center\">≥16</td><td align=\"left\">21.5–32.5</td><td align=\"left\">27</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">50(100)</td></tr><tr><td align=\"left\">Compound I</td><td align=\"left\">500 μg</td><td align=\"center\">≤12</td><td align=\"center\">13–16</td><td align=\"center\">≥17</td><td align=\"left\">12–28</td><td align=\"left\">20</td><td align=\"left\">1(2)</td><td align=\"left\">7(14)</td><td align=\"left\">42(84)</td></tr><tr><td align=\"left\">Compound II</td><td align=\"left\">500 μg</td><td align=\"center\">≤12</td><td align=\"center\">13–16</td><td align=\"center\">≥17</td><td align=\"left\">11–25</td><td align=\"left\">18</td><td align=\"left\">3(6)</td><td align=\"left\">22(44)</td><td align=\"left\">25(50)</td></tr><tr><td align=\"left\">Compound III</td><td align=\"left\">500 μg</td><td align=\"center\">≤12</td><td align=\"center\">13–16</td><td align=\"center\">≥17</td><td align=\"left\">11–19</td><td align=\"left\">15</td><td align=\"left\">13(26)</td><td align=\"left\">19(38)</td><td align=\"left\">18(36)</td></tr><tr><td align=\"left\">Compound IV</td><td align=\"left\">500 μg</td><td align=\"center\">≤12</td><td align=\"center\">13–16</td><td align=\"center\">≥17</td><td align=\"left\">0–11</td><td align=\"left\">5.5</td><td align=\"left\">50(100)</td><td align=\"left\">0</td><td align=\"left\">0</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>Compund IV showed very low activity therefore it was not taken in consideration.</p></table-wrap-foot>", "<table-wrap-foot><p>MRSA (methicillin-resistance <italic>S. aureus</italic>), MSSA (Methicillin Susceptible <italic>S. aureus</italic>). OX (Oxacillin), SXT (trimetoprim-sulphamethoxazole)</p></table-wrap-foot>", "<table-wrap-foot><p>^aZone of inhibition diameter (mm) by disc diffusion method susceptibility testing interpretavive guidelines based on NCCLS 2003.</p><p>^bNumber of parentheses indicate the total number of clinical <italic>S. aureus </italic>isolates tested.</p><p>^cS = susceptible; I = intermediate; R = resistant</p><p>^dTrimetoprim-sulphamethoxazole (SXT) is being taken as a positive control for approximate comparision compounds data</p></table-wrap-foot>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Achalasia is a disorder of esophageal motility which occurs rarely in children [##UREF##0##1##]. Achalasia is caused by loss of inhibitory enervation of lower esophageal sphincter and is characterized by failure of the sphincter to relax. This failure of relaxation causes poor emptying of the esophagus and subsequent dilatation and abnormal contractility of the proximal esophagus. The most commonly presenting symptoms of achalasia include dysphagia, chest pain, vomiting, belching, regurgitation of undigested food and failure to thrive. Cough can occur in achalasia primarily due to aspiration of the undigested food particles or airway compression from dilated esophagus[##REF##3588061##2##].</p>", "<p>Due to its rare occurrence, achalasia is not commonly thought of in evaluating children with chronic cough and diagnosis can be consequently delayed. We report two cases of achalasia in children presenting primarily with chronic cough.</p>" ]

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[ "<title>Discussion</title>", "<p>Achalasia is the most commonly recognized esophageal motor disorder, first described 300 years ago by Sir Thomas Willis[##REF##11319058##4##,##REF##11419820##5##]. It is an idiopathic esophageal motility disorder, characterized by absence of normal peristalsis and failure of relaxation of lower esophageal sphincter. Achalasia occurs in the general population with a prevalence of eight per 100,000. It occurs mainly in adulthood, with less than 5% of cases found before adolescence[##UREF##0##1##]. It has been associated with other diseases such as Parkinson's disease, progressive cerebellar ataxia, familial glucocorticoid deficiency and Down syndrome[##REF##1778580##6##,##REF##7807329##7##]. Childhood achalasia is more common in boys[##REF##6728534##8##]. Few cases have been reported in infants [##REF##12576387##9##]. Familial forms are rare.</p>", "<p>The most frequent symptoms of achalasia are dysphagia, chest pain, regurgitation of food, and weight loss. Secondary pulmonary disease can occur due to regurgitation and aspiration of retained esophageal contents. This can cause symptoms of chronic cough, especially nocturnal cough, choking, recurrent pulmonary infections, pneumonia, wheezing, atelectasis and rarely pulmonary empyema [##REF##10772286##10##]. Some patients may develop hoarseness of the voice caused by direct pressure of distended esophagus on the recurrent laryngeal nerve [##REF##2771470##11##].</p>", "<p>Tracheal obstruction due to compression from dilated esophagus may occur in achalasia and can be the only presentation [##REF##3979480##12##]. This can be a serious and potentially life threatening complication of achalasia [##REF##3183882##13##,##REF##16691299##14##].</p>", "<p>Diagnosis of achalasia is suspected by the presence of dilated esophagus with tapering of distal esophagus on contrast esophagography (bird peak appearance). Esophagography, however, suffers from low sensitivity as a diagnostic test [##REF##2026805##15##]. CT scan of chest can also detect dilated esophagus, esophageal wall thickening, and stagnant food [##REF##9128311##16##]. CT scan is particularity helpful in detecting associated comorbidities such as malignancies and lung infiltrates [##REF##18196338##17##]. The diagnostic value of chest CT for achalasia compared to manometry has not been systematically studied. Pressure manometry detects motility dysfunction of the esophagus and failure of relaxation of the distal esophageal sphincter and is considered the golden standard for diagnosis of achalsia. If biopsy of distal esophagus is done, lack of myenteric plexus enervation can be demonstrated.</p>", "<p>In this report both cases presented with chronic nocturnal cough as the main presenting symptoms of achalasia. Other symptoms such as vomiting of undigested or semi digested food was present but were not enough red-herring to raise suspicion for diagnosis. Diagnosis of achalasia was finally reached after prolonged history of symptoms and after several non-diagnostic evaluations and several empirical therapies. Interestingly, diagnosis in both cases was made by CT scan finding of dilated esophagus and then confirmed by esophagography showing the dilated, tapering and dysfunctional esophagus. Even though, an esophagogram was done earlier in the second case, the diagnosis of achalasia was not made on that study. Meanwhile, patient continued to have cough and recurrent aspiration pneumonia. The severely dilated esophagus was seen years later on the CT scan and became more obvious in the second esophagogram.</p>", "<p>The second case had more severe complications from aspiration than the first case despite similar age of presentation. This could be due to poor airway clearance and the non-specific immune compromise associated with trisomy 21. The presence of esinophilia in the brochoalveolar lavage could not be clearly explained. It could possibly reflect an associated atopic airway inflammation or asthma.</p>", "<p>The presence of trachea compression on the CT scan in the first case suggests that tracheal compression was the mechanism of chronic cough. On the other hand, the presence of extensive pulmonary infiltrates on the chest CT scan and the high lipid laden macrophage index in the BAL fluid suggests that chronic aspiration was the mechanism of chronic cough in the second case [[##REF##14760168##18##,##REF##12576387##19##],20].</p>", "<p>In conclusion, both cases clearly demonstrate that achalasia could present primarily as chronic cough due to tracheal compression from dilated esophagus and/or chronic aspiration from regurgitated food. They also demonstrate that failure to entertain the likelihood of achalasia as a cause of chronic cough could result in late diagnoses and unwarranted morbidity.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Achalasia is a rare motility disorder of the esophagus which results from lack of enervation of the lower esophageal sphincter muscles and leads to dilatation of proximal esophagus. Patients with achalasia presents typically with dysphagia, vomiting of undigested food and failure to thrive. Cough can be present in achalasia patients due to aspiration of food or due to airway compression by the dilated esophagus. We report two cases of achalasia presenting primarily with prolonged cough. Diagnosis of achalasia in both cases was delayed due to this atypical presentation. This highlights the importance of recognizing achalasia as a potential cause of chronic cough in order to avoid delayed diagnosis and mismanagement.</p>" ]

[ "<title>Case 1</title>", "<p>A 9-your old girl presented for evaluation of 18 month history of nocturnal cough and post-tussive emesis. Cough occurred mainly at nighttime, occasionally triggered by exercise and was almost always followed with non-bilious vomiting of semi-digested food. Several courses of antibiotics had been given with no improvement in symptoms. Codeine containing cough suppressants were only temporarily effective. There was no response to albuterol inhaler, oral antihistamines and nasal steroids. Besides cough and post-tussive emesis, patient's parents also described less bothersome symptoms of nausea, gagging and epigastric pain. Past medical history was remarkable for being diagnosed with pneumonia a year ago and with bronchiolitis in infancy.</p>", "<p>On examination, she was above the 25^thpercentile for weight and above the 75^thpercentile for height. Vital signs were normal. Chest exam showed no signs of respiratory distress and was clear to auscultation. Initial evaluation showed normal chest x-ray, normal lung spirometry, normal exercise challenge, and negative skin testing to common inhaled allergens.</p>", "<p>Combined endoscopy and bronchoscopy were done under conscious sedation. Endoscopy identified no abnormality of the esophagus or stomach. Bronchoscopy, on the other hand, showed oval shaped trachea at its mid portion about 2.5 cm above the carina. The anterior and posterior walls of the trachea approach each other, especially during vigorous coughing, and came to complete contact on the right side creating a teardrop shaped lumen. No abnormalities of the bronchi were observed. Broncoalveolar lavage (BAL) fluid cell count contained 8% lymphocytes, 7% neutrophils, 10% eosinophils and 70% macrophages. BAL culture grew only mixed flora.</p>", "<p>Because of the mid tracheal collapse observed during bronchoscopy, a cine-CT with contrast was done to rule out vascular ring with compression of the trachea. The CT showed no abnormal vasculature but did show a large dilated esophagus with air-fluid level from stagnant food material (Figure ##FIG##0##1##). The trachea was compressed by the dilated esophagus and deviated towards the right. A Barium swallow study done later confirmed the diagnosis of achalasia and demonstrated the presence of megaesophagus with tapering and marked narrowing at the gastroesophageal junction causing functional obstruction with significant delay of contrast passage into the stomach (figure ##FIG##1##2##). There were no primary peristalsis throughout most of the esophagus and only non-peristaltic contractions were seen. No aspiration was observed. Patient underwent corrective surgical procedure after which the symptoms of chronic cough disappeared.</p>", "<title>Case 2</title>", "<p>A 10-year old African-American female with Down syndrome was evaluated by our pulmonary service for history of chronic daily cough and recurrent pneumonias for eight and a half years duration. Cough was worse at night, in supine position and during exertion. Cough also worsened during viral respiratory tract infections. There was history of frequent vomiting of undigested food but not necessarily associated with the cough.</p>", "<p>Patient was diagnosed with asthma exacerbations and pneumonia and treated as such several times in her lifetime. She had history of transient clinical improvement with antibiotics, bronchodilators and oral corticosteroids. Daily inhaled corticosteroids failed to completely control cough. Past medical history was significant for small ventricular septal defect and chronic constipation.</p>", "<p>On examination, she was between 75^thand 90^thpercentile for weight, and between 10^thand 25^thpercentile for height. Chest examination was unremarkable. Chest roentgenograms showed predominantly patchy peribronchial air space consolidation with more involvement of the right middle lobe. A Barium swallow study was first done at 5 years of age. There was no frank aspiration or laryngeal penetration and the esophagogram revealed normal anatomy of the esophagus with mildly delayed hypopharyngeal contraction but no contrast retention.</p>", "<p>Flexible bronchoscopy showed normal airway anatomy. The BAL fluid contained 16% neutrophils, 35% lymphocytes, 35% macrophages with 14% percent epithelial cells. Cultures grew only mixed flora. Lipid laden macrophages were present with Colombo index of 110 which is consistent with aspiration[##REF##1500657##3##].</p>", "<p>CT scan of the chest showed diffuse lung infiltrates that seemed worse on right middle lobe and left lower lobe. The esophagus was enlarged along its entire length but with no obvious tracheal compression (figure ##FIG##2##3##). In view of the CT scan findings, a repeat Barium swallow study was done which showed severe esophageal dysfunction with multiple waves of tertiary contractions throughout a markedly dilated thoracic esophagus. the distal esophagus appeared tapered caudally with severe narrowing at the gartroesophageal junction. Small food particles with air bubbles were seen within the mid esophagus. Only small amount of contrast passed to the stomach (figure ##FIG##3##4##).</p>", "<title>Consent </title>", "<p>The patients are lost to our follow-up, so obtaining consent is not possible. Verbal consent was obtained by the treating physicians and the coauthors (Dr. Mehdi and Dr. Weinberger)</p>", "<title>Authors' contributions</title>", "<p>All authors conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>CT scan of chest showing dilatation of esophagus with air-fluid level.</bold> Dilated esophagus is compressing the trachea anteriorly.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Esophagogram showing severe dilatation of esophagus with smooth tapering at the gastroesophageal junction.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>CT scan of chest showing bilateral lung opacification with septal thickening and esophageal dilatation.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Esophagogram showing diffuse dilatation of esophagus with tapering at gastroesophageal junction.</bold> Esophagus appears filled with food particles.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1745-9974-4-6-1\"/>", "<graphic xlink:href=\"1745-9974-4-6-2\"/>", "<graphic xlink:href=\"1745-9974-4-6-3\"/>", "<graphic xlink:href=\"1745-9974-4-6-4\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Recent position statements have re-affirmed the benefits of an active lifestyle [##REF##17671237##1##,##REF##17671236##2##]. The current physical activity recommendation for adults, aged between 18–65 years, to promote and maintain health is to accumulate at least 30 minutes of moderately intense physical activity on at least five days of the week. Promoting accumulative, lifestyle physical activity is an ideal approach to combat the high levels of inactivity evident in global populations [##UREF##0##3##,##REF##15888228##4##]. Brisk walking has been suggested as the mode of physical activity most likely to increase physical activity at a population level [##REF##8799589##5##] and is the most commonly reported mode of physical activity amongst adults in many populations [##UREF##0##3##,##REF##12165679##6##]. It is available to almost all individuals with little risk of injury, is a no cost activity and it can be incorporated into peoples' daily routines [##REF##9181668##7##]. Researchers have identified that self determined brisk walking, even in short bouts of 10 minutes, for 30 minutes a day (including simple everyday walking activities such as walking a dog) produce moderate physical activity at the intensity required to achieve health benefits [##REF##10993420##8##,##REF##12453718##9##].</p>", "<p>Walking interventions can be effective in reducing body weight, body mass index (BMI), waist and hip circumference, body fat, blood pressure and the cholesterol:high-density lipoprotein (HDL) ratio [##REF##11493045##10##, ####REF##14507493##11##, ##REF##14625129##12##, ##REF##15066369##13##, ##REF##17319328##14##, ##REF##17275896##15##, ##REF##17699531##16####17699531##16##] and may be effective in improving mood, affect [##REF##17319328##14##,##REF##10863677##17##,##REF##12218740##18##] and quality of life [##REF##15576257##19##]. Conversely, some studies have demonstrated that a walking intervention is not sufficient to affect any of these health-related outcomes [##REF##14521248##20##, ####REF##15136288##21##, ##REF##14569279##22##, ##REF##17156836##23##, ##REF##8843042##24####8843042##24##]. The reasons for such equivocal results are unclear, therefore determining the potential health benefits that can be achieved through walking is crucial to the public health message.</p>", "<p>Whilst several meta-analytical and systematic reviews exist that examine how best to promote physical activity [##UREF##1##25##,##REF##11985936##26##] there is comparatively limited evidence on the most effective methods to specifically promote walking. A recent systematic review from Ogilvie and colleagues (2007) examined the effectiveness of interventions aimed at increasing walking at both an individual and population level. The review concluded that the strongest evidence exists for tailored interventions that are targeted at individuals most motivated to change. The authors suggested that future studies should also attempt to examine whether walking interventions \"<italic>are sufficiently frequent, intense, or sustained to produce measurable outcomes in anthropometric, physiological, biochemical or clinical outcomes</italic>\" (Ogilvie et al., 2007 p.1207).</p>", "<p>One category of intervention, discussed by Ogilvie and colleagues, was the use of pedometers as an integral component of the intervention. A substantial body of research exists that supports the use of pedometers to measure physical activity [##REF##12238942##27##,##REF##15107007##28##]. A recent systematic review examined the association between pedometer use, physical activity levels and a variety of health related outcomes [##REF##18029834##29##]. The authors concluded that pedometer use was significantly associated with increased physical activity levels and reductions in BMI and systolic blood pressure. In 2006 the National Institute for Health and Clinical Excellence (NICE) in the United Kingdom produced a review of pedometer-based intervention studies between 1990 and 2005 [##UREF##2##30##]. Due to stringent inclusion criteria, conclusions from this review were drawn from only four studies. Both reviews provide support for the suggestion that pedometers may be useful motivational tools for increasing walking. However, there are several limitations when considering the volume of published studies in this area highlighted by these reviews. Studies were predominantly of short duration (&lt; 12 weeks) and based in the United States of America (USA) with small samples consisting mostly of clinical sub-populations. There is limited evidence regarding their effectiveness in non-clinical samples or in countries other than the USA. Additionally, few studies reported more than one outcome variable of interest. There is a need for cross-cultural, sufficiently powered randomized controlled trials to further examine the effectiveness of pedometers in a community setting.</p>", "<p>Evidence from two of the studies included in the NICE review suggests that a support structure, that addresses social and cognitive factors, is required for a pedometer-based intervention to be effective [##REF##14569279##22##,##REF##12588583##31##]. A physical activity consultation, using a theoretically grounded framework, constitutes one method of addressing these factors that has been demonstrated to effectively promote physical activity [##REF##11985936##26##,##REF##12663595##32##]. Researchers have suggested that pedometers may provide an important point of discussion for in-depth physical activity consultations [##REF##16148243##33##] yet this is an area that has not been particularly well addressed by pedometer-based intervention studies.</p>", "<p>The Walking for Well-being in the West (WWW) study is a multi-dimensional community-based randomized controlled trial which aims to promote and maintain increased walking behavior through the use of physical activity consultations and a pedometer-based walking program. The purpose of this article is to investigate the short term effects of a pedometer based intervention, in conjunction with a physical activity consultation, on walking behavior and health related outcomes in individuals not meeting current physical activity guidelines. Full details of the study design and rationale are reported elsewhere [##REF##18655723##34##] Details of the subsequent stages of the WWW intervention study can be found on the Scottish Physical Activity Research Collaboration website <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.sparcoll.org.uk\"/>.</p>" ]

[ "<title>Methods</title>", "<title>Recruitment</title>", "<p>The WWW intervention was set in the surrounding community of a West of Scotland university. Recruitment was targeted specifically at individuals in the lowest socio-economic groups. Recruitment was targeted at data zones within 1.5 km of the university campus that were ranked within the top 15% of the Scottish Index of Multiple Deprivation (SIMD) (i.e. the most deprived zones). The SIMD is the official measure of relative area based deprivation in Scotland and is based on 37 deprivation indicators across 7 domains: current income, employment, housing, health, education, skills and training, and geographical access to services and telecommunications. These measures are used to split the country into data zones of between 500 and 1000 people, which are then ranked from the most deprived (1) to least deprived (6505) on the overall SIMD index. The sampling frame of 1.5 km was utilised as it was estimated that this would provide a sufficient number of participants who were within a suitable walking distance from the university campus for assessments. Recruitment in the top 15% of the SIMD index produced few responses and so recruitment was extended to include all households within the specified study area regardless of socio-economic status. Participants were recruited between August and December of 2006 using mail drops, adverts in a local newspaper, posters (placed in physicians' surgeries and shops within the study area) and community stalls.</p>", "<title>Participants</title>", "<p>Individuals interested in participating in the study contacted the research team via email, telephone or postal method and in turn were provided with further study information through the individual's preferred mode of contact. Upon satisfactory inspection of this information individuals attended a screening meeting at the research centre to determine suitability for participation. Inclusion criteria were: independently ambulatory, English speaking and between the ages of 18–65 years. Only individuals who were self-classified as not meeting current physical activity recommendations, by means of an adapted stage of exercise behavior change model [##UREF##3##35##], were invited to participate. This method of screening physical activity behavior was chosen due to the uncertainty of how to determine meeting current recommendations based on the main outcome measure of pedometer step-counts. Classification by stage of change has been shown to be associated with several positive health habits such as fewer health related costs and physical activity stage of change was found to be behaviorally valid as evidenced by self-reported physical activity, self-reported exercise, self-reported sedentary behaviors, pedometers and physical functioning [##REF##18248105##36##]. Participants were also required to complete the Physical Activity Readiness Questionnaire to assess their suitability for an exercise program [##REF##1330274##37##]. A positive response in this questionnaire required a letter of approval from the participant's physician in order to take part. Participants not meeting any aspect of these criteria were excluded from participation and provided with written information on the benefits of physical activity. Written informed consent was obtained from all participants for their involvement in the physical activity intervention. Participants provided additional consent for the optional health related outcome measures. Upon completion of this initial screening meeting participants completed baseline outcome measures and were subsequently randomized. All research procedures were approved by the relevant university research ethics committee. Data for this stage of the study were collected between August 2006 and December 2006.</p>", "<title>Randomization Procedure</title>", "<p>The WWW study is a two group (intervention and control) by six time points (baseline, 12, 24, 36, 48 and 60 week) randomized controlled trial. The data reported in this paper concerns the initial intervention stage from baseline to 12 weeks. Randomization was carried out via an independent interactive voice response system (IVRS) which concealed all details of the randomization method from the end users. The IVRS is an interactive telephone based system which allows an authenticated caller (researchers) to randomize a subject into the study. Randomization was stratified by gender (male/female) and baseline step counts (≤ 7,999/≥ 8000) creating a total of four distinct stratification groups. Researchers who conducted the physical activity consultations were not blinded to group assignment in order to implement the physical activity intervention. Additional researchers who performed physiological measurements were blinded to group assignment. The value of 8,000 steps was used as a stratification variable to account for individuals with a high baseline step-count. This value has previously been used as a baseline descriptor for sedentarism [##REF##16177618##38##]. Researchers have also suggested that individuals are more likely to attain public health guidelines by walking at least 8000 steps/day [##REF##12471314##39##]. Positive effects on conventional metabolic parameters, such as blood pressure, have been found when steps are above 8000 steps/day [##REF##16908952##40##].</p>", "<title>Outcome measures</title>", "<title>Physical Activity</title>", "<p>Daily physical activity was measured using two methods. The primary outcome measure was steps/day measured by the Omron HJ-109E Step-O-Meter (Omron Healthcare UK Ltd). To the authors' knowledge this model of pedometer has not been utilized in any previous intervention studies. However, Ryan and colleagues have demonstrated good inter-reliability between units and acceptable accuracy (less than 5% error) at speeds above 1.56 m/s for this model [##REF##16825270##41##]. The Omron HJ-109E has several features beneficial to an intervention of this nature, including a cover to prevent accidental resetting and a 7-day memory which negates the need for participants to record their own step-counts. Daily physical activity was also measured using a 7-day recall of physical activity in the form of the long (self-reported) version of the International Physical Activity Questionnaire (IPAQ) [##REF##12900694##42##]. This subjective measure of physical activity was used to examine changes in modes of physical activity that would not be measured by the pedometer such as swimming or other forms of structured sport or exercise. The IPAQ long version is a 31-item instrument that collects information about moderate and vigorous physical activity across four domains: work-related, transportation, housework/gardening, and leisure time physical activity. This detail on specific physical activity domains therefore allows researchers to identify where changes in physical activity may have occurred. Walking time is also included for the work, transport and leisure domains. Two additional questions measure time spent sitting which can be used as an indication of sedentary time.</p>", "<title>Health Related Outcomes</title>", "<p>Affect (an individuals feelings and emotions) was assessed using the Positive and Negative Affect Schedule (PANAS) [##REF##3397865##43##] which has been demonstrated to be a valid and reliable measure of the constructs in a non-clinical sample of U.K. adults [##REF##15333231##44##]. The PANAS is a self report measure consisting of 10 words relating to positive feelings and emotions, such as 'interested' and 'alert', and 10 words that relate to negative feelings such as 'distressed' and 'upset'. Participants are asked to rate each item according to what extent they have felt that way in the previous few weeks using a Likert scale from (1) very slightly or not at all to (5) extremely. Items were summed to give mean scores (out of 50) for positive affect and negative affect.</p>", "<p>Quality of life was measured using the Euroqol EQ-5D instrument [##REF##10109801##45##]. The EQ-5D is a self-report questionnaire comprised of the EQ-5D descriptive system and the EQ VAS. The EQ-5D descriptive system is a five item questionnaire that assesses participants' current health state over five dimensions: mobility; self-care; usual activities; pain/discomfort; and anxiety/depression. Each item is comprised of three levels (no problems, some/moderate problems, extreme problems). A unique health state can be obtained by combining the participants' levels from the five dimensions. The score can then be converted into a weighted health index using \"value sets\" gained from population data. The UK value set, developed by Dolan and colleagues, was used in this study [##UREF##4##46##]. The EQ VAS records an individual's self-rated health status on a vertical graduated (0 to 100) visual analogue scale.</p>", "<p>Body mass was measured on a precision balance (Sartorius, AG Gottingen, accuracy ± 0.001 kg). From these measurements body mass index (BMI) was calculated as height(m)/weight(kg)²; height was measured using a standard laboratory stadometer. Waist-to-hip ratio was calculated from measurements made using a SECA 200 (SECA, Birmingham, UK) measuring tape. Percentage body fat was estimated from skinfold thickness (Harpenden, British Indicators, West Sussex, UK) measurements taken at four sites (biceps, triceps, subscapularis and suprailiac) according to the methods of Durnin and Womersley [##REF##4760798##47##].</p>", "<p>Blood pressure was measured using an automated blood pressure monitor (Omron HEM-907, Bannockburn, IL). On each visit blood pressure measurements were performed three times with a rest period of one minute between measurements. Three measurements of resting heart rate were also recorded simultaneously by the blood pressure monitor. The average of these measurements is reported in these results.</p>", "<p>Fasting blood samples were taken from an intravenous butterfly cannula inserted into an antecubital vein. Samples were drawn into K⁺EDTA vacutainers (BD Biosciences, Oxford, UK) which were centrifuged and the plasma removed and stored at -80°C for subsequent analysis. Total cholesterol and high-density lipoprotein (HDL) cholesterol (direct method), from the plasma, were measured in duplicate on a fully automated spectrophotometric analyzer (Pentra 400, Horiba-ABX, Montpellier, France) using commercially available kits (Horiba-ABX, Montpellier, France). The co-efficient of variation for these assays was as follows: total cholesterol: 1.4%, HDL-cholesterol: 1.6%.</p>", "<title>Procedures</title>", "<p>All participants completed a baseline week wearing a pedometer, sealed with tape, for seven days at all times (except when showering, sleeping or taking part in structured sport or exercise) with instructions not to alter their daily routine. The WWW study was designed to impact walking behavior therefore only ambulatory activity was recorded. Irregular bouts of structured sport or exercise that could significantly affect an individual's mean step-count were not recorded. Each pedometer was individually calibrated consistent with manufacturers guidelines to within 5% of actual steps walked in a 100-step test. Participants were required to provide at least five days of step counts including at least one weekend day to gain an accurate reflection of physical activity levels. Pre-intervention measures of all health related outcomes were obtained and participants completed the IPAQ before being randomly assigned to either intervention or control group.</p>", "<p>Participants assigned to the intervention group received a physical activity consultation and then followed a 12-week pedometer-based walking program. The sessions were based on a theoretical framework, recommended to ensure quality [##REF##15530754##48##]. The Transtheoretical Model of exercise behavior change (TTM) [##REF##7837962##49##] was chosen for this purpose as there are published guidelines for health professionals to conduct consultations using this model as a theoretical framework [##REF##17650156##50##,##UREF##5##51##]. The TTM is a common theoretical framework for physical activity consultations [##REF##17625711##52##] and has been used successfully in intervention studies designed to increase physical activity in a Scottish population [##REF##12663595##32##,##REF##12166883##53##,##REF##15138687##54##].</p>", "<p>The consultations were semi-structured following established guidelines [##REF##17650156##50##,##UREF##5##51##]. A guiding style was used with participants making decisions about how to change their walking behavior [##REF##16239696##55##]. The consultations were focused on the uptake of physical activity, in this context promoting increases in walking. Strategies used included enhancing motivation, overcoming barriers and developing appropriate walking plans which were tailored to the individual as recommended by Ogilvie and colleagues (2007). The sessions also included discussion of the three mediators of the TTM that have been shown to be important to behavior change [##REF##7837962##49##]. These are self-efficacy (confidence in ability to change), decisional balance (pros and cons of change) and processes of change (strategies and techniques used to change, e.g., social support). Although the sessions were flexible and individualized, the TTM was used to create a standard protocol to follow during the sessions. Table ##TAB##0##1## shows the steps followed.</p>", "<p>The walking program was based on a 12-week time frame: the first six weeks consisted of graduated bi-monthly goals with an aim for the increased walking behavior to be maintained for the remaining six weeks. The overall goal of the walking program was for participants to increase their mean daily step-count by 3,000 accumulated steps above their baseline value on five days of the week. This value is based on the assumption that moderate brisk walking produces 100 steps a minute (1,000 steps per 10 minutes) [##REF##16485518##56##] therefore 3,000 steps would equate to approximately 30 minutes of moderate physical activity, in line with current physical activity recommendations [##UREF##6##57##]. This program has previously been successfully used with similar UK samples over a shorter time-frame [##UREF##7##58##]. Intervention group participants retained their pedometers, open for feedback, for the duration of the intervention period and were shown how to use this to monitor their daily step-counts. The full list of goals is displayed in Table ##TAB##1##2##. Goals were retained for two consecutive weeks to enable participants to reinforce their increased levels of walking, or to try other strategies to successfully accumulate the additional steps. Participants were advised on the nature of the intensity and duration of the desired increases in walking. Participants were familiarized with the Borg 6–20 scale [##REF##10812930##59##] and advised that additional walking should be of a brisk nature that would leave them slightly breathless and hot but still able to talk (indicated as between 12–14 on this scale). Bouts of at least 10 minutes in duration were advised for additional walking although the accumulation of walking during everyday tasks wherever possible was also advocated.</p>", "<p>Participants assigned to the control group were asked to maintain their normal walking levels between baseline and week 12. At the end of week 11 these participants collected an individually calibrated pedometer from the research centre and wore this sealed during week 12 to gain a record of their step-counts. At the end of week 12 researchers met with all participants to record step-counts at which time participants completed the IPAQ and post-intervention health measures were taken.</p>", "<title>Statistical Power and Analyses</title>", "<p>G-Power analysis [##UREF##8##60##] set for F-test analysis of variance (ANOVA) was used to calculate sample size for between group analyses of the primary outcome measure (i.e., daily step count). Power was set at 0.8, Alpha level was set at 0.05 and effect size (Cohen's <italic>f </italic>[##UREF##9##61##]) was set at 0.4 (large) for the two group (intervention and control) design based on previous unpublished work from this research group. A minimum sample size of 52 was calculated (26 participants in each group).</p>", "<p>Data were analyzed using SPSS v.14.0 (SPSS, Inc, Chicago, IL). All results reported were analyzed by the main intervention groups: analyses by separate stratification variables (gender, baseline step-count) found no significant interaction effects between groups (males/females and ≤ 7,999/≥ 8000) therefore are not presented here. The analyses were performed on an intention to treat basis. Missing week 12 data (due to participant drop-out) were substituted with the participants' baseline value. Baseline differences between the intervention and control group were examined using independent t-tests. Steps/day and health related outcome data were analyzed using two-way mixed factorial analyses of variance (ANOVA). Missing weekday step-count data were replaced by inputting the mean of the remaining weekdays and missing weekend step-count data were replaced by inputting the alternate weekend day [##UREF##10##62##]. Exploratory analysis revealed that data from several sub-sections of the IPAQ were non-normally distributed. Non-parametric analyses were therefore used to analyze these data. Mann Whitney U tests were used to examine between group differences and Wilcoxon's signed-rank tests were used to examine within group differences over time. Due to the number of variables available from the IPAQ only statistically significant results are presented. Statistical significance was defined as <italic>p </italic>&lt; 0.05 for all tests with data presented as mean (SD) unless otherwise stated.</p>" ]

[ "<title>Results</title>", "<title>Participants</title>", "<p>From 169 initial enquiries to the study, 91 individuals met the inclusion criteria and provided informed consent at an initial meeting. Seventy-nine participants (63 females, 16 males, age = 49.2 ± 8.9) provided baseline measurements of pedometer step counts, IPAQ and measures of affect and quality of life (specific numbers for participants who consented to other health related outcome measures can be found in Table ##TAB##3##4##). The intervention group (<italic>n </italic>= 39) consisted of 31 females and eight males and the control group (<italic>n </italic>= 40) consisted of 32 females and eight males. Overall, 55 of 79 participants (70%) were below the randomization stratification variable of 8,000 steps at baseline: this consisted of 28 of 39 (72%) of participants in the intervention group and 27 of 40 (68%) of participants in the control group. Figure ##FIG##0##1## displays the flow of participants through the study. As shown in Figure ##FIG##0##1## there were 15 participants who withdrew from the study between baseline and week 12. The following results are presented on an intention to treat basis where all participants were considered. Table ##TAB##2##3## displays the proportion of participants in each level of the five dimensions in the EQ-5D descriptive system. Table ##TAB##3##4## displays descriptive statistics (mean [<italic>M</italic>] and standard deviation [<italic>SD</italic>]) for age, pedometer steps and all health related outcomes, at baseline and week 12. Table ##TAB##4##5## displays descriptive statistics (median [<italic>Mdn</italic>] and range [<italic>r</italic>] for all IPAQ variables at baseline and week 12.</p>", "<title>Physical Activity</title>", "<title>Step counts</title>", "<p>Figure ##FIG##1##2## displays the mean steps/day for both groups at both time-points. A significant interaction was identified between group (intervention, control) and time (baseline, week 12) in terms of the recorded step-counts, (<italic>F</italic>_(1,77)= 25.18, <italic>p </italic>&lt; .001, partial η²0.25). A paired t-test found a significant increase in steps/day for the intervention group between baseline (<italic>M </italic>= 6802, <italic>SD </italic>= 3212) and week 12 (<italic>M </italic>= 9977, <italic>SD </italic>= 4669, <italic>t</italic>(38) = -6.06, <italic>p </italic>&lt; .001, <italic>d </italic>= 0.79, confidence intervals [<italic>CI</italic>] 2,115 – 4236). No significant difference was observed in the control group between baseline (<italic>M </italic>= 6924, <italic>SD </italic>= 3201) and week 12 (<italic>M </italic>= 7078, <italic>SD </italic>2911, <italic>t</italic>(39) = -0.50, <italic>p </italic>= 0.618, <italic>CI </italic>-463 – 770). The mean difference in change between the two groups was 3,022 steps/day and was statistically significant (<italic>t</italic>(77) = 5.02, <italic>p </italic>&lt; .001, <italic>d </italic>= 1.96). Chi-square analysis determined that a significantly greater percentage (χ²= 24.88, <italic>p </italic>&lt; .001) of participants in the intervention group (25/39, 64%) achieved an increase of 15,000 steps per week, equivalent to physical activity guidelines of the accumulation of 150 minutes of moderate physical activity, compared with the control group (4/40, 10%).</p>", "<title>7-day recall of physical activity (IPAQ)</title>", "<p>Wilcoxon's signed-rank tests revealed that at week 12 the intervention group recalled a significant increase in the number of leisure minutes walked (<italic>Z </italic>= 2.32, <italic>p </italic>= 0.02, <italic>r </italic>= 0.37, median [<italic>Mdn</italic>] difference = 100 minutes per week) and a significant decrease in weekday sitting (<italic>Z </italic>= 2.94, <italic>p </italic>= 0.003, <italic>r </italic>= 0.47, <italic>Mdn </italic>difference = 1200 minutes per week), weekend sitting (<italic>Z </italic>= 3.41, <italic>p </italic>= 0.001, <italic>r </italic>= 0.55, <italic>Mdn </italic>difference 360 minutes per week) and total sitting (<italic>Z </italic>= 3.38, <italic>p </italic>= 0.001, <italic>r </italic>= 0.54, <italic>Mdn </italic>difference = 1680 minutes per week) from baseline. At week 12 the control group recalled a significantly greater number of vigorous leisure minutes of physical activity (Z = 2.02, p = 0.043, <italic>r </italic>= 0.32, <italic>Mdn </italic>difference = 0 minutes) than at baseline. This result is due to five individuals in the control group increasing their vigorous leisure minutes recalled. As the majority of participants (34 of 40) report zero minutes at both time-points the median difference equals zero despite the group reporting a significant increase.</p>", "<p>Mann Whitney U tests revealed that at week 12 the intervention group recalled a significantly greater number of leisure minutes walked (<italic>U </italic>= 513.00, <italic>p </italic>= 0.008, <italic>r </italic>= 0.30, <italic>Mdn </italic>difference 83.8 minutes), number of occupational minutes walked (<italic>U </italic>= 602.00, <italic>p </italic>= 0.045, <italic>r </italic>= 0.23, <italic>Mdn </italic>difference 0 minutes) and total number of minutes walked (<italic>U </italic>= 560.50, <italic>p </italic>= 0.03, <italic>r </italic>= 0.24, <italic>Mdn </italic>difference = 57.5 minutes) than the control group. The intervention group also recalled significantly less total time spent sitting (<italic>U </italic>= 546.00, <italic>p </italic>= 0.022, <italic>r </italic>= 0.26, <italic>Mdn </italic>difference = -420 minutes) due to significantly less time spent sitting at the weekend (<italic>U </italic>= 474.50, <italic>p </italic>= 0.003, <italic>r </italic>= 0.34, <italic>Mdn </italic>difference = -240 minutes).</p>", "<title>Health related outcomes</title>", "<title>Affect (PANAS)</title>", "<p>A significant interaction was identified between group (intervention, control) and time (baseline, week 12) in terms of the positive affect scores, (<italic>F</italic>_(1,77)= 4.26, <italic>p </italic>= .042, partial η²0.05). A paired t-test found a significant increase in positive affect for the intervention group between baseline (<italic>M </italic>= 31.2, <italic>SD </italic>= 6.7) and week 12 (<italic>M </italic>= 33.5, <italic>SD </italic>= 7.4, <italic>t</italic>(38) = 2.29, <italic>p </italic>= .027, <italic>d </italic>= <italic>0.33</italic>, <italic>CI </italic>.27 – 4.39). No significant difference was observed in the control group between baseline (<italic>M </italic>= 31.7, <italic>SD </italic>= 6.9) and week 12 (<italic>M </italic>= 31.3, <italic>SD </italic>7.6, <italic>t</italic>(39) = -0.524, <italic>p </italic>= 0.604, -2.31 – 1.36). There was no significant interaction or main effect found for the negative affect scores or for any of the other health related outcomes measured in the present study (Table ##TAB##3##4##).</p>" ]

[ "<title>Discussion</title>", "<p>This study is one of the first adequately powered, UK based randomized controlled trials to examine the impact of a pedometer-based walking intervention on step-counts in a community setting. The major finding of this study was that a graduated pedometer-based walking program, in conjunction with a physical activity consultation increased walking in low-active adults over a period of 12 weeks. The control group, included to account for the intrinsic motivation of volunteer participants [##REF##17303369##63##], displayed no significant change in steps/day over time. The conservative intention to treat analysis (baseline carried forward for missing values) produced a mean change in the intervention group of 3,175 steps/day, an increase of 47% above baseline values, a favorable increase compared with other pedometer-based randomized controlled trials [##REF##14569279##22##,##REF##12588583##31##,##REF##16148243##33##]. In their systematic review, Bravata and colleagues (2007) reported that pedometer users increase physical activity by an average of 26.9% over baseline values.</p>", "<p>The overall goal for participants was to increase their baseline step-counts by 3,000 steps/day on five days of the week (i.e., equivalent to current physical activity recommendations); equating to an overall weekly increase of 15,000 steps/week. The intervention group displayed a mean increase in weekly step counts of 22,225 steps/week thus exceeding the recommended goal. At an individual level 64% of participants in the intervention group achieved the goal of 15,000 steps/week. Participants in the intervention group progressed from being classified as \"low active\" (5,000–7,499 steps/day) to within 23 steps of being classed as \"active\" (≥ 10,000) according to suggested public health ranges for pedometer counts [##REF##14715035##64##]. These results suggest that the intervention is a successful method of promoting walking and allowing individuals to meet suggested public health recommendations.</p>", "<p>One issue of the study, also discussed in the Bravata <italic>et al</italic>. systematic review, is that it is not possible to disentangle the respective contributions of the physical activity consultation from the benefits of the pedometer-based goals of the walking program. Physical activity consultations have been demonstrated to be effective at promoting physical activity [##REF##12663595##32##,##REF##15138687##54##], and this particular walking program has previously been shown to be effective at promoting short-term increases in walking [##UREF##7##58##]. Consistent with recommendations from Bravata and colleagues, the next stage of the WWW project involves the control group following the 12 week walking program without the additional physical activity consultation, while the intervention group will be provided with continued support in the form of a further physical activity consultation. These longer term comparative results will help to determine the most effective components of this intervention.</p>", "<p>The increase observed in the step-count data was supported by the self-reported results of the IPAQ; an increase in reported minutes of leisure time walking was found in the intervention group (median increase of 100 minutes per/week). While it is not directly comparable, the increase of 22,225 steps/week observed in the intervention group is approximately equivalent to an additional 222 minutes of walking per week. Although we must consider possible errors in perception when recalling walking [##REF##10795795##65##] this suggests that the primary means by which participants increased their walking was during their leisure time, consistent with previous research [##REF##15539058##66##]. The discrepancy between the objective and subjective measures of activity could be partially explained by the pedometer measuring all activity and the IPAQ only measuring activity in bouts of 10 minutes and greater. Alternatively, additional increases in step-counts could be attributed to an accumulation of walking in other domains and other non-significant increases in ambulatory activity. This may be demonstrated in the significant difference in occupational and total minutes of walking recalled between the intervention and control groups at week 12.</p>", "<p>The IPAQ also revealed that the intervention group reduced time spent sitting during both weekdays and weekend days. Researchers have suggested that sedentary behavior, such as time spent sitting, is positively associated with coronary heart disease risk factors, obesity and development of the metabolic syndrome [##REF##15833947##67##, ####REF##12947427##68##, ##REF##12900679##69####12900679##69##]. It has been suggested that interventions should seek to both increase physical activity and to decrease sedentary behavior [##REF##16211373##70##]. In this study we did not aim to directly reduce sedentary behavior and as the IPAQ does not measure sitting time across a specific domain it is impossible to determine where the reductions in sitting time occurred. Future interventions incorporating physical activity consultations should ensure that identifying and reducing sedentary behaviors is an integral part of the consultation process and that any physical activity questionnaires used should describe sedentary behaviors to the same extent as physical activity behaviors. These results should be treated with a degree of caution given the disparity between the reduced time spent sitting as indicated by the IPAQ (4 hours of total sitting per day) and the increase in physical activity as measured by the pedometer (approximately 30 minutes of activity per day). It may be possible that non-sitting activities such as standing may attribute to a proportion of this difference however this does not provide an adequate explanation given the magnitude of this observed discrepancy. A more probable explanation is that the error and limitations associated with self-report measures of physical activity [##REF##10925819##71##] are also associated with self-report measures of sedentary behaviors. Preliminary evidence that compares activity levels as measured by a pedometer and the IPAQ would suggest that direct comparisons are unwise as evident by low correlations between the two methods [##REF##18036764##72##].</p>", "<p>Outcome measures were only assessed at baseline and week 12. Participants were asked to record their pedometer readings from intermittent sub-goals in self-recorded diaries. Completion of these was not an essential requirement of participants and as such these were often incomplete. The level of missing data in these diaries made it impractical to perform statistical analysis on a week by week basis. We were reluctant to constantly monitor participants to try and mirror a 'real-world' scenario. As a result we were unable to determine whether participants actually achieved, or exceeded, their targets in the periods between assessments. Therefore, the possibility remains that, in a worst case scenario, participants increased their physical activity levels only during week 12 in order to achieve their final target; although such a substantial increase in step-counts over a one week period would be unlikely. A previous study from our research group [##UREF##7##58##] that followed individuals throughout the intervention reported an incremental increase in step-counts on a week by week basis. While only measuring at pre and post intervention may be seen as a limitation of the current study, this approach removes the possibility of increased motivation through researcher presence and may also decrease the risk of participant drop-out due to repeated meetings. Making completion of step-count diaries a requirement of participants would have increased the level of data available for analysis. However, this substantially increases the responsibility on the participant which, over a prolonged time-period, may provide a potential source for participant drop-out. Conversely, filling in the step-count diaries on a regular basis may act as an extrinsic motivational factor; which could potentially mask the effects of the walking program or the consultation. The recent systematic review on pedometer use suggests that future trials compare pedometer use with versus without a step-count diary [##REF##18029834##29##] and the results of this study support this suggestion given the issues discussed above.</p>", "<p>In this study contact with intervention group participants was minimal and yet significant behavior change was still achieved. Following the RE-AIM framework for health behavior interventions [##REF##10474547##73##], this intervention was simple to implement, was efficacious at an individual level and has the capacity to be adopted and implemented within a variety of real-world settings.</p>", "<p>Whilst the current study was successful in increasing the daily walking of participants, there was no effect on any of the health-related outcomes measured other than a small to medium, significant increase in positive affect reported by the intervention group. There is contradicting evidence regarding the relationship between walking and affect. Some researchers have suggested that walking may not be performed at a sufficient intensity to produce corresponding positive changes in affect [##UREF##11##74##]. Conversely, the current study supports research that has demonstrated a positive benefit on affect following a walking intervention [##REF##17319328##14##,##REF##12218740##18##,##REF##10146803##75##]. Researchers have also demonstrated that short, acute bouts of walking may also improve affect [##REF##10863677##17##,##UREF##12##76##]. These findings provide support for walking as a pleasurable activity and it has been proposed that this enjoyment is linked to intrinsic motivation and subsequent adherence to physical activity [##UREF##12##76##].</p>", "<p>The lack of changes in the other health-related outcomes measured in this study may not be unexpected given the pragmatic approach of the walking intervention. The walking program was designed to increase participants' walking in graduated bi-monthly stages: participants began the program by accumulating an additional 1,500 steps on at least three days of the week for the first two weeks before progressing with the frequency of this goal and then the quantity of walking. This approach was utilized to allow participants the opportunity to follow progressive short term goals in order to reinforce successful strategies or attempt alternative strategies in order to achieve their goals. Subsequently, if this approach was followed by participants, the goal of accumulating an additional 3,000 steps at least five days of the week was only applicable for the final six weeks of the intervention. Recent meta-analyses [##REF##15066369##13##,##REF##17275896##15##], that have found decreases in body weight, BMI, percentage body fat, blood pressure and the cholesterol:HDL ratio after a walking intervention, report means and ranges of duration and frequency consistent with the 30 minutes (3000 steps), five days a week target promoted in the current study. These meta-analyses used data from studies ranging between eight and 104 weeks in length.</p>", "<p>It may be the case therefore, that a period longer than six weeks at this duration and frequency is required to allow positive physiological changes to occur. Future follow-up stages of the WWW study will attempt to evaluate this aspect. However, as previously mentioned; we are unable to conclude whether participants strictly followed the graduated approach or whether they were successful in doing so throughout the program. Indeed, previous work investigating the dose-response relationship has shown that it can take up to two years for an increase in HDL to occur as the result of exercise training [##REF##7743622##77##]. On the other hand similar changes in HDL and other anthropometric variables have occurred after 12 weeks in other investigations [##REF##17699531##16##,##REF##8494471##78##]. It is possible, therefore, that the current intervention may have resulted in positive health benefits if it had continued.</p>", "<p>Although we may not have expected physiological changes at week 12 due to the graduated walking program, we must consider alternative methodological considerations of the study that may have contributed to the lack of significant changes in health outcomes. With the exception of BMI, participants' health outcomes values were deemed to be within normal ranges at baseline. Significant, and clinically meaningful, changes will consequently be harder to achieve in this population and may indeed be unnecessary for many participants. It has been recommended that 45–60 minutes of moderate physical activity per day is required for weight maintenance [##REF##12760445##79##]. Therefore it was unlikely that these changes would have occurred following an increase of approximately 30 minutes of walking. This study also did not attempt to control for dietary factors. Previous studies have demonstrated that calorific restriction is a more effective weight loss tool than physical activity [##REF##17581621##80##]. As we did not control for or monitor diet it is possible that participants may have compensated for the increase in physical activity by increasing energy intake or by deceasing energy expenditure during other parts of the day. Such a possibility is supported by previous research showing that there is an increase in appetite after a single bout of exercise [##REF##16157416##81##] although this is not always been the case [##REF##9716432##82##]. In the current study no measure of energy intake/expenditure was made hence we are unable to determine whether an increase in energy intake, or decreasing energy expenditure in other parts of the day, has counteracted the increase in energy expenditure due to the walking.</p>", "<p>Finally, it may be that the intensity of the walking undertaken by the participants was not sufficient to stimulate health benefits. It is possible that the changes in step-count observed in our participants were caused by short (less than 10 minutes) bouts at low speeds. To date there has been little community based work where the intensity of physical activity has been closely monitored. Results from this and similar community based studies [##REF##17319328##14##,##REF##17699531##16##,##REF##17156836##23##] present equivocal and conflicting findings of producing corresponding physiological changes following successful behavior change. This illustrates that in comparison with controlled, laboratory based studies positive changes in health may be more difficult to achieve in a real world setting, where the frequency, duration and intensity of the intervention cannot be objectively measured.</p>", "<title>Study strengths and limitations</title>", "<p>Strengths of this study include using a sealed pedometer at baseline and the use of a pedometer with a 7-day memory which negates the need for participants to record their daily steps. This study is also one of the first UK based, adequately powered randomized controlled trials to examine the effectiveness of pedometers as motivational tools within a community based, non-clinical sample. The use of a multidisciplinary approach to provide measures of health related outcomes adds significantly to the study, and it is of considerable importance that all analyses were performed on an intention to treat basis. The lack of an intention to treat approach in the literature has been identified as a weakness when considering application to a population setting [##REF##17275896##15##].</p>", "<p>Although the pedometer is a useful measurement tool with regards to ambulatory physical activity, one limitation of the instrument is that the lack of any direct measure of intensity makes it difficult to draw conclusions about time spent in moderate or vigorous physical activity. Pedometers are currently being developed that address the issue of measuring only walking at a pre-determined moderate intensity (aerobic steps) although further research into the validity of these measures is required before they can be used confidently in intervention studies. The pedometer measures ambulatory activity, not strictly walking, which suggests that the increase in steps/day found between baseline and week 12 in the intervention group could be attributed to other forms of physical activity. However, participants were asked to remove the pedometer whilst engaging in structured sport or exercise, and self-report measures of physical activity do not show evidence of changes in ambulatory activity other than walking.</p>" ]

[ "<title>Conclusion</title>", "<p>In summary, this study has demonstrated that a 12-week pedometer-based walking program in combination with a physical activity consultation was an effective way to increase walking, reduce sedentary behavior and increase positive affect in a community based sample not meeting current physical activity recommendations. The intervention was relatively simple to implement and has the capacity to be reproduced in a variety of settings. The intervention was not sufficient to induce beneficial physiological changes. Future stages of this study will examine adherence to the intervention, compare the effects of the walking program with versus without the physical activity consultation and provide longitudinal data on health related outcomes.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Recent systematic reviews have suggested that pedometers may be effective motivational tools to promote walking. However, studies tend to be of a relatively short duration, with small clinical based samples. Further research is required to demonstrate their effectiveness in adequately powered, community based studies.</p>", "<title>Objective</title>", "<p>Using a randomized controlled trial design, this study assessed the impact of a 12-week graduated pedometer-based walking intervention on daily step-counts, self-reported physical activity and health outcomes in a Scottish community sample not meeting current physical activity recommendations.</p>", "<title>Method</title>", "<p>Sixty-three women and 16 men (49.2 years ± 8.8) were randomly assigned to either an intervention (physical activity consultation and 12-week pedometer-based walking program) or control (no action) group. Measures for step-counts, 7-day physical activity recall, affect, quality of life (<italic>n </italic>= 79), body mass, BMI, % body fat, waist and hip circumference (<italic>n </italic>= 76), systolic/diastolic blood pressure, total cholesterol and HDL cholesterol (<italic>n </italic>= 66) were taken at baseline and week 12. Analyses were performed on an intention to treat basis using 2-way mixed factorial analyses of variance for parametric data and Mann Whitney and Wilcoxon tests for non-parametric data.</p>", "<title>Results</title>", "<p>Significant increases were found in the intervention group for step-counts (<italic>p </italic>&lt; .001), time spent in leisure walking (<italic>p </italic>= .02) and positive affect (<italic>p </italic>= .027). Significant decreases were found in this group for time spent in weekday (<italic>p </italic>= .003), weekend (<italic>p </italic>= .001) and total sitting (<italic>p </italic>= .001) with no corresponding changes in the control group. No significant changes in any other health outcomes were found in either group. In comparison with the control group at week 12, the intervention group reported a significantly greater number of minutes spent in leisure time (p = .008), occupational (p = .045) and total walking (p = .03), and significantly fewer minutes in time spent in weekend (p = .003) and total sitting (p = .022).</p>", "<title>Conclusion</title>", "<p>A pedometer-based walking program, incorporating a physical activity consultation, is effective in promoting walking and improving positive affect over 12 weeks in community based individuals. The discussion examines possible explanations for the lack of significant changes in health outcomes. Continued follow-up of this study will examine adherence to the intervention and possible resulting effects on health outcomes.</p>" ]

[ "<title>Abbreviations</title>", "<p>NICE: National Institute for Health and Clinical Excellence; WWW: Walking for Well-being in the West; IPAQ: International Physical Activity Questionnaire; PANAS: Positive and Negative Affect Schedule; BMI: Body mass index; HDL: High-density lipoprotein; TTM: Transtheoretical Model of exercise behavior change; ANOVA: Analysis of Variance; M: Mean; SD: Standard deviation; Mdn: Median.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>GB participated in the design and coordination of the study, was responsible for data collection and statistical analysis on step-counts, IPAQ, mood and quality of life measures, performed the physical activity consultations and drafted the manuscript. SG was responsible for collection of health related outcome data, assisted with drafting the health related outcome sections of the manuscript, performed statistical analysis on the health related outcome measures and provided feedback during the manuscript preparation stage. AW participated in the design and coordination of the study, was responsible for data collection of step-counts, IPAQ, mood and quality of life measures, performed the physical activity consultations and provided feedback during the manuscript preparation stage. CF participated in the design and coordination of the study, assisted with collection of the health related outcome data and provided feedback during the manuscript preparation stage. MN participated in the design of the study, assisted with collection of the health related outcome data and provided feedback during the manuscript preparation stage. RL participated in the design of the study, statistical analysis and provided feedback during the manuscript preparation stage. NM (on behalf of SPARColl) was principal investigator, conceived the study, participated in the design of the study and provided feedback during the manuscript preparation stage. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to acknowledge the SPARColl advisory group for feedback during the study design and manuscript preparation stage. The authors would like to thank Alex McConnachie and David Rowe for assistance with statistical analysis. The authors would also like to thank Martha Paisi, Rona Sutherland and Martin Watson for their assistance in collecting the health related outcome data. We would also like to acknowledge the participants, without whom this study would not have been possible.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Flow of participants through the study.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Mean steps/day for intervention group (n = 39) and control group (n = 40) at baseline and week 12.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Key points covered during physical activity consultations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Key points covered</td></tr></thead><tbody><tr><td align=\"left\">Step 1: Physical Activity History</td><td align=\"left\">• Participants' reasons for increasing walking</td></tr><tr><td/><td align=\"left\">• Consider why walking is attractive to them</td></tr><tr><td/><td align=\"left\">• Current walking levels</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Step 2: Decisional Balance</td><td align=\"left\">• Weigh up pros and cons of increasing walking</td></tr><tr><td/><td align=\"left\">• Minimize any perceived cons</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Step 3: Barriers</td><td align=\"left\">• Consider barriers to increasing walking</td></tr><tr><td/><td align=\"left\">• Consider how to overcome these barriers</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Step 4: Goal-setting</td><td align=\"left\">• Explanation of walking program and pedometer</td></tr><tr><td/><td align=\"left\">• Informed of baseline step-counts</td></tr><tr><td/><td align=\"left\">• Discuss realistic and time-phased goals</td></tr><tr><td/><td align=\"left\">• Identify situations for increasing walking</td></tr><tr><td/><td align=\"left\">• Identify local walking routes</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Step 5: Summarize</td><td align=\"left\">• Check self-efficacy of achieving goals</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Weekly goals of intervention group participants</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Time-point</bold></td><td align=\"center\"><bold>Goal</bold></td></tr></thead><tbody><tr><td align=\"center\">Week 1</td><td align=\"left\">To walk an extra 1,500 steps (from baseline value) on at least 3 days of the week</td></tr><tr><td align=\"center\">Week 2</td><td align=\"left\">To walk an extra 1,500 steps (from baseline value) on at least 3 days of the week</td></tr><tr><td align=\"center\">Week 3</td><td align=\"left\">To walk an extra 1,500 steps (from baseline value) on at least 5 days of the week</td></tr><tr><td align=\"center\">Week 4</td><td align=\"left\">To walk an extra 1,500 steps (from baseline value) on at least 5 days of the week</td></tr><tr><td align=\"center\">Week 5</td><td align=\"left\">To walk an extra 3,000 steps (from baseline value) on at least 3 days of the week</td></tr><tr><td align=\"center\">Week 6</td><td align=\"left\">To walk an extra 3,000 steps (from baseline value) on at least 3 days of the week</td></tr><tr><td align=\"center\">Week 7</td><td align=\"left\">To walk an extra 3,000 steps (from baseline value) on at least 5 days of the week</td></tr><tr><td align=\"center\">Week 8</td><td align=\"left\">To walk an extra 3,000 steps (from baseline value) on at least 5 days of the week</td></tr><tr><td align=\"center\">Weeks 9–12</td><td align=\"left\">To maintain walking levels using the week 7 goal</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Number of participants in each level for the five domains of the EuroQol EQ-5D descriptive system</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td/><td/><td align=\"center\" colspan=\"2\">Mobility</td><td align=\"center\" colspan=\"2\">Self Care</td><td align=\"center\" colspan=\"2\">Usual Care</td><td align=\"center\" colspan=\"2\">Pain/Discomfort</td><td align=\"center\" colspan=\"2\">Anxiety/Depression</td></tr><tr><td/><td/><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td></tr><tr><td/><td/><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\">No Problems</td><td align=\"left\">Intervention^a</td><td align=\"center\">34</td><td align=\"center\">33</td><td align=\"center\">39</td><td align=\"center\">39</td><td align=\"center\">35</td><td align=\"center\">34</td><td align=\"center\">27</td><td align=\"center\">30</td><td align=\"center\">25</td><td align=\"center\">24</td></tr><tr><td/><td align=\"left\">Control^b</td><td align=\"center\">33</td><td align=\"center\">33</td><td align=\"center\">40</td><td align=\"center\">40</td><td align=\"center\">35</td><td align=\"center\">35</td><td align=\"center\">26</td><td align=\"center\">28</td><td align=\"center\">28</td><td align=\"center\">27</td></tr><tr><td align=\"left\">Some/Moderate</td><td align=\"left\">Intervention</td><td align=\"center\">5</td><td align=\"center\">6</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">4</td><td align=\"center\">5</td><td align=\"center\">12</td><td align=\"center\">9</td><td align=\"center\">14</td><td align=\"center\">15</td></tr><tr><td/><td align=\"left\">Control</td><td align=\"center\">7</td><td align=\"center\">7</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">5</td><td align=\"center\">5</td><td align=\"center\">14</td><td align=\"center\">12</td><td align=\"center\">12</td><td align=\"center\">13</td></tr><tr><td align=\"left\">Extreme Problems</td><td align=\"left\">Intervention</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td></tr><tr><td/><td align=\"left\">Control</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Descriptive statistics for age, pedometer step-counts and health related outcomes at baseline and week 12 for intervention and control group. Values are mean (<italic>M</italic>) and standard deviation (<italic>SD</italic>).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"2\">Intervention Group (n = 39)</td><td align=\"center\" colspan=\"2\">Control Group (n = 40)</td></tr></thead><tbody><tr><td/><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td></tr><tr><td/><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">Age (years)</td><td align=\"center\">47.3 (9.3)</td><td align=\"center\">^a</td><td align=\"center\">51.2 (7.9)</td><td align=\"center\">^a</td></tr><tr><td align=\"left\">Steps/day</td><td align=\"center\">6802 (3212)</td><td align=\"center\">9977 (4669)</td><td align=\"center\">6924 (3201)</td><td align=\"center\">7078 (2911)</td></tr><tr><td align=\"left\">PANAS positive</td><td align=\"center\">31.2 (6.7)</td><td align=\"center\">33.5 (7.4)</td><td align=\"center\">31.7 (6.9)</td><td align=\"center\">31.3 (7.6)</td></tr><tr><td align=\"left\">PANAS negative</td><td align=\"center\">20.1 (7.2)</td><td align=\"center\">19.1 (6.9)</td><td align=\"center\">20.2 (8.1)</td><td align=\"center\">18.8 (7.5)</td></tr><tr><td align=\"left\">EQ-5D tariff</td><td align=\"center\">0.88 (0.12)</td><td align=\"center\">0.89 (0.11)</td><td align=\"center\">0.87 (0.12)</td><td align=\"center\">0.89 (0.12)</td></tr><tr><td align=\"left\">EQ VAS</td><td align=\"center\">65.4 (18.3)</td><td align=\"center\">69.5 (17.8)</td><td align=\"center\">69.8 (19.7)</td><td align=\"center\">70.7 (18.6)</td></tr><tr><td align=\"left\">Height (m)^b</td><td align=\"center\">1.66 (0.08)</td><td align=\"center\">^a</td><td align=\"center\">1.64 (0.08)</td><td align=\"center\">^a</td></tr><tr><td align=\"left\">Body Mass (kg)^b</td><td align=\"center\">78.9 (15.6)</td><td align=\"center\">79.1 (15.2)</td><td align=\"center\">79.5 (18.1)</td><td align=\"center\">79.6 (17.8)</td></tr><tr><td align=\"left\">BMI (kg/m²)^b</td><td align=\"center\">28.5 (4.8)</td><td align=\"center\">28.7 (4.8)</td><td align=\"center\">29.4 (6.3)</td><td align=\"center\">29.5 (6.2)</td></tr><tr><td align=\"left\">Waist circumference (cm)^b</td><td align=\"center\">89.5 (12.6)</td><td align=\"center\">89.9 (12.6)</td><td align=\"center\">90.4 (14.6)</td><td align=\"center\">91.1 (15.6)</td></tr><tr><td align=\"left\">Hip circumference (cm)^b</td><td align=\"center\">108.9 (8.8)</td><td align=\"center\">108.6 (9.7)</td><td align=\"center\">110.1 (12.4)</td><td align=\"center\">110.3 (11.8)</td></tr><tr><td align=\"left\">Waist:Hip Ratio^b</td><td align=\"center\">0.82 (0.08)</td><td align=\"center\">0.83 (0.08)</td><td align=\"center\">0.82 (0.09)</td><td align=\"center\">0.82 (0.09)</td></tr><tr><td align=\"left\">% body fat^b</td><td align=\"center\">30.7 (4.4)</td><td align=\"center\">31. (4.9)</td><td align=\"center\">31.8 (5.6)</td><td align=\"center\">32.7 (6.3)</td></tr><tr><td align=\"left\">Systolic blood pressure (mm Hg)^b</td><td align=\"center\">118.2 (17.9)</td><td align=\"center\">119.6 (17.0)</td><td align=\"center\">119.9 (15.9)</td><td align=\"center\">121.9 (15.1)</td></tr><tr><td align=\"left\">Diastolic blood pressure (mm Hg)^b</td><td align=\"center\">75.1 (11.4)</td><td align=\"center\">77.1 (12.1)</td><td align=\"center\">75.5 (11.8)</td><td align=\"center\">79.1 (11.6)</td></tr><tr><td align=\"left\">Heart Rate (beats.min^-1)^c</td><td align=\"center\">68.6 (7.2)</td><td align=\"center\">69.8 (7.2)</td><td align=\"center\">67.9 (8.6)</td><td align=\"center\">69.2 (9.0)</td></tr><tr><td align=\"left\">Total Cholesterol (mmol.l^-1)^c</td><td align=\"center\">5.4 (1.3)</td><td align=\"center\">5.4 (1.2)</td><td align=\"center\">5.5 (1.1)</td><td align=\"center\">5.5 (1.0)</td></tr><tr><td align=\"left\">HDL (mmol^-1)^c</td><td align=\"center\">1.3 (0.3) 50.7</td><td align=\"center\">1.3 (0.3)</td><td align=\"center\">1.4 (0.4) 54.6</td><td align=\"center\">1.4 (0.4)</td></tr><tr><td align=\"left\">Chol:HDL Ratio^c</td><td align=\"center\">4.2 (1.1)</td><td align=\"center\">4.2 (1.1)</td><td align=\"center\">4.1 (1.2)</td><td align=\"center\">4.0 (1.3)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Descriptive statistics for IPAQ variables at baseline and week 12. Values are median (<italic>Mdn</italic>) and range (<italic>r</italic>).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"2\">Intervention Group (n = 39)</td><td align=\"center\" colspan=\"2\">Control Group (n = 40)</td></tr></thead><tbody><tr><td/><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td><td align=\"center\">Baseline</td><td align=\"center\">Week 12</td></tr><tr><td/><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold>Work-related PA</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\">Vigorous PA</td><td align=\"center\">0 (1080)</td><td align=\"center\">0 (1800)</td><td align=\"center\">0 (720)</td><td align=\"center\">0 (540)</td></tr><tr><td align=\"left\">Moderate PA</td><td align=\"center\">0 (1500)</td><td align=\"center\">0 (900)</td><td align=\"center\">0 (1500)</td><td align=\"center\">0 (600)</td></tr><tr><td align=\"left\">Walking</td><td align=\"center\">0 (1620)</td><td align=\"center\">0 (2520)</td><td align=\"center\">0 (1350)</td><td align=\"center\">0 (1650)</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">0 (3000)</td><td align=\"center\">0 (4680)</td><td align=\"center\">0 (2500)</td><td align=\"center\">0 (2730)</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Transportation PA</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\">Bicycling</td><td align=\"center\">0 (0)</td><td align=\"center\">0 (0)</td><td align=\"center\">0 (40)</td><td align=\"center\">0 (0)</td></tr><tr><td align=\"left\">Walking</td><td align=\"center\">105 (1680)</td><td align=\"center\">90 (900)</td><td align=\"center\">80 (1680)</td><td align=\"center\">40 (840)</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">105 (1680)</td><td align=\"center\">90 (900)</td><td align=\"center\">80 (1720)</td><td align=\"center\">40 (840)</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Housework PA</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\">Vigorous outside home</td><td align=\"center\">0 (840)</td><td align=\"center\">0 (120)</td><td align=\"center\">0 (750)</td><td align=\"center\">0 (360)</td></tr><tr><td align=\"left\">Moderate outside home</td><td align=\"center\">0 (2100)</td><td align=\"center\">0 (1680)</td><td align=\"center\">0 (1260)</td><td align=\"center\">0 (720)</td></tr><tr><td align=\"left\">Moderate inside home</td><td align=\"center\">210 (2100)</td><td align=\"center\">112.5 (840)</td><td align=\"center\">180 (1680)</td><td align=\"center\">90 (1260)</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">360 (4200)</td><td align=\"center\">120 (2520)</td><td align=\"center\">255 (2640)</td><td align=\"center\">145 (2100)</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Leisure-time PA</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\">Walking</td><td align=\"center\">40 (840)</td><td align=\"center\">100 (840)</td><td align=\"center\">35 (600)</td><td align=\"center\">16.25 (840)</td></tr><tr><td align=\"left\">Vigorous PA</td><td align=\"center\">0 (180)</td><td align=\"center\">0 (120)</td><td align=\"center\">0 (180)</td><td align=\"center\">0 (180)</td></tr><tr><td align=\"left\">Moderate PA</td><td align=\"center\">0 (360)</td><td align=\"center\">0 (60)</td><td align=\"center\">0 (120)</td><td align=\"center\">0 (600)</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">60 (840)</td><td align=\"center\">90 (840)</td><td align=\"center\">60 (600)</td><td align=\"center\">11 (840)</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Combined Domains</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\">Total Walking</td><td align=\"center\">225 (3360)</td><td align=\"center\">260 (2850)</td><td align=\"center\">167.5 (1740)</td><td align=\"center\">90 (1925)</td></tr><tr><td align=\"left\">Total Moderate PA</td><td align=\"center\">420 (4380)</td><td align=\"center\">120 (2760)</td><td align=\"center\">360 (2640)</td><td align=\"center\">175 (2100)</td></tr><tr><td align=\"left\">Total Vigorous PA</td><td align=\"center\">0 (1080)</td><td align=\"center\">0 (1800)</td><td align=\"center\">0 (720)</td><td align=\"center\">0 (600)</td></tr><tr><td align=\"left\">Total PA</td><td align=\"center\">690 (6300)</td><td align=\"center\">590 (5415)</td><td align=\"center\">640 (4300)</td><td align=\"center\">500 (3185)</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>Time Spent Sitting</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\">Weekday</td><td align=\"center\">1500 (3750)</td><td align=\"center\">1200 (3900)</td><td align=\"center\">1500 (3450)</td><td align=\"center\">1500 (2850)</td></tr><tr><td align=\"left\">Weekend</td><td align=\"center\">480 (1320)</td><td align=\"center\">360 (1200)</td><td align=\"center\">600 (1200)</td><td align=\"center\">600 (1320)</td></tr><tr><td align=\"left\">Total</td><td align=\"center\">2265 (4650)</td><td align=\"center\">1680 (5100)</td><td align=\"center\">2130 (4170)</td><td align=\"center\">2100 (3630)</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>^aintervention group (n = 39).</p><p>^bcontrol group (n = 40)</p></table-wrap-foot>", "<table-wrap-foot><p>^anot measured at week 12.</p><p>^banthropometric measures: (n = 37) for intervention group, (n = 39) for control group.</p><p>^cblood measures: (n = 32) for intervention group, (n = 34) for control group.</p><p>Note: there were no significant differences between the intervention and control group for any variable at baseline.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1479-5868-5-44-1\"/>", "<graphic xlink:href=\"1479-5868-5-44-2\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>For decades researchers have tried to determine whether exposure to welding fumes poses an increased risk of lung cancer. Indeed, this health concern is one of the most important questions in welding fume-related toxicological research. The International Agency for Research on Cancer has deemed welding fume a group 2B agent, defined as a mixture \"possibly carcinogenic\" to humans [##REF##2232124##1##]. This categorization of welding fume carcinogenicity, however, was based on limited evidence in humans and a lack of animal data.</p>", "<p>The harmful health effects of welding are well documented and epidemiological evidence generally supports the hypothesis that exposure to welding fume increases lung cancer risk, but confounders such as asbestos exposure and smoking obscure these findings [##REF##10026469##2##, ####REF##9167233##3##, ##REF##17973064##4##, ##REF##2024826##5####2024826##5##]. Debate also exists over which type of welding may pose the greater risk. Interestingly, fumes from both non-carcinogenic metal-containing mild steel (MS) and carcinogenic metal-containing stainless steel (SS) welding wire have been shown to increase lung cancer risk in welders [##REF##8892542##6##,##REF##12109555##7##]. For these reasons, we initiated a multipart study to ultimately determine the carcinogenic potential of SS and MS welding fumes in an animal model.</p>", "<p>Electric arc welding joins pieces of metal that are rendered liquid by heat. Arc temperatures above 4000°C heat the base metal pieces to be joined and the consumable electrode wire that is continuously fed into the weld. The vaporized metals, derived primarily from the wire, react with air and form the fume, which consists of a complex mixture of metal oxides. Depending on the welding process employed, the electrode coating, shielding gases, fluxes, base metal, and paint or surface coatings also may comprise the welding fume [##REF##12585507##8##].</p>", "<p>Among the numerous types of welding processes, manual metal arc (MMA) and gas metal arc (GMA) welding are two types commonly used in the workplace. Welding processes that use SS wire produce fumes that contain carcinogenic metals such as chromium (Cr) and nickel (Ni). Welding fume from MS wire primarily consists of iron (Fe) with a lesser amount of manganese (Mn), but no Cr or Ni. In addition, fumes from MMA-SS wire yield more water-soluble metals in suspension than GMA-SS or GMA-MS fumes and consequently, in animal models, induced a more potent acute lung toxicity [##REF##10580758##9##,##REF##6896394##10##].</p>", "<p>In this investigation, we used lung tumor susceptible A/J mice, a common animal model for lung carcinogenesis studies. Compared to the essentially lung tumor resistant C57BL/6J strain, A/J mice exhibit high susceptibility to spontaneous and chemically induced lung tumors [##REF##1108612##11##]. Further, the lung tumors in the A/J mouse display many morphological, histopathological, and molecular similarities to human pulmonary adenocarcinomas, which makes them a relevant model for lung cancer research [##REF##9659582##12##,##REF##15769940##13##].</p>", "<p>Our first objective was to characterize the potential of welding fumes of different metal compositions, or components thereof, to cause acute lung toxicity in lung tumor susceptible (A/J) and resistant (C57BL/6J) mice. We rationalized that this direct strain comparison would be invaluable for interpretation of our second objective which was to determine the tumorigenic potential of these different welding fumes in the susceptible A/J mouse model.</p>" ]

[ "<title>Methods</title>", "<title>Animals</title>", "<p>Male C57BL/6J and A/J mice, 4 weeks of age were purchased from Jackson Laboratories (Bar Harbor, ME) and housed in an AAALAC-accredited, specific pathogen-free, environmentally controlled facility. All mice were free of endogenous viral pathogens, parasites, mycoplasmas, Helicobacter, and CAR Bacillus. Mice were individually housed in ventilated cages and provided HEPA-filtered air under a controlled light cycle (12 hour light/12 hour dark) at a standard temperature (22–24°C) and 30–70% relative humidity. Animals were acclimated to the animal facility for a minimum of one week and allowed access to a conventional diet (6% Irradiated NIH-31 Diet, Harlan Teklad, Madison, WI) and tap water <italic>ad libitum</italic>. All procedures were performed using protocols approved by the National Institute for Occupational Safety and Health Institutional Animal Care and Use Committee.</p>", "<title>Welding fume collection and characterization</title>", "<p>The welding fumes used in this study were provided by Lincoln Electric Co., (Cleveland, OH). The collection and characterization of these fumes were previously described [##REF##10580758##9##]. Briefly, the fumes were generated in a cubical open-front fume chamber (volume = 1 m³) by a skilled welder, using a manual or automatic technique appropriate for the electrode, and then collected on a sterile 0.2 μm filter. The samples were generated by three welding processes: gas metal arc welding (with argon and CO₂shielding gases) using a mild steel electrode; gas metal arc welding using a stainless steel electrode; and manual metal arc welding using a flux-cored stainless steel electrode. Reported in Table ##TAB##4##5## are the metal constituents, solubility/insolubility ratio, and pH of each welding fume sample [##REF##10580758##9##]. Seven different metals (Cr, Cu, Fe, Mn, Ni, Ti, and V) commonly found in welding fumes were measured using inductively coupled argon plasma atomic emission spectroscopy. Count mean diameters were 1.22, 1.38, and 0.92 μm for the GMA-MS, GMA-SS, and MMA-SS samples, respectively, as determined by electron microscopy [##REF##10580758##9##].</p>", "<title>Welding fume and soluble chromium preparation</title>", "<p>Each welding fume was weighed and suspended in sterile Ca⁺²and Mg⁺²-free phosphate buffered saline (PBS) in a 50 ml sterile conical tube. Following the initial preparation, the fume samples were vortexed then sonicated for 1 minute using a Sonifier 450 Cell Disruptor (Branson Ultrasonics, Danbury, CT). Prior to dosing, the samples were vortexed then sonicated for 15 seconds and vortexed immediately before each mouse exposure. For each experimental time point, fresh welding fume suspensions were made and the same preparation was used to expose both strains of mice.</p>", "<p>Soluble chromium in the form of sodium dichromate dihydrate (Na₂Cr₂O₇·2H₂O) (Sigma-Aldrich, St. Louis, MO) was used to represent the hexavalent chromium species found in the MMA-SS fume as shown in previous studies [##REF##12832661##20##,##UREF##0##40##]. For each experimental time point, fresh Na₂Cr₂O₇·2H₂O was weighed into a sterile 50 ml conical tube, suspended in sterile PBS then vortexed. The same preparation was used to expose both strains of mice.</p>", "<title>Mouse pharyngeal aspiration exposure</title>", "<p>Age and weight-matched A/J and C57BL/6J mice were exposed to GMA-MS, GMA-SS, MMA-SS, S-Cr, or sterile Ca⁺²and Mg⁺²-free PBS (vehicle control) by pharyngeal aspiration as previously described [##REF##12857634##41##]. Briefly, each mouse was placed in a glass jar with a gauze pad moistened with isoflurane (Abbott Laboratories, North Chicago, IL) until slowed breathing was observed. The mouse was then suspended, by its top incisors, on a slanted board in a supine position. The tongue was extended with forceps and the solution was placed by pipette at the back of the throat. The tongue was held extended until the solution was aspirated into the lung and the mouse resumed a regular breathing pattern. When performed properly, this technique allows minimal sample loss to the digestive tract. The mouse was then returned to its cage to recover, typically 10–15 seconds.</p>", "<p>In this study, mice were exposed over a 10 day period to four bolus doses of test material in lieu of a single bolus dose. This regime achieved an accumulation of particles in the lung over time, which may be more representative of an occupational exposure. Mice were exposed four times (once every 3 days) to 85 μg (~5 mg/kg) of GMA-MS, GMA-SS, or MMA-SS welding fume, or 25.5 μg (~1.5 mg/kg) S-Cr. The cumulative fume lung burden was derived from our previous pharyngeal aspiration experiment in the A/J mouse and is equivalent to ~196 days of exposure in a 75 kg welder working an eight hour shift [##REF##16844664##19##]. The dose of S-Cr was equal to the weight % of Cr (~30%) found in the MMA-SS total suspension (Table ##TAB##4##5##). A 25 μl aspiration volume was used and shams were administered an equal volume of PBS. Mice were sacrificed 2, 7 and 28 days post the fourth exposure. For the tumor study, A/J mice (n = 25/group) were exposed using the same protocol to GMA-MS, GMA-SS, or MMA-SS welding fume and sacrificed 48 and 78 weeks after the fourth exposure. S-Cr was not included as a group in the tumor study because our main objective was to first examine the effects of welding fumes, not their components.</p>", "<title>Urethane exposure</title>", "<p>Urethane (Acros Organics N.V., Fair Lawn, NJ, CAS#51-79-6) served as a positive control for confirmation of A/J tumor susceptibility in this study. A single i.p. dose of urethane (0.75 g/kg) was administered to two independent A/J vendor lots. The positive control group was run in parallel with the control and welding fume-exposed groups for both the 48 week (n = 25) and 78 week (n = 20) time points.</p>", "<title>Body weight determination</title>", "<p>For the comparative strain study, mice were weighed after the one week acclimation period, throughout the dosing, and again at the 2, 7, and 28 day sacrifices. The average body weight after the final exposure was approximately 17 ± 0.53 g for both mouse strains. All groups gained weight throughout the study and no treatment effects were observed.</p>", "<p>A/J mice kept for 48 and 78 weeks post-exposure were weighed after the one week acclimation period, during dosing, and every 4 weeks until sacrifice. The average body weight (± SE) at the start of the study for the sham and welding fume groups was 18.9 ± 0.17 g and 18.4 ± 0.20 g for the 48 and 78 week groups, respectively.</p>", "<title>Bronchoalveolar lavage</title>", "<p>BAL of the whole lung was used to assess lung inflammation and injury at 2, 7, and 28 days post-exposure to various welding fumes or S-Cr in A/J and C57BL/6J mice. Mice were deeply anesthetized with Sleepaway [26% sodium pentobarbital, 7.8% isopropyl alcohol and 20.7% propylene glycol] (Fort Dodge Animal Health, Fort Dodge, IA) then weighed. Once unresponsive, the abdomen was opened and the vena cava was exsanguinated. For BAL, the trachea was cannulated with a blunted 22 gauge needle and, while massaging the thorax, 0.6 ml of cold PBS was slowly instilled into the lung then withdrawn and placed into a 15 ml conical tube. This constituted the first fraction BAL fluid. Two subsequent lavages (1.0 ml/instillate) were collected into a separate tube which represented the second fraction. The BAL fluid was preserved on ice until four animals were sacrificed then the samples were centrifuged (500 × <italic>g</italic>, 10 min, 4°C).</p>", "<p>Aliquots of the first fraction BAL supernatant were used to assess lung injury or frozen at -80°C for later analysis. The supernatant of the second fraction was discarded. The cell pellets from both fractions were combined and centrifuged (500 × g, 6 minutes, 4°C) and the supernatant discarded. The final cell pellet was suspended in a known volume of PBS and used for cell enumeration and differential staining.</p>", "<p>Total cell numbers were determined using a Coulter Multisizer II and AccuComp software (Coulter Electronics, Hialeah, FL). For differential staining, BAL cells were plated onto glass slides using a Cytospin 3 centrifuge (Shandon Life Sciences International, Cheshire, England) set at 800 rpm for 5 minutes. Slides were stained using Leukostat stain (Fisher Scientific, Pittsburgh, PA) then coverslipped. A minimum of 300 cells/slide consisting of alveolar macrophages/monocytes, lymphocytes, or PMN were identified using light microscopy. Slides from shams consisted typically of &gt; 99% alveolar macrophages.</p>", "<title>Bronchoalveolar lavage fluid cytokine analysis</title>", "<p>Concentrations of cytokines from the first fraction BAL supernatant were measured using a mouse inflammation cytometric bead array kit (BD Biosciences, San Diego, CA) and analyzed on a FACSCalibur flow cytometer as previously described [##REF##18089291##42##]. The following cytokines were measured: IL-6, IL-10, MCP-1, IFN-γ, TNF-α and IL-12p70. Standard curves with a range of 20–5,000 pg/ml were determined for each cytokine. The sensitivity of the assay for each protein ranged from 2.5–52.7 pg/ml. Because BAL protein levels for some analytes were at or below assay sensitivity, which limited statistical analysis, confirmation of selected BAL profiles by real-time reverse transcription polymerase chain reaction (RT-PCR) [see below] was done [##REF##18089291##42##]. To appropriately represent the protein data, a scatter plot was chosen with the mean values indicated for each group.</p>", "<title>Biochemical measurements</title>", "<p>Albumin, a measure of damage to the lung alveolar epithelial barrier, and LDH activity, indicative of lung cell death, were measured in the first fraction BAL fluid supernatant. The albumin concentration was determined colorimetrically at 628 nm based on albumin binding to bromcresol green, using an albumin BCG diagnostic kit (Sigma Chemical Co., St. Louis, MO). LDH activity was determined by measuring the oxidation of lactate to pyruvate coupled with the formation of NADH at 340 nm. Both measurements were performed with a COBAS MIRA Plus auto-analyzer (Roche Diagnostic Systems, Montclair, NJ).</p>", "<title>Real-Time RT-PCR</title>", "<p>In separate identical experiments, whole lungs were removed from sham and welding fume-exposed mice then snap frozen in liquid nitrogen and stored at -80°C for RNA isolation. RNA was isolated from whole lung homogenates using the TRIzol (Invitrogen, Carlsbad, CA) method and then cleaned according to the manufacturer's instructions using a RNeasy Mini Kit (Qiagen, Valencia, CA) to remove possible DNA contamination. One μg of total RNA was reverse-transcribed using random hexamers (Applied Biosystems, Foster City, CA) and Superscript II (Invitrogen, Carlsbad, CA). Five μl of cDNA (in duplicates for each gene) was then used for gene expression determination using the Applied Biosystems 7900HT (Foster City, CA). The ribosomal subunit 18S was used as the housekeeping gene (Hs99999901_s1, Applied Biosystems). Relative gene expression was calculated using the comparative threshold method (2-ΔΔCt) [##REF##11846609##43##].</p>", "<p>The cytokine bead array findings from the MMA-SS 2 and 7 day post-exposure time points only were verified using the following Pre-designed Assays-on-Demand™ TaqMan^®probes and primers from Applied Biosystems: IFN-γ (Mm00801778_m1), IL-6 (Mm00446190_m1), MCP-1 (Mm00441242_m1), and TNF-α (Mm00443258_m1).</p>", "<p>The following oxidative stress markers were also evaluated using RT-PCR: NOS2 or iNOS [Mm00440485_m1], COX-2 [Mm00440485_m1], and GST-Pi [Mm00839138_g1].</p>", "<title>Gross tumor counts and histopathology</title>", "<p>A/J mice were euthanized by carbon dioxide asphyxiation, weighed, then the abdomen was opened and the vena cava exsanguinated. The whole lung was excised and gross tumor counts and measurements were recorded for each lung lobe. Apparent merged tumors, defined as a single tumor pattern in double-nodule form or an apparent collision of two different tumors, were counted as one because this was impossible to distinguish at necropsy. The lungs were inflated and fixed with 10% neutral buffered formalin for a minimum of 24 hours. Each lung lobe (apical, azygos, cardiac, diaphragmatic, left) was separately embedded in paraffin then a 5 μm standardized section was cut from each lung lobe. Slides were stained with hematoxylin and eosin and interpreted by a contracted board certified veterinary pathologist in a blinded fashion for morphological changes and proliferative/neoplastic lesions. If abnormal changes were found, severity was scored as follows: 1 = minimal, 2 = mild, 3 = moderate, 4 = marked, 5 = severe. The final severity score reflects the average of the right and left lung lobe scores. Proliferative/neoplastic changes were scored as P = preneoplastic epithelial proliferation, AP = adenoma arising within a proliferation, A = adenoma, CA = carcinoma arising within an adenoma, C = carcinoma, or MC = microcarcinoma according to Belinksy <italic>et al</italic>. [##REF##1591728##33##]. Since examination of a single histological section per lung underestimates the total number of lesions per lung [##REF##2483278##44##], the gross count at necropsy would be more representative of the response. However, for completeness, both microscopic and gross exam were statistically evaluated in this study. Histopathological interpretation was not done on lung sections from urethane-exposed mice because this was previously reported and was not our purpose [##REF##3470549##45##,##REF##3863993##46##].</p>", "<title>Statistical comparisons and analysis</title>", "<p>For the 2, 7, and 28 day study, the mouse exposures were designed to account for the following statistical comparisons: 1) MMA-SS versus S-Cr and 2) GMA-MS versus GMA-SS between the two mouse strains within a single time point. Therefore, the exposures for each experimental time point (2, 7, or 28 days post-exposure) were run in parallel with both strains and shams were run with every exposure. Statistical comparisons were not made between different time points post-exposure or between the MMA-SS and GMA welding fumes.</p>", "<p>All analyses were performed either using JMP version 5.0.1, or the SAS system for Windows version 9.1 (SAS Institute, Cary, NC). Factorial analysis of variance (ANOVA) was utilized on continuous variables to incorporate strain and treatment into each analysis. For some variables a log transformation was performed on the data to reduce heterogeneous variance and meet the assumptions of the ANOVA. All post-hoc comparisons were carried out using Fishers Least Significant Difference Test. For all analyses, the criterion of significance was p &lt; 0.05. Gross tumor counts and histopathology counts from sections were analyzed similarly. Tumor incidence (presence or absence of tumors) was analyzed using a Chi-Square test in SAS 'Proc Freq', while tumor multiplicity (number of tumors/lung) was analyzed using Poisson regression in SAS 'Proc Genmod'. All analyses on tumor data utilized only those animals surviving the complete 48 and 78 week time points.</p>" ]

[ "<title>Results</title>", "<title>Bronchoalveolar lavage (BAL) findings 2 days after exposure: GMA-MS and GMA-SS</title>", "<p>GMA-MS welding fume caused a similar degree of lung cell death (measured as lactate dehydrogenase activity [LDH]) in both strains and no significant epithelial damage (measured as albumin) compared to the corresponding sham (Table ##TAB##0##1##). The recovered BAL % polymorphonuclear leukocytes (PMN) was two-fold greater in the A/J compared to the C57BL/6J strain while lymphocytes were not elevated in response to this fume in either strain. GMA-SS exposure was more toxic to the A/J than the GMA-MS fume. Significant lung epithelial damage and cell death occurred in both strains with the A/J having a ~1.7 fold greater response. The %PMN was markedly higher in the A/J strain (44%) versus the C57BL/6J (9%) and lymphocytes were equally elevated in both strains. No strain differences were found for increased macrophage/monocytes in the BAL, but a significant increase in number was observed for the C57BL/6J strain following GMA-SS exposure only (data not shown).</p>", "<title>BAL findings 2 days after exposure: MMA-SS and soluble chromium (S-Cr)</title>", "<p>At 2 days post-exposure, both mouse strains had significant lung cell death and epithelial damage following MMA-SS or S-Cr exposure (Table ##TAB##0##1##). MMA-SS fume was a greater inducer of cell death in the A/J and this was also significantly greater in comparison to the MMA-SS-exposed C57BL/6J strain (~1.5 fold). LDH levels between the MMA-SS and S-Cr exposures were not different in the C57BL/6J. The A/J had significantly greater epithelial damage following MMA-SS exposure compared to the C57BL/6J strain as shown by the increased albumin in the BAL. The C57BL/6J exhibited more epithelial damage than the A/J strain following S-Cr exposure although this was not a consistent finding for other markers of toxicity in this study. Both exposures caused a significant increase in %PMN at 2 days in both mouse strains compared to the corresponding sham (Table ##TAB##0##1##). The C57BL/6J strain responded equally to both MMA-SS and S-Cr with approximately a 9% increase in BAL PMN. The C57BL/6J had ~2% increase in lymphocytes following the exposures, which was greater than both exposed A/J groups. In contrast, the A/J mice had a significantly greater response to MMA-SS (~40% PMN) but responded similarly to the C57BL/6J following S-Cr exposure (~11% PMN). Of note, although treatment effects were found for increased lung macrophage/monocytes in both strains following MMA-SS exposure, no strain differences were found for this inflammatory parameter (data not shown).</p>", "<title>BAL findings 7 days after exposure: GMA-MS and GMA-SS</title>", "<p>By 7 days post-exposure, LDH remained significantly elevated in both mouse strains exposed to GMA-MS welding fume (Table ##TAB##1##2##). At this time point, the A/J mice had significantly greater LDH levels compared to the C57BL/6J strain. As with the earlier time point, no indication of epithelial damage occurred with this fume. The %PMN remained significantly elevated only in the A/J strain at 7 days (~12%). The GMA-SS fume caused a greater LDH and %PMN response in the A/J compared to the C57BL/6J. At 7 days, this fume was again more toxic to the A/J compared to the MS fume. No strain differences were found for increased lymphocytes or macrophage/monocytes, although a mild elevation versus the corresponding shams was found for the GMA-SS groups (macrophage data not shown).</p>", "<title>BAL findings 7 days after exposure: MMA-SS and S-Cr</title>", "<p>No strain differences were observed for LDH or albumin at 7 days post-exposure to MMA-SS fume, although both parameters remained significantly elevated in the A/J, only LDH remained increased in the C57BL/6J (Table ##TAB##1##2##). Both strains in the S-Cr-exposed groups had increased albumin but no strain differences were noted. Significant strain differences were evident for %PMN influx. MMA-SS caused a more pronounced effect in the A/J strain with ~12% PMN versus ~6% in the S-Cr-exposed mice, while only a mild elevation was found for the exposed C57BL/6J groups. No strain differences were found for increased macrophage/monocytes, but an unremarkable increase in number was found in the MMA-SS groups (data not shown).</p>", "<title>BAL findings 28 days after exposure: GMA-MS and GMA-SS</title>", "<p>By 28 days, LDH and albumin had returned to baseline in all groups exposed to GMA-MS (data not shown). The only strain difference noted was the PMN response which remained at ~10% in the A/J mice versus ~1% in the C57BL/6J. The A/J mice continued to have significant lung cell death, lymphocyte and PMN influx associated with GMA-SS exposure, and these responses were ~1.2–2 fold greater in comparison to the GMA-MS fume. The A/J strain exhibited a 9 fold greater %PMN response compared to the C57BL/6J following exposure to GMA-SS.</p>", "<title>BAL findings 28 days after exposure: MMA-SS and S-Cr</title>", "<p>At 28 days post-exposure, LDH and albumin were not significantly elevated in the MMA-SS or S-Cr exposed groups of either strain (data not shown). Only the MMA-SS-exposed A/J mice had significant PMN in the BAL, approximately 4.4%.</p>", "<p>Of note, for all groups, no strain differences were found for any BAL parameter in the sham mice at any time point.</p>", "<title>BAL inflammatory cytokine and lung gene expression analysis</title>", "<p>The first fraction BAL supernatant was used to determine the protein levels of interferon-γ (IFN-γ), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-12p70 (IL-12p70), monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor-α (TNF-α) at 2, 7, and 28 days post-exposure to MMA-SS fume or S-Cr. Protein levels of IL-10 and IL-12p70 were unaltered by either exposure (data not shown).</p>", "<p>IFN-γ protein was increased following MMA-SS exposure in the A/J but not the C57BL/6J mice at 2 days (Figure ##FIG##0##1A##). By 7 days post-exposure, these levels remained moderately elevated (data not shown). No IFN-γ protein was detected in the C57BL/6J strain for either exposure at this time point. Whole lung gene expression confirmed these findings in the MMA-SS-exposed A/J mice. A mild increase in gene expression was found for the MMA-SS-exposed C57BL/6J mice but this was significantly less than levels found in the exposed A/J strain (Figure ##FIG##0##1B##). IL-6 protein was increased following S-Cr and MMA-SS exposure at 2 days in both strains (Figure ##FIG##0##1C##). The C57BL/6J responded equally to both exposures while the mean response to the MMA-SS was greater in the A/J mice. Gene expression confirmed these data as the A/J showed approximately a two fold greater increase in IL-6 mRNA compared to the C57BL/6J (Figure ##FIG##0##1D##). By 7 days, gene expression had returned to baseline and protein levels declined with a slight elevation remaining in the MMA-SS-exposed A/J strain (data not shown). By 28 days, protein levels were undetectable in all groups for both IFN-γ and IL-6 (data not shown). No differences were found between the two strains for gene expression levels in the shams at either time point.</p>", "<p>A similar trend was found for protein and gene expression levels of MCP-1 and TNF-α (Figure ##FIG##1##2##). The A/J mice consistently had a greater response to MMA-SS compared to S-Cr and the C57BL/6J strain at 2 days post-exposure (Figure ##FIG##1##2A## &amp;##FIG##1##2C##). Gene expression for MCP-1 and TNF-α revealed at least a two fold induction difference between the strains (Figure ##FIG##1##2B## &amp;##FIG##1##2D##). By 7 days, gene expression returned to baseline while protein levels decreased but remained mildly elevated in the exposed A/J mice (data not shown). By 28 days, protein levels were undetectable in all groups for MCP-1 and TNF-α (data not shown). In addition, no differences were found between the two strains for gene expression levels in the saline shams at either time point.</p>", "<p>The first fraction BAL supernatant was used to determine the protein levels of IFN-γ, IL-6, IL-10, IL-12p70, MCP-1, and TNF-α at 2, 7, and 28 days post-exposure to GMA welding fumes. Data are shown only for MCP-1 and TNF-α at the 2 and 28 day time points (Figure ##FIG##2##3A–D##); the IFN-γ, IL-6, and 7 day data are described below. No trends were found in either strain for IL-10 and IL-12p70 protein (data not shown).</p>", "<p>IFN-γ protein was increased following GMA-SS fume exposure (9.0 ± 2.4 pg/ml) only in the A/J at 2 days post-exposure but was undetectable by day 7. IL-6 protein was greater in the GMA-SS-exposed A/J compared to the C57BL/6J at 2 days (23.3 ± 1.8 and 15.5 ± 5.3 pg/ml, respectively) and levels remained elevated at 7 days in the A/J (12.5 ± 2.6 pg/ml). By 28 days, IL-6 levels were undetectable in the A/J. GMA-MS exposure did not increase IFN-γ or IL-6 in either strain at any time point post-exposure (data not shown).</p>", "<p>MCP-1 protein levels were increased following GMA-SS exposure at 2, 7, and 28 days in the A/J strain while the C57BL/6J only had elevated levels at day 2 (Figure ##FIG##2##3A## &amp;##FIG##2##3B##). GMA-MS fume did not affect BAL levels of MCP-1 at any time point in either strain. TNF-α levels in the GMA-SS-exposed A/J were elevated at 2 (Figure ##FIG##2##3C##) and 7 days post-exposure and remained mildly elevated at 28 days (Figure ##FIG##2##3D##). The C57BL/6J had lower TNF-α levels at 2 and 7 days post-exposure and no detectable levels by 28 days. At 2 (Figure ##FIG##2##3D##) and 7 days, GMA-MS fume did increase BAL TNF-α levels in the A/J strain, although levels were lower in comparison to GMA-SS.</p>", "<title>Lung oxidative stress</title>", "<p>No increased gene expression was found for prostaglandin-endoperoxide synthase 2 (COX-2), nitric oxide synthase 2 (iNOS or NOS2), or glutathione-<italic>S</italic>-transferase Pi (GST-Pi) at the 2 day time point for either mouse strain exposed to MMA-SS fume (data not shown). S-Cr samples were not analyzed because no strain differences were found by other parameters in this study. At 28 days, GMA or MMA-SS fumes did not cause increased expression of GST-Pi or COX-2 genes in the A/J (data not shown). Gene expression in the C57BL/6J was not analyzed at 28 days as the lung response of this strain had resolved by this time point (data not shown).</p>", "<title>Effects on body weight and survival 48 and 78 weeks after welding fume exposure</title>", "<p>Fluctuations in body weight (± 1–2 g) occurred in all groups, but no effects on final body weight were observed due to welding fume exposure (data not shown). At the 48 and 78 week sacrifices, respectively, mice had gained an average (± SE) of 7.3 ± 0.63 g and 7.6 ± 0.20 g over the course of the study.</p>", "<p>Survival was not different between any welding fume-exposed group and shams at either time point. At 48 weeks post-exposure, survival was &gt; 91% for all groups. At 78 weeks, survival was 80% for the sham, GMA-MS and MMA-SS groups, and 73% for the GMA-SS group.</p>", "<title>Urethane positive control findings</title>", "<p>Urethane exposed A/J mice had an average lung tumor multiplicity of 17.2 ± 0.97 (tumors/lung, n = 24) and 100% (24/24) incidence at 48 weeks. The survival rate was 96% at 48 weeks post-exposure. Due to the observed carcinogenic potency of urethane the 78 week group was sacrificed at 54 weeks. Survival had decreased to 85% by this time point post-exposure. Tumor multiplicity and incidence was 15.41 ± 1.64 (tumors/lung, n = 17) and 94% (16/17 mice), respectively.</p>", "<title>Gross tumor findings in A/J mice 48 and 78 weeks after welding fume exposure</title>", "<p>At 48 weeks post-exposure, lung tumor multiplicity and incidence was greatest in the GMA-SS-exposed group (0.45 ± 0.14 and 40%, respectively) (Table ##TAB##2##3##). However, at this time point, statistical significance was not achieved. Shams had a 33% tumor incidence and a 0.38 ± 0.13 multiplicity upon gross exam. Increases in lung tumor incidence or multiplicity following exposure to GMA-MS or MMA-SS welding fumes were unremarkable. Average tumor size was ≤ 2 mm for all groups at 48 weeks.</p>", "<p>At 78 weeks, exposure to both SS welding fumes increased tumor multiplicity and incidence compared to sham and the GMA-MS fume, but this increase did not reach statistical significance (Table ##TAB##2##3##). However, gross tumor incidence between the GMA-SS and sham groups was 81% and 53%, respectively, and approached significance (p = 0.057). The tumor multiplicity in the GMA-SS was greater in comparison to all groups and was 1.75 ± 0.32 versus 1.00 ± 0.35 in the sham. No significant differences in tumor multiplicity or incidence were found for the MMA-SS or GMA-MS-exposed groups versus sham control. Average tumor size varied between 2.4–3.5 mm at 78 weeks, and was not different among exposure groups.</p>", "<title>Lung histopathological findings in A/J mice 48 and 78 weeks after welding fume exposure</title>", "<p>In addition to the gross tumor evaluation at necropsy, histopathological analysis was done on separately embedded lung lobes from all mice in the study to evaluate morphological changes (Table ##TAB##3##4##). At 48 weeks post-exposure, all lung lesions observed were either adenomas or preneoplastic epithelial proliferations (Figure ##FIG##3##4A## &amp;##FIG##3##4B##). The GMA-SS group had the greatest increase in preneoplasia/tumor multiplicity and incidence (0.75 ± 0.15 and 65%). This was significantly different compared to the GMA-MS group (33%), but not sham (50%). Significance for incidence between the MMA-SS versus GMA-SS groups was borderline (p = 0.06). A significant increase in welding fume-containing macrophages was found in all exposed groups. GMA-SS welding fume was consistently found, in moderate amounts (3.03 ± 0.13), in all five lung lobes of all 20 mice evaluated whereas MMA-SS and GMA-MS fumes were variable and minimal in the lung, 0.67 ± 0.13 and 0.34 ± 0.10, respectively (Figure ##FIG##3##4C##). The presence of perivascular/peribronchial lymphoid infiltrates in the lung was not a significant finding at 48 weeks post-exposure to welding fume.</p>", "<p>By 78 weeks, tumor/preneoplastic lesions were observed in lungs of all groups and primarily were preneoplastic epithelial proliferations, adenomas, and adenomas arising within proliferations (Table ##TAB##3##4##). Carcinomas arising in an adenoma, carcinomas, and microcarcinomas were also observed but were less common. Again, multiplicity and incidence was greatest in the GMA-SS group, 1.94 ± 0.38 and 88%, respectively. This was not statistically different compared to multiplicity and incidence in the shams, 1.47 ± 0.33 and 68%, respectively. There was no association noted between the presence of any welding fume and preneoplastic or neoplastic lesions in the lung at 78 weeks after exposure.</p>", "<p>The GMA-SS group also exhibited a significant increase in perivascular/peribronchial associated lymphoid infiltrates – composed of lymphocytes, macrophages, and plasma cells – at 78 weeks post-exposure (Figure ##FIG##3##4D##). These lung infiltrates, however, were not necessarily associated with the presence of GMA-SS fume particles in the lung. GMA-SS welding fume was present in most lung lobes of all the mice in that group and in twice the amount, as shown by the increased presence of welding fume-laden cells, compared to the other fumes. The GMA-MS and MMA-SS fumes were rarely observed in the lung at 78 weeks post-exposure.</p>" ]

[ "<title>Discussion and conclusion</title>", "<p>This study compared the lung response in lung tumor susceptible (A/J) and resistant (C57BL/6J) mice exposed to GMA-MS, GMA-SS, MMA-SS, and S-Cr and found notable strain-dependent differences with regards to the degree and resolution of the inflammatory response. We also found supportive, but not conclusive, evidence for a possible tumorigenic effect of GMA-SS welding fume in the lung tumor susceptible A/J mouse. The results of this study, however, did not suggest a tumorigenic effect of MMA-SS or GMA-MS welding fumes. To our knowledge, this is the first <italic>in vivo </italic>animal study to provide preliminary evidence for a possible association between welding fume exposure and lung tumorigenesis.</p>", "<p>The A/J mouse model was chosen based on its similarities with human lung adenocarcinoma development-specifically, the anatomy, histogenesis, and molecular features [##REF##9659582##12##]. For example, the pulmonary adenoma susceptibility (<italic>Pas1</italic>) locus, a major mouse lung tumor susceptibility locus first mapped in A/J mice, appears to have a human counterpart which also conveys susceptibility to the development of human lung adenocarcinoma [##REF##11016621##14##,##REF##9364000##15##]. These data suggest that findings in the welding fume-exposed A/J mouse lung tumor model may have direct relevance to humans. In addition, although welding fume-induced lung toxicity has been investigated using other rodent models, the direct comparison of a lung tumor susceptible versus resistant mouse strain will help to elucidate a relationship between lung inflammation and possible welding fume-induced tumorigenesis.</p>", "<p>Stainless steel electrodes used during MMA or GMA welding generate fumes containing carcinogenic Cr and Ni. A major difference between the MMA- and GMA-generated fumes is the solubility and, therefore, possibly the bioavailability of the metals contained in the fumes. Indeed, regardless of fume generation, stainless steel fumes reportedly are toxic and mutagenic to mammalian cells [##REF##339336##16##,##REF##342941##17##], cause DNA strand breaks <italic>in vitro </italic>and increased apoptosis <italic>in vivo </italic>[##REF##16283511##18##], and induce lung cell hyperplasia and atypia in mice [##REF##16844664##19##]. Furthermore, previous data showed the soluble fraction of MMA-SS, which is abundant in Cr, generated free radicals and caused significant lung macrophage toxicity [##REF##10580758##9##,##REF##12832661##20##]. Therefore, S-Cr was used to investigate the acute lung toxicity of this metal, which has been implicated as the main reactive component of MMA-SS fume [##REF##6896394##10##].</p>", "<p>In the C57BL6/J strain, S-Cr appeared to be the main pneumotoxic component as the markers of lung injury and inflammation were not markedly different when compared to exposure to MMA-SS fume at all time points post-exposure. Conversely, the A/J exhibited a greater lung response to MMA-SS, which suggests other fume components such as the insoluble Ni, Mn, and Fe, in addition to S-Cr, exert toxic lung effects. Because chromium, in its hexavalent form, rapidly penetrates lung cells and is detoxified as it travels through the body [##REF##10753182##21##,##REF##9067553##22##], it is possible that an earlier time post-exposure may have revealed a response similar to the C57BL/6J in the A/J strain. In rats, previous time course data showed lung cytotoxicity and damage caused by intratracheal exposure to the insoluble or soluble fraction, or the total MMA-SS fume were similar at 3 hours and 1 day, but by 3 days the total fume caused additive effects in the lung compared to the separate fractions [##REF##12832661##20##]. This divergent response in the rat appears to resemble that of the A/J, but not the C57BL/6J, in this study. Taken together, these data suggest that interactions between the fume fractions are an important feature of MMA-SS lung toxicity, at least in Sprague-Dawley rats and A/J mice.</p>", "<p>Repeated exposure to the insoluble GMA-MS fume revealed a strain-dependent neutrophil influx (A/J &gt; C57BL/6J) that persisted through 28 days. It appears the insoluble components in welding fume – predominantly Fe and Mn – may impact recruitment of lung PMN in A/J mice, a phenomenon also observed in rats [##REF##12832661##20##]. GMA-MS exposure also caused slightly greater cytotoxicity in the A/J, apparent only at 7 days, but no lung damage in either strain. In agreement, intratracheal instillation of MS welding fume in rats, at a single bolus dose of 8 mg/kg, was associated with the least lung toxicity when compared to GMA-SS and MMA-SS fumes [##REF##12832661##20##]. The magnitude of the lung response to GMA-SS fume in the A/J was, overall, also greater compared to the C57BL/6J strain. In contrast to the GMA-MS fume, significant lung cell death and epithelial damage were observed in both strains, but the lung effects of the GMA-SS fume were greater, and the recovery period longer, in the A/J strain. This suggests the GMA-SS fume may cause a more chronic lung response likely related to its increased persistence compared to the GMA-MS [##REF##8806885##23##] and the possible sensitivity of the A/J strain to the insoluble Cr and Ni metal components of this fume.</p>", "<p>For further confirmation of the BAL findings, key cytokines, reportedly involved in welding fume-induced lung inflammation, were evaluated [##REF##12832661##20##]. The cytokine response profiles, both gene expression and protein measurements, mirrored the BAL profiles and revealed that the lung response to aspirated MMA-SS and S-Cr involved the pro-inflammatory cytokines IL-6, MCP-1, and TNF-α in both strains. Similarly, IL-6, MCP-1, and TNF-α were common between the strains after GMA-SS fume exposure and the response profiles also reflected that of the BAL. Again, GMA-SS exposure appeared to cause a prolonged effect in the A/J, evidenced by the persistent MCP-1 levels, which may indicate an ongoing macrophage migration to the lung. GMA-MS fume selectively increased lung TNF-α levels in the A/J mice only, further suggesting that, in comparison to the other welding fumes, it is associated with less lung activation. Of interest was the differential induction of IFN-γ, a potent macrophage-activating T helper 1 (Th1) cytokine. This cytokine was solely induced by the SS fumes and only in the A/J strain. No measurable IFN-γ protein was detected in the MMA-SS-exposed C57BL/6J but a modest increase in gene expression was detected. IFN-γ is produced exclusively by Th1 CD4 and CD8 cytotoxic T lymphocyte (CTL) effector cells and natural killer (NK) cells. Its antiproliferative, antitumor, and immunomodulatory properties have been extensively reviewed [##REF##17504213##24##]. The relevance of our finding that IFN-γ is selectively increased following SS welding fume exposure – primarily in the A/J – is unclear. However, it may suggest a role for cytotoxic T cells and NK cells in the immune response to SS welding fume in the A/J.</p>", "<p>The recovery of the A/J lung response to welding fume, assessed via BAL, was attenuated when compared to the C57BL/6J strain. In fact, at 78 weeks after exposure, histopathology of the A/J lung showed that GMA-SS welding fume continued to exert significant, but mild, inflammatory lung effects, i.e. lung lymphoid infiltrates, which may be correlated with its increased biopersistence compared to the other fumes. In regards to tumorigenic effects, the insoluble Cr and Ni components of this fume may be of even greater importance given that the insoluble, iron-abundant, GMA-MS and soluble chromium-containing MMA-SS fume showed no consistent trends for incidence or multiplicity in this mouse model. In fact, negative or weak effects of soluble chromium on <italic>in vivo </italic>tumorigenicity has been reported which seems to be consistent with our preliminary results [##REF##10753182##21##,##REF##3792485##25##]. Further study is necessary to completely understand the importance of our current observations, but support exists for a relationship between genetic susceptibility to lung tumorigenesis and inflammation. To date, the mechanism(s) remain unknown by which <italic>Pas1 </italic>confers lung tumor susceptibility. Anti-inflammatory drugs have been shown to inhibit tumorigenesis in A/J mice, which suggests inflammation and tumorigenesis may be linked [##REF##11497255##26##]. Our long term preliminary findings which showed gross tumor incidence, but not multiplicity, to be nearly significant (p = 0.057), when considered in conjunction with the BAL results and histopathology, suggest that a chronic lung response to GMA-SS welding fume may enhance tumorigenesis in the A/J model. Certainly, more animal studies are needed to clearly define if welding fume causes lung tumorigenesis and which metal constituents, or combination thereof, play a greater role.</p>", "<p>It is reported that A/J mice begin to develop spontaneous pulmonary tumors at 12–16 weeks of age [##REF##15059877##27##]. Grossly observed background tumor frequency, as reported in the literature, can range from 31–40% between 43–53 weeks of age and increase to 65% by approximately 66 weeks [##REF##14744662##28##, ####REF##9134020##29##, ##REF##15159525##30####15159525##30##]. Microscopically, adenomas and proliferations are the most commonly observed pathologies of both spontaneous and chemically-induced lung lesions in the A/J mouse [##REF##1771369##31##]. Our preliminary results regarding tumor frequency and pathology are largely in agreement with those stated in the literature. We observed that the majority of the lung lesions in the sham and exposed groups were preneoplastic epithelial proliferations, adenomas, and/or adenomas arising within proliferations. In humans, lung cancers are more histologically diverse compared to the mouse, and adenocarcinomas are the more common diagnosis [##REF##10218505##32##]. In A/J mice, the production of lung adenomas in is in fact relevant to the production of lung adenocarcinomas in humans as it appears that lung adenomas are the direct precursor to lung adenocarcinomas. Furthermore, in most cases, human and A/J mouse lung tumors both originate from atypical hyperplastic foci in the lung periphery [##REF##1591728##33##, ####REF##11667981##34##, ##REF##8616876##35##, ##REF##2050022##36####2050022##36##]. Our observed background tumor frequency was 33% at 55 weeks of age and 50% at 85 weeks upon gross exam. Although this model is useful in many respects, the spontaneous tumor rate in the A/J model is an obvious limitation and, when combined with the observed mortality in this study, reduced our statistical power for detecting differences to only 50%. However, the tendency for the GMA-SS group to consistently have the greatest lung tumor incidence and multiplicity – both histopathologically and grossly observed – is difficult to ignore. Although this fume does not appear to be an exceedingly potent carcinogen at our cumulative exposure dose of 340 μg, which is representative of an approximately 196 day exposure in a 75 kg human, further investigation is indeed warranted. Currently, inhalation studies are ongoing using our recently developed automated robotic welder [##REF##16531292##37##] with significantly larger group sizes to better control for the background incidence and to confirm our preliminary results with the GMA-SS fume.</p>", "<p>Welding generates a complex mixture of particles and gaseous by-products; thus, it is not remarkable that notable differences are observed between the lung response following instillation of the fume and inhalation [##REF##17706736##38##]. In fact, it is shown that freshly generated SS welding fumes are more biologically reactive compared to \"aged\" fumes, such as those used in this study [##REF##9776564##39##]. This decreased reactivity may explain why there was no increased gene expression for the selected markers of oxidative stress in this study. Inhalation also more adequately mimics an occupational exposure, and daily exposures in the automated welder will allow for a greater and more gradual accumulation of fume in the mouse lung. Such an exposure is difficult to achieve with pharyngeal aspiration as repeated exposures are labor intensive in a study with such large group sizes. Therefore, it is apparent that the ongoing inhalation studies may offer more insight into the toxicity and tumorigenicity of welding fumes.</p>" ]

[ "<title>Discussion and conclusion</title>", "<p>This study compared the lung response in lung tumor susceptible (A/J) and resistant (C57BL/6J) mice exposed to GMA-MS, GMA-SS, MMA-SS, and S-Cr and found notable strain-dependent differences with regards to the degree and resolution of the inflammatory response. We also found supportive, but not conclusive, evidence for a possible tumorigenic effect of GMA-SS welding fume in the lung tumor susceptible A/J mouse. The results of this study, however, did not suggest a tumorigenic effect of MMA-SS or GMA-MS welding fumes. To our knowledge, this is the first <italic>in vivo </italic>animal study to provide preliminary evidence for a possible association between welding fume exposure and lung tumorigenesis.</p>", "<p>The A/J mouse model was chosen based on its similarities with human lung adenocarcinoma development-specifically, the anatomy, histogenesis, and molecular features [##REF##9659582##12##]. For example, the pulmonary adenoma susceptibility (<italic>Pas1</italic>) locus, a major mouse lung tumor susceptibility locus first mapped in A/J mice, appears to have a human counterpart which also conveys susceptibility to the development of human lung adenocarcinoma [##REF##11016621##14##,##REF##9364000##15##]. These data suggest that findings in the welding fume-exposed A/J mouse lung tumor model may have direct relevance to humans. In addition, although welding fume-induced lung toxicity has been investigated using other rodent models, the direct comparison of a lung tumor susceptible versus resistant mouse strain will help to elucidate a relationship between lung inflammation and possible welding fume-induced tumorigenesis.</p>", "<p>Stainless steel electrodes used during MMA or GMA welding generate fumes containing carcinogenic Cr and Ni. A major difference between the MMA- and GMA-generated fumes is the solubility and, therefore, possibly the bioavailability of the metals contained in the fumes. Indeed, regardless of fume generation, stainless steel fumes reportedly are toxic and mutagenic to mammalian cells [##REF##339336##16##,##REF##342941##17##], cause DNA strand breaks <italic>in vitro </italic>and increased apoptosis <italic>in vivo </italic>[##REF##16283511##18##], and induce lung cell hyperplasia and atypia in mice [##REF##16844664##19##]. Furthermore, previous data showed the soluble fraction of MMA-SS, which is abundant in Cr, generated free radicals and caused significant lung macrophage toxicity [##REF##10580758##9##,##REF##12832661##20##]. Therefore, S-Cr was used to investigate the acute lung toxicity of this metal, which has been implicated as the main reactive component of MMA-SS fume [##REF##6896394##10##].</p>", "<p>In the C57BL6/J strain, S-Cr appeared to be the main pneumotoxic component as the markers of lung injury and inflammation were not markedly different when compared to exposure to MMA-SS fume at all time points post-exposure. Conversely, the A/J exhibited a greater lung response to MMA-SS, which suggests other fume components such as the insoluble Ni, Mn, and Fe, in addition to S-Cr, exert toxic lung effects. Because chromium, in its hexavalent form, rapidly penetrates lung cells and is detoxified as it travels through the body [##REF##10753182##21##,##REF##9067553##22##], it is possible that an earlier time post-exposure may have revealed a response similar to the C57BL/6J in the A/J strain. In rats, previous time course data showed lung cytotoxicity and damage caused by intratracheal exposure to the insoluble or soluble fraction, or the total MMA-SS fume were similar at 3 hours and 1 day, but by 3 days the total fume caused additive effects in the lung compared to the separate fractions [##REF##12832661##20##]. This divergent response in the rat appears to resemble that of the A/J, but not the C57BL/6J, in this study. Taken together, these data suggest that interactions between the fume fractions are an important feature of MMA-SS lung toxicity, at least in Sprague-Dawley rats and A/J mice.</p>", "<p>Repeated exposure to the insoluble GMA-MS fume revealed a strain-dependent neutrophil influx (A/J &gt; C57BL/6J) that persisted through 28 days. It appears the insoluble components in welding fume – predominantly Fe and Mn – may impact recruitment of lung PMN in A/J mice, a phenomenon also observed in rats [##REF##12832661##20##]. GMA-MS exposure also caused slightly greater cytotoxicity in the A/J, apparent only at 7 days, but no lung damage in either strain. In agreement, intratracheal instillation of MS welding fume in rats, at a single bolus dose of 8 mg/kg, was associated with the least lung toxicity when compared to GMA-SS and MMA-SS fumes [##REF##12832661##20##]. The magnitude of the lung response to GMA-SS fume in the A/J was, overall, also greater compared to the C57BL/6J strain. In contrast to the GMA-MS fume, significant lung cell death and epithelial damage were observed in both strains, but the lung effects of the GMA-SS fume were greater, and the recovery period longer, in the A/J strain. This suggests the GMA-SS fume may cause a more chronic lung response likely related to its increased persistence compared to the GMA-MS [##REF##8806885##23##] and the possible sensitivity of the A/J strain to the insoluble Cr and Ni metal components of this fume.</p>", "<p>For further confirmation of the BAL findings, key cytokines, reportedly involved in welding fume-induced lung inflammation, were evaluated [##REF##12832661##20##]. The cytokine response profiles, both gene expression and protein measurements, mirrored the BAL profiles and revealed that the lung response to aspirated MMA-SS and S-Cr involved the pro-inflammatory cytokines IL-6, MCP-1, and TNF-α in both strains. Similarly, IL-6, MCP-1, and TNF-α were common between the strains after GMA-SS fume exposure and the response profiles also reflected that of the BAL. Again, GMA-SS exposure appeared to cause a prolonged effect in the A/J, evidenced by the persistent MCP-1 levels, which may indicate an ongoing macrophage migration to the lung. GMA-MS fume selectively increased lung TNF-α levels in the A/J mice only, further suggesting that, in comparison to the other welding fumes, it is associated with less lung activation. Of interest was the differential induction of IFN-γ, a potent macrophage-activating T helper 1 (Th1) cytokine. This cytokine was solely induced by the SS fumes and only in the A/J strain. No measurable IFN-γ protein was detected in the MMA-SS-exposed C57BL/6J but a modest increase in gene expression was detected. IFN-γ is produced exclusively by Th1 CD4 and CD8 cytotoxic T lymphocyte (CTL) effector cells and natural killer (NK) cells. Its antiproliferative, antitumor, and immunomodulatory properties have been extensively reviewed [##REF##17504213##24##]. The relevance of our finding that IFN-γ is selectively increased following SS welding fume exposure – primarily in the A/J – is unclear. However, it may suggest a role for cytotoxic T cells and NK cells in the immune response to SS welding fume in the A/J.</p>", "<p>The recovery of the A/J lung response to welding fume, assessed via BAL, was attenuated when compared to the C57BL/6J strain. In fact, at 78 weeks after exposure, histopathology of the A/J lung showed that GMA-SS welding fume continued to exert significant, but mild, inflammatory lung effects, i.e. lung lymphoid infiltrates, which may be correlated with its increased biopersistence compared to the other fumes. In regards to tumorigenic effects, the insoluble Cr and Ni components of this fume may be of even greater importance given that the insoluble, iron-abundant, GMA-MS and soluble chromium-containing MMA-SS fume showed no consistent trends for incidence or multiplicity in this mouse model. In fact, negative or weak effects of soluble chromium on <italic>in vivo </italic>tumorigenicity has been reported which seems to be consistent with our preliminary results [##REF##10753182##21##,##REF##3792485##25##]. Further study is necessary to completely understand the importance of our current observations, but support exists for a relationship between genetic susceptibility to lung tumorigenesis and inflammation. To date, the mechanism(s) remain unknown by which <italic>Pas1 </italic>confers lung tumor susceptibility. Anti-inflammatory drugs have been shown to inhibit tumorigenesis in A/J mice, which suggests inflammation and tumorigenesis may be linked [##REF##11497255##26##]. Our long term preliminary findings which showed gross tumor incidence, but not multiplicity, to be nearly significant (p = 0.057), when considered in conjunction with the BAL results and histopathology, suggest that a chronic lung response to GMA-SS welding fume may enhance tumorigenesis in the A/J model. Certainly, more animal studies are needed to clearly define if welding fume causes lung tumorigenesis and which metal constituents, or combination thereof, play a greater role.</p>", "<p>It is reported that A/J mice begin to develop spontaneous pulmonary tumors at 12–16 weeks of age [##REF##15059877##27##]. Grossly observed background tumor frequency, as reported in the literature, can range from 31–40% between 43–53 weeks of age and increase to 65% by approximately 66 weeks [##REF##14744662##28##, ####REF##9134020##29##, ##REF##15159525##30####15159525##30##]. Microscopically, adenomas and proliferations are the most commonly observed pathologies of both spontaneous and chemically-induced lung lesions in the A/J mouse [##REF##1771369##31##]. Our preliminary results regarding tumor frequency and pathology are largely in agreement with those stated in the literature. We observed that the majority of the lung lesions in the sham and exposed groups were preneoplastic epithelial proliferations, adenomas, and/or adenomas arising within proliferations. In humans, lung cancers are more histologically diverse compared to the mouse, and adenocarcinomas are the more common diagnosis [##REF##10218505##32##]. In A/J mice, the production of lung adenomas in is in fact relevant to the production of lung adenocarcinomas in humans as it appears that lung adenomas are the direct precursor to lung adenocarcinomas. Furthermore, in most cases, human and A/J mouse lung tumors both originate from atypical hyperplastic foci in the lung periphery [##REF##1591728##33##, ####REF##11667981##34##, ##REF##8616876##35##, ##REF##2050022##36####2050022##36##]. Our observed background tumor frequency was 33% at 55 weeks of age and 50% at 85 weeks upon gross exam. Although this model is useful in many respects, the spontaneous tumor rate in the A/J model is an obvious limitation and, when combined with the observed mortality in this study, reduced our statistical power for detecting differences to only 50%. However, the tendency for the GMA-SS group to consistently have the greatest lung tumor incidence and multiplicity – both histopathologically and grossly observed – is difficult to ignore. Although this fume does not appear to be an exceedingly potent carcinogen at our cumulative exposure dose of 340 μg, which is representative of an approximately 196 day exposure in a 75 kg human, further investigation is indeed warranted. Currently, inhalation studies are ongoing using our recently developed automated robotic welder [##REF##16531292##37##] with significantly larger group sizes to better control for the background incidence and to confirm our preliminary results with the GMA-SS fume.</p>", "<p>Welding generates a complex mixture of particles and gaseous by-products; thus, it is not remarkable that notable differences are observed between the lung response following instillation of the fume and inhalation [##REF##17706736##38##]. In fact, it is shown that freshly generated SS welding fumes are more biologically reactive compared to \"aged\" fumes, such as those used in this study [##REF##9776564##39##]. This decreased reactivity may explain why there was no increased gene expression for the selected markers of oxidative stress in this study. Inhalation also more adequately mimics an occupational exposure, and daily exposures in the automated welder will allow for a greater and more gradual accumulation of fume in the mouse lung. Such an exposure is difficult to achieve with pharyngeal aspiration as repeated exposures are labor intensive in a study with such large group sizes. Therefore, it is apparent that the ongoing inhalation studies may offer more insight into the toxicity and tumorigenicity of welding fumes.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Welding fume has been categorized as \"possibly carcinogenic\" to humans. Our objectives were to characterize the lung response to carcinogenic and non-carcinogenic metal-containing welding fumes and to determine if these fumes caused increased lung tumorigenicity in A/J mice, a lung tumor susceptible strain. We exposed male A/J and C57BL/6J, a lung tumor resistant strain, by pharyngeal aspiration four times (once every 3 days) to 85 μg of gas metal arc-mild steel (GMA-MS), GMA-stainless steel (SS), or manual metal arc-SS (MMA-SS) fume, or to 25.5 μg soluble hexavalent chromium (S-Cr). Shams were exposed to saline vehicle. Bronchoalveolar lavage (BAL) was done at 2, 7, and 28 days post-exposure. For the lung tumor study, gross tumor counts and histopathological changes were assessed in A/J mice at 48 and 78 weeks post-exposure.</p>", "<title>Results</title>", "<p>BAL revealed notable strain-dependent differences with regards to the degree and resolution of the inflammatory response after exposure to the fumes. At 48 weeks, carcinogenic metal-containing GMA-SS fume caused the greatest increase in tumor multiplicity and incidence, but this was not different from sham. By 78 weeks, tumor incidence in the GMA-SS group versus sham approached significance (p = 0.057). A significant increase in perivascular/peribronchial lymphoid infiltrates for the GMA-SS group versus sham and an increased persistence of this fume in lung cells compared to the other welding fumes was found.</p>", "<title>Conclusion</title>", "<p>The increased persistence of GMA-SS fume in combination with its metal composition may trigger a chronic, but mild, inflammatory state in the lung possibly enhancing tumorigenesis in this susceptible mouse strain.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>PCZE performed the animal exposures, bronchoalveolar lavage, isolated RNA, and drafted the manuscript. MLK conducted the statistical analyses. LAB counted the mouse lung tumors and assisted with the lung preparation for histopathology. SHY performed the CBA assays. AE performed the RT-PCR experiments. JRR participated in the 48 and 78 week study sacrifices. SHR, JMA, and PCZE conceived and designed the study. All authors read and approved the final manuscript.</p>", "<title>Disclaimer</title>", "<p>The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors thank senior staff pathologist, Dr. Meredith A. Simon (Charles River Laboratories) for the interpretation of the histopathology slides. We appreciate Dean Newcomer and Sherri Friend for their excellent technical assistance with the pathology preparation and staining of the slides. We also thank Dr. Victor Johnson (National Institute for Occupational Safety and Health) for his critique of this manuscript.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Effect of S-Cr or MMA-SS welding fume on lavage protein levels and whole lung gene expression of IFN-γ (A&amp;B) and IL-6 (C&amp;D) at 2 days post-exposure in A/J and C57BL/6J mice.</bold> The dotted line represents the assay sensitivity for each protein and mean lines (–) are shown for each group. Gene expression data are presented as fold change from sham controls (dotted line). Values are mean ± SE (n = 4–7 per group). *-Significantly different from corresponding sham. #-Significantly different between strains of the same exposure group <italic>Note: Portions of this figure have been previously published </italic>[##REF##18089291##42##].</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Effect of S-Cr or MMA-SS welding fume on lavage protein levels and whole lung gene expression of MCP-1 (A&amp;B) and TNF-α (C&amp;D) at 2 days post-exposure in A/J and C57BL/6J mice.</bold> The dotted line represents the assay sensitivity for each protein and mean lines (–) are shown for each group. Gene expression data are presented as fold change from sham controls (dotted line). Values are mean ± SE (n = 4–7 per group). *-Significantly different from corresponding sham. <italic>Note: Portions of this figure have been previously published </italic>[##REF##18089291##42##].</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Effect of GMA welding fumes on lavage protein levels of MCP-1 (A&amp;B) and TNF-α (C&amp;D) at 2 and 28 days post-exposure in A/J and C57BL/6J mice.</bold> The dotted line represents the assay sensitivity for each inflammatory protein and mean lines (–) are shown for each group (n = 5–7).</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Photomicrographs of lung tissue from welding fume-exposed A/J mice.</bold> Preneoplastic lesions (panel A) and adenomas (panel B) were the most common lung lesions observed in all exposed and sham groups. These representative low magnification photomicrographs were captured at 48 weeks post-exposure to GMA-SS fume. Panel C is a high magnification photomicrograph showing the presence of GMA-SS fume (brown-black granular pigmented areas) at 48 weeks post-exposure. An increased persistence in the lung was observed for GMA-SS fume compared to the GMA-MS or MMA-SS fume. At 78 weeks post-exposure, the presence of GMA-SS fume is still observed in the lung and an increased lymphohistiocytic infiltrate was associated with this fume (panel D).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Bronchoalveolar lavage parameters 2 days post-exposure</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Mouse Strain</td><td align=\"center\"><italic>n</italic></td><td align=\"center\">Exposure</td><td align=\"center\">%Albumin^§</td><td align=\"center\">%LDH^§</td><td align=\"center\">%Lymphocytes^||</td><td align=\"center\">%PMN^||</td></tr></thead><tbody><tr><td align=\"center\">A/J</td><td align=\"center\">7</td><td align=\"center\">GMA-MS</td><td align=\"center\">126 ± 4</td><td align=\"center\">155 ± 7*</td><td align=\"center\">0.8 ± 0.4 (0.2 ± 0.13)</td><td align=\"center\">24 ± 3*^‡(1.1 ± 1.1)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">GMA-MS</td><td align=\"center\">109 ± 3</td><td align=\"center\">134 ± 10*</td><td align=\"center\">1.3 ± 0.8 (0.3 ± 0.1)</td><td align=\"center\">12 ± 3* (0.05 ± 0.05)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">A/J</td><td align=\"center\">7</td><td align=\"center\">GMA-SS</td><td align=\"center\">229 ± 13*^†‡</td><td align=\"center\">307 ± 12*^†‡</td><td align=\"center\">2.2 ± 0.8*^†(0.2 ± 0.13)</td><td align=\"center\">44 ± 3*^†‡(1.1 ± 1.1)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">6</td><td align=\"center\">GMA-SS</td><td align=\"center\">139 ± 13*^†</td><td align=\"center\">176 ± 16*</td><td align=\"center\">2.1 ± 0.2* (0.3 ± 0.1)</td><td align=\"center\">9 ± 2* (0.05 ± 0.05)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">A/J</td><td align=\"center\">7</td><td align=\"center\">MMA-SS</td><td align=\"center\">331 ± 26*^†‡</td><td align=\"center\">343 ± 33*^†‡</td><td align=\"center\">0.1 ± 0.06 (0.06 ± 0.06)</td><td align=\"center\">41 ± 4*^†‡(0.7 ± 0.6)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">MMA-SS</td><td align=\"center\">218 ± 16*</td><td align=\"center\">230 ± 25*</td><td align=\"center\">1.6 ± 0.24*^‡(0 ± 0)</td><td align=\"center\">9 ± 2* (0.2 ± 0.08)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">A/J</td><td align=\"center\">7</td><td align=\"center\">S-Cr</td><td align=\"center\">209 ± 10*</td><td align=\"center\">178 ± 14*</td><td align=\"center\">0.5 ± 0.16*^†(0.06 ± 0.06)</td><td align=\"center\">11 ± 0.8* (0.7 ± 0.6)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">S-Cr</td><td align=\"center\">266 ± 25*^†‡</td><td align=\"center\">182 ± 20*</td><td align=\"center\">2 ± 0.6*^‡(0 ± 0)</td><td align=\"center\">9 ± 3* (0.2 ± 0.08)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Bronchoalveolar lavage parameters 7 days post-exposure</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Mouse Strain</td><td align=\"center\"><italic>n</italic></td><td align=\"center\">Exposure</td><td align=\"center\">%Albumin^§</td><td align=\"center\">%LDH^§</td><td align=\"center\">%Lymphocytes^||</td><td align=\"center\">%PMN^||</td></tr></thead><tbody><tr><td align=\"center\">A/J</td><td align=\"center\">7</td><td align=\"center\">GMA-MS</td><td align=\"center\">90 ± 3</td><td align=\"center\">156 ± 10*^‡</td><td align=\"center\">0.64 ± 0.16 (0 ± 0)</td><td align=\"center\">12 ± 1.2*^‡(0 ± 0)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">GMA-MS</td><td align=\"center\">105 ± 3</td><td align=\"center\">132 ± 3*</td><td align=\"center\">0.54 ± 0.13 (0.14 ± 0.07)</td><td align=\"center\">0.72 ± 0.3 (0.05 ± 0.05)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">A/J</td><td align=\"center\">6</td><td align=\"center\">GMA-SS</td><td align=\"center\">115 ± 6</td><td align=\"center\">216 ± 16* ^†‡</td><td align=\"center\">0.86 ± 0.18* (0 ± 0)</td><td align=\"center\">20 ± 1.2*^†‡(0 ± 0)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">GMA-SS</td><td align=\"center\">113 ± 4</td><td align=\"center\">148 ± 8*</td><td align=\"center\">0.8 ± 0.17 * (0.14 ± 0.07)</td><td align=\"center\">1.3 ± 0.8 (0.05 ± 0.05)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">A/J</td><td align=\"center\">7</td><td align=\"center\">MMA-SS</td><td align=\"center\">145 ± 11*</td><td align=\"center\">144 ± 17*</td><td align=\"center\">1.8 ± 0.5* (0.1 ± 0.06)</td><td align=\"center\">12 ± 1.0*^†‡(0.1 ± 0.1)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">MMA-SS</td><td align=\"center\">115 ± 8</td><td align=\"center\">130 ± 5*^†</td><td align=\"center\">1.0 ± 0.36* (0 ± 0)</td><td align=\"center\">1.6 ± 0.1*^†(0.07 ± 0.07)</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">A/J</td><td align=\"center\">5</td><td align=\"center\">S-Cr</td><td align=\"center\">137 ± 12*</td><td align=\"center\">111 ± 13</td><td align=\"center\">2.2 ± 0.46* (0.1 ± 0.06)</td><td align=\"center\">5.6 ± 0.6*^‡(0.1 ± 0.1)</td></tr><tr><td align=\"center\">C57BL/6J</td><td align=\"center\">7</td><td align=\"center\">S-Cr</td><td align=\"center\">124 ± 8*</td><td align=\"center\">111 ± 7</td><td align=\"center\">0.44 ± 0.23 (0 ± 0)</td><td align=\"center\">0.22 ± 0.2 (0.07 ± 0.07)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Gross lung tumor findings for A/J mice 48 and 78 weeks post-exposure</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Exposure</td><td align=\"center\" colspan=\"2\">Lung Tumor Multiplicity*</td><td align=\"center\" colspan=\"2\">Lung Tumor Incidence^†</td></tr></thead><tbody><tr><td/><td align=\"center\">48 wk</td><td align=\"center\">78 wk</td><td align=\"center\">48 wk</td><td align=\"center\">78 wk</td></tr><tr><td align=\"center\">Sham</td><td align=\"center\">0.38 ± 0.13 (21)</td><td align=\"center\">1.00 ± 0.35 (19)</td><td align=\"center\">33% (7/21)</td><td align=\"center\">53% (10/19)</td></tr><tr><td align=\"center\">GMA-MS<break/>Gas metal arc-mild steel</td><td align=\"center\">0.42 ± 0.14 (24)</td><td align=\"center\">1.00 ± 0.22 (20)</td><td align=\"center\">33% (8/24)</td><td align=\"center\">65% (13/20)</td></tr><tr><td align=\"center\">GMA-SS<break/>Gas metal arc-stainless steel</td><td align=\"center\">0.45 ± 0.14 (20)</td><td align=\"center\">1.75 ± 0.32 (16)</td><td align=\"center\">40% (8/20)</td><td align=\"center\">81% (13/16)</td></tr><tr><td align=\"center\">MMA-SS<break/>Manual metal arc-stainless steel</td><td align=\"center\">0.25 ± 0.11 (24)</td><td align=\"center\">1.55 ± 0.34 (20)</td><td align=\"center\">21% (5/24)</td><td align=\"center\">80% (16/20)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Lung histopathology for A/J mice 48 and 78 Weeks post-exposure</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Exposure</td><td align=\"center\">n</td><td align=\"center\">Lymphoid Infiltrates*</td><td align=\"center\">Welding Fume-Laden Cells</td><td align=\"center\">Lung Tumor Multiplicity^†</td><td align=\"center\">Lung Tumor Incidence^‡</td></tr></thead><tbody><tr><td align=\"center\">48 wk</td><td align=\"center\">Sham</td><td align=\"center\">21</td><td align=\"center\">1.08 ± 0.16</td><td align=\"center\">0 ± 0</td><td align=\"center\">0.55 ± 0.14</td><td align=\"center\">50%</td></tr><tr><td/><td align=\"center\">GMA-MS</td><td align=\"center\">24</td><td align=\"center\">0.30 ± 0.10</td><td align=\"center\">0.34 ± 0.10^§</td><td align=\"center\">0.38 ± 0.12</td><td align=\"center\">33%</td></tr><tr><td/><td align=\"center\">GMA-SS</td><td align=\"center\">20</td><td align=\"center\">1.23 ± 0.22</td><td align=\"center\">3.03 ± 0.13^§</td><td align=\"center\">0.75 ± 0.15</td><td align=\"center\"> 65%**</td></tr><tr><td/><td align=\"center\">MMA-SS</td><td align=\"center\">24</td><td align=\"center\">0.90 ± 0.16</td><td align=\"center\">0.67 ± 0.13^§</td><td align=\"center\">0.38 ± 0.12</td><td align=\"center\">33%</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">78 wk</td><td align=\"center\">Sham</td><td align=\"center\">19</td><td align=\"center\">1.53 ± 0.29</td><td align=\"center\">0 ± 0</td><td align=\"center\">1.47 ± 0.33</td><td align=\"center\">68%</td></tr><tr><td/><td align=\"center\">GMA-MS</td><td align=\"center\">20</td><td align=\"center\">0.78 ± 0.24</td><td align=\"center\">0.15 ± 0.07^§</td><td align=\"center\">1.40 ± 0.32</td><td align=\"center\">75%</td></tr><tr><td/><td align=\"center\">GMA-SS</td><td align=\"center\">16</td><td align=\"center\">2.53 ± 0.36^§</td><td align=\"center\">1.12 ± 0.17^§</td><td align=\"center\">1.94 ± 0.38</td><td align=\"center\">88%</td></tr><tr><td/><td align=\"center\">MMA-SS</td><td align=\"center\">20</td><td align=\"center\">1.70 ± 0.27</td><td align=\"center\">0.55 ± 0.19^§</td><td align=\"center\">1.85 ± 0.46</td><td align=\"center\">75%</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Welding fume characterization by ICP-AES*</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Welding Fume Sample</td><td align=\"center\">Metal (weight %)^†</td><td align=\"center\">Soluble/insoluble Ratio</td><td align=\"center\">pH</td></tr></thead><tbody><tr><td align=\"center\">GMA-MS<break/>Gas metal arc-mild steel</td><td align=\"center\">Fe 85<break/>Mn 14</td><td align=\"center\">0.020</td><td align=\"center\">Total 7.02<break/>Soluble 7.44<break/>Insoluble 7.03</td></tr><tr><td/><td/><td/><td/></tr><tr><td align=\"center\">GMA-SS<break/>Gas metal arc-stainless steel</td><td align=\"center\">Fe 53<break/>Mn 23<break/>Cr 19<break/>Ni 5</td><td align=\"center\">0.006</td><td align=\"center\">Total 6.94<break/>Soluble 6.97<break/>Insoluble 7.01<break/></td></tr><tr><td/><td/><td/><td/></tr><tr><td align=\"center\">MMA-SS<break/>Manual metal arc-stainless steel</td><td align=\"center\">Fe 41<break/>Cr 29<break/>Mn 17<break/>Ni 3</td><td align=\"center\">0.345<break/>Soluble metals:<break/>Cr 87%<break/>Mn 11%</td><td align=\"center\">Total 6.92<break/>Soluble 7.05<break/>Insoluble 7.09</td></tr></tbody></table></table-wrap>" ]

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[ "<table-wrap-foot><p>*Significantly different from corresponding sham; ^†Between exposed groups of the same mouse strain; ‡Between mouse strains of the same exposure group (p &lt; 0.05)</p><p>^§LDH and albumin data are represented as % corresponding sham.</p><p>^||Percentage from a differential cell count of &gt; 300 cells with the corresponding sham % in parentheses. <italic>Note</italic>. Data are means ± SE. Statistical comparisons were MMA-SS and S-Cr or GMA-MS and GMA-SS. Abbreviations are GMA-MS-gas metal arc-mild steel, GMA-SS-gas metal arc stainless steel, or MMA-SS-manual metal arc stainless steel welding fume; S-Cr-soluble chromium VI; LDH-lactate dehydrogenase; PMN-polymorphonuclear leukocytes</p></table-wrap-foot>", "<table-wrap-foot><p>*Significantly different from corresponding sham; ^†Between exposed groups of the same mouse strain; ^‡Between mouse strains of the same exposure group (p &lt; 0.05)</p><p>^§LDH and albumin data are represented as % corresponding sham. ^||Percentage from a differential cell count of &gt; 300 cells with the corresponding sham % in parentheses.</p><p><italic>Note</italic>. Data are means ± SE. Statistical comparisons were MMA-SS and S-Cr or GMA-MS and GMA-SS. Abbreviations are GMA-MS-gas metal arc-mild steel, GMA-SS-gas metal arc stainless steel, or MMA-SS-manual metal arc stainless steel welding fume; S-Cr-soluble chromium VI; LDH-lactate dehydrogenase; PMN-polymorphonuclear leukocytes</p></table-wrap-foot>", "<table-wrap-foot><p>*Average number of tumors per lung (± SE) and includes mice with no tumors. Parentheses indicate total animal number. †Percentage of tumor-bearing mice out of the total. Parentheses indicate tumor-bearing/total animal number.</p></table-wrap-foot>", "<table-wrap-foot><p>*Perivascular/peribronchial associated lymphocytes, macrophages, and plasma cells.</p><p>^†Average number of tumors/preneoplastic lesions per lung, includes mice with no lesions.</p><p>^‡Percentage of tumor/preneoplasia-bearing mice out of the total. ^§Significantly increased compared to sham (p &lt; 0.05). ^||Significantly increased compared to GMA-MS and MMA-SS welding fumes (p &lt; 0.05). **Significantly increased versus GMA-MS (p ≤ 0.05).</p><p><italic>Note</italic>: Abbreviations are GMA-MS-gas metal arc-mild steel, GMA-SS-gas metal arc stainless steel, or MMA-SS-manual metal arc stainless steel welding fume. Data are mean ± SE.</p></table-wrap-foot>", "<table-wrap-foot><p>*Inductively Coupled Argon Plasma Atomic Emission Spectroscopy. † Relative to all metals analyzed. <italic>Note</italic>. Abbreviations are Cr-chromium; Fe-iron; Mn-Manganese; Ni-nickel. Data presented are referenced from Antonini et al., 1999.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1743-8977-5-12-1\"/>", "<graphic xlink:href=\"1743-8977-5-12-2\"/>", "<graphic xlink:href=\"1743-8977-5-12-3\"/>", "<graphic xlink:href=\"1743-8977-5-12-4\"/>" ]

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[ "<title>Background</title>", "<p>In the August 18th, 2008, <italic>Wall Street Journal</italic>, George Anders wrote a column on the measures being taken by high technology companies in the United States to extend their researchers' age span of productivity. Anders cited an analysis performed by Benjamin Jones, a professor at Northwestern University's Kellogg School of Management, on innovative breakthroughs. Jones was reported to have examined the biographical data of more than 700 Nobel laureates and renowned researchers of the past century. One the conclusions reached by Jones was that \"innovators are productive over a narrowing span (of approximately 25 years) of their life cycle\" with researchers being most productive between the ages of just before 30 to 55, peaking at age 40. Reflecting the notion that innovative research often comes in early- to mid-career, <italic>Retrovirology </italic>seeks to recognize the work of a deserving retovirologist between the ages of 45 and 60 with the <italic>M. Jeang Retrovirology Prize </italic>[##REF##17875209##1##].</p>", "<p>Since its inception, the Retrovirology prize has been awarded three times, in 2005 to Stephen Goff [##REF##16000174##2##], in 2006 to Joseph Sodroski [##REF##16872546##3##], and in 2007 to Karen Beemon [##REF##18070339##4##]. The Prize consists of an attractive crystal trophy (Figure ##FIG##0##1##), a $3,000 cash award, and a profile article of the awardee published in <italic>Retrovirology</italic>. The <italic>Retrovirology </italic>Prize is supported, in part, through a donation from the Ming K. Jeang Foundation, an educational foundation based in Houston, Texas, USA.</p>" ]

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[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>A recent analysis suggested a narrow age range for productivity of innovative work by researchers. The <italic>Retrovirology </italic>Prize seeks to recognize the research of a mid-career retrovirologist between the ages of 45 and 60. The 2007 <italic>Retrovirology </italic>Prize was awarded to Dr. Karen Beemon. Nominations are being solicited for the 2008 prize.</p>" ]

[ "<title>Call for nominations and the selection process</title>", "<p>As stated previously [##REF##17875209##1##], the Prize alternates yearly between recognizing a non-HIV retrovirologist (2007 and odd years) and an HIV retrovirologist (2008 and even years). There can be some discretion on this guideline, exercised from time-to-time by the selection committee. Any individual can initiate a nomination of others or self-nominate. A nomination includes a statement (1000 words or less) of the nominee's significant contributions to retrovirus research, a curriculum vitae of the nominee, and a statement by the nominator that the nominee has agreed to be nominated. The selection committee consists of the Editors of <italic>Retrovirology </italic>(currently, M. Benkirane, B. Berkhout, M. Fujii, K.T. Jeang, M. Lairmore, A. Lever, and M. Wainberg). All nominations submitted to the selection committee must be communicated through an Editorial Board member of <italic>Retrovirology</italic>. Hence, an individuals who is not an Editorial board member but who wishes to make a nomination should seek out a <italic>Retrovirology </italic>Editorial board member to communicate his/her information to the selection committee. A list of current Editorial Board members can be found at the <italic>Retrovirology </italic>website <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.retrovirology.com\"/>. Within the stipulated age limits, all <italic>Retrovirology </italic>Editors and Editorial Board members are eligible to be nominated with the exception of the Editor-in-Chief who will administer the final selection.</p>", "<p>For 2008, nominations will be accepted beginning on September 15^thand will close on October 30^th. All members of the retrovirology community are encouraged to participate in this process for recognizing a deserving colleague.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>A photograph of the crystal trophy presented to Dr. Karen Beemon, winner of the 2007 M. Jeang <italic>Retrovirology </italic>Prize.</p></caption></fig>" ]

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[ "<title>Introduction</title>", "<p>HIV-1 integrase contains 288 amino acids encoded by the 3' end of the HIV-1 <italic>pol </italic>gene. It catalyzes the cleavage of the conserved 3' dinucleotide CA (3' processing) and the ligation of the viral 3'-OH ends to the 5'-DNA of host chromosomal DNA (strand transfer). Integrase also plays a role in stabilizing a pre-integration complex (PIC), which consists of the 3'-processed genome and one or more cellular co-factors involved in nuclear transfer of the PIC (reviewed in [##UREF##0##1##, ####REF##11346660##2##, ##REF##15134551##3##, ##REF##15729361##4####15729361##4##]).</p>", "<p>HIV-1 integrase is composed of three functional domains: the N-terminal domain (NTD), which encompasses amino acids 1–50 and contains a histidine-histidine-cysteine-cysteine (HHCC) motif that coordinates zinc binding, the catalytic core domain (CCD) which encompasses amino acids 51–212 and contains the catalytic triad D64, D116, and E152, known as the DDE motif, and the C-terminal domain (CTD), which encompasses amino acids 213–288 and is involved in host DNA binding.</p>", "<p>Crystal structures of the CCD plus CTD domains [##REF##10890912##5##] and the CCD plus NTD domains [##REF##11743009##6##] have been solved, but the relative conformation of the three domains and of the active multimeric form of the enzyme are not known. There is one published crystal structure of the CCD bound to an early prototype diketo acid inhibitor (5CITEP) [##REF##10557269##7##] but no structures of the CCD bound to one of the integrase inhibitors (INIs) in clinical use or to a DNA template. Because of the difficulties in obtaining structures of the most biologically relevant forms of the enzyme and of most integrase-INI structures, much of the functional roles of different integrase residues have been identified through biochemical and systematic amino acid replacement studies (reviewed in [##REF##18086413##8##]).</p>", "<p>One INI, raltegravir, has been licensed for the treatment of HIV-1 infection and a second INI, elvitegravir, is in advanced clinical trials. Mutations associated with resistance to these inhibitors have been identified through <italic>in vitro </italic>and <italic>in vivo </italic>selection studies (reviewed in [##REF##17668566##9##]) and through <italic>in vitro </italic>susceptibility testing. The purpose of this study is to supplement the structural and biochemical assessment of integrase function and INI resistance by summarizing naturally occurring variation in published sequences of group M integrase, particularly as this variation applies to positions associated with INI resistance.</p>" ]

[ "<title>Methods</title>", "<title>Sequence retrieval and annotation</title>", "<p>The HIV-1 subtype B consensus integrase amino acid published by the Los Alamos HIV Sequence Database was used to query the GenBank database V 165.0 (released on 2008-04-15) using the blastp program. Human and primate lentivirus virus sequences having an e-value of &lt; 0.04 and containing 200 or more homologous amino acids were aligned to the query sequence using a nucleotide to amino acid alignment program [##REF##9021268##10##]. Each sequence was annotated according to its primary publication, the host species from which it was obtained, the year, country, and biological source of its isolation, and the ARV drug class exposure of the individual from whom the sample was obtained. Each set of sequences from a publication was annotated according to whether the sequences were obtained from one or more than one individual in that publication. Sequences from the same individual were annotated according to whether they were obtained at the same or different times. Sequences were also characterized according to whether obtained directly from PCR-amplified material or from one or more separate clones. For the purposes of analysis, only one sequence per individual were used. For individual with multiple sequences, the first sequence was used. For integrase isolates for which multiple clones were sequenced, the consensus of the clones was used.</p>", "<p>Insertions, deletions, and mutations were defined as differences from the HIV-1 subtype B consensus amino acid sequence. The retrovirus species and the HIV-1 group of each sequence was defined according to the sequence annotation in GenBank and confirmed through phylogenetic analysis. HIV-1 group M subtype was assigned phylogenetically by including each group M sequence in a neighbor-joining tree containing 100 sequences that had previously been characterized by full genomic sequencing including sequences belonging to subtypes A, B, C, D, F, G, H, J, and K and to the circulating recombinant forms (CRFs) 01 to 19. This set of 100 sequences included the 65 subtype-specific reference sequences assembled by the Los Alamos HIV Sequence Database [##UREF##1##11##] supplemented by 35 sequences so that a minimum of three published sequences belonging to each subtype and CRF was included. The neighbor joining tree was created from a distance matrix computed using the HKY method with a gamma distribution calculated by PAUP 4.0. Sequences that formed a clade with reference sequences belonging to the same subtype were assigned to that subtype. Sequences that did not form a clade with references belonging to the same subtype but that were within a genetic distance of 0.12 from a reference sequence were assigned to the subtype of the closest sequence.</p>", "<title>Sequence quality control</title>", "<p>Four categories of sequences were excluded from analysis including (i) sequences of uncertain provenance that lacked sufficient annotation as to the sequence's origin, (ii) sequences submitted to GenBank more than once or derived from a previously submitted sequence through experimental manipulation either <italic>in vitro </italic>or in a primate model (\"experimental sequences\"), (iii) case reports of complete genomic sequences that were submitted to GenBank because of some unusual characteristic unrelated to integrase or to sequence diversity (e.g. a strain with unique tropism characteristics, or a strain associated with an epidemiologic cluster), and (iv) sequences of poor quality defined as having two or more of the following features: stop codons, frame shifts, highly ambiguous nucleotides (B, D, H, V, N), active site mutations, or unique insertions or deletions.</p>", "<title>Analysis of sequence heterogeneity</title>", "<p>For most analyses, polymorphisms were defined as mutations present in ≥ 0.5% of group M sequences. However, all mutations at essential integrase positions or at known INI-resistance positions that were present in sequences from one or more individuals are also noted in the text.</p>", "<p>To compare HIV-1 integrase heterogeneity with that of protease and RT, we assembled virus sequences from ARV-naïve individuals for which the complete <italic>pol </italic>gene had been sequenced. For this set of sequences, we calculated the uncorrected pair-wise amino acid differences between sequences belonging to the species HIV-1 and HIV-2, sequences belonging to the different HIV-1 groups (M, N, and O) and HIV-1_cpzisolates, sequences belonging to the different group M HIV-1 subtypes, and within the six most common group M subtypes. For the six most common group M subtypes, we also examined the number of differences from the consensus subtype sequence and examined the distribution of these differences across each of the sequences and each of these genes.</p>", "<p>We used an information-theoretic measure of diversity known as Shannon's entropy [##REF##1758884##12##] to quantify the amount of amino acid variation at each position of protease, RT, and integrase for the set of ARV-naïve sequences for which the complete pol gene was sequenced. For each subtype, the entropy at each position of protease, RT, and integrase was calculated as:</p>", "<p></p>", "<p>for K different amino acids (<italic>A</italic>₁... <italic>A</italic>_{<italic>k</italic>}) at position X where <italic>p</italic>(<italic>A</italic>_{<italic>i</italic>}) is the frequency of amino acid <italic>A</italic>_{<italic>i</italic>}.</p>", "<p>To assess covariation among integrase amino acids, we analyzed sequences belonging to the six most common group M subtypes using the Jaccard similarity coefficient (J). For a given pair of mutations X and Y, the Jaccard similarity coefficient is calculated as <italic>J </italic>= <italic>N</italic>_{<italic>XY</italic>}/(<italic>N</italic>_{<italic>XY </italic>}+ <italic>N</italic>_{<italic>X</italic>0}+ <italic>N</italic>_{0<italic>Y</italic>}) where N_XYrepresents the number of sequences containing X and Y, N_X0represents the number of sequences containing X but not Y and N_0Yrepresents the number of sequences containing Y but not X. To test whether observed Jaccard similarity coefficients were statistically significant, the expected value of the Jaccard similarity coefficients (J_RAND) and its standard error (J_SE) assuming two mutations (X and Y) occur independently were calculated for each pair of mutations. J_RANDwas calculated as the mean Jaccard similarity coefficient after 2,000 random rearrangements of the X or Y vector (containing 0 or 1 for presence or absence of a mutation). J_SEwas calculated using a jack-knifed procedure, which removed one sequence at a time, repeatedly for each sequence. The standardized score Z, <italic>Z </italic>= (<italic>J </italic>- <italic>J</italic>_{<italic>RAND</italic>})/<italic>J</italic>_{<italic>SE</italic>}, indicates a significant positive association (Z &gt; 2.56) or a significant negative association (Z &lt; -2.56) at an unadjusted p &lt; 0.01 [##REF##17500586##13##]. To adjust for multiple comparisons, we used a false discovery rate of 0.05 to identify correlations warranting further examination [##UREF##2##14##].</p>" ]

[ "<title>Results</title>", "<title>Published integrase sequences</title>", "<p>The April 15, 2008 GenBank release contained 2,736 primate lentivirus integrase sequences with 200 or more amino acids. Twenty-nine percent of these sequences (n = 775) were excluded from analysis because they were of poor sequence quality (n = 385), contained insufficient annotation (n = 291), represented experimental sequences (n = 96), or represented case reports of viruses sequenced for phenotypic properties unrelated to integrase (n = 93). Of the remaining 1,961 sequences, 1,863 sequences belonged to HIV-1/SIVcpz, 40 sequences belonged to HIV-2/SIVsmm/SIVmac, and 58 sequences belonged to one of the remaining primate lentivvirus species.</p>", "<p>The 1,863 HIV-1/SIVcpz sequences were obtained from 1,626 separate virus isolations from 1,581 individuals including 1,563 persons with HIV-1 and 18 chimpanzees with SIVcpz. Table ##TAB##0##1## summarizes the taxonomic categories of the HIV-1 sequences according to the number of distinct individuals from whom sequences were obtained. Among 1,482 persons with group M viruses, sequences from 1,351 were classified as belonging to subtypes A, B, C, D, F, G, CRF01, or CRF02; whereas sequences from 131 were classified as belonging to subtypes H, J, K or one of the other CRFs (n = 87); 44 sequences could not be adequately subtyped (n = 44). Among 1,051 group M integrase sequences in the database for which the complete genome sequence had been published, the assigned subtype matched the subtype indicated in the primary publication for the integrase region in 1,045 (99.4%) sequences. Of the 1,563 persons from whom HIV-1 sequences were obtained, none had received an INI. Seven persons had received an RT and/or protease inhibitor and in 525 persons RT and protease inhibitor treatment history was not known. A file containing the nucleotides and GenBank accession numbers of the sequences in Table ##TAB##1##2## is provided [see Additional file ##SUPPL##0##1##].</p>", "<title>HIV-1 group M amino acid polymorphisms</title>", "<p>Figure ##FIG##0##1## shows the distribution of amino acid variation among all group M integrase sequences compared with the consensus B reference sequence. Of the 288 integrase positions, 115 (39.9%) had at least one amino acid polymorphism present in 0.5% or more sequences including 41 (14.2%) at which two or more polymorphisms were present. Of the 185 polymorphisms, many resulted from highly conservative substitutions such as V↔I↔L in 32 cases, K↔R in 15 cases, A↔S↔T in 17 cases, and D↔E in 12 cases.</p>", "<p>Table ##TAB##1##2## summarizes the differences in the consensus amino acid sequence for each of the eight most common subtypes. For 33 (11.5%) of the 288 integrase positions, two or more subtypes had different consensus amino acids. Most of the polymorphic positions shown in Figure ##FIG##0##1## are polymorphic in three or more subtypes [see Additional file ##SUPPL##1##2##]. However, at a few positions, the high level of amino acid variability shown in Figure ##FIG##0##1## results largely from inter-subtype rather than intra-subtype variability. For example, much of the variability at the highly variable positions 112, 124, 125, 201, 234, and 283 results in part because the consensus B amino acid differs from the consensus of most other subtypes.</p>", "<p>Likewise, variability in just one or two subtypes can explain some of the findings in Figure ##FIG##0##1##. For example, the uncommon polymorphism F139Y is due solely to the presence of this mutation in 8% of subtype A sequences. The uncommon polymorphism V151I which appears to be an accessory INI-resistance mutation is due solely to the presence of this mutation in 10% of subtype B sequences. Finally, the uncommon polymorphism K156N, another accessory INI-resistance mutation is due solely to the presence of this mutation in 9% of subtype B and 5% of subtype D sequences.</p>", "<title>HIV integrase, RT, and protease diversity</title>", "<p>Among the 1,961 integrase sequences in Table ##TAB##0##1##, 1,367 were from isolates for which simultaneous protease and RT sequences were also available including 1,301 HIV-1/SIVcpz, 33 HIV-2/SIVstm and 33 NHPL isolates. For this comparative analysis, isolates from ARV-naive individuals of which the subtypes of the three genes are the same were used. When there are multiple isolates available from a same patient, only one isolate is used. Table ##TAB##2##3## displays the extent of protease, RT, and integrase amino acid diversity by species, group, and subtype for these isolates. Integrase amino acid diversity decreased from ~40% at the species level, ~16% at the group level, to ~7% at the subtype level. The mean intra-subtype diversity was ~5%. At all levels, the extent of amino acid diversity was lower in integrase than in protease and RT, although there was no mean difference in amino acid diversity between integrase and RT between HIV-1 and HIV-2.</p>", "<p>Among the 741 ARV-naïve HIV-1 group M isolates belonging to the six subtypes with the most sequences (A, B, C, D, CRF01, and CRF02), the number of differences from the subtype consensus sequence was highly correlated between all three pairs of genes (correlation coefficient ~0.34, p &lt; 0.001). In other words, virus isolates with many differences from the subtype consensus in one gene tended to have many difference from the subtype consensus in all three genes. Nonetheless, a regression model that accounted for this factor (by using the covariance in the number of mutations among protease, RT, and integrase and the variance within each gene) and that accounted for the length of each gene confirmed that there were fewer differences from the subtype consensus in integrase compared with RT and protease.</p>", "<p>Among the 741 ARV-naïve HIV-1 group M isolates belonging to the six most common subtypes, the proportion of positions with ≥ 0.5% variability relative to the consensus subtype amino acid was lower for integrase (34.7%) compared with protease (40.0%; p &lt; 0.001) and RT (37.2%; p &lt; 0.001). The mean level of Shannon's entropy at all positions calculated using the same 741 pol sequences was also significantly lower for integrase (0.11 ± 0.23) than for RT (0.15 ± 0.31) and protease (0.16 ± 0.31) (Figure ##FIG##1##2##). For 92.7%, 89.8%, and 88.2% of integrase, RT, and protease positions across the six most common subtypes, there was an entropy level below 0.5 bits meaning that at these positions, the correct amino acid could be predicted with approximately 90% certainty.</p>", "<title>Catalytic core domain (CCD)</title>", "<p>Of the 162 amino acid catalytic core domain (CCD) residues encompassing positions 51 to 212, 108 (66%) were nonpolymorphic (prevalence ≤ 0.5%) among group M sequences. Based on the published crystallographic structure of the integrase CCD bound to prototype diketo acid active site inhibitor (5CITEP) [##REF##10557269##7##], a putative integrase inhibitor binding pocket containing the active site residues and D64, C65, T66, H67, E92, D116, Q148, V151, E152, N155, K156, and K159 has been proposed [##REF##11063607##15##,##REF##16377678##16##]. These residues were nonpolymorphic, with the exceptions of the conservative mutations V151I, K156N, and K156R, each of which occurred in 1% of sequences (Figure ##FIG##0##1##). Six otherwise normal isolates, however, contained the active site mutation E152K. Similar variation was not observed at the other active site residues (D64 and D116) suggesting that D152 may be particularly prone either to sequencing error or to RNA editing as the observed mutation could result from unhindered APOBEC3F activity.</p>", "<p>A flexible loop region encompassing F139 to G146 and an amphipathic alpha-helix (α4) extending from S147 to V165 are involved in both the direct binding and correct positioning of viral DNA to the integrase catalytic residues. The flexible loop, which is generally poorly resolved in crystallographic structures, is completely conserved in group M sequences with the exception of F139Y, which occurred in 12 subtype A infected persons. The conserved positively charged residues in the amphiphathic α4 helix including Q148, E152, N155, and K159 are positioned to contact negatively charged viral DNA molecules [##REF##12626494##17##]. Site directed mutagenesis studies suggest that other conserved positively charged CCD residues including Q62 and N120 also participate in critical viral DNA binding [##REF##15681450##18##].</p>", "<p>Among the CCD mutations shown to directly reduce raltegravir or elvitegravir susceptibility – H51Y, T66I, E92Q, F121Y, G140S, Y143C/H/R, Q146P, S147G, Q148H/R/K, S153Y, N155H/S, and E157Q [##UREF##3##19##, ####UREF##4##20##, ##UREF##5##21####5##21##] – only positions 153 and 157 are polymorphic (prevalence ≥ 0.5%) with S153A and E157Q each present in 1% of sequences (Figures ##FIG##0##1##). In contrast, as summarized in the next paragraph, mutations at the remaining INI-resistance positions were rare.</p>", "<p>The INI-resistance mutation H51Y was present in one subtype A isolate; H51Q (n = 3) and H51P (n = 2) were present in five isolates. T66A (n = 2) and T66S (n = 1) were present in three subtype C isolates. T66P was present as part of an electrophoretic mixture in one subtype B and one subtype F isolate. E92G (n = 2), E92D (n = 1), and E92A (n = 1) were present in four isolates. F121S (n = 2) and F121L (n = 1) were present in three isolates. G140E was present in one subtype G isolate. Y143H was present in three subtype C isolates and one subtype D isolate. The INI-resistance mutation S147G was present in one CRF01_AE isolate and in one subtype C isolate; S147R was present in one subtype B isolate. The INI-resistance mutations Q148H (subtype G) and Q148K (CRF02_AG) were each present in one isolate. The INI-resistance mutation, N155H was present in one subtype B isolate; N155D was present in one subtype D isolate.</p>", "<p>Among mutations selected by raltegravir or elvitegravir that have not been shown to directly reduce susceptibility, L74R, Q95K, E138A/K, and H183P were conserved, whereas V54I, L68V, L74M, T97A, V151I, G163R, and I203M were present in approximately 1% to 2% of isolates from untreated persons (Figure ##FIG##0##1##).</p>", "<p>In a crystallographic study containing a CCD dimer and the C-terminal LEDGF integrase-binding domain, 11 CCD residues were shown to participate in LEDGF binding: L102, T125, A128, A129, W131, W132, Q168, E170, H171, T174, and M178 [##REF##16260736##22##]. All but T125 and H171 were nonpolymorphic in group M sequences. The side chains of A128, A129, W131, W132, E170, T174, and M178 participated in LEDGF binding; in contrast the main chains of the conserved position 168 and of the polymorphic positions 125 and 171 participated in LEDGF binding.</p>", "<title>N-terminal domain (NTD)</title>", "<p>Of the 50 NTD residues, 25 (50%) were nonpolymorphic among group M sequences (Figure ##FIG##0##1##). The HHCC zinc-binding motif at positions 12, 16, 40, and 43 were nonpolymorphic. This motif interacts with residues 150–196 of an adjacent monomer. The interface between the NTD and the CCD within each monomer involves the connecting residues 47 to 55 (which are poorly resolved crystallographically) and hydrophilic contacts between the NTD side chains R20 and K34 and the CCD side chains T206, Q209, and E212 [##REF##11743009##6##]. Of these interacting residues, R20K, K34R, and T206S occurred in 4%, 2%, and 16% of group M sequences, respectively, whereas Q209 and E212 were invariant among group M sequences. The polar NTD residues K14, N18, and Q44, and the polar CCD residues K160, Q168, and K186 contribute to the dimer-dimer interface in the tetrameric NTD-CCD crystal structure. group M variants at these positions include K14R in 31% of sequences and K160R/Q in 2% of sequences.</p>", "<title>C-terminal domain (CTD)</title>", "<p>Of the 76 CTD residues, 32 (58%) were nonpolymorphic among group M sequences. A crystallographic structure containing the linked CCD and CTD domains demonstrated a Y-shaped dimer in which there are two symmetrically interfacing CCDs at the base and two symmetrically separated CTDs at the \"Y\" branches [##REF##10890912##5##]. The residues linking the CCD to the CTD are part of an extended alpha helix encompass residues 195 to 225 [##REF##10890912##5##]. Residues 270–288 were not delineated in the CCD-CTD crystal structure.</p>", "<p>An electrostatic potential map identifies a strip of positively charged residues extending from the CCD active site through K159, K186, R187, and K188 in the CCD of one monomer towards the CTD of the other monomer [##REF##10890912##5##]. Positively charged CTD residues include K215, K219, R228, R231, K236, K244, K258, R262, R263, K266, R269, K273, and R284. Whereas K215N/R, K219N/Q, R269K, and R284G are reported polymorphisms, the remaining positively charged residues were nonpolymorphic. Many of these positively charged residues have been implicated in DNA binding and been found to be essential to integrase function [##REF##16051828##23##].</p>", "<p>The nonpolymorphic mutation R263K has been shown to reduce elvitegravir susceptibility by five-fold. Its effect on raltegravir has not been reported. Y226C/D/F/H, S230N/R, and D232N have been selected <italic>in vitro </italic>or <italic>in vivo </italic>by raltegravir and/or elvitegravir [##UREF##6##24##,##UREF##7##25##]. Of these mutations, S230N has been reported in 2.0% of untreated isolates. The conservative substitution D232E has also been observed in 2.0% of untreated isolates. R263K (n = 2) and R263G (n = 1) were present in three isolates.</p>", "<title>Amino acid covariation</title>", "<p>Ninety-eight pairs of amino acids were significantly associated with one another at a false discovery rate of 0.05. Fifty-seven pairs of amino acids were from the same subdomain (CCD – 40 pairs, NTD – 10 pairs, and CTD – 7 pairs); 41 were from different subdomains (CCD-NTD – 17 pairs, CCD-CTD – 12 pairs, and CTD-NTD – 12 pairs). Five pairs of CCD residues were associated in two or more subtypes. E157Q, which decreases raltegravir and elvitegravir susceptibility, was associated with K160Q/T in subtypes A, B, C, and CRF02 and with K156N in three unrelated subtype D isolates. In contrast, the other uncommon polymorphisms in the α4 helix including V151I, S153A, M154I/L, I162V, G163E/K/R, and V165I were not found to covary with each other or with other integrase mutations.</p>", "<p>The remaining pairs of residues that were associated in two or more subtypes included S119R and A91T/E in subtypes B, C, and CRF02; S119G and T122I in subtypes B and D; K219N and N222K in subtypes C and CRF02, and T124A and S283G in subtypes A and C. 17 of the CCD pairs involved position 119; whereas the next most commonly involved position was position 124, which was involved in 13 pairs. Position 119, which has been associated with target site specificity [##REF##12610159##26##,##REF##16306609##27##], is one of the most polymorphic residues with S, P, T, G, and R occurring in 80%, 11%, 4%, 3%, and 2% of isolates, respectively.</p>" ]

[ "<title>Discussion</title>", "<p>The development of clinically active INIs is a remarkable therapeutic success story. Two decades of biochemical and biophysical studies established the fundamental mechanisms of HIV-1 integrase activity [##UREF##0##1##,##REF##15134551##3##], facilitated the development of high-throughput inhibitor screening assays [##REF##11016953##28##,##REF##11494874##29##], and led to the identification of highly active, bioavailable, and safe INIs [##REF##10649997##30##, ####REF##15277684##31##, ##REF##17194584##32##, ##REF##17977962##33####17977962##33##]. Several clinical trials have demonstrated the efficacy of these compounds for both initial and salvage ARV therapy [##REF##17434401##34##, ####REF##17721395##35##, ##UREF##8##36##, ##UREF##9##37##, ##REF##16936557##38##, ##UREF##10##39####10##39##].</p>", "<p>The clinically active INIs are competitive inhibitors of target DNA and indeed there is much overlap between the sites associated with target DNA binding and INI binding [##REF##11016953##28##,##REF##11997448##40##]. Several aspects of HIV-1 integration and its inhibition, however, remain poorly understood. The relative positioning of the three separate integrase domains and the three-dimensional structure of the active multimeric form of the enzyme are not known. In addition, although there is a structure of HIV-1 integrase bound to the diketo acid structural homolog 5CITEP [##REF##10557269##7##], there are no structures of integrase bound to a DNA substrate or to one of the recent classes of INIs.</p>", "<p>Nonetheless, there is an increasing body of literature describing which integrase mutations are selected by INIs <italic>in vitro </italic>and <italic>in vivo </italic>and which integrase mutations reduce INI susceptibility. Some of these data are from studies of the early prototype INIs such as the diketo inhibitors S1360 and L-708,906 and the napthyridine carboxamide inhibitor L870,810 [##REF##15729361##4##,##REF##17668566##9##,##REF##10649997##30##,##REF##15277684##31##,##REF##15577623##41##,##REF##18378713##42##]. However, most are from studies of the licensed INI raltegravir or of elvitegravir, an INI in phase III clinical development including several clinical reports detailing the mutations developing in about 150 patients experiencing virological failure while receiving raltegravir or elvitegravir [##UREF##3##19##, ####UREF##4##20##, ##UREF##5##21####5##21##,##UREF##6##24##,##REF##17977962##33##,##UREF##11##43##, ####REF##18227187##44##, ##UREF##12##45##, ##UREF##13##46##, ##UREF##14##47##, ##UREF##15##48##, ##UREF##16##49##, ##UREF##17##50####17##50##].</p>", "<p>Several concepts of INI resistance have emerged from these studies. First, a large number of mutations have been selected by INIs either <italic>in vitro </italic>or <italic>in vivo </italic>(reviewed in [##REF##17668566##9##]). Second, most of mutations that directly reduce INI susceptibility occur close to the active site residues D64, D116, and E152 in the vicinity of the pocket to which 5CITEP binds [##REF##10557269##7##,##REF##11063607##15##,##REF##16377678##16##,##REF##17374162##51##]. Third, many mutations appear to accessory in that they have little or no effect on susceptibility by themselves. Fourth, for both raltegravir and elvitegravir, virological failure has generally been accompanied by two or more INI-resistance mutations and decreases in susceptibility ranging from &gt; 10-fold to &gt; 100-fold [##UREF##4##20##,##UREF##5##21##,##UREF##7##25##,##UREF##18##52##]. Fifth, there is extensive overlap among the integrase mutations associated with raltegravir and elvitegravir resistance [##UREF##3##19##, ####UREF##4##20##, ##UREF##5##21####5##21##,##REF##17977962##33##], as well as between these newer INIs and the earlier generation of INIs [##REF##17668566##9##,##REF##18378713##42##,##UREF##19##53##].</p>", "<p>Our study characterized the distribution of integrase amino acid variants among more than 1,800 group M HIV-1 isolates from more than 1,500 INI-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the CCD positions, 42% of the CTD positions, and 49% of the NTD positions. Among 741 ARV-naïve HIV-1 group M isolates for which complete <italic>pol </italic>sequences were available, integrase displayed higher levels of amino acid conservation compared with RT and protease by several measures of diversity including mean inter- and intra-subtype diversity and Shannon's entropy.</p>", "<p>Nearly all INI-resistance mutations known to directly reduce HIV-1 susceptibility were nonpolymorphic including H51Y, T66I, E92Q, F121Y, G140S, Y143C/H/R, Q146P, S147G, Q148H/R/K, S153Y, N155H/S, and R263K. Most accessory INI-resistance mutations including L74R, Q95K, E138A/K, H183P, Y226C/D/F/H, S230R, and D232N were also nonpolymorphic. The vast majority of integrase residues assigned specific roles such as the CCD active site residues, the NTD zinc binding residues, the residues involved in LEDGF/p75 binding, and the many positively charged CTD residues were also nonpolymorphic.</p>", "<p>In contrast, E157Q – which has been reported to be selected by raltegravir [##REF##18227187##44##] and to reduce elvitegravir susceptibility by about 3 to 6-fold [##UREF##3##19##,##REF##17977962##33##] – occurred in about 1% of untreated persons almost always in combination with the uncommon mutations K156N or K160Q. In addition, several accessory INI-resistance mutations including V54I, L68V, L74M, T97A, V151I, G163R, I203M, and S230N [##UREF##6##24##,##UREF##7##25##,##UREF##12##45##,##UREF##13##46##,##UREF##16##49##,##UREF##17##50##,##UREF##20##54##] also displayed levels of polymorphism ranging from 1% to 2%. Recent independent surveys of isolates from smaller numbers of INI-naïve individuals confirmed these results frequently finding E157Q as well as L74M, T97A, V151I, and I203M in small proportions of untreated persons [##UREF##21##55##, ####UREF##22##56##, ##UREF##23##57##, ##UREF##24##58##, ##UREF##25##59####25##59##].</p>", "<p>Mutations that have been selected <italic>in vitro </italic>or <italic>in vivo </italic>primarily by earlier INI compounds such as L-708,906, S-1360, and L-870,810 but which appear to be less essential for raltegravir or elvitegravir resistance include the highly polymorphic mutations V72I [##REF##15277684##31##], V165I [##REF##15577623##41##], and V201I [##REF##15577623##41##]; the minimally polymorphic mutation M154I [##REF##10649997##30##]; and the nonpolymorphic mutations T125K [##REF##15277684##31##], A128T [##REF##15577623##41##], and K160D [##REF##15577623##41##]. The significance of these residues to the current generation of INIs is not yet known.</p>", "<p>The high level of integrase sequence conservation results from a combination of functional and structural constraints. The functional constraints result from this enzyme's multiple functions including 3' processing, strand transfer which requires simultaneous interactions with both viral and host DNA, and binding to other components of the pre-integration complex including LEDGFp75. The structural constraints include the incompletely defined interactions among the different integrase subdomains and among the monomers that contribute to the multimeric form of the enzyme. HIV-1 integrase also contains a somewhat lower number of well-defined CTL epitopes (n = 11) relative to its size compared with protease (n = 7) and RT (n = 41), which could also contribute to its relatively higher level of sequence conservation compared with these two other enzymatic targets of ARV therapy [##UREF##26##60##].</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>HIV-1 integrase is the third enzymatic target of antiretroviral (ARV) therapy. However, few data have been published on the distribution of naturally occurring amino acid variation in this enzyme. We therefore characterized the distribution of integrase variants among more than 1,800 published group M HIV-1 isolates from more than 1,500 integrase inhibitor (INI)-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the central core domain positions, 42% of the C-terminal domain positions, and 50% of the N-terminal domain positions. Among 727 ARV-naïve individuals in whom the complete <italic>pol </italic>gene was sequenced, integrase displayed significantly decreased inter- and intra-subtype diversity and a lower Shannon's entropy than protease or RT. All primary INI-resistance mutations with the exception of E157Q – which was present in 1.1% of sequences – were nonpolymorphic. Several accessory INI-resistance mutations including L74M, T97A, V151I, G163R, and S230N were also polymorphic with polymorphism rates ranging between 0.5% to 2.0%.</p>" ]

[ "<title>Supplementary Material</title>" ]

[]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Distribution of variants among group M HIV-1 integrase sequences.</bold> The consensus subtype B sequence is shown at the top of each 40 amino acid section. Beneath the consensus B sequence is the number of annotated sequences containing an unambiguous amino acid at the indicated position with the number of such sequence ranging from 1183 to 1288. All variants reported at a level of ≥ 0.5% of sequences are indicated. The central core domain residues are surrounded by grey shading. The signature HHCC zinc-binding motif in the N-terminal domain and the DDE active site residues in the central core domain are indicated by boxes. Positions at which primary INI-resistance mutations for raltegravir and elvitegravir have been reported are indicated by \"*\". Positions at which accessory INI-resistance mutations for raltegravir and elvitegravir have been reported are indicated by \"+\". Positions at which INI-resistance mutations for other inhibitors have been reported are indicated by \".\".</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Level of Shannon's entropy across the 99 amino acids of protease, 560 amino acids of RT, and 288 amino acids of integrase for 727 isolates from the six subtypes for which the most isolates were available.</bold> A dotted line is drawn at an entropy level of 0.5 bits – a level at which the correct amino acid at a position could be predicted with nearly 90% certain.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Numbers of individuals with primate lentivirus integrase sequences &gt; 200 amino acids by species, HIV-1 group, and subtype</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Species</bold></td><td align=\"center\"><bold>Group</bold></td><td align=\"center\"><bold>Subtype</bold></td><td align=\"center\"><bold>No. individuals</bold></td></tr></thead><tbody><tr><td align=\"center\">HIV-1</td><td align=\"center\">M</td><td align=\"center\">A</td><td align=\"center\">157</td></tr><tr><td/><td/><td align=\"center\">B</td><td align=\"center\">367</td></tr><tr><td/><td/><td align=\"center\">C</td><td align=\"center\">431</td></tr><tr><td/><td/><td align=\"center\">CRF01_AE</td><td align=\"center\">130</td></tr><tr><td/><td/><td align=\"center\">CRF02_AG</td><td align=\"center\">93</td></tr><tr><td/><td/><td align=\"center\">D</td><td align=\"center\">82</td></tr><tr><td/><td/><td align=\"center\">F</td><td align=\"center\">56</td></tr><tr><td/><td/><td align=\"center\">G</td><td align=\"center\">35</td></tr><tr><td/><td/><td align=\"center\">Others^†</td><td align=\"center\">131</td></tr><tr><td/><td align=\"center\">N</td><td/><td align=\"center\">5</td></tr><tr><td/><td align=\"center\">O</td><td/><td align=\"center\">76</td></tr><tr><td/><td align=\"center\">CPZ</td><td/><td align=\"center\">18</td></tr><tr><td align=\"center\">HIV-2</td><td/><td/><td align=\"center\">39</td></tr><tr><td align=\"center\">NHPL*</td><td/><td/><td align=\"center\">58</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Integrase positions at which different subtypes have different consensus residues</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Subtype</bold></td><td align=\"center\"><bold>No.</bold></td><td align=\"center\"><bold>14</bold></td><td align=\"center\"><bold>17</bold></td><td align=\"center\"><bold>21</bold></td><td align=\"center\"><bold>25</bold></td><td align=\"center\"><bold>31</bold></td><td align=\"center\"><bold>39</bold></td><td align=\"center\"><bold>50</bold></td><td align=\"center\"><bold>72</bold></td><td align=\"center\"><bold>84</bold></td><td align=\"center\"><bold>100</bold></td><td align=\"center\"><bold>101</bold></td><td align=\"center\"><bold>112</bold></td><td align=\"center\"><bold>113</bold></td><td align=\"center\"><bold>119</bold></td><td align=\"center\"><bold>124</bold></td><td align=\"center\"><bold>125</bold></td><td align=\"center\"><bold>134</bold></td></tr><tr><td/><td/><td colspan=\"17\"><hr/></td></tr><tr><td/><td/><td align=\"center\"><bold>K⁹⁴</bold></td><td align=\"center\"><bold>S⁷⁶</bold></td><td align=\"center\"><bold>A⁹⁵</bold></td><td align=\"center\"><bold>D⁹⁶</bold></td><td align=\"center\"><bold>V⁷⁷</bold></td><td align=\"center\"><bold>S⁹¹</bold></td><td align=\"center\"><bold>M⁸³</bold></td><td align=\"center\"><bold>I⁵¹</bold></td><td align=\"center\"><bold>I⁹⁸</bold></td><td align=\"center\"><bold>F¹⁰⁰</bold></td><td align=\"center\"><bold>L⁵⁶</bold></td><td align=\"center\"><bold>T⁸⁷</bold></td><td align=\"center\"><bold>I⁹⁰</bold></td><td align=\"center\"><bold>S⁶⁹</bold></td><td align=\"center\"><bold>T⁵⁴</bold></td><td align=\"center\"><bold>T⁶⁹</bold></td><td align=\"center\"><bold>G⁹⁸</bold></td></tr></thead><tbody><tr><td align=\"center\"><bold>A</bold></td><td align=\"center\">160</td><td align=\"center\">R⁶⁴</td><td/><td/><td/><td align=\"center\">I⁷⁷</td><td/><td/><td align=\"center\">V⁸⁹</td><td/><td/><td/><td align=\"center\">V⁹²</td><td align=\"center\">V⁷⁵</td><td/><td align=\"center\">A⁷⁸</td><td align=\"center\">A⁹⁶</td><td align=\"center\">N⁵⁷</td></tr><tr><td align=\"center\"><bold>AE</bold></td><td align=\"center\">132</td><td align=\"center\">R⁹⁶</td><td/><td align=\"center\">T⁸⁶</td><td/><td align=\"center\">I⁸⁰</td><td align=\"center\">N⁷⁸</td><td/><td align=\"center\">V⁹³</td><td/><td/><td/><td align=\"center\">V⁹⁸</td><td/><td/><td align=\"center\">A⁹⁵</td><td align=\"center\">A⁹⁸</td><td align=\"center\">N⁹²</td></tr><tr><td align=\"center\"><bold>AG</bold></td><td align=\"center\">93</td><td align=\"center\">R⁸⁹</td><td/><td/><td/><td align=\"center\">I⁷²</td><td/><td/><td/><td/><td/><td align=\"center\">I⁸³</td><td align=\"center\">V⁹¹</td><td/><td/><td align=\"center\">A⁹⁶</td><td align=\"center\">A⁹⁶</td><td align=\"center\">N⁸¹</td></tr><tr><td align=\"center\"><bold>C</bold></td><td align=\"center\">432</td><td/><td/><td/><td align=\"center\">E⁸¹</td><td align=\"center\">I⁷⁶</td><td/><td align=\"center\">I⁵⁸</td><td/><td/><td align=\"center\">Y⁷²</td><td align=\"center\">I⁹⁵</td><td align=\"center\">V⁹²</td><td/><td/><td align=\"center\">A⁷⁰</td><td align=\"center\">A⁹²</td><td/></tr><tr><td align=\"center\"><bold>D</bold></td><td align=\"center\">82</td><td/><td align=\"center\">N⁷⁰</td><td/><td/><td/><td/><td align=\"center\">L⁵⁹</td><td align=\"center\">V⁸²</td><td/><td/><td/><td align=\"center\">V⁸⁴</td><td align=\"center\">V⁸⁹</td><td/><td align=\"center\">A⁸²</td><td align=\"center\">A⁷⁸</td><td/></tr><tr><td align=\"center\"><bold>F</bold></td><td align=\"center\">57</td><td/><td align=\"center\">N⁸¹</td><td/><td/><td/><td/><td/><td align=\"center\">V⁷⁰</td><td align=\"center\">L⁸¹</td><td/><td align=\"center\">I⁸⁶</td><td/><td/><td align=\"center\">T⁴⁶</td><td align=\"center\">A⁷⁰</td><td align=\"center\">A⁷⁰</td><td/></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td align=\"center\">P⁴⁰</td><td/><td/><td/></tr><tr><td align=\"center\"><bold>G</bold></td><td align=\"center\">35</td><td align=\"center\">R⁸⁹</td><td/><td/><td/><td align=\"center\">I⁶⁰</td><td/><td/><td/><td/><td/><td align=\"center\">I⁸⁶</td><td align=\"center\">V⁷⁵</td><td/><td/><td align=\"center\">A⁷¹</td><td align=\"center\">A⁸⁶</td><td align=\"center\">N⁷¹</td></tr><tr><td colspan=\"19\"><hr/></td></tr><tr><td align=\"center\"><bold>Subtype</bold></td><td align=\"center\"><bold>No.</bold></td><td align=\"center\"><bold>135</bold></td><td align=\"center\"><bold>136</bold></td><td align=\"center\"><bold>167</bold></td><td align=\"center\"><bold>201</bold></td><td align=\"center\"><bold>205</bold></td><td align=\"center\"><bold>206</bold></td><td align=\"center\"><bold>211</bold></td><td align=\"center\"><bold>218</bold></td><td align=\"center\"><bold>227</bold></td><td align=\"center\"><bold>234</bold></td><td align=\"center\"><bold>255</bold></td><td align=\"center\"><bold>256</bold></td><td align=\"center\"><bold>265</bold></td><td align=\"center\"><bold>269</bold></td><td align=\"center\"><bold>278</bold></td><td align=\"center\"><bold>283</bold></td><td/></tr><tr><td/><td/><td colspan=\"17\"><hr/></td></tr><tr><td/><td/><td align=\"center\"><bold>I⁹³</bold></td><td align=\"center\"><bold>K⁹⁷</bold></td><td align=\"center\"><bold>D⁹⁸</bold></td><td align=\"center\"><bold>V⁶²</bold></td><td align=\"center\"><bold>A⁹⁹</bold></td><td align=\"center\"><bold>T⁸⁶</bold></td><td align=\"center\"><bold>K⁸⁹</bold></td><td align=\"center\"><bold>T⁹²</bold></td><td align=\"center\"><bold>Y⁹⁵</bold></td><td align=\"center\"><bold>L⁸⁷</bold></td><td align=\"center\"><bold>S⁹⁷</bold></td><td align=\"center\"><bold>D⁷⁹</bold></td><td align=\"center\"><bold>A⁷⁸</bold></td><td align=\"center\"><bold>R⁹⁹</bold></td><td align=\"center\"><bold>D⁹⁸</bold></td><td align=\"center\"><bold>S⁸³</bold></td><td/></tr><tr><td colspan=\"19\"><hr/></td></tr><tr><td align=\"center\"><bold>A</bold></td><td align=\"center\">160</td><td/><td align=\"center\">Q⁸⁶</td><td align=\"center\">E⁸¹</td><td align=\"center\">I⁹⁸</td><td/><td/><td/><td/><td/><td align=\"center\">I⁷⁰</td><td/><td/><td/><td/><td/><td align=\"center\">G⁷³</td><td/></tr><tr><td align=\"center\"><bold>AE</bold></td><td align=\"center\">132</td><td align=\"center\">V⁹²</td><td align=\"center\">R⁶⁹</td><td align=\"center\">E⁹³</td><td align=\"center\">I⁹⁸</td><td/><td/><td/><td/><td/><td align=\"center\">I⁹⁶</td><td/><td/><td/><td/><td/><td align=\"center\">G⁹⁶</td><td/></tr><tr><td align=\"center\"><bold>AG</bold></td><td align=\"center\">93</td><td align=\"center\">V⁷⁸</td><td align=\"center\">T⁸²</td><td/><td align=\"center\">I⁹⁹</td><td/><td align=\"center\">S⁹²</td><td/><td/><td/><td align=\"center\">I⁹⁸</td><td/><td/><td/><td/><td/><td align=\"center\">G⁸⁴</td><td/></tr><tr><td align=\"center\"><bold>C</bold></td><td align=\"center\">432</td><td/><td align=\"center\">Q⁸⁹</td><td/><td align=\"center\">I⁹⁸</td><td/><td/><td/><td align=\"center\">I⁶⁴</td><td/><td align=\"center\">I⁹⁸</td><td/><td/><td align=\"center\">V⁵⁵</td><td align=\"center\">K⁵⁷</td><td align=\"center\">A⁹⁴</td><td align=\"center\">G⁸⁷</td><td/></tr><tr><td align=\"center\"><bold>D</bold></td><td align=\"center\">82</td><td/><td/><td/><td align=\"center\">I⁹⁸</td><td/><td/><td/><td/><td/><td align=\"center\">I⁹⁴</td><td/><td align=\"center\">E⁵⁷</td><td/><td/><td/><td/><td/></tr><tr><td align=\"center\"><bold>F</bold></td><td align=\"center\">57</td><td/><td align=\"center\">Q⁸⁹</td><td/><td align=\"center\">I⁹⁸</td><td align=\"center\">S⁶⁵</td><td/><td align=\"center\">R⁵⁶</td><td align=\"center\">I⁷²</td><td/><td align=\"center\">V⁹¹</td><td/><td align=\"center\">E⁹⁶</td><td/><td/><td/><td align=\"center\">G⁹¹</td><td/></tr><tr><td align=\"center\"><bold>G</bold></td><td align=\"center\">35</td><td/><td align=\"center\">T⁹⁷</td><td/><td align=\"center\">I⁹⁷</td><td/><td align=\"center\">S⁹⁴</td><td/><td/><td align=\"center\">F⁵⁷</td><td align=\"center\">I⁹¹</td><td align=\"center\">N⁹⁴</td><td align=\"center\">E¹⁰⁰</td><td/><td/><td/><td align=\"center\">G⁹⁴</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Amino acid inter-species, inter-group, inter-subtype, and intra-subtype divergence among protease, RT, and integrase sequences</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Divergence</bold></td><td align=\"center\"><bold>Protease</bold></td><td align=\"center\"><bold>RT</bold></td><td align=\"center\"><bold>Integrase</bold></td></tr></thead><tbody><tr><td align=\"left\">Inter-species</td><td/><td/><td/></tr><tr><td align=\"left\">   HIV-1 (789) vs HIV-2 (26)</td><td align=\"center\">0.51 ± 0.03</td><td align=\"center\">0.40 ± 0.04</td><td align=\"center\">0.40 ± 0.02</td></tr><tr><td/><td/><td/><td/></tr><tr><td align=\"left\">Inter-group</td><td/><td/><td/></tr><tr><td align=\"left\">   group M (764) vs O (21)</td><td align=\"center\">0.29 ± 0.02</td><td align=\"center\">0.22 ± 0.01</td><td align=\"center\">0.18 ± 0.01</td></tr><tr><td align=\"left\">   group M (764) vs N (4)</td><td align=\"center\">0.21 ± 0.02</td><td align=\"center\">0.14 ± 0.01</td><td align=\"center\">0.11 ± 0.01</td></tr><tr><td align=\"left\">   group O (21) vs N (4)</td><td align=\"center\">0.30 ± 0.02</td><td align=\"center\">0.21 ± 0.01</td><td align=\"center\">0.18 ± 0.01</td></tr><tr><td/><td/><td/><td/></tr><tr><td align=\"left\">Inter-subtype</td><td/><td/><td/></tr><tr><td align=\"left\">   Subtype A (71) vs B (145)</td><td align=\"center\">0.11 ± 0.03</td><td align=\"center\">0.10 ± 0.01</td><td align=\"center\">0.07 ± 0.01</td></tr><tr><td align=\"left\">   Subtype A (71) vs C (337)</td><td align=\"center\">0.10 ± 0.03</td><td align=\"center\">0.09 ± 0.01</td><td align=\"center\">0.07 ± 0.01</td></tr><tr><td align=\"left\">   Subtype B (145) vs C (337)</td><td align=\"center\">0.11 ± 0.02</td><td align=\"center\">0.09 ± 0.01</td><td align=\"center\">0.07 ± 0.01</td></tr><tr><td/><td/><td/><td/></tr><tr><td align=\"left\">Intra-subtype</td><td/><td/><td/></tr><tr><td align=\"left\">   Subtype A (71)</td><td align=\"center\">0.05 ± 0.02</td><td align=\"center\">0.07 ± 0.02</td><td align=\"center\">0.05 ± 0.01</td></tr><tr><td align=\"left\">   Subtype B (145)</td><td align=\"center\">0.07 ± 0.03</td><td align=\"center\">0.06 ± 0.01</td><td align=\"center\">0.05 ± 0.02</td></tr><tr><td align=\"left\">   Subtype C (337)</td><td align=\"center\">0.06 ± 0.03</td><td align=\"center\">0.06 ± 0.01</td><td align=\"center\">0.04 ± 0.01</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1742-4690-5-74-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtext>Entropy </mml:mtext><mml:mo stretchy=\"false\">(</mml:mo><mml:mtext>X</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mo>−</mml:mo><mml:mstyle displaystyle=\"true\"><mml:munderover><mml:mo>∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>k</mml:mi></mml:munderover><mml:mrow><mml:mi>p</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>A</mml:mi><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>⋅</mml:mo><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mi>p</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>A</mml:mi><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional File 1</title><p>Accession IDs</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional File 2</title><p>Variation by subtype</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>*NHPL: non-human primate lentiviruses exclusive of SIV_CPZand SIV_STM/SIV_MAC. SIV_CPZand SIV_STM/SIV_MACare listed with human HIV-1 and HIV-2 isolates, respectively</p><p>^†Others: Subtypes, H, J, K, circulating recombinant forms other than 01 and 02, as well as non-CRF recombinants, and other non-classifiable group M sequences.</p></table-wrap-foot>", "<table-wrap-foot><p>Abbreviations: No. – number of sequences. The header shows the amino acid consensus for subtype B isolates. The individual rows indicate the amino acid positions at which specific subtypes have a consensus amino acid different from subtype B. The superscript indicates the proportion of isolates of that row's subtype which have the consensus amino acid for that subtype. Empty cells indicate that the subtype has the same consensus amino acid as the consensus for subtype B.</p></table-wrap-foot>", "<table-wrap-foot><p>Divergence was defined as the mean proportion of amino acid difference between all sequence pairs. The number of sequences compared are within parentheses.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1742-4690-5-74-1\"/>", "<graphic xlink:href=\"1742-4690-5-74-2\"/>" ]

[ "<media xlink:href=\"1742-4690-5-74-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1742-4690-5-74-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>In the 1920's, Hoover described a sign that could be considered a marker of severe airway obstruction. While readily recognizable at the bedside, it may also as easily be missed on physical examination. Hoover's sign refers to the inspiratory retraction of the lower intercostal spaces. It results from alteration in dynamics of diaphragmatic contraction due to hyperinflation, resulting in traction on the rib margins by the flattened diaphragm. The sign is reported to have a sensitivity of 58% and specificity of 86% for detection of airway obstruction. Seen in up to 70% of patients with severe obstruction, this sign is often associated with body mass index, degree of dyspnea and frequency of exacerbations. Often overlooked, Hoover's sign may provide valuable prognostic information. When present, the sign can be used, along with arterial blood gasses, pulmonary function and other measures summarized in Table ##TAB##0##1##, as a marker for severity of airway obstruction, as seen in emphysema, chronic obstructive pulmonary disease (COPD) or asthma.</p>", "<p>Better clinical and bedside prognosticators of airway obstruction would be helpful as asthma and COPD are becoming increasingly prevalent in the population [##REF##1538305##1##]. COPD is the fourth leading cause of death in the United States behind coronary artery disease, malignancy, and cerebrovascular disease. In 2000, an estimated 10 million US adults reported physician-diagnosed COPD. Data from the Third National Health and Nutrition Examination Survey (NHANES III), however, estimate that among 11 million US adults with evidence of low lung function, &lt; 40% reported a diagnosis of COPD or asthma, suggesting that COPD is under-diagnosed. Acute exacerbations of COPD can result in ventilator failure, and patients with severe COPD or asthma are more prone to developing this complication. A clinical, quickly identified manifestation of respiratory failure is the Hoover's sign, which does not require expensive tests or waiting for radiological or biochemical results (such as arterial blood gases). Moreover, when patients presents with an acute exacerbation of airway disease in the emergency room or in a physician's office, they are less likely to tolerate laborious radiological examinations (such as computed tomograms) and pulmonary function tests (which require intense patient participation). It is in this situation that a positive Hoover's sign, in association with other clinical parameters, blood gases or peak expiratory flow tests is likely to assist in patient triage and management in emergency settings. We present a review of the clinical and molecular/structural basis of the Hoover's sign and explain how it could be utilized in the bedside and emergent management of severe airway disease.</p>", "<title>Clinical presentation of Hoover's sign</title>", "<title>Case Report</title>", "<p>Figure ##FIG##0##1## demonstrates the chest wall findings in a 65 year old male long-term smoker who had frequent hospitalization for wheezing in spite of oral steroids. The patient's medications included prednisone (20 mg/day), formoterol and lisinopril. Examination revealed a thin, dyspneic Caucasian male. Pursed lip breathing, bilateral expiratory wheezing and Hoover's sign were present. Hoover's sign refers to the paradoxical inspiratory retraction of the rib cage and lower intercostal interspaces (Figure ##FIG##0##1## Panels A and B). This patient had evidence of moderate airway obstruction and elevated residual volumes (Figure ##FIG##0##1## Panels C and D). There was poor reversibility with bronchodilators. The patient had a low alpha-1 antitrypsin level of 83 mg/dl (N = 90–200 mg/dl) and he was classified as a MZ phenotype. Figure ##FIG##1##2## demonstrates the chest roentgenogram of the patient, with panel A being the postero-anterior and B lateral views of the chest roentgenograms of the same patient. The arrow marks refer to the flattening of the diaphragm (white arrows), emphysematous changes (yellow arrow) and the decreased zone of apposition (red arrow). The significance of this is discussed under mechanisms below.</p>", "<title>What is Hoover's sign?</title>", "<p>Originally described in 1920 by Hoover, this eponymous sign refers to the paradoxical inspiratory indrawing of the lateral rib margin which has been attributed to direct traction on the lateral rib margins by the flattened diaphragm [##UREF##0##2##,##REF##16700846##3##]. Normally, the costal margin moves very little during regular breathing, but, if it does, it moves outward and upward. In patients with obstructive airway disease there is a higher tendency for it to move paradoxically [##REF##5763506##4##]. In these patients, paradoxical movements of the sternum as well as of the abdominal wall may be seen [##REF##6719373##5##]. Garcia-Pachon et al., found Hoover's sign expression in 62 out of 82 patients with COPD (sensitivity of 76%), 3 out of 23 patients with asthma (13%) and in 3 out of 101 (3%) of patients with congestive heart failure [##REF##15811278##6##]. In a larger study of 157 patients, the same investigators demonstrated presence of Hoover's sign in 71 patients (45% of study population), and in 36%, 43% and 76% respectively of patients with mild, moderate or severe COPD [##REF##16700846##3##]. Garcia-Pachon also showed that patients with COPD and Hoover's sign tended to have a higher dyspnea index/score, have higher hospitalizations or emergency room visits than patients without the sign [##REF##15066649##7##]. It appears that Hoover's sign may provide excellent prognostication of severe COPD. In a multivariate analysis, severity of dyspnea, the patient's body mass index, numbers of exacerbations historically and numbers of prescribed drugs were independently associated with the sign [##REF##16700846##3##].</p>", "<p>The Hoover's Sign of Hysterical Paralysis, not to be confused with the sign being discussed, can be found in the neurological literature that describes a sign to separate organic from non-organic paresis of the leg. Involuntary extension of the paralyzed leg occurs when flexing the contralateral leg against resistance. The patient lies supine, the examiner's hand is placed under the non-paralyzed heel, and the patient is asked to elevate the paralyzed leg. In organic paresis the examiner feels a downward pressure under the non-paralyzed heel; in malingering no pressure is felt. This sign is not within the purview of the current review.</p>", "<title>Presumed molecular mechanisms behind Hoover's sign</title>", "<p>Studies by Gilmartin and Gibson suggest that transdiaphragmatic pressures play a major role in the pathogenesis of Hoover's sign [##REF##2945502##8##]. Figure ##FIG##2##3## demonstrates the possible mechanism behind Hoover's sign. With emphysema secondary to airway obstruction, flattening of the diaphragm occurs (as shown also in Figure ##FIG##1##2##). This leads to increased radius of curvature, which in turn increases muscle tension. Secondary to the horizontal orientation of the diaphragm and the associated loss of the zone of apposition between the visceral and parietal pleurae (Figure ##FIG##2##3## right panel), the force vector on the lower aspects of the ribs become inward rather than cephalad. This culminates in the lower rib cage motion directed inward on inspiration instead of outward, the paradoxical movement referred to as Hoover's sign. In an exacerbation, the presence of mucus and bronchoconstriction further increases airway resistance, work of breathing and lung inflation. This leads to more diaphragmatic flattening and exacerbation of the mechanisms mentioned above. It would be interesting to study molecular changes in the musculature such as expression of certain muscle genes and ultrastructural alterations in muscle but these have not been done.</p>", "<title>Clinical significance of Hoover's sign</title>", "<p>Hoover's sign is a frequent finding in COPD, and the frequency increases with severity. The sign can also be present in patients with congestive heart failure, asthma, severe pneumonia (especially in children), bronchiolitis, as well as seen unilaterally in diaphragmatic paralysis, pleural effusion and pneumothorax.</p>", "<p>The Hoover's sign is reported to have a sensitivity of 58% and specificity of 86% for detection of airway obstruction in a study by experienced respiratory medicine specialists among a group of first year residents in family medicine [##REF##12171846##9##]. The study compared the accuracy of Hoover's sign detecting obstructive airway disease compared with traditional signs such as wheezing, rhonchi and/or reduced breath sounds. Observer agreement in the study (kappa statistic) was 0.74 for Hoover sign and was lower for the rest of the signs stated above [##REF##12171846##9##]. The Hoover's sign had a positive likelihood ratio of 4.16, which was higher than that of the other signs. Obstructive airway disease in the study was defined as an FEV1/FVC ratio of &lt; 0.70. There have been no studies conducted on the sensitivity and specificity of Hoover's sign in asthma. There is no data available either on the cost savings that may be induced by using Hoover's sign as opposed to use of chest roentgenography, pulmonary function tests or arterial blood gases, for example. The duration of persistence of Hoover's sign, its appearance or disappearance in relationship to exacerbations and remissions and the influence of aggressive therapy on extent of retraction are hitherto unknown. Further studies would certainly improve insights into the pathogenesis of airway obstruction but probably would be unlikely to be done in this day and age of high technology and digital imaging.</p>" ]

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[ "<title>Conclusion</title>", "<p>Hoover's sign refers to the inspiratory retraction of the lower intercostal spaces. It results from alteration in dynamics of diaphragmatic contraction due to hyperinflation, resulting in traction on the rib margins by the flattened diaphragm. Seen in up to 70% of patients with severe obstruction, this sign is associated with body mass index, dyspnea and frequency of exacerbations. This sign can be an excellent marker for severe airway obstruction.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>In the 1920's, Hoover described a sign that could be considered a marker of severe airway obstruction. While readily recognizable at the bedside, it may easily be missed on a cursory physical examination. Hoover's sign refers to the inspiratory retraction of the lower intercostal spaces that occurs with obstructive airway disease. It results from alteration in dynamics of diaphragmatic contraction due to hyperinflation, resulting in traction on the rib margins by the flattened diaphragm. The sign is reported to have a sensitivity of 58% and specificity of 86% for detection of airway obstruction. Seen in up to 70% of patients with severe obstruction, this sign is associated with a patient's body mass index, severity of dyspnea and frequency of exacerbations. Hence the presence of the Hoover's sign may provide valuable prognostic information in patients with airway obstruction, and can serve to complement other clinical or functional tests. We present a clinical and molecular review of the Hoover's sign and explain how it could be utilized in the bedside and emergent management of airway disease.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>", "<title>Authors' contributions</title>", "<p>CRJ carried out the research into Hoover's sign, and in structuring and outline of the manuscript; NK assisted with the case report and editing process; GK conceived the study, helped in the editing process, created the graphics and elaborated the case report.</p>" ]

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[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Hoover's sign refers to the paradoxical inspiratory retraction of the rib cage and lower intercostal interspaces </bold>(<bold>Figure 1 Panels A and B</bold>). This patient had evidence of moderate airway obstruction and elevated residual volumes (<bold>Figure 1 Panels C and D</bold>).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>With A showing PA and B showing lateral views of the chest roentgenograms of the same patient. </bold>The arrow marks refer to the flattening of the diaphragm (white arrows), emphysematous changes (yellow arrow) and the decreased zone of apposition (red arrow).</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Demonstrates the mechanism behind Hoover's sign. </bold>The numbers on the figure refer to the following: 1 = accessory muscles, 2 = hyper-expansion of the lungs, 3 = alteration of rib orientation to horizontal 4 = flattened diaphragm and 5 = decreased zone of apposition (adapted from Mason: Murray and Nadel's Textbook of Respiratory Medicine, 4^thEdition).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Suggested Indices Of Severity Of Airway Obstruction</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\"><bold>Physical findings</bold></td><td align=\"left\">Pursed lip breathing</td></tr><tr><td/><td align=\"left\">Intercostal retraction (Hoover Sign)</td></tr><tr><td/><td align=\"left\">Accessory muscle use</td></tr><tr><td/><td align=\"left\">Cyanosis</td></tr><tr><td/><td align=\"left\"><bold>Hoover's sign?</bold></td></tr><tr><td/><td/></tr><tr><td align=\"left\"><bold>Laboratory Parameters</bold></td><td align=\"left\">Pulmonary function (FEV₁and FEV₁/FVC)</td></tr><tr><td/><td align=\"left\">Peak Expiratory Flow Rate</td></tr><tr><td/><td align=\"left\">Hypoxemia</td></tr></tbody></table></table-wrap>" ]

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[ "<graphic xlink:href=\"1476-7961-6-8-1\"/>", "<graphic xlink:href=\"1476-7961-6-8-2\"/>", "<graphic xlink:href=\"1476-7961-6-8-3\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Many human tumor cells are characterized by over-expression of epidermal growth factor receptor (EGFR), a protein that promotes growth and aggressiveness and resistance of cancer cells to chemo- and radiotherapy [##REF##16854613##1##, ####REF##17670948##2##, ##REF##16024124##3##, ##REF##18058366##4##, ##REF##16000298##5####16000298##5##]. EGFR can be phosphorylated in response to binding of its specific ligands (EGF, TGF alpha and Amphiregulin) [##REF##18023415##6##,##REF##17549382##7##] and after exposure to unspecific stimuli like ionizing radiation [##REF##9294612##8##], UV-radiation [##REF##8895576##9##], hypoxia [##REF##16847054##10##], hyperthermia [##REF##17126326##11##], oxidative stress [##REF##16407214##12##] and trans-activation by G-protein coupled receptors [##REF##17981673##13##,##REF##16495036##14##]. Ligand-dependent as well as ligand-independent phosphorylation of EGFR results in receptor internalization [##REF##17643422##15##] and intracellular signaling [##REF##18058366##4##,##REF##16000298##5##,##REF##15192046##16##, ####REF##17699110##17##, ##REF##16818713##18####16818713##18##]. Up to date internalization is assumed to be essential for receptor silencing and inactivation. Indeed, EGF treatment results in internalization of EGFR into coated pits followed by receptor degradation [##REF##16943190##19##]. As reported by Khan [##REF##16407214##12##], exposure to oxidative stress can lead to internalization of EGFR by caveolae and this process is associated with peri-nuclear accumulation of EGFR.</p>", "<p>A characteristic constituent of caveolae is caveolin. In vertebrates the caveolin gene family has three members: CAV1, CAV2, and CAV3, coding for the proteins caveolin-1, caveolin-2 and caveolin-3, respectively. Caveolins form oligomers and associate with cholesterol and sphingolipids in certain areas of the cell membrane, leading to the formation of caveolae. Caveolae are involved in receptor independent endocytosis [##REF##17318224##20##]. Furthermore Caveolin-1 is an integral transmembrane protein and an essential component in interactions of integrin receptors with cytoskeleton-associated and signaling molecules [##REF##17471232##21##]. Compartmentation into caveolae prevents EGFR degradation and simultaneously enables intracellular EGFR signaling [##REF##16407214##12##]. These findings suggest a new function of EGFR – depending on its intracellular localization -, which supplements its functions described so far. The idea of additional EGFR functions is further supported by the observation, that peri-nuclear EGFR can be transported into cell nucleus in response to irradiation [##REF##16000298##5##]. As we and others have reported earlier [##REF##18058366##4##,##REF##18006754##22##, ####REF##18037521##23##, ##REF##17996386##24####17996386##24##], nuclear EGFR is linked with activation of DNA-PK and regulation of non-homologous end-joining DNA-repair resulting in increased radioresistance [##REF##16000298##5##]. As reported recently [##REF##16854613##1##], nuclear EGFR detection in tumors biopsies correlated strongly with treatment resistance and bad prognosis.</p>", "<p>In the present study, we focused on the radiation-induced nuclear translocation process of EGFR via caveolae. Evidence is provided that inhibition of src activity blocks the caveolin-dependent EGFR internalization and nuclear EGFR transport, which results in impaired DNA-repair.</p>" ]

[ "<title>Materials and methods</title>", "<title>Cell culture, transfection, irradiation and colony formation assay</title>", "<p>Experiments were performed with the human bronchial carcinoma cell line, A549 (ATCC) and the human squamous carcinoma cell line FaDu (ATCC, origin head and neck cancer). Cells were irradiated with 200-kV photons (Gulmay RS 225, dose rate 1 Gy/min) at 37°C. The EGFR-inhibitory antibody Erbitux was purchased from Merck KG aA, Germany and was administered to the cells at a concentration of 30 nM 1 h before irradiation. PP2 (4-amino-5-(4-chlorophenyl)-7-(<italic>t</italic>-butyl)pyrazolo [3,4-<italic>d</italic>]pyrimidine) was received from Sigma and cells were treated at a concentration of 100 nM PP2 dissolved in DMSO for 1 h. For silencing of src cells were treated with specific siRNA for 72 hours before irradiation. Control non-silencing siRNA (sense UUCUCCGAACGUGUCACGUtt; antisense ACGUGACACGU-UCGGAGAAtt) and siRNA targeting src (sense ACUCGCCUUCUUAGAGUUUtt; antisense AAACUCUAAGAAGGCGAGUtt) probes were purchased from MWG-Biotech AG. Both were transfected at a concentration of 30 nM using Lipofectamine 2000 transfection reagent according to manufacture's protocol (Invitrogen). For colony formation assay cells were grown to confluence, treated as indicated and irradiated. After 6 hours cells were typsinized and seeded at a density of 500 cells in 78 cm²plates. After 10 days colonies were fixed, stained and counted. Radiation survival curves were plotted after normalizing for the cytotoxicity induced by siRNA treatment or vehicle alone. Clonogenic survival curves were constructed from at least three independent experiments.</p>", "<title>Subcellular fractionation</title>", "<p>Cytoplasmic and nuclear extracts were prepared according to the instructions of the NE-PER^®nuclear and cytoplasmic extraction kit (Pierce, Rockford, IL, USA).</p>", "<title>Western blot analysis and immune-precipitation</title>", "<p>After irradiation, as described above, cells were lysed and proteins were resolved by SDS-PAGE. Western blotting was performed according to standard procedures [##REF##5432063##25##]. The primary antibodies were diluted as follows: anti-EGFR (BD Transduction Laboratories, clone 13) 1:1000; anti EGFR pY845 (nanotools, clone 12A3) 1:1000; anti-EGFR pY992 (abcam, polyclonal) 1:500); anti-EGFR pY1173 (Cell signaling, clone 53A5) 1:1000; anti-phosphotyrosin (Santa Cruz, clone PY20) 1:500); anti-src (Santa Cruz, clone H-12) 1:1000; anti-src Y416 (cell signaling, polyclonal), 1:1000; anti-caveolin-1 (BD Transduction Laboratories, clone 2297) 1:1000; anti-caveolin pY14 (BD Transduction Laboratories, clone 56) 1:1000; anti-DNA-PK (PharMingen, clone 4F10C5) 1:500; anti-DNA-PK pT2609 (Rockland) 1:1000; anti-lamin B1 (Biozol, clone ZL-5) 1:1000. Quantification of binding was achieved by incubation with a secondary peroxidase-conjugated antibody with the ECL system (Amersham).</p>", "<p>EGFR was immune-precipitated from cytoplasmic and nuclear protein fractions prepared from 20 × 10⁶cells with EGFR antibody clone 13 (BD Transduction Laboratories). Immune-precipitation was performed as described [##REF##9840184##26##].</p>", "<title>Quantification of γH₂AX-foci formation</title>", "<p>Cells cultured on CultureSlides (Becton Dickinson) were incubated with PP2 or src-siRNA, irradiated and fixed with 70% ice-cold ethanol 24 h after irradiation. For immune-fluorescence analysis cells were incubated with <bold>γ</bold>H₂AX antibody (Upstate, clone JBW301)(1:500) at room temperature for 2 h. Positive foci were visualized by incubation with a 1:500 dilution of Alexa488-labelled goat anti-mouse serum (Molecular Probes) for 30 min. Coverslips were mounted in Vectashield/DAPI (Vector Laboratories). For each data point 300 to 500 nuclei were evaluated.</p>" ]

[ "<title>Results</title>", "<title>Caveolin-1 associated EGFR internalization following irradiation was triggered by src kinase</title>", "<p>Ionizing radiation induced protein stabilization of cytoplasmic src in A549 cells within 10 to 20 min (Fig. ##FIG##0##1A##). Stabilization of src was associated with phosphorylation at residue Y416, which indicates src activation [##REF##17804738##27##]. Radiation-induced stabilization and activation of src led to complex formation with caveolin-1 and EGFR as shown by means of a src-specific immune-precipitation. Caveolin-1 associated EGFR was phosphorylated at residue Y845, which is a known src kinase specific phosphorylation site [##REF##7488034##28##]. Moreover, increased src activity was associated with increased caveolin-1 and EGFR binding and phosphorylation at Y14 and respectively Y845 (Fig. ##FIG##0##1A##). EGF treatment also stabilized src protein and triggered a weaker Y416 phosphorylation. However, caveolin-1 and EGFR were not increased over the control in the src associated complex following EGF treatment (Fig. ##FIG##0##1B##). To elucidate the role of src-driven EGFR phosphorylation at residue Y845 following irradiation, we determined the phosphorylation status of additional tyrosine residues of EGFR after irradiation with 4 Gy (Fig. ##FIG##0##1C##). In general, tyrosine phoshorylation of EGFR was markedly increased. Especially phosphorylation at residues Y845 and Y1173 were strongly induced by irradiation, whereas the induction of phosphorylation at residue Y992 was weaker.</p>", "<title>The antibody Erbitux stabilized the cytoplasmic caveolin-1/EGFR complex</title>", "<p>In agreement with Fig. ##FIG##0##1##, immune-precipitation targeting caveolin-1 indicated also an increasing complex formation with EGFR following radiation exposure in A549 cells (Fig. ##FIG##1##2##). Pre-incubation (1 h) with the EGFR inhibitory antibody Erbitux, resulted in a pronounced stabilization of the caveolin-1/EGFR complex in non-irradiated cells. This complex formation could not be further increased by radiation exposure.</p>", "<title>Src kinase inhibitor PP2 prevented radiation-induced EGFR transport into the nucleus and hampered radiation-induced activation of DNA-PK</title>", "<p>As already shown earlier [##REF##16000298##5##], ionizing radiation triggered EGFR transport into the nucleus and complex formation with DNA-PK (Fig. ##FIG##2##3##) [##REF##16000298##5##]. Treatment with the src kinase inhibitor PP2 (100 nM for 1 h) was sufficient to block radiation-induced nuclear translocation of EGFR in A549 cells (Fig. ##FIG##2##3##). Interestingly, basal amount of nuclear EGFR protein was not affected by PP2 treatment. However, total nuclear caveolin-1 protein and its phosphorylated form was decreased by PP2 treatment. In addition, phosphorylation of DNA-PK at residue T2609, which is essential for non-homologous end-joining DNA-repair process [##REF##17189255##29##], was inhibited in response to PP2 incubation, whereas the amount of total DNA-PK protein was unchanged.</p>", "<title>Src siRNA decreased phosphorylation of cytoplasmic EGFR at Y845, reduced EGFR transport into nucleus and impaired phosphorylation of DNA-PK at T2609 after irradiation</title>", "<p>Src protein expression was effectively knocked down in A549 and FaDu cells 72 h after transfection with src specific siRNA (Fig. ##FIG##3##4A/C##). Repression of src-protein markedly inhibited radiation-induced phosphorylation of cytoplasmic EGFR at Y845 and caveolin Y14 (Fig. ##FIG##3##4A/C##) after irradiation. In agreement with the data of Fig. ##FIG##2##3##, src knockdown also reduced radiation-induced EGFR shuttling into nucleus (Fig. ##FIG##3##4B/D##). Moreover, like PP2 inhibitor (see Fig. ##FIG##2##3##) src siRNA treatment led to reduced phosphorylation of DNA-PK at residue T2609 (Fig. ##FIG##3##4B##). It is noteworthy, that basal amount of nuclear EGFR protein was increased already by src siRNA treatment alone. However, this increase did not correspond to an activation/phosphorylation of DNA-PK at T2609.</p>", "<title>Blocking of src signaling increased level of residual DNA-damage following irradiation</title>", "<p>Irradiation of confluent A549 cells treated with control siRNA resulted in a radiation- dose dependent increase in residual γH₂AX positive repair foci, which represent un-repaired DNA double strand breaks (Fig. ##FIG##4##5A##). Pre-treatment with src specific siRNA increased the number of radiation-induced residual γH₂AX foci 24 h after irradiation, by a factor of 1.5 – 2 (Fig. ##FIG##4##5A##). Likewise pre-treatment of cells with the src kinase inhibitor PP2 for 1 h, resulted also in a significant increase in residual γH₂AX foci (Fig. ##FIG##4##5B##). In both cases inhibition of DNA-damage repair was correlated with increased radiosensitivity, as determined by means of colony formation assay (Fig. ##FIG##4##5C/D##).</p>" ]

[ "<title>Discussion</title>", "<p>It is generally accepted, that the epidermal growth factor receptor is localized within the cell membrane and will be internalized following activation and dimerization [##REF##16113650##30##]. Indeed, such a scenario can be observed following EGF stimulation [##REF##16113650##30##], which initiates proliferation associated signaling. However, the EGFR can be also activated by oxidative stress [##REF##16407214##12##], radiation, [##REF##16000298##5##,##REF##9294612##8##] and G-coupled receptors [##REF##17981673##13##]. The molecular mechanisms of this ligand independent activation of EGFR are not fully understood. However, ligand independent stimulation of EGFR, e.g. by ionizing radiation [##REF##9294612##8##], is clearly characterized by receptor internalization also. The data presented herein, give new insights into the mechanism of EGFR internalization process and the intra-nuclear function of EGFR following exposure to ionizing radiation.</p>", "<p>Several pathways enable endocytic transport of cargo molecules from the surface of eukaryotic cells into cytoplasm [##REF##17692542##31##]. The two best understood pathways, relevant for EGFR internalization, are the clathrin-coated pit [##REF##17692542##31##] and the caveolin [##REF##16440447##32##] driven internalization mechanisms. As shown by Khan et al. [##REF##16407214##12##], the clathrin-coated pit associated EGFR internalization can be observed following treatment with EGF and results in a fast degradation and silencing of receptor function. In contrast, treatment with H₂O₂leads to EGFR internalization into caveolae, which sort internalized EGFR into a per-nuclear localization associated with an ongoing receptor signaling [##REF##16407214##12##]. In agreement with these data, we could show, that exposure to ionizing radiation induced a caveolin-1 associated EGFR internalization, whereas EGF treatment failed to trigger complex formation between <italic>src</italic>, EGFR and caveolin-1. Sorting into different compartments in response to different stimuli may explain signal discrimination at the level of activated EGFR. Like for H₂O₂treatment [##REF##16407214##12##], exposure to ionizing radiation also mediates the src driven phosphorylations of EGFR at Y845 and of caveolin-1 at Y14, which is needed for internalization of EGFR into caveolae [##REF##16407214##12##]. In response to radiation not only EGFR phosphorylation at Y845 – which is Src dependent – was observed, but also phosphorylation at Y992 and Y1173 could be observed. Both are described as autophosphorylation sites [##REF##15708852##33##]. This implicates that ionizing radiation activates not only src kinase, but also EGFR kinase and both kinases contribute to altered phosphorylation pattern of EGFR following radiation exposure. Caveolin-1 phosphorylation seems to be critical for caveolae formation [##REF##17318224##20##]. On the contrary, Y845 phosphorylation of EGFR probably is rather essential in regulation of EGFR-kinase activity than in formation of coated pits or caveolae [##REF##17643422##15##]. However, as shown by us and by Khan [##REF##16407214##12##] src activity is crucial for radiation- and H₂O₂-induced formation of caveolae. Nevertheless, the molecular mechanism responsible for activation of src has to be resolved. From our data it appears, that radiation leads to a fast activation of src, which is documented by phosphorylation of src at residue Y416. This phosphorylation is described as an autophosphorylation [##REF##17804738##27##]. As activating molecular switch several mechanisms are discussed: (i) oxidation associated structural modifications result in activation of src kinase [##REF##16024778##34##], (ii) inhibition of a phosphatase leads to auto-activation of kinase [##REF##17974954##35##], (iii) G-coupled receptor signaling mediates src activation [##REF##16495036##14##]. Which of these potential mechanisms is relevant for radiation-induced src kinase activity is currently unclear and is subject of ongoing investigations.</p>", "<p>As shown herein, treatment with Erbitux, which binds to the extracellular domain of EGFR, results in receptor internalization and formation of an intracellular complex of EGFR, caveolin-1 and Erbitux. Internalized EGFR however can not be activated by EGF and this observation may explain growth inhibitory effects of Erbitux.</p>", "<p>Khan et al. observed a peri-nuclear EGFR accumulation due to caveolin-1 driven internalization after exposing cells to H₂O₂[##REF##16407214##12##]. We could also detect a peri-nuclear localization of the EGFR [##REF##16000298##5##] in irradiated cells, which is accompanied by a nuclear EGFR shuttling [##REF##16000298##5##]. Based on these results we hypothesized, that peri-nuclear EGFR serves as a pool for nuclear EGFR transport following irradiation. This hypothesis is supported by the observation that inhibition of src either by its specific inhibitor PP2 or by specific siRNA, prevents nuclear translocation of EGFR by blocking caveolin-1 driven EGFR internalization. It is noteworthy, that caveolin-1 driven EGFR internalization occurs predominantly following treatment of cells with genotoxic agents. This observation is in favor with the idea, that EGFR internalization and nuclear transport of EGFR are linked with DNA-repair processes [##REF##18037521##23##,##REF##17714814##36##]. This assumption is supported by the observation, that caveolin-1 driven EGFR internalization is not observed after EGF treatment. As shown for irradiated cells nuclear EGFR is found in complex with DNA-PK, which is an essential compound of non-homologous end-joining DNA-repair [##REF##16000298##5##]. As reported earlier [##REF##16024112##37##], inhibition of EGFR nuclear transport by Erbitux, markedly impaired radiation associated activation of DNA-PK and increased cellular radiosensitivity [##REF##16024112##37##]. In agreement with that, inhibition of src, which blocks EGFR internalization and subsequently nuclear transport after irradiation, abolished activation of DNA-PK, inhibited DNA-repair and increased radiosensitvity. Based on the data presented, it can be concluded, that the radiation-induced activation and nuclear translocation of EGFR is mediated through src kinase activity in a caveolin-1 dependent process. As blocking of these processes markedly effects repair of DNA-double strand breaks, this EGFR-coupled radiation response mechanism offers new interventional molecular targets for cancer therapy, especially by radiation therapy.</p>" ]

[ "<title>Conclusion</title>", "<p>EGFR internalization by caveolin-1 is a stress specific cellular reaction, which is src kinase activity dependent. Linked with EGFR internalization nuclear transport can be observed following irradiation. Nuclear EGFR transport can be hampered by inhibition of src. Consequently, src inhibition is associated with inhibition of EGFR triggered activation of DNA-PK, which leads to an inhibition of DNA-repair and cell survival.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>To elucidate the role of src kinase in caveolin-1 driven internalization and nuclear transport of EGFR linked to regulation of DNA-repair in irradiated cells.</p>", "<title>Results</title>", "<p>Ionizing radiation resulted in src kinase stabilization, activation and subsequent src mediated caveolin-1 Y14- and EGFR Y845-phosphorylations. Both phosphorylations were radiation specific and could not be observed after treatment with EGF. Inhibition of EGFR by the antibody Erbitux resulted in a strong accumulation of caveolin/EGFR complexes within the cytoplasm, which could not be further increased by irradiation. Radiation-induced caveolin-1- and EGFR-phosphorylations were associated with nuclear EGFR transport and activation of DNA-PK, as detected by phosphorylation at T2609. Blockage of src activity by the specific inhibitor PP2, decreased nuclear transport of EGFR and inhibited caveolin-1- and DNA-PK-phosphorylation. Knockdown of src by specific siRNA blocked EGFR phosphorylation at Y845, phosphorylation of caveolin-1 at Y14 and abolished EGFR transport into the nucleus and phosphorylation of DNA-PK. Consequently, both knockdown of src by specific siRNA and also inhibition of src activity by PP2 resulted in an enhanced residual DNA-damage as quantified 24 h after irradiation and increased radiosensitivity.</p>", "<title>Conclusion</title>", "<p>Src kinase activation following irradiation triggered caveolin-1 dependent EGFR internalization into caveolae. Subsequently EGFR shuttled into the nucleus. As a consequence, inhibition of internalization and nuclear transport of EGFR blocked radiation-induced phosphorylation of DNA-PK and hampered repair of radiation-induced double strand breaks.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>KD, CM and RK performed experiments and interpreted data; the authors contribution to this research are reflected in the order shown. HPR supervised all aspects of this research. KD and HPR prepared the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported by grants from Deutsche Forschungsgemeinschaft (DI 402/9-1) and Deutsche Krebshilfe (No. 106401).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Radiation induced caveolin-1 linked EGFR internalization is triggered by src kinase</bold>. Confluent A549 cells were irradiated with 4 Gy (A). At the time points given, src protein was immune-precipitated from cytoplasmic protein fraction. Proteins were separated by SDS-PAGE and after blotting the protein amounts of src, caveolin1 and EGFR were quantified. The same procedure was applied after cell stimulation with EGF (B). Phosphorylation of EGFR at the tyrosine No. 845, 992 and 1173 was quantified with help of specific antibodies following a standard western procedure. Equal protein amounts for immune-precipitation were documented by showing actin expression within aliquots of input proteins. (C). Protein expression was quantified by densitometry and shown as fold-induction relative to untreated control. The mean protein expression derived from three experiments was given below each band.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Stabilization of caveolin1/EGFR complex in cytoplasm after incubation with EGFR inhibitory antibody Erbitux</bold>. Confluent A549 cells were treated with human IgG or EGFR inhibitory antibody Erbitux at a concentration of 30 nM for 1 h. Subsequently cells were irradiated with 4 Gy and cytoplasmic and nuclear proteins were isolated at time points given. Proteins were separated by SDS-PAGE and after blotting EGFR protein was quantified with help of a specific antibody. Experiments were performed three times; shown are representative results. Equal protein input for immune-precipitation was documented by showing actin expression within aliquots of input proteins. Expression of specific proteins was quantified by densitometry and shown as fold-induction relative to untreated control.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Inhibition of nuclear EGFR transport and phosphorylation of DNA-PK by src inhibitor PP2</bold>. Confluent A549 cells were treated with src inhibitor PP2 at a concentration of 100 nM for 1 h. Subsequently cells were irradiated with 4 Gy and nuclear proteins were isolated at the time points given. Proteins were separated by SDS-PAGE and after blotting protein amounts were quantified by help of specific antibodies. Expression of specific proteins was quantified by densitometry, normalized to lamin B1 and shown as fold-induction relative to untreated control. Experiments were performed three times; shown are representative results.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Inhibition of EGFR transport into the cytoplasm/nucleus by src siRNA</bold>. Exponentially growing A549 cells were incubated either with control- or src-specific siRNA for 72 h at a concentration of 30 nM. Subsequently confluent cells were irradiated with 4 Gy and cytoplasmic (A) and nuclear proteins (B) were isolated at the time points given. Corresponding results were presented for FaDu cells (C and D). Expression of specific proteins was quantified by densitometry, normalized either to actin or lamin B1 and shown as fold-induction relative to untreated control. Experiments were performed three times; shown are representative results.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Inhibition of DNA-repair and clonogenic survival by src siRNA or src inhibitor PP2</bold>. A549 cells were either treated with src siRNA (72 h) (A/C) or with src inhibitor PP2 (1 h) (B/D). Subsequently cells were irradiated with 2, 4 and 6 Gy and after 24 h cells were fixed. Residual damage was visualized by incubation with γH₂AX antibody (A/B). Each bar represents the mean ± SE of residual repair foci positive for γH₂AX per cell nucleus. For each data point 300 nuclei were evaluated. Asterisks indicate significant differences (Student's t-test * p &lt; 0.05). For colony formation assay cells pretreated either with src siRNA (C) or PP2 (D) were irradiated and seeded at a density of 500 cells per 78 cm²dish. After 10 days colonies were fixed and stained. Surviving fractions were calculated on the basis of colony counts and plating efficiency. Each value represents the mean of three independent experiments. Differences were considered as statistically significant for p &lt; 0.05 (t-test) and were marked with an asterisk *.</p></caption></fig>" ]

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[ "<graphic xlink:href=\"1476-4598-7-69-1\"/>", "<graphic xlink:href=\"1476-4598-7-69-2\"/>", "<graphic xlink:href=\"1476-4598-7-69-3\"/>", "<graphic xlink:href=\"1476-4598-7-69-4\"/>", "<graphic xlink:href=\"1476-4598-7-69-5\"/>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Malaria remains one of the world's most deadly diseases. However, efforts to control this disease are hampered by drug resistance in parasites, insecticide resistance in mosquitoes, and the lack of an effective vaccine ##REF##15163175##[1]##. Malaria parasites (<italic>Plasmodium sp</italic>) have an intricate and complex life cycle in vertebrate (intermediate) and invertebrate (definitive) hosts, and the multiple developmental forms of <italic>Plasmodium</italic> species are potential targets of distinct antiparasite molecules. For example, the mosquito-stage parasites can be disrupted by natural and engineered peptides, such as the antimicrobial peptides (AMP) cecropin, magainin, defensin, scorpine and cecropin-like peptides ##REF##2759705##[2]##–##REF##17376436##[6]##. However, all the AMPs tested thus far fall short of the requirements for an effective anti-plasmodial molecule since they require high concentrations both <italic>in vivo</italic> and <italic>in vitro</italic> to be effective. These results support the search for alternative molecules, including novel peptides with lower effective doses.</p>", "<p>Antimicrobial peptides kill bacteria by interfering with metabolism, targeting cytoplasmic components and disrupting membranes ##REF##12615953##[7]##. Lipid composition of the target cell membrane is a determining factor in the activity and selectively of AMPs for avoiding damage to host cells ##REF##11897590##[8]##, ##UREF##1##[9]##. Peptides with parasiticidal effects on sporozoites could be utilized to target parasites within their vector mosquitoes. These same peptides, being harmless to vertebrate hosts, would have a broader application in malaria prophylaxis by targeting circulating sporozoites and preventing the establishment of infection. With this aim, we used the avian malaria parasite, <italic>Plasmodium gallinaceum</italic>, as a model system to search for drugs with both properties: toxicity to parasites and harmless to vertebrates and invertebrate hosts. We report here that a synthetic angiotensin II-related, vertebrate-inactive peptide (VC5) kills <italic>P. gallinaceum</italic> sporozoites <italic>in vitro</italic> and <italic>in vivo</italic> and discuss possible applications of this finding in the development of novel malaria control strategies.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Peptide synthesis, purification and characterization</title>", "<p>Angiotensin II (ang II)-related peptides were synthesized by a solid-phase method using the t-Boc strategy on a chloromethylated resin ##UREF##5##[16]##, with substitutions varying from 0.5–0.8 mequiv/g. The following side-chain protected Boc-amino acids were employed from Bachem Inc. (Torrance, CA): Arg(Tos), Asp(OcHex) and (OFm), His(Tos), Lys(Fmoc) and Tyr(2-Cl-Bzl). Ang ll reagents and solvents were of analytical grade and used from freshly opened containers without any further purification. The N^α-terminal protections were removed with 50% TFA in methylene chloride in the presence of 2% anisole for 20 min. Couplings were done using 2.5-fold excess of 1,3-diisopropylcarbodiimide/N-Hydroxybenzotriazole (DIC/HOBt) in methylene chloride-dimethylformamide (DCM-DMF) (1∶1, v/v). Both steps were monitored by the ninhydrin test ##REF##5443684##[17]##. Couplings times were 1–2 h, and when needed, recouplings of 1 h were done using 2.5-fold excess o-benzotriazol-1-yl-N,N,N′,N′-tetramethyluronium tetrafluoroborate (TBTU) in the presence of excess N-N′-diisopropylethylamine (DIEA) in methylene chloride-1-methyl-2-pyrrolidone (DCM-NMP) (1∶1, v/v) ##REF##15680478##[18]##. Boc-His (Tos) DCHA (<italic>dicyclohexylammonium salt</italic>) incorporation employed a 1.5-fold excess of TBTU in presence of excess of diisopropylethylamine (DIPEA). Acetylations were performed with 50% acetic anhydride in DMF for 15 min when required. The orthogonal protection of the side chain of the aspartic acid (OFm) and lysine (Fmoc) residues were used in order to allow the lactam bridge formation with the peptide still attached to the resin ##UREF##6##[19]##. After washes with DCM, DMF, the OFm/Fmoc groups were removed by 20% piperidine in DMF. The peptide-resin was cyclized by reaction with 3.0-fold excess of benzotriazol-l-yl-oxy-tris-(dimethylamino)phosphonium hexa-fluorophosphate (BOP) in the presence of excess DIEA in 20% DMSO/NMP. After washing the cyclization was repeated every 20 minutes. The reaction was followed by the Kaiser ninhydrin test ##REF##5443684##[17]##. The dry protected peptidyl-resin was exposed to anhydrous hydrogen fluoride (HF) in the presence of 5% anisole and of 5% dimethylsulfide for 75 min at 0°C. HF excess and scavenger were eliminated under high vacuum. The crude peptides were precipitated with anhydrous diethyl ether, separated from ether-soluble by filtration, extracted from the resin with 5% acetic acid in H₂O and lyophilized. The crude lyophilized peptides were purified in two steps (triethylammonium phosphate (TEAP) pH = 2.25 and 0.1% TFA) by preparative Reversed Phase-High Performance Liquid Chromatographic (RP-HPLC) on a Waters Associates system (Model Prep 4000), using linear gradients (slope 0.33% B/min). Briefly, they were loaded on a Vydac C₁₈ (25×250 mm, 15 μm particle size, 300Å pore size) preparative RP-HPLC column at a flow rate of 7.0 ml/min and eluted with TEAP (pH = 2.25)/CH₃CN), and detection at 220 nm. Selected fractions were collected and converted to the Trifluoroacetic acid (TFA) salt by loading on a preparative column as mentioned above and eluted using a linear gradient (slope 0.33 or %B/min) containing a mixture of solvents A [0.1% TFA/H₂O] and B [0.1% TFA in CH₃CN/H₂O (75:25)] at a flow rate of 7.0 ml/min. Selected fractions containing the purified peptide were pooled and lyophilized ##REF##18008380##[20]##. Analytical RP-HPLC was performed on a Waters Associated system using a linear gradient of 5–95% B for 30 min, using buffer system: A = 0.1% TFA/H₂O and B = 0.1% TFA-60% CH₃CN/H₂O, at 1.5 ml/min, on a Beckman C₁₈ column (4.6×150 mm, 5 μm particle size, 300Å pore size) at 215 nm. Capillary zone electrophoresis was done by using a Waters System, model CIA (Capillary Ion Analyzer) by hydrostatic injection in 25 seconds, utilizing Phosphate buffer pH 2.50, λ = 214 nm, silica capillary (75 μm×60 cm), voltage 20 kV at 30°C. Amino acids analyses were made by the ninhydrin method using an automatic analyzer Beckman, model System 6300. Peptides were hydrolyzed (1 mg) using 1 ml of HCl 6 M, in the presence of phenol 0.08 ml to 5% in water at 110°C for 72 hours in atmosphere of N₂. After hydrolysis, the material was vacuum-concentrated and dissolved in 0.2 M sodium citrate, pH 2,2, filtered through Millipore (pore 0,45 μm) before being injected in the analyzer. The molar relationship of the amino acids was established using the concentration unitary of the closest amino acid of the average for all the residues ##UREF##7##[21]##. The peptides were analyzed on a Micromass spectrometer model TofSpec SE using voltage = 20 KV, suppression at 500 AMU, Mode Reflectron (10 KV) and the α-ciano-4-hydroxycinnamic acid solid matrix. The spectrometer was periodically calibrated with angiotensin I and AII. Purified peptides were characterized (##TAB##1##Table 2##), by RP-HPLC (Reversed-Phase Liquid Chromatography), CE (Capillary Electrophoreses), AAA (Amino acid Analyses) and MS (Mass Spectroscopy). The characterization results showed that the amino acid proportion were in agreement with the expected values by AAA (data not shown), purity in HPLC and CE showed to be above 95%, and had appropriate molecular weights by mass spectroscopy. (##TAB##1##Table 2##).</p>", "<title>Agonistic VC5 activity to angiotensin II</title>", "<p>Peptide agonist bioassays were performed in isolated guinea pig, rat and chicken ilea comparison the synthetic peptides with ang II. Male guinea pigs (weight: 200–250g) and chickens (30–40g) were sacrificed and the terminal portions of the ileum removed and washed several times with Tyrode solution (8 g NaCl; 0.2 g CaCl₂; 0.1 g MgCl₂; 0.2 g KCl; 1 g NaHCO₃; 0.05 g NaHPO₄ and 1g of glucose per liter of water). After 15 minutes in nutritive solution at room temperature, the ileum was sectioned (4.5 cm) and fixed in the perfusion chamber with 5 ml of aerated Tyrode solution bubbled with a gas mixture of 95% O₂/5% CO₂ at 37±0.5°C. Isotonic contractions were registered by a chimograph (Palmer), under a resting load of 1g. VC5 was dissolved in H₂O (1.0 mg/ml), diluted in 0.9% NaCl and added to the perfusion chamber. After 90 seconds, the preparation was washed with Tyrode solution. The measurements of agonist activity were done in triplicate.</p>", "<p>Blood pressure assays were conducted on female rats (250–300 g) anesthetized with a ketamine-xylazine (Ketamine 80 mg/kg and Xylazine 8 mg/kg) solution and maintained by artificial breathing. A catheter was inserted into the carotid artery and used to register the blood pressure with a pressure transducer (Hewlett-Packard, model 1280C-02), amplifier (Hewlett-Packard, model 8805B) and chart recorder (ECB, model RB102). Isotonic solutions of the peptides were injected in the femoral vein using a polyethylene catheter inserted (##TAB##1##Table 2##).</p>", "<title>Hemolytic activity</title>", "<p>Hemolytic activity was evaluated on fresh human erythrocytes washed three times with phosphate-buffered saline (PBS: 10 mM Na₂HPO₄, 1.8 mM K₂-HPO₄, pH 7.4, containing 140 mM NaCl and 2.7 mM KCl) ) ##REF##16235231##[22]##. Serial dilutions of the peptides with concentrations varying between 0.19–100 μM were incubated in Eppendorf tubes with a suspension of 0.4% erythrocytes in PBS. After 1 h at 37°C, the test tubes were centrifuged at 300g for 5 min at 5°C. Fifty microliter aliquots of the supernatants were transferred to 96-well plates and hemolysis was monitored at 405 nm using a microtiter plate reader. Negative and positive controls were prepared in PBS and in PBS supplemented with 0.1% SDS, respectively. Ang ll of the experiments was performed in triplicate.</p>", "<title>Serum stability</title>", "<p>Twenty microliters of an aqueous peptide stock solution (10 mg/ml) were added to 1 ml of 25% pooled non-heat inactivated human serum in PBS and incubated at 37°C. Aliquots of 50 μl were added to 5 μl of TFA at time intervals (0, 10, 20, 30, 60 and 120 minutes). The resulting mixtures were kept at 5°C for 10 min and then centrifuged at 300×g for 5 min. Twenty microliters of the supernatants were injected in a LC/ESI-MS equipment and the components separated using a linear gradient of acetonitrile in acidified water (0.1% TFA) at a flow rate of 0.4 ml/min from 5% to 95% B (0.1% TFA/60% CH3CN/H2O) in 30 min. Peptide consumption mentored as an area decrease under the corresponding peak in the chromatogram allowed the evaluation of the stability of the peptide in serum. All the experiments were performed in triplicates.</p>", "<title>Mosquito rearing and maintenance of the parasite life cycle</title>", "<p>The RED strain of <italic>Aedes aegypti</italic> is highly susceptible to <italic>P. gallinaceum</italic>\n##REF##7931905##[23]## and was used in all experiments. Mosquitoes were reared using standard laboratory procedures ##UREF##8##[24]##.</p>", "<p>An aliquot of frozen chicken blood infected with <italic>P. gallinaceum</italic> strain 8A was obtained from A. Krettli (René Rachou Institute of Research, FIOCRUZ, MG, Brazil). This sample was used to inoculate and establish initial infections in chickens. All subsequent infections of chickens and mosquitoes were accomplished by feeding mosquitoes on chickens.</p>", "<title>Mosquito injection</title>", "<p>Each synthetic peptide was injected (0.5 μl of 60 μM) into a group of naturally-infected mosquitoes seven days after a blood meal, at a time when sporozoites were anticipated to be present in the hemolymph. The same volume of PBS was injected into a control group. Injections were performed using a finely-drawn calibrated glass microcapillary tube to deliver the solutions into the thorax. After 24 hours, individual pairs of salivary glands were dissected, homogenized in 10 μl PBS, placed on a hemacytometer and the sporozoites counted using phase-contrast microscopy. This procedure allowed the examination of the whole salivary gland for sporozoites ##REF##11220756##[25]##. All fields of the hemacytometer were examined thoroughly in low parasites densities samples and five fields were averaged for high parasite densities samples.</p>", "<title>Inactivation of sporozoite infectivity</title>", "<p>\n<italic>In vitro</italic> experimental treatments were performed with 50–500 sporozoites isolated from salivary glands 13 days after mosquito infection. Parasites were mixed with synthetic peptides to final concentration of 60 μM. After 1-hour incubation at room temperature, the samples were injected intravenously into two-days-old chickens. Blood smears were taken daily from each chicken (6 to 25 days after inoculation), stained with Giemsa after methanol fixation, and examined by light microscopy at magnification of 1000x. The pre-patent period was calculated as number of days between inoculation and detection of circulating parasites in the chickens.</p>", "<title>Effects of Angiotensin I (ang I,) Angiotensin II (ang II) and Vaniceres 1-6 (VC1-6) on salivary gland-derived Plasmodium gallinaceum sporozoites</title>", "<p>Three thousand <italic>P. gallinaceum</italic> mature sporozoites were recovered from salivary glands and incubated with 40 μM digitonin, 60 μM ang I, 60 μM ang II, 60 μM VC1-6 or PBS at room temperature. Cell membrane integrity was then monitored at 10 minutes intervals by adding propidium iodide to the treated parasites.</p>", "<title>Scanning electron microscopy</title>", "<p>Freshly-purified sporozoites from salivary glands were incubated in 50 μl PBS at room temperature in the absence or presence of 60 μM ang II and 60 μM VC5. After incubation, 10 μl aliquots were separated and fixed overnight with 2.5% glutaraldehyde in 0.1 M cacodylate buffer, pH 7.2. The glutaraldehyde-fixed samples were rinsed three times in PBS and post-fixed in 1% osmium tetroxide solution in 0.8% potassium ferrycianide in 0.1 M caccodylate buffer pH 7.2 for two hours, and then washed three times in PBS. The samples were dehydrated in ethanol, dried in critical point device with CO₂ method, mounted in special stubs, coated with platinum particles and analyzed by SEM (JEOL JSM 5600).</p>", "<title>Toxicity assays of VC5 in chicken</title>", "<p>The toxic effect of VC5 was evaluated in chickens. Six animals per cage weighing 30–40 g each were housed in groups of 10 in our institutional animal care facility and allowed to adapt for seven days prior to the onset of experiments. Animals were maintained in a temperature-controlled environment (21±2°C), with free access to water and food. All experiments were carried out in accordance with the guidelines of the Institutional Ethics Review Committee (Colégio Brasileiro de Experimentação Animal–COBEA) and Animal Care of the Institute of Biomedical Sciences (Comissão de ética em experimentação animal–CEEA)–University of São Paulo, protocol #133.</p>", "<title>Statistical analysis</title>", "<p>The Kruskal-Wallis test, Fisher's Exact test, chi-square test and Mann-Whitney U test (GraphPad InStat version 3.00 for Windows 95, GraphPad Software, San Diego California USA, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.graphpad.com\">www.graphpad.com</ext-link>) was used to assess the statistical significance of the differences between control and peptides injected groups.</p>" ]

[ "<title>Results</title>", "<title>Ang I, ang II and VC1-VC6 peptides reduce the number of P. gallinaceum sporozoites in salivary glands</title>", "<p>Injection of ang II (5–60 μM) in the hemolymph of <italic>P.gallinaceum</italic> infected <italic>Ae. aegypti</italic> reduces sporozoites accumulation in the salivary glands and does not affect mosquito survival (Supporting Materials, ##SUPPL##0##Figure S1## and ##SUPPL##1##Figure S2##). Following this initial observation, synthetic ang II related peptides were designed and tested for their anti-parasite activities. Injection of 0.5 μl of synthetic peptides VC1-VC 6, ang I and ang II (at 60 μM concentration) in infected mosquitoes resulted in reduced numbers of sporozoites in their salivary glands when compared with controls injected with either PBS or ang I (##FIG##0##Figure 1##). VC1 showed the least effect on accumulation of sporozoites, while ang II and VC5 where the most effective reducing by 88% (<italic>p</italic>&lt;0.0001) and 76% (<italic>p</italic>&lt;0.001), respectively, the number of parasites compared to control infected mosquitoes. Additionally, each peptide was tested for its anti-sporozoite activity in three independent experiments and only ang II and VC5 were consistently effective (<italic>p</italic>&lt;0.005) in reducing the number of salivary glands parasites.</p>", "<title>Ang I, Ang II and VC1-VC6 increase sporozoite membrane permeability</title>", "<p>Mature sporozoites were recovered from salivary glands and incubated <italic>in vitro</italic> with ang II or VC peptides. Cell membrane integrity was monitored at 10 minutes intervals by adding propidium iodide to the treated parasite samples (##FIG##1##Figure 2##). Sixty-four percent of the sporozoites showed nuclear fluorescence indicative of cell damage after 10 minutes incubation with 60 μM ang II, and 78% showed fluorescence after 30–60 minutes. VC1, VC2, VC3, VC4 and VC6, respectively, resulted in 73%, 51%, 51%, 64% and 38%, sporozoites with fluorescent nuclei after 1 hour incubation. VC5 resulted in a kinetic profile similar to that obtained with ang II. Incubations with 60 μM VC5 yielded 51%, 67% and 78% fluorescent sporozoites at 10, 20 and 60 minutes, respectively. Fluorescence accumulation in the nuclei was observed in only 47% of the sporozoites treated with 60 μM ang I after 1 hour incubation.</p>", "<p>Further evidence of the association of ang II and VC5 peptides with the sporozoite cell membrane was obtained by scanning electron microscopy (##FIG##2##Figure 3##). Sporozoites incubated with VC5 show surface damage evidenced by cytoplasmic protrusions, and this is consistent with the propidium iodide staining of their nuclei (##FIG##1##Figure 2##).</p>", "<title>Parasitological evidence of inactivation of salivary gland sporozoites by VC5</title>", "<p>Vertebrate-infective parasites harvested from mosquito salivary glands were incubated <italic>in vitro</italic> with VC5 and then inoculated into chickens. Both the infection rates (15%) and the pre-patent periods (7–21 days) were affected (##TAB##0##Table 1##). Only four of nine chickens challenged with VC5-treated sporozoites became infected, and those showed an increased pre-patent period, 7 to 21 days, compared to six days post-infection in the control group. Parallel incubations <italic>in vitro</italic>, without VC5, under identical conditions did not diminish the infectivity of parasites, as demonstrated by the infection of 100% of chickens challenged with these control samples. This preliminary experiment further support that VC5 interacts with malaria parasites cell membrane indicates that this interaction results in non-infectious sporozoites.</p>", "<title>Agonistic activities of synthetic VC1-VC6 and ang II</title>", "<p>In addition to applications of VC5 and ang II to target sporozoites in the vector mosquitoes, these peptides also could be useful to block parasite development in vertebrate hosts. Angiotensin II is a well-known direct activator of smooth muscle in the vasculature, constricting arteries and veins and increasing blood pressure. Assays of ileum contraction, commonly used to determine vasoconstriction activities, were utilized to test agonistic activities of the peptides on guinea pig (GPI), chicken ileum (CI) and rat uterus (RU) preparations. When compared with ang II (100% activity), VC1 had 5%, 0% and 2.0% of agonist activity on GPI, CI and RU, respectively (##TAB##1##Table 2##). VC2 had 10%, 0% and 2.9% of activity for GPI, CI and RU. VC3, VC4, VC5 and VC6 activities were less then 0.3%, consistent with the interpretation that the VC1-6 peptides have low or no agonistic action.</p>", "<title>Stability and absence of hemolytic activity of ang II and VC1-VC6</title>", "<p>Hemolytic activity was evaluated using fresh human erythrocytes harvested and incubated with serial dilutions of the peptides, and concentrations varying between 0.19–100 μM. Hemolysis was not detected even at the higher concentrations (##TAB##1##Table 2##). Ang II and VC1-VC6 analogue stability in blood was evaluated in non-heat inactivated human serum, demonstrating that the peptides were degraded within 30 minutes of incubation, as determined by LC/ESI-MS (data not shown).The quick clearing of the molecules, low or no agonist activity and the absence of hemolysis caused by the peptides are indicative of their general non-toxicity to vertebrates.</p>" ]

[ "<title>Discussion</title>", "<p>A recent worldwide trend of attention to malaria control has come with accompanying financial support directed towards the development of new drugs, anti malarial vaccines and alternatives for vector population management ##UREF##2##[10]##. Technical developments such as the sequencing of the genomes of malaria parasites ##REF##12368864##[11]## and the vector mosquito <italic>Anopheles gambiae</italic>\n##REF##12364791##[12]##, and the ability of generating parasite-resistant genetically-modified mosquitoes ##REF##16485025##[13]## have been heralded as keystones for the development of novel malaria control tools. Our efforts to develop peptides with anti-malarial activities led us to determine serendipitously that angiotensin II affects negatively the development of malaria parasites. Here we report our initial examination of the mechanisms that result in such effect.</p>", "<p>Ang II is derived from the constitutively-produced angiotensinogen, a peptide of the serpin family released into the circulation mainly by the vertebrate liver. When blood pressure decreases in the kidneys the enzyme rennin is produced and cleaves the peptide bond between the leucine (Leu) and the valine (Val) residues creating the ten amino acid peptide angiotensin I (ang I). Ang I has little biological effect and it is processed further to ang II by removal of two of the terminal amino acid residues. Ang II plays an endocrine role in the regulation of blood pressure, fluid and electrolyte homeostasis. In addition, studies have shown that numerous tissues and organs contain their own locally-generated angiotensin products that exhibit tissue-specific activities ##UREF##3##[14]##. Therefore, the biological activities of ang II preclude its utilization as an anti-malarial drug. Modifications of the molecular structure of ang II were then considered, and we designed six related peptides (VC1-VC6) that were further analyzed. VC5 displayed no agonistic effects and killed malaria sporozoites in the conditions utilized in our experiments. The mechanism of parasite killing was further investigated by biochemical and morphological applications. VC5 and ang II kill <italic>P. gallinaceum</italic> sporozoites by disruption of their plasma membrane. Moreover, these peptides have no similar effect upon vertebrate cells. The observed specificity may be explained by the markedly different lipid compositions of <italic>Plasmodium</italic> and vertebrate cells plasma membranes ##UREF##4##[15]##. VC5 is a promising molecule to be tested for malaria prevention and chemotherapy.</p>", "<title>Final Remarks</title>", "<p>Our research shows that angiotensin-related peptides affect malaria parasite survival. These peptides were engineered successfully to abolish their agonist functions while retaining parasiticidal activity, opening new research possibilities. Presently, the design, synthesis, and biological evaluation of new analogues are in progress in our laboratories with the ultimate goal of generating further information on the structural requirements for ang II analogues bioactivity and conformation. These studies focus on bridge-length optimization and amino acid chirality that may improve molecular stability against protease presents on plasma and result in longer time of action. Additional research is necessary to further characterize the mechanism of action of these peptides to kill <italic>Plasmodium</italic> parasites and direct future efforts in drug development that can contribute to the control of malaria.</p>" ]

[]

[ "<p>Conceived and designed the experiments: CM VXOJ MAF RNP AM PFP MLC. Performed the experiments: CM VXOJ MAF RNP. Analyzed the data: CM VXOJ MAF RNP AM PFP MLC. Contributed reagents/materials/analysis tools: AM PFP MLC. Wrote the paper: CM VXOJ MAF RNP AM PFP MLC.</p>", "<p>\n<italic>Plasmodium</italic> species are the causative agents of malaria, the most devastating insect-borne parasite of human populations. Finding and developing new drugs for malaria treatment and prevention is the goal of much research. Angiotensins I and II (ang I and ang II) and six synthetic related peptides designated Vaniceres 1-6 (VC1-VC6) were assayed <italic>in vivo</italic> and <italic>in vitro</italic> for their effects on the development of the avian parasite, <italic>Plasmodium gallinaceum.</italic> Ang II and VC5 injected into the thoraces of the insects reduced mean intensities of infection in the mosquito salivary glands by 88% and 76%, respectively. Although the mechanism(s) of action is not completely understood, we have demonstrated that these peptides disrupt selectively the <italic>P.gallinaceum</italic> cell membrane. Additionally, incubation <italic>in vitro</italic> of sporozoites with VC5 reduced the infectivity of the parasites to their vertebrate host. VC5 has no observable agonist effects on vertebrates, and this makes it a promising drug for malaria prevention and chemotherapy.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We thank Dr. Antonio G. de Bianchi, Dr Carlos E. Winter, Dr. Osvaldo Marinotti and Dr Anthony A. James for helpful comments, suggestions and manuscript revision. We also would like to thank Dr. Lincoln Suesdek Rocha, for the statistical analyses.</p>" ]

[ "<fig id=\"pone-0003296-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003296.g001</object-id><label>Figure 1</label><caption><title>Numbers of sporozoites in salivary glands of angiotensin I-, angiotensin II- or synthetic peptide-treated <italic>Ae. aegypti.</italic>\n</title><p>At day 7 post-infection 0.5 μl of ang I (60 μM), ang II (60 μM), VC1 (60 μM), VC2 (60 μM), VC3 (60 μM), VC4 (60 μM), VC5 (60 μM), VC6 (60 μM) and PBS (control) were microinjected intrathoracically on anesthetized <italic>Ae.aegypti</italic>. Salivary glands were dissected 24 hours after the microinjection and sporozoites counted. Kruskal–Wallis tests indicated significant effects (<italic>p</italic>&lt;0.0001 and <italic>p</italic>&lt;0.001) of the peptides in the number of salivary glands sporozoites for ang II and VC5, respectively. VC1, VC2, VC3, VC4, VC6 did not significant effect (<italic>p</italic>&gt;0.05).</p></caption></fig>", "<fig id=\"pone-0003296-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003296.g002</object-id><label>Figure 2</label><caption><title>Effects of peptides on membrane permeability of mature sporozoites were incubated with digitonin, PBS, 60 μM of ang I, ang II, VC1, VC2, VC3, VC4, VC5 or VC6.</title><p>After defined intervals at room temperature, propidium iodide was added and the sporozoites were examined by fluorescent microscopy. A, sporozoites in phase (left) and fluorescent (right) microscopy; B, kinetic curves of membrane fluorescence. Results are the mean of three independent experiments, and bars represent standard errors of the mean. The data were statistical analyzed (60 min) using Fisher's test showing that ang II, VC1 and VC5 are significant different (<italic>p</italic>&lt;0.02) when compared with control. On the other hand, ang I, VC2, VC3, VC4 and VC6 are not significantly different (<italic>p</italic>&gt;0.05).</p></caption></fig>", "<fig id=\"pone-0003296-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003296.g003</object-id><label>Figure 3</label><caption><title>Scanning electron microscopy of salivary gland-derived <italic>P. gallinaceum</italic> sporozoites.</title><p>Parasites were incubated with PBS (A, control), angiotesin II (B) and VC5 (C and D). Note the smooth surface of the non-treated sporozoites (PBS-control) with the rough surface of the drug-treated parasites (ANG II and VC5).</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003296-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003296.t001</object-id><label>Table 1</label><caption><title>Infectivity for chicks of <italic>P. gallinaceum</italic> spzs from salivary glands after incubation with 60 μM of VC5.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Inoculum size<xref ref-type=\"table-fn\" rid=\"nt101\">a</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<underline>Chicks</underline> n° infected/n° injected</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Prepatent period<xref ref-type=\"table-fn\" rid=\"nt102\">b</xref> (Days)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>VC5 (60</bold> μ<bold>M)</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1/3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">500</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3/5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7, 12, 21</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>PBS</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5/5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">500</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1/1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003296-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003296.t002</object-id><label>Table 2</label><caption><title>Effects of peptides on vertebrate tissues</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Peptide</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Compound Name<xref ref-type=\"table-fn\" rid=\"nt103\">a</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HPLC<xref ref-type=\"table-fn\" rid=\"nt104\">b</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CZE<xref ref-type=\"table-fn\" rid=\"nt105\">c</xref>\n</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">MS<xref ref-type=\"table-fn\" rid=\"nt106\">d</xref>\n</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">Agonist Activity<xref ref-type=\"table-fn\" rid=\"nt107\">e</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hemolytic Activity</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Calculated</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Measured</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Guinea Pig Ileum</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rat Uterus</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rat blood pressure</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chicken Ileum</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ang II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">—</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1046-2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1046.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VC 1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cyclo(0-1a)[Asp⁰, endo-(Lys^1a)]-All</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1271.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1272</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VC 2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">[Asp⁰, endo-(Lys^1a)]-All</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1289.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1289</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VC 3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cyclo(1a-2a)[endo-(Asp^1a), endo-(Lys^2a)]-All</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1271.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1272</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VC 4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">[endo-(Asp^1a), endo-(Lys^2a)]-All</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1289.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1291</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&lt;0.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VC 5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cyclo(2a-3a)[endo-(Asp^2a), endo-(Lys^3a)]-All</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1271.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1272</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&lt;0.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&lt;0.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VC 6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">[endo-(Asp^2a), endo-(Lys^3a)]-All</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1289.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1289</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&lt;0.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">neg</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

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[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003296.s001\"><label>Figure S1</label><caption><p>Survival of mosquitoes injected with different ang II concentrations. Ae.aegypti mosquitoes (10 females) were injected intrathoracically (0.5 μl) of ang II at 10 μM, 20 μM, 50 μM, 60 μM, 100 μM and 200 μM. After 24 hour the survival of mosquitoes was scored. Chi-square test indicated that no significant effects of the ang II (<italic>p</italic>&gt;0.5) in mosquito survival for all the experiments. Results are the mean of three independent experiments (20 mosquitoes/group), and bars represent standard errors of the mean.</p><p>(0.18 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003296.s002\"><label>Figure S2</label><caption><p>Numbers of sporozoites in salivary glands of angiotensin I-, angiotensin II- or synthetic peptide-treated Ae. aegypti. At day 7 post-infection 0.5 μl of ang II at 5 μM, 30 μM, 40 μM, 50 μM, 60 μM or PBS (control) were injected intrathoracically in anesthetized <italic>Ae.aegypti</italic>. Salivary glands were dissected 24 hours after the microinjection and sporozoites counted. Mann-Whitney tests indicated significant effects (<italic>p</italic>&lt;0.0001) of the peptides in the number of salivary glands sporozoites at 60 μM concentration.</p><p>(0.48 MB TIF)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label>a</label><p>The chicks were i.v. inoculated after 1 hour incubation of spzs and VC 5 or PBS.</p></fn><fn id=\"nt102\"><label>b</label><p>Pre-patent period is 6 days.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><label>a</label><p>In convention with IUPAC-IUB, Biochemistry 1967, 6(1), 362-368.</p></fn><fn id=\"nt104\"><label>b</label><p>Percent purity determined by RP-HPLC using buffer systems: A = 0.1% TFA/H₂O and B = 60% CH₃CN/0.1% TFA in H₂O with a gradient slope of 3% B/min, at flow rate of 1,5 ml/min on a Beckman C₁₈ column (4,6×150 mm, 5 μm particle size, 300 Å pore). Determination at λ = 214 nm.</p></fn><fn id=\"nt105\"><label>c</label><p>CZE was done using a Waters System, model CIA (Capillary Ion Analyzer) by hydrostatic injection in 25 seconds, utilizing Phosphate buffer pH 2,50, silica capillary (75 μm ID×60 cm length), field strength of 20 kV at temperature 30°C. Determination at λ = 214 nm.</p></fn><fn id=\"nt106\"><label>d</label><p>Molecular weights were determined by Maldi-TOF using a α-ciano-4-hydroxicinamic acid matrix.</p></fn><fn id=\"nt107\"><label>e</label><p>Biological activities of VC1-6 were compared to those of angiotensin II on the guinea pig ileum, rat uterus, rat blood pressure and chicken ileum. The hemolytic activity of angiotensin II and its analogues was measured at a peptide concentration ranging from 0.19 to 100 μM.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work is supported by Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP). A.M., C.M. and M.L.C. are fellows from CNPq.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003296.g001\"/>", "<graphic xlink:href=\"pone.0003296.g002\"/>", "<graphic xlink:href=\"pone.0003296.g003\"/>", "<graphic id=\"pone-0003296-t001-1\" xlink:href=\"pone.0003296.t001\"/>", "<graphic id=\"pone-0003296-t002-2\" xlink:href=\"pone.0003296.t002\"/>" ]

[ "<media xlink:href=\"pone.0003296.s001.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003296.s002.tif\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Investigations on the consequences of endosymbionts on their host's fitness have revealed that some of them exhibit variable effects, blurring the distinction between mutualism and parasitism. It is now admitted that symbionts are deeply involved in the evolutionary process of their hosts and that variations in symbiont genotypes may trigger more important differences in host life history traits than variations of the host genotypes themselves ##REF##16120675##[1]##. Thus, the entity that undergoes selection is clearly the extended phenotype of symbionts in their host. Within such a conceptual framework, the studies that focus on an understanding of host population dynamics need to consider symbiosis as a central parameter. Of the endosymbionts known to exhibit various effects on their host fitness, <italic>Wolbachia</italic> are the most prevalent in arthropods. The diversity of the interactions between <italic>Wolbachia</italic> and their hosts is mainly illustrated by the various strategies these endosymbionts exhibit in order to secure their vertical transmission. Hence, in some host species <italic>Wolbachia</italic> decrease the fitness of uninfected individuals (i.e. cytoplasmic incompatibility) while in others they increase female ratio in populations (i.e. parthenogenesis, male-killing and feminization) ##REF##15012323##[2]##, ##REF##9684374##[3]##. As the transmission of <italic>Wolbachia</italic> is vertical, their fitness is directly linked to the fitness of their hosts. Therefore, such situations could be seen as favourable to evolve towards obligate symbiosis and therefore mutualism. However, such obligate <italic>Wolbachia</italic> symbioses have only been described in filarial nematodes and in the parasitic wasp <italic>Asobara tabida</italic>\n##REF##9884329##[4]##, ##REF##11353833##[5]##. In both models, aposymbiotic females failed to produce mature oocytes showing that <italic>Wolbachia</italic> are obligate for reproduction ##REF##9884329##[4]##, ##REF##11353833##[5]##. Other studies have shown that <italic>Wolbachia</italic> may be mutualists by improving development, survival and reproduction of their hosts ##UREF##0##[6]##–##REF##17439303##[10]##. However, these effects can vary over time or with respect to host genotypes and cause continuous evolutionary changes ##REF##16777731##[7]##, ##REF##17439303##[10]##.</p>", "<p>Despite these few examples of dependency or mutualism between <italic>Wolbachia</italic> and their hosts, <italic>Wolbachia</italic> are mostly described as facultative endosymbionts that negatively influence their hosts' life history traits, including body size ##REF##17246430##[11]##, fecundity ##REF##17246430##[11]##–##REF##11128800##[13]##, survival ##REF##11128800##[13]##–##REF##15305172##[15]##, larval competitiveness ##UREF##1##[16]##, male fertility and sperm cyst production ##REF##10790392##[17]## and mating choice ##REF##15347518##[18]##. Recently, Fytrou et al. (2006) ##REF##16618671##[19]## hypothesized that <italic>Wolbachia</italic> may also immunodepress their hosts. Indeed, they observed that <italic>Drosophila</italic> infected by <italic>Wolbachia</italic> showed less encapsulation of parasitic wasp eggs than cured ones. The capacity of <italic>Wolbachia</italic> to interact with the arthropod immune system has also been recently suggested by (i) the discovery of an intracellular sensor of Gram (-) bacteria in <italic>Drosophila</italic> and (ii) the observed modifications of the immune response in <italic>Drosophila melanogaster</italic> and <italic>Aedes albopictus</italic> cell lineages due to the presence of <italic>Wolbachia</italic>\n##REF##17201680##[20]##–##REF##18171476##[22]##. Moreover, molecular evolution studies within <italic>Wolbachia-</italic>infecting insects have revealed that the <italic>Wolbachia</italic> outer membrane protein <italic>wsp,</italic> which has been shown to play a role in filarial nematode infection success ##REF##17241395##[23]##, is under strong positive selection thus suggesting that invertebrate immune response may be an important selection factor for <italic>Wolbachia</italic>\n##REF##12140246##[24]##. In invertebrates, immune cells (i.e. haemocytes) are essential effectors of immunity ##REF##17201680##[20]##. They are responsible for both cellular (encapsulation, phagocytosis etc.) and humoral (antimicrobial peptides, phenoloxydase cascade etc.) responses. <italic>Wolbachia</italic> have been observed within host haemocytes in only one species: the terrestrial isopod <italic>Armadillidium vulgare</italic>\n##UREF##2##[25]##. In light of this observation and also due to the even more central role of haemocytes in crustacean immune systems ##REF##16697916##[26]##, the <italic>A. vulgare-Wolbachia</italic> association appears to be a very pertinent biological model to study the influence of symbiosis on host immunocompetence. In addition, <italic>A. vulgare</italic> is of particular interest because individuals from the same population are mono-infected (to date, no naturally co-infected individuals have been observed) by one of three different strains of <italic>Wolbachia</italic> (<italic>w</italic>VulM, <italic>w</italic>VulC and <italic>w</italic>VulP) ##REF##15138452##[27]##, ##REF##17537593##[28]##. <italic>w</italic>VulP, which has only been identified recently and which is less prevalent than the others, seems to be the result of a recombination event between <italic>w</italic>VulM and <italic>w</italic>VulC suggesting that co-infections do occur but are unstable. This would explain why co-infected individuals are never observed in sampled populations ##REF##17537593##[28]##. Both <italic>w</italic>VulC or <italic>w</italic>VulM are feminizing strains since offspring from sampled <italic>A. vulgare</italic> females are highly female-biased ##REF##15138452##[27]##. <italic>A. vulgare</italic> lineages infected with <italic>w</italic>VulC or <italic>w</italic>VulM are maintained in laboratory for decades showing that the symbiotic transmission and feminizing phenotypes of these two <italic>Wolbachia</italic> strains persist through generations (Bouchon et al., unpublished data). However, despite these similarities, population genetic studies suggest that <italic>w</italic>Vul strains exhibit different strategies ##REF##15138452##[27]##, ##REF##10430591##[29]##. <italic>w</italic>VulC would be the most invading strain able to replace previous <italic>Wolbachia</italic> strains including <italic>w</italic>VulM ##REF##15138452##[27]##, ##REF##10430591##[29]##, whereas <italic>w</italic>VulM would be the resident strain, more locally adapted to host genotypes. As immunocompetence is obviously a primordial parameter in host dynamics, it is thus of great interest to compare the effect of these two <italic>Wolbachia</italic> strains on host immune capacities.</p>", "<p>In the present study, a comparison was made of the extended phenotype of <italic>w</italic>VulC and <italic>w</italic>VulM in <italic>A. vulgare.</italic> To this end, we evaluated in <italic>A. vulgare</italic> individuals infected by <italic>w</italic>VulC or <italic>w</italic>VulM: (i) the titer of <italic>Wolbachia</italic> in ovaries by qPCR (ii) the presence of <italic>Wolbachia</italic> in haemocytes by electronic microscopy, (iii) the density of haemocytes, (iv) the intensity of natural septicaemia (i.e. number of CFU obtained from haemolymph) (v) their survival over a 7 month period. These results were used to detect differences in immunocompetence and survival of <italic>A. vulgare</italic> as a function of <italic>Wolbachia</italic> genotype.</p>" ]

[ "<title>Materials and Methods</title>", "<title>\n<italic>A. vulgare</italic> lineages</title>", "<p>Gravid females (F0) of <italic>A. vulgare</italic> were sampled in the natural park of Chizé (Western France 46°08′05″N-0°24′21″W) and brought back to the laboratory. The infection status of each gravid female (infected with <italic>Wolbachia w</italic>VulC or <italic>w</italic>VulM or asymbiotic i.e. noninfected by <italic>Wolbachia</italic>) was determined as described below. To avoid any maternal effect in further experiments at least three gravid females (F0) for each infection status were used to start lineages. Their offspring (F1) were born and reared in the laboratory. For each infection status, one hundred virgin females from the F1 generation were kept and placed individually with one male (F1) in individual boxes. Over a 7 month period, the survival of these F1 females was monitored every three days and their progenies (F2) were collected. The virgin F2 females grew during two years before immunocompetence experiments. In order to simplify the reading of the paper, virgin asymbiotic females were called A females, virgin females infected with <italic>w</italic>VulC were called C females, virgin females infected with <italic>w</italic>VuM were called M females. All of these lineages were grown at 20°C on moistened potting mix derived from peat from sphagnum moss (pH = 6.4 and conductivity = 50.0 mS/m) with dead leaves and carrot slices as a food source.</p>", "<p>Additionally, a lineage of females experimentally infected by <italic>w</italic>VulC (herein called injC females) was created. For this, the ovaries of 10 C females (F0) were collected and crushed into 1ml of Ringer solution. The resulting suspension was filtered through a 1.2 µm pore membrane, and 1 µl of filtrate injected into non gravid A females (F0) using a thin glass needle (Bouchon et al., 1998). F0 injC females were then crossed with asymbiotic males for two generations in order to produce two year old F2 virgin injC females.</p>", "<p>F2 females (A, C, M) were used to assess: <italic>Wolbachia</italic> titer, haemocytes density and intensity of natural septicaemia. Due to a small number of individuals, injC females (F2) were only used to highlight the assessment of the effect of <italic>w</italic>VulC on haemocyte density.</p>", "<title>Infection status and <italic>Wolbachia</italic> titer</title>", "<p>The infection status of each <italic>A. vulgare</italic> female used in experiments was determined by a PCR-RFLP assay. Individuals were dissected and total DNA extracted from the ovary as previously described ##REF##2762322##[30]##. PCR amplifications were then performed to test for presence/absence of <italic>Wolbachia</italic> using specific primer sets for the <italic>wsp</italic> gene ##REF##9569669##[31]## and conditions as previously described ##REF##15138452##[27]##. In order to discriminate each <italic>Wolbachia</italic> strain, a PCR-RFLP test was performed based on the analysis of <italic>w</italic>VulC and <italic>w</italic>VulM <italic>wsp</italic> sequences (<italic>w</italic>VulM: AJ419984 and <italic>w</italic>VulC: AJ419987). Two restriction enzymes were used: <italic>Bsr</italic>I, which cuts <italic>wsp</italic> amplicons in <italic>w</italic>VulC but not in <italic>w</italic>VulM, and <italic>MFe</italic>I, which cuts <italic>wsp</italic> amplicons in <italic>w</italic>VulM but not in <italic>w</italic>VulC.</p>", "<p>Comparative analysis of the titer of <italic>Wolbachia</italic> in ovaries between C females and M females was performed using qPCR of the <italic>wsp</italic> gene. Total DNA from the ovaries of 20 females of each infection status were individually extracted ##REF##2762322##[30]##. To prepare the standard, 7 µl of purified <italic>wsp</italic> gene PCR product were directly ligated into a pGEM-T-easy vector (Promega) and one site was cut with <italic>Nc</italic>ol enzyme at 37°C overnight to linearize the plasmid. Plasmid concentration was subsequently determined using a spectrophotometer and the number of <italic>wsp</italic> copies calculated. For each DNA sample, the qPCR was carried out under the following conditions: 2 µl of 10× Light Cycler Mix (Roche™), 0.2 µl of 20 µM of <italic>wsp</italic> primers, 1.6 µl of 25mM MgCl2. The thermal cycling used an initial denaturation period of 8 min at 95°C, followed by 45 cycles of denaturing temperature at 95°C for 15 sec., the annealing temperature for the reaction was 57°C for 14 sec. and 72°C for 28°C and a final extension step at 72°C for 28 sec.</p>", "<title>Haemolymph sampling</title>", "<p>Haemolymph was sampled in the same way for all following experiments: cuticles were disinfected by immersing individuals for 30 sec. in a 10% sodium hypochlorite solution followed by a 30 sec. immersion in distilled water. The cuticle was then pierced dorsally between the sixth and seventh abdominal segments using a fine needle and 10 µl haemolymph were collected with a micropipette.</p>", "<title>\n<italic>Wolbachia</italic> in haemocytes</title>", "<p>The haemolymph from 20 females of each infection status (A females, C females and M females) was individually sampled and half diluted in an anticoagulant solution [Modified Alsever's solution MAS 27 mM sodium citrate: 336 mM NaCl, 115 mM glucose, 9 mM EDTA, pH 7; ##REF##15752546##[32]##]. Haemocytes were separated from plasma by centrifugation (400× g, 10 min, 4°C) and washed with the same buffer. Haemocytes were fixed (9% glutaraldehyde, 0.3M sodium cacodylate, 3% NaCl, v/v/v) for 45 min at 4°C and then centrifuged (400× g, 10 min, 4°C). Cells were washed (0.3M sodium cacodylate, 3% NaCl, 0.8M sucrose, v/v/v) for 15 min at 4°C then centrifuged (400× g, 10 min, 4°C). Haemocytes were included in a 2% agar gel (37°C) and 1mm³ plugs were cut and placed in wash buffer for 2h at 4°C following which they were post fixed into 4% OsO₄, 0.3M sodium cacodylate, 5.5% NaCl for 45 min. Haemocytes were subsequently dehydrated through a graded series of acetone solutions, infiltrated, and embedded in resin (Spurr, Polyscience Inc.). Thick sections (0.5 µm) were stained with 1% toluidin blue. Thin sections (90nm) were contrasted by incubation in 1% uranyl acetate in 50% ethanol for 1 min, and then stained with lead citrate. Sections were observed using a transmission electronic microscope (JEOL 100C).</p>", "<title>Haemocyte density in haemolymph</title>", "<p>The haemolymph (10 µl) of 35 females of each infection status (A females, C females, M females and injC females) was individually sampled and added to 10 µl of MAS and 60 µl of 0.4% Trypan blue to discriminate dead haemocytes from living ones. The actual number of living haemocytes in each sample was evaluated using a Thoma counting chamber.</p>", "<title>Natural septicaemia assessment</title>", "<p>The haemolymph (10 µl) of 60 females of each infection status (A females, C females and M females) was individually sampled and added to 290 µl of LB medium. An aliquot of 100 µl of this suspension was streaked onto one plate of each of the three different solid agar media used: (i) a non selective chocolate medium (Biomérieux) on which most bacteria, even fastidious ones, can grow, (ii) the Columbia Nalidixic Acid Agar (CNA) (Biomérieux) in order to preferentially select Gram (+) bacteria and (iii) the Mueller-Hinton Agar (MHA) (Biomérieux) (35g/l) with 10% sheep's blood and 10 µl/l vancomycin in order to preferentially select Gram (−) bacteria. After 3 days at 28°C, the number of colony forming units (CFUs) on each plate was determined.</p>", "<title>Statistical analyses</title>", "<p>All statistical analyses were performed using JUMP software (JMP, 2001, ver.4.03; SAS Institute, Cary, NC, USA). Survival estimates were assessed by a Kaplan-Meier analysis followed by a univariate Survival Analysis using a Wilcoxon test. As haemocyte density and natural septicaemia data showed homoscedasticity of variance (Levene test <italic>p</italic>&gt;0.05), difference in mean responses was tested by an ANOVA followed by PLSD Fisher post-hoc test.</p>" ]

[ "<title>Results</title>", "<title>Infection status and <italic>Wolbachia</italic> titer</title>", "<p>All C, injC and M females used in this experiment were controlled positive for <italic>Wolbachia</italic>. The two strains of <italic>Wolbachia</italic> exhibited a similar titer (∼7,640×10⁶ bacteria per µg total DNA) in the host (ANOVA, <italic>F</italic>\n_1,35 = 1.92, <italic>p</italic> = 0.17). However, <italic>w</italic>VulM tended to show higher titer than <italic>w</italic>VulC (##FIG##0##Fig. 1##).</p>", "<title>Presence of <italic>Wolbachia</italic> in haemocytes</title>", "<p>\n<italic>Wolbachia</italic> cells were observed by transmission electronic microscopy in haemocytes of all C and M females tested. In haemocytes, <italic>Wolbachia</italic> were included in a vacuole and did not seem to be undergoing any type of degradation process suggesting that they may survive and perhaps even multiply within such cells (##FIG##1##Fig. 2##).</p>", "<title>Effect of <italic>Wolbachia</italic> on host survival</title>", "<p>Comparison of survival plots between A females, C females and M females revealed significant differences (Wilcoxon test, χ² = 10.87 <italic>df</italic> = 2 <italic>p</italic> = 0.004). C Females survived significantly less (19% mortality, mean time before death = 177.4±4.4 days) than A females (6% mortality, mean time before death = 189.1±2.7 days) (Wilcoxon test, χ² = 9.39 <italic>df</italic> = 1 <italic>p</italic> = 0.002) whereas survival of M females (11% mortality, mean time before death = 177.8±2.1 days) was not significantly different from that of A females (Wilcoxon test, χ² = 1.56 <italic>df</italic> = 1 <italic>p</italic> = 0.212) (##FIG##2##Fig. 3##). Finally, C females survived significantly less than M females (Wilcoxon test, χ² = 4.05 <italic>df</italic> = 1 <italic>p</italic> = 0.044).</p>", "<title>Effect of <italic>Wolbachia</italic> on haemocyte density</title>", "<p>Global comparison of haemocyte densities in A females, C females, M females and injC females exhibited significant heterogeneity (ANOVA, <italic>F</italic>\n_3,141 = 18.91, <italic>p</italic>&lt;0.0001) (##FIG##2##Fig. 3##). Statistical analysis revealed that A females exhibited significantly higher haemocyte densities (mean: 29,731 haemocytes per µl) than (i) C females (mean: 11,760 haemocytes per µl) (Fisher's PLSD test: <italic>p</italic>&lt;0.0001), (ii) M females (mean: 22,805 haemocytes per µl) (Fisher's PLSD test: <italic>p</italic> = 0.0232) and injC females (mean: 15,722 haemocytes per µl) (Fisher's PLSD test: <italic>p</italic>&lt;0.0001). However, M females exhibited higher haemocyte densities than either C females (Fisher's PLSD test: <italic>p</italic>&lt;0.0001) or injC females (Fisher's PLSD test: <italic>p</italic>&lt;0.009) (##FIG##3##Fig. 4##). C females and injC females showed similar haemocyte densities (Fisher's PLSD test: <italic>p</italic> = 0.104).</p>", "<title>Effect of <italic>Wolbachia</italic> on natural septicaemia</title>", "<p>On CNA [selective medium for Gram (+) bacteria], the mean number of CFUs obtained for haemolymph samples from (i) A females, (ii) C females and (iii) M females showed heterogeneity (ANOVA, <italic>F</italic>\n_2,174 = 3.961, <italic>p</italic> = 0.0208). The mean CFUs was significantly higher in the haemolymph from C females (mean: 81 bacteria/µl) than in A females (mean: 18 bacteria/µl) (Fisher's PLSD test: <italic>p</italic> = 0.0133) or M females (mean: 21 bacteria/µl) (Fisher's PLSD test: <italic>p</italic> = 0.0179). Differences between mean CFUs on MHA [selective medium for Gram (-) bacteria)] and chocolate medium (“non-selective” medium) were not significant (ANOVA, <italic>F</italic>\n_2,174 = 0.769, <italic>p</italic> = 0.4650 and <italic>F</italic>\n_2,174 = 2.850, <italic>p</italic> = 0.0606, respectively) (##FIG##4##Fig. 5##). However, in all media, C females tend to harbour more bacteria in their haemolymph than other females (##FIG##3##Fig. 4##).</p>" ]

[ "<title>Discussion</title>", "<p>Infection dynamics of vertically transmitted endosymbiotic bacteria is highly dependant on their host's reproductive success. However, symbionts such as <italic>Wolbachia</italic> often lead to physiological alterations which can negatively impact host fitness. Among potentially important effects, the impact on immunocompetence seems of particular interest in light of its fundamental role on host fitness. Two arthropod bacterial endosymbionts (<italic>Serratia symbiotica</italic> and <italic>Hamiltonella defensa</italic>) have been demonstrated to increase pea aphid resistance towards parasitoids showing that some vertically transmitted symbionts are able to improve immunocompetence ##REF##16120675##[1]##, ##REF##18029301##[33]##. For <italic>Wolbachia</italic>, which are the most frequent endosymbiotic bacteria in arthropods, two recent studies suggest that they may interact with the host immune system and thus modify the host's ability to overcome infection by other parasites ##REF##16618671##[19]##, ##REF##18171476##[22]##. In the present study, we showed that reduction of haemocyte density in <italic>A. vulgare</italic> was due to <italic>Wolbachia</italic> and not to difference in host genotypes. Such reduction is an indication of immunodepression as haemocyte load is a determinant factor in the ability of crustaceans to mount an efficient immune response against parasites ##REF##16697916##[26]##. However, differences in the effects of the two <italic>Wolbachia</italic> strains on <italic>A. vulgare</italic> were observed: C females had less haemocytes but also more intense septicaemia than M females. These results highly suggest that haemocyte density and intensity of septicaemia are linked and that, in <italic>A</italic>. <italic>vulgare, w</italic>VulC is a more important immunodepressing biotic factor than <italic>w</italic>VulM.</p>", "<p>Three non exclusive hypotheses can be proposed to explain how <italic>w</italic>VulC triggers a decrease in haemocyte density. A first hypothesis involves a direct negative effect of <italic>Wolbachia</italic> on haemocytes survival <italic>via</italic> toxins. Such /<italic>Wolbachia</italic>/-toxins could for example interfere with apoptosis in haemocytes as previously described for other cell types ##REF##17190825##[34]##, ##UREF##3##[35]##. A second hypothesis is that the decrease in haemocyte density is due to the impact of <italic>Wolbachia</italic> load in haemocytes whereby high symbiotic densities in a cell would lead to its destruction as previously described in other tissues for <italic>w</italic>Pop ##REF##9380712##[36]##. This hypothesis is further supported by previous studies in which <italic>w</italic>VulC has been shown to generate effects comparable to those of <italic>w</italic>Pop when injected into foreign recipient hosts ##REF##9684374##[3]##, ##UREF##4##[37]##. However, haemocytes observed here by transmission electronic microscopy mainly exhibited low bacterial loads. A third hypothesis would be that the global physiological cost of <italic>Wolbachia</italic> on their hosts leads to a decrease in their immunocompetence due to a drop in haemocyte production and a reduced capacity to cure bacteria from the haemolymph.</p>", "<p>Our data revealed that the differences in immunocompetence and survival, in the population of <italic>A. vulgare</italic> we studied, are due to <italic>Wolbachia</italic> strains they harbour. The strain <italic>w</italic>VulC was the most immunodepressing and also reduced host lifespan the most, suggesting that these two life history traits may be linked and showing that <italic>w</italic>VulC is clearly more virulent than <italic>w</italic>VulM. This difference in virulence between <italic>w</italic>VulC and <italic>w</italic>VulM seems not due to different titer or location in haemocytes between these two <italic>Wolbachia</italic> strains but can be interpreted in the light of population genetic works conducted on the same populations ##REF##15138452##[27]##, ##REF##10430591##[29]##. Such studies showed that the <italic>w</italic>VulC strain was widely distributed and associated with all <italic>A. vulgare</italic> mitochondrial lineages while <italic>w</italic>VulM was restricted to particular host mitochondrial lineages. In the area where gravid females (i.e. F0) were sampled, the mitochondrial lineages associated with <italic>w</italic>VulM are very frequent ##REF##15138452##[27]##, ##REF##10430591##[29]##. Taking into account these data, Cordaux et al. (2004) proposed a scenario in which <italic>w</italic>VulM is a locally adapted strain (i.e. resident) while <italic>w</italic>VulC is invasive and widely distributed all over the world. Such a scenario, associated with expected evolutionary trends, would suggest that local adaptation occurred between <italic>w</italic>VulM and local host genotypes leading to the observed attenuation of its virulence compared to <italic>w</italic>VulC.</p>", "<p>Even if virulence seems to decrease during local adaptation processes, we have demonstrated here that <italic>Wolbachia</italic> symbiosis is costly and can lead to a reduced lifespan for <italic>A. vulgare.</italic> It is hard to understand selective forces which would promote and maintain such genomic conflicts between symbionts and their hosts in the context of vertically transmitted symbioses. This discrepancy can be seen as the consequence of various strategies adopted by symbionts in order to invade host populations. While symbionts such as those in the pea aphid may spread by increasing their host's immunocompetence ##REF##16120675##[1]##, ##REF##18029301##[33]##, <italic>Wolbachia</italic> rely on manipulating host reproduction which can generate indirect costs. Such costs would tend to keep the prevalence of <italic>Wolbachia</italic> at lower levels than those predicted by feminizing effects alone and could help explain the low frequency of symbiotic females observed in natural populations of <italic>A. vulgare</italic>\n##REF##10430591##[29]##.</p>" ]

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[ "<p>Conceived and designed the experiments: CBV ML YC DB SS. Performed the experiments: CBV ML JH MJ SS. Analyzed the data: CBV ML MJ SS. Contributed reagents/materials/analysis tools: CBV JH. Wrote the paper: CBV ML MJ DB SS.</p>", "<title>Background</title>", "<p>After decades during which endosymbionts were considered as silent in their hosts, in particular concerning the immune system, recent studies have revealed the contrary. In the present paper, we addressed the effect of <italic>Wolbachia</italic>, the most prevalent endosymbiont in arthropods, on host immunocompetence. To this end, we chose the <italic>A. vulgare</italic>-<italic>Wolbachia</italic> symbiosis as a model system because it leads to compare consequences of two <italic>Wolbachia</italic> strains (<italic>w</italic>VulC and <italic>w</italic>VulM) on hosts from the same population. Moreover, <italic>A. vulgare</italic> is the only host-species in which <italic>Wolbachia</italic> have been directly observed within haemocytes which are responsible for both humoral and cellular immune responses.</p>", "<title>Methodology/Principal Findings</title>", "<p>We sampled gravid females from the same population that were either asymbiotic, infected with <italic>w</italic>VulC, or infected with <italic>w</italic>VulM. The offspring from these females were tested and it was revealed that individuals harbouring <italic>w</italic>VulC exhibited: (i) lower haemocyte densities, (ii) more intense septicaemia in their haemolymph and (iii) a reduced lifespan as compared to individuals habouring <italic>w</italic>VulM or asymbiotic ones. Therefore, individuals in this population of <italic>A. vulgare</italic> appeared to suffer more from <italic>w</italic>VulC than from <italic>w</italic>VulM. Symbiotic titer and location in the haemocytes did not differ for the two <italic>Wolbachia</italic> strains showing that these two parameters were not responsible for differences observed in their extended phenotypes in <italic>A. vulgare</italic>.</p>", "<title>Conclusion/Significance</title>", "<p>The two <italic>Wolbachia</italic> strains infecting <italic>A. vulgare</italic> in the same population induced variation in immunocompetence and survival of their hosts. Such variation should highly influence the dynamics of this host-symbiont system. We propose in accordance with previous population genetic works, that <italic>w</italic>VulM is a local strain that has attenuated its virulence through a long term adaptation process towards local <italic>A. vulgare</italic> genotypes whereas <italic>w</italic>VulC, which is a widespread and invasive strain, is not locally adapted.</p>" ]

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[ "<p>We thank Maryline Raimond for technical support.</p>" ]

[ "<fig id=\"pone-0003286-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003286.g001</object-id><label>Figure 1</label><caption><title>Titer of each <italic>Wolbachia</italic> strains in <italic>A. vulgare</italic> ovaries.</title><p>Comparative analysis of the titer of <italic>Wolbachia</italic> in ovaries between C females and M females was performed using qPCR of the <italic>wsp</italic> gene. The two strains of <italic>Wolbachia</italic> exhibited a similar titer (∼7,640×10⁶ bacteria per µg total DNA; ANOVA, <italic>F</italic>\n_1,35 = 1.92, <italic>p</italic> = 0.17).</p></caption></fig>", "<fig id=\"pone-0003286-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003286.g002</object-id><label>Figure 2</label><caption><title>Haemocyte from an <italic>A. vulgare</italic> female infected with <italic>w</italic>VulC observed by transmission electronic microscopy.</title><p>Haemocytes were included in agar gel and cut. Thick sections (0.5 µm) were stained and observed using a transmission electronic microscope.<italic>Wolbachia</italic> (notated <italic>w</italic> on the photography) cells were observed by transmission electronic microscopy in haemocytes of all C and M females tested.</p></caption></fig>", "<fig id=\"pone-0003286-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003286.g003</object-id><label>Figure 3</label><caption><title>Effect of <italic>Wolbachia</italic> on host survival.</title><p>Comparison of survival plots between A females, C females and M females during 7 months revealed that C females survived significantly less than A females and M females.</p></caption></fig>", "<fig id=\"pone-0003286-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003286.g004</object-id><label>Figure 4</label><caption><title>Effect of <italic>Wolbachia</italic> on haemocyte density.</title><p>Global comparison of haemocyte densities in haemolymph of <italic>A. vulgare</italic> females infected or not by <italic>Wolbachia</italic> revealed that A females exhibited significantly higher haemocyte densities than C females, M females and injC females.</p></caption></fig>", "<fig id=\"pone-0003286-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003286.g005</object-id><label>Figure 5</label><caption><title>Effect of <italic>Wolbachia</italic> on CFUs obtained from haemolymph samples.</title><p>Haemolymph samples from <italic>A. vulgare</italic> females infected or not by <italic>Wolbachia</italic> were streaked onto several agar media (CNA, MHA and Chocolate). On CNA [selective medium for Gram (+) bacteria], the mean number of CFUs obtained for haemolymph samples from C females was significantly higher than in A females or M females.</p></caption></fig>" ]

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[ "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This research was funded by the CNRS, the French Ministère de l'Education Nationale, de l'Enseignement supérieur et de la Recherche, and the Agence Nationale de la Recherche (EndoSymbArt ANR-06-BLAN-0316). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p></fn></fn-group>" ]

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[ "<title>Introduction</title>", "<p>Precise estimates of molecular rates are fundamental to our understanding of the processes of evolution. In principle, mutation and evolutionary rates for neutral regions of the genome from the same species are expected to be equal ##REF##5767777##[1]##. However, on the basis of empirical findings, it has recently been argued that molecular rates vary in relation to the time period over which they are measured ##REF##16015312##[2]##–##REF##16356585##[4]##. For example, Parson et al. ##REF##9090380##[5]##, Santos et al. ##REF##15814829##[6]## and Howell et al. ##REF##12571803##[7]## reported very high mutation rates of the mitochondrial control region using human pedigrees. More recently, a series of ancient DNA-based estimates of evolutionary rates of the control region have been reported in a range of other vertebrate animals ##REF##11910113##[8]##–##REF##15567864##[10]##. For example, Lambert et al. ##REF##11910113##[8]## recorded a rate of 0.96 substitutions/site/Million years (s/s/Myrs) for the HVRI region of the mitochondrial genome of Adélie penguins. These rates are also typically high, and are similar to many pedigree rate estimates ##REF##12571803##[e.g. 7]##. Furthermore, rates estimated using inter-specific divergence levels, typically calibrated against the fossil record ##REF##3033252##[11]## or some biogeographic event ##REF##11091317##[12]##, are slower than the ancient DNA-based estimate. Overall, these rates of molecular change differ by up to an order of magnitude ##REF##16774978##[13]##.</p>", "<p>These recent findings have given rise to the suggestion that the relationship between molecular rates and the times over which they are measured follows an exponential decline, the so-called ‘lazy jay’ curve ##REF##16015312##[2]##. Ho et al. ##REF##16356585##[4]## suggested that it takes 1–2 Myrs for the rate of molecular change to decline to a constant substitution rate. If this temporal variation in molecular rates is substantiated, it has important theoretical implications as well as practical ones. Specifically, time dependency would require that rates be estimated over short and long time periods for each species or group of species, and then used only for the appropriate time interval. Resolving this apparent difference in rates is difficult because precise estimates of both mutation and evolutionary rates for the same species have not been possible. Also many comparisons have been made using data from different species. For example, Ho et al. ##REF##15814826##[3]## compared rates of molecular change estimated from many avian species.</p>", "<p>Therefore, in order to compare molecular rates accurately over different time periods and within a single species, the following are required: extant natural populations from which large numbers of pedigree samples can be collected, along with large numbers of ancient samples of the same species from an undisturbed environment. Adélie penguins meet these requirements and therefore represent an ideal model for resolving disparate views about the time dependency of molecular rates. Using this species, it is possible to estimate both mutation and evolutionary rates for the same region of the genome precisely.</p>", "<p>In Adélie penguins, breeding birds inhabit ice-free areas of the Antarctic coastline during the summer months. Adult pairs typically lay two eggs, and both adults and chicks can readily be blood sampled and banded. In order to test the time dependency of rates, we estimated the mutation rate by sequencing the HVR I of penguins from a large number of known families comprising both parents and chicks. Adélie penguins are also characterised by the presence, under breeding colonies, of large collections of sub-fossil bones of the same species. Given the typically high level of natal return that is characteristic of this species ##UREF##0##[14]##, these remains generally have a close genealogical relationship to the birds now nesting on top of them. In addition, the very cold and dry Antarctic environment has favoured the preservation of both nuclear ##REF##16275908##[15]## and mitochondrial DNA ##REF##11910113##[8]##,##REF##14595092##[16]##. We have expanded a previous dataset and estimated the evolutionary rate for the same HVR I region using a large number of sub-fossil bones aged up to 37,000 yrBP ##REF##11910113##[8]##,##REF##14595092##[16]##. These studies allowed us to assess the relationship between mutation and evolutionary rates of a single region of the genome in Adélie penguins directly and thereby directly test current ideas about the time dependency of molecular rates.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Study Site</title>", "<p>The study was conducted at the Northern Cape Bird Adélie penguin colony, Ross Island, Antarctica (##FIG##3##Figure 4##). All samples were blood collected within an approximately 1000m area within the colony in order to minimise any disturbance to the colony as a whole. Bleeding protocols were approved by Massey University Animal Ethics Committee permits numbers 00/161 and 03/89. Permission to restrain, take blood and work in the Cape Bird Adélie penguins colony was given by Antarctica New Zealand permit numbers 00/007, 01/007, 02/007, 03/030 and 04/030. Blood sampling was typically conducted from the middle of December, soon after the first eggs had hatched, to early January. During this period, the chicks never leave the nest and are always attended by an adult bird. The parents take turns at guarding the chicks and change over every one to three days ##UREF##0##[14]##,##UREF##1##[18]##. During this period, the adult away from the nest feeds at sea. On his/her return to the nest, there is a ritualistic exchange that consists of highly visible greeting calls before the birds change roles and the sitting bird leaves to feed at sea. Family groups were initially identified by the presence of two adult birds and two chicks at a nest site. The adult bird behaviour was then observed; two birds were only considered to be a pair if they were seen to exchange greetings calls and defend the nest when approached. Once family groups had been identified, the nest location was marked, and the adults and chicks removed from the nest. Adults were restrained with a hand net or shepherd's crook, and chicks were caught by hand. The adult birds were placed in a bag and weighed using either a 5 or 10kg Pesola balance. Adult Adélie penguins were permanently marked using a flipper band. These bands had numerals that can be read easily using 8–10 X binoculars from a distance of 10m. Chicks were weighted using either a 1kg or 0.5kg Pesola balance. Typically, 100ml blood samples were taken from the intertarsal vein of adults, using a 1ml syringe with a 25 gauge needle, after the leg had been cleaned with 70% ethanol. Each syringe was washed with 0.2M di-potassium EDTA, preventing the blood from coagulating. The samples were subsequently stored in pre-labelled tubes containing 1 ml of preservation buffer ##UREF##6##[32]## and stored at 4°C on return to the laboratory. While the adults were bled, the chicks were kept confined to a small bag for warmth and protection. Chicks were similarly bled; however, blood was generally collected from the foot intra-digital vein using a 0.5ml syringe with a 29 gauge needle. All birds were returned to the nest and the temporary nest marker removed. Nests were then observed to ensure that one of the adults resumed guarding the chick. Typically, only pairs with two chicks were sampled. The collection dates and samples used in the study are as follows: from the 1993/4 and 1994/5 breeding seasons, there were five nests comprising 25 individuals; in the 2001/2 breeding season, there were 181 nests comprising 537 individuals; in the 2002/3 breeding season, there were 223 nests comprising 881 individuals; in the 2003/4 breeding season there were 132 nests comprising 525 individuals and finally, in the 2004/5 breeding season, there were 170 nests comprising 650 individuals. In total 2618 individuals from 711 families were collected.</p>", "<title>Molecular Methods</title>", "<p>DNA was extracted from the blood/Queens buffer mixture using a Chelex-based method ##REF##1867860##[33]##. For each sample, 10 µl of blood was mixed with 80 µl of 10% w/v Chelex (Biorad) in water and heated to 90°C for 25 mins in a thermal cycler. After allowing the sample to cool to room temperature, the sample was centrifuged for 1 min at 16,000g in a microcentrifuge. For each amplification reaction, 1 µl of supernatant was used as template. Polymerase Chain Reaction (PCR) amplifications were carried out in 25 µl volumes containing 1 µl of Chelex-extracted DNA, 1U of Platinum Taq (Invitrogen), 1.5 mM MgCl₂, 2 µg/µl bovine serum albumin, 0.4 µM of each primer and 200 µM of each dNTP. Samples were amplified using a Applied Biosystems 9700 thermal cycler at 94°C for 10 sec, 50°C for 10sec and 72°C for 25 sec for 35–40 cycles. The HVRI region of the mitochrondrial genome was amplified using primers specific to Adélie penguins AH530 (<named-content content-type=\"gene\">5′- CTGATTTCACGTGAGGAGACCG-3′</named-content>) and L-tRNA^Glu (<named-content content-type=\"gene\">5′-CCCGCTTGGCTTYTC TCCAAGGTC-3′</named-content>) (reference numbers correspond to the sequence deposited in GenBank, accession no. AF272143). All PCR products were purified using either PCR product purification columns (Qiagen) or magnetic beads (Agencourt). PCR products were directly sequenced using the ABI PRISM BigDye Terminator Cycle Sequencing Kit (Applied Biosystems) and analysed on either an ABI 377 automated sequencer or an ABI 3730 automated DNA sequencer. All sequences were analyzed using the computer program PHRED (CodonCode, Dedham, MA). After base calling, PHRED assigns a quality value to each base call ranging from 0 to 60, with higher values corresponding to higher sequence quality. The quality values are logarithmically linked to error probabilities, e.g. a PHRED quality score of 10 corresponds to an accuracy of the base call of 90%, whereas a PHRED quality score of 50 matches a correctness of the base call of 99.999%. In this study, sequences were accepted if ≥90% of the bases had quality scores over 20. Sequence alignment and mutation identification was performed using the Sequencher package (GeneCodes, Ann Arbor, MI). Mixed base calling was set in Sequencher at a detection threshold of 30%. Sequencher defines this in terms of the lower peak being at least 30% of the height of the higher, to be scored as a potential mixed base position. In this study, we have defined the detection threshold for mixed bases in terms of the ratio of absolute peak heights to the total signal. The Sequencher threshold then becomes a threshold of 23% under this definition. This threshold was chosen as an appropriate detection threshold to minimise the chance of false positives in the data.</p>", "<p>We examined this threshold by performing a calibration study to test the accuracy of detecting heteroplasmic bases in this region of HVR I empirically. Two different Adélie penguin haplotypes were chosen that differ at 28 positions within the 344bp region of HVR I considered in this study. The HVR I region was amplified from each of these samples using the primers AH-530 and L-tRNA^Glu. After purification, each PCR product was ligated into the vector pCR 2.1 (Invitrogen) and sequenced. Each haplotype clone was linearised and the concentration determined using spectroscopy. Haplotype mixes representing heteroplasmy at different haplotype ratios were generated by mixing the two haplotype clones (##SUPPL##2##Table S2##). These samples were amplified and sequenced as described previously. The trace data from each of these haplotype mixes were analysed and our ability to discriminate the heteroplasmic positions accurately was tested. To do this, at each heteroplasmic site, we plotted the expected haplotype ratios against the observed ratios (##SUPPL##0##Figure S1##). At each heteroplasmic position, the value should be 1 if the observed ratio is the same as the expected. If the value is &gt;1 or &lt;1, this represents an under-estimate and an over-estimate of the ratio, respectively.</p>", "<p>These data show a clear position dependency of each site to estimate the original haplotype ratio accurately, with some sites consistently over-estimating or under-estimating the ratio within each of the mixed samples. From this analysis, we calculated that there is approximately a 5% error in determining haplotype ratios based on a single heteroplasmic position from trace data.</p>", "<p>Background noise in DNA trace data is a significant factor when detecting heteroplasmic bases. The variability of peak heights and noise in trace data results in a different level of sensitivity for heteroplasmy detection at different positions. To test the variability of noise within and between sequences, we extracted the noise profile from ten independent sequences for each of the test samples. We determined the sequence of the noise in each sample and aligned these sequences. This revealed that the noise sequence was conserved between samples with 68% identity. A comparison of the noise profiles for each sequence suggested that the noise profile is highly conserved between sequences (data not shown).</p>", "<p>The accuracy of detecting heteroplasmic bases is dependent on the noise profile of each sequence. The position of the peak noise is important, as this represents the first site that could be called a false positive. We compared the height of the minor peak at each of the 28 heteroplasmic positions to the peak noise in each of the haplotype mixes. In each haplotype mix, the number of heteroplasmic bases above and below the peak noise threshold were scored (##SUPPL##2##Table S2##). From these data, it is clear that at the lower haplotype ratios (10∶90 and 20∶80) a number of the heteroplasmic bases are lower than the noise threshold. Even with the 30∶70, samples not all the heteroplasmic positions can be discriminated from the noise. This finding reduces the sensitivity of heteroplasmy detection and indicates that setting a low detection threshold in an attempt to increase the sensitivity of heteroplasmy detection will also result in an increased likelihood of scoring false positives. These data suggest a detection threshold between 20 and 30% is the most appropriate to maximise sensitivity while, at the same time, minimising the chance of false positives.</p>", "<p>Next we tested the ability of the program Sequencher to detect the heteroplasmic positions accurately within each haplotype mix at different threshold settings. The trace data from each haplotype mix were analysed for secondary peaks at three different detection thresholds using Sequencher (##SUPPL##3##Table S3##). In each experiment, the ability to detect the heteroplasmic positions for different haplotype ratios with different detection thresholds was tested, the number of correct bases were determined and false positives were scored (##SUPPL##3##Table S3##).</p>", "<p>This experiment demonstrates that when the threshold is reduced below 23%, for the sequences in this study, the number of heteroplasmic positions detected increases slightly but false positives are included. This supports the use of a detection threshold of 23% for these sequences as a threshold that maximises accuracy and minimises false positives. ##TAB##0##Table 1## provides details of the level of heteroplasmy in mothers and chicks, as estimated by the peak heights in DNA trace data.</p>", "<title>Evolutionary Rate Estimation</title>", "<p>Summary statistics were estimated using Molecular Evolutionary Genetics Analysis (MEGA) v3.1 ##REF##15260895##[34]##. The number of variable sites was 156. There were 104 informative sites and 52 singletons. The base composition of the region was as follows: (%T) 31.1, (%C) 18.7, (%A) 30.5, (%G) 19.7. The average pair-wise distance between the sequences was 0.049 (±0.006) per site; the transition and transversion substitutions were 0.047 (±0.006) and 0.002 (±0.000) per site respectively. The evolutionary rate was estimated using Bayesian Evolutionary Analysis Sampling Trees (BEAST) v1.3 ##UREF##5##[27]## with 20 million steps in an MCMC simulation (500,000 step burn-in time). When running an MCMC chain, the number of independent observations is less than the total length. The chain is not random in tree space and the information in each observation is not totally separate from the information in other observations. BEAST circumvents this problem of autocorrelation by adjusting the sample size. The effective sample size is calculated in BEAST as the total chain length divided by the chain autocorrelation coefficient (both metrics are produced by BEAST). Hence, the ESS is 19.5 million/182243.0 = 107.</p>" ]

[ "<title>Results</title>", "<p>We compared high quality DNA sequences from a 344bp region of the 5′ terminus of the mitochondrial HVR I region of a large sample of modern Adélie penguins. These comprised the mother and father from each of 508 families and typically two chicks per family. All blood samples were collected from an Adélie penguin colony at Cape Bird, Ross Island, Antarctica over four consecutive summers starting in 2001/2. DNA sequences were scored for quality using PHRED ##REF##9521922##[17]## and poor sequences were eliminated from our analysis or re-sequenced (see <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>). From the remaining sequence data, a number of mitochondrial heteroplasmic sites were detected. At these sites, two nucleotide signals were apparent in the same individual. Such heteroplasmies are the result of an earlier mutation event and two variants (the original and the mutant) have persisted in the same individual. In order to rule out false positives, such as substitutions that might arise from PCR amplification errors, all heteroplasmies were re-sequenced from different DNA extractions from the same samples. In total, we detected 62 heteroplasmies from DNA trace data. A calibration study (see <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>) showed that the proportions of each mitochondrial haplotype can be accurately inferred from the DNA trace data, with a standard error of approximately 5%. All but one of the recorded heteroplasmies were transitions and all but three of the heteroplasmic sites were at positions in which polymorphisms were recorded in populations of Adélie penguins from colonies in the Ross Sea, Antarctica. ##FIG##0##Figure 1## illustrates the position of the heteroplasmic sites and the frequency of the non-majority base in each case. Using available Adélie penguin life history data ##UREF##0##[14]##,##UREF##1##[18]##, we estimated the average intergenerational age (g) as 6.46 years. Using these data, the observed rate of heteroplasmies (<italic>μ</italic>\n_o) of the HVR I region is 54.9 mutations/site/Myr with 95% confidence intervals of 41.2–68.6 mutations/site/Myr (##FIG##1##Figure 2##).</p>", "<p>Mutation events in mitochondria result in heteroplasmies that can persist over generations and which may or may not be detected, depending on the frequency of rarer variants ##UREF##2##[19]##,##REF##15012752##[20]##. In our study, heteroplasmies appeared to be germline variants rather than somatic, as evidenced by the fact that, in all families, they were transmitted from the mother to one or both chicks (##TAB##0##Table 1##). In combination, these data suggest that, in contrast to mutations in some other species ##REF##15814829##[6]##,##REF##2798094##[21]##, mutations in Adélie penguins persist in the heteroplasmic state for many generations. A heteroplasmy can only be transmitted across generations if a chick inherits multiple copies of its mother's genome. The larger the number of generations that a heteroplasmy persists, the higher will be the probability that it will be detected. A heteroplasmy can persist for many generations in a maternal line of descent until it is either lost or goes to fixation. This persistence time is influenced by the number of segregating mitochondrial genomes (<italic>N</italic>) that pass through the inheritance bottleneck. For human oocytes, <italic>N</italic> has been estimated to be between 15 and 70 ##UREF##2##[19]##,##REF##9199572##[22]##.</p>", "<p>Our estimate of the mutation rate is affected by our ability to discriminate between low frequency heteroplasmies and noise in DNA trace data. If we set the threshold detection level too low, we would mistakenly include ‘noise’ as evidence of heteroplasmies. To avoid such false positives, at least one of the two chicks had to have a haplotype that exceeded a threshold level. As a result of a calibration study (<xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>), we set a detection threshold frequency (<italic>θ</italic>) of 23%. Our further analyses take account of the expected number of heteroplasmies that are excluded using this threshold.</p>", "<p>We used a recently developed model ##UREF##3##[23]## to take account of the above factors in our estimate of the mutation rate. The model defines the rate at which new mutations enter the germ-line (α). Assuming these mutations are neutral and that each mutation is equally likely to be transmitted to the next generation, only 1<italic>/N</italic> of these mutations are expected to go to fixation, so <italic>μ</italic> = α/<italic>N</italic>. This model ##UREF##3##[23]## assumes that we can only observe a heteroplasmy when the proportion of a new haplotype exceeds <italic>θ</italic>. This model also assumes that if <italic>θ</italic> = 0.23, most heteroplasmies are lost without reaching this proportion, and most heteroplasmies that reach this level do not go to fixation. If <italic>N</italic> were doubled, then the number of heteroplasmies that reach the threshold halves, but the observed persistence of those that reach it, doubles. Hence, the rate of observed heteroplasmies (<italic>μ</italic>\n_o) is independent of <italic>N</italic>, and approximated by the expression 2α/ln(1/<italic>θ</italic>−1) ##REF##9199572##[22]##. Thus for the threshold <italic>θ</italic> = 0.23, <italic>μ</italic>\n_o ≈ 2.417α, so <italic>μ</italic>≈0.414 <italic>μ</italic>\n_o/<italic>N</italic>.</p>", "<p>The ratio of the heteroplasmic variants present in mothers and chicks was estimated from the relative peak heights in DNA trace data for each individual (##TAB##0##Table 1##). These represent the relative proportions of each of the four possible nucleotides at any given position in a DNA sequence. Using the binomial distribution to model the inheritance of heteroplasmies, we showed that for a large <italic>N</italic> there is little difference in heteroplasmy ratios between mothers and chicks. We used this finding to infer <italic>N,</italic> from the distribution of differences in heteroplasmy ratios of mothers and chicks. These differences are summarised in ##FIG##2##Figure 3##.</p>", "<p>We present here a brief description of the method used to estimate <italic>N</italic>. A more detailed description is found in ##UREF##3##[23]##. From ##TAB##0##Table 1##, we calculated the mean square difference in the frequency of haplotypes (as estimated by the peak heights in DNA trace data) between mothers and chicks, which we designated the “raw variance” (σ ˆ²\n_raw). The raw variance is dependent on the actual heteroplasmy difference between mother and chick, which we designated the “genetic variance” (<italic>σ</italic>\n²\n_genetic), and the uncertainties in measuring the heteroplasmy, known as the “measurement variance” (<italic>σ</italic>\n²\n_measure). The genetic variance was estimated by subtracting the measurement variance from the raw variance. <italic>N</italic> was estimated from this using the variance of a binomial distribution. We also estimated the uncertainties in our analysis. For a Gaussian distribution, the variance in the sample variance is var (σ ˆ²) = (n−1)/n²\n<italic>σ</italic>\n⁴\n##UREF##4##[24]##, where <italic>n</italic> is the number of samples and <italic>σ</italic>\n² represents the true variance.</p>", "<p>Within the data in ##TAB##0##Table 1##, there are 123 mother-chick pairs, with mean square difference σ ˆ²\n_raw = 1.15×10⁻² (corresponding to a root mean square of 10.71%) with estimator variance var (σ ˆ²\n_raw) = 122/123²×(1.15×10⁻²)² = 2.12×10⁻⁶. From the calibration study, each measurement has variance σ ˆ²\n_measure = 2.14×10⁻³ (i.e. a standard error in measurement of 4.62%) with estimator variance var (σ ˆ²\n_measure) = 3.58×10⁻⁷. Then the genetic variance is σ ˆ²\n_genetic = σ ˆ²\n_raw−2σ ˆ<italic>²</italic>\n_measure = 7.18×10⁻³ with estimator variance var (σ ˆ²\n_genetic) = var (σ ˆ²\n_raw)+2 var (σ ˆ²\n_measure) = 2.83×10⁻⁶ (corresponding to (8.48±0.99)%). If the proportion of each haplotype inherited by the chick comes from a binomial distribution with population size <italic>N</italic> then <italic>σ²</italic>\n_genetic = <italic>p(1−p)/N,</italic> where <italic>p</italic> is the mother's heteroplasmy ratio. The expression <italic>p(1−p)</italic> varies little, so we use the mean value of 0.234 to estimate 1/<italic>N</italic> = 0.0319±0.0075 (standard error), which then becomes <italic>N</italic> = 31.3 (95% confidence interval 21.5–57.9). Using a more detailed model ##UREF##3##[23]##, we found that the posterior distribution of <italic>N</italic> had a median value 38.3 and HPD 95% confidence intervals 24.3 to 63.3. Using a maximum likelihood estimation, the corresponding point estimate for <italic>μ</italic> is 0.55 mutations/site/Myrs with a HPD 95% confidence interval of 0.29–0.88 mutations/site/Myrs (##FIG##1##Figure 2##). A number of authors have recently reported similar high rates of mutation from organisms as phylogenetically diverse as <italic>Caenorhabditis elegans</italic>\n##REF##11009418##[25]## and humans ##REF##9090380##[5]##,##REF##15814829##[6]##,##REF##12571803##[7]##,##REF##10982034##[26]##.</p>", "<p>In order to compare an evolutionary rate with this mutation rate, we expanded on an earlier study ##REF##11910113##[8]##,##REF##14595092##[16]## that analysed 96 known age sub-fossil bones of Adélie penguins to determine the evolutionary rate for the HVR I region. For this study, we sequenced an additional 66 bones of ages up to 37,000 years (##SUPPL##1##Tables S1##) and estimated the rate of evolution for the same 344 bps of the HVR I region used to estimate the mutation rate. These data were characterised by 156 segregating sites and a nucleotide diversity of 0.049 (±0.006 S.E.). The majority of the substitutions were transitional changes (0.047±0.006 S.E.). We estimated the rate of evolution using a Bayesian Markov chain Monte Carlo (MCMC) approach, as implemented in the software Bayesian Evolutionary Analysis Sampling Trees (BEAST v1.3) ##UREF##5##[27]##. An MCMC simulation of 20 million steps, with the first 500,000 steps discarded as the burn-in time, estimated <italic>k</italic> to be between 0.53 and 1.17 substitutions/site/Myr (95% HPD) with a median value of 0.86 substitutions/site/Myr. Our previous median estimate of <italic>k</italic> was 0.96 substitutions/site/Myr and our new analysis reduced the confidence interval from 0.53 to 1.43 ##REF##11910113##[8]##. Our analysis showed that the results were not significantly dependent upon the priors.</p>", "<p>In relation to the power of our analysis, if <italic>μ</italic> was, for example, four times as large as we observed, we would have recorded approximately four times as many heteroplasmies. Hence, the relative size of the confidence interval would be reduced by a factor of two (but as <italic>μ</italic> quadruples, the absolute size of the confidence interval would double). Approximating the posterior distributions of <italic>μ</italic> and <italic>k</italic> as normal distributions, we find that for <italic>μ</italic>&lt;0.44 or <italic>μ</italic>&gt;1.44, we could reject the null hypothesis (<italic>μ</italic> = <italic>k</italic>) at the 95% confidence level.</p>" ]

[ "<title>Discussion</title>", "<p>The estimation of rates of molecular change is one of the most important exercises in evolutionary biology. Using a pedigree approach and a recently reported mathematical model, we have estimated the mutation rate for the Adélie penguin hypervariable region of the mitochondrial genome as 0.55 mutations/site/Myr. This rate is likely to represent the best estimate of the real mutation rate of the species, excluding lethal mutations. It is similar to rates estimated for the same hypervariable region for humans ##REF##15814829##[see 6 for a summary]##. However, it is widely accepted that a range of factors can contribute to inaccurate estimates of rates of molecular change ##REF##15519966##[28]##. In relation to longer term evolutionary rates, these factors range from uncertainty in the timing of calibration points, such as the presence of older undiscovered fossils, incorrect phylogenetic relationships among the forms being studied and imprecise estimates of the levels of genetic divergence. However, estimates of mutation rates have not generally been subject to the same level of scrutiny, stemming from an assumption that mutation rate estimates are inherently more precise. It is now clear that some previous estimates of mutation rates from pedigree data have also been subject to a range of errors, e.g. earlier less sensitive DNA sequencing technologies. In addition, different studies have treated heteroplasmies in different ways, with consequent effects on mutation rates. Some studies have included heteroplasmies in the estimation of mutation rates ##REF##9090380##[e.g. 5]##, while some have not ##REF##10756141##[e.g. 29]##. Others have included them but weighted their contribution to the estimation of rates ##REF##15814829##[6]##. Howell ##REF##12571803##[7]## estimated a mutation rate for the control region of the human mitochondrial genome assuming that each heteroplasmy contributes to the actual mutation rate. According to our model, this assumption over-estimates <italic>μ</italic> by a factor of 5. Thus the authors assume <italic>μ</italic> = α, using our notation. The authors go on to suggest that theirs is an under-estimate of α. In addition, the unique nature of mitochondrial DNA has not been widely appreciated when calculating mutation rates and we suggest that many of these issues are likely to have contributed to poor estimates of mitochondrial mutation rates. The recently reported model ##UREF##3##[23]## explicitly takes account of the above issues and we suggest such analyses are necessary to estimate mutation rates accurately.</p>", "<p>When we take these factors into consideration, our comparative data on molecular rates of change illustrate that for the 5′ end of the mitochondrial HVR I in Adélie penguins, the short-term mutation and longer-term evolutionary rates are similar (##FIG##1##Figure 2##). The respective confidence intervals overlap and they cannot be distinguished statistically (p = 0.13). Hence, the hypothesis that molecular rates vary over time ##REF##16015312##[2]##–##REF##16356585##[4]## cannot be supported and our data suggests that the hypervariable region of the mitochondrial genome is evolving neutrally.</p>", "<p>Emerson ##REF##17464888##[30]## has recently criticised the reliability of some of the data that underlie the proposed relationship between rate estimates and time. Based on a reanalysis of the studies used to estimate rates, Emerson suggested that, for the mitochondrial control region of vertebrate animals, there is little or no relationship between molecular rates and time (see Figure 5b in 29]. In a response to this critique, Ho et al. ##REF##17562475##[31]## not only defended their earlier analysis but, based on a reanalysis of ancient DNA data from bison, argued that there is evidence for time dependency of rates over periods less than 1–2 Myrs (see ##FIG##0##Figure 1## from ##REF##16356585##[4]##). Using a sliding window approach where the authors analysed bison samples from a range of ages, they showed that ancient bison DNA sequences from 0–10,000 yrBP evolved at a rate higher than that recorded for older samples, e.g. 0–50,000 yrBP. These rate distributions are, however, not statistically different from each other and the likely effects of small sample sizes remain unresolved. Emerson ##REF##17464888##[30]## also questioned estimates of molecular rates based on ancient DNA and suggested that they may generally be upwardly biased. This could be, for example, due to a reduction in population size over the time period studied. This would result in higher rates of fixation of even deleterious mutations and thereby result in an increase in molecular rates. However, since high molecular rates have been observed in ancient DNA studies of such diverse groups as primates, artiodactyls, rodents and birds ##REF##15814826##[3]##, such a universal population decline in all these species seems unlikely.</p>", "<p>Finally, our data do not support the concept of a time dependency of molecular rates. If there is a decline in molecular rates in Adélie penguins over time, it is not apparent over the 37,000 year time period examined in this study. Ho et al. ##REF##17562475##[31]## suggested from their data that such a decline should have been observed over the time period we studied. We suggest that, the differences in rates of mutation and evolution that have been detected in some studies may be due to empirical errors associated with heteroplasmy and/or inaccuracies associated with calibration methods.</p>" ]

[]

[ "<p><bold>¤a:</bold> Current address: School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand</p>", "<p><bold>¤b:</bold> Current address: Griffith School of Environment and School of Biomolecular and Physical Sciences, Griffith University, Nathan, Australia</p>", "<p>Conceived and designed the experiments: CDM DML. Performed the experiments: AD JA GCG PAR. Analyzed the data: CDM AD PAR CB MDW MDH DML. Contributed reagents/materials/analysis tools: AD CB MDW MDH. Wrote the paper: CDM DML. Contributed to the fieldwork: GCG PAR CB. Contributed to the development of the mathematical model: MDW MDH. Conducted the field studies: CDM DML.</p>", "<p>Precise estimations of molecular rates are fundamental to our understanding of the processes of evolution. In principle, mutation and evolutionary rates for neutral regions of the same species are expected to be equal. However, a number of recent studies have shown that mutation rates estimated from pedigree material are much faster than evolutionary rates measured over longer time periods. To resolve this apparent contradiction, we have examined the hypervariable region (HVR I) of the mitochondrial genome using families of Adélie penguins (<italic>Pygoscelis adeliae</italic>) from the Antarctic. We sequenced 344 bps of the HVR I from penguins comprising 508 families with 915 chicks, together with both their parents. All of the 62 germline heteroplasmies that we detected in mothers were also detected in their offspring, consistent with maternal inheritance. These data give an estimated mutation rate (<italic>μ</italic>) of 0.55 mutations/site/Myrs (HPD 95% confidence interval of 0.29–0.88 mutations/site/Myrs) after accounting for the persistence of these heteroplasmies and the sensitivity of current detection methods. In comparison, the rate of evolution (<italic>k</italic>) of the same HVR I region, determined using DNA sequences from 162 known age sub-fossil bones spanning a 37,000-year period, was 0.86 substitutions/site/Myrs (HPD 95% confidence interval of 0.53 and 1.17). Importantly, the latter rate is not statistically different from our estimate of the mutation rate. These results are in contrast to the view that molecular rates are time dependent.</p>", "<title>Author Summary</title>", "<p>Molecular evolutionary theory suggests that for neutral DNA sequences, rates of mutation and evolution should be equal. However, there has been considerable variation in empirical estimates of rates of molecular change in vertebrate animals, even for the same regions of the mitochondrial genome. A difficulty is that evolutionary rates estimated from ancient DNA and short-term mutation rates are not available for the same species. We present data on the rate of mutation of the mitochondrial hypervariable region in Adélie penguins from the Antarctic. All recorded mutations were heteroplasmic in mothers, and almost invariably, both genetic variants were passed to their offspring. We compared this rate of mutation to the rate of evolution estimated using serially preserved ancient remains. We show that these two estimates were not statistically different from each other.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We thank the following: D. Ainley, K. Barton, W-H. Chua, W. Cook, E. Esins, B. Hall, R. Heeney, F. Hunter, M. Ives, B. Karl, T. Ohta, T. Parsons, L. Shepherd, H. Spencer, B. Thomas, G. Walter, Y. Wharton, and P. Wilson.</p>" ]

[ "<fig id=\"pgen-1000209-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000209.g001</object-id><label>Figure 1</label><caption><title>A plot of the frequency of the non-majority nucleotide bases across the 344 bp region of the HVR I for all adult penguins examined in this study.</title><p>Only individuals that showed no heteroplasmies were used. The sites that showed transitional mutations are shown. When more than one transition was recorded at a site, the number is shown. The position of the single transversional mutation that was recorded is shown (triangle).</p></caption></fig>", "<fig id=\"pgen-1000209-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000209.g002</object-id><label>Figure 2</label><caption><title>The estimates of the frequency of observed heteroplasmies (<italic>μ</italic>\n_o) with the mean and 95% confidence intervals are shown.</title><p>The distribution, mode and confidence intervals of the mutation rate (<italic>μ</italic>) derived from modeling the inter-generational persistence of the heteroplasmies are also shown. The posterior probability densities of the evolutionary rate (<italic>k</italic>), estimated from 162 ancient penguin bones of known ages, are shown below the line. The median and 95% intervals are given.</p></caption></fig>", "<fig id=\"pgen-1000209-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000209.g003</object-id><label>Figure 3</label><caption><title>The distribution of differences between the two haplotypes in heteroplasmic mothers and their chicks is shown, as determined by DNA trace peak heights.</title><p>The curved line represents the prediction of the model, given the estimated number of mitochondria transmitted between mothers and chicks (<italic>N</italic> = 36.5).</p></caption></fig>", "<fig id=\"pgen-1000209-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000209.g004</object-id><label>Figure 4</label><caption><title>Location of the study site at Cape Bird, Ross Island, Antarctica.</title></caption></fig>" ]

[ "<table-wrap id=\"pgen-1000209-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000209.t001</object-id><label>Table 1</label><caption><title>Details of heteroplasmies recorded from pedigree material of Adélie penguin families.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">Ratio of heteroplasmic sites in each family member</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Variable Nucleotide Site</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Heteroplasmy</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mother</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">Offspring</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">57</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">55∶45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">43.5∶56.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">42.5∶57.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">333</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50∶50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">54∶46</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">62∶38</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">277</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49∶51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40∶60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">46∶54</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40.5∶59.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">44∶56</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">25∶75</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>39</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>C/T</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>62∶38</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>55∶45</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>60.5∶39.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>330</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>G/A</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>47.5∶52.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>39.5∶60.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>35.5∶64.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">206</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49.5∶50.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">59.5∶40.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">54.5∶45.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">70∶30</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">66.5∶33.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">69∶31</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">254</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65.5∶34.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72∶28</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72∶28</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49∶51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65.5∶34.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">53.5∶46.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">104</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71.5∶28.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">62.5∶37.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">66.5∶33.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">326</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71∶29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31∶64</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">32.5∶67.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">64∶36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">59∶41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52∶48</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52.5∶47.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">43∶57</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">41∶59</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>273</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>A/G</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>70∶30</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>58.5∶41.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>65.5∶34.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>335</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>T/C</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>59.5∶40.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>79.5∶20.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>47∶53</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">203</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">68∶32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">48∶52</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">64.5∶35.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>4</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>T/C</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>59.5∶40.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>47.5∶52.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50∶50</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>G/A</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>47∶53</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>56.5∶43.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>48.5∶51.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">209</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">69.5∶30.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75.5∶24.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">78.5∶21.5<xref ref-type=\"table-fn\" rid=\"nt102\">2</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">104</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">76∶24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71∶29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">57.5∶42.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">87</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">19∶81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31∶69</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.5∶82.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71.5∶28.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72.5∶27.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">73.5∶26.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65∶35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">60.5∶39.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65.5∶34.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71∶29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50∶50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">60∶40</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">132</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49.5∶50.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">47.5∶52.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">34∶66</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">166</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16∶84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28∶72</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.5∶83.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">148</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40∶60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21.5∶78.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33.5∶66.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">37.5∶62.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">44.5∶55.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">36.5∶63.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>6</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>T/C</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>66∶43</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>63.5∶36.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>68∶32</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>331</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>C/T</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>44.5∶55.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50∶50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>54∶46</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">265</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33∶67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29.5∶70.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26∶74</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">37.5∶62.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49∶51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">56.5∶43.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">155</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">77.5∶22.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72∶28</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">66.5∶33.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">209</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">51∶49</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50∶50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">34∶66</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">39.5∶60.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49.5∶50.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">42.5∶57.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">155</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71∶29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">73∶27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">57.5∶42.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">331</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65.5∶34.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">58.5∶41.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">61∶39</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">83∶17</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65.5∶34.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">73.5∶26.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">77</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52.5∶47.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">61∶39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">63.5∶36.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">127</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">39∶61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">34∶66</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">47.5∶52.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">278</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">46∶54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">45∶55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">42∶58</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>201</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>A/G</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>31.5∶68.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>48∶52</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>53.5∶46.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>265</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>A/G</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>57∶43</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>70∶30</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>70.5∶29.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">114</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">73∶27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75∶25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52.5∶47.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">71</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">38∶62</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">36∶64</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<xref ref-type=\"table-fn\" rid=\"nt101\">1</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">47</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">35∶65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27.5∶72.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">45.5∶54.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">180</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">70.5∶29.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">60∶40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">69∶31</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">270</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">74.5∶25.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75.5∶24.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">92∶8</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">320</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">46∶54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">41.5∶58.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26.5∶73.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">182</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65∶35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">74∶26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72.5∶27.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G/A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">43.5∶56.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">63∶37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<xref ref-type=\"table-fn\" rid=\"nt101\">1</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">209</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">58.5∶41.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">47∶53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26∶74</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">101</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">C/T</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">69∶31</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">68∶32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">77∶23</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">127</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A/G</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">42.5∶57.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28.5∶71.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">19.5∶80.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">115</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">45∶55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">35.5∶64.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31.5∶68.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71.5∶28.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">63∶37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">63∶37</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>94</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>T/G</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>54∶46</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50∶50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>60.5∶39.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>331</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>C/T</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>70.5∶29.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>66.5∶33.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>66∶34</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">203</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T/C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">60∶40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">58.5∶41.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">56.5∶43.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>4</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>T/C</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>49.5∶50.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50∶50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>51.5∶48.5</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>G/A</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>48.5∶51.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>41.5∶58.5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>50∶50</bold>\n</td></tr></tbody></table></alternatives></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"pgen.1000209.s001\"><label>Figure S1</label><caption><p>Position dependency of heteroplasmy ratios. Combined plot of expected versus observed heteroplasmy ratios for haplotype mixes, as shown by different colours.</p><p>(25.55 MB EPS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000209.s002\"><label>Table S1</label><caption><p>Details of sub-fossil bones of Adélie penguins used to estimate the evolutionary rate for the mitochondrial HVR I region, in addition to those detailed previously ##REF##11910113##[8]##. A total of 62 collection sites and radiocarbon dates of penguin remains from Victoria Land, Antarctica, are listed. A total of 66 bones were obtained from these sites. Carbon-14 dates were supplied by: Geochron Lab.-Krurger Enterprise Inc., Cambridge Massachusetts (conventional and AMS, GX-); IsoTrace Radiocarbon Lab., Toronto (AMS, TO-); NOSAMS, Woods Hole Oceanographic Institution (AMS, OS-); The Institute of Geological and Nuclear Sciences, Lower Hutt, NZ (AMS, NZA-).</p><p>(0.15 MB DOC)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000209.s003\"><label>Table S2</label><caption><p>Discrimination of heteroplasmic bases from background noise.</p><p>(0.04 MB DOC)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000209.s004\"><label>Table S3</label><caption><p>Threshold accuracy.</p><p>(0.05 MB DOC)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label>1</label><p>Indicates one chick only in this family.</p></fn><fn id=\"nt102\"><label>2</label><p>Indicates a third heteroplasmic chick (209 T/C 91.5∶8.5) in this family.</p></fn><fn id=\"nt103\"><label/><p>Bold indicates examples of heteroplasmies at two sites in a mother and her chicks.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p>We gratefully acknowledge support from the Centres of Research Excellence Fund, the Allan Wilson Centre for Molecular Ecology and Evolution, the Marsden Fund, Massey University, and Antarctica New Zealand.</p></fn></fn-group>" ]

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[ "<media xlink:href=\"pgen.1000209.s001.eps\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000209.s002.doc\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000209.s003.doc\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000209.s004.doc\"><caption><p>Click here for additional data file.</p></caption></media>" ]

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[ "<title>Introduction</title>", "<p>In the course of embryonic development, cells are initially totipotent but, after a few divisions, begin to lose potency and are transformed into pluripotent cells, finally becoming terminally differentiated somatic cells. The progressive loss of potency during differentiation has fundamental implications for disease because recovery of pluripotency through nuclear reprogramming is one of the major challenges in regenerative medicine ##REF##17522676##[1]##, and because disruption of the developmental process that gives rise to a terminally differentiated somatic cell from its corresponding progenitor cell may result in malignant transformation ##REF##15864279##[2]##.</p>", "<p>Differentiation of human embryonic stem cells (hESCs) requires the repression of transcription factors involved in maintaining pluripotency and the activation of developmental genes. Both processes are directed by specific epigenetic mechanisms. An example of the first type is the promoter hypermethylation-dependent repression of pluripotency-maintaining genes such as NANOG and OCT4 as stem cells differentiate ##REF##16479162##[3]##. So far, activation of developmental genes during stem cell differentiation upon DNA methylation has been less thoroughly studied. Instead, these developmental genes have been reported as being in a repressed state during early stages of development due to the establishment of a specific pattern of histone modification, termed “bivalent domains”, which consists of large regions of H3 lysine 27 methylation harboring smaller regions of H3 lysine 4 methylation ##REF##16630819##[4]##. This chromatin-repressive status is mediated by the Polycomb group of proteins ##REF##16630818##[5]##, ##REF##17060944##[6]## and is thought to predispose to aberrant promoter hypermethylation in cancer ##REF##17200670##[7]##–##REF##17200673##[9]##. The finding that treatment of hESCs with the demethylating drug 5′-Aza-2′-deoxycytidine causes cardiac differentiation and gene reactivation ##REF##15665584##[10]## prompted us to consider whether promoter DNA methylation could contribute to the establishment and maintenance of specific-gene repression in hESCs. To establish its existence and its putative relationship with aberrant promoter hypermethylation in cancer, we compared the promoter DNA methylation pattern of a panel of 800 cancer-related genes between hESCs and different types of terminally differentiated adult tissues and cancer cell lines.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Stem cell lines</title>", "<p>Cell pellets and/or DNA/RNA were obtained from the following laboratories: Shef-1 (Servicio de Inmunologia, HUCA, Oviedo, Spain), Shef-4, Shef-5, Shef-7, H7, H14 (CSCB, University of Sheffield, Sheffield, UK), H181 (CABIMER, Seville, Spain), I3 (Institute of Reconstructive Neurobiology, University of Bonn, Germany), and cultured and passaged following established protocols by each laboratory. The laboratories that were involved in the establishment and maintenance of these cell lines are members of the European project ESTOOLS (LSHG-CT-2006-018739). The laboratories participating in ESTOOLS only use embryonic stem cell lines derived from IVF embryos that will not be transferred into the womb. These embryos were donated for research according to the legal requirements of the country of origin. All donors gave their written informed consent. Profiling epigenetic regulation in hESCs is one of the research objectives of the ESTOOLS research program, which is supervised by the ethics advisory panel of the ESTOOLS project. The cell lines were established from different embryos and were maintained under different conditions, thereby ensuring the independence of our results for type of line and culture conditions. <italic>In vitro</italic> differentiation of the Shef-1 cell line was achieved as previously described ##REF##17332508##[38]##.</p>", "<p>Primary CD34+ hematopoietic somatic stem cells were purified from cord blood (CB) samples obtained from healthy newborns upon progenitor's informed consent. CB harvesting procedures and informed consents were approved by the Local Hospital Ethics Board. Mononuclear cells were isolated using Ficoll-Hypaque (Amersham Biosciences, Baie d'Urfé, Quebec, Ontario, Canada). CD34+ cells were purified by positive selection using anti-CD34 microbeads (Miltenyi Biotech, Madrid, Spain). Immunomagnetic CD34+ cell-containing cell suspensions were passed through Pro-MACS immunomagnetic columns (Miltenyi Biotech). The flow-through contained the purified CD34+ fraction. The purity was 80% ± 12% (n = 2) (##SUPPL##6##\nFigure S7\n##), as measured by flow cytometry (FACSCanto, Becton Dickinson, Palo Alto, CA) using a fluorochrome-conjugated anti-CD34 antibody (BD).</p>", "<title>Cancer cell lines and primary tissues</title>", "<p>MDA-MB-231, Hela, CasKi, SiHa, HCC1937, BT-474, LoVo, HCT115, DLD1, Co115, HT29, SW48, HCT116, RKO, U937, HL60, AKATA, Raji, Ramos, Karpas, and Farage (ATCC) cell lines were maintained in DMEM medium supplemented with 10% FBS and grown at 37°C under 5% CO₂.</p>", "<p>Lymphocytes and neutrophils were separated from peripheral blood of healthy volunteers, by centrifugation, using Histopaque®-1077 (SIGMA). Lymphocyte-enriched fractions were obtained by collecting the upper pillow of mononuclear cells and granulocytes (mainly neutrophils) following hemolysis of the remaining pellet. RNA from breast, liver, heart, muscle, lung, colon, and lymph node samples were obtained from Ambion (Austin, TX). DNA from breast, heart, brain, and muscle was obtained from Biochain (Hayward, CA). The subjects who participated in this study gave written consent to being subjected to the procedures.</p>", "<title>DNA methylation profiling using bead arrays</title>", "<p>Methylation was assessed at 1,505 CpG sites using Illumina Goldengate Methylation Arrays©, as described in Bibikova <italic>et al.</italic>\n##REF##16899657##[11]##. The amount of bisulfite-modified target DNA that hybridizes to each spot of the Illumina chip was quantified and standardized over a range from 0.0 to 1.0 (effectively 0% and 100% likelihood of gene promoter hypermethylation, respectively). In this work, all sequences with at least 70% likelihood of being hypermethylated (hybridization signal≥0.7) were considered hypermethylated for each specific sample, whereas sequences whose equivalent signal was below 30% (hybridization signal&lt;0.3) were considered unhypermethylated.</p>", "<p>To identify gene promoters that could be hypermethylated in a significant number of samples of a particular group (human embryonic stem cells, normal tissue types, and CCLs), we selected all sequences whose hybridization signal was ≥0.7 in at least 25% of the samples of each group. In general, sequences were classified by the following stepwise algorithm: First, sequences were classified according to the percentage of hESCs hypermethylated in each specific probe set. Therefore, sequences that were hypermethylated in ≥25% and &lt;25% of samples were considered to hypermethylated and unhypermethylated, respectively. Sequences were then tested for hypermethylation in hCCLs and classified according to the percentage (≥25% or &lt;25%) of hypermethylated samples in each probe set. Finally, the percentages of normal tissue types that were hypermethylated in each probe set were calculated, and sequences were classified as hypermethylated in all normal tissue types (100% of samples with signal ≥0.7), unmethylated in all normal tissue types (100% of samples with signal &lt;0.3) or unmethylated in some of the samples but not in all samples (signal&lt;0.3 in at least one, but not all, samples). This algorithm allowed most sequences in the array to be assigned to one of the 12 groups described in ##TAB##0##\nTable 1\n##.</p>", "<p>We next determined whether any of the groups was significantly enriched in a specific type of histone modification. For this reason, all sequences were classified according to publicly available data on histone-modification and Polycomb occupancy ##REF##16630818##[5]##, ##REF##18371363##[12]##, ##REF##17603471##[16]##. A chi-square test was performed to identify significant differences in frequencies between the groups of sequences. Up to 27 tests were conducted so Bonferroni-adjusted, two-tailed probabilities of &lt;0.0018 (0.05/27) were considered significant.</p>", "<title>Bisulfite sequencing of multiple clones</title>", "<p>DNA methylation was determined by PCR analysis after bisulfite modification of the DNA. Bisulfite genomic sequencing was carried out as previously described ##REF##15765097##[39]##. A minimum of six colonies of each sequence and sample were automatically sequenced to determine their degree of methylation. Bisulfite genomic-sequencing primers were designed using Methyl Primer Express Software® (Applied Biosystems). Primer sequences are shown in ##SUPPL##16##\nTable S9\n##.</p>", "<title>RNA purification and real-time RT-PCR analysis</title>", "<p>RNA was isolated with TRIzol Reagent (Invitrogen) according to the manufacturer's instructions. For RT-PCR, 1 μg of total RNA was reverse-transcribed using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Quantitative real-time RT-PCR was performed using TaqMan® Gene Expression Assays and the ABI PRISM® 7900 sequence-detection system (Applied Biosystems). Data are expressed as means ± SD of three replicates of each experiment.</p>" ]

[ "<title>Results</title>", "<title>Promoter DNA methylation profiling in hESCs, normal differentiated tissues and cancer samples</title>", "<p>We used Illumina Goldengate Methylation Arrays© to compare the DNA methylation status of 1,505 sequences (from 807 genes) in eight independently isolated hESCs lines, 21 normal human primary tissues (NPTs) corresponding to six normal tissue types (NTTs) and 21 human cancer cell lines (CCLs) (see <xref ref-type=\"sec\" rid=\"s4\">Methods</xref>). The genes included in the methylation arrays were chosen on the basis of their importance to cellular behavior and differentiation and included genes previously reported to be differentially methylated , as well as tumor suppressor genes, oncogenes and genes coding for factors involved in cell cycle check point ##REF##16899657##[11]##. We first selected the autosomal genes (766) from the arrays in order to exclude DNA methylation-dependent X chromosome inactivated genes. As previously reported, unsupervised clustering of the samples exclusively using the methylation signals of the autosomal genes (1,421 sequences) contained in the arrays enabled the correct classification of each sample within its corresponding group (hESC, NPT, or CCL) (##FIG##0##\nFigure 1A\n##, and see ##SUPPL##0##\nFigure S1\n## in the online supplementary data for this article), thereby confirming that each group of samples has a specific DNA methylation signature ##REF##16899657##[11]##. We then attempted to classify the genes in the array in relation to their methylation status in the three types of sample analyzed (hESC, CCL, and NPT) (##FIG##0##\nFigure 1A\n##, and ##TAB##0##\nTables 1\n## and ##SUPPL##8##\nS1\n##). We found that 65.31% (928/1,421) of the sequences were not frequently hypermethylated in hESCs (array signal≤0.7 in≥25% (2/8) of the samples) and that half of them (464/928) were frequently hypermethylated in CCLs (array signal&gt;0.7 in≥25% (6/21) of the samples). The vast majority of these sequences (99.78%, 463/464) were unmethylated in at least one of the NTTs analyzed (array signal&lt;0.3 in≥1/6 NTTs). This finding is consistent with the view that genes aberrantly hypermethylated in cancer (i.e., not hypermethylated in normal tissues) are not hypermethylated in hESCs ##REF##17211412##[8]##. We called this group of genes classical Class A cancer hypermethylated genes (##TAB##0##\nTables 1\n## and ##SUPPL##8##\nS1\n##).</p>", "<p>Significantly, we found that 34.69% (493/1,421) of the sequences were frequently hypermethylated in hESCs (array signal&gt;0.7 in≥25% (2/8) of the samples). Most of these (79.72%, 393/493) were also frequently hypermethylated in CCLs (array signal&gt;0.7 in≥25% (6/21)) of the samples). Again, many of them (32.32%, 127/393) were unmethylated in at least one of the NTTs analyzed (array signal&lt;0.3 in≥17% (1/6) NTTs) (##FIG##0##\nFigure 1\n##, and ##TAB##0##\nTables 1\n## and ##SUPPL##8##\nS1\n##). In contrast to the Class A cancer hypermethylated genes, those of this group were also frequently hypermethylated in hESCs, so we propose that they can be considered members of a different category of cancer methylated genes, which we have termed Class B cancer hypermethylated genes. Of the 697 sequences frequently hypermethylated in cancer and unmethylated in at least one of the NTTs analyzed, 444 (66.70%) and 127 (18.22%) were respectively classified as Class A and Class B genes (##FIG##0##\nFigure 1\n##, and ##TAB##0##\nTables 1\n## and ##SUPPL##8##\nS1\n##), which indicates, contrary to expectation, that a substantial proportion (around 20%) of cancer methylated genes are also frequently hypermethylated in hESCs.</p>", "<p>Intriguingly, not all the genes frequently hypermethylated in CCLs were completely unmethylated in all the NTTs analyzed (##FIG##0##\nFigure 1\n##, and ##TAB##0##\nTables 1\n## and ##SUPPL##8##\nS1\n##). The frequency of hypermethylation in normal tissues is only of moderate importance for the Class A classical cancer methylated genes, as most of them (78.83%; 350/444 sequences) are unmethylated in NPTs. On the other hand, only 20 sequences corresponding to Class B genes were unmethylated in all the NTTs analyzed (##TAB##0##\nTable 1\n##). When a gene is methylated in some but not all normal tissues, the methylation is probably involved in the specification of a tissue type during development ##REF##18371363##[12]##. When the gene is not hypermethylated in hESCs, tissue-type-dependent selective methylation must occur. In contrast, when the gene is frequently hypermethylated in hESCs, it most probably becomes selectively demethylated upon differentiation as an epigenetic mechanism that is able to facilitate tissue specification. Conversely, when a gene is unmethylated in all normal differentiated cells and hypermethylated in stem cells, the loss of promoter methylation that necessarily occurs during differentiation is more likely to be involved in early differentiation processes than in tissue specification ##REF##18371363##[12]##. Thus, we defined two new subcategories for both Class A and B cancer methylated genes: Subcategory I, for genes that are always unmethylated in normal tissues, and subcategory II, for genes that are sometimes methylated in normal tissues (##FIG##0##\nFigure 1\n##, and ##TAB##0##\nTables 1\n## and ##SUPPL##8##\nS1\n##). The percentage of Class A-II and Class B-II genes is quite similar (7.53% and 6.61%) (##TAB##0##\nTable 1\n##). However, the percentage of genes in Class A-I (24.63%) is much higher than that in Class B-I (1.41%). The genes in these four categories (A-I, A-II, B-I, and B-II) represent 58.2% of all the sequences present in the methylation arrays. By considering the methylation status of the three groups of samples (hESCs, NPTs, and CCLs) we were able to cluster most of the remaining genes in the array into eight additional categories (##TAB##0##\nTable 1\n##), which included, for example, two categories of genes that we define as being constitutively methylated (methylated in hESCs, CCLs, and all NTTs; 11.19%) or constitutively unmethylated (unmethylated in hESCs, CCLs, and all NTTs; 28.43%) genes, respectively. We therefore propose that DNA methylation is not important for the regulation of the genes in these categories. The classification of genes according to their methylation status in hESCs, CCLs, and NTTs, and the interpretation of the biological role of DNA methylation in the genes in each group is summarized in ##TAB##0##\nTable 1\n##. ##SUPPL##8##\nTable S1\n## lists the genes in each group.</p>", "<p>It is important to note here that all the previously described percentages refer to the 807 genes included in methylation arrays, whereas the overall percentage of genes in each group might be different if the entire genome were considered. The classification threshold that we employed to identify genes frequently hypermethylated in hESCs (more than 70% of promoter CpG methylation in more than 25% of samples analyzed) is that which is commonly used to define a gene as being frequently hypermethylated in cancer ##REF##18519670##[13]##. To assess whether our observations hold true for astringent classification thresholds we reexamined our data in search of: i) sequences hypermethylated in most of the hESCs analyzed (array signal&gt;0.7 in≥75% (6/8) of the hESCs) and, ii) sequences “fully methylated” in some of the hESCs analyzed (array signal&gt;0.8) in≥25% (2/8) of the hESCs) (##SUPPL##9##\nTable S2\n##). We found that 5 B-I and 84 B-II sequences fitted the first criterion, and 13 B-I and 86 B-II sequences fitted the second (##SUPPL##9##\nTable S2\n##), which indicates that our conclusions remain valid even with these stricter classification thresholds.</p>", "<p>It has recently been shown that prolonged <italic>in vitro</italic> culture of hESCs is associated with DNA methylation instability ##REF##17409196##[14]##, ##REF##16142235##[15]##. To assess whether promoter hypermethylation of our Class B genes is associated with the <italic>in vitro</italic> culture process, we compared our data with those previously published by Bibikova <italic>et al.</italic>\n##REF##16899657##[11]##. These authors used the Goldengate methylation platform to compare the methylation status of the 1505 CpG sites contained in the arrays in ten hESC lines at low and high passages. They found that, although methylation changes did occur with passage number, such changes were small compared with the differences among cell types. They found five genes (<italic>ASCL2</italic>, <italic>GALR1</italic>, <italic>MEST</italic>, <italic>NPY,</italic> and <italic>SLC5A8</italic>) to be consistently hypermethylated with the passage number (increase in methylation level&gt;0.34 in at least two cell lines (20%)). Three of those genes (<italic>ASCL2</italic>, <italic>NPY,</italic> and <italic>SLC5A8</italic>) are members of Class B-I but, interestingly, none was a Class B-II gene. These results suggest that prolonged <italic>in vitro</italic> culture was only responsible for the promoter hypermethylation of a small fraction (3/97, 3%) of our Class B genes, and that the effect appeared to be greater in Class B-I genes.</p>", "<p>As previously stated, it has recently been proposed that developmental genes are silenced in embryonic stem cells by a Polycomb-dependent bivalent histone-based chromatin mark ##REF##16630819##[4]##, ##REF##16630818##[5]##, which is thought to predispose to aberrant DNA promoter hypermethylation of TSGs in cancer ##REF##17200670##[7]##–##REF##17200673##[9]##. As we found that a subset of cancer methylated genes can also be methylated in hESCs we wanted to investigate the relationship between promoter hypermethylation and the Polycomb-dependent histone modification pattern in hESCs. To this end, we compared our methylation data for the Class A-I, A-II, B-I, and B-II genes with the previously reported histone modification profile and Polycomb occupancy of the same genes in embryonic stem cells ##REF##16630818##[5]##, ##REF##18371363##[12]##, ##REF##17603471##[16]## (##FIG##0##\nFigure 1\n## and ##SUPPL##10##\nTable S3\n##). Consistent with a previous report ##REF##17200673##[9]##, we found that around 35% of the sequences frequently hypermethylated in cancer and unmethylated in at least one of the NTTs analyzed contained chromatin-repressive marks at their promoters (228-277/697 harbored meK27, and 236/697 contained SUZ12). Intriguingly, comparing our methylation data with those of Mikkelsen <italic>et al.</italic>\n##REF##17603471##[16]## we observed that the vast majority (96.4%) of genes harboring meK27 also contained meK4 and that only around 30% of the genes frequently hypermethylated in cancer presented the bivalent chromatin domain (meK4/meK27) in hESCs (##SUPPL##10##\nTable S3\n##).</p>", "<p>When we compared the chromatin patterns and Polycomb occupancy in the Class A-I, A-II, B-I, and B-II genes we found each group to have a specific chromatin signature (p&lt;0.00001). Class A genes were more enriched in Polycomb and bivalent marks (47.5% and 45.5–57.3% of genes, respectively) than Class B genes (19.7% and 21.4–32.7%, respectively) (p&lt;0.00001) (##FIG##0##\nFigure 1B\n## and ##SUPPL##11##\nTable S4\n##). The enrichment of the bivalent mark in Class A genes is primarily due to the low levels of this chromatin signature in Class B-II genes (##SUPPL##11##\nTable S4\n##). Indeed, Class B-I genes exhibit similar levels of meK4/meK27 to Class A genes (##SUPPL##11##\nTable S4\n##) (p&lt;0.00001). Interestingly, the Class II genes, were much less frequently occupied by Polycomb proteins and exhibited fewer bivalent marks (33.3% and 26.5–38.8% of genes, respectively) (p&lt;0.00001) than did Class I genes (45.7% and 47.6–59.3%, respectively), (##FIG##0##\nFigure 1B\n## and ##SUPPL##11##\nTable S4\n##). The lower levels of the bivalent mark in Class II genes were primarily due to the low levels of this chromatin signature in Class B-II genes (##SUPPL##11##\nTable S4\n##). Indeed, Class A-II genes had similar levels of meK4/meK27 to those of Class I genes (##SUPPL##11##\nTable S4\n##) (p&lt;0.00001).</p>", "<title>TSGs repressed by promoter hypermethylation in hESCs</title>", "<p>To test the hypotheses formulated on the basis of the data obtained from the methylation arrays, we focused our attention on four Class B genes (frequently hypermethylated in cancer and hESCs) that were previously widely reported to be genes with tumor suppressor properties and that are frequently hypermethylated in cancer. We selected two (MGMT and SLC5A8) ##REF##11070098##[17]##, ##REF##12829793##[18]## from the Class B-I subcategory (unmethylated in all NTTs) and two (PYCARD and RUNX3) ##REF##11103776##[19]##, ##REF##11955451##[20]## from Class B-II (unmethylated in a number of NTTs). We first employed bisulfite sequencing of multiple clones to determine accurately the promoter DNA methylation status of these genes in hESCs and normal tissues (##FIG##1##\nFigure 2A\n##, and <bold>##SUPPL##1##Figures S2##, ##SUPPL##2##S3##, ##SUPPL##3##S4##, ##SUPPL##4##S5##</bold>). In all cases, bisulfite sequencing data corroborated the results obtained from the arrays and showed that the hypermethylation observed in hESCs affected the majority of the CpGs surrounding the transcriptional start-site of the selected genes. MGMT and SLC5A8 (Class B-I) presented dense promoter hypermethylation in hESCs but not in normal differentiated tissues (##FIG##1##\nFigure 2A\n##, and <bold>Figures ##SUPPL##1##S2##, ##SUPPL##0##S3##</bold>) whilst Class B-II genes were frequently hypermethylated in hESCs and sometimes in normal tissues (<bold>##SUPPL##3##Figures S4##, ##SUPPL##4##S5##</bold>). To understand better the role in promoter hypermethylation of our selected TSGs in hESCs and NTTs, we used q-RT-PCR to measure their expression in both sample groups (##FIG##1##\nFigure 2B\n##, and <bold>##SUPPL##1##Figures S2##, ##SUPPL##2##S3##, ##SUPPL##3##S4##, ##SUPPL##4##S5##</bold>). We found that promoter hypermethylation was always associated with gene repression, but its absence in somatic primary tissues did not necessarily involve the upregulation of the gene. For example, whilst <italic>SLC5A8</italic> was hypomethylated in all the normal tissues analyzed (##SUPPL##2##\nFigure S3A,B\n##), it was only overexpressed in brain, liver, and colon (##SUPPL##2##\nFigure S3C\n##).</p>", "<title>Loss of promoter hypermethylation and gene activation during <italic>in vitro</italic> differentiation of hESCs</title>", "<p>To demonstrate further that the differentiation of hESCs is associated with less DNA methylation at the promoter region of certain genes, we induced the <italic>in vitro</italic> differentiation of the hESC line Shef-1 in two cell lineages (fibroblast-like cells and neural precursors) (##FIG##2##\nFigure 3A\n##). We assessed the lineage specification using previously published markers ##REF##16293578##[21]## (##FIG##2##\nFigure 3A\n##, right-hand panels) and then used methylation arrays to identify genes that became hypomethylated during differentiation. We found that 12.98% (37/285) of the genes hypermethylated in Shef-1 (which were not methylated in all the NTTs analyzed) become unmethylated during <italic>in vitro</italic> differentiation. Of these, 12 genes become unmethylated during neuron differentiation and 25 during spontaneous differentiation (##SUPPL##12##\nTable S5\n##). Three of these genes were common to both groups (##FIG##2##\nFigure 3B\n##) and two of them belonged to Class B-II. It is of particular note that, whilst 9/25 of the genes unmethylated during spontaneous differentiation were of Class B-II, none of the 12 genes unmethylated during neuron differentiation belonged to this category.</p>", "<p>To demonstrate that some TSGs that are frequently hypermethylated in cancer and hESCs can lose methylation during differentiation, we focused our attention on DLC1. We chose this gene because the methylation arrays had shown that it lost promoter methylation during spontaneous differentiation of Shef-1, and because it is known to be a TSG that is frequently hypermethylated in cancer (##SUPPL##5##\nFigure S6\n##) ##REF##17965626##[22]##, ##REF##12645648##[23]##. Bisulfite sequencing of multiple clones corroborated the results obtained with the methylation arrays and showed that DLC1 promoter is hypermethylated in Shef-1 and becomes unmethylated during spontaneous, but not neural, differentiation (##FIG##2##\nFigure 3C\n##). In q-RT-PCR experiments DLC1 was poorly expressed in the Shef-1 cell line and became overexpressed during spontaneous, but not neural, differentiation (##FIG##2##\nFigure 3D\n##).</p>", "<title>TSGs repressed by promoter hypermethylation in hematopoietic stem cell progenitors</title>", "<p>Having demonstrated that some cancer genes are hypermethylated and repressed in hESCs and that they can lose methylation during <italic>in vitro</italic> differentiation of hESCs, we investigated whether this phenomenon is restricted to embryonic development or, conversely, is an epigenetic mechanism associated with stemness status regardless of the ontogenetic stage of the cell. We used methylation arrays to identify genes hypermethylated in CD34+ somatic stem cell progenitors (##SUPPL##6##\nFigure S7\n##) compared with peripheral blood lymphocytes and neutrophils, two types of adult primary cells derived from the CD34+ hematopoietic progenitors. We identified 362 significantly hypermethylated sequences in the CD34+ cells (array signal&gt;0.7) (##SUPPL##13##\nTable S6\n##). The vast majority of these sequences (92.27%, 334/362) were also methylated in hESCs and most were frequently hypermethylated in CCLs (83.43%, 302/362) (##FIG##3##\nFigure 4A\n##, and ##SUPPL##13##\nTable S6\n##). These results suggest that the hypermethylation of cancer genes can occur in stem cells regardless of the ontogenetic stage (embryo vs. adult). We next identified nine sequences that were significantly hypermethylated in CD34+ cells relative to peripheral lymphocytes, and 16 sequences that were hypermethylated in these progenitor cells relative to neutrophils (##SUPPL##14##\nTable S7\n##). Most of the sequences identified were also frequently hypermethylated in hESCs (8/9 for lymphocytes and 14/16 for neutrophils) and CCLs (6/9 for lymphocytes and 13/16 for neutrophils). In addition, there were no sequences common to lymphocytes and neutrophils and most of them were sometimes hypermethylated in NPTs. Interestingly, 28 of these sequences were previously classified as Class B-II genes whilst none of them was from Class B-I (##FIG##3##\nFigure 4A\n##).</p>", "<p>Finally, to demonstrate that some cancer methylated genes are also frequently methylated in somatic progenitor stem cells and that their methylation is important for lineage specification, we considered two genes: <italic>RUNX3</italic> and <italic>AIM2</italic>. We selected <italic>RUNX3</italic> because, in agreement with previously published data ##REF##17352407##[24]##, our methylation arrays showed that, relative to CD34+ cells, <italic>RUNX3</italic> was hypomethylated in peripheral lymphocytes but not in peripheral neutrophils. <italic>AIM2</italic> was selected because it was previously thought to be a TSG that is frequently hypermethylated in cancer (##SUPPL##7##\nFigure S8\n##) ##REF##17726700##[25]## and because, unlike <italic>RUNX3</italic>, it becomes unmethylated specifically in the myeloid lineage (##FIG##3##\nFigure 4B,C\n##). The bisulfite sequencing data confirmed the results obtained with the arrays, showing that the CD34+ cells and the peripheral lymphocytes were densely methylated at the promoter of <italic>AIM2</italic> gene whilst the peripheral neutrophils were almost unmethylated (##FIG##3##\nFigure 4B\n##). To determine the role of promoter hypermethylation of <italic>AIM2</italic> and <italic>RUNX3</italic> in hematopoietic differentiation, we used q-RT-PCR to analyze their expression in our groups of samples (##FIG##3##\nFigure 4C\n##). We found that promoter hypermethylation was always associated with gene repression in both genes and that loss of promoter methylation in <italic>AIM2</italic> and <italic>RUNX3</italic> in peripheral lymphocytes and neutrophils, respectively, was associated with their reexpression (##FIG##3##\nFigure 4C\n##).</p>" ]

[ "<title>Discussion</title>", "<p>Aberrant promoter hypermethylation of TSGs and differentiation factors is a central epigenetic alteration in cancer ##REF##14732866##[26]##, ##REF##17320506##[27]##. The genes undergoing such alterations in cancer have been reported to be repressed in hESCs by the establishment of “bivalent chromatin domains” consisting of activating (H3 lysine 27 methylation) and repressing (H3 lysine 4 methylation) histone marks that keep them poised for activation but, at the same time, predisposes them to aberrant promoter hypermethylation in adult cancers ##REF##17200670##[7]##–##REF##17200673##[9]##. Herein we demonstrate that another level of complexity exists whereby some of the genes frequently aberrantly hypermethylated in cancer are also frequently hypermethylated in hESCs. Our results suggest that, as was previously proposed for mouse cells ##REF##18371437##[28]##, promoter DNA methylation can be an important factor in gene regulation in hESCs.</p>", "<p>On the basis of the methylation status in hESCs we established two categories of cancer methylated genes: Class A genes, which are frequently unmethylated in hESCs, and Class B genes, which are frequently hypermethylated in hESCs. As we unexpectedly found that a substantial proportion of the genes included in both groups were also frequently hypermethylated in normal differentiated tissues, we established two new subcategories of cancer methylated genes: subcategory I, for genes that are mostly unmethylated in normal tissues, and subcategory II, for genes that are sometimes hypermethylated in normal tissues. The biological interpretation of aberrant methylation within Classes A and B cancer methylated genes and their two subcategories is completely different. Class A-I genes are frequently hypermethylated in cancer but not in normal tissues or hESCs. These genes are not supposed to be regulated by DNA methylation during normal development and thus the hypermethylation in cancer should always be interpreted as an aberrant process. Class A-II genes are frequently methylated in CCLs and sometimes in normal tissues, but rarely in hESCs. Methylation of these genes may be important for lineage specification and should be considered aberrant in cancer when it occurs in a tumor type in whose corresponding normal tissue it is not hypermethylated. Class B-I genes (excluding <italic>ASCL2</italic>, <italic>NPY,</italic> and <italic>SLC5A8</italic> genes, whose promoter DNA hypermethylation in hESC lines could be due to the <italic>in vitro</italic> culture process ##REF##16899657##[11]##) are frequently hypermethylated in hESCs and cancer cells lines but never in normal tissues, which suggests that the loss of methylation at the promoters of these genes might be an important influence on the loss of pluripotency during development. Their hypermethylation in cancer should always be considered as aberrant. Class B-II genes are frequently hypermethylated in hESCs and cancer cells, but, as they are also sometimes methylated in normal tissues, their hypermethylation in cancer may only be considered aberrant in tumor types in whose normal counterparts they are completely unmethylated. Apart from this, the fact that not all the genes frequently hypermethylated in cancer were completely unmethylated in all the normal tissues analyzed is a highly important finding in cancer epigenetics ##REF##14732866##[26]## because the promoter hypermethylation of a gene in a particular tumor type should not be considered aberrant when the promoter of this gene is equally hypermethylated in its non-tumorigenic counterpart.</p>", "<p>We found the percentage of Class A-II and Class B-II genes to be quite similar (7.53% and 6.61%), which suggests that the probability of aberrant hypermethylation or improper loss of methylation is similar in genes in which hypermethylation or loss of methylation, respectively, is necessary for lineage specification. However, the percentage of genes in Class A-I is much higher than that in Class B-I (24.63% and 1.41%), implying that it is much easier for a gene that is not naturally regulated by DNA methylation to become aberrantly hypermethylated than for there to be loss of methylation of developmental genes during hESC differentiation.</p>", "<p>Comparing our DNA methylation data with those previously published on the histone modification profile and Polycomb occupancy of the same genes in embryonic stem cells ##REF##16630818##[5]##, ##REF##18371363##[12]##, ##REF##17603471##[16]## we found that the vast majority of genes harboring meK27 also contained meK4. This concurs with the observation that most of the genes repressed in stem cells by Polycomb-repressive marks also contain histone-active marks ##REF##16630819##[4]##. However, as only around one-third of the genes frequently hypermethylated in cancer presented the bivalent chromatin domain (meK4/meK27) in hESCs, our results suggest that this chromatin signature in cancer methylated genes could be less abundant in hESCs than previously expected. However, we must recognize that our study is limited to the set of 807 genes selected for inclusion in the methylation arrays, and that the overall pattern needs to be determined in genome-wide DNA methylation studies, to establish how general our observations are.</p>", "<p>Within our four categories of genes we found those of Class A to be more enriched in Polycomb and bivalent marks than Class B genes, which suggests that the previously described scenario involving bivalent chromatin domains and Polycomb occupancy of cancer methylated genes in embryonic stem cells ##REF##17200670##[7]##–##REF##17200673##[9]## could be more frequent in Class A than in Class B genes. Interestingly, the Class II genes, which we previously suggested were involved in lineage specification because their promoter methylation was tissue-dependent, were much less frequently occupied by Polycomb proteins and exhibited fewer bivalent marks than did Class I genes, which we previously believed to be involved in early differentiation processes. The lower levels of the bivalent mark in Class II genes were primarily due to the low levels of this chromatin signature in Class B-II genes, implying that this subcategory of genes might be relevant to lineage specification. Zhao <italic>et al.</italic>\n##REF##18371363##[12]## proposed that genes harboring meK4/meK27 bivalent marks were primarily involved in early differentiation, whilst those without either mark were involved in lineage specification. As we observed that Class I genes were enriched in the bivalent mark and Class B-II genes were frequently depleted of both marks, the data of Zhao <italic>et al.</italic>\n##REF##18371363##[12]## support our hypothesis that Class I genes are primarily involved in early differentiation processes whilst Class B-II (excluding those whose promoter DNA hypermethylation depends on prolonged <italic>in vitro</italic> culture) are more associated with lineage specification. This hypothesis is further supported by the fact that the gene ontology classification of the two categories shows that Class I genes are associated with biological processes involved in early differentiation, whilst most Class B-II genes are associated with those linked to lineage specification (##SUPPL##15##\nTable S8\n##).</p>", "<p>To investigate further the role of promoter DNA methylation of genes aberrantly hypermethylated in cancer in hESCs, we compared the DNA methylation and expression status of four of the genes identified in the methylation arrays (MGMT and SLC5A8 ##REF##11070098##[17]##, ##REF##12829793##[18]## from Class B-I, and PYCARD and RUNX3 ##REF##11103776##[19]##, ##REF##11955451##[20]## from Class B-II). We found that promoter hypermethylation was always associated with gene repression, but its absence in somatic primary tissues did not necessarily involve the upregulation of the gene, as was the case for <italic>SLC5A8</italic>, in which there was no overexpression upon loss of promoter methylation in peripheral lymphocytes. In view of this, we hypothesized that promoter hypermethylation of the Class B cancer methylated genes in hESCs (excluding those whose promoter DNA hypermethylation depends on prolonged <italic>in vitro</italic> culture ##REF##16899657##[11]##) can be a natural process employed by stem cells to ensure the silencing of genes whose expression is associated with stemness status. When stem cells differentiate, these genes may lose their promoter hypermethylation, which could allow the genes to become overexpressed. However, this does not imply that the gene has become immediately activated, as demonstrated by the fact that some of these genes were still repressed in differentiated tissues. The loss of promoter methylation during differentiation could merely keep these genes poised for activation until they are later required by the somatic cells. The lack of hypomethylation-associated activation in some mature tissues suggests that signals other than the lack of methylation are necessary for these genes to be activated.</p>", "<p>By forcing the <italic>in vitro</italic> differentiation of the hESC line Shef-1 we identified 12 and 25 genes that become unmethylated respectively during neuron and spontaneous differentiation. Interestingly, three of these genes were common to both groups, suggesting that they may be involved in early differentiation processes. This implication is supported by the fact that two of the genes were from Class B-I, which we previously proposed were involved in early development. Whilst the majority of genes unmethylated during spontaneous differentiation were of Class B-II, none of the genes unmethylated during neuron differentiation belonged to this category. This may largely be explained by the fact that the ten genes that were unmethylated during neuron differentiation and did not belong to Class I or II were not classified as “unmethylated in at least one normal tissue type analyzed” because their intermediate levels of methylation in normal tissues did not allowed their classification into any of the four categories described. Moreover, there were many more hypomethylated genes (relative to Shef-1) in normal brain than in neural Shef-1-derived cells. The observations suggest two things: i) the <italic>in vitro</italic> differentiation of hESCs does not reproduce all the epigenetic features present during <italic>in vivo</italic> differentiation, and ii), the unguided spontaneous differentiation of our hESC achieves more epigenetic hits <italic>in vivo</italic> than does neural differentiation.</p>", "<p>One of the genes that we identified using this approach is <italic>DLC1</italic>,. a TSG frequently inactivated by promoter hypermethylation in cancer cells ##REF##17965626##[22]##, ##REF##12645648##[23]##. We found that <italic>DLC1</italic> becomes unmethylated and overexpressed specifically during spontaneous, but not neural, differentiation of the Shef-1 cell line, which suggests that loss of DNA methylation-dependent expression of this gene might be involved in lineage specification. This is supported by the essential role of <italic>DLC1</italic> during embryonic development, whereby <italic>DLC1</italic>-deficient mice are unviable ##REF##15710412##[29]##.</p>", "<p>Finally, we wondered whether the methylation-dependent repression of cancer genes in hESCs is a molecular process associated with embryonic development or if, by contrast, it is an epigenetic mechanism involved in the maintenance of stemness status. The fact that the CD34+ somatic stem cell progenitors featured numerous genes frequently hypermethylated in cancer that are repressed by promoter hypermethylation suggests that, at least for these genes, the process could be associated with stemness status regardless of the ontogenetic stage of the cell, rather than being an event restricted to embryonic development. Since CD34+ cells are primary non-cultured cells, we can also discount the possibility that <italic>in vitro</italic> culture of the hESCs is largely responsible for hypermethylation, which accords with previously published findings ##REF##16899657##[11]##, ##REF##15864307##[30]##, ##REF##17911167##[31]##.</p>", "<p>By comparing the DNA methylation status of CD34+ progenitor cells with those of two types of primary cells that are terminally differentiated from the former (peripheral blood lymphocytes and neutrophils) we identified several genes that lost methylation specifically in just one of lineages. This, in conjunction with knowledge that most of the sequences identified were sometimes hypermethylated in NPTs and most were previously classified as Class B-II genes (those whose regulation by methylation is important for lineage specification and that present aberrant methylation in cancer), suggests that the genes hypermethylated in CD34+ progenitor cells that become unmethylated during differentiation are those primarily involved in lineage specification. That none of the sequences identified in the CD34+ progenitor cells was from Class B-I may well be because the CD34+ cells are not the primary hematopoietic progenitor cells and because Class B-I genes lose methylation in the transition from earlier progenitor stem cells to CD34+ cells. This explanation is consistent with the putative role of these genes in early development ##REF##18371363##[12]## but needs further investigation. Moreover, from our point of view, the fact that some cancer methylated genes are also frequently hypermethylated in adult stem cells is particularly important to our understanding of aberrant methylation in cancer. In the context of the hypothesis of the stem cell origin of cancer ##REF##12629218##[32]##, ##REF##16564000##[33]##, our results suggest that, for TSGs hypermethylated in stem cells <italic>in vivo</italic>, the aberrant process in cancer could be understood as a defect in establishing an unmethylated promoter during differentiation, rather than as an anomalous process of <italic>de novo</italic> hypermethylation (##FIG##4##\nFigure 5\n##).</p>", "<p>Using the above approach, we identified two genes, <italic>AIM2</italic> and <italic>RUNX3,</italic> that were hypermethylated and repressed in CD34+ hematopoietic progenitor cells and that became unmethylated and overexpressed in myeloid and lymphoid lineages, respectively. Both genes are aberrantly hypermethylated in cancer ##REF##11955451##[20]##, ##REF##17726700##[25]##, which indicates that genes frequently hypermethylated in cancer can be naturally repressed by promoter methylation not only in hESCs but also in somatic stem cells. Moreover, the lineage-specific loss of methylation and upregulation of the two <italic>genes</italic> suggests that their expression might be important in lineage specification during hematopoietic differentiation and, more importantly, that the process can be regulated by DNA methylation. <italic>RUNX3</italic> is a well-known transcription factor that regulates lineage-specific gene expression in developmental processes ##REF##12776174##[34]##. Our observation that <italic>RUNX3</italic> loses methylation and becomes expressed during lymphoid, but not myeloid, development is consistent with previous studies showing the necessity of <italic>RUNX3</italic> for T cell development during thymopoiesis ##REF##12796513##[35]##, ##REF##17646406##[36]##, and that RUNX3 knockout mice have T cell phenotypes ##REF##11955451##[20]##, ##REF##12093746##[37]##. Finally, considering all the available evidence and following similar reasoning to before, the aberrant hypermethylation of <italic>RUNX3</italic> observed in the lymphoid human CCL Raji should be understood as the failure of CD34+ cells to lose the promoter methylation necessary to reactivate the gene during hematopoietic differentiation.</p>", "<p>The results presented here are important for four reasons: i) we unexpectedly found a subset of cancer methylated genes that are also frequently methylated in hESCs; ii) the pattern of expression of these genes implies that DNA methylation might have an important role in the control of their expression in hESCs; iii) determining DNA methylation status in hESCs allowed us to define two categories of cancer methylated genes: Class A, containing genes that are never hypermethylated in hESCs, and Class B, containing genes that are frequently hypermethylated in hESCs; and, probably most important, iv) the hypermethylation of some Class B genes in adult stem cells <italic>in vivo</italic> suggests that, for this group of genes, the aberrant methylation in cancer can be understood as a defect in establishing an unmethylated promoter during differentiation, rather than as an anomalous process of <italic>de novo</italic> hypermethylation.</p>" ]

[]

[ "<p>Conceived and designed the experiments: MFF. Performed the experiments: VC AH AH BS AFF EL SC CB RR LB ST NJH. Analyzed the data: VC AH AFF MA. Contributed reagents/materials/analysis tools: AH AH BS PM JGC PL LB NJH HM OB CLL PA BS. Wrote the paper: PA BS ME MFF.</p>", "<p>Developmental genes are silenced in embryonic stem cells by a bivalent histone-based chromatin mark. It has been proposed that this mark also confers a predisposition to aberrant DNA promoter hypermethylation of tumor suppressor genes (TSGs) in cancer. We report here that silencing of a significant proportion of these TSGs in human embryonic and adult stem cells is associated with promoter DNA hypermethylation. Our results indicate a role for DNA methylation in the control of gene expression in human stem cells and suggest that, for genes repressed by promoter hypermethylation in stem cells <italic>in vivo</italic>, the aberrant process in cancer could be understood as a defect in establishing an unmethylated promoter during differentiation, rather than as an anomalous process of <italic>de novo</italic> hypermethylation.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We gratefully acknowledge the Genotyping Unit at the CNIO for their assistance with the methylation arrays technology. The I3 cell line was originally derived by Joseph Itskovitz-Eldor.</p>" ]

[ "<fig id=\"pone-0003294-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003294.g001</object-id><label>Figure 1</label><caption><title>DNA methylation profiling in human embryonic stem cells (hESCs), normal primary tissues, and cancer cell lines.</title><p>(A) Methylation profiles of Class A-I (350), A-II (94), B-I (20), and B-II (107) genes in hESCs (8), normal (21), and cancer (21) samples obtained by Illumina arrays. The methylation levels vary from fully methylated (red) to fully unmethylated (white). The right-hand columns show the methylation status of histone H3 and Polycomb occupancy of the same genes obtained from previously published data ##REF##16630818##[5]##, ##REF##18371363##[12]##, ##REF##17603471##[16]##. Blue, methylation at K4 and K27; orange, methylation at K4 alone; green, no methylation at K4 or K27; black, presence of the Polycomb protein SUZ12. (B) Enrichment of the Polycomb protein SUZ12, the bivalent chromatin signature (K4/K27) or the absence of both marks (none) in Class A and Class B genes (upper panel) and Class I and Class II genes (lower panel).</p></caption></fig>", "<fig id=\"pone-0003294-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003294.g002</object-id><label>Figure 2</label><caption><title>Promoter DNA hypermethylation and repression of <italic>MGMT</italic> in hESCs.</title><p>(A) Bisulfite genomic sequencing of multiple clones of the MGMT promoter in hESCs (I3, H14), normal primary tissues (Pool lymphocytes, normal breast) and two CCLs of lymphoid and breast origin (U937 and MDA-MB-231, respectively). Black, methylated CpG; white, unmethylated CpG; red, CpG not present. The green bar above the diagram of the MGMT CpG island indicates the location of the probe used in the methylation arrays. (B) Relationship between MGMT promoter hypermethylation and expression in hESC, normal, and cancer samples. The upper panel shows the relative methylation signal obtained with the methylation arrays and the lower panel the expression levels of MGMT mRNA relative to GAPDH.</p></caption></fig>", "<fig id=\"pone-0003294-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003294.g003</object-id><label>Figure 3</label><caption><title>Loss of promoter DNA methylation during <italic>in vitro</italic> differentiation of hESCs.</title><p>(A) Left-hand images, Shef-1 stem cell line (upper) and the same cells after neural differentiation (middle) and spontaneous differentiation to fibroblast-like cells (lower). The right-hand panels show the relative mRNA levels of pluripotency (NANOG, OCT4), neuroectodermal (PAX6, NEUROD1), and mesodermal (COL1A1, FN1) markers before and after Shef-1 differentiation. (B) Number of sequences hypomethylated during Shef-1 neural (red circle) and spontaneous (blue circle) differentiation, and their overlap with Class B-I and Class B-II genes (black circles). (C) Bisulfite genomic sequencing of multiple clones of the DLC1 promoter in Shef-1 stem cell line (upper) and the same cells after neural differentiation (middle) and spontaneous differentiation to fibroblast-like cells (lower). The color code is as for ##FIG##1##Figure 2##. (D) Relationship between DLC1 promoter hypermethylation and expression during differentiation of Shef-1 cells. The upper panel shows the relative methylation signal obtained with the methylation arrays and the lower panel the expression levels of DLC1 mRNA relative to GAPDH.</p></caption></fig>", "<fig id=\"pone-0003294-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003294.g004</object-id><label>Figure 4</label><caption><title>Cancer genes hypermethylated in somatic stem cells.</title><p>(A) The left-hand panel shows the numbers of sequences that are hypermethylated in the somatic stem cells CD34+, and hypermethylated in hESCs and CCLs. Note that most of the sequences hypermethylated in somatic stem cells are also hypermethylated in embryonic stem cells. The right-hand panel shows the number of sequences hypermethylated in CD34+ cells (black circle) classified as Class B-II genes (red circle). Sequences hypermethylated in CD34+ cells were never classified as Class B-I genes (blue circle). (B) Bisulfite genomic sequencing of multiple clones of the AIM2 promoter in Shef-1 and I3 stem cell lines (upper), CD34+ hematopoietic stem cell progenitors (middle), and terminally differentiated hematopoietic cells (peripheral lymphocytes and neutrophils). The color code is as for ##FIG##1##Figure 2##. (C) Relationship between <italic>AIM2</italic> and <italic>RUNX3</italic> promoter hypermethylation and expression in CD34+ somatic hematopoietic stem cell progenitors and terminally differentiated hematopoietic cells (peripheral lymphocytes and neutrophils). The upper panel shows the relative methylation signal obtained with the methylation arrays and the lower panel the expression levels of <italic>AIM2</italic> and <italic>RUNX3</italic> mRNAs relative to GAPDH.</p></caption></fig>", "<fig id=\"pone-0003294-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003294.g005</object-id><label>Figure 5</label><caption><title>Proposed model of aberrant methylation in cancer for genes frequently hypermethylated in stem cells <italic>in vivo.</italic>\n</title><p>The loss of promoter hypermethylation might be necessary for overexpression of a subset of Class B genes during differentiation. The aberrant process in cancer for these genes should be understood as a defect in establishing an unmethylated promoter during differentiation, rather than as an anomalous process of <italic>de novo</italic> hypermethylation.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003294-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003294.t001</object-id><label>Table 1</label><caption><title>Classification of genes according to their promoter methylation status in hESCs, normal tissues, and CCLs, and proposed biological role for each group.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Methylation in hESCs</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Methylation in CCLs</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Methylation in NTTs</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Proposed biological role</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Name of the category</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Group of genes from Supplementary ##TAB##0##Table 1##\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1421 Sequences</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hypermethylated in hESCs&gt;0.7 in≥2/8 samples</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hypermethylated in hCCLs&gt;0.7 in≥6/21 samples</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">159 Sequences (11.19%) hypermethylated in all NTTs (&gt;0.7 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes constitutively hypermethylated</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">20 Sequences (1.41%) unmethylated in all NTTs (&lt;0.3 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes that become demethylated early during hESC differentiation or that become aberrantly hypermethylated during <italic>in vitro</italic> culture hESCs. Their hypermethylation might provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Class B-I</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">393 Sequences (27.66%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">107 Sequences (7.53%) sometimes unmethylated (≤0.3 signal in ≥1/6 and ≤5/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes which demethylation during hESC differentiation might be important for lineage specification. Their hypermethylation might provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Class B-II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">493 Sequences (34.69%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not hypermethylated in hCCLs</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16 Sequences (1.13%) hypermethylated in all NTTs (&gt;0.7 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes that become frequently demethylated in cancer</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not&gt;0.7 in≥6/21 samples</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11 Sequences (0.77%) unmethylated in all NTTs (&lt;0.3 in 6/6 samples )</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes that become demethylated early during hESC differentiation. Their hypermethylation might not provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">100 Sequences (7.04%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">39 Sequences (5.07%) sometimes unmethylated (≤0.3 signal in ≥1/6 and ≤5/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes which demethylation during hESC differentiation might be important for lineage specification. Their hypermethylation might not provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not hypermethylated in hESCs not&gt;0.7 in≥2/8 samples</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hypermethylated in hCCLs&gt;0.7 in≥6/21 samples</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 Sequences (0.07%) hypermethylated in all NTTs (&gt;0.7 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes hypermethylated early during hESC differentiation. Their hypermethylation should not provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G7</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">350 Sequences (24.63%) unmethylated in all NTTs (&lt;0.3 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes constitutively unmethylated during normal development. Their aberrant hypermethylation provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Class A-I</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G8</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">464 Sequences (32.65%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">94 Sequences (6.61%) sometimes unmethylated (≤0.3 signal in ≥1/6 and ≤5/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes which hypermethylation during hESC differentiation might be important for lineage specification. Their aberrant hypermethylation provide advantages to the cancer cells.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Class A-II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G9</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">928 Sequences (65.31%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not hypermethylated in hCCLs</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 Sequences (0.07%) hypermethylated in all NTTs (&gt;0.7 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes hypermethylated early during hESC differentiation. These genes could be aberrantly hypomethylated in cancer.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G10</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not&gt;0.7 in≥6/21 samples</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">404 Sequences (28.43%) unmethylated in all NTTs (&lt;0.3 in 6/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes constitutively hypomethylated</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G11</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">464 Sequences (32.65%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52 Sequences (3.66%) sometimes unmethylated (≤0.3 signal in ≥1/6 and ≤5/6 samples)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes which hypermethylation during hESC differentiation might be important for lineage specification. These genes could be aberrantly hypomethylated in cancer.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">-</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G12</td></tr></tbody></table></alternatives></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s001\"><label>Figure S1</label><caption><p>Unsupervised cluster analysis of human embryonic stem cells (hESCs), human cancer cell lines (CCLs), and normal primary tissues based on correlation of methylation profiles of 1,421 sequences. The methylation levels vary from fully methylated (red) to fully unmethylated (white) sequences. The final two rows correspond to in vitro-methylated DNA (IVD), used as a positive control for methylation.</p><p>(0.20 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s002\"><label>Figure S2</label><caption><p>Methylation status of MGMT in hESCs, normal tissues, and CCLs. (A) Methylation profiles of MGMT gene obtained by Illumina arrays and expressed as relative methylation from fully unmethylated (0) to fully methylated (1). (B) Bisulfite genomic sequencing of multiple clones of the MGMT promoter in hESCs and normal primary tissues. Color code as for ##FIG##0##Fig. 1##. (C) Relative expression of MGMT in hESCs and normal tissue. qPCR data are normalized with respect to GAPDH expression and presented as the percentage relative to normal lymphocytes.</p><p>(0.04 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s003\"><label>Figure S3</label><caption><p>Hypermethylation of SLC5A8 in hESCs. (A) Methylation profiles of SLC5A8 gene obtained by Illumina arrays and expressed as relative methylation, from fully unmethylated (0) to fully methylated (1). (B) Bisulfite genomic sequencing of multiple clones of the SLC5A8 promoter in hESCs and normal primary tissues. Color code as for ##FIG##0##Fig. 1##. (C) Relative expression of SLC5A8 in hESCs and normal tissue. qPCR data are normalized with respect to GAPDH expression and are presented as the percentage relative to normal lymphocytes.</p><p>(0.03 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s004\"><label>Figure S4</label><caption><p>Hypermethylation of PYCARD in hESCs. (A) Methylation profiles of PYCARD gene obtained by Illumina arrays and expressed as relative methylation from fully unmethylated (0) to fully methylated (1). (B) Bisulfite genomic sequencing of multiple clones of the PYCARD promoter in hESCs and normal primary tissues. Color code as for ##FIG##0##Fig. 1##. (C) Relative expression of PYCARD in hESCs and normal tissue. qPCR data are normalized with respect to GAPDH expression and are presented as the percentage relative to normal lymphocytes.</p><p>(0.03 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s005\"><label>Figure S5</label><caption><p>Hypermethylation of RUNX3 in hESCs. (A) Methylation profiles of RUNX3 gene obtained by Illumina arrays and expressed as relative methylation from fully unmethylated (0) to fully methylated (1). Red arrow indicates methylation levels in normal lymphocytes purified from blood. (B) Bisulfite genomic sequencing of multiple clones of the RUNX3 promoter in hESCs and normal primary tissues. Color code as for ##FIG##0##Fig. 1##. (C) Relative expression of RUNX3 in hESCs and normal tissue. qPCR data are normalized with respect to GAPDH expression and are presented as the percentage relative to normal lymphocytes.</p><p>(0.02 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s006\"><label>Figure S6</label><caption><p>Hypermethylation of DLC1 in hESCs. Methylation profiles of DLC1 gene obtained by Illumina arrays and expressed as relative methylation, from fully unmethylated (0) to fully methylated (1).</p><p>(0.02 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s007\"><label>Figure S7</label><caption><p>Flow cytometry analysis of the purity of CD34+ cells after purification by positive selection using anti-CD34 microbeads. Detection signals were obtained using a fluorochrome-conjugated anti-CD34 antibody (BD). Purity was 80% ± 12% (n = 2).</p><p>(0.01 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s008\"><label>Figure S8</label><caption><p>Hypermethylation of AIM2 in hESCs. Methylation profiles of AIM2 gene obtained by Illumina arrays and expressed as relative methylation, from fully unmethylated (0) to fully methylated (1).</p><p>(0.02 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s009\"><label>Table S1</label><caption><p>List of genes belonging to each group defined in Supplementary ##TAB##0##Table 1##.</p><p>(1.20 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s010\"><label>Table S2</label><caption><p>List of genes identified as being hypermethylated in hESCs using different classification thresholds than that used in ##SUPPL##8##Table S1##.</p><p>(0.32 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s011\"><label>Table S3</label><caption><p>Methylation data, histone marks, and Polycomb occupancy for genes in the four main categories: A-I, A-II, B-I, and B-II. Raw data from the methylation array for each sample are included. The final three columns summarize information about histone marks and Polycomb occupation published elsewhere. In the HK4/K27 methylation column, K4 stands for 3me-lysine 4 of histone H3, while K27 stands for 3me-lysine 27 of histone H3. In the Polycomb occupation column (+) and (−) respectively refer to the presence and absence of the protein SUZ12.</p><p>(0.89 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s012\"><label>Table S4</label><caption><p>Histone marks and Polycomb occupation in Class A-I, A-II, B-I, and B-II genes. The first table shows each group separately, the second shows Group A vs. group B, and the third Class I vs. Class II genes. The number of genes is presented with the probability of each modification on the right and the percentage on the left.</p><p>(0.04 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s013\"><label>Table S5</label><caption><p>List of genes that are hypomethylated during in vitro differentiation of the embryonic stem cell line Shef-1. Methylation levels from the Illumina array are reported.</p><p>(0.02 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s014\"><label>Table S6</label><caption><p>Genes that are hypermethylated in CD34+ hematopoietic stem cell progenitors. Methylation levels from the Illumina array are reported.</p><p>(0.39 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s015\"><label>Table S7</label><caption><p>Genes that are hypomethylated in peripheral blood lymphocytes and neutrophils relative to CD34+ hematopoietic stem cell progenitors.</p><p>(0.02 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s016\"><label>Table S8</label><caption><p>Summary of the gene ontology GO terms associated with the genes of Classes A-I, A-II, B-I, and B-II. The analysis was done using the web tool of the PANTHER database. Corresponding probabilities of each term and the chromatin-associated gene function (right), based on Zhao et al. (2007), are presented.</p><p>(0.02 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003294.s017\"><label>Table S9</label><caption><p>Primers used for bisulfite sequencing.</p><p>(0.02 MB XLS)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label/><p>The classification criteria are described in the <xref ref-type=\"sec\" rid=\"s4\">Methods</xref> section.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work was primarily supported by the European Union (LSHG-CT-2006-018739; ESTOOLS). MFF is funded by the Spanish Ramon &amp; Cajal Programme and the Health Department of the Spanish Government (PI061267). The Cancer Epigenetics group at the CNIO is supported by the Health (FIS01-04) and Education and Science (I+D+I MCYT08-03, FU2004-02073/BMC and Consolider MEC09-05) Departments of the Spanish Government, the European Grant TRANSFOG LSHC-CT-2004-503438, and the Spanish Association Against Cancer (AECC). VC is a recipient of a Fellowship from the FPU Spanish Research Programme. CLL and BSA are supported by the Health Department of the Spanish Government (PI051707). The BACM is supported by the Consejería de Salud de la Junta de Andalucía (0029 and, 0030/2006 to PM) and, the Spanish Ministry of Health to PM (FIS PI070026). CB is supported by the International Jose Carreras Foundation against Leukemia (EDThomas-05) and the ISCIII (FIS 3+3 contract). The Institute of Reconstructive Neurobiology received additional funding from the DFG and the Hertie Foundation. BS, AbH and AnH are supported by the Fundación Progreso y Salud and Instituto de Salud Carlos III-Red Española de Terapia Celular (RD06/0010/0025 ). PWA, NH and HDM are also supported by the MRC.</p></fn></fn-group>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Immunocompetence has reached a central focus in evolutionary and behavioural ecology after the general upsurge of interest in host-parasite interactions, to the point of the emergence of immunoecology as a new scientific discipline ##REF##21237861##[1]##. Birds have been used as the main models for testing a variety of hypotheses and life-history trade-offs, for which researchers have been prompted to learn and apply immune techniques suitable for both laboratory and field experiments. The PHA-induced skin swelling test has been intensively used, and is now considered a classical immunological technique ##UREF##0##[2]##. Adapted from the poultry science methods used in the seventies ##REF##300748##[3]##, the technique consists of subcutaneous injection of the mitogen phytohemagglutinin (PHA) dissolved in phosphate-buffered saline (PBS), usually in the wing patagium, and quantifying concomitant swelling at the site of injection over time. The resulting swelling, usually measured 24 h post-injection, is interpreted as an index of cell-mediated immunocompetence ##UREF##0##[2]##, ##UREF##1##[4]##. The extreme popularity of this immune test seems to arise from its simplicity, requiring little training and no laboratory facilities, and its feasibility <italic>in vivo</italic> under field conditions ##UREF##0##[2]##. Reflecting its wide use, the simplified protocol proposed by Smits et al ##UREF##1##[4]##, which involves avoiding the injection of PBS in the opposite patagium as an unneeded control ##UREF##0##[2]##, has been cited ca. 200 times since its publication in 1999 (ISI web of Science, acceded on August 2008). The test has broadened its applicability not only in birds but also in fishes, amphibians, reptiles and mammals ##UREF##2##[5]##–##UREF##4##[8]## to address a variety of questions in recent years, covering a range of topics from classical host-parasite interactions ##REF##17717814##[7]##, ##REF##18171155##[9]## to the evolution of coloration ##UREF##2##[5]##, ##REF##17121984##[10]##, behaviour ##UREF##5##[11]##, ##UREF##6##[12]##, mating systems ##UREF##7##[13]##, physiological trade-offs ##REF##17121984##[10]##, ##UREF##8##[14]##, immunocompetence ##REF##17891740##[15]##, ##UREF##9##[16]##, foraging strategies ##REF##17124570##[17]##, ecotoxicology ##REF##16629156##[18]##, ##REF##17454562##[19]##, veterinary sciences ##UREF##10##[20]## and conservation biology ##UREF##3##[6]##, ##UREF##11##[21]##.</p>", "<p>The PHA test has been used as a measure of T-cell mediated immunocompetence after the pioneering work by Goto <italic>et al</italic>\n##REF##674011##[22]##, who showed a reduction of the skin response in thymectomized chickens (thus being unable to produce circulating T-cells). Doubts have arisen in recent years, however, among evolutionary ecologists about the true nature of the immune reaction provoked by PHA and its interpretation. Recent histological work has shown the intensive infiltration of many immune cell types in the PHA-injected patagium of birds over the course of the swelling response, involving both innate and adaptive components of the immune system, and cautions against interpreting larger swellings as greater cell-mediated immunocompetence ##UREF##0##[2]##. Since B and T lymphocytes were not distinguishable in that histological study, there is still a need to differentiate between innate, nonspecific inflammatory reactions and the acquired, or specific cell mediated immune responses supposedly tested through PHA injection. Moreover, there is no conclusive evidence supporting secondary responses as greater after a previous exposure to PHA, as expected from a true acquired immune response ##REF##17028055##[23]##. Overall, the use of the PHA test as a surrogate of T-cell mediated immunocompetence has been recently questioned, posing serious doubts about the interpretation of a huge amount of previous work based on this technique ##REF##17028055##[23]##. Here, we present experimental results showing that secondary responses to PHA injection are consistently larger than primary ones in a number of bird species. Moreover, the simultaneous quantification of several T-lymphocyte subsets and proteins circulating in the bloodstream (see below) shows that PHA-induced skin swellings are related to the proliferation of T-cell subsets responsible for the acquired immune response, thus supporting this test as a reliable technique to measure <italic>in vivo</italic> T-cell mediated immune responses.</p>", "<title>Components of the immune response</title>", "<p>We measured blood-circulating T lymphocytes and proteins associated with the cellular and innate immune responses supposedly elicited by the PHA-immune challenge. Circulating T lymphocytes produced in the thymus, which are characterised by their expression of special T cell receptors (TCR), are responsible for the cell-mediated immune response in vertebrates. Briefly, T-cells are a group of very distinct subsets among which the most abundant are CD4⁺ (active lineages), CD5⁺ (adyuvant lineages), and CD8⁺ cells (memory or antigen presenting cells). The first two subsets are implicated in cellular based defence, while CD8⁺ constitute the most common memory subset. The CD4⁺ subset is implicated in the production of several active substances, such as cytokines, interferon and several types of interleukin, such as interleukin -6 (IL-6). The CD4⁺ subset participates in the first phase of the skin swelling response (i.e., 6–12 h after injection), where there is exudation of plasma from surrounding vascular tissues and edema at the injected site, by activating local innate cell populations (mainly basophils and macrophages) ##UREF##12##[24]##. The CD5⁺ subset is far less common and more specialised, being implicated in intracellular kinase activity (activator and substrate) and cell mediated signalling as well the maturation of other T-cell subsets ##REF##11123317##[25]##. The CD8⁺ subset, on the other hand, is responsible for specific antigen expression, although it also presents discrete cytolytic activity ##UREF##13##[26]##.</p>", "<p>Albumin is the largest single fraction of circulating protein in healthy birds. It serves as the major protein reservoir, the main contributor of colloidal osmotic pressure, a participant in acid-base homeostasis, and transport carrier for small molecules such as minerals, hormones, vitamins and fatty acids. Albumin is transformed by the organism into globulins when facing an infection process ##UREF##14##[27]##. Alpha globulins (α-globulins) are a very heterogeneous group of proteins manufactured almost entirely by the liver, including many transport proteins such as lipoproteins (α-1), haptoglobin, ceruloplasmin, and macroglobulins (α-2) ##UREF##15##[28]##, ##UREF##16##[29]##. Because many of these α-globulins function as acute phase proteins which are elevated in inflammatory processes, they serve as a useful index in the diagnosis and monitoring of many infectious diseases and other causes of acute or chronic inflammation ##UREF##15##[28]##. Briefly, α-1 globulins (lipoproteins) transport lipids throughout circulation, while among α-2 globulins, haptoglobin protects kidneys from tissue destruction by binding free hemoglobin after hemolysis. Ceruloplasmin, an antioxidant glycoprotein, transports copper to cells while macroglobulin is unique as an antiproteinase both in terms of the broad spectrum of enzymes that it can inhibit and the nature of its inhibitory activity. One or two of these subfractions can be identified by electrophoresis ##UREF##17##[30]##. Betaglobulins (β–globulins) are also heterogeneous, including C-reactive protein, complement, and fibrinogen (β-1), or carrier proteins such as lipoproteins and transferrine- (β-2). Many of the β-globulins are also acute phase proteins. Among β-1 globulins, complement is the primary mediator of the antigen-antibody reaction. The C reactive protein plays an important role in initiating and modulating inflammatory and immune responses while fibrinogen plays an important role in homeostasis, but is also the main contributor to inflammatory and tissue repair processes. β-2 globulins, on the other hand, transport lipids throughout circulation (high molecular weight lipoproteins) and carry iron from the cells involved with the absorption or storage of iron (transferrin). Contrary to mammals, no immunoglobulins are present in this fraction in birds ##UREF##14##[27]##. As in the α-globulins, one or two subfractions can be identified ##UREF##17##[30]##. Finally, the gamma (γ-globulins) fraction contains most of the immunoglobulins in birds, which are involved in the humoral immune response.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Experiment 1: Assessment of the secondary immune response</title>", "<p>We used 125 birds from 39 parrot species (Order Psittaciformes, see ##TAB##0##Table 1##) varying in body size (range: 20–250 g), ecological, and life history traits ##UREF##23##[41]##. Birds were purchased in the pet market, comprising both wild-caught and captive-bred species ##UREF##24##[42]##, and were housed indoor in standard cages and provided with commercial parrot food and water <italic>ad libitum</italic>. After a period of two weeks for acclimatisation, birds were injected in the left patagium with 20μl of 5:1 PHA-P (L8754 Sigma-Aldrich) in PBS, following Smits <italic>et al.</italic>\n##UREF##1##[4]##. Patagium width was measured at the point of injection (to the nearest 0.01 mm) three times just prior to and 24 h after injection, using a pressure sensitive micrometer (Baxlo Precission). Average measurements were then used given their high repeatability (<italic>r</italic>&gt;0.99 in all the four measurement instances). The primary response was estimated as the difference between the second and the first patagium width. After a randomly selected time elapsed from the first injection (range: 5–250 days), the same protocol was repeated to estimate the secondary response. The right patagium was used this time, to avoid the potential effects of tissue damage in the previously used patagium. Body mass (to the nearest g) was recorded in both cases to control for its positive effect on the PHA-induced skin swelling in both intra- ##UREF##18##[31]## and interspecific studies ##UREF##21##[35]##.</p>", "<title>Experiment 2: Circulating lymphocyte and globulin components of the primary and secondary immune responses</title>", "<p>A subsample of 20 birds was used for assessing changes in lymphocyte and globulin profiles circulating in blood which are related to T-cell mediated and innate immune responses, respectively. These birds corresponded to five species, which showed very different primary responses (range: 0.54–1.30, see ##TAB##1##Table 2##). After the two-weeks acclimatisation period, birds were bled (0.9 ml taken from the jugular vein) for cytometry and electrophoretic analyses. This sample showed the basal profiles. The first PHA response was elicited ten days later, following the above described protocol, and a second blood sample was obtained when measuring skin swelling 24 h after the injection. The third blood sample was obtained in the same way after provoking a secondary immune response ten days later, using the opposite patagium. A sample of six birds from the same species were used as controls; these birds were injected with just 20μl of PBS (thus do not eliciting an immune response; 2) and manipulated in the same way to obtain blood samples at the same time intervals. Body mass was recorded from all birds in the three sampling instances. Blood was kept cool until centrifugation within the following 12 h to separate plasma for protein electrophoresis.</p>", "<title>Peripheral lymphocyte isolation, flow cytometry and cell sorting</title>", "<p>Lymphocytes of peripheral blood were isolated as described previously ##REF##12712281##[43]##, ##REF##15719198##[44]##. Lymphocytes were isolated with the mononuclear cell layer from an aliquot of the blood layered on top of 3ml of Histopaque 1119 (Sigma) and 3ml of Histopaque 1077 (Sigma) and centrifuged at 700g for 30 min. The mononuclear cell layer (above 1077) was collected and cells washed twice with 10ml of C-RPMI ##REF##12712281##[43]##. For cell sorting, T-cell characterisation, and analysis of the dynamics of γδ T-cell subsets, fluorescing isothiocyanate-labeled mouse anti-avian CD4⁺ and CD5⁺ antibodies, an R-phycoerythrin-labeled mouse anti-avian CD8⁺α monoclonal antibody (all from Abd-Serotec, Oxford, UK), were used. All antibody concentrations and dilutions were tested prior to starting the animal experiment. For every test, 0.5ml of whole blood were incubated in parallel with the appropriate monoclonal antibodies (30 min in the dark). Aliquots of 10μl were directly analysed using a Guava EasyCyte Plus (Guava Technologies, Hayward, California, USA), to measure absolute numbers of each of the marked subsets. Flow cytometry is nowadays widely recognised as the most accurate method to measure cellular components of immunocompetence in vertebrates, including humans ##UREF##25##[45]##–##REF##15876797##[49]##.</p>", "<title>Plasma protein electrophoresis</title>", "<p>Total plasma proteins were quantified by the Biuret method ##UREF##28##[50]##. Then, plasma protein fractions were determined on commercial agarose gels (Hydragel Protein (E), Sebia Hispania S.A., Barcelona, Spain) using a semi-automated Hydrasys System (Sebia Hispania S.A., Barcelona, Spain) with manufacturer's reagents to determine the concentration of albumin and globulins (α, β and γ-globulins).</p>", "<title>Statistical analyses</title>", "<p>Generalized linear mixed models (GLMM) were used to test for individual changes between successive immune challenges. Contrary to simple matched-pairs tests, a GLMM (with normal error distribution and identity link function) allowed the testing of the effect of the second PHA injection (fixed factor) on skin-swelling responses while simultaneously controlling for initial body mass (continuous variable) and individual identity nested on species (random factor). A second GLMM was used to assess whether the magnitude of individual changes between the two successive PHA-induced swellings was related to individual changes in body mass and time elapsed between injections (as covariates) while controlling for species effects (random factor). Repeated measurement tests were used to examine individual changes in lymphocyte subsets and protein concentrations between the three sampling instances of experiment 2. Sphericity tests indicated the use of the F statistic for our data set. Bonferroni's adjustment to α = 0.01 was applied for analyses of proteins since they were expressed as interrelated concentrations. Simple and multivariate regression models were built to assess the single and combined contribution of changes in lymphocyte levels and protein concentrations on local skin swellings. All tests were performed with SAS v. 8.2 (SAS Institute Inc. 2004).</p>", "<p>The first author (JLT) obtained the Spanish certificates that legally allow us to design (Certificate A) and conduct experimental research work using live animals (Certificate B), and all work was done under institutional approval of the competent Spanish wildlife agency (Consejeria de Medio Ambiente, Junta de Andalucía).</p>" ]

[ "<title>Results and Discussion</title>", "<p>The PHA-induced tissue swelling was on average 86% larger in the second than in the first immune challenge (time range between PHA challenges: 5–250 days), with only four out of 125 individuals showing small increases (&lt;10%). Changes in body mass, however, were unappreciable (0.43% on average) between the first and second immune tests (##FIG##0##Fig. 1##). The second PHA-induced tissue swelling was significantly larger than the first (F_1,123 = 482.67, P&lt;0.0001), while controlling for the species body mass (F_1,123 = 26.94, P&lt;0.0001) and the significant differences in PHA responses among the variety of species tested (Z = 7.22, P&lt;0.0001). The swelling increase of individuals (i.e., the absolute difference between the second and the first response) was unrelated to their changes in body mass (<italic>F</italic>\n_1,83 = 0.02, <italic>P</italic> = 0.89) or time elapsed between the two immune tests (F_1,83 = 2.6, P = 0.11), while controlling again for body mass (F_1,83 = 1.02, P = 0.31) and species (Z = 0.67, <italic>P</italic> = 0.25). To our knowledge, this is the first experimental work designed to test larger secondary than primary responses to PHA injection. Nonetheless, the literature shows anecdotal and inconsistent evidence obtained from unrelated experiments and small sample sizes: four captive birds used as experimental controls showed larger secondary responses ##UREF##18##[31]##, while four wild birds recaptured and tested for immunity about one year later ##UREF##19##[32]## and ten captive birds resampled after four months ##UREF##20##[33]## did not show appreciable differences between the first and the second immune challenge. A better sample consisting of 86 broods of nestling passerines showed larger secondary swellings when challenged two days after a first injection, results which were not interpreted as evidence of acquired immunity but rather as a matter of methodology to be considered in statistical analyses ##REF##10917529##[34]##. These larger secondary responses, however, could be confounded by ontogeny and thus reflect to some extent the development of immunocompetence during the growth period of chicks in the nest ##UREF##21##[35]##. Our results, however, clearly demonstrate that the PHA-test provokes a greater swelling on the second compared with the first PHA response, a critical requirement if the test is to be considered indicative of a true cell-mediated acquired immunity ##REF##17028055##[23]##. Moreover, greater secondary responses appear as soon as five days after the first PHA injection as well as long time after injection (at least 250 days), and thus could provide lifelong immunity upon subsequent exposure as expected from the acquired T-cell mediated immune system ##REF##17028055##[23]##.</p>", "<p>A concomitant prediction is that if the swelling is produced by the proliferation of T lymphocytes typically involved in the acquired immune response, then there is likely to be a much lower level of these lymphocytes at first exposure compared to subsequent exposures to PHA ##REF##17028055##[23]##. Our flow cytometry results fully support this. The increases in circulating T-lymphocyte subsets from basal levels to profiles resulting after the first and second PHA-tests (##FIG##1##Fig. 2##) were significant for both CD4⁺ active subset (F_2,28 = 290.57, P&lt;0.0001), CD5⁺ coadyuvant subset (F_2,28 = 82.74, P&lt;0.0001) and CD8⁺ memory subset (F_2,28 = 182.33, P&lt;0.0001), while controlling for significant differences among the species tested (all P&lt;0.006). There were always significant differences between the three instances of blood sampling (Helmert transformation, all P&lt;0.0001). As expected, control birds (injected only with PBS) did not show changes in lymphocyte profiles (P-range: 0.38–0.85, ##FIG##1##Fig. 2##). Therefore, PHA exposure is clearly responsible for the proliferation of lymphocytes associated with an acquired T-cell mediated immune response.</p>", "<p>Plasma protein concentrations of experimental birds also changed as a response to both first and second PHA injections (##FIG##1##Fig. 2##). There was a significant decrease in albumin (F_2,28 = 71.75, P&lt;0.0001) at the same time that α-globulin 2 (F_2,28 = 201.88, P&lt;0.0001) and β-globulin 1 (F_2,28 = 76.22, P&lt;0.0001) increased as a consequence of their contribution to the inflammatory process (##FIG##1##Fig. 2##), while controlling for significant differences among species (all P&lt;0.05). In turn, production of α-globulin 1 and β-globulin 2 were increasingly inhibited during the experiment, as indicated by their decreasing concentrations (F_2,28 = 311.53, P&lt;0.0001 and F_2,28 = 156.54, P&lt;0.0001, respectively; not shown in Figure). There were always significant differences between the three temporal series of blood samples (Helmert transformation, all P&lt;0.004). However, there was minimal change in the protein profiles of control birds (P-range: 0.05–0.67 for α = 0.01 after Bonferroni correction; ##FIG##1##Fig. 2##). As expected, γ-globulins, which are involved in the humoral but not in the cellular immune response, did not change after PHA injections (F_2,28 = 2.45, P = 0.10, species effect: F_4,14 = 1.51, P = 0.25).</p>", "<p>Finally, the swelling of tissue at the point of injection was proportional to the proliferation of lymphocytes circulating in blood, the contribution of different types varying between successive exposures (##FIG##2##Fig. 3##). In the first PHA test, the tissue swelling of experimental birds was positively related to the increase in numbers (from basal levels to 24-h after injection) of the three subsets of circulating lymphocyte types, being significantly correlated for CD5⁺ lymphocytes, as well as those lymphocytes responsible for acquiring a memory response to a novel antigen, CD8⁺ lymphocytes. After a second PHA test the contribution of CD4⁺ and CD5⁺ subsets was moderated, once the organism recognised the antigen from a previous exposure, while maintaining a major role for memory lymphocytes (CD8⁺). Conversely, none of the plasma proteins were significantly correlated to local tissue swelling (r ranges: −0.05–0.37, P-range: 0.12–0.83 for α = 0.01 after Bonferroni correction; see ##FIG##3##Fig. 4##). In multiple regression models, only β-globulins 1 significantly explained variability in tissue swelling (P = 0.007) along with a major contribution from circulating CD8⁺ (P&lt;0.001) as a response to the second PHA injection (model adjusted R² = 0.76, F_2,18 = 30.19, P&lt;0.001).</p>", "<p>The above experiments demonstrate the T-cell mediated nature of the response being measured by the PHA test, through a stronger secondary tissue swelling explained by an increase of circulating lymphocytes which are responsible for acquiring memory from previous antigen exposures. Previous work confirmed an innate component but was unable to identify the contribution of T-lymphocytes to the PHA-induced skin swelling by histology ##UREF##0##[2]##, or did not find clear associations between <italic>in vivo</italic> tissue swelling and <italic>in vitro</italic> mitogenic responses to PHA ##REF##9057208##[36]##. Here we show that the magnitude of local tissue swelling, while indicating innate immunity to some extent ##UREF##0##[2]##, is also reliably reflecting the activation of the T-cell mediated immune system as shown by changes in the bloodstream of T-lymphocyte subsets. The second experiment also suggested that albumin, which can only be obtained through food, may be diverted towards production of acute phase proteins (α- and β-globulins) involved in the non-specific inflammatory process ##UREF##14##[27]##. This could explain why protein-supplemented diets enhance PHA-induced tissue swellings ##UREF##18##[31]##, and why the classic positive relationship between these responses and nutritional condition of birds often disappears in captivity conditions ##UREF##18##[see review also in 31]##, where standard food is provided <italic>ad libitum</italic>, and thus variability in the access to proteins among individuals is greatly reduced. Therefore, a larger relative contribution of non-specific inflammation is expected in wild populations than we have found in captive birds for explaining variability in local skin swellings. This prediction merits further research, and could be tested both in field conditions and in captivity by manipulating the access to dietary proteins.</p>", "<p>In conclusion, the PHA-test can be considered a good measure of T-cell mediated immunity in birds and possibly in vertebrates in general, given that they share the main components of the cell-mediated immune system ##UREF##22##[37]##. Our work solves major concerns about the meaning and interpretation of the test ##REF##17028055##[23]##, and allows its continued widespread use in diverse research disciplines. However, it is important to note that cellular immunity is just one component of the complex immune system in vertebrates ##UREF##22##[37]##, and thus the role of acquired T-cell mediated immunity in combating particular parasites and pathogens is, alone, not enough to explain many immunological patterns and processes ##REF##17296246##[38]##. Finally, we expect that the use of flow cytometry and protein electrophoresis will help researchers to elucidate the relative contribution of T-cell mediated and non-specific inflammatory components of the PHA-response when food accessibility varies in quality and quantity, as occurs in field conditions. These methods thus far have been overlooked as analytical tools in immunoecology studies and may add insight, for example, to properly ascertain the environmental and genetic components of the response to PHA ##UREF##9##[16]##, ##REF##17567550##[39]##, which is influenced by nutritional condition early in life ##REF##28308752##[40]##.</p>" ]

[ "<title>Results and Discussion</title>", "<p>The PHA-induced tissue swelling was on average 86% larger in the second than in the first immune challenge (time range between PHA challenges: 5–250 days), with only four out of 125 individuals showing small increases (&lt;10%). Changes in body mass, however, were unappreciable (0.43% on average) between the first and second immune tests (##FIG##0##Fig. 1##). The second PHA-induced tissue swelling was significantly larger than the first (F_1,123 = 482.67, P&lt;0.0001), while controlling for the species body mass (F_1,123 = 26.94, P&lt;0.0001) and the significant differences in PHA responses among the variety of species tested (Z = 7.22, P&lt;0.0001). The swelling increase of individuals (i.e., the absolute difference between the second and the first response) was unrelated to their changes in body mass (<italic>F</italic>\n_1,83 = 0.02, <italic>P</italic> = 0.89) or time elapsed between the two immune tests (F_1,83 = 2.6, P = 0.11), while controlling again for body mass (F_1,83 = 1.02, P = 0.31) and species (Z = 0.67, <italic>P</italic> = 0.25). To our knowledge, this is the first experimental work designed to test larger secondary than primary responses to PHA injection. Nonetheless, the literature shows anecdotal and inconsistent evidence obtained from unrelated experiments and small sample sizes: four captive birds used as experimental controls showed larger secondary responses ##UREF##18##[31]##, while four wild birds recaptured and tested for immunity about one year later ##UREF##19##[32]## and ten captive birds resampled after four months ##UREF##20##[33]## did not show appreciable differences between the first and the second immune challenge. A better sample consisting of 86 broods of nestling passerines showed larger secondary swellings when challenged two days after a first injection, results which were not interpreted as evidence of acquired immunity but rather as a matter of methodology to be considered in statistical analyses ##REF##10917529##[34]##. These larger secondary responses, however, could be confounded by ontogeny and thus reflect to some extent the development of immunocompetence during the growth period of chicks in the nest ##UREF##21##[35]##. Our results, however, clearly demonstrate that the PHA-test provokes a greater swelling on the second compared with the first PHA response, a critical requirement if the test is to be considered indicative of a true cell-mediated acquired immunity ##REF##17028055##[23]##. Moreover, greater secondary responses appear as soon as five days after the first PHA injection as well as long time after injection (at least 250 days), and thus could provide lifelong immunity upon subsequent exposure as expected from the acquired T-cell mediated immune system ##REF##17028055##[23]##.</p>", "<p>A concomitant prediction is that if the swelling is produced by the proliferation of T lymphocytes typically involved in the acquired immune response, then there is likely to be a much lower level of these lymphocytes at first exposure compared to subsequent exposures to PHA ##REF##17028055##[23]##. Our flow cytometry results fully support this. The increases in circulating T-lymphocyte subsets from basal levels to profiles resulting after the first and second PHA-tests (##FIG##1##Fig. 2##) were significant for both CD4⁺ active subset (F_2,28 = 290.57, P&lt;0.0001), CD5⁺ coadyuvant subset (F_2,28 = 82.74, P&lt;0.0001) and CD8⁺ memory subset (F_2,28 = 182.33, P&lt;0.0001), while controlling for significant differences among the species tested (all P&lt;0.006). There were always significant differences between the three instances of blood sampling (Helmert transformation, all P&lt;0.0001). As expected, control birds (injected only with PBS) did not show changes in lymphocyte profiles (P-range: 0.38–0.85, ##FIG##1##Fig. 2##). Therefore, PHA exposure is clearly responsible for the proliferation of lymphocytes associated with an acquired T-cell mediated immune response.</p>", "<p>Plasma protein concentrations of experimental birds also changed as a response to both first and second PHA injections (##FIG##1##Fig. 2##). There was a significant decrease in albumin (F_2,28 = 71.75, P&lt;0.0001) at the same time that α-globulin 2 (F_2,28 = 201.88, P&lt;0.0001) and β-globulin 1 (F_2,28 = 76.22, P&lt;0.0001) increased as a consequence of their contribution to the inflammatory process (##FIG##1##Fig. 2##), while controlling for significant differences among species (all P&lt;0.05). In turn, production of α-globulin 1 and β-globulin 2 were increasingly inhibited during the experiment, as indicated by their decreasing concentrations (F_2,28 = 311.53, P&lt;0.0001 and F_2,28 = 156.54, P&lt;0.0001, respectively; not shown in Figure). There were always significant differences between the three temporal series of blood samples (Helmert transformation, all P&lt;0.004). However, there was minimal change in the protein profiles of control birds (P-range: 0.05–0.67 for α = 0.01 after Bonferroni correction; ##FIG##1##Fig. 2##). As expected, γ-globulins, which are involved in the humoral but not in the cellular immune response, did not change after PHA injections (F_2,28 = 2.45, P = 0.10, species effect: F_4,14 = 1.51, P = 0.25).</p>", "<p>Finally, the swelling of tissue at the point of injection was proportional to the proliferation of lymphocytes circulating in blood, the contribution of different types varying between successive exposures (##FIG##2##Fig. 3##). In the first PHA test, the tissue swelling of experimental birds was positively related to the increase in numbers (from basal levels to 24-h after injection) of the three subsets of circulating lymphocyte types, being significantly correlated for CD5⁺ lymphocytes, as well as those lymphocytes responsible for acquiring a memory response to a novel antigen, CD8⁺ lymphocytes. After a second PHA test the contribution of CD4⁺ and CD5⁺ subsets was moderated, once the organism recognised the antigen from a previous exposure, while maintaining a major role for memory lymphocytes (CD8⁺). Conversely, none of the plasma proteins were significantly correlated to local tissue swelling (r ranges: −0.05–0.37, P-range: 0.12–0.83 for α = 0.01 after Bonferroni correction; see ##FIG##3##Fig. 4##). In multiple regression models, only β-globulins 1 significantly explained variability in tissue swelling (P = 0.007) along with a major contribution from circulating CD8⁺ (P&lt;0.001) as a response to the second PHA injection (model adjusted R² = 0.76, F_2,18 = 30.19, P&lt;0.001).</p>", "<p>The above experiments demonstrate the T-cell mediated nature of the response being measured by the PHA test, through a stronger secondary tissue swelling explained by an increase of circulating lymphocytes which are responsible for acquiring memory from previous antigen exposures. Previous work confirmed an innate component but was unable to identify the contribution of T-lymphocytes to the PHA-induced skin swelling by histology ##UREF##0##[2]##, or did not find clear associations between <italic>in vivo</italic> tissue swelling and <italic>in vitro</italic> mitogenic responses to PHA ##REF##9057208##[36]##. Here we show that the magnitude of local tissue swelling, while indicating innate immunity to some extent ##UREF##0##[2]##, is also reliably reflecting the activation of the T-cell mediated immune system as shown by changes in the bloodstream of T-lymphocyte subsets. The second experiment also suggested that albumin, which can only be obtained through food, may be diverted towards production of acute phase proteins (α- and β-globulins) involved in the non-specific inflammatory process ##UREF##14##[27]##. This could explain why protein-supplemented diets enhance PHA-induced tissue swellings ##UREF##18##[31]##, and why the classic positive relationship between these responses and nutritional condition of birds often disappears in captivity conditions ##UREF##18##[see review also in 31]##, where standard food is provided <italic>ad libitum</italic>, and thus variability in the access to proteins among individuals is greatly reduced. Therefore, a larger relative contribution of non-specific inflammation is expected in wild populations than we have found in captive birds for explaining variability in local skin swellings. This prediction merits further research, and could be tested both in field conditions and in captivity by manipulating the access to dietary proteins.</p>", "<p>In conclusion, the PHA-test can be considered a good measure of T-cell mediated immunity in birds and possibly in vertebrates in general, given that they share the main components of the cell-mediated immune system ##UREF##22##[37]##. Our work solves major concerns about the meaning and interpretation of the test ##REF##17028055##[23]##, and allows its continued widespread use in diverse research disciplines. However, it is important to note that cellular immunity is just one component of the complex immune system in vertebrates ##UREF##22##[37]##, and thus the role of acquired T-cell mediated immunity in combating particular parasites and pathogens is, alone, not enough to explain many immunological patterns and processes ##REF##17296246##[38]##. Finally, we expect that the use of flow cytometry and protein electrophoresis will help researchers to elucidate the relative contribution of T-cell mediated and non-specific inflammatory components of the PHA-response when food accessibility varies in quality and quantity, as occurs in field conditions. These methods thus far have been overlooked as analytical tools in immunoecology studies and may add insight, for example, to properly ascertain the environmental and genetic components of the response to PHA ##UREF##9##[16]##, ##REF##17567550##[39]##, which is influenced by nutritional condition early in life ##REF##28308752##[40]##.</p>" ]

[]

[ "<p>Conceived and designed the experiments: JLT JAL GB. Performed the experiments: JLT MC. Analyzed the data: MC. Contributed reagents/materials/analysis tools: JAL GB. Wrote the paper: JLT GB. Performed laboratory analyses: JAL.</p>", "<title>Background</title>", "<p>cological immunology requires techniques to reliably measure immunocompetence in wild vertebrates. The PHA-skin test, involving subcutaneous injection of a mitogen (phytohemagglutinin, PHA) and measurement of subsequent swelling as a surrogate of T-cell mediated immunocompetence, has been the test of choice due to its practicality and ease of use in the field. However, mechanisms involved in local immunological and inflammatory processes provoked by PHA are poorly known, and its use and interpretation as an acquired immune response is currently debated.</p>", "<title>Methodology</title>", "<p>Here, we present experimental work using a variety of parrot species, to ascertain whether PHA exposure produces larger secondary than primary responses as expected if the test reflects acquired immunocompetence. Moreover, we simultaneously quantified T-lymphocyte subsets (CD4⁺, CD5⁺ and CD8⁺) and plasma proteins circulating in the bloodstream, potentially involved in the immunological and inflammatory processes, through flow cytometry and electrophoresis.</p>", "<title>Principal Findings</title>", "<p>Our results showed stronger responses after a second PHA injection, independent of species, time elapsed and changes in body mass of birds between first and second injections, thus supporting the adaptive nature of this immune response. Furthermore, the concomitant changes in the plasma concentrations of T-lymphocyte subsets and globulins indicate a causal link between the activation of the T-cell mediated immune system and local tissue swelling.</p>", "<title>Conclusions/Significance</title>", "<p>These findings justify the widespread use of the PHA-skin test as a reliable evaluator of acquired T-cell mediated immunocompetence in diverse biological disciplines. Further experimental research should be aimed at evaluating the relative role of innate immunocompetence in wild conditions, where the access to dietary proteins varies more than in captivity, and to ascertain how PHA responses relate to particular host-parasite interactions.</p>" ]

[]

[ "<p>We thank J.E. Smits, J.A. Donázar, M. Blanco, and an anonymous referee for comments on the manuscript.</p>" ]

[ "<fig id=\"pone-0003295-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003295.g001</object-id><label>Figure 1</label><caption><title>Local tissue swelling (black dots) and body mass (white dots) of 125 birds subjected to two successive PHA-skin tests.</title></caption></fig>", "<fig id=\"pone-0003295-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003295.g002</object-id><label>Figure 2</label><caption><title>Changes in counts of lymphocyte subsets and protein concentrations (μg/L) in the bloodstream from basal levels to those resulting 24 h after a first and a second PHA injection.</title><p>Black dots represent experimental birds (injected with PHA) and white dots represent control birds (injected with PBS).</p></caption></fig>", "<fig id=\"pone-0003295-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003295.g003</object-id><label>Figure 3</label><caption><title>Relationships between local tissue swelling induced by first and second PHA injections and the concomitant changes in circulating lymphocyte subsets.</title><p>Regression coefficients and statistical significance are shown for each case.</p></caption></fig>", "<fig id=\"pone-0003295-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003295.g004</object-id><label>Figure 4</label><caption><title>Relationships between local tissue swelling induced by first and second PHA injections and the concomitant changes in circulating protein concentrations (μg/L).</title><p>Regression coefficient and statistical significance are shown for each case.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003295-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003295.t001</object-id><label>Table 1</label><caption><title>Species and number of individuals used for assessing two consecutive responses to PHA injection.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Species</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Body mass (g)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">First PHA response (mm)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Second PHA response (mm)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Agapornis canus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.86</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Agapornis fischeri</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">43.83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Agapornis personatus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">44.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Agapornis taranta</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">49.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Ara (Primolius) maracana</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">244</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aratinga aurea</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">80.19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.76</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aratinga jendaya</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">123.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.49</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aratinga leucophthalmus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">183</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aratinga pertinax</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">86.02</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.64</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Barnadius zonarius</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">133.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Bolborhynchus (Psilopsiagon) aymara</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28.65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.92</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Cyanoramphus auriceps</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">57.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.06</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Cyanoramphus novaezelandiae</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">64.45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Forpus coelestis</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.71</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Forpus passerinus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">24.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Melopsittacus undulatus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">45.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.79</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Myiopsitta monachus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">107.71</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.52</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Nandayus nenday</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">137.06</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Neophema elegans</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">46.13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.02</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Neophema pulchella</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40.85</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.68</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Neopsephotus bourkii</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">42.65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.49</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pionites leucogaster</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">137.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pionites melanocephala</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">148.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.63</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus adscitus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">98.38</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.68</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus caledonicus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">114</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus elegans</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">128.67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus eximius</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.77</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Poicephalus senegalus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">126.17</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Polytelis anthopeplus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">165.14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.92</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Polytelis swainsonii</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">132.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.47</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Psephotus haematonotus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">64.94</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.87</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Psittacula krameri</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">130.67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura cruentata</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">101.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura lepida</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71.18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.93</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura melanura</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75.7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.86</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura molinae</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">66.54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura perlata</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">78.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.78</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.31</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura picta</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.02</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pyrrhura rodocephala</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">103.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.64</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003295-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003295.t002</object-id><label>Table 2</label><caption><title>Species and number of individuals used to quantify changes in lymphocyte subsets and plasma proteins associated with the primary and secondary responses to PHA injection.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Species</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">First response (mm)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Second response (mm)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Experimental individuals (injected with PHA)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus adscitus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.68</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus caledonicus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus eximius</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.77</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Polytelis anthopeplus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.06</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Psittacula krameri</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.30</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Control individuals (injected with PBS)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus adscitus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Platycercus eximius</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Polytelis anthopeplus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr></tbody></table></alternatives></table-wrap>" ]

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[ "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>The authors have no support or funding to report.</p></fn></fn-group>" ]

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{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Although the use of DNA microarrays and other high throughput (HTP) technologies is increasingly widespread and affordable, identifying the underlying biological themes from HTP data remains a major challenge in the arena of systems biology. Once data from these experiments has been normalized, a tremendous variety of software tools and methods are available for analysis of HTP data, primarily focusing on microarray data. These methods primarily rely on several categories of common gene-level approaches. One category of approaches is gathering patterned genes across samples or datasets by clustering (e.g., hierarchical ##REF##9843981##[1]##, K-means ##UREF##0##[2]##, or SOM ##REF##10077610##[3]## methods, pattern extraction method ##REF##16423281##[4]##); Another category of common approaches is generating differentiated gene lists from two or more class contrasts using a variety of methods (Significance Analysis of Microarray ##REF##11309499##[5]##, moderated t-test ##UREF##1##[6]##–##REF##12710670##[7]##, LPE ##REF##14555628##[8]##, FDR ##REF##12883005##[9]##, as well as other gene selection methods including “unusual ratio method” ##REF##10515934##[10]##, analysis of variance (ANOVA) related methods ##UREF##2##[11]##–##REF##14597312##[16]##, Mixed Model Analysis ##REF##14573485##[17]##. A more recent approach, namely meta-analysis, looks for common signatures across multiple independent datasets by combining multiple statistical methods including simple t-test, FDR, and cross-validation into a single result ##REF##15920528##[18]##.</p>", "<p>In order to identify the biological themes embedded in such differentiated gene lists, the next step typically maps these genes to their pathways or networks. Further integration of this data with literature resources connects the identified genes with their potential biological roles ##REF##16423281##[4]##, ##REF##14597658##[19]##, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ingenuity.com\">www.ingenuity.com</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.genego.com\">www.genego.com</ext-link>. Alternatively, enrichment-based analysis ##REF##16423281##[4]##, ##REF##14519205##[20]##–##REF##14990455##[22]## can be applied to such a gene list to generate ranked functional categories (e.g., GO) or pathways based on their enrichment levels, so that the significantly enriched pathways and their associated genes can be easily identified as the primary biological themes. Additional efforts have been made using various algorithms and statistical methods for gene set-based group testing analysis ##REF##12808457##[23]##–##REF##15941488##[27]##. Some very recent efforts explore the topology and architectures of the networks in conjunction with high-throughput data to seek biological scenarios ##REF##17437023##[28]##–##REF##17408515##[29]##.</p>", "<p>The existence of high levels of natural variation within populations coupled with the observation that very slight changes in multiple relevant genes in a gene set can trigger biological changes has led to the development of several gene-set based or group testing methods: 1. over-representation analysis (ORA) ##REF##16423281##[4]##, ##REF##14519205##[20]##–##REF##14990455##[22]##, ##REF##12620386##[30]##; 2. functional class scoring (FCS) ##REF##12808457##[23]##–##REF##16199517##[24]##, ##REF##15941488##[27]##, ##REF##15176478##[31]##–##REF##12914697##[33]##&amp;semi; 3. global tests ##REF##14693814##[34]##; 4. module-level analysis scheme ##REF##15448693##[35]##–##REF##16273092##[37]##; 5. singular value decomposition or SVD-based method ##REF##16156896##[38]##; 6. a network structure-based method ##REF##17487280##[39]##.</p>", "<p>Most, if not all of these methods directly use cross-sample evaluation for differentiated genes or ranking genes for further gene-set based methods, based on the assumption that, for a given phenotype (e.g. tumor vs. normal tissues, treated vs. control), any relevant genes should behave consistently across the samples or individuals within the studied population within their own class (e.g., Tumor or normal tissues). With existing group-test analysis methods such as GSEA ##REF##12808457##[23]##–##REF##16199517##[24]##, the assertion is made that in order to be significant, the data distribution per gene is significantly shifted between the contrasted classes. However, we challenge this notion with a new more general assertion that while biologically relevant genes may consistently behave in correlation with an associated phenotype across a population, it is even more likely that common pathways can be impacted through distinct gene events that are not reflected at the individual gene level across samples. Such pathway-level consistency seems particularly relevant considering the stochastic nature of many epigenetic events that lead to disease states. For example, a conventional t-test based approach is usually used to evaluate the statistical difference of genes among the individuals between two contrasted classes for a typical microarray dataset. For a specific gene, even with a statistically significant p-value, the expression of this gene in one or more samples of one class could have the same or even lower value than some samples from the other class, although the mean of expression for this gene in the first class is higher than that of the second one with statistical significance suggested by p-value. Thus, with the presence of such sample-level variants, this gene will still be considered as a differentiated gene and become included in the final differentiated gene list because it may have passed statistical criteria including p-value or FDR. This is a result of the fact that all variances of individual gene levels are aggregated into a single decision: differentiated gene or a single measurement: fold change or p-value. However, as we will discuss below, such sample-level variants or specificity in a class population, although some would be more common and some would be unique, can be both realistic and biologically relevant, since even for this same phenotype, other relevant genes could have changed or other types of changes for this gene, such as phosphorylation status or protein stability, which could not be captured by microarray, could happen in this individual. This may otherwise mask the real effect leading to the same or a similar phenotype. In short, multiple genes within a biological pathway could be impacted with the same net-effect on the pathway. Therefore what may be happening at a higher biological level (i.e., group of relevant genes, gene sets, pathways, functionally related genes) may have been excluded from the analysis if such sample-level specificity is not taken into account.</p>", "<p>In order to capture the sample-level specificity of gene-level variance, we introduce a new concept - sample-level differentiated genes (SLDGs). These are defined as genes that are differentially expressed for a sample in one class when compared to the data distribution of the other class population. We believe that this new concept should accommodate both the gene-level changes identified by established methods but also sample-level specific changes related to the phenotype but only evident in individual samples. Although variations and even outliers that can be introduced by technical issues or experimental variations that have nothing to do with biological relevance, the chance that multiple related genes in a pathway or biological process have such issues simultaneously should be rare. Thus, SLDGs for each sample can be used as individual gene lists to evaluate the data consistency at the pathway-level using an ORA-like enrichment method. Instead of using summarized differentiated gene lists, SLDG lists are used to calculate enrichment levels of each term for each sample and a class-contrast based pathway-ranking method is then used to rank the most consistent and enriched pathways (or gene sets, GO terms). We named this method Sample-Level Enrichment-based Pathway-Ranking method (SLEPR).</p>", "<p>In this report, we provide evidence that analyzing data at the level of functional categories, including well-defined or customized pathways and GO terms, for pathway-level consistency, may help understand the underlying biological themes at a higher level or in more detail than other methods provide. Furthermore, in addition to identifying potential biologically relevant processes or pathways, we also look for pathway-level differentiated genes from sample-level differentiated gene lists, which can be combined among sample populations to reveal a whole spectrum of genetic and biochemical changes associated with the phenotype in question. In contrast to conventional methods, we have extended the “differentiated” concept from the gene-level to the pathway-level, so that one can focus on a biological process or pathway that has consistent changes at the pathway-level rather than just individual gene-level across the samples or datasets in a study.</p>", "<p>As a proof of concept, we have used this method to analyze several public microarray datasets with validated results and/or expected biological themes. We have found that the SLEPR method effectively reproduced the previously analyzed and experimentally validated results or generated analysis results that are consistent with biologically relevant expectations. In direct comparison with the GSEA method, we also found that the SLEPR method uncovered many other potentially biologically relevant pathways not identified by GSEA including many sample-specific genes that potentially cover the entire repertoire of candidate genes for pathways or gene sets that are associated with the expected phenotype. We hope that these results give a more complete picture of phenotype-wise genetic and biochemical changes and that this method will help derive biological themes from additional datasets measuring changes at different levels of regulation including transcription, protein expression, and phosphorylation when these data become increasingly available in the future.</p>" ]

[ "<title>Materials and Methods</title>", "<p>Three public microarray datasets ##REF##12808457##[23]##, ##REF##15075390##[41]##, ##REF##11507037##[42]## were obtained from the original publications and used for purpose of demonstration for SLEPR method. All the described procedures for the SLEPR method are implemented into and as a part of newly developed pathway pattern extraction pipeline in the original WPS program developed previously ##REF##16423281##[4]##, which can be downloaded from the WPS website (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.abcc.ncifcrf.gov/wps/wps_index.php\">http://www.abcc.ncifcrf.gov/wps/wps_index.php</ext-link>). The details and program interface of the pathway pattern extraction pipeline in WPS program are described elsewhere in a separate manuscript (Yi and Stephens unpublished work). The following sections are details of those procedures, which were also schematically illustrated in ##FIG##0##Figure 1##.</p>", "<title>Inclusion/Target Class versus Exclusion/Background Class</title>", "<p>For a given dataset intended for contrast studies (e.g., NGT vs. IGT+DM2; tumor vs. normal tissues; muscle tissues vs. other tissues), we separated all of the samples from the dataset into two classes representative of interested contrast: Exclusion/Background class <italic>E</italic> (e.g., normal tissues) as the class for background of data measurement and the interested class: Inclusion/Target class <italic>I</italic> (e.g., tumor tissues) as the target sample group to make comparison with Exclusion/Background class. <italic>E</italic> and <italic>I</italic> is exchangeable and also do not have to cover all the samples in datasets, dependent upon the questions to address. The same sample can not be selected into <italic>E</italic> and <italic>I</italic> classes at the same time. Therefore, if <italic>T_I</italic> as total number of samples from Inclusion class <italic>I</italic> and <italic>T_E</italic> as number of samples from Exclusion class <italic>E</italic>, and there are total T samples in dataset. Thus, we have <italic>T_I</italic>+<italic>T_E</italic>&lt; = T.</p>", "<title>Select Sample-Level Differentiated Genes for Each Sample in Dataset</title>", "<p>For each single gene <italic>k</italic> in a dataset, its data in sample <italic>j</italic> is denoted as D_k,j (<italic>k</italic>: gene <italic>k</italic>; <italic>j</italic>: sample <italic>j</italic> in the dataset, either in Class I or Class E). To decide whether gene <italic>k</italic> is a sample-level differentiated gene for sample <italic>j</italic>, we first used data of gene <italic>k</italic> in samples within Exclusion/Background class <italic>E</italic> as background distribution of data to create a cutoff threshold C<italic>_k</italic> for gene <italic>k</italic>, where we have <italic>C_k</italic> = <italic>MADe</italic>({D<italic>_k</italic>\n_{,<italic>j</italic>}}), where j = 1,2,… <italic>T_E</italic>; <italic>T_E</italic> is number of samples in Class <italic>E</italic> in the dataset.</p>", "<p>Function <italic>MADe</italic>() is defined as following: for n values <italic>x_i</italic> (i = 1,2,..n) in a data set <italic>X</italic>:where the inner median <italic>median</italic>(<italic>X</italic>) is the median of the set <italic>X</italic> and the outer median is the median of the n absolute values of the deviations about the inner median. MAD is conventional Median Absolute Deviation and 1.483 is the scaling factor, which make <italic>MADe</italic> comparable with a SD (Standard Deviation), although <italic>MADe</italic> is more robust than SD and unaffected by the presence of extreme values or outliers ##UREF##6##[57]##–##UREF##7##[58]##. We also define median expression level <italic>M_k</italic> for gene <italic>k</italic> for samples in Exclusion class E as:where j = 1,2,… <italic>T_E</italic>; <italic>T_E</italic> is number of samples in class E in the dataset.</p>", "<p>There are two MADe-based methods for selecting sample-level differentiated genes: one-sided MADe method and two-sided MADe method. The one-sided MADe method intends to only select sample-level differentiated genes from one direction of changes (e.g., only up-regulated genes or only down-regulated genes) in each sample. In contract, the two-sided MADe method intends to select sample-level differentiated genes from both directions of changes (e.g., pooled highly expressed genes and lowly expressed genes together) in each sample.</p>", "<p>For one-sided MADe method, there are two options for selecting genes: higher side (right-side) or lower side (left side) sorting options, which will select only highly expressed (e.g., up-regulated) genes, or only lowly expressed (e.g. down-regulated) genes as sample-level differentiated genes compared to the data distribution of Exclusion/Background class, respectively. For higher side sorting option, considering gene <italic>k</italic>, if and only if <italic>D_k</italic>\n_{,<italic>m</italic>}&gt; = <italic>M_k</italic>+<italic>C_k</italic>, gene <italic>k</italic> will be selected as a sample-level differentiated genes (e.g., highly expressed) for sample m. For lower side sorting option, considering gene <italic>k</italic>, if and only if <italic>D_k</italic>\n_{,<italic>m</italic>}&lt; = <italic>M_k</italic>−<italic>C_k</italic>, gene <italic>k</italic> will be selected as a sample-level differentiated gene (e.g., lowly expressed) for sample m; where sample m is one of the selected samples in the dataset (either a sample from Class <italic>I</italic> with <italic>T_I</italic> samples or Class <italic>E</italic> with <italic>T_E</italic> samples).</p>", "<p>For two-sided MADe method, considering gene <italic>k</italic>, either if <italic>D_k</italic>\n_{,<italic>m</italic>}&gt; = <italic>M_k</italic>+<italic>C_k</italic> or if <italic>D_k</italic>\n_{,<italic>m</italic>}&lt; = <italic>M_k</italic>−<italic>C_k</italic>, gene <italic>k</italic> will be selected as sample-level differentiated gene (e.g., highly expressed or lowly expressed ) for sample m, where sample m is one of the selected samples in the dataset (either a sample from Class <italic>I</italic> with <italic>T_I</italic> samples or Class <italic>E</italic> with <italic>T_E</italic> samples). This method will pool together the genes that have changed at either direction (e.g., highly or lowly expressed) into sample-level differentiated lists.</p>", "<p>Each time sample-level differentiated genes are selected, an intermediate result file can be created, in which a similar binary data matrix with value of either 1 or 0 was generated like the original data matrix, except that for each data point in the original matrix, say, a data point for gene g and sample s, the data was transformed to either 1 if gene g was selected as sample-level differentiated genes for sample g, or 0 if not. The interface for creating such an intermediate result file is implemented into WPS ##REF##16423281##[4]## and described in a separate manuscript (Yi and Stephens unpublished work). Such an intermediate result file is useful if one wants to further pursue the importance of each of the pathway-level differentiated genes involving in the studied phenotype with class-ranking method described as below.</p>", "<title>Compute for Enrichment Scores for Each Sample-Level Differentiated Genes into an Enrichment Score Matrix</title>", "<p>Once the sample-level differentiated gene lists are sorted into individual files in a file folder or directory using WPS program interfaces and utilities of pathway pattern extraction pipeline described in a separate manuscript (Yi and Stephens unpublished work), enrichment scores can be computed in a batch mode for each of these gene lists and merged into a stanford format file. Briefly, Fisher's exact test is performed based on 2×2 contingency tables (whether a gene is in the given list or not vs. whether this gene is associated with a pathway/term or not, described previously ##REF##16423281##[4]## for each term for each list). All Fisher's exact test results are ranked based on the p-values for each list and stored as individual files for further merging. During the merging process, all the p-values are transformed by a formula (−Log₁₀(p-value)) into enrichment scores, where appropriate filtering is applied, typically, ListHits&lt;2 or p-value&gt;0.05 will be used to floor the enrichment scores to 0; otherwise, −Log₁₀(p-value) will be the enrichment scores. The data matrix of enrichment scores without any flooring or filtering (i.e., original enrichment scores (−Log₁₀(p-value))) may be also obtained from a program interface described in a separate manuscript (Yi and Stephens unpublished work).</p>", "<title>Pathway-Ranking for Enrichment Score Matrix</title>", "<p>For each term in the enrichment score matrix, let the enrichment score of sample <italic>i</italic> in pathway or term t as ES<italic>_i,t</italic>, <italic>T_I</italic> as total number of samples from Inclusion class <italic>I</italic> and <italic>T_E</italic> as number of samples from Exclusion class <italic>E</italic>.</p>", "<p>In order to get the Pathway-ranking score for a given pathway or term t, we need compute for two intermediate ranking scores for each term t: class difference ranking scores and p-value sum ranking scores. Class difference ranking scores reflect the difference in the percentages of samples in class <italic>I</italic> and class <italic>E</italic> with significant enrichment scores. p-value sum ranking scores reflect the difference in the magnitude of the enrichment scores in samples of class <italic>I</italic> and samples of class <italic>E</italic>.</p>", "<p>\n<italic>Cfc</italic> is defined as the Cutoff for class difference ranking score, as default, <italic>Cfc</italic> = −log₁₀(0.05) = 1.3 (one can change the default in program interface to other desired value). First, we compute for class difference ranking score CDR for pathway or term <italic>t</italic>, which is defined as <italic>CDR_t</italic>, we have:Where <italic>N</italic>(<italic>ES_i</italic>\n_{,<italic>t</italic>}&gt;<italic>Cfc</italic>, <italic>i</italic>∈<italic>I</italic>) refers to the number of samples in class I with enrichment score larger than the <italic>Cfc</italic>; <italic>and N</italic>(<italic>ES_j</italic>\n_{,<italic>t</italic>}&gt;<italic>Cfc</italic>, <italic>j</italic>∈<italic>E</italic>) refers to the number of samples in class E with enrichment score larger than the <italic>Cfc</italic>.</p>", "<p>Then, we compute for p-value sum ranking scores for pathway or term <italic>t</italic>, which is defined as <italic>PSR_t</italic>, we have:Where refers to the sum of enrichment scores for term <italic>t</italic> of all samples in class <italic>I</italic> and refers to the sum of enrichment scores for term <italic>t</italic> of all samples in class <italic>E</italic>. Thus, to compute the pathway-ranking score for a given pathway or term <italic>t</italic>, which referred as <italic>PR_t</italic>, we have:</p>", "<p>If both <italic>CDR_t</italic> and <italic>PSR_t</italic> are less than 0, <italic>PR_t</italic> is computed as <italic>PR_t</italic> = (−1)*<italic>CDR_t</italic>*<italic>PSR_t</italic>; otherwise, <italic>PR_t</italic> is computed as: <italic>PR_t</italic> = <italic>CDR_t</italic>*<italic>PSR_t</italic>.</p>", "<title>Estimation of Significance of Ranked Pathways/Terms</title>", "<p>The statistical significance of a given pathway ranking score <italic>PR_t</italic> for a given pathway or term <italic>t</italic> is assessed with permutated p-value using permutation testing of class assignments of each sample from both Inclusion and Exclusion classes (e.g., whether a sample has a phenotype of DM2 versus NGT in the human type 2 diabetes mellitus (DM2) dataset ##REF##12808457##[23]##). Briefly, we permutate the sample labels among total selected samples including both class I and class E. For each permutation, we re-calculate pathway-ranking score for each term <italic>t</italic> as permutated <italic>PR_t</italic>. This procedure was repeated 1000 (default setting) or more times. The permutated p-value for each term <italic>t</italic> is calculated as the fraction of random trials resulting in permutated pathway-ranking scores no less than <italic>PR_t</italic>. The FDR q value is also calculated based on this null distribution derived from permutation as followed: to compute an FDR q value, for a given pathway-ranking score <italic>PR_t</italic>, the FDR is the ratio of the percentage of all pathway-ranking scores derived from the permutated data, which are no less than <italic>PR_t</italic>, divided by the percentage of observed pathway-ranking scores derived from the original data, which are no less than <italic>PR_t</italic>. Because such permutation tests randomize the class assignments of samples from both sides of contrasted classes, it is a test of the dependence of the actual class assignment for each individual sample, which is characteristic of the phenotype under study.</p>", "<title>Retrieval and Ranking of the Associated Genes for Significant Ranked Terms as Pathway-Level Differentiated Genes</title>", "<p>The ranked pathways with significant permutated p-values, FDR, and/or rankings may be used for retrieval of their associated genes from the sample-level differentiated genes in samples of Inclusion class. The retrieval can be easily done using newly developed WPS pipeline interface for pathway-level pattern extraction, described in a separate manuscript (Yi and Stephens unpublished work). The retrieved genes can be ranked in a way similar to the class ranking method used for pathway ranking, using the subset of data for these genes derived from the intermediate result file created when selecting the sample-level differentiated genes as described above.</p>", "<p>Within the retrieved associated genes, we compute for class difference ranking score CDRG for gene <italic>g</italic>, which is defined as <italic>CDRG_g</italic>, and each transformed value TV (i.e. 1 or 0) in the data matrix of an intermediate result file referred as <italic>TV_s</italic>\n_{,<italic>g</italic>} for sample s and gene g, then we have:Where <italic>N</italic>(<italic>TV_i</italic>\n_{,<italic>g</italic>} = 1, <italic>i</italic>∈<italic>I</italic>) refers to the number of samples in class I with transformed value in the intermediate file equal to 1; <italic>and N</italic>(<italic>TV_j</italic>\n_{,<italic>g</italic>} = 1, <italic>j</italic>∈<italic>E</italic>) refers to the number of samples in class E with transformed value in the intermediate file equal to 1.</p>", "<p>We define these genes with CDRG larger than 0 as pathway-level differentiated genes, which may potentially represent the whole repertoire of alternations occurring at gene level within the engaged pathway in association with the class contrast or compared phenotypes. Such ranking of pathway-level differentiated genes can be used for evaluating the significance or the probability of the involvement of these genes related to the interested phenotype in the dataset under study.</p>" ]

[ "<title>Results</title>", "<title>Overview: Sample-Level Enrichment-Based Pathway Ranking Method (SLEPR)</title>", "<p>To overcome the issues and limitations of the gene-level consistency paradigm where data analysis primarily considers the change in gene behavior (e.g., expression) that consistently occurs in the majority of the sample population, we devised a simple approach, namely <underline>S</underline>ample-<underline>L</underline>evel <underline>E</underline>nrichment-Based <underline>P</underline>athway <underline>R</underline>anking Method (SLEPR), which is schematically illustrated in ##FIG##0##Figure 1## and described in more detail in the methods section. One of the major goals of the SLEPR method is to consider sample-level specificity for gene-level variances, and place the identified genes in the context of <italic>a priori</italic> defined gene sets, annotated biological processes or pathways, functional categories (e.g., GO terms) and look for pathway-level consistency of enrichment effects from changes occurring at multiple related genes systematically. The goal is to accomplish this objective without sacrificing sensitivity in detecting those genes that do behave consistently within their class.</p>", "<p>Using a recent diabetes study and their class contrast (e.g., highly expressed in individuals with NGT versus those with DM2: ##REF##12808457##[23]##), we first derived sample-level differentiated genes for each sample based on the data distribution of samples from the Exclusion/Background class using MADe-based statistics (##FIG##0##Figure 1##). The null hypothesis for SLEPR is that sample-level differentiated gene lists are random sets of genes with regard to their belonging to a particular sample group in a given class contrast. The alternative hypothesis is that sample-level differentiated genes are associated with the specific class assignment and therefore the biological phenotype under study. We also chose to allow the concept of the gene group to remain arbitrary and thus can include conventional gene sets, pathways, functional categories such as GO terms or simply genes with a particular transcription factor binding site and we will simply refer to these groups as gene sets henceforth. As a consequence, pathway-level consistent enrichment of genes annotated in a gene set within each of these sample-level differentiated gene lists would be biologically relevant to the phenotype being contrasted in the classes under study.</p>", "<p>We then determine the functional enrichment levels in any <italic>a priori</italic> defined gene sets for each derived sample-level differentiated gene list. The derived enrichment scores are used to evaluate the pathway-level consistency of enrichment for gene sets using a pathway-ranking algorithm in the SLEPR method. The method considers both the positive contribution of class I (included) and the negative contribution of class E (excluded) to individual sample-level enrichment. This is done in order to reduce possible bias by using only samples from the Exclusion class as the reference background for cutoff determination for sample-level differentiated genes.</p>", "<title>Case Study 1: Human Diabetes Datasets</title>", "<p>The human type 2 diabetes mellitus (DM2) dataset described previously ##REF##12808457##[23]## consists of 22,000 genes in skeletal muscle biopsy samples from 43 age-matched males: 17 with normal glucose tolerance (NGT), 9 with impaired glucose tolerance (IGT) and 17 with DM2. A goal of the original study ##REF##12808457##[23]## was to identify gene expression changes characteristic of DM2 and pre-defined gene sets for association with the disease phenotype. A novel method, called Gene Set Enrichment Analysis (GSEA), was developed to successfully identify as significant a set of genes involved in oxidative phosphorylation, although none of the individual genes had a significant difference in expression between the diagnostic categories ##REF##12808457##[23]##. Although GSEA successfully identified oxidative phosphorylation as one of major biological themes associated with the disease phenotype, subsequent studies revealed that the GSEA method was biased toward assigning higher enrichment scores to gene sets of large size ##REF##15226741##[40]##.</p>", "<p>In order to compare methods, we applied the SLEPR method to the same microarray dataset from the human type 2 diabetes mellitus study ##REF##12808457##[23]##. To ensure a fair comparison, we also implemented into the SLEPR method the same GSEA annotation database (also call MSigDB) ##REF##16199517##[24]## and compared the analysis results for the same database of gene sets.</p>", "<p>For each single gene in our SLEPR method, we used the Exclusion/Background class as the background or reference distribution of data. In contrast to GSEA-based methods, instead of looking at the change in expression of genes between the two contrasted classes, our SLEPR method starts with sample-level differentiated genes by comparing data of each sample to the data distribution of samples of the Exclusion class. Thus, the expression of each gene from each individual sample (samples from both Inclusion and Exclusion classes) is compared to this background distribution of the same genes' expression and is defined as a sample-level differentiated gene for a sample if the expression of this gene in the corresponding sample has an expression level at a distance larger than MADe compared to the median of background data range for this gene from either one or both directions (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section).</p>", "<p>We used the NGT samples as the Inclusion class and IGT and DM2 samples together or DM2 samples only as our Exclusion class (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section for class definition) and used GSEA annotations of gene sets or MSigDB (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.broad.mit.edu/gsea/\">http://www.broad.mit.edu/gsea/</ext-link>) for SLEPR (##TAB##0##Table 1##, ##TAB##1##2##) and GSEA analysis (##TAB##2##Table 3##, ##TAB##3##4##). Our SLEPR method successfully identified 5 closely related terms: “mitochondrial genes” (two of them, annotated from different sources), “electron transport”, and “oxidative phosphorylation”, “PGC related genes” at the top of the ranked term list using either IGT+DM2 or only DM2 samples as Exclusion class (##TAB##0##Table 1##, ##TAB##1##2##), which is consistent with the previous analysis result of GSEA ##REF##12808457##[23]##. Particularly when both IGT and DM2 samples are used, these relevant terms appear to be even more significant and ranked as the top 5 terms (##TAB##0##Table 1##). However, the GSEA method only ranked 3 of these terms among the top list when using only DM2 samples as the Exclusion class (##TAB##3##Table 4##), and only one of these terms among the top list when using both IGT and DM2 samples as Exclusion class (##TAB##2##Table 3##). Thus, the SLEPR method appears to uncover more terms with expected biological relevance with higher significance scores than GSEA in both settings of class comparison, especially when both IGT and DM2 samples were pooled together as one class (##TAB##0##Table 1##, ##TAB##2##3##). The additional terms uncovered by SLEPR: “mitochondrial genes” and “PGC related genes”, which were absent from the GSEA results and have strong biological relevance with the previously identified and validated term “oxidative phosphorylation”: the mitochondria are well known as the cellular compartment where the oxidative phosphorylation reactions occur and PGC (or PGC-1)-responsive genes involved in oxidative-phosphorylation are coordinately downregulated in human diabetes ##REF##12808457##[23]##. The fact that these additional terms are closely related to electron transport and oxidative phosphorylation, suggests that SLEPR could potentially uncover more related biological themes, presumably due to our consideration of sample-level specificity for gene-level variances and pathway-level consistency across the population.</p>", "<p>Interestingly, for many of the relevant terms identified by both SLEPR and GSEA, SLPER revealed a higher significance compared to GSEA in general. For example, although both SLEPR and GSEA detected “oxidative phosphorylation” as a top ranked term, the permutated p-values of “oxidative phosphorylation” derived from SLEPR (p = 0.00048 or p = 0.00034, ##TAB##0##Table 1## and ##TAB##1##2##) appear to be more significant than the GSEA method (p = 0.029 from original GSEA analysis ##REF##12808457##[23]##, p = 0.02 with current version (v2.0.1) of GSEA) (##TAB##3##Table 4##) comparing NGT with only DM2 samples, and p = 0.3511 comparing NGT with both DM2 and IGT samples, which is not significant and ranked only at 165 (##TAB##2##Table 3## and see the complete list of the result in ##SUPPL##4##Table S1##). This observation is extended further by examining the FDR q-values of “oxidative phosphorylation”: FDR = 0.15 or FDR = 0.082 from SLEPR results (##TAB##0##Table 1## and ##TAB##1##2##) compared to those from GSEA results: FDR = 0.446 and FDR = 1 (##TAB##3##Table 4##, ##SUPPL##4##S1##).</p>", "<p>In addition, the top ranked terms in the GSEA results appeared to have much higher FDR q-values (##TAB##2##Table 3##, ##TAB##3##4##) than those identified with SLEPR. Furthermore, in the SLEPR results, we observe a sharp rise in FDR q-values from 0.3652 to 0.9483 between terms No. 5 and 6 (##TAB##0##Table 1##) and from 0.088 to 0.3335 between terms No. 7 and 8 (##TAB##1##Table 2##), suggesting that these thresholds might be used to separate the identified terms into high and low priority groups.</p>", "<p>Since SLEPR is designed to uncover additional information from sample-level enriched genes, we wanted to evaluate how the top ranked terms are enriched in individual samples. To do this, we put the matrix of enrichment scores of 17 top ranked GSEA annotation terms of SLEPR result (##TAB##0##Table 1##, also see the complete list of the result in ##SUPPL##5##Table S2##) into a heatmap for visualization (##FIG##1##Figure 2##). As expected, although the majority of NGT samples have enrichment scores at a significant level, a small portion of IGT or DM2 samples also have enrichment scores at significant levels for some terms, which expand to a larger portion of the samples for lower ranked terms that have relatively higher FDR q-values (##FIG##1##Figure 2##, ##SUPPL##5##Table S2##).</p>", "<p>In order to get a more complete picture of the genes that are involved in the top ranked terms found by the SLEPR method, we retrieved the pathway-level differentiated genes that are associated with one of the top ranked terms: “Oxidative Phosphorylation” from ##TAB##0##Table 1## using the newly developed WPS pipeline interface for pathway-level pattern extraction, described in a separate manuscript ##REF##16423281##[4]##, Yi and Stephens, unpublished work. As expected, the pathway-level differentiated genes did not display an obvious gene-level consistency in their relative expression levels across the sample population even in the same class (##SUPPL##0##Figure S1##), although there may be higher levels expression in general in the Inclusion class (NGT) compared to Exclusion class (IGT+DM2). Interestingly, after ranking these genes with a method similar to a class difference ranking method used for term ranking (See <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section), many of genes at the top of the ranked list showed strong relevance with diabetes, and metabolism (##SUPPL##6##Table S3##). Although the higher ranked genes appear to be distributed with higher frequency in sample population, each of the sample-level differentiated genes appeared widely varying among the samples. However, less variance was observed within the top ranked genes (##SUPPL##1##Figure S2##). This is consistent with the previous observation ##REF##12808457##[23]##, and explains why common gene-level methods can not reveal the changes that occurred at pathway-level.</p>", "<p>In order to determine how stable the SLEPR method is in terms of the choice of changed directions of sample-level differentiated genes and/or class setting, we also used SLEPR with a two-sided MADe option for highly or lowly expressed genes in NGT samples compared to DM2 samples for the same class setting (NGT versus DM2). Consistent with the one-sided MADe result (##TAB##0##Table 1##, ##TAB##1##2##), we found a very similar result with “Mitochondrial genes” (two of them from different resources: No. 1 and No. 5 terms), “PGC related genes” (No. 3 term), and “oxidative phosphorylation” as the top ranked terms in the lists with two-sided MADe options (highly expressed or lowly expressed in NGT) (##SUPPL##7##Table S4##). We also identified two or more of relevant terms including “Mitochondrial genes”, “PGC related genes”, “Oxidative Phosphorylation”, and “Genes involved in electron transport” as top ranked terms as well in many different class contrast settings: NGT versus DM2+IGT with two-sided MADe; DM2 lower than NGT with one-sided MADe; DM2+IGT lower than NGT with one-sided MADe; NGT versus IGT with one-sided MADe (data not shown).</p>", "<p>Selection of cutoffs for significance testing in any gene-set analysis will have a dramatic impact on the number of pathways identified and the reliability of the results obtained. In order to determine the impact of the cutoffs for sample-level differentiated genes on the final SLEPR results, we used a series of different cutoffs for selection of sample-level differentiated genes for comparison of permutated p-values and ranks of SLEPR analysis results for human type 2 diabetes mellitus (DM2) data ##REF##12808457##[23]## with IGT and DM2 samples as the Exclusion/Background class and with one-side MADe method for highly expressed genes (as above). We selected the top 5 ranked terms from the original SLEPR result (##TAB##0##Table 1##) for comparison of permutated p-values and ranks for the same terms in SLEPR results with other cutoffs for selection of sample-level differentiated genes (##TAB##4##Table 5##). We found that, unlike the conventional ORA method ##REF##15176478##[31]##, which usually uses a gene-level differentiated gene list, the SLEPR method appears to be quite resistant to the cutoff change effects. For a wide range of values for cutoffs of sample-level differentiated genes, SLEPR maintains the main biological themes in its analysis results in that all the top ranked terms based on the original 1× MADe cutoff are primarily ranked at the top level (most of the terms still remained at the top level: ranked within the top 10 functional terms and p-value less than or close to 0.01). This stability is an important property of the SLEPR method that would be beneficial, especially for the situation when different HTP samples with dramatically different dynamic ranges are being analyzed.</p>", "<p>To compare how significant the enrichment score of a top ranked term from SLEPR result is on the DM2 dataset to that of a gene set by random chance, we generated 2000 randomly selected gene sets of the same size as the gene set “Oxidative Phosphorylation (MOOTHA_VOXPHOS)” (80 genes per gene set) from annotated genes in the GSEA database or MSigDB. Then the 80 genes of “Oxidative Phosphorylation” were mixed with the 2000 randomly selected gene sets to build up the synthetic database for SLEPR analysis using the same human DM2 dataset. As expected, “Oxidative Phosphorylation” was identified as the No. 1 top ranked term with FDR q-value as 0.016 when NGT versus IGT+DM2 class contrast was used, whereas the No. 2 ranked term (PermTerm157) has FDR q-value at as high as 0.502, indicating a “gap” between the real relevant terms and the accidental hit of a randomly selected gene set term (##SUPPL##8##Table S5##). A similar result was found using NGT versus DM2 contrast (data not shown).</p>", "<title>Case Study 2: GNF Human Tissue Datasets</title>", "<p>We next used the SLEPR method to analyze another public microarray dataset: Affymetrix U133A tissue expression dataset, derived from 79 human tissues, from the Genomic Institute of the Novartis Research Foundation (GNF) and described previously ##REF##15075390##[41]##. In this case, we used both GSEA annotation and GO (gene ontology) biological processes as the input gene sets for SLEPR analysis. Specifically, we examined whether there were tissue-specific biological processes that are enriched in testis-related tissues that were highly ranked in SLEPR analysis when configured to select testis-related tissues as the Inclusion class and the other tissues as Exclusion class, using one-sided MADe method for highly expressed genes. The expected result was obtained in SLEPR analysis using either GSEA annotation or GO biological processes in WPS ##REF##16423281##[4]##, Yi and Stephens, unpublished work, as shown in ##TAB##5##Table 6## for GSEA annotations and ##TAB##6##Table 7## for GO biological processes. There are two top ranked functional terms from GSEA annotations (the No. 1 and No. 2 ranked terms) that are directly related to testis-related gene expression as obviously described by the terms themselves (##TAB##5##Table 6##). As a comparison, the same data was analyzed using the GSEA method to compare the selected testis-related tissues with other tissues within the GNF dataset. As shown in ##TAB##7##Table 8##, the top 2 GSEA terms obtained by GSEA method do not appear to be directly related to testis-related functions, whereas the same two terms that were found as the top 2 terms in the SLEPR method were only ranked as terms 3 and 4, respectively, in the GSEA analysis result. Interestingly, we also observed that there exists a sharp rise in FDR q-values from 0.121 to 0.417 in between No. 2 and 3 terms of GSEA result and in between No. 1 and No. 2 as well (##TAB##7##Table 8##), which seems to reduce the significance of No. 3 and 4 terms that do not appear to be directly relevant to the function of testis. This observation makes the GSEA result more difficult to interpret in that the testis-specific terms (No. 3 and 4 terms) appear to be less significant (##TAB##7##Table 8##). In contrast, we observed a sharp rise in FDR q-values from 0.0005 to 0.0437 between term No. 2 and 3 of the SLEPR result (##TAB##5##Table 6##) and such a “gap” in SLEPR result may help distinguish the testis-specific terms (The top 2 terms) from more generic terms (No. 3, and 4 term) (##TAB##5##Table 6##)</p>", "<p>Similarly, most of the top ranked terms in the SLEPR result using GO biological processes are related to testis-specific functions such as spermatogenesis, and male gamete generation (##TAB##6##Table 7##). Interestingly, we again observed a sharp rise in FDR q-values from 0.0002 to 0.044167 in between No. 5 term (gametogenesis) and No. 6 term (nuclear division). Interestingly, all of the top 5 terms are testis-specific terms whereas beginning at No. 6 term, the terms that ranked below are more generic terms, which suggested a useful FDR “gap” between significant and insignificant terms that seems to reflect the difference in biological relevance or specificity. This observation is also evident in a heatmap of enrichment scores in that these testis-specific functional terms (The top 5 terms in ##TAB##6##Table 7##) are enriched consistently and more specifically in testis-related tissues compared to rest of the tissues in the dataset (##FIG##2##Figure 3##).</p>", "<p>We also asked the same question as to muscle-related tissues in the data. In contrast to testis, where essentially a single biological process is performed, we felt that muscle would represent a more diverse tissue type, since it is involved in more processes. We expected that muscle-specific functions or processes would be highly ranked in SLEPR analysis if we chose to select muscle-related tissues as the Inclusion class and the other tissues as Exclusion class, and used a one-sided MADe method to include highly expressed genes as the sample-level differentiated genes. As expected, we found that the two top ranked terms are muscle-specific functions in the SLEPR analysis result using GO biological processes (##TAB##8##Table 9##). Despite the fact that the muscle-related tissues we selected are quite divergent in that they include cardiac myocytes, smooth muscle, heart, and skeletal muscle, which were selected together as Inclusion class, the divergence among these tissues might be quite small compared to the divergence among other tissues, which makes the pathway ranking still favor muscle-specific terms. This shows another strength of the SLEPR method in that it may still be able to catch the pathway-level difference when there is divergence or large variation amongst the samples in the same phenotypic class. This is useful in that in cases where sufficient samples are not available from an individual study, they may be able to be combined with samples from other studies.</p>", "<p>Since both testis-related tissues and muscle-related tissues have a limited number of samples: 5 and 4, respectively, which are only a small portion of total 79 tissues in the dataset, there is a possibility that the small number of the samples in the Inclusion class may cause a bias favorable to the inclusion class. To test this possibility, we chose a related tissue type with more samples in the dataset to test whether the sample-size influences the SLEPR method. We choose neural or brain-related tissues as our Inclusion class with a total sample size of 24 and other tissues as the Exclusion tissues. We ran the SLEPR analysis on GO biological processes and used the one-sided MADe method to include highly expressed genes as the sample-level differentiated genes. Interestingly, the sample size of the Inclusion class does not seem to influence the SLEPR result - the top 4 ranked GO terms are indeed very specific to neural-related biological processes (##SUPPL##9##Table S6##).</p>", "<p>As described above, among the several tissue types (e.g., testis, muscle, neural-related tissues) we have chosen from this human tissue dataset to test the SLEPR method, every time it successfully identified many top-ranked terms that are directly relevant to what is expected from the tissue types that were chosen. In order to further characterize the pathway-level differentiated genes at the top of these ranked term lists, we retrieved the associated genes for the top ranked testis-specific terms (##TAB##5##Table 6##) or muscle-specific terms (##TAB##8##Table 9##) using the new features in the pathway pattern extraction pipeline of the WPS program ##REF##16423281##[4]##, Yi and Stephens unpublished work. Interestingly, we found that many of pathway-level differentiated genes associated with these testis-specific or muscle-specific terms are expressed at relatively higher level in only a small portion of these selected testis-related or muscle-related tissues although some genes are highly expressed in other tissue types. ##SUPPL##2##Figure S3## shows the expression patterns of such genes, which are associated with the top 2 ranked muscle-specific terms from SLEPR analysis shown in ##TAB##8##Table 9## (i.e., muscle contraction and muscle development). This observation suggests that individual sample-level variations widely exist across the sample population, even for the genes that are involved in these highly relevant biological processes. This suggests that the commonly used gene-level analysis methods may fail to identify such relevant pathway-level differentiated genes.</p>", "<title>Case Study 3: Prostate Cancer Datasets</title>", "<p>We also used the SLEPR method to analyze a well studied prostate cancer microarray dataset: Affymetrix U95a dataset, derived from 25 human prostate cancer tissues and 9 nonmalignant tissues described previously ##REF##11507037##[42]##, ##REF##16895928##[43]##. In this case, we used both GSEA annotation and KEGG pathway collections ##REF##16423281##[4]##. Interestingly, in our SLEPR analysis for both highly and lowly expressed genes (two-sided MADe option for SLEPR) (##TAB##9##Table 10##), we found that the top ranked functional gene sets from GSEA annotation are obviously cancer-related including: 1) “Sixty-seven genes commonly upregulated in cancer relative to normal tissue from a meta-analysis of the OncoMine gene expression database” (p = 5.43E-7, FDR q-value = 0.00011) and 2) “Genes highly expressed in hepatocellular carcinoma with poor survival” (p = 5.43E-7, FDR q-value = 2.94E-5). Another top ranked gene set: “Genes up-regulated by MYC in P493-6 (B-cell)” (p = 5.43E-7, FDR q-value = 3.45E-5), may be also consistent with the previous observation as to the presence of varying amount of B-cells within these tumors ##REF##11507037##[42]## and the fact that c-MYC is a proto-oncogene that is commonly activated in a variety of human tumors and has been shown to promote tumor angiogenesis ##REF##12368264##[44]##. In contrast, in the GSEA analysis result (##TAB##10##Table 11##), only two of the top terms were found in the top list: “Genes up-regulated by MYC in P493-6 (B-cell)” (p = 0 (actually p = 0.001 based on 1000 permutation according to GSEA manual), FDR q-value = 0.031) and “Sixty-seven genes commonly upregulated in cancer relative to normal tissue from a meta-analysis of the OncoMine gene expression database” (p = 0.004, FDR q-value = 0.058). However, for the third term: Genes highly expressed in hepatocellular carcinoma with poor survival, GSEA only ranked it at position 124 in the list with a very low significance level (p = 0.167, FDR q-value = 0.467) (##SUPPL##10##Table S7##).</p>", "<p>We also ran SLEPR analysis using KEGG annotation for this dataset with both highly and lowly expressed genes (two-sided MADe option for SLEPR). Surprisingly, we saw a pathway “Cholera – Infection” at the top of the ranked list (##SUPPL##11##Table S8##). As found by others using the same dataset with the conventional ORA method ##REF##16895928##[43]##, “Cholera – Infection” is related to tumorgenesis since this pathway contains genes such as adenylate cyclase signaling and phospholipase C that are changed in tumor cells. In addition, “Integrin-mediated cell adhesion” was found as the next top ranked pathway (##SUPPL##11##Table S8##), which has been suggested as a target pathway in many other studies to achieve an optimization of anticancer treatments, probably through interfering with anti-apoptotic signaling ##REF##16448744##[45]## and/or metastasis. However, this pathway was not found by conventional ORA analysis or gene-level based analysis ##REF##11507037##[42]##, ##REF##16895928##[43]##, probably due to the dispersion of the data or a lack of consistency at the gene-level for genes in this pathway.</p>" ]

[ "<title>Discussion</title>", "<p>More and more evidences have shown that conventional gene-level analysis methods seeking biomarkers or differential genes encountered limitations and difficulties from both statistical and biological sides ##UREF##3##[46]##–##UREF##4##[47]##. As with the analysis approaches discussed in the Introduction section, most, if not all of these gene selection methods consider the global behavior of individual genes across the sample population in one class compared to another class as the basis for grouping by applying various statistics including fold change, p-value and FDR. The genes associated with the phenotype of interest that behave more consistently within both sides of the contrasted classes will be favorably selected as differential genes and pursued in follow-up studies. The assumption that the most critically involved genes tend to behave in a similar way between samples within each class is well founded in many cases, especially for single genes that cause rare diseases. However, the inherent complexity of biological systems, the multiple stages where protein function can be regulated, and the high overall levels of individual variations, suggest that this approach may miss important aspects of biology.</p>", "<p>Interestingly, Chinnaiyan's group has hypothesized that many oncogenes may exhibit marked over-expression only in a subset of tumor samples and traditional analysis methods such as t-statistic has limitation to detect them ##REF##16254181##[48]##. Consequently, they proposed a novel method, commonly known as “Cancer outlier profile analysis” or COPA, which can effectively uncover such oncogene outlier expression profile ##REF##16254181##[48]##. Such efforts have been improved and extended by a few other groups ##REF##15307894##[49]##–##REF##18048648##[52]##. These methods are great renovations over the conventional t-statistic based or other gene-level consistency-based methods. However, since these methods mainly focus on extremely expressed genes or outliers and still consider all of their statistics at gene-level, although they may use other genes' data to estimate the significance of their statistics, they are still considered as gene-level approaches.</p>", "<p>In the current study, we explored a new method termed SLEPR, which considers the possibility that genetic impacts leading to class distinctions can occur, and consequently be measured, at the pathway level rather than at the individual gene level. Our method is motivated not only similarly as COPA methods intended for oncogene outliers occurred in only a subset of tumor samples, but also more importantly by the observation that many diseases are not simply caused by single genes, including complex diseases such as cancers, heart diseases, and hypertension, which have been shown to be caused by mutations in multiple genes in the same or related pathways or caused by single but different genes in individuals that causing biological changes in the same or related pathways among the population ##REF##11710888##[53]##–##REF##11233446##[56]##. This is what we proposed as pathway-level consistency instead of gene-level consistency that traditional methods are based on.</p>", "<p>In order to evaluate inter-sample consistency at the pathway-level, we introduce a new concept: sample-level differentiated genes (SLDGs). Unlike conventional approaches for gene-level differentiated genes, which use data from the sample population of one class compared to those of the other class, the SLDGs are based on the data of each individual sample from both sides of the contrasted class compared to the Exclusion/Background class. We make no assumptions of the data distribution and use MADe, a factored Median Absolute Deviation (MAD), which has more robust statistics compared to standard deviation-based statistics and is largely unaffected by the presence of extreme values ##UREF##6##[57]##–##UREF##7##[58]## (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section). Since we select SLDGs from the higher and/or lower ends (distance of MADe from the median) of that genes' data distribution in the Exclusion/Background class sample, the method should capture both gene-level and pathway-level differential effects. It should be noticed that our SLDGs are different from the outlier genes selected by COPA methods mentioned early in that SLDGs are sample-wise genes called on behalf of each sample, whereas outlier genes from COPA methods are called population-wise in spite of considering the occurrence of outlier genes in only a subset of population. The second difference is that the SLDGs not only include outliers as conventionally defined, but also cover high and/or low end of expressers as the basis for the next-step analysis of SLEPR.</p>", "<p>It is possible that when SLEPR method selects SLDGs with 1XMADe as the cutoff, the chance of outlier data leading to mistakenly selecting genes would be higher. The reason that we did not filter out the outlier data in advance is that we believe some outliers have biological relevance, just like what the COPA methods seek for, which is not caused by experimental issues. Simply filtering these genes out before evaluating their biological relevance could lead to loss of important information. Since we use the Fisher's exact test based enrichment method for pathway-level consistency analysis, the outliers could work together with other relevant genes of high and/or low end expressers to contribute to enrichment scores, which otherwise would be reduced to less significant levels.</p>", "<p>We have tested our method with a series of constants (0.5, 0.75, 1.25, 1.5; ##TAB##4##Table 5##; even 1.75, data not shown) that multiply MADe as the final cutoffs for selecting sample-level differentiated genes rather than the default setting of 1.0 and our MADe selections are quite stable in the final pathway-ranking results in that they pick up the same set of terms as highly or top ranked terms. This suggests that the SLEPR method is quite stable in terms of the cutoff for selection of genes, which is in contrast to the conventional ORA method using a single summary gene list as a starting point that has been claimed to be sensitive to the cutoff used for getting the gene lists ##REF##15176478##[31]##.</p>", "<p>Thus, sample-level differentiated genes represent a robust input starting point for subsequent SLEPR enrichment analysis using Fisher's exact test as the basis for discrimination of changed pathways. The derived enrichment score for each sample from both sides of the contrasted classes was used to evaluate the pathway-level consistency. We further evaluated the consistency across samples between both Inclusion and Exclusion classes for the best pathway that was present at a higher frequency and higher enrichment magnitudes in samples of the Inclusion/Target class but not in Exclusion/Background class, or with less frequency or lower enrichment magnitudes. This is the basic rationale that we used to set up the pathway-ranking algorithm in SLEPR method.</p>", "<p>As we have shown in example datasets, the SLEPR method worked quite well and was able to not only reproduce the previously analyzed and experimentally validated results (the human DM2 dataset, ##TAB##0##Table 1##,##TAB##1##2##; prostate cancer dataset, ##TAB##9##Table 10##) or generated analysis results that are consistent with biologically relevant expectations (the GNF tissue dataset, ##TAB##5##Table 6##, ##TAB##6##7## and ##TAB##8##9##; prostate cancer dataset, ##TAB##9##Table 10##), but also may have provided more opportunity to study those highly ranking terms using the pathway-level differentiated genes derived from the corresponding sample-level differentiated genes. We also suggest that one could even rank these genes for their possible relevance to a phenotype of interest between the contrasted classes as we showed for our pathway-ranking algorithms (##SUPPL##0##Figure S1##, ##SUPPL##6##Table S3##, also see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section).</p>", "<p>As a comparison with other group test methods such as the GSEA method ##REF##12808457##[23]##, we carefully selected three datasets, which are well characterized public datasets that either have had the results validated (the human DM2 dataset, prostate cancer dataset ##REF##12808457##[23]##, ##REF##11507037##[42]##) or have clear biological expectations based on the nature of the studies they were derived from (the GNF human tissue dataset ##REF##15075390##[41]##). Thus, the analysis results from these datasets can be easily interpretated and compared for different analysis methods. In addition, we are confident the choice of these well-characterized data should be better than any simulated data or synthetic datasets, since they carry natural noise levels from both experimental and biological variations. In fact, we did a couple of tests using synthetic databases derived from randomly selected genes forming artificial gene sets mixed with a real gene set and SLEPR worked very well in these cases (##SUPPL##8##Table S5##).</p>", "<p>We have found that in all the head-to-head comparisons with the GSEA method, our SLEPR method consistently did a better job or got at least compatible results with those from the GSEA method (##TAB##0##Table 1##, ##TAB##1##2## vs. 3, 4; 6 vs. 8; 10 vs.11). First of all, our method was more sensitive than the GSEA method at uncovering biological themes with higher significance in general. Such a conclusion was drawn by comparing p-values, FDR q-values and rankings obtained by both methods for the sense of relative significance considering all the terms in the results, taking into account the difficulty in directly comparing the p-values and FDR q-values derived from the two quite different methods with differences in algorithms and rationales. For example, the highly ranked term “oxidative phosphorylation” has higher significance revealed by SLEPR than by GSEA as mentioned in the Result section (##TAB##0##Table 1##–\n\n##TAB##3##4##). Secondly, as evident in ##TAB##0##Table 1## to \n\n##TAB##3##4## and ##TAB##9##10## to##TAB##10##11##, our SLEPR method was more powerful than the GSEA method in terms of finding more relevant terms with a broader scope for biological relevance functionally linked to the phenotypes under study. For example, 5 related terms were consistently uncovered by SLEPR (##TAB##0##Table 1##, ##TAB##1##2##) compared to only 1 or 3 of them that were found by GSEA with the same class setting, respectively (##TAB##2##Table 3##, ##TAB##3##4##). Thirdly, our method was consistent and powerful in the analysis result with flexible inclusion of relatively diversified but related samples into analysis, especially when the intermediate class samples were included. For example, as evident in ##TAB##0##Table 1## to \n\n##TAB##3##4##, particularly in ##TAB##0##Table 1## vs. 3, where DM2 and IGT were pooled together as one class in class comparison with NGT (NGT vs. DM2+IGT) based on the observation that the intermediate class IGT is more similar to DM2 in phenotype than NGT, SLEPR has consistently uncovered many of the relevant functional terms similar to class comparison of NGT vs. DM2 (##TAB##0##Table 1##, ##TAB##1##2##), whereas GSEA failed to do so (##TAB##2##Table 3##, ##TAB##3##4##). In addition, SLEPR was able to find consensus of underlying functions within related but different samples, which can be only “loosely” defined as one class (e.g., testis-related tissue in ##TAB##5##Table 6## and ##TAB##7##8##; muscle-related tissues in ##TAB##8##Table 9##; neural-related tissue in ##SUPPL##9##Table S6##). This would give SLEPR more flexibility and power to overcome the variations and naturally existing noise in biology samples to find the major biological consensus. Fourthly, in a number of cases mentioned in the RESULTS section, the appearance of FDR “gap” (the sharp rise) in SLEPR results implicated a potential statistical threshold that may have biological relevance, which may help users distinguish the significant terms from non-significant ones and easily draw a line to select the terms for further investigation. Fifthly, in contrast to the potential bias in GSEA method that higher enrichment scores were assigned preferentially to gene sets of large size ##REF##15226741##[40]##, no such bias exists in SLEPR method (##SUPPL##3##Figure S4##). Lastly, since our SLEPR method begins with sample-level differentiated genes in contrast to the gene-level consistency-based gene ranking in the GSEA method, SLEPR is designed to capture the sample-wise gene-level changes taking into account individual variations and specificity over the population and obviously would cover more possible gene-level changes in the population with the phenotype of interest. This is another benefit that SLEPR is designed to pursue. Consequently, SLEPR would be able to retrieve more possible relevant genes as pathway-level differentiated genes that may account for phenotype of interest, which GSEA or other group test methods may have missed due to the fact that they only consider the genes with better across-sample data behavior (e.g., SNR on top of mean and standard deviation of both contrasted classes in GSEA ##REF##15608639##[32]##; correlated expression pattern ##REF##12914697##[33]##; fold change or ratio in between two classes ##REF##15941488##[27]##).</p>", "<p>It is very important to emphasize that SLEPR is neither a simple extension of GSEA or other group test methods with similar analysis goals nor COPA methods specifically looking for outlier genes, but rather a novel pathway analysis method in terms of its unique concepts and methodology. Unlike others, SLEPR does not attempt to rank the genes or derive conventional differentiated genes at the beginning; instead, it just collects the potential genes for each sample that behave unusually compared to the population. Then SLEPR ranks the pathways or terms based on how consistent the enrichment levels of the terms amongst the selected sample-level differentiated genes of each sample. It is SLEPR that points out the new concept for the analysis: pathway-level consistency as the basis for analysis, which is not considered in any of the other analysis methods including GSEA.</p>", "<p>In conclusion, the SLEPR method represents a novel way to analyze high throughput data through pathway-level consistencies that have been proven to be effective in uncovering biological themes. Since sample-level differentiated genes can be selected from datasets measuring changes at different levels of regulation, including transcription, protein expression, and phosphorylation occurring in the same individual samples, all HTP data measuring these changes in the systems biology era can be integrated and included in SLEPR method. Furthermore, we feel that using sample-level rather than gene-level enrichment as a starting point may represent a much more robust and versatile approach for integration of data from multiple sources as new technologies advance the ability to assess regulatory networks at multiple levels.</p>" ]

[]

[ "<p>Conceived and designed the experiments: MY RS. Performed the experiments: MY. Analyzed the data: MY. Wrote the paper: MY RS.</p>", "<p>Analysis of microarray and other high throughput data often involves identification of genes consistently up or down-regulated across samples as the first step in extraction of biological meaning. This gene-level paradigm can be limited as a result of valid sample fluctuations and biological complexities. In this report, we describe a novel method, SLEPR, which eliminates this limitation by relying on pathway-level consistencies. Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes. As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field. We found that our method was able to reproduce the earlier observations with significant improvements in depth of coverage for validated or expected biological themes, but also produced additional insights that make biological sense. This new method extends existing analyses approaches and facilitates integration of different types of HTP data.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We thank Jigui Shan, Uma Mudunuri, Anney Che and David Liu for technical assistance. We would like to thank the Editor and two referees for helpful comments that led to improvements in this paper.</p>" ]

[ "<fig id=\"pone-0003288-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.g001</object-id><label>Figure 1</label><caption><title>Schematic overview of SLEPR method (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section for more details).</title><p>The goal of SLEPR method is to use sample-level differentiated genes for each sample to capture the sample-level specificity for gene-level variance, and then use functional enrichment levels of these gene lists to evaluate pathway-level data consistency associated with the contrasted classes in study: Inclusion/Target class versus Exclusion/Background class (e.g., NGT versus DM2+IGT in the human type 2 diabetes mellitus (DM2) study ##REF##12808457##[23]##). Step 1 of SLEPR is to assign the samples to the Inclusion class (I) and Exclusion class (E). Then for each genes or features in study (i.e., G1, G2, G3…Gn), consider the data distribution and use median and MADe of data in samples of class E to set up the cutoff for sample-level differentiated genes for each genes (Step 2). Each gene Gi will have its own cutoff to determine if it is a sample-level differentiated gene. Gene Gi will be selected as the sample-level differentiated gene for a sample if the data of gene Gi in this sample is beyond the cutoff (Step 3). Each sample including samples from both I and E classes will have its own sample-level differentiated gene list (L1, L2, L3….) (Step 3). To determine the functional enrichment levels in any <italic>a priori</italic> defined gene sets, pathways, or functional categories (e.g., GO terms) for each of the sample-level differentiated lists, batch computation of Fisher's exact test based enrichment analysis is performed and the results are merged automatically into a matrix (e.g., Stanford format file) of enrichment scores which consists of enrichment scores of each sample from class I and E for each term (T1, T2, T3, …Tm), which are transformed as −log₁₀(p-value) of Fisher's exact test p-values (Step 4). To determine whether a gene set, pathway, or functional category (e.g., GO term) is significant in terms of how consistent it is enriched across samples, a pathway ranking algorithm is applied to the enrichment score matrix to obtain pathway ranking scores, which considers both positive contribution of class I and negative contribution of class E from individual sample-level enrichment level (see details in <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section) (Step 5). To determine the statistical significance of actual ranking of a gene set or a GO term in the contrasted classes: I versus E, the entire procedure (steps 1 to 5) is repeated 1000 times or more by simply permutating the class labels for each selected samples (Step 6). The pathway ranking scores of each term from each permutation are pooled together and used to build the empirically derived distribution of pathway ranking scores from the permutation procedure. The permutated p-value for each term is calculated as the fraction of random trials resulting in permutated pathway ranking scores higher than the actual score from the original sample assignments.</p></caption></fig>", "<fig id=\"pone-0003288-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.g002</object-id><label>Figure 2</label><caption><title>Heatmap of enrichment scores in all samples from NGT versus IGT and DM2 for the top 17 ranked terms of SLEPR result listed in ##SUPPL##5##Table S2##.</title><p>The enrichment scores, which in general derived from Fisher's exact test p-value using formula (−Log10(p-value)), were floored to 0 if the ListHits&lt;2 or p-value&gt;0.05. The rows of the heatmap are the ranked terms in the same order as in ##SUPPL##5##Table S2## (Top 7 of them shown in ##TAB##0##Table 1##) from top to bottom with the higher ranks at the top. The gradient of red color in heatmap indicated the enrichment levels.</p></caption></fig>", "<fig id=\"pone-0003288-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.g003</object-id><label>Figure 3</label><caption><title>Heatmap of enrichment scores of sample-level differentiated genes of all samples in human GNF tissue dataset </title><p>\n##REF##15075390##[41]## for the top 8 ranked GO biological process terms shown in ##TAB##6##Table 7##. The enrichment scores, which in general derived from Fisher's exact test p-value using formula (−Log10(p-value)), were floored to 0 if the ListHits&lt;2 or p-value&gt;0.05. The rows of the heatmap are the terms and columns are tissue samples from the dataset. The gradient of red color in heatmap indicated the enrichment levels.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003288-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t001</object-id><label>Table 1</label><caption><title>Top ranked GSEA annotation terms in SLEPR Analysis Result for Comparison of NGT vs DM2+IGT in human DM2 data.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Combined Ranking</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Permutated P_Val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR q_Val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mitochondrial genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HUMAN_MITODB_6_2002</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.009408</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00011557</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.144</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mitochondrial genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MITOCHONDRIA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.96734041</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00013403</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0835</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes involved in electron transport</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELECTRON_TRANSPORT_CHAIN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.73313179</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00033066</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.13733333</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Oxidative Phosphorylation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MOOTHA_VOXPHOS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.63908609</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00048395</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.15075</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PGC related genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PGC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.41673472</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00146549</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3652</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIBOSOMAL_PROTEINS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIBOSOMAL_PROTEINS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.26145395</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00456661</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.9483</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t002</object-id><label>Table 2</label><caption><title>Top ranked GSEA annotation terms in SLEPR Analysis Result for Comparison of NGT vs DM2 in human DM2 data.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Combined Ranking</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Permutated P_Val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR_q_Val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mitochondrial genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HUMAN_MITODB_6_2002</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.33012855</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0000025</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.003</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mitochondrial genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MITOCHONDRIA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.19377468</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0000975</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0585</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PROPANOATE_METABOLISM</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PROPANOATE_METABOLISM</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.87576134</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00029917</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.11966667</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PGC related genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PGC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.85709181</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00031583</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.09475</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Oxidative Phosphorylation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MOOTHA_VOXPHOS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.83877765</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0003425</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0822</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes involved in electron transport</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELECTRON_TRANSPORT_CHAIN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.80602325</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0003875</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0775</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIBOSOMAL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PROTEINS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIBOSOMAL_PROTEINS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.73004401</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00051333</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.088</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Downregulated in correlation with overt Alzheimer's Disease, in the CA1 region of the hippocampus</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALZHEIMERS_DISEASE_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.43387443</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00222333</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3335</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t003</object-id><label>Table 3</label><caption><title>Top ranked GSEA annotation terms in GSEA Analysis Result for Comparison of NGT vs DM2+IGT in human DM2 data.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NOM p-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR q-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FWER p-val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Upregulated by expression of mutant MeCP2 (Rett syndrome) vs. wt MeCP2 in fibroblasts</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RETT_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6723</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.830771</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.93558</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.56</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Granule constituents expressed during mouse promyelocytic cell line cell differentiation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">LIAN_MYELOID_DIFF_GRANULE</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5568</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.791872</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.002012</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.700521</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.683</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes highly associated with medulloblastoma treatment failure</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">POMEROY_MD_TREATMENT GOOD_VS_POOR_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5402</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.720124</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.016327</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.971015</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.875</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Regulated by UV-B light in normal human epidermal keratinocytes, cluster 8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UVB_NHEK3_C8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4442</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.685022</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.931</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes involved in electron transport</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELECTRON_TRANSPORT_CHAIN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3457</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.680579</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.060797</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.863601</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.937</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Down-regulated in mycosis fungoides (cutaneous T-cell lymphoma) T-cells resistant to IFN-alpha, compared to sensitive parent cell line</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IFNALPHA_RESIST_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5722</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.648226</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.014315</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.980393</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.968</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Regulated by UV-B light in normal human epidermal keratinocytes, cluster 6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UVB_NHEK3_C6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4663</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.642358</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.018987</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.885222</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.979</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t004</object-id><label>Table 4</label><caption><title>Top ranked GSEA annotation terms in GSEA Analysis Result for Comparison of NGT vs DM2 in human DM2 data.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NOM p-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR q-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FWER p-val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Up-regulated following treatment with Et-743 at any timepoint in at least 8 of 11 sarcoma cell lines</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ET743_SARCOMA_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4778</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.851262</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0019455</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.835225</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.416</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Oxidative Phosphorylation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MOOTHA_VOXPHOS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6187</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.844164</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.02</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.460014</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.446</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Target genes down regulated by p53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KANNAN_P53_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6835</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.84351</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.005848</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.309037</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.447</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes involved in electron transport</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELECTRON_TRANSPORT_CHAIN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.594</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.840375</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0217822</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.240362</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.46</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">p-regulated in liver, heart or kidney tissue from hypophysectomized rats (lacking growth hormone), compared to normal controls</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HYPOPHYSECTOMY_RAT_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5129</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.776757</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0040404</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3918</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.664</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Upregulated by expression of mutant MeCP2 (Rett syndrome) vs. wt MeCP2 in fibroblasts</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RETT_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.544</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.697153</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0179641</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.740229</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.855</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes down-regulated by LIF treatment (10 ng/ml, overnight) in AtT20 cells</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ABBUD_LIF_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.569</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.682703</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0226804</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.727445</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.872</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">OXIDATIVE_PHOSPHORYLATION</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">OXIDATIVE_PHOSPHORYLATION</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5167</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.653935</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0459082</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.832665</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.908</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t005</object-id><label>Table 5</label><caption><title>Comparison of SLEPR results using a series of cutoffs for selection of sample-level differentiated genes.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TermName (TermID)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">0.5XMADe</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">0.75XMADe</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">1XMADe</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">1.25XMADe</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">1.5XMADe</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">p-Value*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rank</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p-Value*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rank</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p-Value*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rank</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p-Value*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rank</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p-Value*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rank</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mitochondrial genes (HUMAN_MITODB_6_2002)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.150</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">153</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.08E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.16E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.58E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.03E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mitochondrial genes (MITOCHONDRIA)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.170</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">179</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.38E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.34E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.22E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.31E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes involved in electron transport (ELECTRON_TRANSPORT_CHAIN)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.49E-03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8.82E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.31E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.75E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.61E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Oxidative Phosphorylation (MOOTHA_VOXPHOS)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.01E-02</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.91E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.83E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.22E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.53E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PGC related genes (PGC)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.05E-02</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.93E-03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.47E-03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.05E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.21E-04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t006</object-id><label>Table 6</label><caption><title>Top ranked terms in SLEPR analysis result for testis-related tissues in GNF dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Combined_Ranking</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Permutated_P_Val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR_q_Val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes expressed specifically in human testis tissue</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HUMAN_TISSUE_TESTIS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">25.62201</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.29E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Testis related genes curated from the GNF normal tissue compendium</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TESTIS_EXPRESSED_GENES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">24.08417</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.29E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0005</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cell-cycle dependent genes regulated following exposure to serum in a variety of human fibroblast cell lines</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SERUM_FIBROBLAST_CELLCYCLE</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.951284</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.56E-05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0437</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">50 top ranked SAM-defined over-expressed genes in each subgroup__PR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ZHAN_MM_CD138_PR_VS_REST</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.523997</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000106</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0365</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t007\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t007</object-id><label>Table 7</label><caption><title>Top ranked GO Biological Processes terms in SLEPR analysis result for testis-related tissues in GNF dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Term</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Combined_Ranking</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Permutated_P_Val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR_q_Val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">spermatogenesis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0007283</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.21279</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.71E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0005</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">male gamete generation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0048232</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.21279</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.71E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0005</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">sexual reproduction</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0019953</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.27175</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.71E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000333</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">reproduction</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0000003</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.17275</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.71E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00025</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">gametogenesis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0007276</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13.95838</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.71E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0002</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">nuclear division</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0000280</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.461007</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000178</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.044167</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">M phase</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0000279</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.361697</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000195</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.041429</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t008\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t008</object-id><label>Table 8</label><caption><title>Top ranked terms in GSEA analysis result for testis-related tissues in GNF dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NOM p-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR q-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FWER p-val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">50 most interesting genes upregulated by the combination of TSA and DAC in at least one of four pancreatic cancer cell lines, but not in normal (HPDE) cells</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TSADAC_PANC50_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.571787</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.3071</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.002</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.004</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Up-regulated 2 hours after VEGF treatment in human umbilical vein endothelial cells</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VEGF_HUVEC_2HRS_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.562051</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.077</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.121</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Testis related genes curated from the GNF normal tissue compendium</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TESTIS_EXPRESSED_GENES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.868249</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.8032</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.271</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.417</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes expressed specifically in human testis tissue</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HUMAN_TISSUE_TESTIS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.904183</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.7737</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.255</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.474</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t009\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t009</object-id><label>Table 9</label><caption><title>Top ranked GO Biological Processes terms of SLEPR result for muscle-related tissues in GNF dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Term</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Combined_Ranking</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Permutated_P_Val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR_q_Val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">muscle contraction</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0006936</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.035783</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000195</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.289</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">muscle development</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0007517</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.766843</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000438</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.325</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">cell-cell signaling</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0007267</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.115529</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000755</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.373667</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">morphogenesis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0009653</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.51698</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001281</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.47525</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">development</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0007275</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.509388</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001292</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3836</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">organogenesis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0009887</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.434454</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001375</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.34</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">cell motility</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0006928</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.410239</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00141</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.298857</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">striated muscle contraction</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0006941</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.781977</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.002482</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4605</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">regulation of body fluids</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0050878</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.602872</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.003043</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.501778</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">angiogenesis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GO∶0001525</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.40132</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.003982</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5909</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t010\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t010</object-id><label>Table 10</label><caption><title>Top ranked terms in SLEPR analysis results for a well-studied prostate cancer dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Combined_Ranking</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Permutated_P_Val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR q_Val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Sixty-seven genes commonly upregulated in cancer relative to normal tissue, from a meta-analysis of the OncoMine gene expression database</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CANCER_NEOPLASTIC_META_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.312481</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.43E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.000111</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes downregulated in response to glutamine starvation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PENG_GLUTAMINE_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.578343</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.43E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.25E-05</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">These are genes identified by simple statistical criteria as differing in their mRNA expresssion between WTs and fetal kidneys LOW</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">LI_FETAL_VS_WT_KIDNEY_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.961163</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.43E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00004</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes 2fold upregulated by insulin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ROME_INSULIN_2F_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.905375</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.43E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.7E-05</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes up-regulated by MYC in P493-6 (B-cell)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SCHUMACHER_MYC_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.762658</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.43E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.45E-05</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes highly expressed in hepatocellular carcinoma with poor survival.</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HCC_SURVIVAL_GOOD_VS_POOR_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.449725</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.43E-07</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.94E-05</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003288-t011\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003288.t011</object-id><label>Table 11</label><caption><title>Top ranked terms in GSEA analysis results for a well-studied prostate cancer dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermName</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GSEA_TermID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NES</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NOM p-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FDR q-val</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FWER p-val</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes up-regulated by MYC in P493-6 (B-cell)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SCHUMACHER_MYC_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6769</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.043</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.031466</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.039</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes overexpressed in polyclonal plasmablastic cells (PPCs), mature plasma cells isolated from tonsils (TPCs), and mature plasma cells isolated from bone marrow (BMPCs), as compared to B cells purified from peripheral blood (PBBs) and tonsils (TBCs)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TARTE_PC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6101</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.954</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0019193</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.07472</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.144</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes downregulated in response to glutamine starvation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PENG_GLUTAMINE_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4842</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.939</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.058919</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.167</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes downregulated in response to leucine starvation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PENG_LEUCINE_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5067</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.911</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001**</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.066378</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.238</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Downregulated in HL-60 promyeloid leukemic cells after treatment with the cytotoxic drug cantharidin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CANTHARIDIN_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6218</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.903</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.001*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.059042</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.26</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Genes downregulated in response to rapamycin starvation</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PENG_RAPAMYCIN_DN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5000</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.891</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0020576</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.060076</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.309</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Sixty-seven genes commonly upregulated in cancer relative to normal tissue, from a meta-analysis of the OncoMine gene expression database</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CANCER_NEOPLASTIC_META_UP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6634</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.883</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0042105</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.058265</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.335</td></tr></tbody></table></alternatives></table-wrap>" ]

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[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s001\"><label>Figure S1</label><caption><p>Sample-wise gene-level variations shown by the heatmap of z-scores for pathway-level differentiated genes, which are associated with one of the top terms (Oxidative Phosphorylation) from the SLEPR result in ##TAB##0##Table 1##. The z-scores of these genes were computed using all samples from both Inclusion and Exclusion classes, and were displayed in the heatmap using color gradient for their values as red for positive z-scores and green for negative z-scores, black for scores of 0. The z-scores are calculated on each gene basis. For each sample, the z-score (also referred as standard score sometime) of an intended gene is derived by subtracting the population mean of this gene from the original data of the corresponding sample of this gene and then dividing the difference by the population standard deviation of this gene. In general, a positive z-score indicates a relatively higher expression level of a gene in the corresponding sample over the sample population for this gene; negative for a lower expression; 0 for average expression.</p><p>(1.41 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s002\"><label>Figure S2</label><caption><p>Heatmap of call values for sample-level differentiated genes, which are associated with one of the top terms (Oxidative Phosphorylation) from the SLEPR result in ##TAB##0##Table 1##. The call value is 1 if the gene is called as sample-level differentiated genes for the corresponding sample, 0 if not. The genes were ranked in a way as described in <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> Section, and were displayed in the heatmap in the order of ranks from top to bottom with higher ranked genes at the top.</p><p>(1.17 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s003\"><label>Figure S3</label><caption><p>Sample-wise gene-level variations shown by the heatmap of Z-scores for sample-level differentiated genes, which are associated with the No. 1 (Muscle contraction) and No. 2 (Muscle development) terms from the SLEPR result in ##TAB##8##Table 9##. The z-scores of these associated genes were computed using all samples from both Inclusion and Exclusion classes, and were displayed in the heatmap using color gradient for their values as red for positive z-scores and green for negative z-scores, black for scores of 0.</p><p>(1.37 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s004\"><label>Figure S4</label><caption><p>No bias for the SLEPR ranking scores vs. sizes of gene sets. A pdf file with several plots showing no bias for the SLEPR ranking scores vs. sizes of the gene sets: for distribution of SLEPR pathway ranking scores vs. gene set sizes (with different gene set size windows) and histogram distribution of gene set sizes for data in ##SUPPL##5##Table S2##, ##SUPPL##7##Table S4##, and ##SUPPL##9##Table S6## (for all terms or different numbers of top ranked terms in the tables).</p><p>(1.92 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s005\"><label>Table S1</label><caption><p>The complete list of result of GSEA analysis result for NGT vs. IGT+DM2 comparison, which has the top ranked terms shown in ##TAB##2##Table 3##\n</p><p>(0.19 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s006\"><label>Table S2</label><caption><p>The complete list of result of SLEPR analysis result of GSEA annotations for NGT vs. IGT+DM2 comparison with one-side MADe option for highly expressed genes in NGT, which has the top ranked terms shown in ##TAB##0##Table 1##.</p><p>(0.33 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s007\"><label>Table S3</label><caption><p>The complete list of ranked pathway-level differentiated genes of the No. 1 term (Oxidative Phosphorylation) in ##TAB##0##Table 1##. The call values for sample-level differentiated genes of these genes are also included in the file.</p><p>(0.06 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s008\"><label>Table S4</label><caption><p>The complete list of SLEPR analysis result of GSEA annotations for NGT vs. DM2 comparison with two-side MADe option for highly or lowly expressed genes in NGT.</p><p>(0.30 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s009\"><label>Table S5</label><caption><p>The complete list of SLEPR analysis result of a synthetic database that consisted of 2000 randomly selected gene sets (with matched size of gene set) mixed with the known gene set of “Oxidative Phosphorylation” from MSigDB. NGT versus IGT+DM2 class contrast was used with one-side MADe option for highly expressed genes in NGT.</p><p>(0.22 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s010\"><label>Table S6</label><caption><p>The complete list of SLEPR analysis result of GO biological processes for comparison of neural or brain-related tissues vs. other tissues with one-side MADe option for highly expressed genes in neural or brain-related tissues.</p><p>(0.28 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s011\"><label>Table S7</label><caption><p>The complete list of result of GSEA analysis result for tumor vs. normal comparison, which has the top ranked terms shown in ##TAB##10##Table 11##\n</p><p>(0.16 MB XLS)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003288.s012\"><label>Table S8</label><caption><p>The complete list of SLEPR analysis result of KEGG pathways for comparison of tumor vs. normal with two-side MADe option for highly or lowly expressed genes in tumors.</p><p>(0.02 MB XLS)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label/><p>Microarray data for human type 2 diabetes mellitus (DM2) study ##REF##12808457##[23]## was re-analyzed with SLEPR method to compare either NGT versus IGT+DM2 (IGT+DM2 as Exclusion/Background class in SLEPR). One-side MADe method was used in SLEPR for selection of highly expressed genes as sample-level differentiated genes in the comparison of NGT versus IGT+DM2. Two-side MADe method was also used for selection of highly and lowly expressed genes as sample-level differentiated genes, and similar result was obtained (see ##SUPPL##7##Table S4##). 1000 permutations were performed. Combined_Ranking: Combined ranking scores for terms; Permutated_P_Val: p-value of terms derived from permutated data; FDR_q_Val: FDR of terms derived from permutated data (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section for details).</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt102\"><label/><p>Microarray data for human type 2 diabetes mellitus (DM2) study ##REF##12808457##[23]## was re-analyzed with SLEPR method to compare either NGT versus DM2 (DM2 as Exclusion/Background class in SLEPR). One-side MADe method was used in SLEPR for selection of highly expressed genes as sample-level differentiated genes in the comparison of NGT versus DM2. 1000 permutations were performed. Combined_Ranking: Combined ranking scores for terms; Permutated_P_Val: p-value of terms derived from permutated data; FDR_q_Val: FDR of terms derived from permutated data (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section for details).</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><label/><p>Microarray data for human type 2 diabetes mellitus (DM2) study ##REF##12808457##[23]## was re-analyzed with GSEA method (using the newest version (v 2.0.1) GSEA tool ##REF##14990455##[22]##) to compare NGT versus IGT+DM2. 1000 permutations were performed. **: p-value(s) is adjusted to p = 1/number of permutation for p = 0 according to GSEA manual.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt104\"><label/><p>Microarray data for human type 2 diabetes mellitus (DM2) study ##REF##12808457##[23]## was re-analyzed with GSEA method (using the newest version (v 2.0.1) GSEA tool ##REF##14990455##[22]##) to compare NGT versus DM2. 1000 permutations were performed. **: p-value(s) is adjusted to p = 1/number of permutation for p = 0 according to GSEA manual.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt105\"><label/><p>Comparison of permutated p-values and ranks of SLEPR analysis results of for human type 2 diabetes mellitus (DM2) data ##REF##12808457##[23]## with IGT and DM2 samples as Exclusion/Background class by using a series of different cutoffs (0.5, 0.75,1,1.25,1.5× of MADe) for selection of highly expressed genes as sample-level differentiated genes. The one-side MADe method selecting for highly expressed genes was used (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section). The top 5 ranked terms from the case of 1XMADe are selected for comparison of permutated p-values and ranks for the same terms with those derived from other cutoffs. 1000 permutations were performed.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt106\"><label/><p>Microarray data for GNF human tissues study ##REF##15075390##[41]## was analyzed with SLEPR method to compare testis related tissues (total 5 testis related tissues selected: Testis Germ Cells, Testis Interstitial, Testis Leydig Cell, Testis Seminiferous Tubule, Testis) (as Inclusion/Target tissues in SLEPR) to the other tissues (total 74 tissues) (as Exclusion/Background class in SLEPR) as for GSEA annotated gene sets. In SLEPR method, one-side MADe method for selection of highly expressed genes as sample-level differentiated genes was used. 1000 permutations were performed.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt107\"><label/><p>Microarray data for GNF human tissues study ##REF##15075390##[41]## was analyzed with SLEPR method to compare testis related tissues (total 5 testis related tissues selected: Testis Germ Cells, Testis Interstitial, Testis Leydig Cell, Testis Seminiferous Tubule, Testis) as Inclusion/Target tissue to the rest of the tissues (74 other tissues) as Exclusion/Background class for testis-specific GO biological processes, using one-side MADe method for selection of highly expressed genes as sample-level differentiated genes. 1000 permutations were performed.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt108\"><label/><p>Microarray data for GNF human tissues study ##REF##15075390##[41]## was analyzed with GSEA method ##REF##12808457##[23]## (Using the newest version (v2.0.1) GSEA tool ##REF##16199517##[24]##) to compare testis related tissues (total 5 testis related tissues selected: Testis Germ Cells, Testis Interstitial, Testis Leydig Cell, Testis Seminiferous Tubule, Testis) to the other tissues (total 74 tissues) as for GSEA annotated gene sets. 1000 permutations were performed. **: p-value(s) is adjusted to p = 1/number of permutation for p = 0 according to GSEA manual.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt109\"><label/><p>Microarray data for GNF human tissues study ##REF##15075390##[41]## was analyzed with SLEPR method to compare muscle related tissues (total 4 muscle related tissues selected: Cardiac Myocytes, Heart, Skeletal Muscle, Smooth Muscle) as Inclusion/Target tissue to the rest of tissues (74 other tissues) as Exclusion/Background class for testis-specific GO biological processes, using one-side MADe method for selection of highly expressed genes as sample-level differentiated genes (see <xref ref-type=\"sec\" rid=\"s4\">Materials And Methods</xref> section). 1000 permutations were performed.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt110\"><label/><p>A well studied prostate cancer dataset ##REF##11507037##[42]##, ##REF##16895928##[43]## was analyzed with SLEPR method. SLEPR method used the 25 tumor samples as Inclusion/Target class compared to 9 nonmalignant tissues as Exclusion/Background class for GSEA annotated terms, by two-sided MADe method for selection of both highly and lowly expressed genes as sample-level differentiated genes. Only top ranked functional terms were shown in the table (the chromosomal location-based annotation terms were taken out for simplicity). 1000 permutations were performed.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt111\"><label/><p>A well studied prostate cancer dataset ##REF##11507037##[42]##, ##REF##16895928##[43]## was analyzed with GSEA method (Using the newest version (v2.0.1) GSEA tool ##REF##16199517##[24]##). GSEA compared the tumor samples to the nonmalignant tissues. Only top ranked functional terms were shown in the table (the chromosomal location-based annotation terms were taken out for simplicity, the full ranked list can be obtained from ##SUPPL##10##table S7##). 1000 permutations were performed. **: p-value(s) is adjusted to p = 1/number of permutation for p = 0 according to GSEA manual.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institute of Health, under Contract N01-CO-12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government</p></fn></fn-group>" ]

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[ "<media xlink:href=\"pone.0003288.s001.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s002.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s003.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s004.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s005.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s006.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s007.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s008.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s009.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s010.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s011.xls\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003288.s012.xls\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>We live in a dynamic environment where object relevancy to the task in hand could be altered through the time making some potentially useful stimuli irrelevant to the task in a later stage. Frontal cortex has been shown to be critical in blocking irrelevant information from entering working memory (WM) when their irrelevancy is clear from the beginning of the task ##REF##11571223##[1]##–##REF##18066057##[3]##. However, it is not always possible to dissociate relevant and irrelevant objects from the very first moment they come to our sight. In this condition, any imprudent filtering could impair subjects' performance by eliminating relevant items from further processing. Here, subjects need to retain maximum possible information in their WM until it becomes clear which items should be eliminated from WM to free attentional and memory resources. The mechanism underlying this type of irrelevancy elimination from WM is not known yet.</p>", "<p>The role of frontal and parietal cortices respectively in information retention and distracter filtering is well established. Recent studies have shown that parietal activity in memory maintenance period is correlated to the amount of WM load ##REF##15085133##[4]##–##UREF##0##[6]## while frontal activity during is shown to be necessary to prevent distracters from entering WM when human subjects are involved in two interleaving, main and distracting, spatial memory tasks ##REF##11953754##[2]##. In these experiments and other similar studies ##REF##11571223##[1]##, ##REF##18066057##[3]##, relevant and irrelevant items have been clearly dissociated from each other from the very beginning of the task. Thus, activities in frontal and other brain areas reported in these studies are an indication of their involvement in preventing irrelevant items from entering WM. In such studies parietal involvement in distracter filtering seems to be unnecessary since irrelevant items had been eliminated before reaching parietal cortex which is responsible for retention of items in WM ##REF##15085133##[4]##–##REF##15085132##[5]##. In contrary, when the irrelevant items in addition to the relevant ones are already stored in WM, parietal involvement in irrelevancy elimination might be crucial. In this condition, in addition to the frontal cortex, parietal cortex could be a part of irrelevancy filtering network.</p>", "<p>An alternative view to irrelevancy filtering has been put forward by some authors ##UREF##1##[7]##–##UREF##2##[9]## suggesting that biasing attentional resources toward relevant objects, called selection process, is responsible for irrelevancy suppression. According to this hypothesis feedback signal, mainly from frontal cortex, biases the competition between relevant and irrelevant items in favour of the task relevant items ##UREF##1##[7]##–##UREF##2##[9]##. Thus, in a selection process the number of relevant items and the time needed for their detection and biasing attention towards them mainly influence the processing duration. In contrast to this selection procedure, in a filtering mechanism in which irrelevant items are directly detected and inhibited, processing duration is proportional to the number of irrelevant items.</p>", "<p>To explore the brain mechanism for elimination of irrelevant items from WM (filtering vs. selection) and its neural correlates, we examined brain ERP activities of normal human subjects, during a modified version of change detection task. In this task the relevancy or irrelevancy of sample items were revealed to the subjects after a delay, when test stimuli were presented, forcing the subjects to store all of the sample items in WM. In order to understand the mechanism underling irrelevancy elimination we controlled the amount of relevancy and irrelevancy loads independent from each other as they are two indexes representing selection and filtering processes, respectively. We found that subjects' RT and ERP latency depended on the amount of irrelevant objects number and therefore, filtering and not selection mechanism is responsible for eliminating irrelevant information from visual WM.</p>" ]

[ "<title>Methods</title>", "<title>Participants</title>", "<p>Fourteen healthy male undergraduate students (age range: 20–28 years) were paid to participate in this experiment. None of the participants had any history of neurological or psychiatric disorders. Participants had normal or corrected to normal visual acuity. The experiment was approved by the Shahid Beheshti Medical University ethics committee and Iranian Society for Physiology and Pharmacology and subjects gave written informed contest before the experiments when all procedures were explained to them.</p>", "<title>Stimuli and Procedure</title>", "<p>In this study we used a procedure partially similar to the one used previously by Vogels &amp; Machizawa (2004). In this procedure each trial started by presenting a fixation cross in the center of the screen. After 300–400ms a cue arrow was presented above the fixation cross. Direction of the arrow indicated that objects presented in the pointed visual hemifield should be memorized and that the objects in the other hemifield should be ignored. The fixation cross remained on screen during the rest of trial but the arrow was removed after 200ms. After a 1000ms interval, two arrays of sample stimuli were presented. Each array was presented within a 4°×7.3° rectangular regions in each visual hemifield. These regions were centred 3° from the fixation cross and consisted of 2–7 coloured squares. Each coloured square subtended 0.65°×0.65° of visual field and its colour was selected randomly from a set of seven highly discriminable colours (black, white, red, green, blue, yellow &amp; pink). A particular colour was not selected more than two times in each hemifield. All stimuli were presented on a light gray background (30cd/mm²). Positions of the coloured squares within the rectangular regions were randomized in each trial with the constraint that the distance between each two squares be at least 2° (centre to centre). In each trial the number of items in the left and right hemifields was identical but location and colour of the presented items could vary between the hemifields. We presented sample stimuli for 100ms and participants had to memorize presented objects in the cued hemifield to compare them later with test stimuli. The test stimuli were presented 900ms from the sample offset (##FIG##0##Figure 1a##).</p>", "<p>The most prominent difference between our procedure and the one used by Vogel &amp; Machizawa (2004) was in the test set. In their procedure, subjects participated in a whole report (WR) paradigm. In their paradigm, the number of objects within sample and test sets was always the same and all the presented items within sample set were required and relevant to the task. In our experiment, in addition to WR paradigm, in some trials we randomly used partial report (PR) paradigm. In this condition, the number of objects in the test set was smaller than those in the sample set. In both trial types, participants had to report whether there was a colour discrepancy (50% of trials) between the test set objects and their corresponding objects within the sample. In PR trials participants should ignore any change regarding a potential difference between the number of objects in the sample and test sets and they had to confine their colour comparison to those objects presented in both sets. In this condition the eliminated sample objects became irrelevant to the task (##FIG##0##Figure 1b##).</p>", "<p>In this experiment all possible combinations of relevancy and irrelevancy loads were presented with equal frequency. Thus in contrast to previous studies that confined PR to cueing or presenting just one object in the test set ##REF##9384378##[10]##–##REF##11900102##[11]##, in our paradigm, number of objects within the test set varied across different trials. Altogether 77.8% (21/27) of trials were PR and 22.2% (6/27) were WR. The sequence of trials was randomized so participants did not know whether a trial was WR or PR until the test image was presented. It is noteworthy that in this condition relevancy (number test objects number) and irrelevancy loads (the number of eliminated) varied independently. For example, when relevancy load was equal to one, the irrelevancy load still could varied between one to six corresponding to the trials with two to seven objects within the sample sets.</p>", "<p>During the experiment, accuracy and speed were both stressed. We accepted those responses within 1500ms after test onset and few trials with longer response time were eliminated from the results. Subsequent trials started 1800ms after the test offset. Before the experiment, subjects participated in a few training trials (&lt;50 trials) to become familiar with the task. Participants' responses during these trials were not included in results. Each subject participated in 1260 trials within 15 blocks with 2 minutes break between them. Two participants with more than 20% eliminated trials (due to late response) were excluded from the experiment.</p>", "<title>ERP Recording</title>", "<p>EEG recording were made by using a Neuroscan system with 32 Ag/AgCl sintered electrodes mounted on an elastic cap. Data were acquired continuously in AC mode (0.05–30Hz) with 1 kHz sampling rate. Reference electrodes were linked mastoids, grounded to AFz. Four electrodes monitored horizontal and vertical eye movements for off-line artifact rejection. Electrodes impedance were kept &lt;5kΩ. Data was resampled off-line by 250Hz sampling rate. Baseline was corrected on the basis of activities, recorded 100ms before the sample stimulus onset. A separate analysis was applied in order to eliminate those trials with eye movement and eye blinks, during100ms before the sample onset up to 800ms after the test onset, by detecting those trials on which the peak-to-peak voltage in the horizontal and vertical eye movement channels exceeded 30 µV (&lt;10% of trials).</p>", "<p>Here we divided cortical activities into four groups according to their spatial distribution and participants brain activity mapping; 1) frontal leads (recorded by FP1, F3, F7, FC3, Fz, FCz, FP2, F4, F8 and FC4 sensors), 2) parietal leads (recorded by P3, P7, CP3, P4, P8, CP4, CPz and Pz sensors), 3) occipital lead (recorded O1, O2 and Oz sensors) and, 4) temporal leads (recorded by T7, T8, TP7, TP8, FT7 and FT8 sensors). We only analyzed the ERP activities after test onset because earlier activities are shown to be correlated with memory retention ##REF##15085132##[5]##–##UREF##0##[6]##, ##REF##11369947##[12]## rather than those processes related to irrelevancy filtering or change detection.</p>", "<title>Data Analysis</title>", "<p>For each experimental condition averaged ERP signal was calculated for each participant separately. Grand averaged ERPs were calculated by averaging individual participants' signal. In order to examine the effects of experimental parameters on frontal and parietal activities we measured ERP activity using a sliding window. In this method, we divided the first 800ms of ERP activities, which was recorded after onset of test object set into separate time windows with 48ms length and 36ms overlap between each two adjacent windows. In each time window, we applied a factorial ANOVA to ERP area under curve. Using this method enabled us to detect any modulation in ERP activities related to experimental conditions with very low onset time estimation error (&lt;12ms).</p>" ]

[ "<title>Results</title>", "<title>Participants Behavior</title>", "<p>We checked the effect of number of sample objects and trial type on participants' response accuracy and RT by applying two separate two-factor ANOVA (##FIG##1##figure 2a##). Consistent with the previous studies of visual WM ##REF##9384378##[10]##–##REF##11900102##[11]##, ##UREF##3##[13]## we found that increasing the number of objects in sample set significantly reduced participants' response accuracy (F(5,132) = 52.75, <italic>p</italic>&lt;0.001). We did not find any significant difference between participants' response accuracy during partial report (PR) trials that needed irrelevancy elimination and whole report (WR) trials that did not need any elimination (F(1,132) = 0.66, <italic>p</italic>&gt;0.05). The interaction between the two factors also remained non-significant (F(5,132) = 0.87, <italic>p</italic>&gt;0.05). Lack of trial type effect indicates that participants' response accuracy depends on the amount of memory load (i.e. sample objects number) and reducing the number of objects within the test set does not improve their response accuracy.</p>", "<p>Despite the fact that participants' response accuracy remained insensitive to trials type, it was still possible that participants used excessive processes during PR or WR trials, relative to the other one, which consequently affected participants' RT. In order to examine this possibility we applied a two-factor ANOVA (sample objects number and trials type) to participants' RT (##FIG##1##figure 2b##). In contrast to participants' response accuracy, we found that participants' RT was significantly (F(1, 132) = 17.06, <italic>p</italic>&lt;0.001) different between trials that required irrelevancy elimination (i.e. PR trials) and those that did not require any irrelevancy elimination (i.e. WR trials). Here, participants showed significantly shorter RT during WR trials (767±123ms) compared to PR trials (905±132ms). The effect of sample objects number (F(5, 132) = 1.20, <italic>p</italic>&gt;0.05) and its interaction with trial type (F(5, 132) = 0.06, <italic>p</italic>&gt;0.05) remained non-significant.</p>", "<p>We further checked the effect of two experimental parameters on subjects' RT: (1) number of objects within the test set which represents the amount of relevancy load (##FIG##2##figure 3a##) and, (2) amount of difference between objects quantity in the sample and test sets which represents the amount of irrelevancy load (##FIG##2##figure 3b##). Since sum of relevant and irrelevant objects numbers should be equal to the sample objects number, we could not generate trials with all combinations of these two values (e. g. we could not generate a trial with 6 relevant and 4 irrelevant objects number since it needs 10 objects within the sample set and our sample set always contained less than 8 objects). Therefore we could not assess the effect of these two experimental parameters on subjects' RT by a single application of two-way ANOVA. Here, we used three different tests to assess the effect of experimental parameters on subjects' RT. First, we confined our analysis to a subset of trials in which all combinations of relevant and irrelevant objects number existed (i.e. trials in which relevant and irrelevant objects number was less than 4). In these trials, application of two-factor ANOVA (relevant and irrelevant objects number) yielded a significant effect of irrelevant objects number (F(2, 99) = 10.779, <italic>p</italic>&lt;0.001) without any significant effect of relevant objects number (F(2, 99) = 0.336, <italic>p</italic>&gt;0.05) or interaction between the two factors (F(4, 99) = 0.350, <italic>p</italic>&gt;0.05).</p>", "<p>Second, In order to use a larger subset of trials for assessing the effect of experimental parameters, we repeated the application of two-factor ANOVA but here we used trial types (WR trials vs. PR trials) and number of test objects as independent parameters. This test enabled us to assess whether number of test objects (i.e. selection load) was responsible for subjects' RT variation or objects elimination between sample and test sets. In this test, trials with either one or seven objects within test set were excluded since these trials were always PR and WR respectively and there was no alternative trial types for them. Application of two-way ANOVA (test objects number vs. trial type) yielded that subjects' RT was significantly longer during PR trials compared to WR trials (F(1,110) = 42.67, <italic>p</italic>&lt;0.001). While the effect of test objects number (F(4,110) = 0.08, <italic>p</italic>&gt;0.05) and the interaction between the two factors (F(4,110) = 1.07, <italic>p</italic>&gt;0.05) remained non-significant. Thus, eliminating irrelevant objects between sample and test sets and not the exact number of test objects affected subjects' RT.</p>", "<p>Third, we measured the predictability of subjects' RT on the basis of relevant (i.e. number of test objects), irrelevant objects (i.e. number of objects eliminated between sample and test) and also sample objects numbers by measuring the correlation between participants' RT and these three factors. Here we used all data trials rather than a subset of trials. Applying three separate Pearson tests of correlation indicated that participants' RT showed the highest correlation with the irrelevancy load (<italic>p</italic>&lt;0.001, r = 0.401). We also found correlation between the number of sample objects (<italic>p</italic>&lt;0.001, r = 0.215) and the number of test objects (<italic>p</italic>&lt;0.001, r = −0.204) with participants' RT but their correlation was not comparable to the correlation between number of irrelevant objects and participants' RT. Applying subsequent Pearson test for comparing correlation coefficients, we found that the difference between correlation coefficients was significant: participants' RT was significantly more correlated to the amount of difference between sample and test sets (<italic>p</italic>&lt;0.01).</p>", "<p>Showing that participants' RT increase as we eliminate more objects between sample and test sets also rules out the possibility that shifting attention between test objects number, to find the possible change location, is responsible for delayed participants' RT. Remembering the eliminated items is also unlikely to be responsible for such delay since in trials with numerous eliminated objects this process could be highly erroneous whereas participants' response accuracy did not show any impairment in PR trials. The only possible reason for the increased participants' RT seems to be WM re-organization by filtering of task irrelevant objects. Here, rather than remembering the eliminated objects, irrelevant objects are actively suppressed from WM. Using this mechanism enables participants to free memory and attentional resources, already used by irrelevant objects, for further decision making processes.</p>", "<title>Participants' ERP</title>", "<p>In previous section we showed that participants' RT increased as we increased the number of eliminated objects between sample and test sets (i.e. irrelevancy load) suggesting that participants used a filtering process to eliminate irrelevant objects from their WM. In order to understand neural correlates underlying this filtering process we assessed ERP brain activities of 12 human participants when they were performing the change detection task. As mentioned in the method section we only analyzed the ERP activities after test onset because filtering process started only when the irrelevant objects were revealed. Much of the results presented here concerns two ERP potentials observed in frontal (N150) and parietal (N200) cortices since they were found to be tightly correlated with different aspects of the filtering mechanism used to eliminate irrelevant objects.</p>", "<p>Finding neural correlates underlying filtering of irrelevant objects from WM we applied several two-factor ANOVAs (trial type and sample objects number) to ERP area under curve, recorded from frontal, parietal, occipital and temporal leads, across 800ms after the test stimuli onset (see <xref ref-type=\"sec\" rid=\"s2\">method</xref>). Using this method we were able to examine all time intervals without any bias toward predefined ERP components (e.g. P1, N1 or P3). This measure enabled us to find any possible effect of irrelevant objects elimination (i.e. trials type effect) and memory load (i.e. sample objects number) through ERP activities in various brain regions. Using this method we found that in both frontal (##FIG##3##figure 4a##) and parietal (##FIG##3##figure 4b##) leads, ERP activities in response to partial report (PR) trials, which needed irrelevancy elimination, dissociated from ERP activities in response to whole report (WR) trials, which did not require any irrelevancy elimination. However, the onset time of this dissociation varied largely between these two cortical areas. The first site that showed significantly dissociable ERP activities was frontal area (two-factor ANOVA (sample objects number vs. trials type); F(1,132) = 5.247, <italic>p</italic>&lt;0.05). In frontal leads this dissociation started from 152ms after the test onset but in parietal leads, the first significant dissociation (F(1,132) = 12.828, <italic>p</italic>&lt;0.01) occurred 208ms after test onset which was 56 later than the same effect found in frontal leads. In both sites, similar to participants' RT, WR trials showed earlier rise of ERP signal compared to PR trials (see ##FIG##3##figure 4##). Except for this rise time difference, in both sites the pattern of ERP signal (positive-negative-positive) remained intact during both types of trials.</p>", "<p>We also checked whether sample set size or the number of relevant objects, besides the trial type, affected the frontal and parietal ERP activities or not. We did not find any significant effect of number of sample objects or interaction (F(5,132)&lt;1, <italic>p</italic>&gt;0.05) between the sample objects number and trials type in the first 400ms of ERP activities. Another sets of one-factor ANOVAs (test object number) and also two-factor ANOVA (test object number and trial types) did not yield any effect of relevancy load (i.e. test object number) or interaction between relevancy load and trial types on frontal and parietal ERP activities during first 400ms time window after the test onset (F(4,110)&lt;1, <italic>p</italic>&gt;0.05). While, the effect of trial types on both frontal and parietal ERPs remained significant in the later test (F(1,110)&gt;5, <italic>p</italic>&lt;0.05) similar to our previous tests mentioned in previous paragraph. Thus, early ERP activities (first 400ms) were only sensitive to the trials type and not the sample set size or the number of relevant objects number.</p>", "<p>We further examined whether the shift of ERP latency between PR and WR trials, reported above, could be also observed during different PR trials with different number of irrelevant objects. We assessed the latency of ERP negative peak, adjacent to the area that the ERP in response to PR trials dissociated from ERP in response to WR trials (i.e. N150 and N200 in frontal and parietal cortices, respectively). Brain activity mapping in 130–170ms and 190–230ms intervals after test onset suggested that N150 and N200 activities were localized in frontal and parietal areas, respectively (##FIG##3##figure 4b, d##). Assessing peak latency of these negative ERP components we found that, similar to participants' RT, frontal N150 and parietal N200 peak latencies varied with the amount of irrelevancy load. But, in parietal leads, rather than being linearly correlated to the irrelevancy load, about 46% of latency variation was related to the difference between WR and the PR trials with the minimum amount of irrelevancy load and shortest RT (##FIG##4##Figure 5a, c##). In spite of the short range of parietal N200 latency variation (25ms), this characteristic of parietal N200 activity was highly similar to participants' RT because 50% of participants' RT variation was also related to the difference between WR and fastest PR trials (see ##FIG##2##Figure 3b##). Pearson test of correlation yielded a significant correlation between participants' RT and peak latency of parietal N200 activity (r = 0.830, <italic>p</italic>&lt;0.05). In contrast to parietal N200 latencies, frontal N150 latency better encoded the amount of irrelevancy load in each trial and varied linearly with the number of irrelevant objects (r = 0.847, <italic>p</italic>&lt;0.05). It also showed greater range of variation (55ms) between trials with different irrelevant object number (##FIG##4##Figure 5b, d##).</p>", "<p>We further ruled out any possibility that the difference between WR and PR related activities was due to base-line differences between two experimental conditions. As we mentioned before in the method section, base-line was corrected on the basis of 100ms pre-sample activities rather than pre-test activities. If baseline variation, before test stimulus onset, was responsible for the difference between PR and WR activities, we expected to see significant correlation between frontal and parietal ERP amplitudes and participants RT. Two separate applications of Pearson tests of correlation did not yield any significant correlation between the ERPs amplitude and participants RT (<italic>p</italic>&gt;0.05). It is noteworthy that base-line correction according to pre-test activities, rather than pre-sample activities, did not affect our findings. We avoided using this method of base-line correction since pre-test activities did not correctly represent the baseline and could be contaminated with those activities related to sample retention. Thus, frontal N150 and parietal N200 peak latencies, and not their peak amplitude, varied with irrelevancy load and pre-test base-line differences could not be responsible for this correlation.</p>", "<p>Since previous studies have indicated a contra-lateral organization for memory retention ##REF##15085132##[5]##–##UREF##0##[6]## and right hemisphere dominancy ##REF##16120797##[14]## for change detection we checked whether noise filtering process was also lateralized or not. We found that parietal N200 peak latency in right hemisphere seems to be better correlated to participants' RT (r = 0.930, <italic>p</italic>&lt;0.001) compared to the left hemisphere (r = 0.738, <italic>p</italic>&lt;0.05) (##FIG##5##Figure 6##). Such difference was not found when we compared the amount of correlation between participants' RT and parietal N200 peak latencies within ipsi-lateral (r = 0.902, <italic>p</italic>&lt;0.01) and contra-lateral (r = 0.881, <italic>p</italic>&lt;0.01) hemispheres. In contrast to parietal N200 activity, comparing the correlation between frontal N150 activity and participants' RT (or irrelevancy load) within right (r = 0.881, <italic>p</italic>&lt;0.05), left (r = 0.764, <italic>p</italic>&lt;0.05), ipsi-lateral (r = 0.788, <italic>p</italic>&lt;0.05) and contra-lateral (r = 0.799, <italic>p</italic>&lt;0.05) hemispheres did not show any noticeable differences.</p>", "<p>To check whether functional connectivity ##REF##9408041##[15]##–##REF##12377172##[18]## between modules generating ERP activities within frontal and parietal areas also varied with irrelevancy load, we assessed frontal N150 and parietal N200 latency differences. Interestingly, we found that frontal N150 and parietal N200 latency difference decreased as the number of irrelevant objects increased (Pearson correlation, r = −0.872, <italic>p</italic> = 0.01) indicating more strongly coupled activity in larger irrelevancy loads (##FIG##6##Figure 7##). We checked this relation in the left and right hemispheres separately and found that fronto-parietal ERP latency difference within the right hemisphere was better correlated with the amount of irrelevancy load (r = −0.906, <italic>p</italic>&lt;0.01) compared to the fronto-parietal ERP latency difference within the left hemisphere (r = −0.762, <italic>p</italic>&lt;0.05). This finding supports the notion that modules underlying ERP activities within right parietal area played a more crucial role in irrelevancy filtering process.</p>", "<p>One factor that could have contaminated our results was unbalanced number of trials between PR (77.8% of all trials) and WR trials (22.2% of all trials). To check whether our findings emanated from unbalanced trial number between PR and WR trials we repeated the above mentioned analysis for WR trials against those trials with only one object in the test rather than all of PR trials. Here, the number of trials was identical between PR and WR trials. We found again a significant effect of trial type in both sites (<italic>p</italic>&lt;0.05) and frontal activities showed earlier effect of trial type (t = 152ms after test onset) compared to the parietal activities (t = 212ms after test onset). The rest of analyses also showed the same tendency despite the fact that in this condition signal to noise ratio decreased to great extent.</p>" ]

[ "<title>Discussion</title>", "<p>In brief, here we have found that participants' RT was increased as we eliminated irrelevant objects between sample and test sets indicating that filtering mechanism rather than selection was used for eliminating irrelevant objects from WM. Similar to participants' RT, latency of ERP negativity in frontal (N150) and parietal (N200) cortices increased concomitant with the amount of irrelevancy load. In this condition, frontal N150 latency varied linearly with the number of irrelevant objects while parietal N200 latency was better correlated to participants' RT. This correlation was even stronger when we confined our analysis to right parietal activities, regardless of whether the memorized set was in ipsi or contra lateral hemisphere. We also found that the time difference between frontal N150 and parietal N200 latencies decreased as the irrelevancy load increased pointing to the notion that functional connectivity ##REF##9408041##[15]##–##REF##12377172##[18]## between modules underlying these activities could vary with the amount of irrelevancy load.</p>", "<p>Our behavioural findings were unlikely to be confounded by memory load (sample set size) or relevancy load (test set size) since we showed that participants' RT was significantly better correlated to the amount of irrelevancy load compared to memory or relevancy loads. Application of different ANOVAs to trials subsets with independent number of relevant and irrelevant objects also yielded that, our results was not confounded by dependency between relevancy and irrelevancy loads. It rules out the possibility that attentional shift between test objects or sample reconstruction is responsible for increased RT in PR trials. Rather it seems that detecting irrelevant objects and their suppression is responsible for delayed responses in PR report trials relative to WR trials.</p>", "<p>Similar to participants' RT, frontal and parietal potentials in first 400ms after the test onset were also insensitive to the memory and relevancy load variations. Sweeping all time windows in this interval by using a sliding window method, confirmed that the only parameter that influenced frontal N150 and parietal N200 peak latencies was the amount of irrelevancy load. Thus, participants' RT and brain activities in a visual change detection task are highly under the influence of irrelevancy load, leaving only participants response accuracy and late parietal potential (not reported here) to be affected by sample objects number (memory load).</p>", "<p>Parietal N200, reported in our study, differed from memory related activities reported by Vogel and Machizawa (2004). These authors' findings about memory related activities are confined to retention interval. These activities are measured by subtracting ipsi-lateral activities from the contra lateral ERPs within a fix interval (300–900ms after the sample onset) and are highly correlated to the number of objects within WM. But in our study, the parietal N200 was detected during decision making phase (after the test onset) and showed variable peak times that were correlated to subjects' RT. Furthermore, rather than being localized in contra lateral hemisphere relative to the memorized sets, parietal N200 was observed in both hemispheres with relatively stronger correlation between subjects' RT and right parietal N200 compared to the left parietal N200. Parietal N200 also varied from N2pc component which is mainly detected in visual search tasks whenever subjects attend to target object or its location ##REF##7964526##[19]##–##UREF##4##[20]##. Similar to memory related activities, this component is detected in contra lateral hemisphere relative to the attended hemifield without any correlation between its onset time and subjects' RT. High correlation between subjects RT and parietal N200 rules out the possibility that parietal N200 and N2pc component are generated by the same modules or represent the same phenomenon as described in our study.</p>", "<p>Imaging studies have shown that frontal activity is significantly higher in trials with successful elimination of distracter interference on participants' memory performance ##REF##11571223##[1]##–##REF##11953754##[2]##. We found that frontal N150 peak latency was better correlated with the number of irrelevant objects and not participants' RT and, presumably, attentional demand ##REF##11702537##[21]## of irrelevancy filtering. Our observation of the effect of irrelevancy load, besides the lack of any significant effect of sample or test sizes on frontal activities, indicates that module(s) underlying frontal activity is also a part of network which participates in irrelevancy filtering when the irrelevant objects are already stored in WM. However, being linearly correlated to the number of irrelevant objects, rather than participants' RT raises the possibility that frontal activity is related to irrelevant objects detection rather than their elimination. Contribution of frontal cortex in detection of irrelevant objects is previously indicated by fMRI imaging studies ##REF##12783960##[22]##–##UREF##5##[23]##. Interestingly, this frontal cortex contribution was not limited to one specific type of search suggesting a critical role for this brain area during different types of visual search tasks.</p>", "<p>Importantly, here we found that in addition to frontal N150, parietal N200 was tightly correlated with the task irrelevancy load indicating that modules underlying parietal N200 activity could be a part of the irrelevancy filtering network. At first glance this finding seems to be in contrast to the previous studies which have not found any evidence for parietal involvement in filtering of irrelevant objects ##REF##11571223##[1]##–##REF##18066057##[3]##. This inconsistency could be related to the difference between the natures of the tasks used in these studies. In these studies irrelevant objects are defined from the beginning of each trial and filtering role is confined to avoiding the irrelevant objects from entering WM. But in our study, all of the objects presented in the sample set could be relevant and had to be stored in WM and the irrelevancy of objects was revealed when the test set was presented. Thus, in our study, irrelevant objects needed to be excluded from WM and further decision related processes in a later stage of the task. Therefore, parietal N200 might be the neural correlate of the elimination of irrelevant objects from WM.</p>", "<p>Since in our study the number of relevant and irrelevant objects could not be manipulated completely independent from each other, it seems plausible that the observed increase in RTs and ERP component latencies could still be due to a prolonged search for the test objects in WM. This hypothesis would be consistent with the involvement of the parietal cortex in selection within working memory representations ##UREF##6##[24]##–##REF##15955482##[25]##. However, our behavioural results suggest that increasing the number of relevant objects could not be responsible for delayed subjects' RT. As we showed that there was not any significant effect of relevancy load in the subset of trials with completely independent number of relevant and irrelevant objects. Thus it is more likely that filtering of irrelevant objects rather than selection of relevant ones was responsible for our subjects delayed RTs. Our ERP results also expand previous findings by suggesting two different modules to be responsible for irrelevant object elimination from WM whose connectivity increased concomitant with irrelevancy load. Our finding that there was no significant effect of number of relevant objects on frontal and parietal ERPs strengthens the possibility that filtering and not selection is used for elimination of irrelevant objects from WM.</p>", "<p>In this experiment we also assessed the mechanism of interaction between modules underlying frontal N150 and parietal N200 ERP activities. Here we showed that frontal ERP potentials related to irrelevancy elimination, on average, starts 50ms earlier than the parietal potentials. The temporal lead of frontal activities relative to the parietal ones in demonstration of irrelevancy elimination effect raises the possibility that elimination related activities within parietal leads is initiated by modules underlying frontal N150. Findings from different lines of experiments support this notion. For example, neuroanatomical studies have shown that frontal afferent connections trigger inhibition mechanisms within temporal cortex, presumably initiating a distracter suppression process ##REF##15635060##[26]##–##UREF##7##[27]##. Others have shown that frontal cortex controls the impact of distracters when cortical sensory areas are exposed to noisy environments ##REF##8527724##[28]##–##UREF##8##[29]##. Since previous WM studies have shown that parietal cortex is responsible for retaining objects representations in WM ##REF##15085133##[4]##–##REF##15085132##[5]## the parietal N200 potential in our study could be related to processes responsible for suppressing the irrelevant objects representation from WM. This hypothesis rely on the idea that frontal control is not limited to sensory areas and it also covers memory related areas such as parietal cortex. Heavy reciprocal connections between these two cortical areas could provide the necessary neural substrate for such interaction ##REF##6480903##[30]##–##REF##2477406##[31]##. This idea was also supported by the enhanced connectivity, between modules underlying these ERP activities, with increasing irrelevancy load.</p>", "<p>Here we presented evidence that the difference between frontal N150 and parietal N200 peak latencies decreased by increasing the amount of irrelevancy load. This variation could be related to the enhanced functional connectivity between the modules underlying frontal N150 and parietal N200 activities as irrelevancy load was increased. The enhancement could result in faster rising of parietal N200 relative to frontal N150 activity and therefore shorter intervals between the peaks of these two potentials. This idea is supported by previous studies showing that increasing task difficulty or attentional demand could activate new functional connections between frontal and parietal cortices which facilitate frontal access to parietal WM resources ##REF##12377135##[17]##–##REF##12377172##[18]##. Similarly here, we showed that filtering processes highly relies on fronto-parietal ERP activities. Since filtering could be initiated and probably controlled by modules underlying frontal ERP activities, enhanced connectivity between modules underlying frontal and parietal potentials might be necessary in higher irrelevancy loads.</p>", "<p>Comparing left and right parietal activities showed that in general right parietal activity seems to play a more crucial role in the irrelevancy elimination. Parietal N200 activity within right hemisphere was better correlated with the participants' RT. Interestingly, it also demonstrated more systematic fronto-parietal connectivity enhancement when irrelevancy load increased which points to the notion that it is more under the influence of task demand. This lateralized effect is consistent with previous study by Beck et <italic>al.</italic> (2006) showing that, in a change detection task, stimulation of right parietal, but not the left, cortex results in longer participants' RTs compared to non-stimulated conditions. On the basis of these findings we suggest that modules underlying right parietal N200 could play a more crucial role in irrelevancy elimination despite the fact that previous studies ##REF##15085132##[5]##–##UREF##0##[6]## have shown that contra lateral parietal activities, and not only right hemisphere, are correlated to objects maintenance in WM. This inconsistency could be related to different neural mechanisms responsible for memory retention and irrelevancy elimination within parietal cortex.</p>", "<p>In conclusion, we showed a sequence of fronto-parietal ERP activities to be responsible for irrelevancy filtering when relevant and irrelevant information are stored in WM. Although we could not be sure about the location of modules underlying these ERP potentials, we showed great similarities between frontal and parietal activities reported by previous imaging studies and fronto-parietal ERPs found in our experiment. While imaging studies suffer from poor temporal resolution, and consequently miss the dynamics of neural activities, our results provide direct evidences that functional connectivity between modules underlying these fronto-parietal ERP activities was enhanced correlated with the irrelevancy load. This connectivity enhancement could facilitate the fronto-parietal interaction as the filtering demand increased.</p>" ]

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[ "<p>Analyzed the data: SN HE. Contributed reagents/materials/analysis tools: AM. Wrote the paper: SN AM HE.</p>", "<p>In a dynamic environment stimulus task relevancy could be altered through time and it is not always possible to dissociate relevant and irrelevant objects from the very first moment they come to our sight. In such conditions, subjects need to retain maximum possible information in their WM until it is clear which items should be eliminated from WM to free attention and memory resources. Here, we examined the neural basis of irrelevant information filtering from WM by recording human ERP during a visual change detection task in which the stimulus irrelevancy was revealed in a later stage of the task forcing the subjects to keep all of the information in WM until test object set was presented. Assessing subjects' behaviour we found that subjects' RT was highly correlated with the number of irrelevant objects and not the relevant one, pointing to the notion that filtering, and not selection, process was used to handle the distracting effect of irrelevant objects. In addition we found that frontal N150 and parietal N200 peak latencies increased systematically as the amount of irrelevancy load increased. Interestingly, the peak latency of parietal N200, and not frontal N150, better correlated with subjects' RT. The difference between frontal N150 and parietal N200 peak latencies varied with the amount of irrelevancy load suggesting that functional connectivity between modules underlying fronto-parietal potentials vary concomitant with the irrelevancy load. These findings suggest the existence of two neural modules, responsible for irrelevant objects elimination, whose activity latency and functional connectivity depend on the number of irrelevant object.</p>" ]

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[ "<fig id=\"pone-0003282-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g001</object-id><label>Figure 1</label><caption><title>Example of stimuli and experiment procedure.</title><p>(a) <italic>The sequence of cue and sample presentati</italic>on. Participants had to retain the sample <italic>objects in th</italic>e cued hemifield for 900ms during blank interval and then compare it with the test set to find the potential colour discrepancy. (b) An example of a test set corresponding to the presented sample in part a. Participants had to report any colour discrepancy between sample and test sets while they had to ignore any change due to object elimination. The first row corresponds to whole report trials while other rows demonstrate partial report trials with different number of objects within the test set. Left and right columns represent examples of match and non-match conditions, respectively.</p></caption></fig>", "<fig id=\"pone-0003282-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g002</object-id><label>Figure 2</label><caption><title>Participants' response accuracy (a) and RT (b) in different experimental conditions.</title><p>Participants' performance declined as the number of sample objects increased (<italic>p</italic>&lt;0.001) while participants' RT was mainly affected by the trial type (<italic>p</italic>&lt;0.001). In both graphs open and closed squares correspond to whole report and partial report trials respectively. Error bars represent one standard error.</p></caption></fig>", "<fig id=\"pone-0003282-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g003</object-id><label>Figure 3</label><caption><title>The relation between participants' RT and the number of (a) relevant and (b) irrelevant objects.</title><p>Pearson test of correlation showed that there was a significant correlation between participants' RT and the number of relevant (r = −0.204, <italic>p</italic>&lt;0.001) and irrelevant (r = 0.401, <italic>p</italic>&lt;0.001) objects. Importantly, subsequent Pearson test for comparing two correlation coefficients yielded that participants RT is significantly better correlated to irrelevant objects number (<italic>p</italic>&lt;0.01). Open and closed squares correspond to whole report and partial report trials, respectively. Error bars represent one standard error.</p></caption></fig>", "<fig id=\"pone-0003282-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g004</object-id><label>Figure 4</label><caption><title>Early (first 400ms) ERP activities recorded in frontal (a) and parietal (c) leads after test onset.</title><p>Activity mappings also demonstrate distribution of frontal (b) and parietal (d) activities during 130–150ms and 190–220ms after the test onset respectively. These timings correspond to averaged frontal N150 and parietal N200 peak latencies. Blue and red lines correspond to whole report (WR) and partial report (PR) trials, respectively. Pink bar in both graphs represents test stimulus presentation time. Gray areas depict the period with a significant difference between ERP area under curve of WR and PR trials (<italic>p</italic>&lt;0.05).</p></caption></fig>", "<fig id=\"pone-0003282-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g005</object-id><label>Figure 5</label><caption><title>The relation between the parietal N200 (a, c) and frontal N150 (b, d) peak latencies and the participants' RT.</title><p>Plots represent the ERP activities (left) and the corresponding scatter plots of their peak times (right). In both brain regions the peak latency of the ERP components increased with increasing the number of irrelevant objects and correlated with participants' RT. In scatter plots asterisks demonstrate values corresponding to whole report (WR) trials and squares depict values of partial report (PR) trials. The numbers close to each square show the amount of irrelevant load in each PR trial. Colour legends are the same for the scatter plots and the ERP plot. Lines in part c and d demonstrate the regression line.</p></caption></fig>", "<fig id=\"pone-0003282-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g006</object-id><label>Figure 6</label><caption><title>The relation between the parietal N200 peak latencies recorded in left (a) and right (b) hemispheres and the participants' RT.</title><p>Parietal N200 peak latency in right hemisphere showed better correlation to participants' RT. Each symbol depicts values related to whole report (asterisk) and partial report trials (square) and the lines regression line.</p></caption></fig>", "<fig id=\"pone-0003282-g007\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003282.g007</object-id><label>Figure 7</label><caption><title>The difference between peak latencies of frontal N150 and parietal N200.</title><p>The interval between the latency of these two ERP components decreased when the number of irrelevant objects increased (Pearson test of correlation, r = −0.872, <italic>p</italic> = 0.01). Symbols and lines represent are similar to ##FIG##5##figure 6##.</p></caption></fig>" ]

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[ "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>The authors have no support or funding to report.</p></fn></fn-group>" ]

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[ "<p>G.P.S. and L.D.B.E. contributed equally to this work.</p>", "<p>Present address: G. P. Stafford, Department of Oral Pathology, School of Clinical Dentistry, University of Sheffield, Claremont Crescent, Sheffield S10 2TA, UK.</p>", "<p>The bacterial flagellum assembles in a strict order, with structural subunits delivered to the growing flagellum by a type III export pathway. Early rod-and-hook subunits are exported before completion of the hook, at which point a subunit-specificity switch allows export of late filament subunits. This implies that in bacteria with multiple flagella at different stages of assembly, each export pathway can discriminate and sort unchaperoned early and chaperoned late subunits. To establish whether subunit sorting is distinct from subunit transition from the cytosol to the membrane, in particular docking at the membrane-associated FliI ATPase, the pathway was manipulated <italic>in vivo</italic>. When ATP hydrolysis by the FliI ATPase was disabled and when the pathway was locked into an early export state, both unchaperoned early and chaperoned late subunits stalled and accumulated at the inner membrane. Furthermore, a chaperone that attenuates late subunit export by stalling when docked at the wild-type ATPase also stalled at the ATPase in an early-locked pathway and inhibited export of early subunits in both native and early-locked pathways. These data indicate that the pathways for early and late subunits converge at the FliI ATPase, independent of ATP hydrolysis, before a distinct, separable sorting step. To ascertain the likely signals for sorting, the export of recombinant subunits was assayed. Late filament subunits unable to bind their chaperones were still sorted accurately, but chaperoned late subunits were directed through an early-locked pathway when fused to early subunit N-terminal export signal regions. Furthermore, while an early subunit signal directed export of a heterologous type III export substrate through both native and early-locked pathways, a late subunit signal only directed export via native pathways. These data suggest that subunits are distinguished not by late chaperones but by N-terminal export signals of the subunits themselves.</p>", "<title>Keywords</title>", "<p>Edited by I. B. Holland</p>" ]

[ "<p>Bacterial motility is commonly conferred by cell surface flagella, comprising a long helical filament that is connected by a flexible hook to a central rod in the cell envelope basal body that also houses the flagellar motor.<xref rid=\"bib1 bib2 bib3\" ref-type=\"bibr\">^1–3</xref> Flagella substructures are assembled in strict sequence, with formation of the basal body and rod structures preceding polymerisation of the hook and, finally, the filament subunits.<xref rid=\"bib1 bib2 bib3\" ref-type=\"bibr\">^1–3</xref> The order of assembly is achieved by sequential expression of the gene hierarchy##REF##2404955##4##^,##REF##14550943##5## and by a subunit-specificity switch in the flagellar type III export pathway. This ensures that, prior to hook completion, only ‘early’ rod-and-hook subunits are exported,##REF##12753195##6##^,##REF##12670972##7## while those forming the later distal substructures of the filament, filament cap and hook–filament junction are not. The outline of the subunit-specificity switching mechanism is evident. When the hook reaches its mature length, a signal is transmitted by the hook length control protein FliK to the integral membrane export component FlhB, triggering a switch in subunit specificity to allow export of late subunits.<xref rid=\"bib6 bib7 bib8 bib9\" ref-type=\"bibr\">^6–9</xref> Nevertheless, peritrichously flagellated bacteria such as <italic>Escherichia coli</italic> and <italic>Salmonella</italic> have multiple flagella at different stages of assembly,##REF##9893020##10## so an individual export pathway potentially encounters both unchaperoned early and chaperoned late subunits from the cytosol. This implies that early and late subunits are discriminated and sorted by the pathway.</p>", "<p>We have previously shown that late filament subunits are piloted by their chaperones to dock at the membrane-associated FliI ATPase.##REF##15001708##11## Here we manipulate the export pathway to determine whether subunit docking and sorting are separable and sequential events. We also assess the relative influence of subunit export signals and bound export chaperones in discriminating early and late subunits.</p>", "<title>Stalling of early and late subunits at the membrane in an early-locked pathway attenuated in ATP hydrolysis</title>", "<p>To examine the relationship between the proposed sorting step and subunit transition from the cytosol to the inner membrane, we aimed to generate stalled export intermediates of both early and late subunits. Our previous work had exploited export-defective chaperones to stall late cognate (hook–filament junction) subunits, which they piloted to and docked at the membrane-associated FliI ATPase.##REF##15001708##11## To similarly interrupt the movement of unchaperoned early subunits, we attenuated FliI ATP hydrolysis, which, as in other export systems,##REF##1825804##12##^,##REF##9822594##13## is envisaged to drive unfolding and export of substrates engaged at the membrane machinery,##REF##16208377##14## in this case prior to assembly into the growing flagellum. After creating single-amino-acid substitutions in the active site region, one variant was chosen for full study, variant FliI_E211A, which is mutated immediately adjacent to the Walker A motif. ATP was still bound by FliI_E211A [<italic>K</italic>_m = 0.2 mM, compared to wild type (1 mM); triplicate assays ± 15%] but was poorly hydrolysed [<italic>V</italic>_max = 0.22 μmol min^− 1mg^− 1 compared to wild type (2.30)] in a coupled assay in the presence of phospholipids.##REF##17088562##15##</p>", "<p>Export supported by FliI_E211A was assayed in a <italic>fliIflgKflgM</italic> triple mutant (by our previously published method##REF##15001708##11##). The resulting pathway is not subject to negative feedback (via the FlgM anti-sigma factor) arising from the disabling of the export apparatus (<italic>fliI</italic> ATPase), and late and early subunits are thus constitutively synthesized. When wild-type <italic>fliI</italic> is expressed in <italic>trans</italic>, exported late subunits such as filament subunit FliC accumulate in the culture supernatant as a result of the <italic>flgK</italic> hook–junction lesion that precludes filament polymerisation (##FIG##1##Fig. 1##a). Export of FliC was severely attenuated by substitution of FliI by FliI_E211A. Like the wild-type ATPase, FliI_E211A assembled into hexamers <italic>in vitro</italic> in the presence of phospholipids and the short-arm crosslinker disuccinimidylglutamate (<xref rid=\"app1\" ref-type=\"sec\">Supplementary Data</xref>), and cell fractionation and sucrose gradient ultracentrifugation##REF##15001708##11##^,##REF##12054792##16## showed that, <italic>in vivo</italic>, it localised normally to the inner membrane (##FIG##1##Fig. 1##b and c).</p>", "<p>The <italic>fliIflgKflgM</italic> pathway containing the nonhydrolysing FliI_E211A is locked into an early export state.<xref rid=\"bib6 bib7 bib11\" ref-type=\"bibr\">^6,7,11</xref>\n<italic>In vivo</italic> localisation of nonexported subunits in this pathway revealed (##FIG##1##Fig. 1##b and c) that the unchaperoned early subunit FliK##REF##10564473##17## accumulated as a membrane-associated intermediate in a FliI-dependent manner. This indicates that, like chaperoned late subunits, unchaperoned early subunits can be stalled at the membrane, putatively docked at the FliI ATPase. If late subunits are sorted before they dock at FliI, then late subunit–chaperone complexes should not accumulate at the membrane in the FliI_E211A early-locked <italic>fliIflgKflgM</italic> pathway, but they should accumulate if sorting occurs after late subunit docking. The <italic>in vivo</italic> fractionation and sucrose gradients of <italic>fliIflgKflgM</italic> cells expressing FliI_E211A (##FIG##1##Fig. 1##b and c) revealed that the late subunits FliC and FlgL and the FlgN chaperone##REF##11169117##18##^,##REF##10320579##19## accumulate, like early FliK, at the inner membrane.</p>", "<p>The data indicate that FliI enzymatic activity is not required for <italic>in vivo</italic> docking of late subunits at the membrane ATPase (compatible with <italic>in vitro</italic> interaction of virulence chaperones with a catalytically inactive type III export ATPase##REF##16208377##14##), and they indicate that this is also true for unchaperoned early subunits. Furthermore, they argue that sorting is separable from docking at FliI, occurring most likely afterwards, and that progression to sorting requires ATP hydrolysis by FliI.</p>", "<title>Early and late subunits converge at the ATPase prior to sorting</title>", "<p>We have described a late FlgN chaperone variant (now called FlgN^rel, as it putatively fails to release from the ATPase) that attenuates export of cognate and noncognate late subunits when expressed in <italic>trans</italic> in wild-type pathways, with chaperoned subunits trapped after docking at the membrane FliI, accumulating chaperone–subunit–ATPase intermediates.##REF##15001708##11## We used this dominant-negative chaperone variant to extend indications that chaperoned late subunits engage the wild-type FliI ATPase before sorting, asking whether FlgN^rel-stalled membrane intermediates accumulate in an early export-locked pathway and attenuate early subunit export.</p>", "<p>Cell fractionation was performed to establish FlgN^rel localisation and putative interaction with the ATPase in the actively secreting early-locked pathway lacking the hook protein FlgE and the wild-type FlgN chaperone (exp^E; Δ<italic>flgE</italic>Δ<italic>flgN</italic>), and also in native pathways of Δ<italic>flgN</italic> control (exp^E + L) that export early subunits and then late subunits after completion of the hook substructure. The results (##FIG##2##Fig. 2##a) show that FlgN^rel localised to the membrane in a FliI-dependent manner in both pathways. When His-FlgN^rel was used as bait in <italic>in vivo</italic> affinity chromatography (##FIG##2##Fig. 2##b), cognate subunit FlgK, FliI and its regulator FliH were all copurified, showing that ATPase–chaperone–subunit intermediate complexes were formed in early-locked pathways analogous to native pathways.</p>", "<p>These findings support the earlier indication that both unchaperoned early and chaperoned late subunits engage the export ATPase before they are sorted for export or exclusion, and furthermore suggest that the export pathways for the two classes of subunit converge at the ATPase. To substantiate the idea of convergence, we again used the docked but stalled late FlgN^rel to assess whether it could attenuate export of not only chaperoned late subunits but also early subunits in native export pathways of Δ<italic>flgN</italic>. The results (##FIG##3##Fig. 3##) confirm that export of cognate (FlgK) and noncognate (FliC) chaperoned late subunits is reduced by 5- to 10-fold and reveal a comparable attenuation in the export of unchaperoned early subunits FlgD and FliK. Significantly, they show that FlgN^rel caused a comparable reduction of FlgD and FliK export in an early export-locked (Δ<italic>flgE</italic>Δ<italic>flgN</italic>; exp^E) pathway (##FIG##3##Fig. 3##). These FlgN^rel experiments strengthen the indication from those using FliI_E211A, that is, that the pathways for unchaperoned early and chaperoned late subunits converge at the ATPase before progressing (dependent on ATP hydrolysis) to sorting.</p>", "<title>Are subunits discriminated by their own signals or by late chaperones?</title>", "<p>An obvious difference between early and late subunits is that only late subunits are bound by export chaperones, acting as cytosolic bodyguards and pilots for docking at the membrane export ATPase.##REF##15001708##11##^,##REF##16359332##20##^,##REF##14756788##21## Chaperones could act as flagellar sorting signals, labelling subunits for rejection during the early stages of flagella assembly. This is especially so as in a virulence type III secretion system, bound chaperones (e.g., <italic>Salmonella</italic> InvB chaperone of the SopE effector), are reported to form part of the secretion signal, preventing promiscuous export through the flagellar pathway.<xref rid=\"bib20 bib21\" ref-type=\"bibr\">^20,21</xref> If this were true, late subunits from which C-terminal polymerisation and chaperone-binding domains are deleted might be exported as early subunits. To test this possibility, we assessed the export of recombinant FliC and FlgK late subunit variants lacking their chaperone-binding domains (FlgK_Δchap, and FliC_Δchap)##REF##12753195##6##^,##REF##11169117##18##^,##REF##11327763##22## and found (##FIG##4##Fig. 4##a) that, although these variants were exported in native pathways that export both early and late subunits (exp^E + L), neither variant was exported in an early-locked pathway (exp^E; i.e., the unchaperoned subunits were still faithfully sorted by the export pathway). We then assessed the export of recombinant subunits in which the N-terminal export signal residues 1–100 (FlgD_sig) were fused to truncated late FliC (FliC_Δsig) or FlgK (FlgK_Δsig) lacking their N-terminal export signals##REF##16897036##23## but still able to bind their respective chaperones. Like wild-type FlgD, these hybrid subunits were exported by both early export-locked (exp^E) and native export (exp^E + L) pathways (##FIG##4##Fig. 4##b), substantiating the view that chaperones are not a sorting signal to preclude late subunit export before hook completion. The marginal (twofold) reduction in the export of early subunits (FlgD, FlgD_sig–FliC_Δsig, FlgD_sig–FlgK_Δsig) in native pathways (##FIG##4##Fig. 4##b; exp^E + L), compared to the early export-locked strain (exp^E), possibly indicates that once an export apparatus has switched specificity, it no longer accepts early subunits for export (a view compatible with observations in <italic>Yersinia</italic> T3SS indicating that once pathways have switched specificity to late effectors, they do not export early substrates##REF##17050689##24##).</p>", "<p>These assays also suggest that the subunit N-terminal 100 residues contain both export and sorting signals. To confirm this, we constructed recombinant subunits comprising the N-terminal 100 residues of the late subunit FliC (FliC_sig) or FlgK (FlgK_sig), or the early subunit FlgD (FlgD_sig) fused to the catalytic phosphatase domain of the <italic>Salmonella</italic> SPI-1 SptP effector (residues 161–543; SptP_phos)##REF##16208377##14## and assayed export in early export-locked and wild-type equivalent pathways. As expected, FlgD_sig–SptP_phos fusion was exported in both early-locked (exp^E) and wild-type (exp^L + E) pathways (##FIG##4##Fig. 4##c). In contrast, the FliC_sig–SptP_phos and FlgK_sig–SptP_phos fusion proteins were exported only in the wild-type pathway (exp^E + L) and not by the early export-locked pathway (exp^E) (##FIG##4##Fig. 4##c). This supports our view that the N-terminal regions contain sufficient information to determine sorting as a late subunit. While there is primary sequence similarity among the N-terminal regions of rod subunits, there seems to be little identity between these and other early subunits##REF##2129540##25##^,##REF##2193164##26## and no obvious identity distinguishing the N-terminal regions of late proteins. This suggests that subunit sorting might rely on the recognition of structural features specific to each subunit class.</p>" ]

[ "<title>Supplementary Data</title>", "<p></p>", "<title>Acknowledgements</title>", "<p>We thank Vasillis Koronakis for SptP antisera. This work was supported by a Wellcome Trust Programme grant (C.H.) and a Biotechnology and Biological Sciences Research Council studentship (P.D.).</p>" ]

[ "<fig id=\"d32e913\" position=\"anchor\"><label>Supplementary Fig. 1</label><caption><p><italic>In vitro</italic> oligomerisation of FliI_E211A ATPase (FliI^EA). Purified variant FliI ATPase (0.5 μM) was incubated in cross-linking buffer (20 mM Hepes pH 8.0, 0.1 M NaCl, 0.1 mM ethylenediaminetetraacetic acid and 1 mM DTT) in the presence of <italic>E. coli</italic> liposomes, with (+) or without (−) 0.1 mM disuccinimidylglutamate). Aliquots were precipitated (10% trichloroacetic acid), subjected to electrophoresis through an SDS 4–10% acrylamide gradient gel and Coomassie stained.</p></caption></fig>", "<fig id=\"fig1\"><label>Fig. 1</label><caption><p>Membrane accumulation of early and late subunits in the pathway attenuated by enzymatically impaired FliI ATPase. (a) FliC export, assayed by immunoblotting, filtered supernatants from midexponential Luria broth (LB) cultures (<italic>A</italic>₆₀₀ = 1.0) of Δ<italic>fliIflgKflgM</italic> cells (made by P22 transduction combined with the method of Datsenko and Wanner##REF##10829079##27##) expressing in <italic>trans</italic> either wild-type FliI (FliI^WT) or variant FliI_E211A (FliI^EA) from pBAD33 (0.1% arabinose). A Δ<italic>fliIflgKflgM</italic> strain containing empty pBAD33 was shown to be nonmotile and attenuated in the export of early FliK subunit and late FliC subunit (data not shown). (b) <italic>Salmonella fliIflgKflgM</italic> cultures expressing wild-type FliI^WT or variant FliI^EA separated into membrane (m) and cytoplasmic (c) fractions.##REF##15001708##11##^,##REF##12054792##16## Immunoblotted for FliI ATPase, FlgN chaperone and subunits. (c) Separation of the membrane fractions into outer membrane (OMP; Coomassie stained) and inner membrane (NADH oxidase marker) by sucrose gradient ultracentrifugation (0.8–2.0 M##REF##15001708##11##^,##REF##12054792##16## top and bottom of the gradient indicated). Proteins immunoblotted using antisera described above.</p></caption></fig>", "<fig id=\"fig2\"><label>Fig. 2</label><caption><p>Membrane accumulation of early and late subunits in an early-locked pathway attenuated by stalling docked chaperone FlgN^rel. (a) Localisation of FlgN^rel (expressed in <italic>trans</italic> by 0.01% arabinose) in the whole cell (wc), membrane (m) and cytoplasm (c)##REF##15001708##11##^,##REF##17088562##15## of the Δ<italic>flgN</italic> and Δ<italic>fliI</italic> pathways, and in the isogenic (exp^E) early-locked pathways Δ<italic>flgEN</italic> and Δ<italic>flgEfliI</italic>. (b) Affinity copurification of stalled docking complexes by His–FlgN^rel bait (+)##REF##15001708##11## from native Δ<italic>flgN</italic> and early-locked (exp^E; Δ<italic>flgEN</italic>) pathways [(−) vector-only controls]. Cell extracts were incubated with Ni–NTA resin [20 mM tris(hydroxymethyl)aminomethane–HCl pH 8.0, 300 mM NaCl and 5 mM imidazole] before washing (10 mM imidazole) and elution in SDS sample buffer. FlgN chaperone, FlgK cognate subunit and ATPase complex components FliI and FliH were detected by immunoblotting.</p></caption></fig>", "<fig id=\"fig3\"><label>Fig. 3</label><caption><p>Attenuation of early and late subunits export by stalling FlgN^rel. Export of subunits by native Δ<italic>fliD</italic> (exp^E + L) and early-locked Δ<italic>flgE</italic> (exp^E) pathways containing FlgN^rel [expressed using 0.01% arabinose; (−) vector-only controls], assayed following precipitation from supernatants (snt) of midexponential LB cultures (wc, whole culture) by SDS-PAGE and immunoblotting for early (FliK and FlgD) and late (FliC and FlgK) subunits.</p></caption></fig>", "<fig id=\"fig4\"><label>Fig. 4</label><caption><p>Influence of subunit domains on sorting. (a) Export of chaperoned late subunits (FlgK and FliC) and their variants that cannot bind chaperone (FlgK_Δchap and FliC_Δchap) in export pathways that are either early locked (exp^E; Δ<italic>flgEKL</italic>##REF##10829079##27## Δ<italic>flgE</italic>, SJW1353 acquired from Ohnishi <italic>et al.</italic>##REF##8157595##28##) or native (exp^E + L; Δ<italic>flgKL</italic> or Δ<italic>fliC</italic>). Proteins from whole cells (wc) and supernatants (snt) were immunoblotted with FlgK or FliC antisera. (b) Export of FlgD and recombinant late subunits FlgK_Δsig and FliC_Δsig lacking amino acids 1–100 fused to residues 1–100 of early FlgD in export pathways (described above) that are either early locked (exp^E) or native (exp^E + L). Proteins from whole cells (wc) and supernatants (snt) were immunoblotted with FlgD, FlgK or FliC antisera. (c) Export of recombinant fusion proteins comprising putative early or late subunit N-terminal signal regions (FlgD_sig, FlgK_sig and FliC_sig; amino acids 1–100) fused to the signal-less SptP tyrosine phosphatase domain (SptP_phos; residues 161–543) in early locked (exp^E; Δ<italic>flgE</italic>) and native (exp^E + L; Δ<italic>fliC</italic>) pathways. Proteins were immunoblotted with SptP antisera (V. Koronakis, University of Cambridge). Genes encoding variant wild-type and variant FliC, FlgK, FlgD and SptP were amplified by overlap extension PCR using <italic>Salmonella</italic> chromosomal DNA as template. PCR products were inserted into XbaI–HindIII restriction sites of the pBAD18 expression vector. Recombinant genes were expressed (LB, 0.01% arabinose) and proteins were assayed as in ##FIG##2##Fig. 2##b. Control experiments performed in isogenic Δ<italic>fliI</italic> and Δ<italic>flgEfliI</italic> strains (created by P22 transduction of Δ<italic>fliI</italic> allele into Δ<italic>flgE</italic>) showed that none of the recombinant proteins was exported (data not shown).</p></caption></fig>" ]

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