Hirudo medicinalis, has been used in plastic and reconstructive surgery, to relieve venous congestion and to improve the microrevascularization of flaps. In many countries, wild leeches are still provided from local markets and utilised with antibiotic prophylaxies. In this research, results of identification of bacteria in the transport fluid is reported, oral and intestinal floras and the antibiograms of the identified microorganisms are investigated. Also, to avoid possible infections, the ability of hypochloric acid, a disinfectant, to suppress the relevant microorganisms without changing the life style and behavior of leeches in terms of sucking function, is investigated.Medicinal leech, ppm concentrations in different groups of 25 leeches. Finally, 20 leeches were applied atraumatically to the bleeding areas of rats, the duration of suction was determined and compared statistically between the leeches treated and not treated with hypochloric acid solution.Bacterial identifications and antibiograms of oral and intestinal flora and transport medium were performed for 10 leeches. The optimum concentration of hypochloric acid which eliminated microorganisms without affecting the viability and sucking function of the leeches were determined by dilution of hypochloric acid to 100, 50, 25, 12.5, 6.25 Aeromonas hydrophilia was the most commonly identified microorganism and found to be resistant to first generation cephalosporins, frequently used in prophylaxis at surgical wards. In the next stages of the study, the leeches were subjected to a series of diluted hypochloric acid solutions. Although disinfection of the transport material and suppression of the oral flora of hirudo medicinalis were successful in 100, 50, 25, 12.5, 6.25 ppm concentrations; 12.5 ppm solution was the greatest concentration in which hirudo medicinalis could survive and sucking function was not affected significantly.External decontamination of wild leeches with 12.5 ppm hypochloric acid enables bacterial suppression without causing negative effects on leech sucking function and life. Hirudo medicinalis, has been used with increasing frequency during the past few decades for salvage of venous compromised pedicled flaps, microvascular free-tissue transfers and replantations. Although the therapeutic use of leeches in medicine dates back 50 BC; for centuries they were collected from various water supplies and utilised under septic conditions with the risk of wound infection and infestation. The supply of leeches was modernized by medicinal leech farm set up in the 1970s [The medicinal leech, Aeromonas is the most common microorganism in leech infections and may cause a wide spectrum of deseases such as cellulitis, ocular infections, arthritis, myocarditis, peritonitis, meningitis, bacteremia and sepsis [Today, leech therapy is indicated in plastic and reconstructive surgery, to relieve venous congestion and to improve the microrevascularization of flaps Fig ,2,3,4 ord sepsis . In manyIn the first stage of the study, bacterial content of the transport fluid of leeches that were bought from local markets were studied, also oral and intestinal flora cultures and antibiograms of the identified microorganisms were performed subsequently.In the next stages hypochloric acid, a disinfectant, was tested on animals that were not bred in specific laboratories, to suppress the relevant microorganisms in order to avoid possible infections, without changing the life style and behavior of leeches in terms of sucking function.This study was approved by the Animal Care and Ethics Committee of our institution.A. hydro/caviae and A. sobria for definite identification. Since bacterial growth was observed in specimens taken from oral and intestinal flora or transport fluid of all animals except one ; antibiograms for aeromonas isolates were performed.Ten leeches were obtained with their 100 cc original water from different stores. Their sizes varied between 6–10 cm in length and 0, 5 – 1, 5 cm in width. They were transported in sterile boxes immersed in the water which the animals were kept at the market. For 2 days they were observed at room temperature. Specimens were taken and smears from transport fluids were prepared. All leeches were held with sterile gloves and prepared in sterile conditions. Specimens were obtained from their mouth  with the help of sterile cotton – swab. After traction was applied between the mouth and posterior muscular organ, the animal was cleaned with alcoholic solution of povidone-iodine, as described by Hokelek et al. [ppm solutions were prepared by adding apropriate amounts of hypochloric acid into the transport fluids of 25 leeches seperately with five animals in each concentration group. After 10 minutes of contact with hypochloric acid solutions at 20°C, smears were taken from mouths and transport fluids of each leech under sterile conditions with cotton-swabs. Cotton-swabs were put into a neutralizing media (lecithinized agar media) because they could also contain disinfectant fluid which would prevent microorganism reproduction. Then the neutralized smears were planted into MacConkey and blood agar [ppm solutions lost their muscular activity and died ;the leeches which were treated with 12.5 and 6.25 ppm hypochloric acid solutions were alive. Bacterial growth was not observed in either concentration group for the specimens taken from oral flora and transport fluid, however bacterial cultures were positive for in specimens taken from the intestine or crop. Of these microorganisms, bacterial colonies for Aeromonas spp were counted. To compare the changes in the number of Aeromonas colonies in leech intestinal flora induced with the application of hypochloric acid, the intestine of five new leeches were exposed as described for Stage 1. Based on the findings of Stage 2, a concentration of 12.5 ppm was chosen for Stage 3 studies.30 leeches from different stores were obtained and transported in different sterile boxes with their 100 cc original water as in stage 1. On the following day, samples were taken from transport fluids and oral region and planted in MacConkey and blood agar. Twenty five leeches, which had bacterial growth in either oral flora or transport water were used for the second stage. 100, 50, 25, 12.5, 6.25 ood agar . The leeppm hypochloric acid solution was prepared with the transport fluids. After waiting for 10 min at 20°C temperature, smears were taken from the oral floras and fluids again. All leeches were put into boxes containing distilled water and watched for survival and blood suction function on sedated rats (ketamine 30 mg/kg and xylazine 10 mg/kg). After shaving dorsal region of 20 rats, 2 mm long skin incissions were done in order to produce bleeding. The leeches were applied to the bleeding areas atraumatically and the duration of suction was determined and compared statistically (ANOVA) between the leeches treated and not treated with hypochloric acid solution. Statistical significance was presumed at p < 0.05.20 leeches were obtained with their 100 cc original water from different stores and equally divided into two groups. One group was treated with hypochloric acid while the others had no treatment at all. After taking specimens from the transport fluids and oral floras, for 10 leeches 12.5 aeromonas species, peudomonas species, acinetobacter species, sphingobacterium species) was observed. In one media, Gram (+) growth was seen :meticilline susceptible coagulase (-) staphylococcus. Dominant microorganisms were aeromonas species, Table Aeromonas spp. was investigated by using conventional methods and a commercial kit ID 32 GN ATB System (BioMérieux). In this study, with this system the results were obtained as A. hydro/caviae, A. sobria, A. salmonicidia and A. spp, with the latter nomenclature designating all other Aeromonas species. The most commonly encountered agents, A. hydro/caviae and A. sobria underwent further biochemical studies, as suggested by Abbott, et al.[A. hydro/caviae was in fact A. hydrophila, and A. sobria was in fact A. veronii biovar sobria , intestinal flora in 9 animals (90%) and transport media in 5 animals (50%). In one leech, no growth was observed in either oral, intestinal and transport fluid cultures. In all culture media, 4 different gram (-) bacterial growth  however the difference between control group and 6.25 ppm group was not significant.Fluid and oral flora cultures that were prepared before hypochloric acid application showed multiple microorganism growth, as it was in stage 1. After adding hypochloric acid there was no growth in transport fluid and oral media cultures in either concentration so that no identification and antibiogram study could be performed. After 10 minutes in hypochloric acid solution, leeches were taken to sterile containers which contained distilled water. The muscle activity of all leeches that had been treated in 100 All the leeches survived while hyperactivity followed by hypoactivity was seen in the group of leeches treated with hypochloric acid. In this group, two of the leeches never made suction but the other eight leeches sucked the bleeding area for 5–16 min (mean 12.2 ± 3.8). Non hypochloric acid treated group sucked for 9–22 min (mean 15.5 ± 4.4) and the difference between two groups was not significant (p > 0.05, F = 2.6, ANOVA).Aeromonas spp) were observed. After hypochloric acid application no growth was observed in any of the specimens taken from animals, therefore no identifications or antibiograms could be performed.In 70 % of cultures that were prepared from transport fluids of leeches and in 50% of cultures that were prepared from oral floras of leeches before hypochloric acid application, bacterial growth  rods, Acinetobacter Iwofii and A sobria were isolated. All of the isolates were sensitive to ciprofloxacine, cefotaxime, ceftazidime, gentamycine and trimetoprim-sulfamethoxasole [Aeromonas hydrophylia colonies which produced inducable betalactamase. In case of infections with these species, beta lactam antibiotics except carbapenems should not be used.In countries, where special farms for medicinal leeches do not exist, animals obtained from markets should be studied for their floras and antibiotic susceptibilities. Eroğlu et al. investigated the floras and the antibiotic susceptibility of leeches in Black Sea region. Most commonly hoxasole . LikewisIn addition, we aimed to supress possible bacterial contamination of the transport media and oral floras of leeches but not intestinal flora because of the endosymbiotic relationship of the aeromonas and leech, with hypochloric acid solutions at disinfectant concentrations that does not affect the life style of leeches.Aeromonas spp. are sensitive for 12 hours but could not eradicate aeromonas from the intestines [Investigators have attempted to disinfect the guts of leeches before they are placed on patients by placing the ectoparasites in % 0.02 chlorhexidine for 15 seconds or in antibiotic solutions (tetracycline or cefoperazone solutions) for 12 hours, but these attempts were unsuccessful [testines .We preferred hypochloric acid which is an ideal disinfectant and has a wide antibacterial spectrum for desired purpose. Chlorine in the form of hypochloric acid exhibits rapid microbicidal activity by inhibiting of key enzymatic reactions within the cell and eventual protein denaturation. It has a rapid bactericidal effect and can dissolve in water. However, it has some disadvantages as it irritates mucosal membranes, has interactions with some chemicals and metals .ppm concentrations on pseudomonas was achieved within 10 min exposure [Aeromonas spp. cause similar nosocomial infections and has similar antibiotic susceptibility with pseudomonas spp. Therefore, in the second stage of our study, beginning with 100 ppm, we applied decreasing concentrations of hypochloric acid in transportation fluids, observed bacterial growth by taking specimens from transport material and oral flora of hirudo medicinalis. We tried to find the dilution ratio that was closest to 100 ppm, suppresing oral flora and transfer liquid and also allowing the leech to survive with normal function. As a result of the second stage of the study we found out that concentration to be 12.5 ppm.It was showed that bactericidal effect of hypochloric acid of 100 exposure . AeromonIn the third stage, we observed that mean sucking duration of the hypochloric acid treated group was shorter than the other group but the difference was not significant (12.2 min & 15.5 min respectively). However hypochloric acid had successful disinfection effect for transport liquid and oral flora. In our opinion, such a decrease in duration of sucking function can be preferable to infection possibility. Since leeches are much cheaper than antibiotics, it is logical to use them once, after treating with hypochloric acid, and never utilise them again.We do not advise to use "full-up" leeches over and over again by putting them in hypertonic solutions to force them vomitting because if they regurgitate, the intestinal flora can readly contaminate the environment where the leeches are kept and cause infection eventually. Although the oral flora and transport enviroment studies do not really address the problem since excretory contamination is probably the major factor in leech infections ; we believe that to take any measure in order to decrease the infection risk during utilisation of ordinary leeches is valuable.ppm hypochloric acid solution with transport fluids of ordinary leeches obtained from the local market for 10 minutes and then taking the leeches gently from water before application can prevent possible infections caused by contamination from leech oral flora and transport medium.We can comment that preparation of 12.5 None declared.AA and SVK participated in design of the study, involved in the dissections of leeches. EH and ST participated in the design of the study and writing of the manuscript.HN, NG and BO involved in the antibiogram tests. SNK participated in design of the study.The pre-publication history for this paper can be accessed here:


Stevie Wonder and Ray Charles are often cited as evidence that blindness confers superior musical ability. Wonder lost his sight after an incubator-related oxygen overdose during infancy; Charles lost his as a boy to glaucoma. It's impossible to know whether sight would have compromised their success, but many gifted musicians, from Jose Feliciano to Rahsaan Roland Kirk, lost their sight at an early age.A number of human studies show that blind persons perform nonvisual tasks better than those with sight. Neuroimaging studies of blind persons performing nonvisual tasks, including hearing, show activity in brain areas normally associated with vision. But much remains to be learned about the nature and extent of this phenomenon: how these “visual areas” are used, the mechanisms that generate individual differences , and the neural processes that underlie it.The task of localizing sound—which requires integrating information available to one ear only  or information derived from comparing sounds binaurally—is particularly suited to investigating the neural remapping that seems to follow vision loss. In a previous study, Franco Lepore and colleagues showed that people who lost their sight at an early age could localize sound, particularly from monaural cues, better than those who could see. These findings suggested that areas of the brain normally dedicated to processing visual stimuli  might play a role in processing sound in these individuals. In a new report, Lepore and colleagues use functional imaging studies to investigate the functional relationship between neural activity and enhanced hearing abilities in the blind, and find a strong correlation between superior sound localization skills and increased activity in the brain's visual center.The authors hypothesized that if visual cortex recruitment bolstered auditory function in some individuals, then visual cortex activity would correlate with individual differences in performance, and the degree of activity should predict such differences. Nineteen people—seven sighted and twelve who lost their sight at an early age—were placed in an echo-free chamber and asked to indicate where a sound was coming from, using either one  or both  ears. The participants then performed the same tasks within a positron emission tomography (PET) machine, which measures brain activity through changes in cerebral blood flow (CBF).Five of the blind participants could accurately localize sounds monaurally; most of the sighted could not.  Only the blind individuals with superior localization skills showed increased CBF in the visual cortex while performing monaural localization tasks. Interestingly, during binaural localization, the sighted participants showed decreased CBF in visual cortical areas. This decrease comports with previous studies showing that engaging one brain center—say, the temporal lobe, which processes sound—inhibits activation of others—such as the occipital lobe, which processes visual cues. These inhibitions appear to be absent in blind persons, though it's not clear why. It could be that blind persons don't need such inhibitions, the authors speculate, or maybe unrestricted access to the visual center serves to compensate for vision loss by boosting nonvisual senses.Whether the enhanced auditory performance reported here simply reflects increased efficiency of auditory processing or indicates “supranormal” powers, Lepore and colleagues argue that their results show that the visual cortex is “specifically recruited to process subtle monaural cues more effectively.” It will be interesting to learn whether blind persons can recruit visual centers for other auditory tasks or to help them navigate the world without sight. Such studies would be vital for tailoring sensory support to suit individual needs and maybe even suggest ways to facilitate the neural cross talk that enhances auditory performance. But don't expect such innovations to recreate the likes of Rahsaan Kirk or Ray Charles anytime soon.


A systematic search among the latter for a fusogenic activity had led to the identification of two bona fide genes, named syncytin-1 and syncytin-2, most probably co-opted by primate genomes for a placental function related to the formation of the syncytiotrophoblast by cell-cell fusion. Here, we show that one of the newly identified envelope gene, named envP(b), is fusogenic in an ex vivo assay, but that its expression – as quantified by real-time RT-PCR on a large panel of human tissues – is ubiquitous, albeit with a rather low value in most tissues. Conversely, the second envelope gene, named envV, discloses a placenta-specific expression, but is not fusogenic in any of the cells tested. Altogether, these results suggest that at least one of these env genes may play a role in placentation, but most probably through a process different from that of the two previously identified syncytins.A recent  These sequences  share strong similarities with present-day retroviruses, and are the proviral remnants of ancestral germ-line infections by active retroviruses, which have thereafter been transmitted in a Mendelian manner (reviewed in -3). The ectively ,8. The sh genome . The seqenv gene, namely on the alignment of a conserved domain of the transmembrane (TM) subunit [env gene is closely related to that of MER66, MER84 and Z69907 families. This gene seems to be part of a very degenerate proviral structure, with only the LTR being identifiable . 3' LTRs are also found just downstream of the envelope genes . The analysis of the PBS (Primer Binding Site) region located downstream of the two 5' LTRs of this family reveals a high degree of homology to the PBS for Val-tRNA , are clribed in ).env genes with an open reading frame would be amplified among all the envelope genes of a given family, by positioning them within domains of maximal divergence between the coding and the non-coding copies. For the HERV-V coding envelope, the primer pair was designed in the 3' part of the gene, where the two envV genes are the most divergent (79% identity in the last 200 nt). An additional primer pair was also designed to monitore the expression of the truncated HERV-V env gene. To assess the specificity of each primer pair for the corresponding env gene, the PCR products obtained upon amplification of genomic DNA were cloned into a pGEM-T vector and 6 clones per amplicon were sequenced. In each case, the 6 sequences corresponded to the expected env gene. Analysis of the expression level of the coding envP(b) and envV genes was achieved on a series of 19 healthy human tissues, and the results are represented in Figure envV was found to be placenta-specific. Interestingly, the truncated envelope of the HERV-V family is highly expressed in the placenta as well, but poorly in other tissues (data not shown). EnvP(b) expression, on the other hand, was observed at a rather low level in almost all the tissues tested, without any specificity for the placenta.To determine whether these two genes could play a role in human placentation, we then characterized their expression pattern and fusogenic properties, as previously performed for the 16 coding envelope genes already identified . To get env genes of the human genome tested in [envW (syncytin-1) and envFRD (syncytin-2), had been found to be fusogenic in an ex vivo assay. As these two env genes were highly and specifically expressed in the placenta, it was suggested that they are involved in a major physiological process within this organ, namely fusion of the cytotrophoblast cells to form the syncytiotrophoblast layer. The two newly identified env genes were therefore similarly tested. To do so, they were first cloned and introduced into a eukaryotic expression vector. The envP(b) gene was PCR-amplified from the DNA of BAC RP11-828K24 by using a proofreading DNA polymerase and running a 15-cycle PCR reaction, whereas the envV gene -not available as BAC DNA- was PCR amplified from the genomic DNA of a Caucasian individual using the Expand long template enzyme mix (Roche Applied Science). Both env genes were then assayed for cell-cell fusion on a large panel of mammalian cells  using a transient transfection assay and two clones from each construct. As shown in Figure envP(b), and in none of them for envV. The truncated envelope protein member of the HERV-V family was also tested and, as expected, was not fusogenic (data not shown). In some respect, these results are surprising. Indeed, the putative protein encoded by envP(b) is fusogenic despite the absence of a canonical fusion peptide, i.e. of a hydrophobic region located at the N-terminus of the putative TM subunit, just downstream of the SU-TM cleavage site . To check that the lack of fusogenicity of the latter gene is not due to a fortuitous gene polymorphism of the envV gene from the selected individual, we PCR-amplified, cloned and assayed the envV gene from two other individuals (for both the complete and the truncated envV genes): no cell-cell fusion was observed either (data not shown). Finally, we identified and cloned the chimpanzee orthologous envV gene (which is fully coding as well): neither did it display any fusogenic activity in our assay (data not shown).Among the 16 coding ested in , only twenvV and envP(b) genes are most probably not "syncytin-like" genes, sensu stricto. Additional experiments should now be devised (e.g. search for conservation among primates, search for Single Nucleotide Polymorphisms) to assess their role -if any- in human physiology.In conclusion, the present analysis shows, rather paradoxically, that the envelope protein with fusogenic properties is not placenta-specific, whereas the one which is exclusively expressed in the placenta -a characteristic pattern of the two previously described fusogenic syncytin-1 and syncytin-2 gene products- is not fusogenic. In this respect, these results suggest that the two newly identified HERV, human endogenous retrovirus; TM, transmembrane; LTR, Long Terminal Repeat; PBS, Primer Binding Site.The author(s) declare that they have no competing interests.env genes and the cell-cell fusion assays.SB carried out the cloning of the NdP analyzed the sequences, constructed the phylogenetic tree, designed and carried out the Real-Time RT-PCR experiments, and drafted the manuscript.TH conceived the study.


Doctors and researchers often look for the rapid proliferation of T cell populations, key defensive players in the immune system, as a telltale sign that the body is working hard to fend off a foreign threat. Every one of these circulating white blood cells carries a T cell receptor (TCR) that binds to a specific protein, or antigen, when displayed on the surface of a cell. A match between TCR and displayed antigen results in the cell's death and the subsequent expansion of T cell clones, all programmed to recognize the original offending protein. Some TCRs bind and expand in response to pathogenic antigens, such as viral or bacterial proteins. But T cells can also react and proliferate inappropriately in response to the body's own proteins, leading to destructive autoimmune diseases such as multiple sclerosis, which is characterized by immune system attacks on nervous tissue. Self-recognizing TCRs, however, can also target and destroy tumors—though full activation of these T cells is inconsistent and poorly understood.PLoS Biology, Frances Crawford and colleagues have developed a novel method for rapidly identifying TCR mimotopes—peptide sequences similar or identical to epitopes that also elicit the immune response—which can be used to determine the antigen of a given T cell population.Identifying the particular antigen behind an exploding population of T cells is invaluable for finding the source of autoimmune diseases and studying immune responses to cancer. But it's a laborious and time-consuming process, as researchers are faced with the prospect of sifting through millions upon millions of possible matches between TCRs and their prospective antigen epitopes—the part of the antigenic molecule to which the receptor binds. Now, as they report in this issue of Working backwards, the team started off with two different T cell clones that had been previously selected for with a known antigen—a peptide called p3K. One clone was derived from mice genetically engineered to have broadly reactive T cells; the other, a conventional clone, was much more sensitive to the precise molecular structure of p3K.Crawford and colleagues then created a “peptide library” comprising more than 30,000 baculoviruses (viruses that selectively target insect cells), each one carrying a slightly different version of the p3K gene, varied in regions of the peptide known to be important for TCR binding. These p3K genes were embedded within a major histocompatibility complex (MHC) gene—a type of cell surface protein that holds displayed antigens and is also important for proper TCR recognition. The team then unleashed their virus library onto insect cells that, once infected, began to produce the specific peptide–MHC complexes encoded on the viral DNA. The insect cells then shuttled these proteins to their surfaces, resulting in a vast array of cells that each displayed a unique variant of the p3K–MHC complex. This “display library” was then incubated with fluorescently labeled TCRs from the two different clones. By observing and isolating the insect cells that lit up, the researchers could see which of the thousands of cells displaying peptide–MHC possessed a mimotope capable of binding a TCR. Because the genetic information about the displayed complex was still stored within the virus-infected cell, the researchers could determine the full peptide sequence responsible for the identified mimotopes.Confirming the effectiveness of their method, the results of the fluorescence experiments echoed the authors' original characterizations about the two populations of T cells. The broadly reactive TCR bound to several different uniquely displayed complexes; it had 20 mimotopes. The conventional TCR, however, bound only to one peptide–MHC complex, an almost perfect match to the original p3K peptide. Though this study was based on a known antigen and epitope , the baculovirus display library technique described here could easily be used on T cell populations with unknown antigens. With such a tool, researchers could, for example, identify the antigens connected with tumor-fighting T cells and, through inoculation, possibly induce the production of similar T cells in cancer patients who lack them.


Disturbances in the immune system has been described in Turner syndrome, with an association to low levels of IgG and IgM and decreased levels of T- and B-lymphocytes. Also different autoimmune diseases have been connected to Turner syndrome (45, X), thyroiditis being the most common.Besides the typical features of Turner syndrome (short stature, failure to enter puberty spontaneously and infertility due to ovarian insufficiency) ear problems are common .Levels of IgG, IgA, IgM, IgD and the four IgG subclasses as well as T- and B-lymphocyte subpopulations were investigated in 15 girls with Turners syndrome to examine whether an immunodeficiency may be the cause of their high incidence of otitis media. No major immunological deficiency was found that could explain the increased incidence of otitis media in the young Turner girls. Recurrent otitis media is often a problem in children with Turner syndrome (TS) ,2. More TS is caused by the presence of only one normally functioning X-chromosome. The other sex chromosome can be missing (45, X) or abnormal and mosaicism is often present. Occurring in one of every 2000 female births, TS is one of our most common sex chromosome abnormalities . TS is cImmunological disturbances have previously been described in TS, with an association to reduced levels of serum IgG and IgM, increased IgA and decreased levels of circulating T- and B-lymphocytes. However, the results have not been conclusive -12.2 deficiency commonly develop recurrent acute otitis media. It is believed that these infections are secondary to impaired antibody response, rather than Eustachian tube dysfunction [In the normal population children with IgGfunction . As immuThe aim of this study was to investigate immunoglobulin and lymphocyte subpopulations in girls with Turners syndrome to examine whether an immunodeficiency may be the cause of their high incidence of otitis media. Immunotherapy would then be a possible treatment.Blood samples from patients with the diagnosis TS, genetically confirmed, were investigated according to the Swedish ethical record no 88–265.Analyses regarding immunoglobulin- and lymhpocyte subpopulations were performed in 15 girls, aged 5–17 years (median age 11 years), randomly selected from all girls in this age group with TS attending the Karolinska Hospital, Stockholm . Of these 53% (n = 8) had suffered from repeated attacks of otitis media. All TS girls had been treated with growth hormones and their karyotypes were: 45, X (n = 8); 45, X/46, XX (n = 4); 45, X/46, X, i(Xq) (n = 2); and 45, X/46, X, r(X) (n = 1) (r = ring chromosome).A medical history was attained, focusing on autoimmune diseases, previous and current ear diseases and other infectious diseases, ear operations, and hearing problems.9/L) were analysed in a Coulter MicroDiff II (Beckman-Coulter). The differential leukocyte (lymphocytes, monocytes and granulocytes) counts and percentages were obtained by 2-color FACS-analysis with CD14/CD45 markers. The number and percentage of lymphocyte subpopulations were obtained by standardized 2- or 3-color FACS-analysis on Epics XL or Elite flowcytometer (Beckman-Coulter) using commercial reagents. CD19+ was marker for B-cells and CD3+ for T-cells, CD3+CD4+ for helper T-cells, CD3+CD8+ for cytotoxic T-cells, CD56+CD3- for NK-cells and HLA-DR+ for activated T-cell subsets. The ratio of CD4+/CD8+ was also calculated. The monoclonal antibody clones used were: UCHT1 (CD3+), SFCI12T4D11/T4 (CD4+), SFCI21Thy2D3/T8 (CD8+), 116/Mo2 (CD14+), 89B/B4 (CD19+), KC56 (CD45+), NKH1 (CD56+) and 9-49/I3 (HLA-DR+), all from Cytostat, Beckman-Coulter. All FACS-analyses were performed at the routine laboratory, Department of Clinical Immunology, Karolinska Hospital and the results were compared to age-related in-house and published reference ranges (5 to 95 percentiles) [+CD3- for which an adult reference was used (10–90 percentile).Leukocyte counts (101, IgG2, IgG3 and IgG4 as well as the Gm(23)-allotyping of IgG2 were analysed by standard methods and compared to age related reference ranges used at the routine laboratory, Department of Clinical Immunology, Karolinska Hospital, Stockholm.Hemolytic complement , IgA antibodies to gliadin and endomysium, IgG antibodies to pneumococcal polysaccharide and tetanus toxoid antigen, the serum concentrations (g/L) of circulating IgA, IgG, IgM, IgD, IgGMedians of continuous parameters were compared between groups by Mann-Whitney U-test and correlations were performed by Spearman rank analysis. A two-tailed p < 0.05 was considered significant.+ and CD8+ T-cells (HLA-DR+). However, the CD4+/CD8+ ratio was in the lower range (girls aged ≥10), with one girl having a very low ratio (0.6).The leukocyte counts as well as the absolute counts and percentages of lymphocytes, monocytes, and granulocytes were within normal limits for all 15 Turner girls. Likewise most girls had normal counts and percentages of lymphocyte subpopulations as compared to the 5 to 95% percentiles age-related reference ranges Fig.  and 1b iHemolytic complement  was within normal limits for all 15 Turner girls.1 (10.2 and 10.8 g/L), one with low IgG2 (0.4 g/L) and two girls with low IgG4 (<0.01 g/L).The serum concentrations of IgG, IgA, IgM, IgD and the four IgG subclasses were for most Turner girls within the age-related 95% confidence intervals Fig. . The excThe frequency of homozygous G2m(23)-negative Turner girls was 33% (5/15).Normal levels of IgG antibodies to tetanus toxoid and polysaccharide antigen were detected among most Turner girls, except for two respectively one, having too low levels. Slightly elevated IgA antibodies to gliadin were observed in 3 (20%) girls, whereas no IgA antibodies to endomysium could be detected in any of the 15 girls.+ (p = 0.0053) and CD4+HLA-DR+ (p = 0.035), as well as the percentage of CD19+ (p = 0.023). Also IgG2 increased with age (p = 0.05). These findings are in line with the reference literature for the normal population [When comparing girls aged <10 years (n = 4) and ≥10 years (n = 11) the following parameters were found to be influenced by age with decreased values among the older girls: total counts of leukocytes (p = 0.0093), lymphocytes (p < 0.05), monocytes (p = 0.0093), granulocytes (p = 0.015), CD19pulation .+ T-cells (p = 0.0087), CD4+ T-cells (p = 0.012) and CD4+HLA-DR+ (p = 0.05) as well as in the percentage of CD3+ T-cells (p = 0.05) in otitis prone (n = 5) compared to otitis free (n = 6) Turner girls was shown. No such differences were noticed for any immunoglobulin levels, antibody titers, CD4+/CD8+-ratio or CD8+, CD19+, CD56+CD3- lymphocyte subpopulations.The girls with TS were divided into two groups according to their history of recurrent otitis media. As age influenced some of the parameters we only considered girls ≥10 years old (n = 11). Significant increases in absolute counts of lymphocytes (p = 0.004), CD3Any apparent influence, of the different karyotypes, on any of the parameters studied was not observed within the group.In this study no major derangement in the immune status was found among the girls with TS. Normal levels of most lymphocyte- and immunoglobulin subpopulations were registered. The few outliers noted must be considered as a normal individual variation.+/CD8+ ratio in the lower range [+ population. Although, the patients were few, we noticed some differences between the otitis prone and otitis free Turner girls. The elevated counts of lymphocytes, CD3+, CD4+ cells and CD4+HLA-DR+ cells seen among the otitis prone girls, probably reflects a secondary effect of an activated immune system involving T-helper cells, rather than any immune deficient state. Moreover, the levels of IgG antibodies to pneumococcal polysaccharide antigen, which are important in the defense of bacteria, were normal. A homozygous lack of the IgG2m(23) allotype was seen in 33% of the girls, which is the same frequency as in the normal population [2. In the study group a negative IgG2m(23) allotype was not correlated to a positive history of recurrent otitis media, neither could the different karyotypes be associated to the levels of immunoglobulin- or lymphocyte subpopulations. Perhaps the cause of the repeated attacks of otitis media in Turners syndrome is not to be found in the periphery, but rather more locally. Even if earlier computed tomography scans of the temporal bone have not shown any abnormalities [However, as described in an earlier study of Turner girls, the present study confirmed a CD4er range , supposepulation . A negatmalities . The SHOmalities . As the Our findings of normal immunoglobulin- and lymphocyte subpopulations are not entirely in concordance with some earlier studies, where a reduction of circulating IgM and IgG as well as T- and B-lymphocytes has been observed ,10. HoweIn conclusion, we did not find any major immunological deficiency in immunoglobulins or lymphocyte subpopulations that could explain the increased incidence of otitis media observed in girls with TS. Therefore, treatment with immunotherapy is not an option in this patient group. Further studies are warranted to elucidate local pathology, both from an immunological and anatomical point of view.AES participated in the design of the study, performed the statistical analysis and drafted the manuscript. LS participated in the design of the study and collected the blood samples. CGMM performed the statistical analysis. MH participated in the design and coordination of the study and collected the blood samples.All authors read and approved the final manuscript.


A detailed description of the aims and methods of the Bioconductor project, an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples. The Bioconductor project  is an inAmong the many challenges that arise for both statisticians and biologists are tasks of data acquisition, data management, data transformation, data modeling, combining different data sources, making use of evolving machine learning methods, and developing new modeling strategies suitable to CBB. We have emphasized transparency, reproducibility, and efficiency of development in our response to these challenges. Fundamental to all these tasks is the need for software; ideas alone cannot solve the substantial problems that arise.The primary motivations for an open-source computing environment for statistical genomics are transparency, pursuit of reproducibility and efficiency of development.a priori how sensitive the ultimate analyses are to variations or errors in the many steps in the pipeline. Credible work in this domain requires exposure of the entire process.High-throughput methodologies in CBB are extremely complex, and many steps are involved in the conversion of information from low-level information structures (for example, microarray scan images) to statistical databases of expression measures coupled with design and covariate data. It is not possible to say Experimental protocols in molecular biology are fully published lists of ingredients and algorithms for creating specific substances or processes. Accuracy of an experimental claim can be checked by complete obedience to the protocol. This standard should be adopted for algorithmic work in CBB. Portable source code should accompany each published analysis, coupled with the data on which the analysis is based.By development, we refer not only to the development of the specific computing resource but to the development of computing methods in CBB as a whole. Software and data resources in an open-source environment can be read by interested investigators, and can be modified and extended to achieve new functionalities. Novices can use the open sources as learning materials. This is particularly effective when good documentation protocols are established. The open-source approach thus aids in recruitment and training of future generations of scientists and software developers.The rest of this article is devoted to describing the computing science methodology underlying Bioconductor. The main sections detail design methods and specific coding and deployment approaches, describe specific unmet challenges and review limitations and future aims. We then consider a number of other open-source projects that provide software solutions for CBB and end with an example of how one might use Bioconductor software to analyze microarray data.The software development strategy we have adopted has several precedents. In the mid-1980s Richard Stallman started the Free Software Foundation and the GNU project  as an atOne of the key success factors of the Linux kernel is its modular design, which allows for independent and parallel development of code  in a virIn this section, we review seven topics important to establishment of a scientific open source software project and discuss them from a CBB point of view: language selection, infrastructure resources, design strategies and commitments, distributed development and recruitment of developers, reuse of exogenous resources, publication and licensure of code, and documentation.CBB poses a wide range of challenges, and any software development project will need to consider which specific aspects it will address. For the Bioconductor project we wanted to focus initially on bioinformatics problems. In particular we were interested in data management and analysis problems associated with DNA microarrays. This orientation necessitated a programming environment that had good numerical capabilities, flexible visualization capabilities, access to databases and a wide range of statistical and mathematical algorithms. Our collective experience with R suggested that its range of well-implemented statistical and visualization tools would decrease development and distribution time for robust software for CBB. We also note that R is gaining widespread usage within the CBB community independently of the Bioconductor Project. Many other bioinformatics projects and researchers have found R to be a good language and toolset with which to work. Examples include the Spot system , MAANOVAR is a high-level interpreted language in which one can easily and quickly prototype new computational methods. These methods may not run quickly in the interpreted implementation, and those that are successful and that get widely used will often need to be re-implemented to run faster. This is often a good compromise; we can explore lots of concepts easily and put more effort into those that are successful.The R environment includes a well established system for packaging together related software components and documentation. There is a great deal of support in the language for creating, testing, and distributing software in the form of 'packages'. Using a package system lets us develop different software modules and distribute them with clear notions of protocol compliance, test-based validation, version identification, and package interdependencies. The packaging system has been adopted by hundreds of developers around the world and lies at the heart of the Comprehensive R Archive Network, where several hundred independent but interoperable packages addressing a wide range of statistical analysis and visualization objectives may be downloaded as open source.The complexity of problems in CBB is often translated into a need for many different software tools to attack a single problem. Thus, many software packages are used for a single analysis. To secure reliable package interoperability, we have adopted a formal object-oriented programming discipline, as encoded in the 'S4' system of formal classes and methods . The BioAccess to data from on-line sources is an essential part of most CBB projects. R has a well developed and tested set of functions and packages that provide access to different databases and to web resources (via http, for example). There is also a package for dealing with XML , availabAmong the statistical and numerical algorithms provided by R are its random number generators and machine learning algorithms. These have been well tested and are known to be reliable. The Bioconductor Project has been able to adapt these to the requirements in CBB with minimal effort. It is also worth noting that a number of innovations and extensions based on work of researchers involved in the Bioconductor project have been flowing back to the authors of these packages.Among the strengths of R are its data and model visualization capabilities. Like many other areas of R these capabilities are still evolving. We have been able to quickly develop plots to render genes at their chromosomal locations, a heatmap function, along with many other graphical tools. There are clear needs to make many of these plots interactive so that users can query them and navigate through them and our future plans involve such developments.snow and rpvm simplify the development of portable interpreted code for computing on a Beowulf or similar computational cluster of workstations. These tools provide simple interfaces that allow for high-level experimentation in parallel computation by computing on functions and environments in concurrent R sessions on possibly heterogeneous machines. The snow package provides a higher level of abstraction that is independent of the communication technology such as the message-passing interface (MPI) [rsprng. Practical benefits and problems involved with programming parallel processes in R are described more fully in Rossini et al. [R has also been the basis for pathbreaking research in parallel statistical computing. Packages such as ce (MPI)  or the pce (MPI) . Parallece (MPI) , essentii et al.  and Li ai et al. .Perhaps the most important aspect of using R is its active user and developer communities. This is not a static language. R is undergoing major changes that focus on the changing technological landscape of scientific computing. Exposing biologists to these innovations and simultaneously exposing those involved in statistical computing to the needs of the CBB community has been very fruitful and we hope beneficial to both communities.We began with the perspective that significant investment in software infrastructure would be necessary at the early stages. The first two years of the Bioconductor project have included significant effort in developing infrastructure in the form of reusable data structures and software/documentation modules (R packages). The focus on reusable software components is in sharp contrast to the one-off approach that is often adopted. In a one-off solution to a bioinformatics problem, code is written to obtain the answer to a given question. The code is not designed to work for variations on that question or to be adaptable for application to distinct questions, and may indeed only work on the specific dataset to which it was originally applied. A researcher who wishes to perform a kindred analysis must typically construct the tools from scratch. In this situation, the scientific standard of reproducibility of research is not met except via laborious reinvention. It is our hope that reuse, refinement and extension will become the primary software-related activities in bioinformatics. When reusable components are distributed on a sound platform, it becomes feasible to demand that a published novel analysis be accompanied by portable and open software tools that perform all the relevant calculations. This will facilitate direct reproducibility, and will increase the efficiency of research by making transparent the means to vary or extend the new computational method.exprSet class of the Biobase package, and the various Bioconductor metadata packages, for example hgu95av2. An exprSet is a data structure that binds together array-based expression measurements with covariate and administrative data for a collection of microarrays. Based on R data.frame and list structures, exprSets offer much convenience to programmers and analysts for gene filtering, constructing annotation-based subsets, and for other manipulations of microarray results. The exprSet design facilitates a three-tier architecture for providing analysis tools for new microarray platforms: low-level data are bridged to high-level analysis manipulations via the exprSet structure. The designer of low-level processing software can focus on the creation of an exprSet instance, and need not cater for any particular analysis data structure representation. The designer of analysis procedures can ignore low-level structures and processes, and operate directly on the exprSet representation. This design is responsible for the ease of interoperation of three key Bioconductor packages: affy, marray, and limma.Two examples of the software infrastructure concepts described here are the hgu95av2 package is one of a large collection of related packages that relate manufactured chip components to biological metadata concerning sequence, gene functionality, gene membership in pathways, and physical and administrative information about genes. The package includes a number of conventionally named hashed environments providing high-performance retrieval of metadata based on probe nomenclature, or retrieval of groups of probe names based on metadata specifications. Both types of information (metadata and probe name sets) can be used very fruitfully with exprSets: for example, a vector of probe names immediately serves to extract the expression values for the named probes, because the exprSet structure inherits the named extraction capacity of R data.frames.The Well-designed scientific software should reduce data complexity, ease access to modeling tools and support integrated access to diverse data resources at a variety of levels. Software infrastructure can form a basis for both good scientific practice  and for innovation.The adoption of designing by contract, object-oriented programming, modularization, multiscale executable documentation, and automated resource distribution are some of the basic software engineering strategies employed by the Bioconductor Project.exprSet functionality must deliver a specified set of functionalities. Whatever object the provider's code returns, it must satisfy the exprSets contract. Among other things, this means that the object must respond to the application of functions exprs and pData with objects that satisfy the R matrix and data.frame contracts respectively. It follows that exprs(x) i,j][, for example, will return the number encoding the expression level for the ith gene for the jth sample in the object x, no matter what the underlying representation of x. Here i and j need not denote numerical indices but can hold any vectors suitable for interrogating matrices via the square-bracket operator. Satisfaction of the contract obligations simplifies specification of analysis procedures, which can be written without any concern for the underlying representations for exprSet information.While we do not employ formal contracting methodologies (for example, Eiffel ) in our A basic theme in R development is simplifying the means by which developers can state, follow, and verify satisfaction of design contracts of this sort. Environment features that support convenient inheritance of behaviors between related classes with minimal recoding are at a premium in this discipline.There are various approaches to the object-oriented programming methodology. We have encouraged, but do not require, use of the so-called S4 system of formal classes and methods in Bioconductor software. The S4 object paradigm (defined primarily by Chambers  with modexprSet structure, for example, contains information on expression levels (exprs slot), variability (se.exprs), covariate data (phenoData slot), and several types of metadata (slots description, annotation and notes). The tight binding of covariate data with expression data spares developers the need to track these two types of information separately. The exprSet structure explicitly excludes information on gene-related annotation (such as gene symbol or chromosome location) because these are potentially volatile and are not needed in many activities involving exprSets. Modularization at the R function level entails that functions are written to do one meaningful task and no more, and that documents (help pages) are available at the function level with worked examples. This simplifies debugging and testing. Modularization at the package level entails that all packages include sufficient functionality and documentation to be used and understood in isolation from most other packages. Exceptions are formally encoded in files distributed with the package.The notion that software should be designed as a system of interacting modules is fairly well established. Modularization can occur at various levels of system structure. We strive for modularization at the data structure, R function and R package levels. This means that data structures are designed to possess minimally sufficient content to have a meaningful role in efficient programming. The vignette concept. Vignettes go beyond typical man page documentation, which generally focuses on documenting the behavior of a function or small group of functions. The purpose of a vignette is to describe in detail the processing steps required to perform a specific task, which generally involves multiple functions and may involve multiple packages. Users of a package have interactive access to all vignettes associated with that package.Accurate and thorough documentation is fundamental to effective software development and use, and must be created and maintained in a uniform fashion to have the greatest impact. We inherit from R a powerful system for small-scale documentation and unit testing in the form of the executable example sections in function-oriented manual pages. We have also introduced a new concept of large-scale documentation with the Sweave system [tools package. However, new users will need a simpler interface. Our first offering in this area is the vignette explorer vExplorer which provides a widget that can be used to navigate the various code chunks. Each chunk is associated with a button and the code is displayed in a window, within the widget. When the user clicks on the button the code is evaluated and the output presented in a second window. Other buttons provide other functionality, such as access to the PDF version of the document. We plan to extend this tool greatly in the coming years and to integrate it closely with research into reproducible research  that all members of the project can access and modify together with some form of version management system. We adopted the Concurrent Versions System ,29 and cAdditional discipline is needed to ensure that changes by one programmer should not result in a failure of other code in the system. Within the R language, software components are naturally broken into packages, with a formal protocol for package structure and content specified in the R Extensions manual . Each paWe rely on the testing mechanisms supported by the R package testing system  to ensurMembers of the development team communicate via a private mailing list. In many cases they also use private email, telephone and meetings at conferences in order to engage in joint projects and to keep informed about the ideas of other members.We now present three arguments in favor of using and adapting software from other projects rather than re-implementing or reinventing functionality. The first argument that we consider is that writing good software is a challenging problem and any re-implementation of existing algorithms should be avoided if possible. Standard tools and paradigms that have been proven and are well understood should be preferred over new untested approaches. All software contains bugs but well used and maintained software tends to contain fewer.graph, RBGL and Rgraphviz. The first of these provides the class descriptions and basic infrastructure for dealing with graphs in R, the second provides access to algorithms on graphs, and the third to a rich collection of graph layout algorithms. The graph package was written from scratch for this project, but the other two are interfaces to rich libraries of software routines that have been created by other software projects, BOOST [Graphviz [The second argument is that CBB is an enormous field and that progress will require the coordinated efforts of many projects and software developers. Thus, we will require structured paradigms for accessing data and algorithms written in other languages and systems. The more structured and integrated this functionality, the easier it will be to use and hence the more it will be used. As specific examples we consider our recent development of tools for working with graph or network structures. There are three main packages in Bioconductor of interacting with graphs. They are s, BOOST ,32 and GGraphviz  respectiThere are many benefits from this approach for us and for the other projects. For bioinformatics and computational biology we gain rapid access to a variety of graph algorithms including graph layout and traversal. The developers in those communities gain a new user base and a new set of problems that they can consider. Gaining a new user base is often very useful, as new users with previously unanticipated needs tend to expose weaknesses in design and implementation that more sophisticated or experienced users are often able to avoid.In a similar vein, we plan to develop and encourage collaboration with other projects, including those organized through the Open Bioinformatics Foundation and the International Interoperability Consortium. We have not specifically concentrated on collaboration to this point in part because we have chosen areas for development that do not overlap significantly with the tools provided by those projects. In this case our philosophy remains one of developing interfaces to the software provided by those projects and not re-implementing their work. In some cases, other projects have recognized the potential gains for collaboration and have started developing interfaces for us to their systems, with the intent of making future contributions .Another argument in favor of standardization and reuse of existing tools is best made with reference to a specific example. Consider the topic of markup and markup languages. For any specific problem one could quickly devise a markup that is sufficient for that problem. So why then should we adopt a standard such as XML? Among the reasons for this choice is the availability of programmers conversant with the paradigm, and hence lower training costs. A second reason is that the XML community is growing and developing and we will get substantial technological improvements without having to initiate them. This is not unusual. Other areas of computational research are as vibrant as CBB and by coordinating and sharing ideas and innovations we simplify our own tasks while providing stimulus to these other areas.Modern standards of scientific publication involve peer review and subsequent publication in a journal. Software publication is a slightly different process with limited involvement to date of formal peer review or official journal publication. We release software under an open-source license as our main method of publication. We do this in the hope that it will encourage reproducibility, extension and general adherence to the scientific method. This decision also ensures that the code is open to public scrutiny and comment. There are many other reasons for deciding to release software under an open-source license, some of which are listed in Table Another consideration that arose when determining the form of publication was the need to allow an evolutionary aspect to our own software. There are many reasons for adopting a strategy that would permit us to extend and improve our software offerings over time. The field of CBB is relatively volatile and as new technologies are developed new software and inferential methods are needed. Further, software technology itself is evolving. Thus, we wanted to have a publication strategy that could accommodate changes in software at a variety of levels. We hope that that strategy will also encourage our users to think of software technology as a dynamic field rather than a static one and to therefore be on the lookout for innovations in this arena as well as in more traditional biological ones.Our decision to release software in the form of R packages is an important part of this consideration. Packages are easy to distribute, they have version numbers and define an API. A coordinated release of all Bioconductor packages occurs twice every year. At any given time there is a release version of every package and a development version. The only changes allowed to be made on the release version are bug fixes and documentation improvements. This ensures that users will not encounter radical new behaviors in code obtained in the release version. All other changes such as enhancements or design changes are carried out on the development branch .Approximately six weeks before a release, a major effort is taken to ensure that all packages on the development branch are coordinated and work well together. During that period extensive testing is carried out through peer review amongst the Bioconductor core. At release time all packages on the development branch that are included in the release change modes and are now released packages. Previous versions of these packages are deprecated in favor of the newly released versions. Simultaneously, a new development branch is made and the developers start to work on packages in the new branch. Note that these version-related administrative operations occur with little impact on developers. The release manager is responsible for package snapshot and file version modifications. The developers' source code base is fairly simple, and need not involve retention of multiple copies of any source code files, even though two versions are active at all times.We would also like to point out that there are compelling arguments that can be made in favor of choosing different paradigms for software development and deployment. We are not attempting at this juncture to convince others to distribute software in this way, but rather elucidating our views and the reasons that we made our choice. Under a different set of conditions, or with different goals, it is entirely likely that we would have chosen a different model.We now consider four specific challenges that are raised by research in computational biology and bioinformatics: reproducibility, data evolution and complexity, training users, and responding to user needs.We would like to address the reproducibility of published work in CBB. Reproducibility is important in its own right, and is the standard for scientific discovery. Reproducibility is an important step in the process of incremental improvement or refinement. In most areas of science researchers continually improve and extend the results of others but for scientific computation this is generally the exception rather than the rule.Buckheit and Donoho , referriThere are substantial benefits that will come from enabling authors to publish not just an advertisement of their work but rather the work itself. A paradigm that fundamentally shifts publication of computational science from an advertisement of scholarship to the scholarship itself will be a welcome addition. Some of the concepts and tools that can be used in this regard are contained in ,37.et al. [When attempting to re-implement computational methodology from a published description many difficulties are encountered. Schwab et al.  make the"Indeed the problem occurs wherever traditional methods of scientific publication are used to describe computational research. In a traditional article the author merely outlines the relevant computations: the limitations of a paper medium prohibit complete documentation including experimental data, parameter values and the author's programs. Consequently, the reader has painfully to re-implement the author's work before verifying and utilizing it.... The reader must spend valuable time merely rediscovering minutiae, which the author was unable to communicate conveniently."The development of a system capable of supporting the convenient creation and distribution of reproducible research in CBB is a massive undertaking. Nevertheless, the Bioconductor project has adopted practices and standards that assist in partial achievement of reproducible CBB.Publication of the data from which articles are derived is becoming the norm in CBB. This practice provides one of the components needed for reproducible research - access to the data. The other major component that is needed is access to the software and the explicit set of instructions or commands that were used to transform the data to provide the outputs on which the conclusions of the paper rest. In this regard publishing in CBB has been less successful. It is easy to identify major publications in the most prestigious journals that provide sketchy or indecipherable characterizations of computational and inferential processes underlying basic conclusions. This problem could be eliminated if the data housed in public archives were accompanied by portable code and scripts that regenerate the article's figures and tables.The combination of R's well-established platform independence with Bioconductor's packaging and documentation standards leads to a system in which distribution of data with working code and scripts can achieve most of the requirements of reproducible and replayable research in CBB. The steps leading to the creation of a table or figure can be clearly exposed in an Sweave document. An R user can export the code for modification or replay with variations on parameter settings, to check robustness of the reported calculations or to explore alternative analysis concepts.Thus we believe that R and Bioconductor can provide a start along the path towards generally reproducible research in CBB. The infrastructure in R that is used to support replayability and remote robustness analysis could be implemented in other languages such as Perl  and PythMetadata are data about data and their definition depends on the perspective of the investigator. Metadata for one investigator may well be experimental data for another. There are two major challenges that we will consider. First is the evolutionary nature of the metadata. As new experiments are done and as our understanding of the biological processes involved increases the metadata changes and evolves. The second major problem that concerns metadata data is its complexity. We are trying to develop software tools that make it easier for data analysts and researchers to use the existing metadata appropriately.reposTools package. There is a natural way to apply version numbers so users can determine if their data are up to date or if necessary they can obtain older versions to verify particular analyses. Further, users can synchronize a variety of metadata packages according to a common version of the data sources that they were constructed from.The constant changing and updating of the metadata suggests that we must have a system or a collection process that ensures that any metadata can be updated and the updates can be distributed. Users of our system will want access to the most recent versions. Our solution has been to place metadata into R packages. These packages are built using a semi-automatic process  and are There are a number of advantages that come from automating the process of building data packages. First, the modules are uniform to an extent that would not be possible if the packages were human written. This means that users of this technology need only become acquainted with one package to be acquainted with all such packages. Second, we can create many packages very quickly. Hence the labor savings are substantial. For microarray analyses all data packages should have the same information . The only difference between the packages is that each references only the specific set of genes (probes) that were assayed. This means that data analysts can easily switch from one type of chip to another. It also means that we can develop a single set of tools for manipulating the metadata and improvements in those tools are available to all users immediately. Users are free to extend data packages with data from other, potentially proprietary, sources.Treating the data in the same manner that we treat software has also had many advantages. On the server side we can use the same software distribution tools, indicating updates and improvements with version numbering. On the client side, the user does not need to learn about the storage or internal details of the data packages. They simply install them like other packages and then use them.One issue that often arises is whether one should simply rely on online sources for metadata. That is, given an identifier, the user can potentially obtain more up-to-date information by querying the appropriate databases. The data packages we are proposing cannot be as current. There are, however, some disadvantages to the approach of accessing all resources online. First, users are not always online, they are not always aware of all applicable information sources and the investment in person-time to obtain such information can be high. There are also issues of reproducibility that are intractable as the owners of the web resources are free to update and modify their offerings at will. Some, but not all, of these difficulties can be alleviated if the data are available in a web services format.AnnBuilder package and paper [Another argument that can be made in favor of our approach, in this context, is that it allows the person constructing the data packages to amalgamate disparate information from a number of sources. In building metadata packages for Bioconductor, we find that some data are available from different sources, and under those circumstances we look for consensus, if possible. The process is quite sophisticated and is detailed in the nd paper .Most of the projects in CBB require a combination of skills from biology, computer science, and statistics. Because the field is new and there has been little specialized training in this area it seems that there is some substantial benefit to be had from paying attention to training. From the perspective of the Bioconductor project, many of our potential users are unfamiliar with the R language and generally are scientifically more aligned with one discipline than all three. It is therefore important that we produce documentation for the software modules that is accessible to all. We have taken a two-pronged approach to this, we have developed substantial amounts of course material aimed at all the constituent disciplines and we have developed a system for interactive use of software and documentation in the form of vignettes and more generally in the form of navigable documents with dynamic content.Course materials have been developed and refined over the past two to three years. Several members of the Bioconductor development team have taught courses and subsequently refined the material, based on success and feedback. The materials developed are modular and are freely distributed, although restrictions on publication are made. The focus of the materials is the introduction and use of software developed as part of the Bioconductor project, but that is not a requirement and merely reflects our own specific purposes and goals.In this area we feel that we would benefit greatly from contributions from those with more experience in technical document authoring. There are likely to be strategies, concepts and methodologies that are standard practice in that domain that we are largely unaware of. However, in the short term, we rely on the students, our colleagues and the users of the Bioconductor system to guide us and we hope that many will contribute. Others can easily make substantial contributions, even those with little or no programming skills. What is required is domain knowledge in one field of interest and the recognition of a problem that requires additional domain knowledge from another of the fields of interest.Our experience has been that many of these new users often transform themselves into developers. Thus, our development of training materials and documentation needs to pay some attention to the needs of this group as well. There are many more software components than we can collectively produce. Attracting others to collaboratively write software is essential to success.bioconductor@stat.math.ethz.ch) has been successful: there are approximately 800 subscribers and about 3,000 email messages per year.The success of any software project rests on its ability to both provide solutions to the problems it is addressing and to attract a user community. Perhaps the most effective way of addressing user needs is through an e-mail help list and one was set up as soon as the project became active. In addition it is important to keep a searchable archive available so that the system itself has a memory and new users can be referred there for answers to common questions. It is also important that members of the project deal with bug reports and feature requests through this public forum as it both broadcasts their intentions and provides a public record of the discussion. Our mailing list  that made interactions with the system sufficiently self-explanatory that documentation was not needed. We note that this solution is generally more applicable to cases where the underlying software tasks are well defined and well known. In the present case, the software requirements  are constantly evolving. R is primarily command-line oriented and we have chosen to follow that paradigm at least for the first few years of development. We would of course welcome and collaborate with those whose goal was in GUI development but our own forays into this area are limited to the production of a handful of widgets that promote user interaction at specific points.Users have experienced difficulties downloading and installing both R and the Bioconductor modules. Some of these difficulties have been caused by the users' local environments , and some by problems with our software (bugs) which arise in part because it is in general very difficult to adequately test software that interacts over the internet. We have, however, managed to help every user, who was willing to persist, get both R and Bioconductor properly installed. Another substantial difficulty that we had to overcome was to develop a system that allowed users to download not just the software package that they knew they wanted, but additionally, and at the same time, all other software packages that it relies on. With Bioconductor software there is a much larger inter-reliance on software packages  than for most other uses of R and the R package system. The package, reposTools contains much of the necessary infrastructure for handling these tasks. It is a set of functions for dealing with R package repositories which are basically internet locations for collections of R packages.Once the basic software is installed, users will need access to documentation such as the training materials described above and other materials such as the vignettes, described in a previous section. Such materials are most valuable if the user can easily obtain and run the examples on their own computer. We note the obvious similarity with this problem and that described in the section on reproducible research. Again, we are in the enjoyable situation of having a paradigm and tools that can serve two purposes.The Open Bioinformatics Foundation supports projects similar to Bioconductor that are nominally rooted in specific programming languages. BioPerl , BioPythRSPerl package [In this section we consider commonalities and differences between BioPerl and Bioconductor. Both projects have commitments to open source distribution and to community-based development, with an identified core of developers performing primary design and maintenance tasks for the project. Both projects use object-oriented programming methodology, with the intention of abstracting key structural and functional features of computational workflows in bioinformatics and defining stable application programming interfaces (API) that hide implementation details from those who do not need to know them. The toolkits are based on highly portable programming languages. These languages have extensive software resources developed for non-bioinformatic purposes. The repositories for R (Comprehensive R Archive Network, CRAN) and Perl (Comprehensive Perl Archive Network, CPAN) provide mirrored WWW access to structured collections of software modules and documents for a wide variety of workflow elements. Development methodologies targeted at software reuse can realize large gains in productivity by establishing interfaces to existing CPAN or CRAN procedures instead of reimplementing such procedures. For reuse to succeed, the maintainer of the external resource must commit to stability of the resource API. Such stability tends to be the norm for widely-used modules. Finally, both languages have considerable interoperability infrastructure. One implication is that each project can use software written in unrelated languages. R has well-established interfaces to Perl, Python, Java and C. R's API allows software in R to be called from other languages, and the  package  facilita> library(RSPerl)> .PerlPackage("Bio::Perl")> x <- .Perl("get_sequence", "swiss",    "ROA1_HUMAN")> x$division[1] "HUMAN"> x$accession[1] "P09651"> unlist(x$get_keywords)[1] "Nuclear protein" "RNA-binding"[3] "Repeat" "Ribonucleoprotein"[5] "Methylation" "Transport"...RSPerl is not a Bioconductor-supported utility, and that installation of the BioPerl and RSPerl resources to allow interoperation can be complicated.The .PerlPackage command brings the BioPerl modules into scope. .Perl invokes the BioPerl get_sequence subroutine with arguments "swiss" and "ROA1_HUMAN". The resulting R object is a reference to a perl hash. RSPerl infrastructure permits interrogation of the hash via the $ operator. Note that Key differences between the Bioconductor and BioPerl projects concern scope, approaches to distribution, documentation and testing, and important details of object-oriented design.BioPerl is clearly slanted towards processing of sequence data and interfacing to sequence databases, with support for sequence visualization and queries for external annotation. Bioconductor is slanted towards statistical analysis of microarray experiments, with major concerns for array preprocessing, quality control, within- and between-array normalization, binding of covariate and design data to expression data, and downstream inference on biological and clinical questions. Bioconductor has packages devoted to diverse microarray manufacturing and analysis paradigms and to other high-throughput assays of interest in computational biology, including serial analysis of gene expression (SAGE), array comparative genomic hybridization (arrayCGH), and proteomic time-of-flight (SELDI-TOF) data. We say the projects are 'slanted' towards these concerns because it is clear that both projects ultimately aim to support general research activities in computational biology.perl -MCPAN -e shell. This process supports automated retrieval of requested packages and dependencies, but is not triggered by runtime events. Bioconductor has extended the CRAN distribution functionalities so that packages can be obtained and installed 'just in time', as required by a computational request. For both Perl and R, software modules and packages are structured collections of files, some of which are source code, some of which are documents about the code. The relationship between documentation and testing is somewhat tighter in Bioconductor than in BioPerl. Manual pages and vignettes in Bioconductor include executable code. Failure of the code in a man page or vignette is a quality-control event; experimentation with executable code in manual pages (through the example function of R) is useful for learning about software behavior. In Perl, tests occupy separate programs and are not typically integrated with documentation.BioPerl inherits the distribution paradigm supported by CPAN. Software modules can be acquired and installed interactively using, for example Both R and Perl are extensible computer languages. Thus it is possible to introduce software infrastructure supporting different approaches to object-oriented programming (OOP) in various ways in both languages.R's core developers have provided two distinct approaches to OOP in R. These approaches are named S3 and S4. In S3, any object can be assigned to a class (or sequence of classes) simply by setting the class name as the value of the object's class attribute. Class hierarchies are defined implicitly at the object level. Generic methods are defined as ordinary functions and class-specific methods are dispatched according to the class of the object being passed as an argument. In S4, formal definition of class structure is supported, and class hierarchy is explicitly defined in class definitions . Class iClass::Multimethod module can be used to allow multiple dispatch behavior of generic subroutines. The specific classes of objects identified in BioPerl are targeted at sequence data (Seq, LocatableSeq, RelSegment are examples), location data (Simple, Split, Fuzzy), and an important class of objects called interface objects, which are classes whose names end in 'I'. These objects define what methods can be called on objects of specified classes, but do not implement any methods.OOP methodology in Perl has a substantial history and is extensively employed in BioPerl. The basic approach to OOP in Perl seems to resemble S3 more than S4, in that Perl's bless operation can associate any perl data instance with any class. The CPAN Other open bioinformatics projects have intentions and methods that are closely linked with those of Bioconductor.SJava interface [BioJava  providesnterface .BioPython  providesThe Generic Model Organism Database (GMOD) project targets construction of reusable components that can be used to reproduce successful creation of open and widely accessible databases of model organisms (for example, worm, fruitfly and yeast). The main tasks addressed are genome visualization and annotation, literature curation, biological ontology activities, gene expression analysis and pathway visualization and annotation.BioMOBY  providesAs these diverse projects mature, particularly with regard to interoperability, we expect to add infrastructure to Bioconductor to simplify the use of these resources in the context of statistical data analysis. It is our hope that the R and Bioconductor commitments to interoperability make it feasible for developers in other languages to reuse statistical and visualization software already present and tested in R.Results of the Bioconductor project include an extensive repository of software tools, documentation, short course materials, and biological annotation data at . We descGOstats package.Acute lymphocytic leukemia (ALL) is a common and difficult-to-treat malignancy with substantial variability in therapeutic outcomes. Some ALL patients have clearly characterized chromosomal aberrations and the functional consequences of these aberrations are not fully understood. Bioconductor tools were used to develop a new characterization of the contrast in gene expression between ALL patients with two specific forms of chromosomal translocation. The most important tasks accomplished with Bioconductor employed simple-to-use tools for state-of-the-art normalization of hundreds of microarrays, clear schematization of normalized expression data bound to detailed covariate data, flexible approaches to gene and sample filtering to support drilling down to manageable and interpretable subsets, flexible visualization technologies for exploration and communication of genomic findings, and programmatic connection between expression platform metadata and biological annotation data supporting convenient functional interpretation. We will illustrate these through a transcript of the actual command/output sequence. More detailed versions of some of the processing and analysis activities sketched here can be found in the vignettes from the The dataset is from the Ritz laboratory at the Dana Farber Cancer Institute . It contgcrma from the affy package. The output of this is an object of class exprSet which can be used as input for other functions. The package hgu95av2 provides biological metadata including mappings from the Affymetrix identifiers to GO, chromosomal location, and so on. These data can, of course be obtained from many other sources, but there are some advantages to having them as an R package.The Affymetrix HGu95Av2 platform was used, and expression measures were normalized using exprSet to extract those samples with the covariates of interest. The design of the exprSet class includes methods for subsetting both cases and probes. By using the square-bracket notation on ALL, we derive a new exprSet with data on only the desired patients.After loading the appropriate packages we first subset the ALL > data("ALL")> eset <- ALL[, ALL$mol %in%c("BCR/ABL", "ALL1/AF4")]lmFit from the limma package, which can assess differential expression between many different groups and conditions simultaneously. The function lmFit accepts a model matrix which describes the experimental design and produces an output object of class MArrayLM which stores the fitted model information for each gene. The fitted model object is further processed by the eBayes function to produce empirical Bayes test statistics for each gene, including moderated t-statistics, p-values and log-odds of differential expression. The log2-fold changes, average intensites and Holm-adjusted p-values are displayed for the top 10 genes < 0.05> esetSel <- eset [selected, ]There are 165 genes selected for further analysis. A heat map produced by the heatmap function from R allows us to visualize the differential action of these genes between the two groups of patients. Note how the different software modules can be integrated to provide a very rich data-analysis environment. Figure t-test. Many of these questions are normally addressed in terms of a hypergeometric distribution, but they can also be thought of as two-way or multi-way tables, and alternate statistical tests  can be applied to the resulting data.We can carry out many other tests, for example, whether genes encoded on a particular chromosome (or perhaps on a specific strand of a chromosome) are over-represented amongst those selected by moderated GOHyperG is found in the GOstats package. It carries out a hypergeometric test for an overabundance of genes in our selected list of genes for each term in the GO graph that is induced by these genes  annotation in conjunction with these data. We first identify the set of unique LocusLink identifiers among our selected Affymetrix probes. The function s Figure .p-value found was 1.1e-8 and it corresponds to the term, "MHC class II receptor activity". We see that six of the 12 genes with this GO annotation have been selected. Had we used a slightly less conservative gene selection method then the number of selected genes in this GO annotation would have been even higher.The smallest hgu95av2, with those for their array and the basic principles and code are unchanged.Reproducing the above results for any other species or chip for which an annotation package was available would require almost no changes to the code. The analyst need only substitute the references to the data package, Similarly, substitution of other algorithms or statistical tests is possible as the data analyst has access to the full and complete source code. All tools are modifiable at the source level to suit local requirements.We have detailed the approach to software development taken by the Bioconductor project. Bioconductor has been operational for about three years now and in that time it has become a prominent software project for CBB. We argue that the success of the project is due to many factors. These include the choice of R as the main development language, the adoption of standard practices of software design and a belief that the creation of software infrastructure is an important and essential component of a successful project of this size.The group dynamic has also been an important factor in the success of Bioconductor. A willingness to work together, to see that cooperation and coordination in software development yields substantial benefits for the developers and the users and encouraging others to join and contribute to the project are also major factors in our success.To date the project provides the following resources: an online repository for obtaining software, data and metadata, papers, and training materials; a development team that coordinates the discussion of software strategies and development; a user community that provides software testing, suggested improvements and self-help; more than 80 software packages, hundreds of metadata packages and a number of experimental data packages.At this point it is worth considering the future. While many of the packages we have developed have been aimed at particular problems, there have been others that were designed to support future developments. And that future seems very interesting. Many of the new problems we are encountering in CBB are not easily addressed by technology transfer, but rather require new statistical methods and software tools. We hope that we can encourage more statisticians to become involved in this area of research and to orient themselves and their research to the mixture of methodology and software development that is necessary in this field.In conclusion we would like to note that the Bioconductor Project has many developers, not all of whom are authors of this paper, and all have their own objectives and goals. The views presented here are not intended to be comprehensive nor prescriptive but rather to present our collective experiences and the authors' shared goals. In a very simplified version these can be summarized in the view that coordinated cooperative software development is the appropriate mechanism for fostering good research in CBB.