Johrei is an alternative healing practice which involves the channeling of a purported universal healing energy to influence the health of another person. Despite little evidence to support the efficacy of such practices the use of such treatments is on the rise.We assessed cultured human cancer cells for potential responsiveness to Johrei treatment from a short distance. Johrei treatment was delivered by practitioners who participated in teams of two, alternating every half hour for a total of four hours of treatment. The practitioners followed a defined set of mental procedures to minimize variability in mental states between experiments. An environmental chamber maintained optimal growth conditions for cells throughout the experiments. Computerized time-lapse microscopy allowed documentation of cancer cell proliferation and cell death before, during and after Johrei treatments.Comparing eight control experiments with eight Johrei intervention experiments, we found no evidence of a reproducible cellular response to Johrei treatment.Cell death and proliferation rates of cultured human cancer cells do not appear responsive to Johrei treatment from a short distance. Recent surveys indicate the majority of the United States public has used alternative medical therapies, and that energy healing therapies are among the fastest growing complementary and alternative medicine treatments [Relatively little documentation supports a scientific basis for alternative healing therapies involving the manipulation of a purported healing energy associated with the body. Despite this paucity of evidence, such eatments ,2. JohreTwo scientific studies evaluating Johrei healing practices have found provocative results. In one, Johrei was shown to have a beneficial affect on the mood of practitioners . Results2, and humidity controlled time-lapse microscope incubator chamber. Johrei practitioners participated in teams of two, alternating every half hour such that a total of 4 hours of Johrei treatment was delivered. A total of eight control and eight Johrei intervention experiments were accomplished. Johrei treatments were initiated after 4 hours of baseline data had been collected and the observation period extended for a total of 22 hours. We quantified tumor cell death and proliferation throughout the observation period. We also quantified the rate of cellular emigration (i.e. how many tracked cells left the microscopic field per hour) in order to accurately assess cell population dynamics (i.e. cell death and proliferation rates).For each session Johrei practitioners were asked to direct healing intention toward cell cultures in a temperature, COExperiments were conducted with blinding applied to each of the scientists based on previously reported methods . The exp2 before beginning each time-lapse experiment.As the target of Johrei healing intentionality in these studies we used a human cell line derived from a brain tumor biopsy specimen from a patient with glioblastoma multiforme (SF188 GBM). This cell culture model is used widely and can show responsiveness to conventional therapeutic agents including ionizing radiation and chemotherapeutics. SF188 GBM cells were grown in RPMI media supplemented with 10% fetal bovine serum, 100 U/ml penicillin, 100 μg/ml streptomycin sulfate, and 0.25 μg/ml amphotericin. A fresh aliquot of cryogenically preserved cells was thawed at the start of each experiment to ensure uniformity in the genetic profile of the target cells throughout the experiments. Cells were plated at a density of 5,000 cells per well in six-well culture plates and allowed to grow uninterrupted for 20 hours in a humidified incubator maintained at 37°C and 5% CO2 chamber, and a plexi-glass environmental chamber . Cell cultures were maintained at routine incubation settings (37°C, 5% CO2) and optimum humidity. Temperature and CO2 concentration were independently maintained using digital controlling units (Zeiss, Gottingen, Germany). Two sets of phase contrast images (100 X magnification) from each well were taken in 300 second intervals using a Cohu 2600 Series compact monochrome interline transfer CCD camera. Images were acquired during a four-hour baseline period and then continuously for another 18 hours. An Openlab software automation (Improvision, Lexington, MA) drove the camera and stage movements, and compiled the acquired phase images. Images were subsequently processed as Quicktime movies using Openlab.For each experiment cell cultures were transferred from the incubator to a time-lapse microscope in our laboratory equipped with a heated stage, COJohrei practitioners were selected based on experience and willingness to participate by the Center for the Science of Life, a Johrei organizational body in the United States. Five Johrei practitioners with a minimum of 17 years experience participated in the experiments in teams of two. Johrei treatment was administered by the practitioner teams for a total of four hours, beginning after the four-hour baseline period. This exceptionally long treatment period (4 hours) was chosen as the highest "dose" that was practical within the experimental model. Each practitioner treated the cells for a total of 2 hours per experiment, switching every half hour with the team member. Treatment began with one of the two practitioners being seated in front of the time-lapse microscope and raising one hand toward the cellular target. One hand remained raised toward the cell cultures for the duration of any given Johrei treatment. Johrei treatments were delivered from a distance of 6 – 9 cm, from outside the plexiglass environmental chamber.In collaboration with The Center for the Science of Life, we developed a set of standard mental procedures for practitioners to follow to minimize variability in the mental states among practitioners. These mental cues were used by all practitioners in all experiment. The mental cues can be summarized briefly as: 1) establishing a connection to the divine, 2) consciously relaxing body and mind, 3) visualizing healing energy penetrating the cellular target, 4) taking enjoyment in participating in the experiment, 5) maintaining a feeling of gratitude.Every cell in the initial microscopic field was identified and numbered. For each experiment, we counted the initial number of cells in each of 12 microscopic fields. All numbered cells and their progeny were then tracked for the duration of their onscreen viability using compiled Quicktime movies. Each cell's life events were identified using a modified version of a previously described cell pedigree system . Cells iStatistical analysis was based on a model which categorizes a cell as engaged in any one of four activities at any time: 1) division, resulting in an additional cell (division), 2) death, resulting in the loss of a cell (death), 3) movement out of the microscopic field (emigration), or 4) the cell can remain unchanged . Under tN(t) = N(t-1) exp(λ(t) - μ(t) - ν(t))],where λ(t), μ(t) and ν(t) are the transition probabilities for division, death and emigration, respectively, at time t. We estimated the transition probabilities in one-hour time blocks. For example, the estimate for λ(t) isλ(t) = [ln(N(t) + div(t)) - ln(N(t-1))],where div(t) is the number of divisions during (t-1, t). A similar equation was used for estimating death and emigration transition probabilities at each hour.Statistical analyses focused on two types of comparisons: comparisons within the Johrei treatment experiments, where division and death rates (transition probabilities) pre-treatment were compared with those during and post-treatment; and comparisons between Johrei and control experiments at similar times. Data from each experiment was pooled at 30 minute time intervals. Each of the cellular events (division, death or emigration) occurs infrequently to each cell, so it is necessary to pool results from many cells in order to have nonzero data. Additionally, in instances where few events were recorded due to relatively few cells being observed it was necessary to pool over several time intervals in order to have enough data to perform statistical tests.Overall we documented the behavior of 336 cells in the eight control experiments and 351 cells in the eight Johrei intervention experiments. Initial numbers of cells per microscopic field ranged from 5 to 10; the average cell count per field was 7.0 for controls and 7.3 for Johrei. The numbers of cells per experiment ranged from 40 to 48 with averages of 42.0 and 43.9 for controls and Johrei. Observation over 22 hours showed 312 divisions, 15 deaths and 17 emigrations in the control experiments and 316 divisions, 21 deaths and 7 emigrations in the Johrei experiments. Differences in number of divisions or deaths is not significant (p = 0.19 for divisions and p = 0.37 for deaths based on chi-square test comparing frequencies). While the difference in emigrations is statistically significant (p = 0.03, chi-square test comparing frequencies), this was largely affected by a difference present in the 0–4 hour baseline period making it unlikely that the observed effect is due to Johrei treatment.Experimental treatments (control or Johrei) were confined to a four-hour period starting after collection of four hours of baseline data. During the four-hour treatment period the numbers of divisions were 84 (control), 59 (Johrei); deaths were 4 (control), 5 (Johrei); and emigrations were 0 (control) and 2 (Johrei). Taking into account the numbers of cells at the start of the treatment period, only the difference in divisions is statistically significant (p = 0.018 based on comparing the division rates during the treatment period). This result is based on pooling observations from all cells over the four-hour period and the p-value is based on an assumption that counts observed follow a Poisson distribution. It is possible that counts do not follow a Poisson distribution and that their variability is greater than that expected for Poisson counts. To examine this we calculated division rates separately for each of the eight control experiments and eight Johrei experiments and then compared these rates using the nonparametric Mann-Whitney rank sum test. This analysis confirmed the result based on the total counts (p = 0.016 for Mann-Whitney test).We also tried fitting parametric models to the data in an effort to gain degrees of freedom for performing statistical tests. For example, we tried fitting low order polynomials to division rates over time, but the fits were unsatisfactory, as judged by assuming counts were Poisson distributed with rates predicted from the polynomial fit. The fits were particularly deficient in following the rapid initial rise in division rates over the first four hours of baseline data Figure . We obta-5 compared to 6.8 × 10-5 for the 4–8 hours period. The ratio of these is 1.17 which is not statistically significant (p = 0.41 based on F distribution with numerator and denominator df = 8). This suggests that the discrepancies between the rates during the 4–8 hour period are statistically no larger than those observed during the 0–4 hour period when there were no treatment differences. This comparison requires no assumption of Poisson variability of counts and takes advantage of a priori knowledge that treatment conditions were identical in the first four hours of the experiments. The only assumption is that the variances arise from normally distributed data, so this requirement was tested. A Mann-Whitney comparison of the ranks of the absolute differences in control and Johrei rate during 0–4 hours vs. 4–8 hours give a p-value of 0.92. Thus, there appears to be no evidence that differences in rates of division during 4–8 hours for control and Johrei were any different from those during 0–4 ours. A plot of these absolute differences is shown in Figure The division rates for control and Johrei experiments plotted in Figure Our initial examination of the data suggested that Johrei may have affected the rate of division of cultured human brain tumor cells. This analysis, however, was based on the assumption that the baseline period in both the control and Johrei treated cultures were statistically identical with respect to cell divisions and cell deaths. Subsequent analysis revealed that a significant difference existed in the baseline period between control and Johrei treated samples, with Johrei cultures exhibiting fewer divisions. Taking this into account it appears that there was no observable effect of Johrei on these cell behaviors.The failure to observe evidence of a reproducible cellular response to Johrei treatment is consistent with prior studies in our laboratory evaluating another popular energy medicine modality, external Qigong. Like Johrei, practitioners of external Qigong generally claim the ability to emit or direct healing energy to treat patients. Qigong practices originate from China and are based on the manipulation of a purported healing energy called "Qi." Our prior study investigated the ability of experienced Qigong practitioners to enhance the growth of normal human brain cells in culture as measured by a colony-forming efficiency assay. Following a rigorously designed protocol with randomization, blinding and controls for variability, we did not observe reproducible effects of external Qigong treatment on the growth of these cells . Such "nCell death and proliferation rates of cultured human cancer cells do not appear responsive to Johrei treatment from a short distance.The Center for the Science of Life, a Johrei organizational body in the United States, has provided funding for this work.RT and GY conceived of the study and participated in its design, coordination and implementation. DM performed statistical analysis. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:Johrei Experimental Data. The supplementary file includes the raw data for all experiments, including number of events for cell death, division, and emigration by half-hourly intervals and cumulative totals.Click here for file


Streptococcus pneumoniae. We report the identification of the first putative LT enzyme in S. pneumoniae and discuss its role in pneumococcal peptidoglycan metabolism.The metabolism of bacterial peptidoglycan is a dynamic process, synthases and cleavage enzymes are functionally coordinated. Lytic Transglycosylase enzymes (LT) are part of multienzyme complexes which regulate bacterial division and elongation. LTs are also involved in peptidoglycan turnover and in macromolecular transport systems. Despite their central importance, no LTs have been identified in the human pathogen PEptidoglycan CArbohydrate Cleavage Enzyme). This sequence has been found exclusively in Gram-positive bacteria and gene clusters containing pecace are conserved among Streptococcal species. The PECACE domain is, in some instances, found in association with other domains known to catalyze peptidoglycan hydrolysis.Homology searches of the pneumococcal genome allowed the identification of a new domain putatively involved in peptidoglycan cleavage (PECACE, S. pneumoniae. The probable enzymatic activity deduced from the detailed analysis of the amino acid sequence suggests that the PECACE domain may proceed through a LT-type or goose lyzosyme-type cleavage mechanism. The PECACE function may differ largely from the other hydrolases already identified in the pneumococcus: LytA, LytB, LytC, CBPD and PcsB. The multimodular architecture of proteins containing the PECACE domain is another example of the many activities harbored by peptidoglycan hydrolases, which is probably required for the regulation of peptidoglycan metabolism. The release of new bacterial genomes sequences will probably add new members to the five groups identified so far in this work, and new groups could also emerge. Conversely, the functional characterization of the unknown domains mentioned in this work can now become easier, since bacterial peptidoglycan is proposed to be the substrate.A new domain, PECACE, putatively involved in peptidoglycan hydrolysis has been identified in  N-acetylglucosamine (GlcNAc) and N-acetylmuramyl (MurNAc) residues linked together by β-1,4 glycosidic bonds. Peptides are covalently attached to the lactyl group of the muramic acid and their cross-linking results in the net structure of the peptidoglycan , the β-1,4 glycosidic bond between GlcNAc and MurNAc is hydrolyzed by glucosaminidases and amidases are responsible for the cleavage of the MurNAc-L-alanine bond . This domain sequence was found exclusively in Gram-positive bacterial species, suggesting a significant cellular role. Finally, the PECACE domain is in some instances found in association with other domains, known to catalyze peptidoglycan hydrolysis: this observation reinforces the predicted function of PECACE as participating in peptidoglycan cleavage and represents another example of multifunctional proteins involved in peptidoglycan metabolism.Our interest in the biology of Escherichia coli Slt70 (Soluble Lytic Transglycosylase) has a lysozyme-like fold and its amino acid sequence was employed in a search of Bacilli genomes within the NCBI Conserved Domain Search server [S. pneumoniae translated genome. Subsequently, each of these 34 sequences was compared with the non-redundant protein database using PSI-BLAST with a E-value threshold of 0.005 and 5 sequences showed significant matches with a unique protein in S. pneumoniae. This sequence (accession numbers NP358524, gi:15902974) contains 204 amino acids: the first 21 amino acids are predicted to form a transmembrane anchor and the subsequent 192-residue region is putatively exposed to the extracellular space  and LysG . The sequence alignment between NP358524 and Slt70 is shown in Fig. . The catalytic acid residue in the PECACE domain is most probably Glu61 since it aligns with the catalytic Glu478 residue in the Slt70 sequence  and no sequences from Gram-negative bacteria were retrieved. These sequences were aligned with ClustalW and manually edited. A conserved pattern could be extracted from this alignment: E- [ST]-X-G-X(1,16)-D-X-M-Q- [SA]- [SA]-E- [SG] which was used to search for additional sequences, but no new sequence could be detected from databases, even with a degenerated pattern. PSI-BLAST performed through the GOLD server led to the identification of 10 new sequences from Gram-positive bacteria [S. pneumoniae PECACE domain is shown in Fig. S. pneumoniae PECACE domain, is conserved in all sequences and the following residue is a Ser or Thr in accordance with Slt70 and LysG patterns. In addition, the D(68)VMQS motif in the S. pneumoniae PECACE domain is also well represented in the large majority of sequences with the consensus sequence DI/VMQSSES. Finally, the second motif AYNxG is also conserved while the Ala residue is often replaced by a Ser. In conclusion, the features identified in the S. pneumoniae PECACE domain regarding the potential enzymatic properties of peptidoglycan polysaccharide cleavage are also shared by the similar PECACE domains in Gram-positive bacteria.The 204 amino acid sequence from bacteria . In summpecace genes has been analyzed in a variety of Gram-positive bacteria and a conserved distribution was observed in various streptococci species  but no information about the function of the protein encoded by this locus is available in databases. Transcriptional analysis of these two genes may bring informations about their potential co-regulation, a first stage in deciphering cellular function.The genomic organization of ies Fig. . This feThe PECACE domain is found in a large range of protein architectures, commonly associated with other peptidoglycan hydrolases, suggesting that these proteins have multiple peptidoglycan cleavages activities Fig. . The idePECACE-containing proteins appear to fall into 5 main categories , leading in both cases to cell surface expression.The 19 proteins which contain only the PECACE domain belong to group (i) and harbor either a signal peptide or a transmembrane helix , and no function could be identified for the N-terminus domain preceding the PECACE domain. However the former domain is Lys-rich (14%) suggesting an electrostatic interaction with the peptidoglycan as proposed for B. subtilis endopeptidase [B. cereus ATCC 14579 (NP 833427, gi:30021796). Neither a signal peptide nor a transmembrane anchor have been detected. Furthermore, the domain of unknown function, which is different from the ones identified in groups (iii) and (v) is present in other multimodular proteins of B. cereus, in association with peptidoglycan hydrolysis enzymes. Finally, two sequences share the architecture defining the group (v) which harbor CHAP-Nlpc/P60 and Peptidase M37 domains [Staphylococcus species which cleaves the pentaglycine bridge in the peptidoglycan [Bacillus anthracis plasmid pXO1 and is required for synthesis of various anthrax toxin proteins [Bacillus cereus ATCC 10987 plasmid pBc10987 (NP 982030, gi:44004362) and contains, in addition to CHAP-Nlpc/P60, Peptidase M37 and PECACE domain as well as an extra sequence to which no function has been attributed but with significant similarity with a B. anthracis plasmid pXO1 sequence (NP 652874, gi:21392794) [The CHAP-Nlpc/P60 domain is commonly associated with the PECACE domain in different modular organizations, namely in groups (ii), (iii), and (v) ,19,27. T enzymes ,19. Howe strains . Proteineptidase . Group  .S. pneumoniae. The probable enzymatic activity deduced from the detailed analysis of the amino acid sequence suggests a LT-type or goose lyzosyme-type mechanism; we are currently characterising the enzymatic properties and cellular role of the PECACE domain from S. pneumoniae. This new putative pneumococcal peptidoglycan cleavage enzyme differs largely from the other hydrolases already identified in this bacteria. Indeed, LytA, LytB, LytC and CBPD proteins are all bound to the cell wall choline residues and thus expressed at the cell surface. The presence of a signal peptide within the amino acid sequence of PcsB suggests that it is either exposed on the cell surface or secreted. On the contrary, the pneumococcal NP358524 protein displaying the PECACE domain is embeded in the cytoplasmic membrane by a hydrophobic helix. The physiological role of this membranous peptidoglycan cleavage enzyme might differ from the other peptidoglycan hydrolysing enzymes.In summary, a new domain named PECACE, putatively involved in peptidoglycan cleavage has been identified in Interestingly, the PECACE domain has only been found in Gram-positive bacteria. It is tempting to speculate that the multilayered structure of Gram-positive peptidoglycan relates to the PECACE putative activity.The architecture of multimodular proteins containing the PECACE domain is another example of the pattern of multiple activities harbored by many peptidoglycan hydrolases, probably needed for the regulation of peptidoglycan metabolism. The release of new bacterial genomes sequences will probably add new members that will complete the five groups identified so far in this work and new groups could also emerge. Conversely, the functional characterization of the unknown domains mentioned in this work should now be easier, as their substrate, the peptidoglycan, is now identified.[ with (E) value threshold of 0.005 [[[. Identification of domains associated with PECACE proteins was realized using NCBI Conserved Domain Search [[ and SignalP-2.0 servers  respectively [The non-redudant database of protein sequences  and whole bacterial genomes sequences  was searof 0.005 . Multiplf 0.005 [ followed 0.005 [[. Conservn Search  and Pfam Search [. Finallyectively ,38.OD conceived of the study and participated in the sequences alignment. EP carried out the sequences analysis and the writing of the manuscript with AMDG. TV coordinated the study. All authors read and approved the final manuscript.


In this study we evaluated if salivary flow and composition as well as dental caries are oral markers of disease severity in pSS.in 20 patients fulfilling the American-European Consensus criteria for pSS and 20 age-matched healthy controls whole and parotid saliva flow rates and composition, measures of oral dryness, scores of decayed, missing and filled tooth surfaces (DMFS), periodontal indices, oral hygiene, and dietary habits were examined.in pSS, salivary flow rates, pH, and buffer capacities were lower, and DMFS, salivary sodium and chloride concentrations higher than in the healthy controls. DMFS also correlated inversely to salivary flow rates and positively to oral dryness. Apart from slightly increased gingival index, and more frequent dental visits in pSS, the periodontal condition, oral hygiene or sugar intake did not differ between these two groups. In pSS, findings were correlated to labial salivary gland focus score (FS) and presence of serum-autoantibodies to SSA/SSB (AB). The patients having both presence of AB and the highest FS (>2) also had the highest salivary sodium and chloride concentrations, the lowest salivary phosphate concentrations, lowest salivary flow rates, and highest DMFS compared to those with normal salivary concentrations of sodium and chloride at a given flow rate.the salivary changes observed in some pSS patients reflect impaired ductal salt reabsorption, but unaffected acinar transport mechanisms, despite low salivary secretion. Our results suggest that changes in salivary flow and composition as well as dental caries may serve as potential markers of the extent of autoimmune-mediated salivary gland dysfunction in pSS. The study also indicates that the ductal epithelium is functionally affected in some pSS patients, which calls for future pathophysiological studies on the mechanisms underlying this impaired salt reabsorption. Primary Sjögren's syndrome (pSS) is a common systemic autoimmune disease that mainly affects middle-aged women. The exact aetiology remains elusive, and appears multifactorial. The disease is characterised by a chronic periductal lymphocytic infiltration of the exocrine glands, predominantly of the lacrimal and salivary glands. The chronic inflammation is assumed to lead to glandular tissue destruction, resulting in keratoconjunctivitis sicca and hyposalivation and associated symptoms of ocular and oral dryness ,2.The salivary dysfunction in pSS is of significant clinical importance and may cause chronic oral discomfort as well as compromised oropharyngeal functions -5. SubseThe American-European Consensus Classification Criteria for pSS include evaluation of salivary gland dysfunction by means of parotid sialography, salivary gland scintigraphy, whole saliva sialometry and labial salivary gland biopsy as well as questionnaire concerning symptoms of oral dryness . The purThe study included 20 randomly selected patients with pSS, who attended the Department of Oral Medicine, University of Copenhagen, for routine follow-up examinations. They were diagnosed according to the Copenhagen criteria, but also met the American-European Consensus Classification Criteria for pSS ,14. All In order to understand the underlying salivary pathophysiology in pSS, the study also included 20 healthy controls selected among persons attending the Institute of Odontology for dental treatment to obtain reference values of normalcy. The selection was based on the requirements that controls had no present or past medical history of systemic disease, did not take any medication including contraceptives and hormonal replacement, had no current use of tobacco products, and matched the pSS patients with regard to age.One examiner (AMLP) conducted the whole saliva collections, interviews, and oral clinical examinations. About 2 hours after collection of whole saliva, another examiner (AB) conducted collections of parotid saliva. In order to minimize the influence of circadian cycle on salivary secretion and composition all procedures were carried out in the same order and at a fixed time of the day, i.e. between 9.00 and 11.45 a.m. The local Danish Ethical Committees approved the study protocol, and all participants completed an informed consent form according to the Declaration of Helsinki. The number of decayed, missing and filled surfaces (DMFS) was recorded excluding third molars as previously described in details . Each su2 was used [Unstimulated whole saliva (UWS) and paraffin-stimulated whole saliva (SWS) were sampled over a 15-min and 5-min period, respectively, as described previously . Unstimuwas used . Stimulawas used . The subConcentrations (mM) of sodium, potassium and total calcium were determined by atomic absorption spectroscopy ,17. ConcCO2, buffer capacity, and saturation with regard to hydroxyapatite Parotid saliva pH and PCO2 were determined on an ABL 605 blood gas analyser (Radiometer™), and the HCO3- concentration was calculated from the pH and Pco2 values as previously described [3- and phosphate buffer systems, was calculated individually for each saliva sample at the pH value of the sample [Parotid saliva pH, Pescribed . The pare sample . BrieflyB]/[C]) * (1-([CB]/[C]))2.3 [C] * ([CB]) states the concentration of the base in the buffer system. The concentrations of the bases was calculated as previously described [2PO4- [3- and phosphate buffer systems are in this study denoted as saliva β. At pH values above 5  the contribution from the protein buffer system, relative to the HCO3- and phosphate buffer systems, was considered negligible [Where ([C]) states the total concentration of the buffer system and ([Cescribed  and the escribed ,17 and 6d [2PO4- . The sumgligible  and therHAP) of saliva with respect to hydroxyapatite, i.e. the calcium phosphate salt and main mineral of the tooth tissues, was calculated according to the method described by Schmidt-Nielsen [HAP) was calculated from the saliva p [Ca2+], p [HPO42-], and p [H+]. The negative logarithm of the solubility product of hydroxyapatite (pSPHAP) was calculated by the constant given by Schmidt-Nielsen [HAP acceptable. Finally, the critical pH of parotid saliva, i.e. the pH value at which saliva is saturated (i.e., neither super- nor undersaturated) with respect to hydroxyapatite  was calculated.The degree of saturation . Fisher's test (less than ten in one category) and the chi-squared test (more than ten) were used for analysis of distributions between the two groups. Associations between variables were analysed by the Spearman rank order correlation analysis (rs). In order to find the best predictor for a given outcome, multiple regression analysis was used with stepwise backward elimination with the adjusted R-squared values given. Significance was selected at a level of P ≤ 0.05.Differences in the salivary and clinical parameters between the patient and control groups were analysed by Wilcoxon rank-sum test (categorised variables) and two-sampled rs = -0.50, P = 0.025), but only a tendency toward a relationship between the oral dryness and UWS, UPS and SPS. On the other hand, in both groups as a whole, displaying large variations in oral dryness and salivary flow rates, the subjective measures were significantly inversely correlated to UWS (rs = -0.83, P < 0.001), SWS (rs = -0.81, P < 0.001), UPS (rs = -0.74, P < 0.001), and SPS (rs = -0.77, P < 0.001).Table rs = 0.33, P = 0.04).The results of the clinical examination are shown in Table rs = 0.79, P < 0.001 and rs = 0.45, P < 0.05, respectively), but only in pSS a mutual correlation was obtained between UPS and SPS (rs = 0.74, P < 0.001).As shown in Tables In 10, 9, 13 and 7 cases, respectively, volume of UWS, SWS, UPS and SPS samples from pSS patients were insufficient for full sialochemical assessment. In pSS, the concentrations of sodium were significantly higher in both whole and parotid saliva as compared to the healthy controls. Similar results were obtained for chloride concentrations (except for the UPS) Tables . RegardiHAP) in their UPS than the controls. In pSS, the pH in UPS was in fact only 0.1 pH units from their critical pH. Overall, the salivary β and DSHAP were reduced due to low pH, bicarbonate and phosphate concentrations. In pSS, PCO2 of SPS was lower than in that of the healthy controls (P = 0.02). Nevertheless, at corresponding parotid flow rates, be it stimulated or not, the relations between the flow rates, the saliva pH and the bicarbonate concentrations were similar to those of the healthy controls . Also the prevalence of dental treatment, i.e. the number of filled surfaces relative to the total number of present tooth surfaces, was significantly higher in the patients (55 ± 27%) than in the controls (25 ± 14%) (P < 0.001). However, no significant differences were obtained for the number of decayed surfaces between the patients and controls.As shown in Table rs = 0.63, P < 0.001). As shown DMFS increases with increasing age (per year) and increasing complaints of oral dryness, but decreases with increasing salivary flow rates.Table rs = 0.53, P < 0.05) and the prevalence of dental treatment (rs = 0.51, P < 0.05). In addition, the prevalence of dental treatment increased with the duration of pSS (rs = 0.49, P < 0.05), independently of the patient's age.In the pSS patients, regardless of their age, the complaint of oral dryness, but not the actual salivary flow rate, was associated with dental status (DMFS). The lack of significant correlation between flow rate and DMFS may be ascribed to the narrow window of flow rates in pSS. Scores of oral dryness correlated significantly with the total DMFS (rs = -0.53, P < 0.05), SWS (rs = -0.68, P < 0.01), SPS (rs = -0.57, P < 0.01), but not to UPS. Focus scores were not correlated to oral dryness, time since pSS diagnosis, and duration of disease symptoms. It is noteworthy, however, that the patient group exhibited large variability with regard to time since diagnosis and age (Table rs = 0.61, P < 0.05 and rs = 0.71, P < 0.01). Although highly increased sodium and chloride concentrations were found in UPS as well, the number of observations was too small to generate statistical significance due to the sample volumes that did not allow for sialochemistry (Table vs. 0.7, respectively, P < 0.05), presence of serum autoantibodies (n = 14), highest concentrations of salivary sodium and chloride, but lowest salivary concentrations of total phosphate compared to patients with UWS ≥ 0.05 ml/min. Pooling data of UPS and SPS for the pSS group allowed us to compare profiles of the patients with high sodium and chloride concentrations to those with low ones. The results of this analysis revealed that pSS with more than 40 mM sodium in their parotid saliva also had significantly higher focus scores as well as presence of serum autoantibodies, than pSS patients below this value (P < 0.01). The former also tended to have lower parotid flow rates, more decayed tooth surfaces and to be younger than the other pSS patients.In the pSS group, the focus scores (which ranged from 0 to 4) were significantly inversely correlated to UWS , thereby protecting the teeth against demineralisation. The buffer systems responsible for the human saliva buffer capacity include the bicarbonate, phosphate and protein systems ,36-38. IIn this study, the parotid saliva buffer capacity was calculated individually for each pSS patient and healthy control based on the saliva bicarbonate and phosphate concentrations at the respective saliva pH values. This calculation gives an estimate of the buffer capacity of the saliva at the time it is secreted from the parotid gland. In the pSS patients, the buffer capacity of UPS was significantly lower than in the healthy controls, mainly due to the low pH value and bicarbonate concentration in saliva caused by the low flow rates. Moreover, in pSS most of the pH values of UPS were below the relevant pK values of both the bicarbonate and phosphate buffer systems. As compared to healthy controls, the pSS patients will therefore experience far more abundant pH drops in their saliva if exposed to acidic challenges leading to a higher risk of tooth demineralisation. Apart from a low buffer capacity, and thereby impaired ability to maintain a non-acidic saliva pH, the pSS patients also had a significantly lower degree of saturation with respect to HAP in their saliva Table . Thus, i3- concentration and saliva pH did not differ between the two groups  and secrete (at high secretion rates due to increased metabolic turnover of the gland).Despite the differences between pSS patients and healthy controls in sodium and chloride concentrations at comparable low flow rates, stimulated or not, the HCOups Fig. . The traThis study demonstrated a tendency towards lower total phosphate concentrations in pSS patients than in healthy controls. Previous studies have found significantly reduced phosphate concentrations in stimulated parotid and SM/SL saliva of patients with SS compared to healthy controls and patients with conditions resembling SS -42. It sOur sialochemical results are interpreted within the frame of the classical two-stage model of saliva formation . Under nDespite the low salivary flow rates seen in the pSS, the acinar transport mechanisms involved in the formation of primary saliva seem to be unaffected by the glandular lymphocytic infiltration. Accordingly, concentrations of potassium, total calcium, total protein and amylase activity in whole and parotid saliva did not differ from those of the healthy controls, which is in agreement with previous reports ,45. FurtThe changes in salivary composition indicate that the duct epithelium, and mainly the striated duct epithelium, cannot effectively reabsorb the high concentrations of sodium and chloride of the primary saliva in some of the pSS patients, despite low salivary flow rates. The pSS patients who exhibited high concentrations of sodium and chloride were also characterised by having the lowest flow rates, the highest focus score (FS) and highest concentrations of serum autoantibodies (AB) in addition to a tendency of being younger than the pSS patients with normal salivary concentrations of sodium and chloride. Overall, the subgroup of pSS patients with the highest concentrations of salivary sodium and chloride and lowest total phosphate concentrations appeared to be more severely affected by pSS having more exocrine and non-exocrine disease manifestations than those without these salivary changes supporting previous observations . It shouin vitro study on isolated human acini and duct segments from pSS patients have shown that these cells possess functional receptor systems and normal response in changes in the intracellular free calcium concentration upon maximal secretagogue stimulation [via amiloride-sensitive epithelial sodium channel (ENaC) is regulated by circulating adrenal mineralocorticoids, e.g. aldosterone [In pSS, the salivary gland histopathology is characterised by periductal lymphocytic infiltration and acinar destruction. The duct epithelium, however, appears relatively unaffected by the lymphocytic infiltration, which contrasts the observed salivary changes in pSS. On the other hand, the discrepancy may be explained by morphological differences between the labial salivary glands, which predominantly consist of mucous acini and have a very short duct system, and the parotid glands, which comprise serous acini and have long duct system. Nevertheless, it has been stated that the histopathological changes of the labial salivary glands mimic those of the parotid glands ,50. It hmulation . The facosterone  could alThe results of this study indicate that specific sialometric and sialochemical glandular changes, particularly changes in sodium and chloride concentrations, may serve as oral markers of disease severity in pSS. The question arises whether pSS represents a continuum of patients with different stages of disease/affection of salivary glands or different diseases affecting the salivary gland tissues. There is great need of disease assessment and outcome markers in pSS. The hypotheses generated from our results on changes in salivary flow and composition as well as high caries experience as potential markers of the extent of autoimmune-mediated salivary gland dysfunction in pSS therefore need to be tested in a large prospective cohort study including patients with early to long-standing disease. In addition, the mechanisms underlying the impaired ductal salt reabsorption observed in the pSS patients with presence of both labial salivary gland focus score and serum-autoantibodies need to be further elucidated in future pathophysiological studies.SS = Sjögren's syndrome; pSS = primary Sjögren's syndrome; FS = focal lymphocytic infiltration in the labial salivary glands; UWS = unstimulated whole saliva flow rate; SWS = stimulated whole saliva flow rate; UPS = unstimulated parotid saliva flow rate; SPS = stimulated parotid saliva flow rate; AB = presence of serum autoantibodies to Ro (SSA) and/or La (SSB) antigens; DMFS = decayed, missing and filled tooth surfaces; PI and GI = plaque and gingival indices; PPD = periodontal probing pocket depth; HAP = hydroxyapatite.The author(s) declare that they have no competing interests.All three authors participated in the design of the study and the statistical analysis. AMLP attended coordination of the study and conducted the whole saliva collections, interviews, oral clinical examinations and labial salivary gland biopsies. AB performed the parotid saliva collections and sialochemical analyses. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Young women are a group at high risk of weight gain. This study examined a range of perceived personal, social and environmental barriers to physical activity and healthy eating for weight maintenance among young women, and how these varied by socioeconomic status (SES), overweight status and domestic situation.In October-December 2001, a total of 445 women aged 18–32 years, selected randomly from the Australian electoral roll, completed a mailed self-report survey that included questions on 11 barriers to physical activity and 11 barriers to healthy eating . Height, weight and socio-demographic details were also obtained. Statistical analyses were conducted mid-2003.The most common perceived barriers to physical activity and healthy eating encountered by young women were related to motivation, time and cost. Women with children were particularly likely to report a lack of social support as an important barrier to physical activity, and lack of social support and time as important barriers to healthy eating. Perceived barriers did not differ by SES or overweight status.Health promotion strategies aimed at preventing weight gain should take into account the specific perceived barriers to physical activity and healthy eating faced by women in this age group, particularly lack of motivation, lack of time, and cost. Strategies targeting perceived lack of time and lack of social support are particularly required for young women with children. One gn (2.3%) . This rin (2.3%) .In an effort to reverse the current global epidemic of overweight and obesity, strategies to promote increased physical activity and to encourage healthy eating have been promoted in many countries -15. In AMost existing studies examining perceived barriers to physical activity and healthy eating have focused on the general population,,22-25. wAs well as perceiving different barriers to those faced by other groups in the population, the perceived barriers to increasing physical activity and improving diet that young women face may vary according to their social and personal circumstances. For example, having children is likely to impact on a women's ability to adopt healthy habits ,28,29. IIn order to develop appropriate and effective obesity prevention strategies for young women it is important to understand the barriers they perceive in attempting to control their weight. The aim of this study was to examine perceptions of a range of personal, social and environmental barriers to physical activity and healthy eating, specifically related to weight maintenance, among young women, and how these vary by domestic situation, SES and overweight status.A total of 445 women provided data for this study. Initially, a sample of 1200 women aged 18–32 years was selected from the Australian Electoral Roll using a stratified random sampling procedure, with strata based on the number of eligible cases in each of the eight States/Territories of Australia. As voting is compulsory for Australian adults, the electoral roll provides a complete record of population data on Australian residents aged 18 years and over. Excluding those who had moved and left no forwarding address, the study achieved a response rate of 41% (462 women participated), which is comparable to response rates reported in similar postal surveys with this age group ,34. DataThe socio-demographic characteristics of the sample are reported in full elsewhere . BrieflyA questionnaire was developed and pilot-tested with a convenience sample of 10 women in the same age group as participants. The questionnaire, a study description, an invitation to participate, a consent form and a reply-paid envelope for returns were mailed to the study sample of women in October 2001. Non-responders were sent a reminder postcard two weeks later and a second reminder with replacement questionnaire a further three weeks later.The participants completed the following questions.No-one, I live alone; Partner/spouse; Own children; someone else's children; parents; brothers/sisters; Other adult relatives; and Other adults who are not family members. This was subsequently re-categorized as living with parental family; living alone/share 'flatting'; living with partner (no children); or living with children (including those living with partner and child/ren, and single mothers). Education level  was subsequently categorized as tertiary educated or not tertiary educated and used as an indicator of SES.The socio-demographic questions included domestic situation (household composition) and education. Domestic situation was assessed by asking 'Who lives with you?' with response options: 2)). Self-reported height and weight have been shown to provide a reasonably valid measure of actual height and weight for the purpose of investigating relationships in epidemiological studies [Women were asked to self-report their height and weight and this information was used to calculate body mass index (BMI = weight (kg)/height , participants were asked the following two open-ended questions: 'What is the one thing that makes it hardest for you to be physically active?' and 'What is the one thing that makes it hardest for you to eat a healthy diet?'Analyses were conducted mid-2003, using SPSS version 11.0.0 statistical software. . InitialTwo separate exploratory factor analyses using SPSS FACTOR were performed with the 11 barriers to physical activity and the 11 barriers to healthy eating, to identify underlying patterns of relationships among individual items, and to reduce and simplify the items in order to facilitate subsequent analyses. Principal components analysis with varimax rotation (since factors were not correlated) was used. For any cross-loading items (i.e. items that had loadings of greater than 0.4 on more than one factor), only the higher loading was taken into account when calculating final factor scores. Inter-item reliability for each factor was assessed by Cronbach's α coefficients. Kaiser's measure of sampling adequacy was used to confirm the appropriateness of factor analysis . StandarTable Table Consistent with women's responses to the closed-ended questions, the most important perceived barriers to physical activity reported in response to the open-ended questions were lack of time due to work, study or family commitments (78%), lack of motivation (37%) and childcare issues (25%). The most important perceived barriers to healthy eating related to taste (24%); lack of time (21%); lack of motivation (13%); and the perception that healthy foods are inconvenient or expensive (13%).The factor analysis of the perceived barriers to physical activity revealed three interpretable factors Table  with eigThe principal components analysis of the 11 barriers to healthy eating resulted in two distinct interpretable factors with eigenvalues greater than one Table . The CroMean factor scores did not vary according to women's overweight status or SES. Mean factor scores did differ significantly by domestic situation for two factors: social support barriers to physical activity and social and environmental barriers to healthy eating  or overweight/obese (31%), 18% of the women were underweight . It shouThe findings of this study highlight the need for health promotion strategies that provide increased motivation, support and skills to enable young women to shop and prepare healthy, quick and inexpensive meals. Similarly, the findings suggest a need to promote more time-efficient physical activity alternatives. Additional strategies that recognize the perceived barriers to physical activity and healthy eating faced by young women with children are particularly required.The authors declare that they have no competing interests.SA conducted the literature review, final statistical analyses and early drafts of the results and conclusions sections. KB and DC conceived the study, design and measures, collected the data, coordinated the analyses and participated in the write-up of all sections. NW conducted preliminary analyses and drafting of early results. VI contributed to drafting the final manuscript.


High fruit and vegetable intake is known to reduce the risk of colon cancer. To improve understanding of this phenomenon the action of different phytochemicals on colon cells has been examined. One such compound is quercetin that belongs to the group known as flavonoids. The purpose of this study was to determine the influence of quercetin on the proteome of the SW480 human colon adenocarcinoma cell line, specifically to identify proteins that could be the molecular targets of quercetin in its amelioration of the progression of colon cancer. To this end, two-dimensional gel electrophoresis and mass spectrometry were used to identify proteins that underwent a change in expression following treatment of the cells with 20 μM quercetin. This could elucidate how quercetin may reduce the progression of colon cancer.Quercetin treatment of the SW480 human colon cancer cells was found to result in the decreased expression of three proteins and the increased expression of one protein. The identified proteins with decreased expression were type II cytoskeletal 8 keratin and NADH dehydrogenase Fe-S protein 3. The other protein with decreased expression was not identified. The protein with increased expression belonged to the annexin family.Several proteins were determined to have altered expression following treatment with quercetin. Such changes in the levels of these particular proteins could underlie the chemo-protective action of quercetin towards colon cancer. Colorectal cancer is the third most common cancer diagnosed both in men and in women in the United States . The Amein vitro and in vivo have suggested that quercetin may have a protective role against breast [Genetic factors account for only 10% of colorectal cancers ,4 and tht breast , lung [1t breast , liver [t breast , ovariant breast  and colot breast -17 canceKnowledge of how quercetin protects against cancer in general and colorectal cancer in particular could be gained by examining how quercetin affects the proteome of colon cancer cells. Specifically, the influence of quercetin on protein expression in the SW480 colon adenocarcinoma cell line could be instructive in elucidating the mechanisms underlying the protective role of the flavonoid against colon cancer. This would strengthen the scientific evidence for advocating a diet rich in fruit and vegetables to decrease the risk of developing colon cancer. Moreover, an identification of those proteins affected by quercetin could enhance understanding of the roles of these proteins in colon neoplasia. Use of proteomic techniques was therefore adopted in this study to determine the influence of quercetin treatment on protein expression in SW480 colon cancer cells. Quercetin treatment was found to result consistently in the decreased expression of three proteins and the increased expression of one protein. All, except one of the down-expressed proteins, were identified by mass spectrometry. Thus protein targets that could be the molecular basis of inhibition of colon cancer by quercetin were obtained.2 canted-neck flasks in 15 ml medium and incubated at 37°C without CO2. They were subcultured once per week at a ratio of 1:4.SW480 human colon carcinoma cells (ATCC, Rockville, MD) were grown in Leibovitz's L-15 medium with 2 mM L-glutamine (ATCC, Rockville, MD), supplemented with 10% fetal bovine serum (Equitech-Bio Inc., Kerrville, TX). Cells were maintained in 75 cmWhen cells were about 90% confluent at seven days after passage the medium was discarded and replaced with medium containing 20 μM quercetin (Sigma, St. Louis MO). Cells were incubated for 48 h in the quercetin-containing medium at 37°C in air.Following incubation of the cells in quercetin for 48 h the medium was discarded and the cells washed three times for 1 min each time with phosphate-buffered saline. After complete removal of the final wash buffer, to each culture flask was added 240 μl boiling sample buffer I (0.3% sodium dodecyl sulfate (SDS), 200 mM dithiothreitol (DTT), 50 mM Tris-HCl, pH 8.0). The lysed cells were scraped together using a cell scraper (Fisher, Pittsburgh PA). The lysate from each culture flask was transferred to a 1.5 ml microfuge tube and heated for 5 min at 100°C. After chilling the tube on ice 24 μl (1/10 volume) of sample buffer II (50 mM magnesium chloride, 0.1% DNAse I, 0.025% RNAse A, 0.5 M Tris-HCl, pH 8.0) was added. Acetone was added to 80% (v/v) and the tube incubated on ice for 20 min. After centrifugation at 12,000 rpm for 10 min the supernatant was discarded and the pellet resuspended in 240 μl freshly prepared immobilized pH gradient (IPG) sample buffer (7 M urea, 2 M thiourea, 4% CHAPS, 1% DTT and 2% pH 3–10 ampholytes). The protein concentrations of the suspensions were measured using the method of Bradford with Bio-Rad reagent and bovine plasma gamma globulin as standard (Bio-Rad, Hercules, CA).As the first dimension of two-dimensional electrophoresis Bio-Rad pH 3–10 immobilized pH gradient (IPG) strips were used to separate the cell proteins according to their isoelectric points. A volume of the cell protein solution containing 2 mg protein was mixed with rehydration buffer (6 M urea, 2 M thiourea, 2% CHAPS, 0.4% DTT and 0.5% pH 3–10 ampholytes) for a final volume of 300 μl per IPG gel. The IPG strips were loaded with the protein sample and the strips passively rehydrated for 16 h. Isoelectric focusing of the strips was at 250 V for 15 min followed by rapid ramping to10,000 V for 3 h and maintenance at the peak voltage for another 60,000 Vh. Current was limited to 50 μA per gel.The IPG strips were equilibrated with 6 M urea, 30% glycerol, 2% SDS, 1.55 M Tris, 2 mM tributylphosphine (TBP) and 0.00125% bromophenol blue (BPB) for 25 min with shaking at room temperature. The strips were rinsed in cathode buffer and applied to the top of 12% acrylamide slab gels. The cathode buffer contained 50 mM Tris, 384 mM glycine and 6.9 mM SDS. Low-melting point agarose (1% in cathode buffer) was layered over the strips. The anode buffer contained 25 mM Tris, 192 mM glycine and 3.5 mM SDS. The buffers were chilled to 4°C prior to use. A cooling plate maintained the system (Genomic Solutions, Ann Arbor, MI) at low temperature. The gels (22 cm × 22 cm × 1 mm) were run at 20 W per gel until the BPB dye front had migrated to within 1 cm from the bottom of the gel. The gels were stained with Coomassie blue.Second dimension gels were analyzed by Phoretix software (Nonlinear Dynamics, Newcastle, UK). Comparison between gels was achieved using normalized spot volumes. To begin with, differences greater or equal to 1.5-fold were considered to be significant. If these differences were subsequently reproduced in additional experiments, despite possibly being of lower magnitude, they were held to be consistent.Differentially expressed protein spots were excised from the gels and digested with trypsin as reported previously . Each ge were used to determine protein identification. The NCBInr database, i.e. the non-identical nr protein database of the National Center for Biotechnology Information, was utilized for the search.MS/MS ions produced by MALDI-TOF from the tryptic peptides and the results of a Mascot search Fig. The protein spots that were differentially expressed following quercetin treatment were excised from the gels and digested with trypsin. The tryptic digests were subjected to matrix-assisted laser desorption and ionization-time of flight (MALDI-TOF) mass spectrometry. The spectra were analyzed and the data entered into appropriate databases to identify the proteins. Table Four proteins were found to have their expression consistently altered on quercetin treatment of SW480 colon carcinoma cells. Three of these proteins were down-regulated and one was up regulated following exposure to quercetin. Using mass spectrometry three of the proteins were identified. Those that were down-regulated were type II cytoskeletal 8 keratin and NADH dehydrogenase (ubiquinone) Fe-S protein 3. The up-regulated protein belonged to the annexin family.Type II cytoskeletal 8 keratin (keratin 8) in another proteomic study has been found to have a significantly lower abundance in the normal mucosa compared with the adjacent colon tumor for one specific patient for two out of three gel protein features identified as keratin 8 . For theFurther support for the reduction in expression of type II cytoskeletal 8 keratin following quercetin treatment of SW480 colon cancer cells being reflective of decreased neoplasia is derived from a proteomic analysis of lung adenocarcinomas . CytoskeNADH dehydrogenase (ubiquinone) Fe-S protein 3 is a component of complex 1 of the mitochondrial electron transport chain. It is involved in transfer of electrons from NADH to ubiquinone in the respiratory chain. A similar component of complex 1 of the respiratory chain, NADH-ubiquinone oxidoreductase, has been determined from a proteomic analysis to be present in colon tumor tissue and the surrounding normal mucosa . InteresFollowing quercetin treatment, the only protein to be up-regulated belonged to the annexin family. In another proteomic study annexins I, III, IV and V have been determined to have a greater abundance in normal mucosa compared with neighboring tumor tissue . Thus thThree proteins have been identified as potential molecular targets for the proposed action against colon cancer of quercetin the plant flavonoid. The application of proteomic techniques demonstrated the response of these proteins to quercetin treatment of colon cancer cells. Other research in the field supported the response of each of these proteins to quercetin. This serves to validate the previous work. Furthermore, the responses could be rationally described in terms of an anti-cancer action. This strengthens earlier findings of quercetin's protection against colon cancer using cell culture and animal models. A basis is thus provided for further research with quercetin and perhaps even advancement to studies with humans. An intriguing aspect to consider is whether quercetin could form the basis of directed drug design to yield drugs with greater efficacy against the identified molecular targets and thereby provide an effective treatment of colon cancer.NADH, nicotinamide adenine dinucleotide, reduced;MALDI-TOF, matrix-assisted laser desorption and ionization-time of flight;MS, mass spectrometry2-D, two-dimensional;SDS, sodium dodecyl sulfate;DTT, dithiothreitol;IPG, immobilized pH gradient;CHAPS, 3-[(3-cholamidopropyl) dimethylammonio]-1-propane-sulfonate;TBP, tributylphosphine;BPB, bromophenol blue;DMSO, dimethylsulfoxide;NCBI, National Center for Biotechnology Information.The authors declare that they have no competing interests.MFM treated the cells, performed the two-dimensional electrophoresis and gel analysis, submitted protein spots for mass spectrometry, undertook the literature search on the identified proteins, drafted the manuscript, submitted the manuscript and completed all the necessary revisions to make it acceptable for publication. KK carried out trypsin digestion of the protein spots and undertook the mass spectrometry. RO provided oversight for the mass spectrometry. JLH and AG participated in conception and design of the study. All the authors read and approved the final manuscript.


Plasmodium falciparum is the causative agent of the most burdensome form of human malaria, affecting 200–300 million individuals per year worldwide. The recently sequenced genome of P. falciparum revealed over 5,400 genes, of which 60% encode proteins of unknown function. Insights into the biochemical function and regulation of these genes will provide the foundation for future drug and vaccine development efforts toward eradication of this disease. By analyzing the complete asexual intraerythrocytic developmental cycle (IDC) transcriptome of the HB3 strain of P. falciparum, we demonstrate that at least 60% of the genome is transcriptionally active during this stage. Our data demonstrate that this parasite has evolved an extremely specialized mode of transcriptional regulation that produces a continuous cascade of gene expression, beginning with genes corresponding to general cellular processes, such as protein synthesis, and ending with Plasmodium-specific functionalities, such as genes involved in erythrocyte invasion. The data reveal that genes contiguous along the chromosomes are rarely coregulated, while transcription from the plastid genome is highly coregulated and likely polycistronic. Comparative genomic hybridization between HB3 and the reference genome strain (3D7) was used to distinguish between genes not expressed during the IDC and genes not detected because of possible sequence variations. Genomic differences between these strains were found almost exclusively in the highly antigenic subtelomeric regions of chromosomes. The simple cascade of gene regulation that directs the asexual development of P. falciparum is unprecedented in eukaryotic biology. The transcriptome of the IDC resembles a “just-in-time” manufacturing process whereby induction of any given gene occurs once per cycle and only at a time when it is required. These data provide to our knowledge the first comprehensive view of the timing of transcription throughout the intraerythrocytic development of P. falciparum and provide a resource for the identification of new chemotherapeutic and vaccine candidates. Plasmodium genesA tight cascade of gene regulation during the lifecycle of the malaria parasite in human blood cells suggests new functions for many  Plasmodium. Of these four species, Plasmodium falciparum is responsible for the vast majority of the 300–500 million episodes of malaria worldwide and accounts for 0.7–2.7 million annual deaths. In many endemic countries, malaria is responsible for economic stagnation, lowering the annual economic growth in some regions by up to 1.5%  lack sequence similarity to genes from any other known organism  oligonucleotides as representative elements for predicted ORFs in the sequenced genome (strain 3D7)  . Using tP. falciparum IDC was generated by measuring relative mRNA abundance levels in samples collected from a highly synchronized in vitro culture of parasites. The strain used was the well-characterized Honduran chloroquine-sensitive HB3 strain, which was used in the only two experimental crosses carried out thus far with P. falciparum , and the trophozoite-specific gene, dihydrofolate reductase–thymidylate synthetase (dhfr-ts) (asl) (r) is greater than 0.90 for 68% (0.75 for 86%) of the transcripts represented by multiple oligonucleotides with detectable expression during the IDC (r) for these features is 0.98±0.02.To measure the relative abundance of mRNAs throughout the IDC, total RNA from each timepoint was compared to an arbitrary reference pool of total RNA from all timepoints in a standard two-color competitive hybridization . The tradhfr-ts) B and 1C.s) (asl) D, displa the IDC . Cases iP. falciparum IDC dataset, a similar computational approach was taken. We performed simple Fourier analysis, which allowed us to calculate both the apparent phase and frequency of expression for each gene during the IDC (see Periodicity in genome-wide gene expression datasets has been used to identify cell-cycle-regulated genes in both yeast and human cells . Owing t IDC see . The faseba175 (peak B), dhfr-ts (peak C), and asl (peak D) are indicated. It is striking that 79.5% of the expression profiles have a very high score (greater than 70%). For comparison, we applied our FFT analysis to the Saccharomyces cerevisiae cell cycle data, yielding only 194 profiles (3.8%) above a 70% score  or that lack differential expression throughout the IDC. Since the majority of the profiles display a single low-frequency peak in the power spectrum, we have taken advantage of this feature to classify profiles, similar to the application of a low-pass filter in signal processing. By measuring the power present in the peak frequency window (the main component plus two adjacent peaks) relative to the power present at all frequencies of the power spectrum, we were able to define a score (percent power) that we have used to stratify the dataset. The resulting distribution of expression profiles, scored in this way, is shown in 0% score . In addi0% score F. The raP. falciparum . In one case, chr5.glm_185 overlaps with the manually annotated ORF PFE0850w, which is found on the opposite strand. Oligonucleotide elements for both of these ORFs are present on the array. The oligonucleotide corresponding to the automated prediction yielded a robust FFT score and a phase consistent with the translation machinery, yet no PFE0850w expression was detected. These results suggest that the automated prediction for chr5.glm_185 most likely represents the correct gene model for this genomic locus and illustrates the use of the IDC expression data for further verification of the P. falciparum genome annotations.Following invasion, approximately 950 ORFs are induced during the ring and early trophozoite stage, including genes associated with the cytoplasmic transcriptional and translational machinery, glycolysis and ribonucleotide biosynthesis B–2E. Repmerase I  and RNA merase I  and RNA merase I . The cytmerase I C consistPlasmoDB.org). In addition, one of these factors, ribosomal protein S9, has been experimentally immunolocalized within the plastid . In another case, the malaria genome sequencing consortium has predicted two homologues of triose phosphate isomerase, PF14_0378 and PFC0381w. The latter is not detected by our analysis, suggesting that this gene is utilized in another developmental stage or may be a nonfunctional, redundant homologue.In addition to transcription and translation, genes involved in several basic metabolic pathways were also induced during the ring and early-trophozoite stage, including glycolysis and ribonucleotide biosynthesis D and 2E.entified . The glyentified D is tighectively . HoweverP. falciparum parasites generate pyrimidines through a de novo synthesis pathway while purines must be acquired by the organism through a salvage pathway  cycle were detected in the m genome , althougm genome . The peam genome H. Consism genome , and sevm genome . Althougm genome , the expP. falciparum IDC.A transition from early to mid-schizont is marked by the maximal induction of 29 ORFs predicted to encode various subunits of the proteasome I. Seven In the schizont stage, one of the first specialized processes induced was expression from the plastid genome J. The esPlasmodium yoelii merozoite antigen 1. As expected, peak expression of these antigens coincides with the maturation of merozoites and development of several apical organelles, including rhoptries, micronemes, and dense granules. Many of these proteins have been considered as vaccine candidates since antibodies against these antigens were readily detected in the immune sera of both convalescent patients as well as individuals with naturally acquired immunity . RESA1 is secreted into the host cell cytoplasm at the final stages of the invasion process, where it binds to erythrocytic spectrin, possibly via its DnaJ-like chaperone domain   . In eighd genes) C. The avThe largest group demonstrating coregulation on the nuclear chromosomes corresponds to seven genes of the SERA family found on Chromosome 2 see B Miller. Besidesvar, rifin, and stevor families, have a high degree of genomic variability and are highly polymorphic between strains and even within a single strain (rifin, 47.1% of var, and 51.0% of stevor genes predicted for the 3D7 strain were detected for the HB3 genomic DNA (gDNA) when hybridized to the 3D7-based microarray. Thus, the underrepresentation of these gene families in the HB3 IDC transcriptome is likely due to the high degree of sequence variation present in these genes. Excluding the three surface antigen families in the subtelomeric regions, 97% of the remaining oligonucleotide microarray elements exhibit an equivalent signal in the CGH analysis. However, 144 of the differences detected by CGH reside in internal chromosomal regions and include several previously identified plasmodial antigens: MSP1, MSP2 , resulting in a list of 124 in-phase apicoplast genes (PlasmoDB.org as apicoplast proteins by inference from direct assay (IDA). In addition, 30% of the nuclear-encoded translational genes that are not coexpressed with the known cytoplasmic machinery are found within this small group of genes. More importantly, 76 ORFs (62%) are of unknown function, with little or no homology to other genes. This limited subgroup of putative plastid-targeted ORFs are likely excellent candidates for further studies in the ongoing search for malaria-specific functions as putative drug targets.Given that over 10% of the ORFs in the ated see C. We reaated see  , and IV (A family of ten aspartyl proteases, the plasmepsins (PMs), has been identified in the , and IV . Our dat, and IV . The coiP. falciparum contains a variety of proteases involved in cellular processing, including a group of Clps and signal peptidases that are all expressed maximally at the late-trophozoite stage ; PM X parallels the expression of PfSUB1 (PFE0370c), suggesting that aspartyl proteases may also be involved in merozoite invasion. In addition, the phase of the PfSUB1 homologue suggests a concomitant role, with PM IX slightly preceding merozoite invasion. In total, we have detected gene expression for over 80 putative proteases throughout the entire IDC , yet this was not observed; the mRNA transcripts for 75% of proteins determined to be gamete-, gametocyte-, or sporozoite-specific by mass spectrometry are also transcribed in the plasmodial IDC. These findings confirm previous studies demonstrating that not only genes used for generic cellular processes are present in multiple developmental stages, but also factors of highly specialized unctions . This maP. falciparum genome. The Plasmodium parasite devotes 3.9% of its genome to a complex system of antigenic determinants essential for host immune evasion during a single developmental stage  was grown in a standard 4.5 l microbial bioreactor (Aplikon, Brauwweg, Netherlands) equipped with a Bio Controller unit ADI 1030 (Aplikon, Brauwweg, Netherlands). Cells were initially grown in a 2% suspension of purified human RBCs and RPMI 1640 media supplemented with 0.25% Albumax II , 2 g/l sodium bicarbonate, 0.1 mM hypoxanthine, 25 mM HEPES (pH 7.4), and 50 μg/l gentamycin, at 37°C, 5% O2, and 6% CO2. Cells were synchronized by two consecutive sorbitol treatments for three generations, for a total of six treatments. Large-scale cultures contained 32.5 mM HEPES (pH 7.4). The bioreactor culture was initiated by mixing 25.0 ml of parasitized RBCs (20% late schizonts, approximately 45 hpi) with an additional 115.0 ml of purified RBC in a total of 1.0 l of media (14% hematocrit). Invasion of fresh RBCs occurred during the next 2 h, raising the total parasitemia from an initial 5% to 16%. After this period, the volume of the culture was adjusted to 4.5 l, bringing the final RBC concentration to approximately 3.3% to reduce the invasion of remaining cells. Immediately after the invasion period, greater than 80% of the parasites were in the ring stage. Temperature and gas conditions were managed by the Bio Controller unit. Over the course of 48 h, 3–4 ml of parasitized RBCs was collected every hour, washed with prewarmed PBS, and flash-frozen in liquid nitrogen.A large-scale culture of P. falciparum RNA sample isolation, cDNA synthesis, labeling, and DNA microarray hybridizations were performed as described by http://ucsf-nomad.sourceforge.net/). In brief, a scalar normalization factor was calculated for each array using unflagged features with median intensities greater than zero for each channel and a pixel regression correlation coefficient greater than or equal to 0.75. Quality spots were retained based on the following criteria. The log2(Cy5/Cy3) ratio for array features that were unflagged and had a sum of median intensities greater than the local background plus two times the standard deviation of the background were extracted from the database for further analysis. Subsequently, expression profiles consisting of 43 of 46 timepoints (approximately 95%) were selected. For those timepoints that were represented by multiple arrays, the ratio values were averaged.In total, 55 DNA microarray hybridizations covering 46 timepoints were performed. Timepoints 1, 7, 11, 14, 18, 20, 27, and 31 were represented by more than one array hybridization. Data were acquired and analyzed by GenePix Pro 3 . Array data were stored and normalized using the NOMAD microarray database system (http://www.R-project.org). Fourier analysis was performed on each profile using the fft function of R, padded with zeros to 64 measurements. The power spectrum was calculated using the spectrum function of R. The power at each frequency (Power), the total power (Ptot), and the frequency of maximum power (Fmax) were determined. The periodicity score was defined as Power[(Fmax−1) + (Fmax) + (Fmax+1)]/Ptot. The most frequent value of Fmax across all profiles was deemed the major frequency (m) and used in determining phase information. The phase of each profile was calculated as atan2\[−(I (m)],R (m)\, where atan2 is R's arctangent function and I and R are the imaginary and real parts of the FFT. Profiles were then ordered in increasing phase from −π to π. The loess smooth profiles were drawn through the raw expression data using the loess function found in the modern regression library of R (version 1.5.1). The default parameters were used, with the exception that local weighting was reduced to 30%. For the averaged profiles of the functional groups . Profiles were smoothed with missing values imputed using a locally weighted regression algorithm with local weighting restricted to 12% using R  was isolated from a minimum of 500 ml of total culture for each P. falciparum strain, as previously described , resulting in 124 genes represented by 128 oligonucleotides on the microarray. This select group represents the in-phase plastid targeted genes (see The range of FFT-based phases for the expression profiles of the plastid genome is between 0.32 and 1.05 (or roughly π/9 −π/3). Using the list of 551 apicoplast-targeted genes available at enes see .To select the expression profiles most related to the AMA1, MSP1, MSP3, MSP5, EBA175, RAP1, and RESA1 vaccine candidates, we calculated the similarity of all expression profiles in the dataset to those of these antigens by Euclidian distance. The minimum Euclidian distance calculated for every profile was then binned into 60 bins and plotted as a histogram. A natural break in the histogram was seen that included the set of 262 ORFs see .Dataset S1(29.5 MB ZIP).Click here for additional data file.Dataset S2(3.7 MB TXT).Click here for additional data file.Dataset S3(2.4 MB TXT).Click here for additional data file.Dataset S4(3.1 MB TXT).Click here for additional data file.Figure S1The percent of power in the maximum frequency of the FFT power spectrum was used to determine periodicity of the yeast cell cycle data from (223 KB EPS).Click here for additional data file.Figure S2PlasmoDB.org.A matrix of the pairwise Pearson correlations was calculated for every expression profile along the chromosomes. The analysis included all annotated ORFs. The gray areas correspond to a Pearson correlation d(x, y) = 0 and indicate ORFs with no detectable IDC expression or ORFs not represented on the microarray. The starting point (left) and the end point (right) of the chromosomes and the ORF order along the chromosomes are identical to the order in (30.9 MB EPS).Click here for additional data file.Figure S3Genomic differences between strain 3D7 and strain HB3 were measured by CGH. The relative hybridization between the gDNA derived from these two strains is shown as a percent reduction of the signal intensity for 3D7 along individual chromosomes. (1.7 MB ZIP).Click here for additional data file.(A)Click here for additional data file.(B)Click here for additional data file.(C)Click here for additional data file.(D)Click here for additional data file.(E)Click here for additional data file.(F)Click here for additional data file.(G)Click here for additional data file.(H)Click here for additional data file.(I)Click here for additional data file.(J)Click here for additional data file.(K)Click here for additional data file.(L)Click here for additional data file.(M)Click here for additional data file.(N)Click here for additional data file.Figure S4i − yi)2. The Euclidian distance value to the closest vaccine homologue was selected for each IDC profile and used to generate this plot. Genes with d(x,y) < 20 were selected for the phaseogram of putative vaccine targets  = Σ(xgets see .(494.02 KB EPS).Click here for additional data file.Table S1This table contains all of the ORFs in the analyzed dataset that are represented by multiple oligonucleotides on the DNA microarray. The average Pearson correlation value has been calculated for the expression profiles of all oligonucleotides for each given ORF.(44 KB TXT).Click here for additional data file.Table S2P. falciparum groups discussed. The groups include the following: transcription machinery, cytoplasmic translation machinery, the glycolytic pathway, ribonucleotide synthesis, deoxyribonucleotide synthesis, DNA replication machinery, the TCA cycle, the proteaseome, the plastid genome, merozoite invasion, actin–myosin motility, early-ring transcripts, mitochondrial genes, and the organellar translational group.This table contains all of the (291 KB TXT).Click here for additional data file.Table S3P. falciparum determined by calculating the Pearson correlation between expression profiles for contiguous ORFs. The cutoff was 70% pairwise correlation of greater than 0.75 for each group. Only groups of two ORFs or more are listed.This table contains the regions of coregulation found in the chromosomes of (6 KB TXT).Click here for additional data file.Table S4P. falciparum. The averaged intensities from three microarray hybridization experiments are listed.This table contains all of the intensity data from CGH of gDNA derived from the 3D7 and HB3 strains of (414 KB TXT).Click here for additional data file.Table S5PlasmoDB.org. The presence of each ORF on the DNA microarray is tabulated, as well as whether each ORF is present in the overview set. Finally, the plastid ORFs in-phase with plastid genome expression are listed, as well as the corresponding oligonucleotide identifiers.This table contains all of the predicted apicoplast-targeted ORFs from (147 KB TXT).Click here for additional data file.Table S6The table was constructed by searching the database for any putative protease annotations and contains all of the 92 proteases identified by (59 KB TXT).Click here for additional data file.Table S7The similarity of all expression profiles to seven known vaccine candidates was evaluated by a Euclidian distance calculation to all expression profiles measured. These 262 ORFs constitute the top 5% of genes in the IDC with minimum distance to these seven ORFs. The seven candidates used are AMA1, MSP1, MSP3, MSP5, EBA175, RAP1, and RESA1.(204 KB TXT).Click here for additional data file.


Many professions in the fields of engineering, aviation and medicine employ this form of scheduling. However, on-call work has received significantly less research attention than other work patterns such as shift work and overtime hours. This paper reviews the current body of peer-reviewed, published research conducted on the health effects of on-call work The health effects studies done in the area of on-call work are limited to mental health, job stress, sleep disturbances and personal safety. The reviewed research suggests that on-call work scheduling can pose a risk to health, although there are critical gaps in the literature. The question of whether work hours and schedules affect people's health has been reviewed for a range of work patterns including shift work and overtime. Research in these areas indicates that shift work, and in particular night work can interrupt sleep patterns , aggravaHowever, the health effects of on-call work, where workers are called to work either between regular hours or during set on-call periods, has not merited as much attention. This form of work scheduling occurs in a variety of diverse occupations, for example medical technologists, doctors, ship engineers, utility workers, electrical technicians, tug boat pilots, midwives, information technologists, media personnel and junior airline pilots. For many of these professions being on-call is not an option, but rather a component of the job. This form of scheduling is often used to provide 24 hour coverage, 7 days a week, for facilities such as hospitals and laboratories, where emergencies require personnel to immediately deal with critical situations and where the volume of evening and weekend work does not necessitate full shift coverage. Having employees on-call, even if they are being paid a stipend for their call time, is often seen as less expensive for employers than providing full shift coverage during off-peak hours .While on-call work scheduling may be less expensive, it is not without human costs. On-call employees must plan their lives and the lives of their families around a call schedule. This often means limiting behaviours and obliges employees to restrict their on-call time to activities that would not interfere with their ability to work. The unpredictability of the call scheduling can also generate a great deal of stress, as home life is interrupted and workers are required to "change hats" to shift to their professional roles at any time during call. These limitations and interferences present unique challenges for on-call workers that are not encountered by those working set schedules or even people with rotating shifts. It is thus not surprising that researchers have found that on-call work patterns can have a major influence on employees' lifestyles and their interactions with family members and friends . HoweverWithin the limited literature that has explored on-call work, there exists some pertinent findings concerning the impact of on-call for an employee's physical and psychological health, and social relationships, which this review seeks to bring together. Specific attention has been devoted to the areas of stress, sleep, mental health and personal safety.The implementation of on-call schedules varies. For many occupations, workers leave their place of employment and are placed "on-call" on evenings and weekends, which means they can be called back to work during these periods. For many professions this form of scheduling is a normal component of the occupation, for example, marine pilots can spend up to 60% of their working time on-call. However, for a limited number of occupations such as airline pilots, on-call hours are reduced with seniority. Generally, but not always, employees are compensated monetarily for the period of call, usually with a stipend which is less than their hourly rate. When on-call employees are usually expected to restrict their use of alcohol and limit distance or travel time from the work-site. The on-call experience of these workers includes aspects of interruption, either of sleep or family or social life, and often includes an element of uncertainty as to the time of call or the occurrence of the call.Other forms of on-call include work done by junior doctors during their medical training. Medical residents spend periods of time "on-call" at a hospital, where space may be provided for them to sleep. This form of on-call work is distinct because workers remain at work to undertake their call duty. During these periods, residents often put in 30–36 hour shifts with little to no sleep , resultiThis review focuses on the health effects of on-call work in which an employee spends a period of time on-call outside of their workplace and/or their regular working hours. The research on medical residents has been excluded because the medical resident experience is distinctly different from that of other professions where on-call is utilized. However, research on medical residents is used to illustrate findings from other work-related areas when appropriate.This review explores the published literature referring to on-call work patterns and health. For the purpose of this review, the on-call period may be formal  or informal . Search terms for this review included "on-call" and "work schedule tolerance". The terms "stand-by" and "night call" are used by some professions to describe on-call type work, and were also used as search parameters. This literature review was undertaken on journal articles included in databases up to December 2000. Database searches were performed on the following electronic sources:1) OVID Databases: including Medline (1966–2000) and Current Contents (1996–2000).2) Canadian Centre for Occupational Health and Safety Database3) Cambridge Abstracts  1981–2000.4) PsycInfo (1989–2000).5) Web of Science: including Science Citation Index and Social Science Citation Index (1989–2000).A manual review of the references generated from the computer-search was also done. Articles were excluded from the review if they were not original research, were not written in English or focused on medical residents experiences with on-call work.Two reviewers read through each of the eligible research papers independently.In total, 24 papers met the search criteria. Eight (8) were excluded as they focused on the impact of on-call work patterns on patient's health and not on the health of workers. The remaining sixteen studies were used for this review. The results are divided into four health-related sections; 1) Stress, 2) Sleep, 3) Mental Health and 4) Personal Safety.Of the five studies pertaining to on-call and stress uncovered in this review, all focus on the General Practitioners (GPs) as their subject. In these studies, the relationship between on-call work and stress was measured through self-report and perceived stress.Three of the studies were part of a major UK study carried out from 1989 to 1998 -13. In tth in a ranking of 14 major stressors. The authors believe this reduction in the level of stress from on-call work could be explained by the introduction of GP co-operatives in the mid 1990s for the management of out-of-hours calls. This cooperative system allowed GPs to either do their own calls or share them with a cooperative formed by 10 or more doctors. The cooperatives gave GPs greater flexibility for how and where they saw their patients and how they implemented 24-hour care and appear to have successfully reduced the stress of night visits for GPs. Indeed, night visit stress went from being one of two top stressors for GPs in 1987 and 1990 to being one of the least stressful issues by 1998. The authors also posit that this "success may also explain the reported reduction by 1998 in stress attributable to disturbance of home/family life" [[In the first two studies, GPs ranked working on-call at night as one of the top two most stressful aspects of their work situation ,12. Howey life" [ pg. 370]The fourth study also dealt with the changes in the British health care system, in particular the introduction of partial shifts to decrease long on-call periods . A smallThe fifth study on GPs and stress was a qualitative analysis of 25 GPs and their spouses in Manchester . This reOther studies have revealed that the amount of time spent on-call varies between male and female doctors, but no clear pattern has emerged ,17. It hResearch conducted in other professions support the idea that work patterns, particularly night shifts, can increase stress in workers and have a negative impact on family life. Working late afternoon and evening shifts has been related to increased stress for both workers and their families . VariablBesides stress, the interruption of sleep is another major component of on-call work, particularly for those who work nights on-call and in professions that deal with emergencies that occur at all hours. Three studies have dealt specifically with the sleeping patterns and problems experienced by train and ship engineers and transplant coordinators, all of whom regularly work on-call.The first study researched the on-call sleep patterns of 198 train engineers using prospective activity logs over a 14-day period in the United States . It was The second study of on-call and sleep explored the sleeping patterns of 53 predominantly female organ transplant coordinators in the UK, using a postal questionnaire . This reThe third study, conducted on a small sample (n = 5) of ship engineers in Sweden, measured sleep during on-call periods using electroencephalogram (EEG) and electrocardiogram (ECG) recordings and subjective ratings. . This reThe impacts of sleep loss on job performance remain unclear and controversial. For example, research on the cognitive performance in sleep deprived medical residents has produced mixed results -27. HoweWork-related fatigue has been related to an increase in car accidents. A review of traffic accidents determined that falling asleep while driving accounted for a major proportion of accidents while driving under monotonous conditions . This fiSix studies were found that examined the impact of on-call work schedules on mental health. All of these studies used self-reported questionnaires and/or mood diaries. Five studies were conducted on GPs in the UK and one examined gas and electrical employees in France.Two surveys were conducted by Chambers et al. ,34 on GPThe second survey conducted by Chambers et al in 1996 (n = 620) employed the Hospital Anxiety and Depression scale to assess the mental health of GPs . It was A third survey done on GPs in Leeds in 1993 was designed to determine the psychological symptoms and sources of stress among 268 GPs . This suThe fourth study in this area surveyed mental health and job stress on 414 GPs in England in 1992 . This reA pilot study of 44 male and female volunteer GPs using cognitive behavioural diaries assessed self-reported emotional states recorded in conjunction with hourly activities over 2 days . DoctorsThe sixth study examined male gas and electrical employees working in France . EmployeThe research conducted on GPs in the UK supports a negative role of on-call work related to mental health. However, the results from the gas and electrical workers do not reflect the same findings from the research on GPs. This may be the result of either a difference in study methodology or a difference that is profession-specific. On-call gas and electrical workers did experience psychological disruption and the lack of significant diagnostic findings may be a function of other factors, such as self-selection, in this profession, where those most affected opt out early on. The on-call gas and electrical workers experience of family and social life disruption does mirror the experiences of doctors and transplant coordinators as discussed previously ,15,22.Working on-call often necessitates leaving home alone, at night, to attend work, conditions that can jeopardize personal safety. Unfortunately, there is only sparse data regarding this issue. A study done in the north west of England, in a hospital where the on-call sleeping quarters were separate from the hospital found that 40% of anaesthetists feared for their safety while walking through hospital grounds at night .In medical professions, patients can also present a danger to those working on-call. Doctors have cited fear of violence from night call visits as a significant stressor . A studyThis issue has only been peripherally studied and further attention needs to be given to personal safety, particularly when being called in at night.What emerges from this review is the limited research that has been done in the area of on-call work. Preliminary work done in the areas of stress and mental health suggests that on-call work may play a role in increasing stress and decreasing mental well-being. The three studies that examined sleep indicate that on-call work does decrease the quality and quantity of sleep for workers and can leave people feeling fatigued for periods after their on-call work.The current body of literature on the health effects of on-call work is limited in part due to the narrow range of professions studied. The majority of research done to date has been on general practitioners. It is reasonable to assume that the effects of on-call will vary across occupations, given the host of other factors that can influence occupational health. However, the degree to which this variation exists might only be determined by examining a wider occupational base. The need to undertake more on-call research across a greater variety of occupational groups is suggested given that this form of work scheduling touches many occupations, and given that on-call work is estimated to continue to increase in many sectors in the future .There is also an obvious lack of research focusing on the impact of on-call shifts on psychosocial factors. Given the very disruptive and limiting nature of on-call schedules, it would not be surprising that workers' family and social life suffer due to this type of scheduling. The results of the research addressing gender (discussed above) do suggest, albeit indirectly, that such social and familial impacts may be significant. However, without more research, it is not possible to determine the magnitude of these effects, nor the relative importance compared to other factors such as physiological responses.More rigorous methodological designs are needed for future research in the area of on-call work and health. The current research is predominantly cross-sectional in nature, a factor that makes it difficult to determine causality. Only two studies employed external comparison groups ,38 and oFuture research on the health effects of on-call work also needs to examine the role of gender, not only from a physiological standpoint, (e.g. reproductive issues), but also from a psychosocial perspective. Many of the articles reviewed above indicate differences in how males and females experience the stress of on-call work ,15,17,36The range of health effects studied in relation to on-call work has to date been inadequate. Health conditions such as cardiovascular disease, reproductive problems, gastrointestinal issues and overall mortality need to be explored as has been done in conjunction with work patterns such as overtime and shift work ,45. FactWhile the results of this review are limited, initial research in this area suggest that being on-call can have negative impacts on workers' sleep patterns, mental health and personal life. Further research in this area is required to provide a clear picture of the risks of this form of work scheduling.UK, United KingdomUS, United States of AmericaThe authors declare that they have no competing interests.AMN designed the research project, carried out the literature search, reviewed articles and drafted the manuscript. JSB reviewed articles and edited the manuscript. Both authors approved the final manuscript.