100 research outputs found

    MscS-like mechanosensitive channels in plants and microbes

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    The challenge of osmotic stress is something all living organisms must face as a result of environmental dynamics. Over the past three decades, innovative research and cooperation across disciplines have irrefutably established that cells utilize mechanically gated ion channels to release osmolytes and prevent cell lysis during hypoosmotic stress. Early electrophysiological analysis of the inner membrane of Escherichia coli identified the presence of three distinct mechanosensitive activities. The subsequent discoveries of the genes responsible for two of these activities, the mechanosensitive channels of large (MscL) and small (MscS) conductance, led to the identification of two diverse families of mechanosensitive channels. The latter of these two families, the MscS family, consists of members from bacteria, archaea, fungi, and plants. Genetic and electrophysiological analysis of these family members has provided insight into how organisms use mechanosensitive channels for osmotic regulation in response to changing environmental and developmental circumstances. Furthermore, determining the crystal structure of E. coli MscS and several homologues in several conformational states has contributed to our understanding of the gating mechanisms of these channels. Here we summarize our current knowledge of MscS homologues from all three domains of life and address their structure, proposed physiological functions, electrophysiological behaviors, and topological diversity

    Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta-analysis

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    Objectives A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire-9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum. Methods Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics. Results Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased. Conclusion Different interviews may not classify major depression equivalently

    Insight into the proteome of the hyperthermophilic Crenarchaeon Ignicoccus hospitalis: the major cytosolic and membrane proteins

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    Ignicoccus hospitalis, a hyperthermophilic, chemolithoautotrophic Crenarchaeon, is the host of Nanoarchaeum equitans. Together, they form an intimate association, the first among Archaea. Membranes are of fundamental importance for the interaction of I. hospitalis and N. equitans, as they harbour the proteins necessary for the transport of macromolecules like lipids, amino acids, and cofactors between these organisms. Here, we investigated the protein inventory of I. hospitalis cells, and were able to identify 20 proteins in total. Experimental evidence and predictions let us conclude that 11 are soluble cytosolic proteins, eight membrane or membrane-associated proteins, and a single one extracellular. The quantitatively dominating proteins in the cytoplasm (peroxiredoxin; thermosome) antagonize oxidative and temperature stress which I. hospitalis cells are exposed to at optimal growth conditions. Three abundant membrane protein complexes are found: the major protein of the outer membrane, which might protect the cell against the hostile environment, forms oligomeric complexes with pores of unknown selectivity; two other complexes of the cytoplasmic membrane, the hydrogenase and the ATP synthase, play a key role in energy production and conversion

    Campylobacter jejuni transcriptome changes during loss of culturability in water

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    Background: Water serves as a potential reservoir for Campylobacter, the leading cause of bacterial gastroenteritis in humans. However, little is understood about the mechanisms underlying variations in survival characteristics between different strains of C. jejuni in natural environments, including water. Results: We identified three Campylobacter jejuni strains that exhibited variability in their ability to retain culturability after suspension in tap water at two different temperatures (4°C and 25°C). Of the three strains C. jejuni M1 exhibited the most rapid loss of culturability whilst retaining viability. Using RNAseq transcriptomics, we characterised C. jejuni M1 gene expression in response to suspension in water by analyzing bacterial suspensions recovered immediately after introduction into water (Time 0), and from two sampling time/temperature combinations where considerable loss of culturability was evident, namely (i) after 24 h at 25°C, and (ii) after 72 h at 4°C. Transcript data were compared with a culture-grown control. Some gene expression characteristics were shared amongst the three populations recovered from water, with more genes being up-regulated than down. Many of the up-regulated genes were identified in the Time 0 sample, whereas the majority of down-regulated genes occurred in the 25°C (24 h) sample. Conclusions: Variations in expression were found amongst genes associated with oxygen tolerance, starvation and osmotic stress. However, we also found upregulation of flagellar assembly genes, accompanied by down-regulation of genes involved in chemotaxis. Our data also suggested a switch from secretion via the sec system to via the tat system, and that the quorum sensing gene luxS may be implicated in the survival of strain M1 in water. Variations in gene expression also occurred in accessory genome regions. Our data suggest that despite the loss of culturability, C. jejuni M1 remains viable and adapts via specific changes in gene expression

    A Unified Model of the GABA(A) Receptor Comprising Agonist and Benzodiazepine Binding Sites

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    We present a full-length α(1)β(2)γ(2) GABA receptor model optimized for agonists and benzodiazepine (BZD) allosteric modulators. We propose binding hypotheses for the agonists GABA, muscimol and THIP and for the allosteric modulator diazepam (DZP). The receptor model is primarily based on the glutamate-gated chloride channel (GluCl) from C. elegans and includes additional structural information from the prokaryotic ligand-gated ion channel ELIC in a few regions. Available mutational data of the binding sites are well explained by the model and the proposed ligand binding poses. We suggest a GABA binding mode similar to the binding mode of glutamate in the GluCl X-ray structure. Key interactions are predicted with residues α(1)R66, β(2)T202, α(1)T129, β(2)E155, β(2)Y205 and the backbone of β(2)S156. Muscimol is predicted to bind similarly, however, with minor differences rationalized with quantum mechanical energy calculations. Muscimol key interactions are predicted to be α(1)R66, β(2)T202, α(1)T129, β(2)E155, β(2)Y205 and β(2)F200. Furthermore, we argue that a water molecule could mediate further interactions between muscimol and the backbone of β(2)S156 and β(2)Y157. DZP is predicted to bind with interactions comparable to those of the agonists in the orthosteric site. The carbonyl group of DZP is predicted to interact with two threonines α(1)T206 and γ(2)T142, similar to the acidic moiety of GABA. The chlorine atom of DZP is placed near the important α(1)H101 and the N-methyl group near α(1)Y159, α(1)T206, and α(1)Y209. We present a binding mode of DZP in which the pending phenyl moiety of DZP is buried in the binding pocket and thus shielded from solvent exposure. Our full length GABA(A) receptor is made available as Model S1

    Depression prevalence using the HADS-D compared to SCID major depression classification:An individual participant data meta-analysis

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    Objectives: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale – depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence. Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated. Results: 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was −21.1% to 19.5%. Conclusions: HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview.This study was funded by the Canadian Institutes of Health Research (CIHR, KRS-144045 & PCG 155468). Ms. Neupane was supported by a G.R. Caverhill Fellowship from the Faculty of Medicine, McGill University. Drs. Levis and Wu were supported by Fonds de recherche du Québec - Santé (FRQS) Postdoctoral Training Fellowships. Mr. Bhandari was supported by a studentship from the Research Institute of the McGill University Health Centre. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. Dr. Patten was supported by a Senior Health Scholar award from Alberta Innovates, Health Solutions. The primary study by Scott et al. was supported by the Cumming School of Medicine and Alberta Health Services through the Calgary Health Trust, and funding from the Hotchkiss Brain Institute. The primary study by Amoozegar et al. was supported by the Alberta Health Services, the University of Calgary Faculty of Medicine, and the Hotchkiss Brain Institute. The primary study by Cheung et al. was supported by the Waikato Clinical School, University of Auckland, the Waikato Medical Research Foundation and the Waikato Respiratory Research Fund. The primary study by Cukor et al. was supported in part by a Promoting Psychological Research and Training on Health-Disparities Issues at Ethnic Minority Serving Institutions Grants (ProDIGs) awarded to Dr. Cukor from the American Psychological Association. The primary study by De Souza et al. was supported by Birmingham and Solihull Mental Health Foundation Trust. The primary study by Honarmand et al. was supported by a grant from the Multiple Sclerosis Society of Canada. The primary study by Fischer et al. was supported as part of the RECODEHF study by the German Federal Ministry of Education and Research (01GY1150). The primary study by Gagnon et al. was supported by the Drummond Foundation and the Department of Psychiatry, University Health Network. The primary study by Akechi et al. was supported in part by a Grant-in-Aid for Cancer Research (11−2) from the Japanese Ministry of Health, Labour and Welfare and a Grant-in-Aid for Young Scientists (B) from the Japanese Ministry of Education, Culture, Sports, Science and Technology. The primary study by Kugaya et al. was supported in part by a Grant-in-Aid for Cancer Research (9–31) and the Second-Term Comprehensive 10-year Strategy for Cancer Control from the Japanese Ministry of Health, Labour and Welfare. The primary study Ryan et al. was supported by the Irish Cancer Society (Grant CRP08GAL). The primary study by Keller et al. was supported by the Medical Faculty of the University of Heidelberg (grant no. 175/2000). The primary study by Love et al. (2004) was supported by the Kathleen Cuningham Foundation (National Breast Cancer Foundation), the Cancer Council of Victoria and the National Health and Medical Research Council. The primary study by Love et al. (2002) was supported by a grant from the Bethlehem Griffiths Research Foundation. The primary study by Löwe et al. was supported by the medical faculty of the University of Heidelberg, Germany (Project 121/2000). The primary study by Navines et al. was supported in part by the Spanish grants from the Fondo de Investigación en Salud, Instituto de Salud Carlos III (EO PI08/90869 and PSIGEN-VHC Study: FIS-E08/00268) and the support of FEDER (one way to make Europe). The primary study by O'Rourke et al. was supported by the Scottish Home and Health Department, Stroke Association, and Medical Research Council. The primary study by Sanchez-Gistau et al. was supported by a grant from the Ministry of Health of Spain (PI040418) and in part by Catalonia Government, DURSI 2009SGR1119. The primary study by Gould et al. was supported by the Transport Accident Commission Grant. The primary study by Rooney et al. was supported by the NHS Lothian Neuro-Oncology Endowment Fund. The primary study by Schwarzbold et al. was supported by PRONEX Program (NENASC Project) and PPSUS Program of Fundaçao de Amparo a esquisa e Inovacao do Estado de Santa Catarina (FAPESC) and the National Science and Technology Institute for Translational Medicine (INCT-TM). The primary study by Simard et al. was supported by IDEA grants from the Canadian Prostate Cancer Research Initiative and the Canadian Breast Cancer Research Alliance, as well as a studentship from the Canadian Institutes of Health Research. The primary study by Singer et al. (2009) was supported by a grant from the German Federal Ministry for Education and Research (no. 01ZZ0106). The primary study by Singer et al. (2008) was supported by grants from the German Federal Ministry for Education and Research (# 7DZAIQTX) and of the University of Leipzig (# formel. 1–57). The primary study by Meyer et al. was supported by the Federal Ministry of Education and Research (BMBF). The primary study by Stone et al. was supported by the Medical Research Council, UK and Chest Heart and Stroke, Scotland. The primary study by Turner et al. was supported by a bequest from Jennie Thomas through Hunter Medical Research Institute. The primary study by Walterfang et al. was supported by Melbourne Health. Drs. Benedetti and Thombs were supported by FRQS researcher salary awards. No other authors reported funding for primary studies or for their work on this study. No funder had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication

    Erratum to: Methods for evaluating medical tests and biomarkers

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    [This corrects the article DOI: 10.1186/s41512-016-0001-y.]

    A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well

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    The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings

    Probability of Major Depression Classification Based on the SCID, CIDI and MINI Diagnostic Interviews : A Synthesis of Three Individual Participant Data Meta-Analyses

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    Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results.To compare the odds of the major depression classification based on the SCID, CIDI, and MINI.We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis.In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80).Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics

    Probability of major depression diagnostic classification using semi-structured vs. fully structured diagnostic interviews

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    Background: Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification. Aims: To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics. Method: Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analyzed. Binomial Generalized Linear Mixed Models were fit. Results: 17,158 participants (2,287 major depression cases) from 57 primary studies were analyzed. Among fully structured interviews, odds of major depression were higher for the MINI compared to the Composite International Diagnostic Interview (CIDI) [OR (95% CI) = 2.10 (1.15-3.87)]. Compared to semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores 6) as having major depression [OR (95% CI) = 3.13 (0.98-10.00)], similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) [OR (95% CI) = 0.96 (0.56-1.66)], and significantly less likely for high-level symptoms (PHQ-9 scores 16) [OR (95% CI) = 0.50 (0.26-0.97)]. Conclusions: The MINI may identify more depressed cases than the CIDI, and semi- and fully structured interviews may not be interchangeable methods, but these results should be replicated
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