Candidates registered for reasonable adjustments underperform compared to other candidates in the national undergraduate Prescribing Safety Assessment: Retrospective cohort analysis (2014-2018).

AIMS: Candidates with disabilities are eligible for reasonable adjustments (RA) while undertaking the national Prescribing Safety Assessment (PSA). The PSA is a novel open-book, time-constrained, multiformat assessment that may pose challenges to candidates with dyslexia and other disabilities. METHODS: Retrospective cohort analysis of 36 140 UK candidates undertaking first-sitting of the PSA (2014-2018). RESULTS: Of the 36 140 candidates, 9.1% (3284) were registered for RA. The RA group had lower pass rates (absolute difference 1.94%, 95% confidence interval 1.01-2.87%; P < .001) and assessment scores (1.16 percentage marks, 95% confidence interval 0.83-1.48; P < .001) compared with the non-RA group. This absolute difference is small relative to overall variability. This difference persists after adjusting for confounding factors (medical school and paper), and was present for all 8 different question types. The attainment gap within each medical school is negatively correlated with the school's overall performance, both in terms of pass rate (P < .001) and scores (P = .01). The RA group were also less likely to perceive the PSA as an appropriate test, having easy to follow layout/presentation or clear/unambiguous questions, even after adjusting for candidate performance. CONCLUSION: This analysis identifies slight differences in academic performance of candidates requiring RA in a national undergraduate assessment. The study is limited by the unavailability of data on ethnicity, sex, age, diagnosis and time of diagnosis. While further research is required to determine the cause of the attainment gap, this study emphasises the need to maintain a careful review on the fairness and validity of all aspects of the assessment

Concordance of freshwater and terrestrial biodiversity

Efforts to set global conservation priorities have largely ignored freshwater diversity, thereby excluding some of the world\u27s most speciose, threatened, and valuable taxa. Using a new global map of freshwater ecoregions and distribution data for about 13,300 fish species, we identify regions of exceptional freshwater biodiversity and assess their overlap with regions of equivalent terrestrial importance. Overlap is greatest in the tropics and is higher than expected by chance. These high-congruence areas offer opportunities for integrated conservation efforts, which could be of particular value when economic conditions force conservation organizations to narrow their focus. Areas of low overlap-missed by current terrestrially based priority schemes-merit independent freshwater conservation efforts. These results provide new information to conservation investors setting priorities at global or regional scales and argue for a potential reallocation of future resources to achieve representation of overlooked biomes. © 2010 Wiley Periodicals, Inc

Laboratory-based evaluation of legionellosis epidemiology in Ontario, Canada, 1978 to 2006

BACKGROUND: Legionellosis is a common cause of severe community acquired pneumonia and respiratory disease outbreaks. The Ontario Public Health Laboratory (OPHL) has conducted most testing for Legionella species in the Canadian province of Ontario since 1978, and represents a multi-decade repository of population-based data on legionellosis epidemiology. We sought to provide a laboratory-based review of the epidemiology of legionellosis in Ontario over the past 3 decades, with a focus on changing rates of disease and species associated with legionellosis during that time period. METHODS: We analyzed cases that were submitted and tested positive for legionellosis from 1978 to 2006 using Poisson regression models incorporating temporal, spatial, and demographic covariates. Predictors of infection with culture-confirmed L. pneumophila serogroup 1 (LP1) were evaluated with logistic regression models. Results: 1,401 cases of legionellosis tested positive from 1978 to 2006. As in other studies, we found a late summer to early autumn seasonality in disease occurrence with disease risk increasing with age and in males. In contrast to other studies, we found a decreasing trend in cases in the recent decade (IRR 0.93, 95% CI 0.91 to 0.95, P-value = 0.001); only 66% of culture-confirmed isolates were found to be LP1. CONCLUSION: Despite similarities with disease epidemiology in other regions, legionellosis appears to have declined in the past decade in Ontario, in contrast to trends observed in the United States and parts of Europe. Furthermore, a different range of Legionella species is responsible for illness, suggesting a distinctive legionellosis epidemiology in this North American region

Extracting key information from historical data to quantify the transmission dynamics of smallpox

<p>Abstract</p> <p>Background</p> <p>Quantification of the transmission dynamics of smallpox is crucial for optimizing intervention strategies in the event of a bioterrorist attack. This article reviews basic methods and findings in mathematical and statistical studies of smallpox which estimate key transmission parameters from historical data.</p> <p>Main findings</p> <p>First, critically important aspects in extracting key information from historical data are briefly summarized. We mention different sources of heterogeneity and potential pitfalls in utilizing historical records. Second, we discuss how smallpox spreads in the absence of interventions and how the optimal timing of quarantine and isolation measures can be determined. Case studies demonstrate the following. (1) The upper confidence limit of the 99th percentile of the incubation period is 22.2 days, suggesting that quarantine should last 23 days. (2) The highest frequency (61.8%) of secondary transmissions occurs 3–5 days after onset of fever so that infected individuals should be isolated before the appearance of rash. (3) The U-shaped age-specific case fatality implies a vulnerability of infants and elderly among non-immune individuals. Estimates of the transmission potential are subsequently reviewed, followed by an assessment of vaccination effects and of the expected effectiveness of interventions.</p> <p>Conclusion</p> <p>Current debates on bio-terrorism preparedness indicate that public health decision making must account for the complex interplay and balance between vaccination strategies and other public health measures (e.g. case isolation and contact tracing) taking into account the frequency of adverse events to vaccination. In this review, we summarize what has already been clarified and point out needs to analyze previous smallpox outbreaks systematically.</p

Author Correction: Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Emmanuelle Souzeau, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this Article. This has now been corrected in both the PDF and HTML versions of the Article

Is the meiofauna a good indicator for climate change and anthropogenic impacts?

Our planet is changing, and one of the most pressing challenges facing the scientific community revolves around understanding how ecological communities respond to global changes. From coastal to deep-sea ecosystems, ecologists are exploring new areas of research to find model organisms that help predict the future of life on our planet. Among the different categories of organisms, meiofauna offer several advantages for the study of marine benthic ecosystems. This paper reviews the advances in the study of meiofauna with regard to climate change and anthropogenic impacts. Four taxonomic groups are valuable for predicting global changes: foraminifers (especially calcareous forms), nematodes, copepods and ostracods. Environmental variables are fundamental in the interpretation of meiofaunal patterns and multistressor experiments are more informative than single stressor ones, revealing complex ecological and biological interactions. Global change has a general negative effect on meiofauna, with important consequences on benthic food webs. However, some meiofaunal species can be favoured by the extreme conditions induced by global change, as they can exhibit remarkable physiological adaptations. This review highlights the need to incorporate studies on taxonomy, genetics and function of meiofaunal taxa into global change impact research

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers