Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

Background: Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Methods: Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Results: Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Conclusions: Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, ‘dark matter’ and ‘dark energy’ are posited to balance various theoretical equations, so medical student selection must also have its ‘dark variance’, whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills

Multi-parallel qPCR provides increased sensitivity and diagnostic breadth for gastrointestinal parasites of humans: field-based inferences on the impact of mass deworming

BACKGROUND: Although chronic morbidity in humans from soil transmitted helminth (STH) infections can be reduced by anthelmintic treatment, inconsistent diagnostic tools make it difficult to reliably measure the impact of deworming programs and often miss light helminth infections. METHODS: Cryopreserved stool samples from 796 people (aged 2-81 years) in four villages in Bungoma County, western Kenya, were assessed using multi-parallel qPCR for 8 parasites and compared to point-of-contact assessments of the same stools by the 2-stool 2-slide Kato-Katz (KK) method. All subjects were treated with albendazole and all Ascaris lumbricoides expelled post-treatment were collected. Three months later, samples from 633 of these people were re-assessed by both qPCR and KK, re-treated with albendazole and the expelled worms collected. RESULTS: Baseline prevalence by qPCR (n = 796) was 17 % for A. lumbricoides, 18 % for Necator americanus, 41 % for Giardia lamblia and 15% for Entamoeba histolytica. The prevalence was <1% for Trichuris trichiura, Ancylostoma duodenale, Strongyloides stercoralis and Cryptosporidium parvum. The sensitivity of qPCR was 98% for A. lumbricoides and N. americanus, whereas KK sensitivity was 70% and 32%, respectively. Furthermore, qPCR detected infections with T. trichiura and S. stercoralis that were missed by KK, and infections with G. lamblia and E. histolytica that cannot be detected by KK. Infection intensities measured by qPCR and by KK were correlated for A. lumbricoides (r = 0.83, p < 0.0001) and N. americanus (r = 0.55, p < 0.0001). The number of A. lumbricoides worms expelled was correlated (p < 0.0001) with both the KK (r = 0.63) and qPCR intensity measurements (r = 0.60). CONCLUSIONS: KK may be an inadequate tool for stool-based surveillance in areas where hookworm or Strongyloides are common or where intensity of helminth infection is low after repeated rounds of chemotherapy. Because deworming programs need to distinguish between populations where parasitic infection is controlled and those where further treatment is required, multi-parallel qPCR (or similar high throughput molecular diagnostics) may provide new and important diagnostic information

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data

Travelling in time with networks: revealing present day hybridization versus ancestral polymorphism between two species of brown algae, Fucus vesiculosus and F. spiralis

Background: Hybridization or divergence between sympatric sister species provides a natural laboratory to study speciation processes. The shared polymorphism in sister species may either be ancestral or derive from hybridization, and the accuracy of analytic methods used thus far to derive convincing evidence for the occurrence of present day hybridization is largely debated. Results: Here we propose the application of network analysis to test for the occurrence of present day hybridization between the two species of brown algae Fucus spiralis and F. vesiculosus. Individual-centered networks were analyzed on the basis of microsatellite genotypes from North Africa to the Pacific American coast, through the North Atlantic. Two genetic distances integrating different time steps were used, the Rozenfeld (RD; based on alleles divergence) and the Shared Allele (SAD; based on alleles identity) distances. A diagnostic level of genotype divergence and clustering of individuals from each species was obtained through RD while screening for exchanges through putative hybridization was facilitated using SAD. Intermediate individuals linking both clusters on the RD network were those sampled at the limits of the sympatric zone in Northwest Iberia. Conclusion: These results suggesting rare hybridization were confirmed by simulation of hybrids and F2 with directed backcrosses. Comparison with the Bayesian method STRUCTURE confirmed the usefulness of both approaches and emphasized the reliability of network analysis to unravel and study hybridization

Predicting the Impact of Climate Change on Threatened Species in UK Waters

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina)

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Pharmacogenomics in diabetes mellitus:insights into drug action and drug discovery

Genomic studies have greatly advanced our understanding of the multifactorial aetiology of type 2 diabetes mellitus (T2DM) as well as the multiple subtypes of monogenic diabetes mellitus. In this Review, we discuss the existing pharmacogenetic evidence in both monogenic diabetes mellitus and T2DM. We highlight mechanistic insights from the study of adverse effects and the efficacy of antidiabetic drugs. The identification of extreme sulfonylurea sensitivity in patients with diabetes mellitus owing to heterozygous mutations in HNF1A represents a clear example of how pharmacogenetics can direct patient care. However, pharmacogenomic studies of response to antidiabetic drugs in T2DM has yet to be translated into clinical practice, although some moderate genetic effects have now been described that merit follow-up in trials in which patients are selected according to genotype. We also discuss how future pharmacogenomic findings could provide insights into treatment response in diabetes mellitus that, in addition to other areas of human genetics, facilitates drug discovery and drug development for T2DM.</p

Lp-PLA2 activity is associated with increased risk of diabetic retinopathy:a longitudinal disease progression study

Aims/hypothesis: The aim of the study was to examine the association between lipoprotein-associated phospholipase A2 (Lp-PLA2) activity levels and incident diabetic retinopathy and change in retinopathy grade.Methods: This was a cohort study of diabetic participants with serum collected at baseline and routinely collected diabetic retinal screening data. Participants with type 2 diabetes from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) cohort were used. This cohort is composed of individuals of white Scottish ancestry from the Tayside region of Scotland. Survival analysis accounting for informative censoring by modelling death as a competing risk was performed for the development of incident diabetic retinopathy from a disease-free state in a 3 year follow-up period (n = 1364) by stratified LpPLA2 activity levels (in quartiles). The same analysis was performed for transitions to more severe grades.Results: The hazard of developing incident diabetic retinopathy was 2.08 times higher (95% CI 1.64, 2.63) for the highest quartile of Lp-PLA2 activity compared with the lowest. Higher Lp-PLA2 activity levels were associated with a significantly increased risk for transitions to all grades. The hazards of developing observable (or more severe) and referable (or more severe) retinopathy were 2.82 (95% CI 1.71, 4.65) and 1.87 (95% CI 1.26, 2.77) times higher for the highest quartile of Lp-PLA2 activity compared with the lowest, respectively.Conclusions/interpretation: Higher Lp-PLA2 levels are associated with increased risk of death and the development of incident diabetic retinopathy, as well as transitions to more severe grades of diabetic retinopathy. These associations are independent of calculated LDL-cholesterol and other traditional risk factors. Further, this biomarker study shows that the association is temporally sensitive to the proximity of the event to measurement of Lp-PLA2

Operation and performance of the ATLAS Tile Calorimeter in Run 1

The Tile Calorimeter is the hadron calorimeter covering the central region of the ATLAS experiment at the Large Hadron Collider. Approximately 10,000 photomultipliers collect light from scintillating tiles acting as the active material sandwiched between slabs of steel absorber. This paper gives an overview of the calorimeter’s performance during the years 2008–2012 using cosmic-ray muon events and proton–proton collision data at centre-of-mass energies of 7 and 8TeV with a total integrated luminosity of nearly 30 fb−1. The signal reconstruction methods, calibration systems as well as the detector operation status are presented. The energy and time calibration methods performed excellently, resulting in good stability of the calorimeter response under varying conditions during the LHC Run 1. Finally, the Tile Calorimeter response to isolated muons and hadrons as well as to jets from proton–proton collisions is presented. The results demonstrate excellent performance in accord with specifications mentioned in the Technical Design Report

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe