Parsimony and Maximum Likelihood phylogenetic analyses of morphology do not generally integrate uncertainty in inferring evolutionary history:A response to Brown et al.

Our recent study evaluated the performance of parsimony and probabilistic models of phylogenetic inference based on categorical data [1]. We found that a Bayesian implementation of a probabilistic Markov model produced more accurate results than either of the competing parsimony approaches (the main method currently employed), and the maximum-likelihood implementation of the same model. This occurs principally because the results of Bayesian analyses are less resolved (less precise) as a measure of topological uncertainty is intrinsically recovered in this MCMC-based approach and can be used to construct a majority-rule consensus tree that reflects this. Of the three main methods, maximum likelihood performed theworst of all as a single exclusively bifurcating tree is estimated in this framework which does not integrate an intrinsic measure of support.N

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Longitudinal Assessment and Functional Neuroimaging of Movement Variability Reveal Novel Insights Into Motor Dysfunction in Clinical High Risk for Psychosis.

Motor dysfunction in youth at clinical high risk (CHR) for psychosis is thought to reflect abnormal neurodevelopment within cortical-subcortical motor circuits and may be important for understanding clinical trajectories of CHR individuals. However, to date, our perspective of brain-behavior relationships has been informed solely by cross-sectional correlational studies linking behavior in the lab to brain structure or respective resting-state network connectivity. Here, we assess movement dysfunction from 2 perspectives: study 1 investigates the longitudinal progression of handwriting variability and positive symptoms in a sample of 91 CHR and healthy controls during a 12-month follow-up and study 2 involves a multiband functional magnetic resonance imaging task exploring the relationship between power grip force stability and motor network brain activation in a subset of participants. In study 1, we found that greater handwriting variability was a stable feature of CHR participants who experienced worse symptom progression. Study 2 results showed that CHR individuals had greater variability in their grip force and greater variability was related to decreased activation in the associative cortico-striatal network compared to controls. Motor variability may be a stable marker of vulnerability for psychosis risk and possible indicator of a vulnerable cortico-striatal brain network functioning in CHR participants, although the effects of antipsychotic medication should be considered