Processing of alcohol-related health threat in at-risk drinkers: an online study of gender-related self-affirmation effects

Aims: Defensiveness in response to threatening health information related to excessive alcohol consumption prevents appropriate behaviour change. Alternatively, self-affirmation may improve cognitive-affective processing of threatening information, thus contributing to successful self-regulation. Methods: Effects of an online self-affirmation procedure were examined in at-risk university student drinkers. Participants were randomly assigned to a self-affirmation (writing about personally relevant values) or control task (writing about values relevant to another person) prior to presentation of alcohol-related threatening information. Assessment of prosocial feelings (e.g. ‘love’) after the task served as a manipulation check. Generic and personalized information regarding the link between alcohol use and cancer was presented, followed by assessment of perceived threat, message avoidance and derogation. Page dwell-times served as indirect indices of message engagement. Alcohol consumption and intention to drink less were assessed during the first online session and at 1-week and 1-month follow-up. Results: Although self-affirmation resulted in higher levels of prosocial feelings immediately after the task, there was no effect on behaviour in the self-affirmation group. Effects on intention were moderated by gender, such that men showed lower intention immediately after self-affirmation, but this increased at 1-week follow-up. Women's intention to reduce consumption in the self-affirmation group reduced over time. Trend-level effects on indices of derogation and message acceptance were in the predicted direction only in men. Conclusion: It is feasible to perform self-affirmation procedures in an online environment with at-risk drinkers. However, use of internet-based procedures with this population may give rise to (gender-dependent) effects that are substantially diluted compared with lab-based experiments

Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins.

Funder: ExscientiaFunder: Diamond Light SourceFunder: Kungliga Tekniska HoegskolanFunder: Chinese Center for Disease Control and PreventionFunder: European Federation of Pharmaceutical Industries and AssociationsFunder: European CommissionFunder: Kennedy Trust for Rheumatology ResearchFunder: Ontario Institute for Cancer ResearchFunder: Royal Institution for the Advancement of Learning McGill UniversityFunder: UCBSelectivity is a crucial property in small molecule development. Binding site comparisons within a protein family are a key piece of information when aiming to modulate the selectivity profile of a compound. Binding site differences can be exploited to confer selectivity for a specific target, while shared areas can provide insights into polypharmacology. As the quantity of structural data grows, automated methods are needed to process, summarize, and present these data to users. We present a computational method that provides quantitative and data-driven summaries of the available binding site information from an ensemble of structures of the same protein. The resulting ensemble maps identify the key interactions important for ligand binding in the ensemble. The comparison of ensemble maps of related proteins enables the identification of selectivity-determining regions within a protein family. We applied the method to three examples from the well-researched human bromodomain and kinase families, demonstrating that the method is able to identify selectivity-determining regions that have been used to introduce selectivity in past drug discovery campaigns. We then illustrate how the resulting maps can be used to automate comparisons across a target protein family

Investigating the missing data mechanism in quality of life outcomes: a comparison of approaches

Background: Missing data is classified as missing completely at random (MCAR), missing at random (MAR) or missing not at random (MNAR). Knowing the mechanism is useful in identifying the most appropriate analysis. The first aim was to compare different methods for identifying this missing data mechanism to determine if they gave consistent conclusions. Secondly, to investigate whether the reminder-response data can be utilised to help identify the missing data mechanism. Methods: Five clinical trial datasets that employed a reminder system at follow-up were used. Some quality of life questionnaires were initially missing, but later recovered through reminders. Four methods of determining the missing data mechanism were applied. Two response data scenarios were considered. Firstly, immediate data only; secondly, all observed responses (including reminder-response). Results: In three of five trials the hypothesis tests found evidence against the MCAR assumption. Logistic regression suggested MAR, but was able to use the reminder-collected data to highlight potential MNAR data in two trials. Conclusion: The four methods were consistent in determining the missingness mechanism. One hypothesis test was preferred as it is applicable with intermittent missingness. Some inconsistencies between the two data scenarios were found. Ignoring the reminder data could potentially give a distorted view of the missingness mechanism. Utilising reminder data allowed the possibility of MNAR to be considered.The Chief Scientist Office of the Scottish Government Health Directorate. Research Training Fellowship (CZF/1/31

A comprehensive radio view of the extremely bright gamma-ray burst 130427A

GRB 130427A was extremely bright as a result of occurring at low redshift whilst the energetics were more typical of high-redshift gamma-ray bursts (GRBs). We collected well-sampled light curves at 1.4 and 4.8 GHz of GRB 130427A with the Westerbork Synthesis Radio Telescope (WSRT); and we obtained its most accurate position with the European Very Long Baseline Interferometry Network (EVN). Our flux density measurements are combined with all the data available at radio, optical and X-ray frequencies to perform broad-band modelling in the framework of a reverse–forward shock model and a two-component jet model, and we discuss the implications and limitations of both models. The low density inferred from the modelling implies that the GRB 130427A progenitor is either a very low metallicity Wolf–Rayet star, or a rapidly rotating, low-metallicity O star. We also find that the fraction of the energy in electrons is evolving over time, and that the fraction of electrons participating in a relativistic power-law energy distribution is less than 15 per cent. We observed intraday variability during the earliest WSRT observations, and the source sizes inferred from our modelling are consistent with this variability being due to interstellar scintillation effects. Finally, we present and discuss our limits on the linear and circular polarization, which are among the deepest limits of GRB radio polarization to date