Changes in Body Weight and Psychotropic Drugs: A Systematic Synthesis of the Literature

<div><h3>Introduction</h3><p>Psychotropic medication use is associated with weight gain. While there are studies and reviews comparing weight gain for psychotropics within some classes, clinicians frequently use drugs from different classes to treat psychiatric disorders.</p> <h3>Objective</h3><p>To undertake a systematic review of all classes of psychotropics to provide an all encompassing evidence-based tool that would allow clinicians to determine the risks of weight gain in making both intra-class and interclass choices of psychotropics.</p> <h3>Methodology and Results</h3><p>We developed a novel hierarchical search strategy that made use of systematic reviews that were already available. When such evidence was not available we went on to evaluate randomly controlled trials, followed by cohort and other clinical trials, narrative reviews, and, where necessary, clinical opinion and anecdotal evidence. The data from the publication with the highest level of evidence based on our hierarchical classification was presented. Recommendations from an expert panel supplemented the evidence used to rank these drugs within their respective classes. Approximately 9500 articles were identified in our literature search of which 666 citations were retrieved. We were able to rank most of the psychotropics based on the available evidence and recommendations from subject matter experts. There were few discrepancies between published evidence and the expert panel in ranking these drugs.</p> <h3>Conclusion</h3><p>Potential for weight gain is an important consideration in choice of any psychotropic. This tool will help clinicians select psychotropics on a case-by-case basis in order to minimize the impact of weight gain when making both intra-class and interclass choices.</p> </div

A second update on mapping the human genetic architecture of COVID-19

Matters Arising From: COVID-19 Host Genetics Initiative. Nature https://doi.org/10.1038/s41586-021-03767-x (2021)Data availability: Summary statistics generated by the COVID-19 HGI are available online, including per-ancestry summary statistics for African, admixed American, East Asian, European and South Asian ancestries (https://www.covid19hg.org/results/r7/). The analyses described here used the data release 7. If available, individual-level data can be requested directly from contributing studies, listed in Supplementary Table 1. We used publicly available data from GTEx (https://gtexportal.org/home/), the Neale laboratory (http://www.nealelab.is/uk-biobank/), the Finucane laboratory (https://www.finucanelab.org), the FinnGen Freeze 4 cohort (https://www.finngen.fi/en/access_results) and the eQTL catalogue release 3 (http://www.ebi.ac.uk/eqtl/).Code availability: The code for summary statistics lift-over, the projection PCA pipeline including precomputed loadings and meta-analyses (https://github.com/covid19-hg/); for heritability estimation (https://github.com/AndrewsLabUCSF/COVID19_heritability); for Mendelian randomization and genetic correlation (https://github.com/marcoralab/MRcovid); and subtype analyses (https://github.com/mjpirinen/covid19-hgi_subtypes) are available at GitHub.Reporting summary: Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article online at: https://www.nature.com/articles/s41586-023-06355-3#MOESM2 .Supplementary information is available online at: https://www.nature.com/articles/s41586-023-06355-3#Sec4 .Copyright © The Author(s) 2023. Investigating the role of host genetic factors in COVID-19 severity and susceptibility can inform our understanding of the underlying biological mechanisms that influence adverse outcomes and drug development1,2. Here we present a second updated genome-wide association study (GWAS) on COVID-19 severity and infection susceptibility to SARS-CoV-2 from the COVID-19 Host Genetic Initiative (data release 7). We performed a meta-analysis of up to 219,692 cases and over 3 million controls, identifying 51 distinct genome-wide significant loci—adding 28 loci from the previous data release2. The increased number of candidate genes at the identified loci helped to map three major biological pathways that are involved in susceptibility and severity: viral entry, airway defence in mucus and type I interferon

Effect of fine to coarse aggregate ratio on the rheology and fracture energy of steel fibre reinforced self-compacting concretes

In this study, the influence of aggregate grading and steel fibre properties on the flow properties and fracture energy of steel fibre reinforced self-compacting concrete (SFRSCC) has been investigated. Two types of hooked-end steel fibres at three different dosages (20,40 and 60 kg/m(3)) were incorporated into self-compacting mixtures having similar paste contents but different fine to coarse aggregate (FA/CA) ratios (0.94, 1.72 and 2.50 by weight). Besides the flowability and passing ability of fresh concrete, the mechanical properties of hardened concrete including the fracture energy have also been investigated. The relations between flexural parameters and fibre orientation were established by image analysis technique. Test results showed that hooked-end steel fibre inclusion into the plain self-compacting concrete negatively affects the flowability and passing ability of the mixture. Increasing FA/CA ratio enhances these rheological parameters and provides better fibre orientation. On the other hand, increasing FA/CA ratio decreases the fracture energy of plain SCC mixtures and the fibre incorporated series which were less affected from fibre inclusion follow the same trend with the plain SCC. The proper FA/CA ratio for the best rheological and mechanical performance depends on the fibre content, aspect ratio and their influence on the flowability of the mixture. In order to obtain better fibre orientation and hence higher fracture energy, relatively higher FA/CA ratios should be used when the fibre content and aspect ratio are relatively high