Neonatal research:the parental perspective

Objectives: To investigate the recollections of parents consenting for their infants to be research subjects and determine their views about the need for consent. Subjects: Parents of 154 sick newborn infants enrolled in a randomised trial in the early neonatal period. All parents had given written consent and received printed information. Methods: A questionnaire and accompanying letter was sent to the parental home 18 months later. Non-responders were sent a further questionnaire and letter. Results: Response rate was 64% (99/154). Some respondents (12%) did not remember being asked to consent to their baby joining a study, and a further 6% were unsure. Most of the respondents (79%) were happy, 13% neutral, and 8% unhappy with their decision to give consent. None felt heavy pressure to agree. Entering the trial caused 24% of respondents to feel more anxious, 56% neutral, and 20% less anxious about their baby. Most of the respondents (83%) would be unhappy to forgo the consent process for trials passed by the institutional ethics committee. Conclusions: A significant proportion of parents who give written consent for a trial in the early neonatal period do not later remember having done so. Parents who have had experience of neonatal research would be unhappy for their baby to be enrolled in a study that had ethics committee approval without their consent being obtained

The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc

The Human Gene Mutation Database: 2008 update

The Human Gene Mutation Database (HGMD®) is a comprehensive core collection of germline mutations in nuclear genes that underlie or are associated with human inherited disease. Here, we summarize the history of the database and its current resources. By December 2008, the database contained over 85,000 different lesions detected in 3,253 different genes, with new entries currently accumulating at a rate exceeding 9,000 per annum. Although originally established for the scientific study of mutational mechanisms in human genes, HGMD has since acquired a much broader utility for researchers, physicians, clinicians and genetic counselors as well as for companies specializing in biopharmaceuticals, bioinformatics and personalized genomics. HGMD was first made publicly available in April 1996, and a collaboration was initiated in 2006 between HGMD and BIOBASE GmbH. This cooperative agreement covers the exclusive worldwide marketing of the most up-to-date (subscription) version of HGMD, HGMD Professional, to academic, clinical and commercial users

Post-Foucauldian governmentality: what does it offer critical social policy analysis?

This article considers the theoretical perspective of post-Foucauldian governmentality, especially the insights and challenges it poses for applied researchers within the critical social policy tradition. The article firstly examines the analytical strengths of this approach to understanding power and rule in contemporary society, before moving on to consider its limitations for social policy. It concludes by arguing that these insights can be retained, and some of the weaknesses overcome, by adopting a ‘realist governmentality’ approach (Stenson 2005, 2008). This advocates combining traditional discursive analysis with more ethnographic methods in order to render visible the concrete activity of governing, and unravel the messiness, complexity and unintended consequences involved in the struggles around subjectivity

X-CAP improves pathogenicity prediction of stopgain variants

Abstract: Stopgain substitutions are the third-largest class of monogenic human disease mutations and often examined first in patient exomes. Existing computational stopgain pathogenicity predictors, however, exhibit poor performance at the high sensitivity required for clinical use. Here, we introduce a new classifier, termed X-CAP, which uses a novel training methodology and unique feature set to improve the AUROC by 18% and decrease the false-positive rate 4-fold on large variant databases. In patient exomes, X-CAP prioritizes causal stopgains better than existing methods do, further illustrating its clinical utility. X-CAP is available at https://github.com/bejerano-lab/X-CAP

The Effects of COVID-19 Restrictions on College Students Physical Activity and Mental Health

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CDG: an online server proposing biologically closest disease-causing genes and pathologies and its application to primary immunodeficiency

Summary: In analyses of exome data, candidate gene selection can be challenging in the absence of variants in known disease-causing genes. We calculated the putative biologically closest known disease-causing genes for 13,005 human genes not currently reported to be disease-causing. We used these data to construct the Closest Disease-Causing Genes (CDG) server, which can be used to infer the closest associated disease-causing genes and phenotypes for lists of candidate genes. This resource will be a considerable asset for ascertaining the poten-tial relevance of lists of genes to specific diseases of interest

A Model-Based Analysis of GC-Biased Gene Conversion in the Human and Chimpanzee Genomes

GC-biased gene conversion (gBGC) is a recombination-associated process that favors the fixation of G/C alleles over A/T alleles. In mammals, gBGC is hypothesized to contribute to variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations, but its prevalence and general functional consequences remain poorly understood. gBGC is difficult to incorporate into models of molecular evolution and so far has primarily been studied using summary statistics from genomic comparisons. Here, we introduce a new probabilistic model that captures the joint effects of natural selection and gBGC on nucleotide substitution patterns, while allowing for correlations along the genome in these effects. We implemented our model in a computer program, called phastBias, that can accurately detect gBGC tracts about 1 kilobase or longer in simulated sequence alignments. When applied to real primate genome sequences, phastBias predicts gBGC tracts that cover roughly 0.3% of the human and chimpanzee genomes and account for 1.2% of human-chimpanzee nucleotide differences. These tracts fall in clusters, particularly in subtelomeric regions; they are enriched for recombination hotspots and fast-evolving sequences; and they display an ongoing fixation preference for G and C alleles. They are also significantly enriched for disease-associated polymorphisms, suggesting that they contribute to the fixation of deleterious alleles. The gBGC tracts provide a unique window into historical recombination processes along the human and chimpanzee lineages. They supply additional evidence of long-term conservation of megabase-scale recombination rates accompanied by rapid turnover of hotspots. Together, these findings shed new light on the evolutionary, functional, and disease implications of gBGC. The phastBias program and our predicted tracts are freely available. © 2013 Capra et al

The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting

The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that are thought to underlie, or are closely associated with human inherited disease. At the time of writing (June 2020), the database contains in excess of 289,000 different gene lesions identified in over 11,100 genes manually curated from 72,987 articles published in over 3100 peer-reviewed journals. There are primarily two main groups of users who utilise HGMD on a regular basis; research scientists and clinical diagnosticians. This review aims to highlight how to make the most out of HGMD data in each setting

Quark-model study of few-baryon systems

We review the application of non-relativistic constituent quark models to study one, two and three non-strange baryon systems. We present results for the baryon spectra, potentials and observables of the NN, N$\Delta$, $\Delta\Delta$ and NN$^*(1440)$ systems, and also for the binding energies of three non-strange baryon systems. We make emphasis on observable effects related to quark antisymmetry and its interplay with quark dynamics.Comment: 82 pages, 36 figures, 18 tables. Accepted for publication in Reports on Progress in Physic