Neutralizing Antibody-Resistant Hepatitis C Virus Cell-to-Cell Transmission

Hepatitis C virus (HCV) can initiate infection by cell-free particle and cell-cell contact-dependent transmission. In this study we use a novel infectious coculture system to examine these alternative modes of infection. Cell-to-cell transmission is relatively resistant to anti-HCV glycoprotein monoclonal anti- bodies and polyclonal immunoglobulin isolated from infected individuals, providing an effective strategy for escaping host humoral immune responses. Chimeric viruses expressing the structural proteins rep- resenting the seven major HCV genotypes demonstrate neutralizing antibody-resistant cell-to-cell trans- mission. HCV entry is a multistep process involving numerous receptors. In this study we demonstrate that, in contrast to earlier reports, CD81 and the tight-junction components claudin-1 and occludin are all essential for both cell-free and cell-to-cell viral transmission. However, scavenger receptor BI (SR-BI) has a more prominent role in cell-to-cell transmission of the virus, with SR-BI-specific antibodies and small-molecule inhibitors showing preferential inhibition of this infection route. These observations highlight the importance of targeting host cell receptors, in particular SR-BI, to control viral infection and spread in the liver

A Comparison of Four Probability-Based Online and Mixed-Mode Panels in Europe

Inferential statistics teach us that we need a random probability sample to infer from a sample to the general population. In online survey research, however, volunteer access panels, in which respondents self-select themselves into the sample, dominate the landscape. Such panels are attractive due to their low costs. Nevertheless, recent years have seen increasing numbers of debates about the quality, in particular about errors in the representativeness and measurement, of such panels. In this article, we describe four probability-based online and mixed-mode panels for the general population, namely, the Longitudinal Internet Studies for the Social Sciences (LISS) Panel in the Netherlands, the German Internet Panel (GIP) and the GESIS Panel in Germany, and the Longitudinal Study by Internet for the Social Sciences (ELIPSS) Panel in France. We compare them in terms of sampling strategies, offline recruitment procedures, and panel characteristics. Our aim is to provide an overview to the scientific community of the availability of such data sources to demonstrate the potential strategies for recruiting and maintaining probability-based online panels to practitioners and to direct analysts of the comparative data collected across these panels to methodological differences that may affect comparative estimates

La plaza pública

1 archivo PDF (269 páginas) : incluye ilustraciones"El interés central de la publicación radica en discutir sobre la crisis de la “ciudad” o de la “urbanidad” que se manifiesta con más fuerza en el espacio público, ya que actualmente existen formas que obstaculizan el contacto; esto es, la relación entre personas y entre actividades dentro del espacio urbano. Algunos autores han insinuado que el espacio público está condenado a la irrelevancia, de manera que incluso plantean la existencia de los llamados “no lugares” que no están vinculados a algún sitio específico. ...

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe