293 research outputs found

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

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    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

    Risks of introduction and economic consequences associated with African swine fever, classical swine fever and foot-and-mouth disease: A review of the literature

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    African swine fever (ASF), classical swine fever (CSF) and foot-and-mouth disease (FMD) are considered to be three of the most detrimental animal diseases and are currently foreign to the U.S. Emerging and re-emerging pathogens can have tremendous impacts in terms of livestock morbidity and mortality events, production losses, forced trade restrictions, and costs associated with treatment and control. The United States is the world\u27s top producer of beef for domestic and export use and the world\u27s third-largest producer and consumer of pork and pork products; it has also recently been either the world\u27s largest or second largest exporter of pork and pork products. Understanding the routes of introduction into the United States and the potential economic impact of each pathogen are crucial to (a) allocate resources to prevent routes of introduction that are believed to be more probable, (b) evaluate cost and efficacy of control methods and (c) ensure that protections are enacted to minimize impact to the most vulnerable industries. With two scoping literature reviews, pulled from global data, this study assesses the risk posed by each disease in the event of a viral introduction into the United States and illustrates what is known about the economic costs and losses associated with an outbreak

    First-in-Human Phase I Study of the OX40 Agonist GSK3174998 With or Without Pembrolizumab in Patients With Selected Advanced Solid Tumors (Engage-1)

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    BACKGROUND: The phase I first-in-human study ENGAGE-1 evaluated the humanized IgG1 OX40 agonistic monoclonal antibody GSK3174998 alone (Part 1 (P1)) or in combination with pembrolizumab (Part 2 (P2)) in patients with advanced solid tumors. METHODS: GSK3174998 (0.003-10 mg/kg) ± pembrolizumab (200 mg) was administered intravenously every 3 weeks using a continuous reassessment method for dose escalation. Primary objectives were safety and tolerability; secondary objectives included pharmacokinetics, immunogenicity, pharmacodynamics, and clinical activity. RESULTS: 138 patients were enrolled (45 (P1) and 96 (P2, including 3 crossovers)). Treatment-related adverse events occurred in 51% (P1) and 64% (P2) of patients, fatigue being the most common (11% and 24%, respectively). No dose-toxicity relationship was observed, and maximum-tolerated dose was not reached. Dose-limiting toxicities (P2) included Grade 3 (G3) pleural effusion and G1 myocarditis with G3 increased troponin. GSK3174998 ≥0.3 mg/kg demonstrated pharmacokinetic linearity and \u3e80% receptor occupancy on circulating T cells; 0.3 mg/kg was selected for further evaluation. Limited clinical activity was observed for GSK3174998 (P1: disease control rate (DCR) ≥24 weeks 9%) and was not greater than that expected for pembrolizumab alone (P2: overall response rate 8%, DCR ≥24 weeks 28%). Multiplexed immunofluorescence data from paired biopsies suggested that increased infiltration of natural killer (NK)/natural killer T (NKT) cells and decreased regulatory T cells (Tregs) in the tumor microenvironment may contribute to clinical responses: CD16+CD56-CD134+ NK /NKT cells and CD3+CD4+FOXP3+CD134+ Tregs exhibited the largest magnitude of change on treatment, whereas CD3+CD8+granzyme B+PD-1+CD134+ cytotoxic T cells were the least variable. Tumor gene expression profiling revealed an upregulation of inflammatory responses, T-cell proliferation, and NK cell function on treatment with some inflammatory cytokines upregulated in peripheral blood. However, target engagement, evidenced by pharmacologic activity in peripheral blood and tumor tissue, did not correlate with clinical efficacy. The low number of responses precluded identifying a robust biomarker signature predictive of response. CONCLUSIONS: GSK3174998±pembrolizumab was well tolerated over the dose range tested and demonstrated target engagement. Limited clinical activity does not support further development of GSK3174998±pembrolizumab in advanced cancers. TRIAL REGISTRATION NUMBER: NCT02528357

    Individual Differences in Processing Speed and Working Memory Speed as Assessed with the Sternberg Memory Scanning Task

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    The Sternberg Memory Scanning (SMS) task provides a measure of processing speed (PS) and working memory retrieval speed (WMS). In this task, participants are presented with sets of stimuli that vary in size. After a delay, one item is presented, and participants indicate whether or not the item was part of the set. Performance is assessed by speed and accuracy for both the positive (item is part of the set) and the negative trials (items is not part of the set). To examine the causes of variation in PS and WMS, 623 adult twins and their siblings completed the SMS task. A non-linear growth curve (nLGC) model best described the increase in reaction time with increasing set size. Genetic analyses showed that WMS (modeled as the Slope in the nLGC model) has a relatively small variance which is not due to genetic variation while PS (modeled as the Intercept in the nLGC model) showed large individual differences, part of which could be attributed to additive genetic factors. Heritability was 38% for positive and 32% for negative trials. Additional multivariate analyses showed that the genetic effects on PS for positive and negative trials were completely shared. We conclude that genetic influences on working memory performance are more likely to act upon basic processing speed and (pre)motoric processes than on the speed with which an item is retrieved from short term memory

    Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies

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    Background The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this ‘missing heritability’ have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms. Methodology We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants. Conclusion We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20-99

    Genetic mechanisms of critical illness in COVID-19.

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    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

    Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

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    The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

    Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients

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