14 research outputs found

    “Others-in-Law”: Legalism in the Economy of Religious Differences

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    Religious legalism encompasses a wide range of attitudes that assign religious meaning to legal content or to legal compliance. The phenomenology of religious legalism is assuming a significant role in various contemporary debates about legal pluralism, accommodation of religious minorities, religious freedom, and so forth. This article revises this conception and the commonplace equation of Judaism and legalism. It suggests that we ought to regard both as part of the economy of religious differences by which religious identities are expressed and defined as alternatives. The common ascription of religious legalism to Judaism (and Islam) is criticized here through a historical analysis of the law-religion-identity matrix in three cultural settings: late ancient Judeo-Hellenic, medieval Judeo–Arabic, and post-Reformation Europe

    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)

    Population Turnover in a Microcystis Bloom Results in Predominantly Nontoxigenic Variants Late in the Season▿ †

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    Surface samples of the 2007 Microcystis bloom occurring in Copco Reservoir on the Klamath River in Northern California were analyzed genetically by sequencing clone libraries made with amplicons at three loci: the internal transcribed spacer of the rRNA operon (ITS), cpcBA, and mcyA. Samples were taken between June and October, during which time two cell count peaks occurred, in mid-July and early September. The ITS and cpcBA loci could be classified into four or five allele groups, which provided a convenient means for describing the Microcystis population and its changes over time. Each group was numerically dominated by a single, highly represented sequence. Other members of each group varied by changes at 1 to 3 nucleotide positions, while groups were separated by up to 30 nucleotide differences. As deduced by a partial sampling of the clone libraries, there were marked population turnovers during the season, indicated by changes in allele composition at both the ITS and cpcBA loci. Different ITS and cpcBA genotypes appeared to be dominant at the two population peaks. Toxicity (amount of microcystin per cell) and toxigenic potential (mcyB copy number) were lower during the second peak, and the mcyB copy number fell further as the bloom declined
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