119 research outputs found

    Selenium-containing amino acids are targets for myeloperoxidase-derived hypothiocyanous acid: determination of absolute rate constants and implications for biological damage

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    Elevated MPO (myeloperoxidase) levels are associated with multiple human inflammatory pathologies. MPO catalyses the oxidation of Cl−, Br− and SCN− by H2O2 to generate the powerful oxidants hypochlorous acid (HOCl), hypobromous acid (HOBr) and hypothiocyanous acid (HOSCN) respectively. These species are antibacterial agents, but misplaced or excessive production is implicated in tissue damage at sites of inflammation. Unlike HOCl and HOBr, which react with multiple targets, HOSCN targets cysteine residues with considerable selectivity. In the light of this reactivity, we hypothesized that Sec (selenocysteine) residues should also be rapidly oxidized by HOSCN, as selenium atoms are better nucleophiles than sulfur. Such oxidation might inactivate critical Sec-containing cellular protective enzymes such as GPx (glutathione peroxidase) and TrxR (thioredoxin reductase). Stopped-flow kinetic studies indicate that seleno-compounds react rapidly with HOSCN with rate constants, k, in the range 2.8×103–5.8×106 M−1·s−1 (for selenomethionine and selenocystamine respectively). These values are ~6000-fold higher than the corresponding values for H2O2, and are also considerably larger than for the reaction of HOSCN with thiols (16-fold for cysteine and 80-fold for selenocystamine). Enzyme studies indicate that GPx and TrxR, but not glutathione reductase, are inactivated by HOSCN in a concentration-dependent manner; k for GPx has been determined as ~5×105 M−1·s−1. Decomposed HOSCN did not induce inactivation. These data indicate that selenocysteine residues are oxidized rapidly by HOSCN, with this resulting in the inhibition of the critical intracellular Sec-dependent protective enzymes GPx and TrxR

    The Treatment In Morning versus Evening (TIME) study:Analysis of recruitment, follow-up and retention rates post-recruitment

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    Abstract Background The use of information technology (IT) is now the preferred method of capturing and storing clinical research data. The Treatment In Morning versus Evening (TIME) study predominantly uses electronic data capture and IT to compare morning dosing of hypertensive medication against evening dosing. Registration, consent, participant demographics and follow-up data are all captured via the study website. The aim of this article is to assess the success of the TIME methodology compared with similar studies. Methods To assess the TIME study, published literature on similar clinical trials was reviewed and compared against TIME recruitment, follow-up and email interaction data. Results The TIME website registered 31,695 individuals, 21,116 of whom were randomised. Recruitment cost per randomised participant varied by strategy: £17.40 by GP practice, £3.08 by UK Biobank and £58.82 for GoShare. Twelve-month follow-up retention rates were 96%. A total of 1089 participants have withdrawn from their assigned time of dosing, 2% of whom have declined follow-up by record linkage or further contact. When the TIME data are compared with similar study data, study recruitment is very successful. However, TIME suffers difficulties with participant follow-up and withdrawal rates similar to those of conventional studies. Conclusions The TIME study has been successful in recruitment. Follow-up, retention rates and withdrawal rates are all acceptable, but ongoing work is required to ensure participants remain engaged with the study. Various recruitment strategies are necessary, and all viable options should be encouraged to maintain participant engagement throughout the life of studies using IT

    Network Formation with Local Complements and Global Substitutes: The Case of R&D Networks

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    CMS physics technical design report : Addendum on high density QCD with heavy ions

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    Use of anticoagulants and antiplatelet agents in stable outpatients with coronary artery disease and atrial fibrillation. International CLARIFY registry

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    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

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
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