9 research outputs found

    A comparison of body composition assessment methods in climbers: Which is better?

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    Objective To compare body composition estimations of field estimation methods: Durnin & Womersley anthropometry (DW-ANT), bioelectrical impedance analysis (BIA) and Deborah-Kerr anthropometry (DK-ANT) against dual-energy X-ray absorptiometry (DXA) in a male Chilean sport climbing sample. Methods 30 adult male climbers of different performance levels participated in the study. A DXA scan (Lunar Prodigy (R)) was used to determine fat mass, lean mass and total bone mineral content (BMC). Total muscle mass (MM, kg) was estimated through a validated prediction model. DW-ANT and BIA ("non-athletes" and "athletes" equations) were used to determinate fat mass percentage (FM %), while DK-ANT was utilized to estimate MM and BMC. Results A significant (p<0.01) inter-method difference was observed for all methods analyzed. When compared to DXA, DW-ANT and BIA underestimated FM% and DK-ANT overestimated MM and BMC (All p< 0.01). The inter-method differences was lower for DW-ANT. Discussion We found that body composition estimation in climbers is highly method dependent. If DXA is not available, DW-ANT for FM% has a lower bias of estimation than BIA in young male Chilean climbers. For MM and BMC, further studies are needed to compare and estimate the DK-ANT bias level. For both methods, correction equations for specific climbing population should be considered

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

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    Mapping the human genetic architecture of COVID-19

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    The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

    Fish as bioindicators: coal and mercury pollution in Colombia’s ecosystems

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    Mapping the human genetic architecture of COVID-19

    Get PDF
    The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease
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