25 research outputs found

    Fluctuating risk of acute kidney injury-related mortality for four weeks after exposure to air pollution: A multi-country time-series study in 6 countries.

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    BACKGROUND: Recent studies have reported that air pollution is related to kidney diseases. However, the global evidence on the risk of death from acute kidney injury (AKI) owing to air pollution is limited. Therefore, we investigated the association between short-term exposure to air pollution-particulate matter ≤ 2.5 μm (PM2.5), ozone (O3), and nitrogen dioxide (NO2)-and AKI-related mortality using a multi-country dataset. METHODS: This study included 41,379 AKI-related deaths in 136 locations in six countries during 1987-2018. A novel case time-series design was applied to each air pollutant during 0-28 lag days to estimate the association between air pollution and AKI-related deaths. Moreover, we calculated AKI deaths attributable to non-compliance with the World Health Organization (WHO) air quality guidelines. RESULTS: The relative risks (95% confidence interval) of AKI-related deaths are 1.052 (1.003, 1.103), 1.022 (0.994, 1.050), and 1.022 (0.982, 1.063) for 5, 10, and 10 µg/m3 increase in lag 0-28 days of PM2.5, warm-season O3, and NO2, respectively. The lag-distributed association showed that the risk appeared immediately on the day of exposure to air pollution, gradually decreased, and then increased again reaching the peak approximately 20 days after exposure to PM2.5 and O3. We also found that 1.9%, 6.3%, and 5.2% of AKI deaths were attributed to PM2.5, warm-season O3, and NO2 concentrations above the WHO guidelines. CONCLUSIONS: This study provides evidence that public health policies to reduce air pollution may alleviate the burden of death from AKI and suggests the need to investigate the several pathways between air pollution and AKI death

    Minimal information for studies of extracellular vesicles 2018 (MISEV2018):a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines

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    The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points

    Кераміка «terra sigillata» з с. Зимне на Волині

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    Стаття присвячена публікації чотирьох керамічних посудин типу «terra sigillata», знайдених на дні р. Луги у с. Зимне Володимир-Волинського району Волинської області. Попередній аналіз цих знахідок дозволяє віднести їх до Понтійського центру виробництва такого посуду. Вірогідним шляхом потрапляння цієї колекції на Волинь була готська експансія у Північне Причорномор’я

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    From the ground up: cultivating teacher educator knowledge from the situated knowledges of emerging, asset-oriented teacher educators

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    This article offers findings from a qualitative study of the development of novice, asset-oriented teacher educators in the U.S. who, over three years, engaged monthly in an informal learning space inspired by Freirean Culture Circles and Boalian Theatre of the Oppressed. The article outlines the dynamic knowledges, perspectives, and tools that emerged as central to participants’ understandings about facilitating asset-oriented learning among prospective and practicing teachers in school and university settings. The article then argues that learning arrangements designed to support the coconstruction of contextualized, embodied understandings of asset-oriented teacher education hold special promise for equipping teacher educators to transform teacher education from an enterprise that centers whiteness to one that advances equity and justice

    Associations between greenness and kidney disease in Massachusetts: The US Medicare longitudinal cohort study

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    Background: Recent studies have identified the association of environmental stressors with reduced kidney function and the development of kidney disease. While residential greenness has been linked to many health benefits, the association between residential greenness and the development of kidney disease is not clear. We aimed to investigate the association between residential greenness and the development of kidney disease. Methods: We performed a longitudinal population-based cohort study including all fee-for-service Medicare Part A beneficiaries (aged 65 years or older) in Massachusetts (2000–2016). We assessed greenness with the annual average Enhanced Vegetation Index (EVI) based on residential ZIP codes of beneficiaries. We applied Cox-equivalent Poisson models to estimate the association between EVI and first hospital admission for total kidney disease, chronic kidney disease (CKD), and acute kidney injury (AKI), separately. Results: Data for 1,462,949 beneficiaries who resided in a total of 644 ZIP codes were analyzed. The total person-years of follow-up for total kidney disease, CKD, and AKI were 9.8, 10.9, and 10.8 million person-years, respectively. For a 0.1 increase in annual EVI, the hazard ratios (HRs) were 0.95 (95% CI: 0.93 to 0.97) for the first hospital admission for total kidney disease, and the association was more prominent for AKI (HR: 0.94 with 95% CI: 0.92 to 0.97) than CKD (HR: 0.98 with 95% CI: 0.95–1.01]). The estimated effects of EVI on kidney disease were generally more evident in White beneficiaries and those residing in metropolitan areas compared to the overall population. Conclusions: This study found that higher levels of annual residential greenness were associated with a lower risk of the first hospital admission for kidney diseases. Results are consistent with the hypothesis that higher residential greenness benefits kidney patients

    Markers of myocardial damage predict mortality in patients with aortic stenosis

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    Background: Cardiovascular magnetic resonance (CMR) is increasingly used for risk stratification in aortic stenosis (AS). However, the relative prognostic power of CMR markers and their respective thresholds remains undefined. Objectives: Using machine learning, the study aimed to identify prognostically important CMR markers in AS and their thresholds of mortality. Methods: Patients with severe AS undergoing AVR (n = 440, derivation; n = 359, validation cohort) were prospectively enrolled across 13 international sites (median 3.8 years' follow-up). CMR was performed shortly before surgical or transcatheter AVR. A random survival forest model was built using 29 variables (13 CMR) with post-AVR death as the outcome. Results: There were 52 deaths in the derivation cohort and 51 deaths in the validation cohort. The 4 most predictive CMR markers were extracellular volume fraction, late gadolinium enhancement, indexed left ventricular end-diastolic volume (LVEDVi), and right ventricular ejection fraction. Across the whole cohort and in asymptomatic patients, risk-adjusted predicted mortality increased strongly once extracellular volume fraction exceeded 27%, while late gadolinium enhancement >2% showed persistent high risk. Increased mortality was also observed with both large (LVEDVi >80 mL/m2) and small (LVEDVi ≤55 mL/m2) ventricles, and with high (>80%) and low (≤50%) right ventricular ejection fraction. The predictability was improved when these 4 markers were added to clinical factors (3-year C-index: 0.778 vs 0.739). The prognostic thresholds and risk stratification by CMR variables were reproduced in the validation cohort. Conclusions: Machine learning identified myocardial fibrosis and biventricular remodeling markers as the top predictors of survival in AS and highlighted their nonlinear association with mortality. These markers may have potential in optimizing the decision of AVR
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