59 research outputs found

    Asymptomatic Atrial Fibrillation among Hospitalized Patients:clinical correlates and in-hospital outcomes in Improving Care for Cardiovascular Disease in China-Atrial Fibrillation

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    AIMS: The clinical correlates and outcomes of asymptomatic atrial fibrillation (AF) in hospitalized patients are largely unknown. We aimed to investigate the clinical correlates and in-hospital outcomes of asymptomatic AF in hospitalized Chinese patients.METHODS AND RESULTS: We conducted a cross-sectional registry study of inpatients with AF enrolled in the Improving Care for Cardiovascular Disease in China-Atrial Fibrillation Project between February 2015 and December 2019. We investigated the clinical characteristics of asymptomatic AF and the association between the clinical correlates and the in-hospital outcomes of asymptomatic AF. Asymptomatic and symptomatic AF were defined according to the European Heart Rhythm Association score. Asymptomatic patients were more commonly males (56.3%) and had more comorbidities such as hypertension (57.4%), diabetes mellitus (18.6%), peripheral artery disease (PAD; 2.3%), coronary artery disease (55.5%), previous history of stroke/transient ischaemic attack (TIA; 17.9%), and myocardial infarction (MI; 5.4%); however, they had less prevalent heart failure (9.6%) or left ventricular ejection fractions ≀40% (7.3%). Asymptomatic patients were more often hospitalized with a non-AF diagnosis as the main diagnosis and were more commonly first diagnosed with AF (23.9%) and long-standing persistent/permanent AF (17.0%). The independent determinants of asymptomatic presentation were male sex, long-standing persistent AF/permanent AF, previous history of stroke/TIA, MI, PAD, and previous treatment with anti-platelet drugs. The incidence of in-hospital clinical events such as all-cause death, ischaemic stroke/TIA, and acute coronary syndrome (ACS) was higher in asymptomatic patients than in symptomatic patients, and asymptomatic clinical status was an independent risk factor for in-hospital all-cause death, ischaemic stroke/TIA, and ACS.CONCLUSION: Asymptomatic AF is common among hospitalized patients with AF. Asymptomatic clinical status is associated with male sex, comorbidities, and a higher risk of in-hospital outcomes. The adoption of effective management strategies for patients with AF should not be solely based on clinical symptoms.</p

    Forward jet production in deep inelastic ep scattering and low-x parton dynamics at HERA

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    Differential inclusive jet cross sections in neutral current deep inelastic ep scattering have been measured with the ZEUS detector. Three phase-space regions have been selected in order to study parton dynamics where the effects of BFKL evolution might be present. The measurements have been compared to the predictions of leading-logarithm parton shower Monte Carlo models and fixed-order perturbative QCD calculations. In the forward region, QCD calculations at order alpha_s^1 underestimate the data up to an order of magnitude at low x. An improved description of the data in this region is obtained by including QCD corrections at order alpha_s^2, which account for the lowest-order t-channel gluon-exchange diagrams, highlighting the importance of such terms in parton dynamics at low x.Comment: 25 pages, 4 figure

    Genome-Wide Association Study Identified a Narrow Chromosome 1 Region Associated with Chicken Growth Traits

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    Chicken growth traits are important economic traits in broilers. A large number of studies are available on finding genetic factors affecting chicken growth. However, most of these studies identified chromosome regions containing putative quantitative trait loci and finding causal mutations is still a challenge. In this genome-wide association study (GWAS), we identified a narrow 1.5 Mb region (173.5–175 Mb) of chicken (Gallus gallus) chromosome (GGA) 1 to be strongly associated with chicken growth using 47,678 SNPs and 489 F2 chickens. The growth traits included aggregate body weight (BW) at 0–90 d of age measured weekly, biweekly average daily gains (ADG) derived from weekly body weight, and breast muscle weight (BMW), leg muscle weight (LMW) and wing weight (WW) at 90 d of age. Five SNPs in the 1.5 Mb KPNA3-FOXO1A region at GGA1 had the highest significant effects for all growth traits in this study, including a SNP at 8.9 Kb upstream of FOXO1A for BW at 22–48 d and 70 d, a SNP at 1.9 Kb downstream of FOXO1A for WW, a SNP at 20.9 Kb downstream of ENSGALG00000022732 for ADG at 29–42 d, a SNP in INTS6 for BW at 90 d, and a SNP in KPNA3 for BMW and LMW. The 1.5 Mb KPNA3-FOXO1A region contained two microRNA genes that could bind to messenger ribonucleic acid (mRNA) of IGF1, FOXO1A and KPNA3. It was further indicated that the 1.5 Mb GGA1 region had the strongest effects on chicken growth during 22–42 d

    Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

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    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

    Integrative Bioinformatics Analysis Provides Insight into the Molecular Mechanisms of Chronic Kidney Disease

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    Background/Aims: Chronic kidney disease (CKD) is a worldwide public health problem. Regardless of the underlying primary disease, CKD tends to progress to end-stage kidney disease, resulting in unsatisfactory and costly treatment. Its common pathogenesis, however, remains unclear. The aim of this study was to provide an unbiased catalog of common gene-expression changes of CKD and reveal the underlying molecular mechanism using an integrative bioinformatics approach. Methods: We systematically collected over 250 Affymetrix microarray datasets from the glomerular and tubulointerstitial compartments of healthy renal tissues and those with various types of established CKD (diabetic kidney disease, hypertensive nephropathy, and glomerular nephropathy). Then, using stringent bioinformatics analysis, shared differentially expressed genes (DEGs) of CKD were obtained. These shared DEGs were further analyzed by the gene ontology (GO) and pathway enrichment analysis. Finally, the protein-protein interaction networks(PINs) were constructed to further refine our results. Results: Our analysis identified 176 and 50 shared DEGs in diseased glomeruli and tubules, respectively, including many transcripts that have not been previously reported to be involved in kidney disease. Enrichment analysis also showed that the glomerular and tubulointerstitial compartments underwent a wide range of unique pathological changes during chronic injury. As revealed by the GO enrichment analysis, shared DEGs in glomeruli were significantly enriched in exosomes. By constructing PINs, we identified several hub genes (e.g. OAS1, JUN, and FOS) and clusters that might play key roles in regulating the development of CKD. Conclusion: Our study not only further reveals the unifying molecular mechanism of CKD pathogenesis but also provides a valuable resource of potential biomarkers and therapeutic targets
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