126 research outputs found

    Serrated trailing edges for improving lift and drag characteristics of lifting surfaces

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    An improvement in the lift and drag characteristics of a lifting surface is achieved by attaching a serrated panel to the trailing edge of the lifting surface. The serrations may have a saw-tooth configuration, with a 60 degree included angle between adjacent serrations. The serrations may vary in shape and size over the span-wise length of the lifting surface, and may be positioned at fixed or adjustable deflections relative to the chord of the lifting surface

    Patients' experiences with quality of hospital care: the Consumer Quality Index Cataract Questionnaire

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    Background. Patients' feedback is of great importance in health care policy decisions. The Consumer Quality Index Cataract Questionnaire (CQI Cataract) was used to measure patients' experiences with quality of care after a cataract operation. This study aims to evaluate the reliability and the dimensional structure of this questionnaire and assesses its ability to measure differences between hospitals in patients' experiences with quality of care. Methods. Survey data of 4,635 respondents were available. An exploratory factor analysis was performed to evaluate the construct validity of the questionnaire and item-correlations and inter-factor correlations were calculated. Secondly, Cronbach's alpha coefficients were calculated to assess the internal consistency of the scales. Thirdly, to evaluate the ability of the questionnaire to discriminate between hospitals, multilevel analyses were performed with patients hierarchically nested within hospitals. Results. Exploratory factor analysis resulted in 14 quality of care items subdivided over three factors (i.e. communication with ophthalmologist, communication with nurses, and communication about medication). Cronbach's alpha coefficients of 0.89, 0.76 and 0.79 indicated good internal consistency. Multilevel analyses showed that the questionnaire was able to measure differences in patients' experiences with hospital care regarding communication with ophthalmologist and communication about medication. In addition, there was variation between hospitals regarding ophthalmologist ratings, hospital ratings and one dichotomous information item. Conclusion. These findings suggest that the CQI Cataract is a reliable and valid instrument. This instrument can be used to measure patients' experiences with three domains of hospital care after a cataract operation and is able to assess differences in evaluated care between hospitals

    The Consumer Quality Index Hip Knee Questionnaire measuring patients' experiences with quality of care after a total hip or knee arthroplasty

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    <p>Abstract</p> <p>Background</p> <p>The Dutch Consumer Quality Index Hip Knee Questionnaire (CQI Hip Knee) was used to assess patients' experiences with and evaluations of quality of care after a total hip (THA) or total knee arthroplasty (TKA). The aim of this study is to evaluate the construct validity and internal consistency reliability of this new instrument and to assess its ability to measure differences in quality of care between hospitals.</p> <p>Methods</p> <p>Survey data of 1,675 subjects who underwent a THA or TKA were used to evaluate the psychometric properties. Exploratory factor analyses were performed and item-total correlations and inter-factor correlations were calculated to assess the construct validity of the instrument. Reliability analyses included tests of internal consistency (Cronbach's alpha coefficients). Finally, multilevel analyses were performed to assess the ability of the instrument to discriminate between hospitals in quality of care.</p> <p>Results</p> <p>Exploratory factor analyses indicated that the survey consisted of 21 items measuring five aspects of care (i.e. communication with nurses, communication with doctors, communication with general practitioner, communication about new medication, and pain control). Cronbach's alpha coefficients ranged from 0.76 to 0.90 indicating good internal consistency. The survey's ability to discriminate between hospitals was partly supported by multilevel analysis. Two scales (i.e. communication with nurses and communication with doctors) were able to measure differences between hospitals with respect to patients' experiences with quality of care. Logistic multilevel analyses indicated that hospitals explained part of the variation between patients in receiving information.</p> <p>Conclusion</p> <p>These findings suggest that the CQI Hip Knee is reliable and valid for use in Dutch health care. Health care providers or health plans can use this survey to measure patients' experiences with hospital care and to identify variations in care between hospitals.</p

    The North American tree-ring fire-scar network

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    Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America

    Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

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    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

    Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

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    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

    Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

    Get PDF
    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

    Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

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    Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe
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