649 research outputs found

    Reconnaissance surveying of Bechevin Bay, AK using satellite-derived bathymetry

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    Recently, a remote sensing study has been conducted over Bechevin Bay Channel, Alaska as part of a collaboration project between NOAA and the U.S. Coast Guard (USCG). The goal of the study to develop a procedure to prioritize survey areas and plan the annual deployment of Aids to Navigation (AtoN) along the channel. Bechevin Bay is considered a priority for marine surveying because it constitutes the easternmost passage through the Aleutians from the Bering Sea to the Gulf of Alaska. The channel is located in a mud flat area, where every winter the passage is closed due to ice cover. As a result, the path of the channel may change after sea ice has melted. Because of the geographic location of Bechevin Bay, many resources are required in order to conduct an annual survey to map the channel’s path. The surveys are typically conducted by the USCG buoy tenders using small boats and reconnaissance-style single beam lines. This paper presents the use of single-image satellite-derived bathymetry (SDB) as an economic alternative approach. The study compares the performance using different band ratios. Datasets that were used in the study included Landsat 8 and WorldView 2 (WV-2) imagery

    Variation in compulsory psychiatric inpatient admission in England:a cross-sectional, multilevel analysis

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    Background: Rates of compulsory admission have increased in England in recent decades, and this trend is accelerating. Studying variation in rates between people and places can help identify modifiable causes. Objectives: To quantify and model variances in the rate of compulsory admission in England at different spatial levels and to assess the extent to which this was explained by characteristics of people and places. Design: Cross-sectional analysis using multilevel statistical modelling. Setting: England, including 98% of Census lower layer super output areas (LSOAs), 95% of primary care trusts (PCTs), 93% of general practices and all 69 NHS providers of specialist mental health services. Participants: 1,287,730 patients. Main outcome measure: The study outcome was compulsory admission, defined as time spent in an inpatient mental illness bed subject to the Mental Health Act (2007) in 2010/11. We excluded patients detained under sections applying to emergency assessment only (including those in places of safety), guardianship or supervision of community treatment. The control group comprised all other users of specialist mental health services during the same period. Data sources: The Mental Health Minimum Data Set (MHMDS). Data on explanatory variables, characterising each of the spatial levels in the data set, were obtained from a wide range of sources, and were linked using MHMDS identifiers. Results: A total of 3.5% of patients had at least one compulsory admission in 2010/11. Of (unexplained) variance in the null model, 84.5% occurred between individuals. Statistically significant variance occurred between LSOAs [6.7%, 95% confidence interval (CI) 6.2% to 7.2%] and provider trusts (6.9%, 95% CI 4.3% to 9.5%). Variances at these higher levels remained statistically significant even after adjusting for a large number of explanatory variables, which together explained only 10.2% of variance in the study outcome. The number of provider trusts whose observed rate of compulsory admission differed from the model average to a statistically significant extent fell from 45 in the null model to 20 in the fully adjusted model. We found statistically significant associations between compulsory admission and age, gender, ethnicity, local area deprivation and ethnic density. There was a small but statistically significant association between (higher) bed occupancy and compulsory admission, but this was subsequently confounded by other covariates. Adjusting for PCT investment in mental health services did not improve model fit in the fully adjusted models. Conclusions: This was the largest study of compulsory admissions in England. While 85% of the variance in this outcome occurred between individuals, statistically significant variance (around 7% each) occurred between places (LSOAs) and provider trusts. This higher-level variance in compulsory admission remained largely unchanged even after adjusting for a large number of explanatory variables. We were constrained by data available to us, and therefore our results must be interpreted with caution. We were also unable to consider many hypotheses suggested by the service users, carers and professionals who we consulted. There is an imperative to develop and evaluate interventions to reduce compulsory admission rates. This requires further research to extend our understanding of the reasons why these rates remain so high. Funding: The National Institute for Health Research Health Services and Delivery Research programme

    Size and clustering of ethnic groups and rates of psychiatric admission in England

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    Aims and method To compare rates of admission for different types of severe mental illness between ethnic groups, and to test the hypothesis that larger and more clustered ethnic groups will have lower admission rates. This was a descriptive study of routinely collected data from the National Health Service in England. Results There was an eightfold difference in admission rates between ethnic groups for schizophreniform and mania admissions, and a fivefold variation in depression admissions. On average, Black and minority ethnic (BME) groups had higher rates of admission for schizophreniform and mania admissions but not for depression. This increased rate was greatest in the teenage years and early adulthood. Larger ethnic group size was associated with lower admission rates. However, greater clustering was associated with higher admission rates. Clinical implications Our findings support the hypothesis that larger ethnic groups have lower rates of admission. This was a between-group comparison rather than within each group. Our findings do not support the hypothesis that more clustered groups have lower rates of admission. In fact, they suggest the opposite: groups with low clustering had lower admission rates. The BME population in the UK is increasing in size and becoming less clustered. Our results suggest that both of these factors should ameliorate the overrepresentation of BME groups among psychiatric in-patients. However, this overrepresentation continues, and our results suggest a possible explanation, namely, changes in the delivery of mental health services, particularly the marked reduction in admissions for depression

    Religious perspectives on the use of psychopharmaceuticals as an enhancement technology

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    The use of psychopharmaceuticals as an enhancement technology has been the focus of attention in the bioethics literature. However, there has been little examination of the challenges that this practice creates for religious traditions that place importance on questions of being, authenticity and identity. We asked expert commentators from six major world religions to consider the issues raised by psychopharmaceuticals as an enhancement technology. These commentaries reveal that in assessing the appropriate place of medical therapies, religious traditions, like secular perspectives, rely upon ideas about health and disease and about normal human behavior. But unlike secular perspectives, faith traditions explicitly concern themselves with ways in which medicine should or should not be used to live a ‘good life’. KEYWORDS: Enhancement; bioethics, psychopharmacology, religio

    Development and validation of a risk calculator for major mood disorders among the offspring of bipolar parents using information collected in routine clinical practice.

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    Family history is a significant risk factor for bipolar disorders (BD), but the magnitude of risk varies considerably between individuals within and across families. Accurate risk estimation may increase motivation to reduce modifiable risk exposures and identify individuals appropriate for monitoring over the peak risk period. Our objective was to develop and independently replicate an individual risk calculator for bipolar spectrum disorders among the offspring of BD parents using data collected in routine clinical practice. Data from the longitudinal Canadian High-Risk Offspring cohort study collected from 1996 to 2020 informed the development of a 5 and 10-year risk calculator using parametric time-to-event models with a cure fraction and a generalized gamma distribution. The calculator was then externally validated using data from the Lausanne-Geneva High-Risk Offspring cohort study collected from 1996 to 2020. A time-varying C-index by age in years was used to estimate the probability that the model correctly classified risk. Bias corrected estimates and 95% confidence limits were derived using a jackknife resampling approach. The primary outcome was age of onset of a major mood disorder. The risk calculator was most accurate at classifying risk in mid to late adolescence in the Canadian cohort (n = 285), and a similar pattern was replicated in the Swiss cohort (n = 128). Specifically, the time-varying C-index indicated that there was approximately a 70% chance that the model would correctly predict which of two 15-year-olds would be more likely to develop the outcome in the future. External validation within a smaller Swiss cohort showed mixed results. Findings suggest that this model may be a useful clinical tool in routine practice for improved individualized risk estimation of bipolar spectrum disorders among the adolescent offspring of a BD parent; however, risk estimation in younger high-risk offspring is less accurate, perhaps reflecting the evolving nature of psychopathology in early childhood. Based on external validation with a Swiss cohort, the risk calculator may not be as predictive in more heterogenous high-risk populations. The Canadian High-Risk Study has been funded by consecutive operating grants from the Canadian Institutes for Health Research, currently CIHR PJT Grant 152796 he Lausanne-Geneva high-risk study was and is supported by five grants from the Swiss National Foundation (#3200-040,677, #32003B-105,969, #32003B-118,326, #3200-049,746 and #3200-061,974), three grants from the Swiss National Foundation for the National Centres of Competence in Research project "The Synaptic Bases of Mental Diseases" (#125,759, #158,776, and #51NF40 - 185,897), and a grant from GlaxoSmithKline Clinical Genetics

    The Green Bank Ammonia Survey: Unveiling the Dynamics of the Barnard 59 star-forming Clump

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    Understanding the early stages of star formation is a research field of ongoing development, both theoretically and observationally. In this context, molecular data have been continuously providing observational constraints on the gas dynamics at different excitation conditions and depths in the sources. We have investigated the Barnard 59 core, the only active site of star formation in the Pipe Nebula, to achieve a comprehensive view of the kinematic properties of the source. These information were derived by simultaneously fitting ammonia inversion transition lines (1,1) and (2,2). Our analysis unveils the imprint of protostellar feedback, such as increasing line widths, temperature and turbulent motions in our molecular data. Combined with complementary observations of dust thermal emission, we estimate that the core is gravitationally bound following a virial analysis. If the core is not contracting, another source of internal pressure, most likely the magnetic field, is supporting it against gravitational collapse and limits its star formation efficiency.Comment: 18 pages, 18 figure

    White Blood Cell Differentials Enrich Whole Blood Expression Data in the Context of Acute Cardiac Allograft Rejection

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    Acute cardiac allograft rejection is a serious complication of heart transplantation. Investigating molecular processes in whole blood via microarrays is a promising avenue of research in transplantation, particularly due to the non-invasive nature of blood sampling. However, whole blood is a complex tissue and the consequent heterogeneity in composition amongst samples is ignored in traditional microarray analysis. This complicates the biological interpretation of microarray data. Here we have applied a statistical deconvolution approach, cell-specific significance analysis of microarrays (csSAM), to whole blood samples from subjects either undergoing acute heart allograft rejection (AR) or not (NR). We identified eight differentially expressed probe-sets significantly correlated to monocytes (mapping to 6 genes, all down-regulated in ARs versus NRs) at a false discovery rate (FDR) ≤ 15%. None of the genes identified are present in a biomarker panel of acute heart rejection previously published by our group and discovered in the same data***

    Population Frequencies Determined by Next-generation Sequencing Provide Strategies for Prospective HLA Epitope Matching for Transplantation

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    Compatibility for human leukocyte antigen (HLA) genes between transplant donors and recipients improves graft survival but prospective matching is rarely performed due to the vast heterogeneity of this gene complex. To reduce complexity, we have combined next-generation sequencing and in silico mapping to determine population frequencies and matching probabilities of 150 antibody-binding eplets across all 11 classical HLA genes in 2000 ethnically heterogeneous renal patients and donors. We show that eplets are more common and more uniformly distributed between donors and recipients than the respective HLA isoforms. Simulation of targeted eplet matching shows that a high degree of overall compatibility, and perfect identity at the clinically important HLA class II loci, can be obtained within a patient waiting list of approximately 250 subjects. Internal epitope-based allocation is thus feasible for most major renal transplant programs, while regional or national sharing may be required for other solid organs
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