1,056 research outputs found

    Mapping a balanced translocation t(1;11)(q42.2;q21) linked to schizophrenia

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    (WP 2017-02) The Great Recession and Public Education

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    We examine the impact of the Great Recession on K-12 education finance and employment and generate five key results. First, nearly 300,000 school employees lost their jobs. Second, schools that were heavily dependent financially on state governments were particularly vulnerable to the recession. Third local revenues from the property tax actually increased during the recession, primarily because millage rates rose in response to declining property values. Fourth, inequality in school spending rose sharply during the Great Recession. Fifth, the federal government’s efforts to shield education from some of the worst effects of the recession achieved their major goal

    Reproductive justice and black lives: A concept analysis for public health nursing

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    Inequities in maternal mortality in the US are a form of structural violence against Black women. The concept of reproductive justice has been employed in the social sciences for almost thirty years, yet nursing has been slow to adopt this concept in promoting maternal-child health. Objective: to analyze the concept of reproductive justice as used in peer-reviewed publications with the aim of reframing black maternal health in public health nursing scholarship, research, practice, and advocacy. Design: We conducted a systematic review of the social science literature. We analyzed selected articles though a principle-based concept analysis focusing on epistemological, pragmatic, linguistic, and logical principles. Sample: 8 articles were selected from a pool of 377. Results: Race was identified as a source of power for understanding reproductive justice through individual knowledge, collective knowledge, and praxis. Pragmatically, reproductive justice is a social justice-oriented platform that bridges the pro-choice/pro-life divide; aids coalition building; and promotes inclusion. Linguistically, the concept is distinct from both reproductive health and reproductive rights. Reproductive justice is logically situated within intersectionality theory and the cumulative embodiment of oppressions Black women experience based on race, class, and gender. Conclusion: Reproductive justice reframes public health nursing actions for Black women by focusing on uncovering systems of oppression, recognizing past historical injustices, and advancing cultural safety in health promotion. Multilevel interventions are needed to simultaneously address these injustices particularly in the areas of preconception health, maternal health, infant and child health, and Black family well-being across the reproductive lifespan

    The Great Recession and Public Education

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    We examine the impact of the Great Recession on public education finance and employment. Five major themes emerge from our work. First, nearly 300,000 school employees lost their jobs. Second, schools that were heavily dependent financially on state governments were particularly vulnerable to the recession. Third, local revenues from the property tax actually increased during the recession, primarily because millage rates rose in response to declining property values. Fourth, inequality in school spending rose sharply during the Great Recession. We argue, however, that we need to be very cautious about this result. School spending inequality has risen steadily since 2000; the trend in inequality we see in the 2008-13 period is very similar to the trend we see in the 2000-08 period. Fifth, the federal government\u27s efforts to shield education from some of the worst effects of the recession achieved their major goal

    Speeding disease gene discovery by sequence based candidate prioritization

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    BACKGROUND: Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. RESULTS: We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. CONCLUSION: PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies

    Computational comparison of human genomic sequence assemblies for a region of chromosome 4

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    Much of the available human genomic sequence data exist in a fragmentary draft state following the completion of the initial high-volume sequencing performed by the International Human Genome Sequencing Consortium (IHGSC) and Celera Genomics (CG). We compared six draft genome assemblies over a region of chromosome 4p (D4S394–D4S403), two consecutive releases by the IHGSC at University of California, Santa Cruz (UCSC), two consecutive releases from the National Centre for Biotechnology Information (NCBI), the public release from CG, and a hybrid assembly we have produced using IHGSC and CG sequence data. This region presents particular problems for genomic sequence assembly algorithms as it contains a large tandem repeat and is sparsely covered by draft sequences. The six assemblies differed both in terms of their relative coverage of sequence data from the region and in their estimated rates of misassembly. The CG assembly method attained the lowest level of misassembly, whereas NCBI and UCSC assemblies had the highest levels of coverage. All assemblies examined included <60% of the publicly available sequence from the region. At least 6% of the sequence data within the CG assembly for the D4S394–D4S403 region was not present in publicly available sequence data. We also show that even in a problematic region, existing software tools can be used with high-quality mapping data to produce genomic sequence contigs with a low rate of rearrangements. [All sequence accessions for the genomic sequence assemblies analyzed and the data sets used to assess coverage and rates of misassembly are available from http://www.ed.ac.uk/∌csemple.

    Improving Nursing Facility Care Through an Innovative Payment Demonstration Project: Optimizing Patient Transfers, Impacting Medical Quality, and Improving Symptoms: Transforming Institutional Care Phase 2

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    Optimizing Patient Transfers, Impacting Medical Quality, and Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) is a 2‐phase Center for Medicare and Medicaid Innovations demonstration project now testing a novel Medicare Part B payment model for nursing facilities and practitioners in 40 Indiana nursing facilities. The new payment codes are intended to promote high‐quality care in place for acutely ill long‐stay residents. The focus of the initiative is to reduce hospitalizations through the diagnosis and on‐site management of 6 common acute clinical conditions (linked to a majority of potentially avoidable hospitalizations of nursing facility residents1): pneumonia, urinary tract infection, skin infection, heart failure, chronic obstructive pulmonary disease or asthma, and dehydration. This article describes the OPTIMISTIC Phase 2 model design, nursing facility and practitioner recruitment and training, and early experiences implementing new Medicare payment codes for nursing facilities and practitioners. Lessons learned from the OPTIMISTIC experience may be useful to others engaged in multicomponent quality improvement initiatives

    Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design

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    BACKGROUND: CpG methylation levels can help to explain inter-individual differences in phenotypic traits. Few studies have explored whether identifying probe subsets based on their biological and statistical properties can maximise predictions whilst minimising array content. Variance component analyses and penalised regression (epigenetic predictors) were used to test the influence of (i) the number of probes considered, (ii) mean probe variability and (iii) methylation QTL status on the variance captured in eighteen traits by blood DNA methylation. Training and test samples comprised ≀ 4450 and ≀ 2578 unrelated individuals from Generation Scotland, respectively. RESULTS: As the number of probes under consideration decreased, so too did the estimates from variance components and prediction analyses. Methylation QTL status and mean probe variability did not influence variance components. However, relative effect sizes were 15% larger for epigenetic predictors based on probes with known or reported methylation QTLs compared to probes without reported methylation QTLs. Relative effect sizes were 45% larger for predictors based on probes with mean Beta-values between 10 and 90% compared to those based on hypo- or hypermethylated probes (Beta-value ≀ 10% or ≄ 90%). CONCLUSIONS: Arrays with fewer probes could reduce costs, leading to increased sample sizes for analyses. Our results show that reducing array content can restrict prediction metrics and careful attention must be given to the biological and distribution properties of CpG probes in array content selection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-022-01320-9
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