127 research outputs found

    BT-Nurse : computer generation of natural language shift summaries from complex heterogeneous medical data

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    Objective: To determine if a computer system can automatically generate a useful natural language nursing shift summary solely from an electronic patient record system, in a neonatal intensive care unit (NICU). Design: A system was built which automatically generates NICU shift summaries, using datato- text technology. The system was tested for two months in the Royal Infirmary of Edinburgh NICU. Measurements: Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were also asked for free-text comments about the summaries. Results: The nurses found the majority of the summaries to be understandable, accurate, and helpful (p < .001 for all measures). However, nurses also pointed out many deficiencies, especially with regard to extra content they wanted to see in the computer-generated summaries. Conclusions: Natural language NICU shift summaries can be automatically generated from an electronic patient record. However our proof-of-concept software needs considerable additional development work.peer-reviewe

    Working in the Public Interest Law Conference

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    Entirely student organized, WIPI seeks to bring together eminent practitioners in their respective fields, students, and faculty to discuss practical approaches to lawyering which can best serve the poor. Practical methods of challenging poverty are often not covered in traditional law school courses. This conference seeks to remedy that and provide dynamic, creative ways to combat poverty through the vehicle of the law

    Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

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    The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis

    Investigation of inter- and intraspecies variation through genome sequencing of Aspergillus section Nigri

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    Aspergillus section Nigri comprises filamentous fungi relevant to biomedicine, bioenergy, health, and biotechnology. To learn more about what genetically sets these species apart, as well as about potential applications in biotechnology and biomedicine, we sequenced 23 genomes de novo, forming a full genome compendium for the section (26 species), as well as 6 Aspergillus niger isolates. This allowed us to quantify both inter-and intraspecies genomic variation. We further predicted 17,903 carbohydrateactive enzymes and 2,717 secondary metabolite gene clusters, which we condensed into 455 distinct families corresponding to compound classes, 49% of which are only found in single species. We performed metabolomics and genetic engineering to correlate genotypes to phenotypes, as demonstrated for the metabolite aurasperone, and by heterologous transfer of citrate production to Aspergillus nidulans. Experimental and computational analyses showed that both secondary metabolism and regulation are key factors that are significant in the delineation of Aspergillus species.Peer reviewe

    A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

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    This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H

    Distinct monocyte gene-expression profiles in autoimmune diabetes

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    OBJECTIVE-There is evidence that monocytes of patients with type 1 diabetes show proinflammatory activation and disturbed migration/adhesion, but the evidence is inconsistent. Our hypothesis is that monocytes are distinctly activated/disturbed in different subforms of autoimmune diabetes. RESEARCH DESIGN AND METHODS-We studied patterns of inflammatory gene expression in monocytes of patients with type 1 diabetes (juvenile onset, n = 30; adult onset, n = 30) and latent autoimmune diabetes of the adult (LADA) (n = 30) (controls subjects, n = 49; type 2 diabetic patients, n = 30) using quantitative PCR. We tested 25 selected genes: 12 genes detected in a prestudy via whole-genome analyses plus an additional 13 genes identified as part of a monocyte inflammatory signature previously reported. RESULTS-We identified two distinct monocyte gene expression clusters in autoimmune diabetes. One cluster (comprising 12 proinflammatory cytokine/compound genes with a putative key gene PDE4B) was detected in 60% of LADA and 28% of adult-onset type 1 diabetic patients but in only 10% of juvenile - onset type 1 diabetic patients. A second cluster (comprising 10 chemotaxis, adhesion, motility, and metabolism genes) was detected in 43% of juvenile-onset type 1 diabetic and 33% of LADA patients but in only 9% of adult-onset type 1 diabetic patients. CONCLUSIONS-Subgroups of type 1 diabetic patients show an abnormal monocyte gene expression with two profiles, supporting a concept of heterogeneity in the pathogenesis of autoimmune diabetes only partly overlapping with the presently known diagnostic categories
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