240 research outputs found

    A Targeted Enrichment Strategy for Massively Parallel Sequencing of Angiosperm Plastid Genomes

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    Premise of the study: We explored a targeted enrichment strategy to facilitate rapid and low-cost next-generation sequencing (NGS) of numerous complete plastid genomes from across the phylogenetic breadth of angiosperms

    The images of psychiatry scale: development, factor structure, and reliability.

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    BACKGROUND: This analysis is based on a survey questionnaire designed to describe medical educators' views of psychiatry and psychiatrists. Our goals in this paper were to assess the psychometric properties of the survey questions by (a) using exploratory factor analysis to identify the basic factor structure underlying 37 survey items; (b) testing the resulting factor structure using confirmatory factor analysis; and (c) assessing the internal reliability of each identified factor. To our knowledge, this is the first attempt to use these techniques to psychometrically assess a scale measuring the strength of stigma that medical educators attached to psychiatry. METHODS: Survey data were collected from a random sample of 1,059 teaching faculty in 23 academic teaching sites in 15 countries. We conducted exploratory and confirmatory factor analysis to identify the scale structure and Cronbach's alpha to assess internal consistency of the resulting scales. RESULTS: Results showed that a two-factor solution was the best fit for the data. Following exploratory factor analysis, we conducted confirmatory factor analysis on a split half of the sample. Results highlighted several items with low loadings. Excluding factors with low correlations and allowing for several correlated variances resulted in a good fitting model explaining 95% of the variance in the data. CONCLUSIONS: We identified two unidimensional scales. The Images Scale contained 11 items measuring stereotypic content concerning psychiatry and psychiatrists. The Efficacy of Psychiatry Scale contained 5 items addressing perceptions of the challenges and effectiveness of psychiatry as a discipline

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Protecting children in low-income and middle-income countries from COVID-19

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    CITATION: Ahmed, S. et al. 2020. Protecting children in low-income and middle-income countries from COVID-19. BMJ Global Health, 5:e002844. doi:10.1136/bmjgh-2020-002844.The original publication is available at https://gh.bmj.comA saving grace of the COVID-19 pandemic in high-income and upper middle-income countries has been the relative sparing of children. As the disease spreads across low-income and middle-income countries (LMICs), long-standing system vulnerabilities may tragically manifest, and we worry that children will be increasingly impacted, both directly and indirectly. Drawing on our shared child pneumonia experience globally, we highlight these potential impacts on children in LMICs and propose actions for a collective response.https://gh.bmj.com/content/5/5/e002844.abstractPublisher's versio
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