172 research outputs found

    Association of Trauma Molecular Endotypes With Differential Response to Transfusion Resuscitation Strategies

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    IMPORTANCE: It is not clear which severely injured patients with hemorrhagic shock may benefit most from a 1:1:1 vs 1:1:2 (plasma:platelets:red blood cells) resuscitation strategy. Identification of trauma molecular endotypes may reveal subgroups of patients with differential treatment response to various resuscitation strategies. OBJECTIVE: To derive trauma endotypes (TEs) from molecular data and determine whether these endotypes are associated with mortality and differential treatment response to 1:1:1 vs 1:1:2 resuscitation strategies. DESIGN, SETTING, AND PARTICIPANTS: This was a secondary analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios (PROPPR) randomized clinical trial. The study cohort included individuals with severe injury from 12 North American trauma centers. The cohort was taken from the participants in the PROPPR trial who had complete plasma biomarker data available. Study data were analyzed on August 2, 2021, to October 25, 2022. EXPOSURES: TEs identified by K-means clustering of plasma biomarkers collected at hospital arrival. MAIN OUTCOMES AND MEASURES: An association between TEs and 30-day mortality was tested using multivariable relative risk (RR) regression adjusting for age, sex, trauma center, mechanism of injury, and injury severity score (ISS). Differential treatment response to transfusion strategy was assessed using an RR regression model for 30-day mortality by incorporating an interaction term for the product of endotype and treatment group adjusting for age, sex, trauma center, mechanism of injury, and ISS. RESULTS: A total of 478 participants (median [IQR] age, 34.5 [25-51] years; 384 male [80%]) of the 680 participants in the PROPPR trial were included in this study analysis. A 2-class model that had optimal performance in K-means clustering was found. TE-1 (n = 270) was characterized by higher plasma concentrations of inflammatory biomarkers (eg, interleukin 8 and tumor necrosis factor α) and significantly higher 30-day mortality compared with TE-2 (n = 208). There was a significant interaction between treatment arm and TE for 30-day mortality. Mortality in TE-1 was 28.6% with 1:1:2 treatment vs 32.6% with 1:1:1 treatment, whereas mortality in TE-2 was 24.5% with 1:1:2 treatment vs 7.3% with 1:1:1 treatment (P for interaction = .001). CONCLUSIONS AND RELEVANCE: Results of this secondary analysis suggest that endotypes derived from plasma biomarkers in trauma patients at hospital arrival were associated with a differential response to 1:1:1 vs 1:1:2 resuscitation strategies in trauma patients with severe injury. These findings support the concept of molecular heterogeneity in critically ill trauma populations and have implications for tailoring therapy for patients at high risk for adverse outcomes

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Assessing the Effects of Personal Characteristics and Context on U.S. House Speakers’ Leadership Styles, 1789-2006

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    Research on congressional leadership has been dominated in recent decades by contextual interpretations that see leaders’ behavior as best explained by the environment in which they seek to exercise leadership—particularly, the preference homogeneity and size of their party caucus. The role of agency is thus discounted, and leaders’ personal characteristics and leadership styles are underplayed. Focusing specifically on the speakers of the U.S. House of Representatives from the first to the 110th Congress, we construct measures of each speaker’s commitment to comity and leadership assertiveness. We find the scores reliable and then test the extent to which a speaker’s style is the product of both political context and personal characteristics. Regression estimates on speakers’ personal assertiveness scores provide robust support for a context-plus-personal characteristics explanation, whereas estimates of their comity scores show that speakers’ personal backgrounds trump context

    A population-based study of effect of multiple birth on infant mortality in Nigeria

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    <p>Abstract</p> <p>Background</p> <p>Multi-foetal pregnancies and multiple births including twins and higher order multiples births such as triplets and quadruplets are high-risk pregnancy and birth. These high-risk groups contribute to the higher rate of childhood mortality especially during early period of life.</p> <p>Methods</p> <p>We examined the relationship between multiple births and infant mortality using univariable and multivariable survival regression procedure with Weibull hazard function, controlling for child's sex, birth order, prenatal care, delivery assistance; mother's age at child birth, nutritional status, education level; household living conditions and several other risk factors.</p> <p>Results</p> <p>Children born multiple births were more than twice as likely to die during infancy as infants born singleton (hazard ratio = 2.19; 95% confidence interval: 1.50, 3.19) holding other factors constant. Maternal education and household asset index were associated with lower risk of infant mortality.</p> <p>Conclusion</p> <p>Multiple births are strongly negatively associated with infant survival in Nigeria independent of other risk factors. Mother's education played a protective role against infant death. This evidence suggests that improving maternal education may be key to improving child survival in Nigeria. A well-educated mother has a better chance of satisfying important factors that can improve infant survival: the quality of infant feeding, general care, household sanitation, and adequate use of preventive and curative health services.</p

    LSST: from Science Drivers to Reference Design and Anticipated Data Products

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    (Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg2^2 field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5σ\sigma point-source depth in a single visit in rr will be 24.5\sim 24.5 (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg2^2 with δ<+34.5\delta<+34.5^\circ, and will be imaged multiple times in six bands, ugrizyugrizy, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg2^2 region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to r27.5r\sim27.5. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

    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 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

    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

    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
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