449 research outputs found

    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

    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

    Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

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    Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations

    Characterization and modeling of the Haemophilus influenzae core and supragenomes based on the complete genomic sequences of Rd and 12 clinical nontypeable strains

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    The genomes of 9 non-typeable H. influenzae clinical isolates were sequenced and compared with a reference strain, allowing the characterisation and modelling of the core-and supra genomes of this organism

    Virulence phenotypes of low-passage clinical isolates of Nontypeable Haemophilus influenzae assessed using the chinchilla laniger model of otitis media

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    <p>Abstract</p> <p>Background</p> <p>The nontypeable Haemophilus influenzae (NTHi) are associated with a spectrum of respiratory mucosal infections including: acute otitis media (AOM); chronic otitis media with effusion (COME); otorrhea; locally invasive diseases such as mastoiditis; as well as a range of systemic disease states, suggesting a wide range of virulence phenotypes. Genomic studies have demonstrated that each clinical strain contains a unique genic distribution from a population-based supragenome, the distributed genome hypothesis. These diverse clinical and genotypic findings suggest that each NTHi strain possesses a unique set of virulence factors that contributes to the course of the disease.</p> <p>Results</p> <p>The local and systemic virulence patterns of ten genomically characterized low-passage clinical NTHi strains (PittAA – PittJJ) obtained from children with COME or otorrhea were stratified using the chinchilla model of otitis media (OM). Each isolate was used to bilaterally inoculate six animals and thereafter clinical assessments were carried out daily for 8 days by blinded observers. There was no statistical difference in the time it took for any of the 10 NTHi strains to induce otologic (local) disease with respect to any or all of the other strains, however the differences in time to maximal local disease and the severity of local disease were both significant between the strains. Parameters of systemic disease indicated that the strains were not all equivalent: time to development of the systemic disease, maximal systemic scores and mortality were all statistically different among the strains. PittGG induced 100% mortality while PittBB, PittCC, and PittEE produced no mortality. Overall Pitt GG, PittII, and Pitt FF produced the most rapid and most severe local and systemic disease. A post hoc determination of the clinical origins of the 10 NTHi strains revealed that these three strains were of otorrheic origin, whereas the other 7 were from patients with COME.</p> <p>Conclusion</p> <p>Collectively these data suggest that the chinchilla OM model is useful for discriminating between otorrheic and COME NTHi strains as to their disease-producing potential in humans, and combined with whole genome analyses, point the way towards identifying classes of virulence genes.</p

    SPY: A Magnet System for a High-pressure Gaseous TPC Neutrino Detector

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    We present a novel conceptual design for a magnet system that provides the magnetic field necessary for the analysis of tracks in a high-pressure gaseous argon TPC while simultaneously serving as a pressure vessel to contain the TPC gas volume. The magnet was developed within a Near Detector proposal for the Deep Underground Neutrino Experiment (DUNE). The high-pressure gaseous argon TPC is a component proposed to be one of the elements of an ensemble of near detectors that are needed for DUNEComment: 37 pages with 35 figure

    A review of swine heat production: 2003 to 2020

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    Swine heat production (HP) data are an essential element of numerous aspects affecting swine production sustainability, such as, housing environmental control design, energetics and thermoregulation modeling, as well as understanding of feed energy partitioning. Accurate HP values that reflect the continuous advances in growth, nutrition, health, and reproduction are needed to update outdated models and data; hence, this review of swine HP values is a critical contribution. This review updates the last previous review conducted in 2004, by reviewing literature from growing and breeding pigs from 2003 to 2020. In total, 33 references were identified that provided relevant HP data and from these references, 192 records were identified for pigs ranging in weight from 12.5 to 283 kg and exposed to temperatures between 12.0°C and 35.5°C. For growing pigs at thermoneutral conditions, a 4.7% average increase in HP was observed compared to HP data summarized from 1988 to 2004. Only five records were identified for gestating sows and the 43 records for lactating sows plus litter. This sow data shows high variability and inconsistent trends with temperature, most likely attributed to variation in experimental protocols, management, and limited reported information. There is still a lack of data on growing pigs greater than 105 kg, gilts and gestating sows housed in different systems (stall, pen, mixed, etc.), and latent HP values that reflect different housing systems. Further, there is a need to standardize reporting of HP values (with an example provided) across different disciplines to drive documentation of increased swine production efficiency, environmental control design, and energetics modeling.This article is published as Ramirez, Brett C., Steven J. Hoff, Morgan D. Hayes, Tami Brown-Brandl, Jay D. Harmon, and Gary A. Rohrer. "A review of swine heat production: 2003 to 2020." Frontiers in Animal Science 3 (2022): 908434. doi: https://doi.org/10.3389/fanim.2022.908434

    Illegal Killing of Nongame Wildlife and Recreational Shooting in Conservation Areas

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    Illegal killing of nongame wildlife is a global yet poorly documented problem. The prevalence and ecological consequences of illegal killing are often underestimated or completely unknown. We review the practice of legal recreational shooting and present data gathered from telemetry, surveys, and observations on its association with illegal killing of wildlife (birds and snakes) within conservation areas in Idaho, USA. In total, 33% of telemetered long‐billed curlews (Numenius americanus) and 59% of other bird carcasses found with known cause of death (or 32% of total) were illegally shot. Analysis of spatial distributions of illegal and legal shooting is consistent with birds being shot illegally in the course of otherwise legal recreational shooting, but snakes being intentionally sought out and targeted elsewhere, in locations where they congregate. Preliminary public surveys indicate that most recreational shooters find abhorrent the practice of illegal killing of wildlife. Viewed through this lens, our data may imply only a small fraction of recreational shooters is responsible for this activity. This study highlights a poorly known conservation problem that could have broad implications for some species and populations of wildlife
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