74 research outputs found

    How knowledge of the gastrointestinal absorption of elements could be used to predict transfer to milk

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    The quality and quantity of data used to derive transfer parameter values for milk are variable and there are many data gaps for elements/radionuclides which may need to be considered for risk assessment of the agricultural foodchain. There has been a recent focus on critically evaluating current methods to fill data gaps and on identifying extrapolation methods to derive suitable values for the elements, and particularly radioisotopes, with no or sparse data. The relationship between fractional absorption of elements in the ruminant gastrointestinal tract and transfer to milk has been explored to determine whether knowledge of the former can be used to predict the latter. A relationship has been derived between fractional absorption of elements and two empirical ratios commonly used to quantify transfer to milk; transfer coefficients (element concentration in milk divided by element daily intake) and concentrations ratios (concentration in milk divided by concentration in feed). We propose that fractional absorption may be used to predict the order of magnitude of the transfer to milk of elements/radionuclides for which no relevant data have yet been identified or collated

    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

    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

    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

    New Models for Large Prospective Studies: Is There a Better Way?

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    Large prospective cohort studies are critical for identifying etiologic factors for disease, but they require substantial long-term research investment. Such studies can be conducted as multisite consortia of academic medical centers, combinations of smaller ongoing studies, or a single large site such as a dominant regional health-care provider. Still another strategy relies upon centralized conduct of most or all aspects, recruiting through multiple temporary assessment centers. This is the approach used by a large-scale national resource in the United Kingdom known as the “UK Biobank,” which completed recruitment/examination of 503,000 participants between 2007 and 2010 within budget and ahead of schedule. A key lesson from UK Biobank and similar studies is that large studies are not simply small studies made large but, rather, require fundamentally different approaches in which “process” expertise is as important as scientific rigor. Embedding recruitment in a structure that facilitates outcome determination, utilizing comprehensive and flexible information technology, automating biospecimen processing, ensuring broad consent, and establishing essentially autonomous leadership with appropriate oversight are all critical to success. Whether and how these approaches may be transportable to the United States remain to be explored, but their success in studies such as UK Biobank makes a compelling case for such explorations to begin

    A highly conserved protein of unknown function in Sinorhizobium meliloti affects sRNA regulation similar to Hfq

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    The SMc01113/YbeY protein, belonging to the UPF0054 family, is highly conserved in nearly every bacterium. However, the function of these proteins still remains elusive. Our results show that SMc01113/YbeY proteins share structural similarities with the MID domain of the Argonaute (AGO) proteins, and might similarly bind to a small-RNA (sRNA) seed, making a special interaction with the phosphate on the 5′-side of the seed, suggesting they may form a component of the bacterial sRNA pathway. Indeed, eliminating SMc01113/YbeY expression in Sinorhizobium meliloti produces symbiotic and physiological phenotypes strikingly similar to those of the hfq mutant. Hfq, an RNA chaperone, is central to bacterial sRNA-pathway. We evaluated the expression of 13 target genes in the smc01113 and hfq mutants. Further, we predicted the sRNAs that may potentially target these genes, and evaluated the accumulation of nine sRNAs in WT and smc01113 and hfq mutants. Similar to hfq, smc01113 regulates the accumulation of sRNAs as well as the target mRNAs. AGOs are central components of the eukaryotic sRNA machinery and conceptual parallels between the prokaryotic and eukaryotic sRNA pathways have long been drawn. Our study provides the first line of evidence for such conceptual parallels. Furthermore, our investigation gives insights into the sRNA-mediated regulation of stress adaptation in S. meliloti

    Power efficiency of outer hair cell somatic electromotility

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    © 2009 Rabbitt et al. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS Computational Biology 5 (2009): e1000444, doi:10.1371/journal.pcbi.1000444.Cochlear outer hair cells (OHCs) are fast biological motors that serve to enhance the vibration of the organ of Corti and increase the sensitivity of the inner ear to sound. Exactly how OHCs produce useful mechanical power at auditory frequencies, given their intrinsic biophysical properties, has been a subject of considerable debate. To address this we formulated a mathematical model of the OHC based on first principles and analyzed the power conversion efficiency in the frequency domain. The model includes a mixture-composite constitutive model of the active lateral wall and spatially distributed electro-mechanical fields. The analysis predicts that: 1) the peak power efficiency is likely to be tuned to a specific frequency, dependent upon OHC length, and this tuning may contribute to the place principle and frequency selectivity in the cochlea; 2) the OHC power output can be detuned and attenuated by increasing the basal conductance of the cell, a parameter likely controlled by the brain via the efferent system; and 3) power output efficiency is limited by mechanical properties of the load, thus suggesting that impedance of the organ of Corti may be matched regionally to the OHC. The high power efficiency, tuning, and efferent control of outer hair cells are the direct result of biophysical properties of the cells, thus providing the physical basis for the remarkable sensitivity and selectivity of hearing.This work was supported by NIDCD R01 DC04928 (Rabbitt), NIDCD R01 DC00384 (Brownell) and NASA Ames GSRA56000135 (Breneman)

    Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

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    Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

    The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

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