112 research outputs found

    The Effects of Dietary Carotenoid Supplementation and Retinal Carotenoid Accumulation on Vision-Mediated Foraging in the House Finch

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    BACKGROUND: For many bird species, vision is the primary sensory modality used to locate and assess food items. The health and spectral sensitivities of the avian visual system are influenced by diet-derived carotenoid pigments that accumulate in the retina. Among wild House Finches (Carpodacus mexicanus), we have found that retinal carotenoid accumulation varies significantly among individuals and is related to dietary carotenoid intake. If diet-induced changes in retinal carotenoid accumulation alter spectral sensitivity, then they have the potential to affect visually mediated foraging performance. METHODOLOGY/PRINCIPAL FINDINGS: In two experiments, we measured foraging performance of house finches with dietarily manipulated retinal carotenoid levels. We tested each bird's ability to extract visually contrasting food items from a matrix of inedible distracters under high-contrast (full) and dimmer low-contrast (red-filtered) lighting conditions. In experiment one, zeaxanthin-supplemented birds had significantly increased retinal carotenoid levels, but declined in foraging performance in the high-contrast condition relative to astaxanthin-supplemented birds that showed no change in retinal carotenoid accumulation. In experiments one and two combined, we found that retinal carotenoid concentrations predicted relative foraging performance in the low- vs. high-contrast light conditions in a curvilinear pattern. Performance was positively correlated with retinal carotenoid accumulation among birds with low to medium levels of accumulation (∼0.5-1.5 µg/retina), but declined among birds with very high levels (>2.0 µg/retina). CONCLUSION/SIGNIFICANCE: Our results suggest that carotenoid-mediated spectral filtering enhances color discrimination, but that this improvement is traded off against a reduction in sensitivity that can compromise visual discrimination. Thus, retinal carotenoid levels may be optimized to meet the visual demands of specific behavioral tasks and light environments

    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

    Fragment-Based Learning of Visual Object Categories in Non-Human Primates

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    When we perceive a visual object, we implicitly or explicitly associate it with an object category we know. Recent research has shown that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category. We have previously reported, using human psychophysical studies, that when subjects learn new object categories using whole objects, they incidentally learn informative fragments, even when not required to do so. However, the neuronal mechanisms by which we acquire and use informative fragments, as well as category knowledge itself, have remained unclear. Here we describe the methods by which we adapted the relevant human psychophysical methods to awake, behaving monkeys and replicated key previous psychophysical results. This establishes awake, behaving monkeys as a useful system for future neurophysiological studies not only of informative fragments in particular, but also of object categorization and category learning in general
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