130 research outputs found

    Multivitamins,Nutrition,and Antiretroviral Therapy for HIV Disease in Africa

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    The Molecular Basis of Monopolin Recruitment to the Kinetochore

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    The monopolin complex is a multifunctional molecular crosslinker, which in S. pombe binds and organises mitotic kinetochores to prevent aberrant kinetochore-microtubule interactions. In the budding yeast S. cerevisiae, whose kinetochores bind a single microtubule, the monopolin complex crosslinks and mono-orients sister kinetochores in meiosis I, enabling the biorientation and segregation of homologs. Here, we show that both the monopolin complex subunit Csm1 and its binding site on the kinetochore protein Dsn1 are broadly distributed throughout eukaryotes, suggesting a conserved role in kinetochore organisation and function. We find that budding yeast Csm1 binds two conserved motifs in Dsn1, one (termed Box 1) representing the ancestral, widely conserved monopolin binding motif and a second (termed Box 2-3) with a likely role in enforcing specificity of sister kinetochore crosslinking. We find that Box 1 and Box 2-3 bind the same conserved hydrophobic cavity on Csm1, suggesting competition or handoff between these motifs. Using structure-based mutants, we also find that both Box 1 and Box 2-3 are critical for monopolin function in meiosis. We identify two conserved serine residues in Box 2-3 that are phosphorylated in meiosis and whose mutation to aspartate stabilises Csm1-Dsn1 binding, suggesting that regulated phosphorylation of these residues may play a role in sister kinetochore crosslinking specificity. Overall, our results reveal the monopolin complex as a broadly conserved kinetochore organiser in eukaryotes, which budding yeast have co-opted to mediate sister kinetochore crosslinking through the addition of a second, regulatable monopolin binding interface

    The Balloon-Borne Large Aperture Submillimeter Telescope (BLAST) 2005: A 10 deg^2 Survey of Star Formation in Cygnus X

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    We present Cygnus X in a new multi-wavelength perspective based on an unbiased BLAST survey at 250, 350, and 500 micron, combined with rich datasets for this well-studied region. Our primary goal is to investigate the early stages of high mass star formation. We have detected 184 compact sources in various stages of evolution across all three BLAST bands. From their well-constrained spectral energy distributions, we obtain the physical properties mass, surface density, bolometric luminosity, and dust temperature. Some of the bright sources reaching 40 K contain well-known compact H II regions. We relate these to other sources at earlier stages of evolution via the energetics as deduced from their position in the luminosity-mass (L-M) diagram. The BLAST spectral coverage, near the peak of the spectral energy distribution of the dust, reveals fainter sources too cool (~ 10 K) to be seen by earlier shorter-wavelength surveys like IRAS. We detect thermal emission from infrared dark clouds and investigate the phenomenon of cold ``starless cores" more generally. Spitzer images of these cold sources often show stellar nurseries, but these potential sites for massive star formation are ``starless" in the sense that to date there is no massive protostar in a vigorous accretion phase. We discuss evolution in the context of the L-M diagram. Theory raises some interesting possibilities: some cold massive compact sources might never form a cluster containing massive stars; and clusters with massive stars might not have an identifiable compact cold massive precursor.Comment: 42 pages, 31 Figures, 6 table

    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
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