151 research outputs found

    Patient endothelial colony-forming cells to model coronary artery disease susceptibility and unravel the role of dysregulated mitochondrial redox signalling

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    Mechanisms involved in the individual susceptibility to atherosclerotic coronary artery disease (CAD) beyond traditional risk factors are poorly understood. Here, we describe the utility of cultured patient-derived endothelial colony-forming cells (ECFCs) in examining novel mechanisms of CAD susceptibility, particularly the role of dysregulated redox signalling. ECFCs were selectively cultured from peripheral blood mononuclear cells from 828 patients from the BioHEART-CT cohort, each with corresponding demographic, clinical and CT coronary angiographic imaging data. Spontaneous growth occurred in 178 (21.5%) patients and was more common in patients with hypertension (OR 1.45 (95% CI 1.03–2.02), p = 0.031), and less likely in patients with obesity (OR 0.62 [95% CI 0.40–0.95], p = 0.027) or obstructive CAD (stenosis > 50%) (OR 0.60 [95% CI 0.38–0.95], p = 0.027). ECFCs from patients with CAD had higher mitochondrial production of superoxide (O2 −–MitoSOX assay). The latter was strongly correlated with the severity of CAD as measured by either coronary artery calcium score (R2 = 0.46; p = 0.0051) or Gensini Score (R2 = 0.67; p = 0.0002). Patient-derived ECFCs were successfully cultured in 3D culture pulsatile mini-vessels. Patient-derived ECFCs can provide a novel resource for discovering mechanisms of CAD disease susceptibility, particularly in relation to mitochondrial redox signalling.Marie Besnier, Meghan Finemore, Christine Yu, Katharine A. Kott, Stephen T. Vernon, Nicole A. Seebacher, Elijah Genetzakis, Anamarija Furman, Owen Tang, Ryan L. Davis, Thomas Hansen, Peter J. Psaltis, Kristen J. Bubb, Steven G. Wise, Stuart M. Grieve, Belinda A. Di Bartolo, and Gemma A. Figtre

    Detector Description and Performance for the First Coincidence Observations between LIGO and GEO

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    For 17 days in August and September 2002, the LIGO and GEO interferometer gravitational wave detectors were operated in coincidence to produce their first data for scientific analysis. Although the detectors were still far from their design sensitivity levels, the data can be used to place better upper limits on the flux of gravitational waves incident on the earth than previous direct measurements. This paper describes the instruments and the data in some detail, as a companion to analysis papers based on the first data.Comment: 41 pages, 9 figures 17 Sept 03: author list amended, minor editorial change

    Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

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    We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--1.0M1.0 M_\odot. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--1.0M1.0 M_\odot, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

    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

    Effect of age, sex and gender on pain sensitivity: A narrative review

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    © 2017 Eltumi And Tashani. Introduction: An increasing body of literature on sex and gender differences in pain sensitivity has been accumulated in recent years. There is also evidence from epidemiological research that painful conditions are more prevalent in older people. The aim of this narrative review is to critically appraise the relevant literature investigating the presence of age and sex differences in clinical and experimental pain conditions. Methods: A scoping search of the literature identifying relevant peer reviewed articles was conducted on May 2016. Information and evidence from the key articles were narratively described and data was quantitatively synthesised to identify gaps of knowledge in the research literature concerning age and sex differences in pain responses. Results: This critical appraisal of the literature suggests that the results of the experimental and clinical studies regarding age and sex differences in pain contain some contradictions as far as age differences in pain are concerned. While data from the clinical studies are more consistent and seem to point towards the fact that chronic pain prevalence increases in the elderly findings from the experimental studies on the other hand were inconsistent, with pain threshold increasing with age in some studies and decreasing with age in others. Conclusion: There is a need for further research using the latest advanced quantitative sensory testing protocols to measure the function of small nerve fibres that are involved in nociception and pain sensitivity across the human life span. Implications: Findings from these studies should feed into and inform evidence emerging from other types of studies (e.g. brain imaging technique and psychometrics) suggesting that pain in the older humans may have unique characteristics that affect how old patients respond to intervention

    Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

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    Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

    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

    Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

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    The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing
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