1,126 research outputs found

    Glucose uptake and lipid metabolism are impaired in epicardial adipose tissue from heart failure patients with or without diabetes

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    Type 2 diabetes mellitus is a complex metabolic disease, and cardiovascular disease is a leading complication of diabetes. Epicardial adipose tissue surrounding the heart displays biochemical, thermogenic, and cardioprotective properties. However, the metabolic cross-talk between epicardial fat and the myocardium is largely unknown. This study sought to understand epicardial adipose tissue metabolism from heart failure patients with or without diabetes. We aimed to unravel possible differences in glucose and lipid metabolism between human epicardial and subcutaneous adipocytes and elucidate the potential underlying mechanisms involved in heart failure. Insulin-stimulated [(14)C]glucose uptake and isoproterenol-stimulated lipolysis were measured in isolated epicardial and subcutaneous adipocytes. The expression of genes involved in glucose and lipid metabolism was analyzed by reverse transcription-polymerase chain reaction in adipocytes. In addition, epicardial and subcutaneous fatty acid composition was analyzed by high-resolution proton nuclear magnetic resonance spectroscopy. The difference between basal and insulin conditions in glucose uptake was significantly decreased (P= 0.006) in epicardial compared with subcutaneous adipocytes. Moreover, a significant (P< 0.001) decrease in the isoproterenol-stimulated lipolysis was also observed when the two fat depots were compared, and it was strongly correlated with lipolysis, lipid storage, and inflammation-related gene expression. Moreover, the fatty acid composition of these tissues was significantly altered by diabetes. These results emphasize potential metabolic differences between both fat depots in the presence of heart failure and highlight epicardial fat as a possible therapeutic target in situ in the cardiac microenvironment.info:eu-repo/semantics/publishedVersio

    Comparison and relative utility of inequality measurements: as applied to Scotland’s child dental health

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    This study compared and assessed the utility of tests of inequality on a series of very large population caries datasets. National cross-sectional caries datasets for Scotland’s 5-year-olds in 1993/94 (n = 5,078); 1995/96 (n = 6,240); 1997/98 (n = 6,584); 1999/00 (n = 6,781); 2002/03 (n = 9,747); 2003/04 (n = 10,956); 2005/06 (n = 10,945) and 2007/08 (n = 12,067) were obtained. Outcomes were based on the d3mft metric (i.e. the number of decayed, missing and filled teeth). An area-based deprivation category (DepCat) measured the subjects’ socioeconomic status (SES). Simple absolute and relative inequality, Odds Ratios and the Significant Caries Index (SIC) as advocated by the World Health Organization were calculated. The measures of complex inequality applied to data were: the Slope Index of Inequality (absolute) and a variety of relative inequality tests i.e. Gini coefficient; Relative Index of Inequality; concentration curve; Koolman and Doorslaer’s transformed Concentration Index; Receiver Operator Curve and Population Attributable Risk (PAR). Additional tests used were plots of SIC deciles (SIC10) and a Scottish Caries Inequality Metric (SCIM10). Over the period, mean d3mft improved from 3.1(95%CI 3.0–3.2) to 1.9(95%CI 1.8–1.9) and d3mft = 0% from 41.1(95%CI 39.8–42.3) to 58.3(95%CI 57.8–59.7). Absolute simple and complex inequality decreased. Relative simple and complex inequality remained comparatively stable. Our results support the use of the SII and RII to measure complex absolute and relative SES inequalities alongside additional tests of complex relative inequality such as PAR and Koolman and Doorslaer’s transformed CI. The latter two have clear interpretations which may influence policy makers. Specialised dental metrics (i.e. SIC, SIC10 and SCIM10) permit the exploration of other important inequalities not determined by SES, and could be applied to many other types of disease where ranking of morbidity is possible e.g. obesity. More generally, the approaches described may be applied to study patterns of health inequality affecting worldwide populations

    Structural analysis and corrosion studies on an ISO 5832-9 biomedical alloy with TiO2 sol–gel layers

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    The aim of this study was to demonstrate the relationship between the structural and corrosion properties of an ISO 5832-9 biomedical alloy modified with titanium dioxide (TiO2) layers. These layers were obtained via the sol–gel method by acid-catalyzed hydrolysis of titanium isopropoxide in isopropanol solution. To obtain TiO2 layers with different structural properties, the coated samples were annealed at temperatures of 200, 300, 400, 450, 500, 600 and 800 C for 2 h. For all the prepared samples, accelerated corrosion measurements were performed in Tyrode’s physiological solution using electrochemical methods. The most important corrosion parameters were determined: corrosion potential, polarization resistance, corrosion rate, breakdown and repassivation potentials. Corrosion damage was analyzed using scanning electron microscopy. Structural analysis was carried out for selected TiO2 coatings annealed at 200, 400, 600 and 800 C. In addition, the morphology, chemical composition, crystallinity, thickness and density of the deposited TiO2 layers were determined using suitable electron and X-ray measurement methods. It was shown that the structure and character of interactions between substrate and deposited TiO2 layers depended on annealing temperature. All the obtained TiO2 coatings exhibit anticorrosion properties, but these properties are related to the crystalline structure and character of substrate–layer interaction. From the point of view of corrosion, the best TiO2 sol–gel coatings for stainless steel intended for biomedical applications seem to be those obtained at 400 C.This study was supported by Grant No. N N507 501339 of the National Science Centre. The authors wish to express their thanks to J. Borowski (MEDGAL, Poland) for the Rex 734 alloy

    The effect of graphite and carbon black ratios on conductive ink performance

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    Conductive inks based on graphite and carbon black are used in a host of applications including energy storage, energy harvesting, electrochemical sensors and printed heaters. This requires accurate control of electrical properties tailored to the application; ink formulation is a fundamental element of this. Data on how formulation relates to properties have tended to apply to only single types of conductor at any time, with data on mixed types of carbon only empirical thus far. Therefore, screen printable carbon inks with differing graphite, carbon black and vinyl polymer content were formulated and printed to establish the effect on rheology, deposition and conductivity. The study found that at a higher total carbon loading ink of 29.4% by mass, optimal conductivity (0.029 Ω cm) was achieved at a graphite to carbon black ratio of 2.6 to 1. For a lower total carbon loading (21.7 mass %), this ratio was reduced to 1.8 to 1. Formulation affected viscosity and hence ink transfer and also surface roughness due to retention of features from the screen printing mesh and the inherent roughness of the carbon components, as well as the ability of features to be reproduced consistently

    Potential toxic elements in stream sediments, soils and waters in an abandoned radium mine (central Portugal)

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    The Alto da Várzea radium mine (AV) exploited ore and U-bearing minerals, such as autunite and torbernite. The mine was exploited underground from 1911 to 1922, closed in 1946 without restoration, and actually a commercial area is deployed. Stream sediments, soils and water samples were collected between 2008 and 2009. Stream sediments are mainly contaminated in As, Th, U and W, which is related to the AV radium mine. The PTEs, As, Co, Cr, Sr, Th, U, W, Zn, and electrical conductivity reached the highest values in soils collected inside the mine influence. Soils are contaminated with As and U and must not be used for any purpose. Most waters have pH values ranging from 4.3 to 6.8 and are poorly mineralized (EC = 41-186 µS/cm; TDS = 33-172 mg/L). Groundwater contains the highest Cu, Cr and Pb contents. Arsenic occurs predominantly as H2(AsO4)- and H(AsO4)2-. Waters are saturated in goethite, haematite and some of them also in lepidocrocite and ferrihydrite, which adsorbs As (V). Lead is divalent in waters collected during the warm season, being mobile in these waters. Thorium occurs mainly as Th(OH)3(CO3)-, Th(OH)2(CO3) and Th(OH)2(CO3) 22- , which increase water Th contents. Uranium occurs predominantly as UO2CO3, but CaUO2(CO3) 32- and CaUO2(CO3)3 also occur, decreasing its mobility in water. The waters are contaminated in NO2-, Mn, Cu, As, Pb and U and must not be used for human consumption and in agricultural activities. The water contamination is mainly associated with the old radium mine and human activities. A restoration of the mining area with PTE monitoring is necessary to avoid a public hazard.Thanks are due to Prof. Joao Coutinho for the determination of organic matter and cation exchange capacity in samples of stream sediments and soils and A. Rodrigues for the water analyses, EDM for some information on the Alto da Varzea mine area. This study had the support of Portuguese Fundacao para a Ciencia e Tecnologia (FCT), through the strategic projects UID/GEO/04035/2013 and UID/MAR/04292/2013 (MARE).info:eu-repo/semantics/publishedVersio

    X-Ray Spectroscopy of Stars

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    (abridged) Non-degenerate stars of essentially all spectral classes are soft X-ray sources. Low-mass stars on the cooler part of the main sequence and their pre-main sequence predecessors define the dominant stellar population in the galaxy by number. Their X-ray spectra are reminiscent, in the broadest sense, of X-ray spectra from the solar corona. X-ray emission from cool stars is indeed ascribed to magnetically trapped hot gas analogous to the solar coronal plasma. Coronal structure, its thermal stratification and geometric extent can be interpreted based on various spectral diagnostics. New features have been identified in pre-main sequence stars; some of these may be related to accretion shocks on the stellar surface, fluorescence on circumstellar disks due to X-ray irradiation, or shock heating in stellar outflows. Massive, hot stars clearly dominate the interaction with the galactic interstellar medium: they are the main sources of ionizing radiation, mechanical energy and chemical enrichment in galaxies. High-energy emission permits to probe some of the most important processes at work in these stars, and put constraints on their most peculiar feature: the stellar wind. Here, we review recent advances in our understanding of cool and hot stars through the study of X-ray spectra, in particular high-resolution spectra now available from XMM-Newton and Chandra. We address issues related to coronal structure, flares, the composition of coronal plasma, X-ray production in accretion streams and outflows, X-rays from single OB-type stars, massive binaries, magnetic hot objects and evolved WR stars.Comment: accepted for Astron. Astrophys. Rev., 98 journal pages, 30 figures (partly multiple); some corrections made after proof stag

    Difference-based clustering of short time-course microarray data with replicates

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    <p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p
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