173 research outputs found

    Insulin resistance in type 1 diabetes: what is ‘double diabetes’ and what are the risks?

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    In this review, we explore the concept of ‘double diabetes’, a combination of type 1 diabetes with features of insulin resistance and type 2 diabetes. After considering whether double diabetes is a useful concept, we discuss potential mechanisms of increased insulin resistance in type 1 diabetes before examining the extent to which double diabetes might increase the risk of cardiovascular disease (CVD). We then go on to consider the proposal that weight gain from intensive insulin regimens may be associated with increased CV risk factors in some patients with type 1 diabetes, and explore the complex relationships between weight gain, insulin resistance, glycaemic control and CV outcome. Important comparisons and contrasts between type 1 diabetes and type 2 diabetes are highlighted in terms of hepatic fat, fat partitioning and lipid profile, and how these may differ between type 1 diabetic patients with and without double diabetes. In so doing, we hope this work will stimulate much-needed research in this area and an improvement in clinical practice

    Multi-Gene Expression Predictors of Single Drug Responses to Adjuvant Chemotherapy in Ovarian Carcinoma: Predicting Platinum Resistance

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    Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Standard therapy includes treatment with platinum-based combination chemotherapies yet there is no biomarker model to predict their responses to these agents. We here have developed and independently tested our multi-gene molecular predictors for forecasting patients' responses to individual drugs on a cohort of 55 ovarian cancer patients. To independently validate these molecular predictors, we performed microarray profiling on FFPE tumor samples of 55 ovarian cancer patients (UVA-55) treated with platinum-based adjuvant chemotherapy. Genome-wide chemosensitivity biomarkers were initially discovered from the in vitro drug activities and genomic expression data for carboplatin and paclitaxel, respectively. Multivariate predictors were trained with the cell line data and then evaluated with a historical patient cohort. For the UVA-55 cohort, the carboplatin, taxol, and combination predictors significantly stratified responder patients and non-responder patients (p = 0.019, 0.04, 0.014) with sensitivity = 91%, 96%, 93 and NPV = 57%, 67%, 67% in pathologic clinical response. The combination predictor also demonstrated a significant survival difference between predicted responders and non-responders with a median survival of 55.4 months vs. 32.1 months. Thus, COXEN single- and combination-drug predictors successfully stratified platinum resistance and taxane response in an independent cohort of ovarian cancer patients based on their FFPE tumor samples

    Are Happiness and Life Satisfaction Different Across Religious groups? Exploring Determinants of Happiness and Life Satisfaction

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    This study explores whether different religions experience different levels of happiness and life satisfaction and in case this is affected by country economic and cultural environment. Using World Value Survey (from 1981 to 2014), this study found that individual religiosity and country level of development play a significant role in shaping people’s subjective well-being (SWB). Protestants, Buddhists and Roman Catholic were happier and most satisfied with their lives compared to other religious groups. Orthodox has the lowest SWB. Health status, household’s financial satisfaction and freedom of choice are means by which religious groups and governments across the globe can improve the SWB of their citizens. Keywords: happiness; life satisfaction; religion; religious differences; cultur

    Relationship Between Risk Factors and Mortality in Type 1 Diabetic Patients in Europe: The EURODIAB Prospective Complications Study (PCS)

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    OBJECTIVE—The purpose of this study was to examine risk factors for mortality in patients with type 1 diabetes

    Plasma levels of matrix metalloproteinase-2, -3, -10, and tissue inhibitor of metalloproteinase-1 are associated with vascular complications in patients with type 1 diabetes: The EURODIAB Prospective Complications Study

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    Impaired regulation of extracellular matrix remodeling by matrix metalloproteinases (MMPs) and tissue inhibitor of metalloproteinase (TIMP) may contribute to vascular complications in patients with type 1 diabetes. We investigated associations between plasma MMP-1, -2, -3, -9, -10 and TIMP-1, and cardiovascular disease (CVD) or microvascular complications in type 1 diabetic patients. We also evaluated to which extent these associations could be explained by low-grade inflammation (LGI) or endothelial dysfunction (ED). Methods: 493 type 1 diabetes patients (39.5 ± 9.9 years old, 51% men) from the EURODIAB Prospective Complications Study were included. Linear regression analysis was applied to investigate differences in plasma levels of MMP-1, -2, -3, -9, -10, and TIMP-1 between patients with and without CVD, albuminuria or retinopathy. All analyses were adjusted for age, sex, duration of diabetes, Hba1c and additionally for other cardiovascular risk factors including LGI and ED. Results: Patients with CVD (n = 118) showed significantly higher levels of TIMP-1 [ÎČ = 0.32 SD (95%CI: 0.12; 0.52)], but not of MMPs, than patients without CVD (n = 375). Higher plasma levels of MMP-2, MMP-3, MMP-10 and TIMP-1 were associated with higher levels of albuminuria (p-trends were 0.028, 0.004, 0.005 and 0.001, respectively). Severity of retinopathy was significantly associated with higher levels of MMP-2 (p-trend = 0.017). These associations remained significant after further adjustment for markers of LGI and ED. Conclusions: These data support the hypothesis that impaired regulation of matrix remodeling by actions of MMP-2, -3 and-10 and TIMP-1 contributes to the pathogenesis of vascular complications in type 1 diabetes

    Priorities for synthesis research in ecology and environmental science

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    ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

    Priorities for synthesis research in ecology and environmental science

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    ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

    Application of Ligninolytic Enzymes in the Production of Biofuels from Cotton Wastes

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    The application of ligninolytic fungi and enzymes is an option to overcome the issues related with the production of biofuels using cotton wastes. In this dissertation, the ligninolytic fungus and enzymes were evaluated as pretreatment for the biochemical conversion of Cotton Gin Trash (CGT) in ethanol and as a treatment for the transformation of cotton wastes biochar in other substances. In biochemical conversion, seven combinations of three pretreatments (ultrasonication, liquid hot water and ligninolytic enzymes) were evaluated on CGT. The best results were achieved by the sequential combination of ultrasonication, hot water, and ligninolytic enzymes with an improvement of 10% in ethanol yield. To improve these results, alkaline-ultrasonication was evaluated. Additionally, Fourier Transform Infrared (FT-IR) and principal component analysis (PCA) were employed as fast methodology to identify structural differences in the biomass. The combination of ultrasonication-alkali hydrolysis, hot liquid water, and ligninolytic enzymes using 15% of NaOH improved 35% ethanol yield compared with the original treatment. Additionally, FT-IR and PCA identified modifications in the biomass structure after different types of pretreatments and conditions. In thermal conversion, this study evaluated the biodepolymerization of cotton wastes biochar using chemical and biological treatments. The chemical depolymerization evaluated three chemical agents (KMnO4, H2SO4, and NaOH), with three concentrations and two environmental conditions. The sulfuric acid treatments performed the largest transformations of the biochar solid phase; whereas, the KMnO4 treatments achieved the largest depolymerizations. The compounds released into the liquid phase were correlated with fulvic and humic acids and silicon compounds. The biological depolymerization utilized four ligninolytic fungi Phanerochaete chrysosporium, Ceriporiopsis subvermispora, Postia placenta, and Bjerkandera adusta. The greatest depolymerization was obtained by C. subvermispora. The depolymerization kinetics of C. subvermispora evidenced the production of laccase and manganese peroxidase and a correlation between depolymerization and production of ligninolytic enzymes. The modifications obtained in the liquid and solid phases showed the production of humic and fulvic acids from the cultures with C. subvermispora. The results of this research are the initial steps for the development of new processes using the ligninolytic fungus and their enzymes for the production of biofuels from cotton wastes

    Priorities for synthesis research in ecology and environmental science

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    Synthesis research in ecology and environmental science improves understanding, advances theory, identifies research priorities, and supports management strategies by linking data, ideas, and tools. Accelerating environmental challenges increases the need to focus synthesis science on the most pressing questions. To leverage input from the broader research community, we convened a virtual workshop with participants from many countries and disciplines to examine how and where synthesis can address key questions and themes in ecology and environmental science in the coming decade. Seven priority research topics emerged: (1) diversity, equity, inclusion, and justice (DEIJ), (2) human and natural systems, (3) actionable and use-inspired science, (4) scale, (5) generality, (6) complexity and resilience, and (7) predictability. Additionally, two issues regarding the general practice of synthesis emerged: the need for increased participant diversity and inclusive research practices; and increased and improved data flow, access, and skill-building. These topics and practices provide a strategic vision for future synthesis in ecology and environmental science
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