384 research outputs found

    COVID-19 in People with Diabetes: Urgently Needed Lessons from Early Reports

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    Epidemic infections have frightened and harmed people for millennia. Plague and typhus, bacterial infections associated with poor sanitation and high mortality, have devastated populations. Both still reappear intermittently, but they are generally contained with better sanitation and control of rodent and insect vectors along with antibiotics. In contrast, viral epidemics persist. A unique strain of influenza caused a global epidemic (pandemic) in 1918 resulting in millions of deaths. Among recent outbreaks of viral infections, several have been caused by coronaviruses. One of these, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is now causing a pandemic illness termed coronavirus disease 2019 (COVID-19) that poses unique challenges. This novel coronavirus is readily transmitted from person-to-person, even by thosewho are infected but without symptoms. In susceptible people it causes severe illness and often death from pulmonary and systemic injuries. At present, we have neither a preventive vaccine nor well-studied pharmacotherapy, although work to develop these is vigorously underway

    HIV-1 diversity among young women in rural South Africa: HPTN 068

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    Background South Africa has one of the highest rates of HIV-1 (HIV) infection world-wide, with the highest rates among young women. We analyzed the molecular epidemiology and evolutionary history of HIV in young women attending high school in rural South Africa. Methods Samples were obtained from the HPTN 068 randomized controlled trial, which evaluated the effect of cash transfers for school attendance on HIV incidence in women aged 13–20 years (Mpumalanga province, 2011–2015). Plasma samples from HIV-infected participants were analyzed using the ViroSeq HIV-1 Genotyping assay. Phylogenetic analysis was performed using 200 pol gene study sequences and 2,294 subtype C reference sequences from South Africa. Transmission clusters were identified using Cluster Picker and HIV-TRACE, and were characterized using demographic and other epidemiological data. Phylodynamic analyses were performed using the BEAST software. Results The study enrolled 2,533 young women who were followed through their expected high school graduation date (main study); some participants had a post-study assessment (follow-up study). Two-hundred-twelve of 2,533 enrolled young women had HIV infection. HIV pol sequences were obtained for 94% (n = 201/212) of the HIV-infected participants. All but one of the sequences were HIV-1 subtype C; the non-C subtype sequence was excluded from further analysis. Median pairwise genetic distance between the subtype C sequences was 6.4% (IQR: 5.6–7.2). Overall, 26% of study sequences fell into 21 phylogenetic clusters with 2–6 women per cluster. Thirteen (62%) clusters included women who were HIV-infected at enrollment. Clustering was not associated with study arm, demographic or other epidemiological factors. The estimated date of origin of HIV subtype C in the study population was 1958 (95% highest posterior density [HPD]: 1931–1980), and the median estimated substitution rate among study pol sequences was 1.98x10-3 (95% HPD: 1.15x10-3–2.81x10-3) per site per year. Conclusions Phylogenetic analysis suggests that multiple HIV subtype C sublineages circulate among school age girls in South Africa. There were no substantive differences in the molecular epidemiology of HIV between control and intervention arms in the HPTN 068 trial

    Magnetization and specific heat of the dimer system CuTe2O5

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    We report on magnetization and specific heat measurements on single-crystalline CuTe2O5. The experimental data are directly compared to theoretical results for two different spin structures, namely an alternating spin-chain and a two-dimensional (2D) coupled dimer model, obtained by Das et al. [Phys. Rev. B 77, 224437 (2008)]. While the analysis of the specific heat does not allow to distinguish between the two models, the magnetization data is in good agreement with the 2D coupled dimer model.Comment: 5 pages, 3 figure

    Massive Star Formation

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    This chapter reviews progress in the field of massive star formation. It focuses on evidence for accretion and current models that invoke high accretion rates. In particular it is noted that high accretion rates will cause the massive young stellar object to have a radius much larger than its eventual main sequence radius throughout much of the accretion phase. This results in low effective temperatures which may provide the explanation as to why luminous young stellar objects do not ionized their surroundings to form ultra-compact H II regions. The transition to the ultra-compact H II region phase would then be associated with the termination of the high accretion rate phase. Objects thought to be in a transition phase are discussed and diagnostic diagrams to distinguish between massive young stellar objects and ultra-compact H II regions in terms of line widths and radio luminosity are presented.Comment: 21 pages, 6 figures, chapter in Diffuse Matter from Star Forming Regions to Active Galaxies - A Volume Honouring John Dyson, Edited by T.W. Hartquist, J. M. Pittard, and S. A. E. G. Falle. Series: Astrophysics and Space Science Proceedings. Springer Dordrecht, 2007, p.6

    Enhanced glycemic control with combination therapy for type 2 diabetes in primary care

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    Type 2 diabetes mellitus is an increasingly common medical problem for primary care clinicians to address. Treatment of diabetes has evolved from simple replacement of insulin (directly or through insulin secretagogs) through capture of mechanisms such as insulin sensitizers, alpha-glucosidase inhibitors, and incretins. Only very recently has recognition of the critical role of the gastrointestinal system as a major culprit in glucose dysregulation been established. Since glycated hemoglobin A1c reductions provide meaningful risk reduction as well as improved quality of life, it is worthwhile to explore evolving paths for more efficient use of the currently available pharmacotherapies. Because diabetes is a progressive disease, even transiently successful treatment will likely require augmentation as the disorder progresses. Pharmacotherapies with complementary mechanisms of action will be necessary to achieve glycemic goals. Hence, clinicians need to be well informed about the various noninsulin alternatives that have been shown to be successful in glycemic goal attainment. This article reviews the benefits of glucose control, the current status of diabetes control, pertinent pathophysiology, available pharmacological classes for combination, limitations of current therapies, and suggestions for appropriate combination therapies, including specific suggestions for thresholds at which different strategies might be most effectively utilized by primary care clinicians

    The Role of Oestrogen Receptor Beta (ERβ) in the Aetiology and Treatment of Type 2 Diabetes Mellitus

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    Introduction: Challenges facing the treatment of type 2 diabetes necessitate the search for agents which act via alternative pathways to provide better therapeutic outcomes. Recently, an increasing body of evidence implicates the activation of oestrogen receptors (ERα and ERβ) in the development and treatment of underlying conditions in type 2 diabetes. This article summarizes available evidence for the involvement of oestrogen receptors in insulin secretion, insulin resistance as well as glucose uptake and highlights the potential of ERβ as a therapeutic target. Background: Recent studies indicate an association between the activation of each of the isoforms of ER and recent findings indicate that ERβ shows promise as a potential target for antidiabetic drugs. In vitro and in vivo studies in receptor knockout mice indicate beneficial actions of selective agonists of ERβ receptor and underscore its therapeutic potential. Conclusion: Studies are needed to further elucidate the exact mechanism underlying the role of ERβ activation as a therapeutic approach in the management of type 2 diabetes

    How to move ionized gas: an introduction to the dynamics of HII regions

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    This review covers the dynamic processes that are important in the evolution and structure of galactic HII regions, concentrating on an elementary presentation of the physical concepts and recent numerical simulations of HII region evolution in a non-uniform medium. The contents are as follows: (1) The equations (Euler equations; Radiative transfer; Rate equations; How to avoid the dynamics; How to avoid the atomic physics). (2) Physical concepts (Static photoionization equilibrium; Ionization front propagation; Structure of a D-type front; Photoablation flows; Other ingredients - Stellar winds, Radiation pressure, Magnetic fields, Instabilities). (3) HII region evolution (Early phases: hypercompact and ultracompact regions; Later phases: compact and extended regions; Clumps and turbulence).Comment: To be published as a chapter in 'Diffuse Matter from Star Forming Regions to Active Galaxies' - A volume Honouring John Dyson. Eds. T. W. Harquist, J. M. Pittard and S. A. E. G. Falle. 25 pages, 7 figures. Some figures degraded to meet size restriction. Full-resolution version available at http://www.ifront.org/wiki/Dyson_Festschrift_Chapte

    Evidence for gene-smoking interactions for hearing loss and deafness in Japanese American families

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    Background: This study investigated the relationship between smoking and hearing loss and deafness (HLD) and whether the relationship is modified by genetic variation. Data for these analyses was from the subset of Japanese American families collected as part of the American Diabetes Association Genetics of Non-insulin Dependent Diabetes Mellitus study. Logistic regression with generalized estimating equations assessed the relationship between HLD and smoking. Nonparametric linkage analysis identified genetic regions harboring HLD susceptibility genes and ordered subset analysis was used to identify regions showing evidence for gene-smoking interactions. Genetic variants within these candidate regions were then each tested for interaction with smoking using logistic regression models. Results: After adjusting for age, sex, diabetes status and smoking duration, for each pack of cigarettes smoked per day, risk of HLD increased 4.58 times (odds ratio (OR) = 4.58; 95% Confidence Interval (CI): (1.40,15.03)), and ever smokers were over 5 times more likely than nonsmokers to report HLD (OR = 5.22; 95% CI: (1.24, 22.03)). Suggestive evidence for linkage for HLD was observed in multiple genomic regions (Chromosomes 5p15, 8p23 and 17q21), and additional suggestive regions were identified when considering interactions with smoking status (Chromosomes 7p21, 11q23, 12q32, 15q26, and 20q13) and packs-per-day (Chromosome 8q21). Conclusions: To our knowledge this was the first report of possible gene-by-smoking interactions in HLD using family data. Additional work, including independent replication, is needed to understand the basis of these findings. HLD are important public health issues and understanding the contributions of genetic and environmental factors may inform public health messages and policies

    “The Times They Are A-Changin’” at Diabetes Care

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    Every five years or so, the editorial team leading Diabetes Care turns over with the appointment of new leadership. This issue of volume 46 represents the first of a new editorial team, making it the tenth group to be responsible for the scientific content of the journal. Starting in 1978 with Jay Skyler as its first editor, Diabetes Care has gone from strength to strength with new initiatives and a steady increase in its influence. This impact has been in line with the charge given at the journal’s founding by the then president of the American Diabetes Association Norbert Freinkel when he wrote, “The new journal is designed to promote better patient care by serving the expanded needs of all health professionals committed to the care of patients with diabetes.

    Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

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    Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)
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