96 research outputs found

    Survey and alignment of the synchrotron SIS18

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    Mesenteric fat belongs to visceral fat. An increased deposition of mesenteric fat contributes to obesity associated complications such as type 2 diabetes and cardiovascular diseases. We have investigated the therapeutic effects of bardoxolone methyl (BARD) on mesenteric adipose tissue of mice fed a high-fat diet (HFD). Male C57BL/6J mice were administered oral BARD during HFD feeding (HFD/BARD), only fed a high-fat diet (HFD), or fed low-fat diet (LFD) for 21 weeks. Histology and immunohistochemistry were used to analyse mesenteric morphology and macrophages, while Western blot was used to assess the expression of inflammatory, oxidative stress, and energy expenditure proteins. Supplementation of drinking water with BARD prevented mesenteric fat deposition, as determined by a reduction in large adipocytes. BARD prevented inflammation as there were fewer inflammatory macrophages and reduced proinflammatory cytokines (interleukin-1 beta and tumour necrosis factor alpha). BARD reduced the activation of extracellular signal-regulated kinase (ERK) and Akt, suggesting an antioxidative stress effect. BARD upregulates energy expenditure proteins, judged by the increased activity of tyrosine hydroxylase (TH) and AMP-activated protein kinase (AMPK) and increased peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), and uncoupling protein 2 (UCP2) proteins. Overall, BARD induces preventive effect in HFD mice through regulation of mesenteric adipose tissue

    Bardoxolone methyl prevents the development and progression of cardiac and renal pathophysiologies in mice fed a high-fat diet

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    Obesity caused by the consumption of a high-fat (HF) diet is a major risk factor for the development of associated complications, such as heart and kidney failure. A semi-synthetic triterpenoid, bardoxolone methyl (BM) was administrated to mice fed a HF diet for 21 weeks to determine if it would prevent the development of obesity-associated cardiac and renal pathophysiologies. Twelve week old male C57BL/6J mice were fed a lab chow (LC), HF (40% fat), or a HF diet supplemented with 10 mg/kg/day BM in drinking water. After 21 weeks, the left ventricles of hearts and cortex of kidneys of mice were collected for analysis. Histological analysis revealed that BM prevented HF diet-induced development of structural changes in the heart and kidneys. BM prevented HF diet-induced decreases in myocyte number in cardiac tissue, although this treatment also elevated cardiac endothelin signalling molecules. In the kidneys, BM administration prevented HF diet-induced renal corpuscle hypertrophy and attenuated endothelin signalling. Furthermore, in both the hearts and kidneys of mice fed a HF diet, BM administration prevented HF diet-induced increases in fat accumulation, macrophage infiltration and tumour necrosis factor alpha (TNFα) gene expression. These findings suggest that BM prevents HF diet-induced developments of cardiac and renal pathophysiologies in mice fed a chronic HF diet by preventing inflammation. Moreover, these results suggest that BM has the potential as a therapeutic for preventing obesity-induced cardiac and renal pathophysiologies

    A Novel Strategy to Construct Yeast Saccharomyces cerevisiae Strains for Very High Gravity Fermentation

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    Very high gravity (VHG) fermentation is aimed to considerably increase both the fermentation rate and the ethanol concentration, thereby reducing capital costs and the risk of bacterial contamination. This process results in critical issues, such as adverse stress factors (ie., osmotic pressure and ethanol inhibition) and high concentrations of metabolic byproducts which are difficult to overcome by a single breeding method. In the present paper, a novel strategy that combines metabolic engineering and genome shuffling to circumvent these limitations and improve the bioethanol production performance of Saccharomyces cerevisiae strains under VHG conditions was developed. First, in strain Z5, which performed better than other widely used industrial strains, the gene GPD2 encoding glycerol 3-phosphate dehydrogenase was deleted, resulting in a mutant (Z5ΔGPD2) with a lower glycerol yield and poor ethanol productivity. Second, strain Z5ΔGPD2 was subjected to three rounds of genome shuffling to improve its VHG fermentation performance, and the best performing strain SZ3-1 was obtained. Results showed that strain SZ3-1 not only produced less glycerol, but also increased the ethanol yield by up to 8% compared with the parent strain Z5. Further analysis suggested that the improved ethanol yield in strain SZ3-1 was mainly contributed by the enhanced ethanol tolerance of the strain. The differences in ethanol tolerance between strains Z5 and SZ3-1 were closely associated with the cell membrane fatty acid compositions and intracellular trehalose concentrations. Finally, genome rearrangements in the optimized strain were confirmed by karyotype analysis. Hence, a combination of genome shuffling and metabolic engineering is an efficient approach for the rapid improvement of yeast strains for desirable industrial phenotypes

    Sensory Communication

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    Contains table of contents for Section 2, an introduction and reports on twelve research projects.National Institutes of Health Grant R01 DC00117National Institutes of Health Grant R01 DC02032National Institutes of Health/National Institute of Deafness and Other Communication Disorders Grant 2 R01 DC00126National Institutes of Health Grant 2 R01 DC00270National Institutes of Health Contract N01 DC-5-2107National Institutes of Health Grant 2 R01 DC00100U.S. Navy - Office of Naval Research Grant N61339-96-K-0002U.S. Navy - Office of Naval Research Grant N61339-96-K-0003U.S. Navy - Office of Naval Research Grant N00014-97-1-0635U.S. Navy - Office of Naval Research Grant N00014-97-1-0655U.S. Navy - Office of Naval Research Subcontract 40167U.S. Navy - Office of Naval Research Grant N00014-96-1-0379U.S. Air Force - Office of Scientific Research Grant F49620-96-1-0202National Institutes of Health Grant RO1 NS33778Massachusetts General Hospital, Center for Innovative Minimally Invasive Therapy Research Fellowship Gran

    Effects of Data Quality Vetoes on a Search for Compact Binary Coalescences in Advanced LIGO's First Observing Run

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    The first observing run of Advanced LIGO spanned 4 months, from September 12, 2015 to January 19, 2016, during which gravitational waves were directly detected from two binary black hole systems, namely GW150914 and GW151226. Confident detection of gravitational waves requires an understanding of instrumental transients and artifacts that can reduce the sensitivity of a search. Studies of the quality of the detector data yield insights into the cause of instrumental artifacts and data quality vetoes specific to a search are produced to mitigate the effects of problematic data. In this paper, the systematic removal of noisy data from analysis time is shown to improve the sensitivity of searches for compact binary coalescences. The output of the PyCBC pipeline, which is a python-based code package used to search for gravitational wave signals from compact binary coalescences, is used as a metric for improvement. GW150914 was a loud enough signal that removing noisy data did not improve its significance. However, the removal of data with excess noise decreased the false alarm rate of GW151226 by more than two orders of magnitude, from 1 in 770 years to less than 1 in 186000 years.Comment: 27 pages, 13 figures, published versio

    The burden of unintentional drowning : global, regional and national estimates of mortality from the Global Burden of Disease 2017 Study

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    Background Drowning is a leading cause of injury-related mortality globally. Unintentional drowning (International Classification of Diseases (ICD) 10 codes W65-74 and ICD9 E910) is one of the 30 mutually exclusive and collectively exhaustive causes of injury-related mortality in the Global Burden of Disease (GBD) study. This study's objective is to describe unintentional drowning using GBD estimates from 1990 to 2017. Methods Unintentional drowning from GBD 2017 was estimated for cause-specific mortality and years of life lost (YLLs), age, sex, country, region, Socio-demographic Index (SDI) quintile, and trends from 1990 to 2017. GBD 2017 used standard GBD methods for estimating mortality from drowning. Results Globally, unintentional drowning mortality decreased by 44.5% between 1990 and 2017, from 531 956 (uncertainty interval (UI): 484 107 to 572 854) to 295 210 (284 493 to 306 187) deaths. Global age-standardised mortality rates decreased 57.4%, from 9.3 (8.5 to 10.0) in 1990 to 4.0 (3.8 to 4.1) per 100 000 per annum in 2017. Unintentional drowning-associated mortality was generally higher in children, males and in low-SDI to middle-SDI countries. China, India, Pakistan and Bangladesh accounted for 51.2% of all drowning deaths in 2017. Oceania was the region with the highest rate of age-standardised YLLs in 2017, with 45 434 (40 850 to 50 539) YLLs per 100 000 across both sexes. Conclusions There has been a decline in global drowning rates. This study shows that the decline was not consistent across countries. The results reinforce the need for continued and improved policy, prevention and research efforts, with a focus on low- and middle-income countries.Peer reviewe

    The burden of unintentional drowning: Global, regional and national estimates of mortality from the Global Burden of Disease 2017 Study

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    __Background:__ Drowning is a leading cause of injury-related mortality globally. Unintentional drowning (International Classification of Diseases (ICD) 10 codes W65-74 and ICD9 E910) is one of the 30 mutually exclusive and collectively exhaustive causes of injury-related mortality in the Global Burden of Disease (GBD) study. This study's objective is to describe unintentional drowning using GBD estimates from 1990 to 2017. __Methods:__ Unintentional drowning from GBD 2017 was estimated for cause-specific mortality and years of life lost (YLLs), age, sex, country, region, Socio-demographic Index (SDI) quintile, and trends from 1990 to 2017. GBD 2017 used standard GBD methods for estimating mortality from drowning. __Results:__ Globally, unintentional drowning mortality decreased by 44.5% between 1990 and 2017, from 531 956 (uncertainty interval (UI): 484 107 to 572 854) to 295 210 (284 493 to 306 187) deaths. Global age-standardised mortality rates decreased 57.4%, from 9.3 (8.5 to 10.0) in 1990 to 4.0 (3.8 to 4.1) per 100 000 per annum in 2017. Unintentional drowning-associated mortality was generally higher in children, males and in low-SDI to middle-SDI countries. China, India, Pakistan and Bangladesh accounted for 51.2% of all drowning deaths in 2017. Oceania was the region with the highest rate of age-standardised YLLs in 2017, with 45 434 (40 850 to 50 539) YLLs per 100 000 across both sexes. __Conclusions:__ There has been a decline in global drowning rates. This study shows that the decline was not consistent across countries. The results reinforce the need for continued and improved policy, prevention and research efforts, with a focus on low-and middle-income countries

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
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