3,276 research outputs found

    Transcriptional up-regulation of relaxin-3 by Nur77 attenuates β-adrenergic agonist-induced apoptosis in cardiomyocytes.

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    The relaxin family peptides have been shown to exert several beneficial effects on the heart, including anti-apoptosis, anti-fibrosis, and anti-hypertrophy activity. Understanding their regulation might provide new opportunities for therapeutic interventions, but the molecular mechanism(s) coordinating relaxin expression in the heart remain largely obscured. Previous work demonstrated a role for the orphan nuclear receptor Nur77 in regulating cardiomyocyte apoptosis. We therefore investigated Nur77 in the hopes of identifying novel relaxin regulators. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) data indicated that ectopic expression of orphan nuclear receptor Nur77 markedly increased the expression of latexin-3 (RLN3), but not relaxin-1 (RLN1), in neonatal rat ventricular cardiomyocytes (NRVMs). Furthermore, we found that the -adrenergic agonist isoproterenol (ISO) markedly stimulated RLN3 expression, and this stimulation was significantly attenuated in Nur77 knockdown cardiomyocytes and Nur77 knockout hearts. We showed that Nur77 significantly increased RLN3 promoter activity via specific binding to the RLN3 promoter, as demonstrated by electrophoretic mobility shift assay (EMSA) and chromatin immuno-precipitation (ChIP) assays. Furthermore, we found that Nur77 overexpression potently inhibited ISO-induced cardiomyocyte apoptosis, whereas this protective effect was significantly attenuated in RLN3 knockdown cardiomyocytes, suggesting that Nur77-induced RLN3 expression is an important mediator for the suppression of cardiomyocyte apoptosis. These findings show that Nur77 regulates RLN3 expression, therefore suppressing apoptosis in the heart, and suggest that activation of Nur77 may represent a useful therapeutic strategy for inhibition of cardiac fibrosis and heart failure. © 2018 You et al

    Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations

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    Stochastic partial differential equations (SPDEs) are crucial for modelling dynamics with randomness in many areas including economics, physics, and atmospheric sciences. Recently, using deep learning approaches to learn the PDE solution for accelerating PDE simulation becomes increasingly popular. However, SPDEs have two unique properties that require new design on the models. First, the model to approximate the solution of SPDE should be generalizable over both initial conditions and the random sampled forcing term. Second, the random forcing terms usually have poor regularity whose statistics may diverge (e.g., the space-time white noise). To deal with the problems, in this work, we design a deep neural network called Deep Latent Regularity Net (DLR-Net). DLR-Net includes a regularity feature block as the main component, which maps the initial condition and the random forcing term to a set of regularity features. The processing of regularity features is inspired by regularity structure theory and the features provably compose a set of basis to represent the SPDE solution. The regularity features are then fed into a small backbone neural operator to get the output. We conduct experiments on various SPDEs including the dynamic Φ^{4}_{1} model and the stochastic 2D Navier-Stokes equation to predict their solutions, and the results demonstrate that the proposed DLR-Net can achieve SOTA accuracy compared with the baselines. Moreover, the inference time is over 20 times faster than the traditional numerical solver and is comparable with the baseline deep learning models

    Soybean \u3ci\u3eGm\u3c/i\u3eSAUL1, a Bona Fide U-Box E3 Ligase, Negatively Regulates Immunity Likely through Repressing the Activation of \u3ci\u3eGm\u3c/i\u3eMPK3

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    E3 ubiquitin ligases play important roles in plant immunity, but their role in soybean has not been investigated previously. Here, we used Bean pod mottle virus (BPMV)-mediated virusinduced gene silencing (VIGS) to investigate the function of GmSAUL1 (Senescence-Associated E3 Ubiquitin Ligase 1) homologs in soybean. When two closely related SAUL1 homologs were silenced simultaneously, the soybean plants displayed autoimmune phenotypes, which were significantly alleviated by high temperature, suggesting that GmSAUL1a/1b might be guarded by an R protein. Interestingly, silencing GmSAUL1a/1b resulted in the decreased activation of GmMPK6, but increased activation of GmMPK3 in response to flg22, suggesting that the activation of GmMPK3 is most likely responsible for the activated immunity observed in the GmSAUL1a/1b-silenced plants. Furthermore, we provided evidence that GmSAUL1a is a bona fide E3 ligase. Collectively, our results indicated that GmSAUL1 plays a negative role in regulating cell death and immunity in soybean

    Deficiency and excess of groundwater iodine and their health associations.

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    More than two billion people worldwide have suffered thyroid disorders from either iodine deficiency or excess. By creating the national map of groundwater iodine throughout China, we reveal the spatial responses of diverse health risks to iodine in continental groundwater. Greater non-carcinogenic risks relevant to lower iodine more likely occur in the areas of higher altitude, while those associated with high groundwater iodine are concentrated in the areas suffered from transgressions enhanced by land over-use and intensive anthropogenic overexploitation. The potential roles of groundwater iodine species are also explored: iodide might be associated with subclinical hypothyroidism particularly in higher iodine regions, whereas iodate impacts on thyroid risks in presence of universal salt iodization exhibit high uncertainties in lower iodine regions. This implies that accurate iodine supply depending on spatial heterogeneity and dietary iodine structure optimization are highly needed to mitigate thyroid risks in iodine-deficient and -excess areas globally

    Deficiency and excess of groundwater iodine and their health associations

    Get PDF
    More than two billion people worldwide have suffered thyroid disorders from either iodine deficiency or excess. By creating the national map of groundwater iodine throughout China, we reveal the spatial responses of diverse health risks to iodine in continental groundwater. Greater non-carcinogenic risks relevant to lower iodine more likely occur in the areas of higher altitude, while those associated with high groundwater iodine are concentrated in the areas suffered from transgressions enhanced by land over-use and intensive anthropogenic overexploitation. The potential roles of groundwater iodine species are also explored: iodide might be associated with subclinical hypothyroidism particularly in higher iodine regions, whereas iodate impacts on thyroid risks in presence of universal salt iodization exhibit high uncertainties in lower iodine regions. This implies that accurate iodine supply depending on spatial heterogeneity and dietary iodine structure optimization are highly needed to mitigate thyroid risks in iodine-deficient and -excess areas globally

    Evaluation of inpatient services of tertiary comprehensive hospitals based on DRG payment

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    ObjectiveThis study aims to evaluate inpatient services in 49 tertiary comprehensive hospitals using indicators from the diagnosis related groups (DRG) payment system.MethodDRG data from 49 tertiary comprehensive hospitals were obtained from the quality monitoring platform for provincial hospitals, and relevant indicators were identified. The analytic hierarchy process (AHP) was used to compute the weight of each indicator. The rank sum ratio method was used to calculate the weight rank sum ratio (WRSR) value and the corresponding probit value of each hospital. The hospitals were divided into four grades based on the threshold value: excellent, good, fair, and poor.ResultsEight indicators of the 49 hospitals were scored, and the hospital rankings of indicators varied. The No. 1 hospital ranked first in the indicators of “total number of DRG”, “number of groups”, and “proportion of relative weights (RW) ≥ 2”. The WRSR value of the No.1 hospital was the largest (0.574), and the WRSR value of the No. 44 hospital was the smallest (0.139). The linear regression equation was established: WRSRpredicted =-0.141+0.088*Probit, and the regression model was well-fitted (F = 2066.672, p < 0.001). The cut-off values of the three WRSRspredicted by the four levels were 0.167, 0.299, and 0.431, respectively. The 49 hospitals were divided into four groups: excellent (4), good (21), average (21), and poor (3). There were significant differences in the average WRSR values of four categories of hospitals (p < 0.05).ConclusionThere were notable variances in the levels of inpatient services among 49 tertiary comprehensive hospitals, and hospitals of the same category also showed different service levels. The evaluation results contribute to the health administrative department and the hospital to optimize the allocation of resources, improve the DRG payment system, and enhance the quality and efficiency of inpatient services

    FlyRNAi.org—the database of the Drosophila RNAi screening center: 2012 update

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    FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database
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