1,248 research outputs found

    Alpha Lipoic Acid Modulated High Glucose-Induced Rat Mesangial Cell Dysfunction via mTOR/p70S6K/4E-BP1 Pathway

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    The aim of this study was to investigate whether alpha lipoic acid (LA) regulates high glucose-induced mesangial cell proliferation and extracellular matrix production via mTOR/p70S6K/4E-BP1 signaling. The effect of LA on high glucose-induced cell proliferation, fibronectin (FN), and collagen type I (collagen-I) expression and its mechanisms were examined in cultured rat mesangial cells by methylthiazol tetrazolium (MTT) assay, flow cytometry, ELISA assay, and western blot, respectively. LA at a relatively low concentration (0.25 mmol/L) acted as a growth factor in rat mesangial cells, promoted entry of cell cycle into S phase, extracellular matrix formation, and phosphorylated AKT, mTOR, p70S6K, and 4E-BP1. These effects disappeared when AKT expression was downregulated with PI3K/AKT inhibitor LY294002. Conversely, LA at a higher concentration (1.0 mmol/L) inhibited high glucose-induced rat mesangial cell proliferation, entry of cell cycle into S phase, and extracellular matrix exertion, as well as phosphorylation of mTOR, p70S6K, and 4E-BP1 but enhanced the activity of AMPK. However, these effects disappeared when AMPK activity was inhibited with CaMKK inhibitor STO-609. These results suggest that LA dose-dependently regulates mesangial cell proliferation and matrix protein secretion by mTOR/p70S6K/4E-BP1 signaling pathway under high glucose conditions

    ∣Vub∣|V_{ub}| and B→η(′)B\to\eta^{(')} Form Factors in Covariant Light Front Approach

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    B→(π,η,η′)B\to (\pi, \eta, \eta') transition form factors are investigated in the covariant light-front approach. With theoretical uncertainties, we find that B→(π,η,η′)B\to (\pi, \eta, \eta') form factors at q2=0q^2=0 are f+(π,η,η′)(0)=(0.245−0.001+0.000±0.011,0.220±0.009±0.009,0.180±0.008−0.007+0.008)f^{(\pi, \eta, \eta')}_{+}(0)=(0.245^{+0.000}_{-0.001}\pm 0.011, 0.220 \pm 0.009\pm0.009, 0.180\pm 0.008^{+0.008}_{-0.007}) for vector current and fT(π,η,η′)(0)=(0.239−0.003−0.018+0.002+0.020,0.211±0.009−0.015+0.017,0.173±0.007−0.013+0.014)f^{(\pi, \eta, \eta')}_{T}(0)=(0.239^{+0.002+0.020}_{-0.003-0.018}, 0.211\pm 0.009^{+0.017}_{-0.015}, 0.173\pm 0.007^{+0.014}_{-0.013}) for tensor current, respectively. With the obtained q2q^2-dependent f+π(q2)f^{\pi}_{+}(q^2) and observed branching ratio (BR) for Bˉd→π+ℓνˉℓ\bar B_d\to \pi^+ \ell \bar \nu_{\ell}, the VubV_{ub} is found as ∣Vub∣LF=(3.99±0.13)×10−3|V_{ub}|_{LF}= (3.99 \pm 0.13)\times 10^{-3}. As a result, the predicted BRs for Bˉ→(η,η′)ℓνˉℓ\bar B\to (\eta, \eta') \ell \bar\nu_{\ell} decays with ℓ=e,μ\ell=e,\mu are given by (0.49−0.04−0.07+0.02+0.10,0.24−0.02−0.03+0.01+0.04)×10−4(0.49^{+0.02+0.10}_{-0.04- 0.07}, 0.24^{+0.01+0.04}_{-0.02-0.03})\times 10^{-4}, while the BRs for D−→(η,η′)ℓνˉℓD^-\to (\eta,\eta')\ell\bar\nu_{\ell} are (11.1−0.6−0.9+0.5+0.9,1.79−0.08−0.12+0.07+0.12)×10−4(11.1^{+0.5+0.9}_{-0.6-0.9}, 1.79^{+0.07+0.12}_{-0.08-0.12})\times 10^{-4}. In addition, we also study the integrated lepton angular asymmetries for Bˉ→(π,η,η′)τνˉτ\bar B\to (\pi,\eta,\eta')\tau \bar\nu_{\tau}:(0.277−0.001−0.007+0.001+0.005,0.290−0.000−0.003+0.002+0.003,0.312−0.000−0.006+0.004+0.005)(0.277^{+0.001+0.005}_{-0.001-0.007},0.290^{+0.002+0.003}_{-0.000-0.003},0.312^{+0.004+0.005}_{-0.000-0.006}).Comment: 14 pages, 2 figures, final version to appear in PL

    Provable Training for Graph Contrastive Learning

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    Graph Contrastive Learning (GCL) has emerged as a popular training approach for learning node embeddings from augmented graphs without labels. Despite the key principle that maximizing the similarity between positive node pairs while minimizing it between negative node pairs is well established, some fundamental problems are still unclear. Considering the complex graph structure, are some nodes consistently well-trained and following this principle even with different graph augmentations? Or are there some nodes more likely to be untrained across graph augmentations and violate the principle? How to distinguish these nodes and further guide the training of GCL? To answer these questions, we first present experimental evidence showing that the training of GCL is indeed imbalanced across all nodes. To address this problem, we propose the metric "node compactness", which is the lower bound of how a node follows the GCL principle related to the range of augmentations. We further derive the form of node compactness theoretically through bound propagation, which can be integrated into binary cross-entropy as a regularization. To this end, we propose the PrOvable Training (POT) for GCL, which regularizes the training of GCL to encode node embeddings that follows the GCL principle better. Through extensive experiments on various benchmarks, POT consistently improves the existing GCL approaches, serving as a friendly plugin

    QT Interval Prolongation Associated with Intramuscular Ziprasidone in Chinese Patients: A Case Report and a Comprehensive Literature Review with Meta-Analysis

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    Intramuscular (IM) ziprasidone has been associated with QTc interval prolongations in patients with preexisting risk factors. A 23-year-old male Chinese schizophrenia patient experienced an increase of QTc interval of 83 milliseconds (ms) after receiving 20 mg IM ziprasidone (baseline and increased QT/QTc were, respectively, 384/418 and 450/501). This was rated as a probable adverse drug reaction (ADR) by the Liverpool ADR causality assessment tool. A systematic review including all types of trials reporting the effect of IM ziprasidone on the QTc interval prolongation identified 19 trials with a total of 1428 patients. Mean QTc change from baseline to end of each study was -3.7 to 12.8 ms after IM ziprasidone. Four randomized trials (3 of 4 published in Chinese) were used to calculate a meta-analysis of QTc interval prolongation which showed no significant differences between IM ziprasidone and IM haloperidol groups (risk ratio 0.49 to 4.31, 95% confidence interval 0.09 to 19.68, P = 0.06 to 0.41). However, our review included two cases of patients who experienced symptoms probably related to QTc prolongation after IM ziprasidone. Thus, careful screening and close monitoring, including baseline ECG, should be considered in patients receiving IM ziprasidone for the first time
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