Publications by authors named "Xinyu Xing"

Objectives: To observe the effect of electroacupuncture (EA) at "Neiguan"(PC6) on cardiac function, cardiac morphology and transient receptor potential channel (TRPC) protein expressions in myocardial tissue of mice with myocardial hypertrophy, so as to explore its mechanisms underlying improvement of myocardial hypertrophy.

Methods: Forty-five male C57BL/6 mice were randomly divided into control, model and EA groups (15 mice/group). The myocardial hypertrophy model was established by subcutaneous injection of isoproterenol hydrochloride (15 mg·kg·d) for 14 days.

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How to repair dentin-pulp injury effectively has always been a clinical problem, and the comparative study of repair process between different injuries is unknown. Dental pulp stem cells (DPSCs) often are selected as seed cells for the study of dentin-pulp injury repair due to excellent advantages in odontogenesis and pulp differentiation. Although many previous researches have indicated that the Wnt protein and Wnt/β-catenin signaling pathway were crucial for dental growth, development, and injury repair, the specific mechanism remained unknown.

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Influences of Glycyrrhetinic acid on expression of inflammatory factors in interleukin (IL)-1β-induced SW982 cells and its anti-inflammatory effects were discussed in this study. MTT results showed that Glycyrrhetinic acid (≤80 μmol·L-1) almost has no toxicity on SW982 cells. The results of ELISA and real-time PCR showed that Glycyrrhetinic acid (10, 20 and 40 μmol · L-1) can significantly inhibit the expression of inflammatory factors such as IL-6, IL-8 and matrix metalloproteinase-1 (MMP-1).

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This study investigated the seasonal characterization of dissolved organic matter (DOM) in reclaimed wastewater (RW) with a special focus on dissolved organic nitrogen (DON) from two full-scale municipal wastewater reclamation plants (WRPs) where the produced RW was used to augment urban rivers. Results showed that the concentrations of DON in RW ranged from 0.32 mg/L to 1.

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Oxidation of magnesium sulfite (MgSO) is a crucial step for reclaiming the product in wet magnesia desulfurization processes. Here, for enhancing this reaction, a bimetallic catalyst was developed by loading CoO and MnO species on a biomass-derived active carbon (AC) support to minimize the costs and potential environmental risks during catalyst application. The substitution effect of Mn to Co sites was investigated, and a comparison of the catalyst with plain cobalt suggested that the ratio of Co/Mn must be greater than 3.

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Rule extraction from black box models is critical in domains that require model validation before implementation, as can be the case in credit scoring and medical diagnosis. Though already a challenging problem in statistical learning in general, the difficulty is even greater when highly nonlinear, recursive models, such as recurrent neural networks (RNNs), are fit to data. Here, we study the extraction of rules from second-order RNNs trained to recognize the Tomita grammars.

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