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        Hypoglycemic and Antioxidant Activities of Paeonol and Its Beneficial Effect on Diabetic Encephalopathy in Streptozotocin-Induced Diabetic Rats

        Jiping Liu,Shuyuan Wang,Liang Feng,Dongying Ma,Qiang Fu,Yu Song,Xiaobin Jia,Shiping Ma 한국식품영양과학회 2013 Journal of medicinal food Vol.16 No.7

        Diabetic encephalopathy (DE) is one of the severe complications in patients with diabetes mellitus. Paeonol, an active compound isolated from the root bark of Paeonia suffruticosa, has significant antidiabetic activity in vivo. However, its underlying beneficial effects on DE were unclear. In the present study, the protective activity of paeonol on DE was evaluated in streptozotocin (STZ)-induced diabetic rats. Paeonol at 50 and 100mg/kg significantly increased body weight and decreased blood glucose levels, glycosylated serum proteins, and serum advanced glycation end products (AGEs) levels. Immunohistochemistry assays and Western blot analysis revealed a significant decrease in expressions on receptor for advanced glycation end products (RAGE) and nuclear factor kappa B (NF-jB) in hippocampus and cerebral cortical neurons after paeonol treatment. Furthermore, paeonol significantly increased glutathione content and remarkedly decreased induced nitric oxide synthase activity in hippocampus tissue. Our findings indicated that paeonol could improve the pathological damage of DE in STZ-induced diabetic rats. It might be associated with the modulating AGEs/RAGE/NF-jB pathway. This study suggested that paeonol might be a promising candidate for the prevention and treatment of DE.

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        RESEARCH ON MILLIMETER WAVE RADAR SIMULATION MODEL FOR INTELLIGENT VEHICLE

        Xin Li,Weiwen Deng,Sumin Zhang,Yaxin Li,Shiping Song,Shanshan Wang,Guanyu Wang 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.2

        Radar simulation models can effectively overcome the drawbacks of real vehicle experiment and speed up the development process of intelligent vehicle technologies based on millimeter wave radar via virtual testing. However, there are still many gaps between the radar model using in the virtual driving environment and the real radar. In this paper, a novel simulation model of intelligent vehicle millimeter wave radar is proposed. Based on the analysis of the real radar performance in typical application scenes, the radar model considers the mechanism and characteristics of the vehicle radar synthetically and a systematic radar modeling architecture with innovation is introduced. The highlights of this radar model include the design of the RCS simulation model for radar targets with both high accuracy and real-time performance, the establishment of the quantitative false alarm model, missed detection model and measurement error simulation model. Vast amounts of data collected by real vehicle radar are applied to fetch model parameters and verify the accuracy of the radar model. Simulation results show that the proposed model can reach both high reliability and computational efficiency.

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