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47 results on '"Zhang, Lewen"'

7. Progress of Pancreatic Stellate Cells in Research of Pancreatic Disease Model

Author

WEI Xun, JIANG Xia, ZHENG Yuxuan, ZHANG Lewen, and ZHOU Zhengyu

Subjects
animal model, pancreatic stellate cells, pancreatic disease, Medicine
Abstract

Common types of pancreatic diseases are pancreatitis, diabetes and pancreatic cancer. Clinical studies have found that pancreatic stellate cells (PSCs) in patients with pancreatic diseases, contributes to fibrosis, oxidative stress and inflammation, and lead to pancreatic diseases. This article reviewed the modeling methods of different pancreatic diseases, and the influence and application prospects of PSCs in pancreatic diseases, providing a new idea for the research and treatment of pancreatic diseases.

Published
2022
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8. 1,25(OH)2D3 inhibits pancreatic stellate cells activation and promotes insulin secretion in T2DM.

Author

Zhou, Zhengyu, Zhang, Lewen, Wei, Xun, Wang, Aiqing, Hu, Yudie, Xiao, Min, and Zheng, Yuxuan

Abstract

Purpose: To evaluate the effect and mechanism of 1,25(OH)2D3 on pancreatic stellate cells (PSCs) in type 2 diabetes mellitus (T2DM). Methods: A mouse model of T2DM was successfully established by high-fat diet (HFD) /streptozotocin (STZ) and administered 1,25(OH)2D3 for 3 weeks. Fasting blood glucose (FBG), glycated hemoglobin A1c (GHbA1c), insulin (INS) and glucose tolerance were measured. Histopathology changes and fibrosis of pancreas were examined by hematoxylin and eosin staining and Masson staining. Mouse PSCs were extracted, co-cultured with mouse insulinoma β cells (MIN6 cells) and treated with 1,25(OH)2D3. ELISA detection of inflammatory factor expression. Tissue reactive oxygen species (ROS) levels were also measured. Immunofluorescence or Western blotting were used to measure fibrosis and inflammation-related protein expression. Results: PSCs activation and islets fibrosis in T2DM mice. Elevated blood glucose was accompanied by significant increases in serum inflammatory cytokines and tissue ROS levels. 1,25(OH)2D3 attenuated islet fibrosis by reducing hyperglycemia, ROS levels, and inflammatory factors expression. Additionally, the co-culture system confirmed that 1,25(OH)2D3 inhibited PSCs activation, reduced the secretion of pro-inflammatory cytokines, down-regulated the expression of fibrosis and inflammation-related proteins, and promoted insulin secretion. Conclusion: Our findings identify that PSCs activation contributes to islet fibrosis and β-cell dysfunction. 1,25(OH)2D3 exerts beneficial effects on T2DM potentially by inhibiting PSCs activation and inflammatory response, highlighting promising control strategies of T2DM by vitamin D. Highlights: PSCs activation leads to islet fibrosis in T2DM mice. TGF- β, IL-1 β, TNF-α, ROS induce PSCs activation, thereby inhibiting MIN6 cell proliferation and function. 1,25(OH)2D3 inhibits PSCs activation by downregulating the expression of factors such as TGF-β, protecting β cell function. [ABSTRACT FROM AUTHOR]

Published
2024
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22. 1,25(OH)2D3inhibits pancreatic stellate cells activation and promotes insulin secretion in T2DM

Author

Zhou, Zhengyu, Zhang, Lewen, Wei, Xun, Wang, Aiqing, Hu, Yudie, Xiao, Min, and Zheng, Yuxuan

Abstract

PSCs activation leads to islet fibrosis in T2DM mice.TGF- β, IL-1 β, TNF-α, ROS induce PSCs activation, thereby inhibiting MIN6 cell proliferation and function.1,25(OH)2D3inhibits PSCs activation by downregulating the expression of factors such as TGF-β, protecting β cell function.

Published
2024
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28. Highly efficient flame‐retardant and transparent epoxy resin

Author

Wang Qiwei, Deng Jingjing, Zhang Lewen, Deng Weihao, Liao Wang, Chen Ming-Jun, Zhong Liu, Wang Rong, Zhang Kaixin, Zhao Yu, Tang Qiaolin, Liu Zhi-guo, and Chen Jin

Subjects
Materials science, Polymers and Plastics, visual_art, visual_art.visual_art_medium, Epoxy, Composite material, Fire retardant
Published
2021

38. Characterization of shallow karst using electrical resistivity imaging in a limestone mining area

Author

Ming Cheng, Kai Li, Sun Huaifeng, Maoxin Su, Su Chuanxi, Zhang Bo, Shu Cai Li, Zhang Lewen, Zhao Guodong, and Li Haiyan

Subjects
Global and Planetary Change, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Soil Science, Drilling, Geology, 010502 geochemistry & geophysics, Karst, 01 natural sciences, Pollution, Mining engineering, Fracture (geology), Erosion, Environmental Chemistry, Carbonate rock, Sedimentary rock, Electrical resistivity tomography, Geomorphology, Groundwater, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology
Abstract

The Guangxi area is famous for its high degree of karstification due to a long period of groundwater erosion and the development of fracture networks. Karst collapse appeared during the mining process and caused many environmental problems. Applying electrical resistivity imaging (ERI) is the most cost-effective method to study the characteristic of the subsurface karst environment. In this area, more than 24 km of ERI profiles around a mining area is carried out to present the development of karst which will be used to evaluate the effects on the ground water and the surrounding environment. The area represents a classical limestone rock which is of high quality and is used for cement production. In this study, the ERI is used to determine the geometry of the karst range at depth. The results are in good agreement with drilling experiments. The ERI survey provided near-surface resistivity information, which is very useful for establishing the geometry and the position of potential karst.

Published
2017

41. Manganese-Based Nanoactivator Optimizes Cancer Immunotherapy viaEnhancing Innate Immunity

Author

Hou, Lin, Tian, Chunyu, Yan, Yingshan, Zhang, Lewen, Zhang, Huijuan, and Zhang, Zhenzhong

Abstract

Cyclic GMP-AMP synthase (cGAS) and stimulator of interferon genes (STING) are essential components of the innate immune sensors to cytosolic DNA and elicit type I interferon (IFN). Recent studies have revealed that manganese (Mn) can enhance cGAS and STING activation to viral infection. However, the role of Mn in antitumor immunity has not been explored. Here, we designed a nanoactivator, which can induce the presence of DNA in cytoplasm and simultaneously elevate Mn2+accumulation within tumor cells. In detail, amorphous porous manganese phosphate (APMP) NPs that are highly responsive to tumor microenvironment were employed to construct doxorubicin (DOX)-loaded and phospholipid (PL)-coated hybrid nanoparticles (PL/APMP-DOX NPs). PL/APMP-DOX NPs were stably maintained during systemic circulation, but triggered to release DOX for inducing DNA damage and Mn2+to augment cGAS/STING activity. We found that PL/APMP-DOX NPs with superior tumor-targeting capacity boosted dendritic cell maturation and increased cytotoxic T lymphocyte infiltration as well as natural killer cell recruitment into the tumor site. Furthermore, the NPs increased production of type I IFN and secretion of pro-inflammatory cytokines (for example, TNF-α and IL-6). Consequently, PL/APMP-DOX NPs exhibited excellent antitumor efficacy and prolonged the lifespan of the tumor-bearing mice. Collectively, we developed a PL-decorated Mn-based hybrid nanoactivator to intensify immune activation and that might provide therapeutic potential for caner immunotherapy.

Published
2020
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42. Identifying Prestress Loss of Long Span Bridge Based on Genetic Algorithm Combined with Neural Network

Author

Liu Jianxin, Wang Ying, Zhang Lewen, and Zhao Ren-da

Subjects
Artificial neural network, Computer science, business.industry, Subroutine, Genetic algorithm, Process (computing), Computational intelligence, Artificial intelligence, business, Algorithm, Bridge (interpersonal), Backpropagation, Field (computer science)
Abstract

In recent years, computational intelligence methods are widely used to solve problems in engineering structural field by more and more researchers. In this paper, a method based on combining artificial neural networks (ANN) and genetic algorithm (GA) in identifying the prestress loss of the long span bridge was proposed. A model with some parameters was constructed to access the prestress loss. Based on the differences of the bridge deck elevation of the long span bridge in service between damaged structure and intact structure, the model parameters were identified by the genetic algorithm, and the prestress loss values of different time were obtained. At the same time, the differences of responses were constructed within BP neural networks. In fact, the trained BP neural networks were used as a subroutine in the process of identification using GA. It is demonstrated that the method combining BP neural networks with GA of identification for prestress loss is efficient and the identified results fit well with the actual value.

Published
2009

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