Astragalin improves cognitive disorder in Alzheimer's disease: Based on network pharmacology and molecular docking simulation.

We investigate the mechanism of action of astragalin (AST) in the treatment of Alzheimer's disease (AD). Network pharmacology was conducted to analyze the relationships among AST, AD, and neuroinflammation, The APP/PS1 transgenic mice with AD were used in the experiments; to be specific, the influence of AST on the behavior of mice was analyzed by Morris water maze and eight-arm radial maze tests, the tissue inflammatory factor levels were detected by ELISA, and pathological changes were analyzed by H&E and immunohistochemical staining. Analysis results of network pharmacology suggested that AST exerted the multi-target effect on neuroinflammation in AD. Through molecular docking and dynamics analyses, COX2 might be the target of AST. Moreover, animal experimental results demonstrated that AST improved the behavior of AD mice, and enhanced the motor and memory abilities, meanwhile, it suppressed the expression of inflammatory factors in tissues and the activation of microglial cells. this study discovers that AST can suppress microglial cell activation via COX2 to improve neuroinflammation in AD.

High-density volatile organic compound monitoring network for identifying pollution sources.

The elusive sources of air pollution have hampered effective control across all sectors, with long-term consequences for the greenhouse effect and human health. Multiple monitoring systems have been highly desired for locating the sources. However, when faced with extensive sources, diverse air environments and meteorological conditions, the low spatiotemporal resolution, poor reliability and high cost of existing monitors were significant obstacles to their applications. Extending our previous demonstration of sensitive and reliable electrochemical sensors, we here present a machine-learning-assisted sensor arrays for monitoring typical volatile organic compounds (VOCs), which shows the consistent response with gas chromatography-mass spectrometry in the actual air environment. As a proof-of-concept, a low-cost and high-resolution VOC network of 152 sets of monitors across ~55 km2 of mixed-used land is established in southwest Beijing. Benefiting from the strong reliability, the pollution sources are revealed by the VOC network and supported by the joint mobile sampling of a vehicle-mounted gas chromatography-mass spectrometry system. With the sustained help of the network, the sources polluted by the local industrial facilities, traffic, and restaurants are effectively site-specific abatement by the local authorities and enterprises during the next half-year. Our findings open up a promising path toward more effective tracing of regional pollution sources, as well as accelerate the long-term transformation of industry and cities.