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Background: Vascular dementia (VaD) is a degenerative cerebrovascular disease that leads to progressive decline of patients' cognitive ability and memory. Yizhi Tongmai (YZTM) decoction is an empirical prescription first formulated by Professor Guomin Si. Our previous experiments proved the effectiveness of this prescription in the treatment of VaD. In this study, we aimed to use network pharmacology and molecular docking technology to systematically explain the potential anti-VaD mechanism of YZTM.Methods: We identified the core compounds of YZTM and their potential targets through the TCMSP, BATMAN, and SwissTargetPrediction databases. Then, we identified the molecular targets of YZTM in VaD using the Online Mendelian Inheritance in Man and GeneCards databases. The common targets of YZTM and VaD were screened out, and then the pathways of these target genes were analyzed using the Database for Annotation, Visualization and Integrated Discovery v6.8. Molecular docking was used to verify the relationship between the core compounds and proteins.Results: Through network pharmacology analysis, we discovered that the 5 core compounds in YZTM exert an anti-VaD effect. The potential mechanism of YZTM anti-VaD may be through inhibiting the NLRP3 inflammasome, TNF signaling pathway, and toll-like receptor signaling pathways. Subsequently, key compounds were docked with related proteins in the NLRP3 inflammasome (NLRP3, ASC, caspase-1, interleukin-18, and interleukin-1 β) using molecular docking technology. The compounds were found to spontaneously bind to the proteins.Conclusions: YZTM may exert an anti-VaD effect through inhibition of the NLRP3 inflammasome.In addition, TNF signaling pathway and toll-like receptor signaling pathway may also be its underlying mechanism. The application of network pharmacology and molecular docking technology may provide a novel method for research of Chinese herbal medicine. YZTM may also provide a complementary treatment option for patients with VaD

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Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and factor analysis (FA), were used to evaluate temporal and spatial variations in and to interpret large and complex water quality datasets collected from the Shuangji River Basin. The datasets, which contained 19 parameters, were generated during the 2 year (2018–2020) monitoring programme at 14 different sites (3192 observations) along the river. Hierarchical CA was used to divide the twelve months into three periods and the fourteen sampling sites into three groups. Discriminant analysis identified four parameters (CODMn, Cu, As, Se) loading more than 68% correct assignations in temporal analysis, while seven parameters (COD, TP, CODMn, F, LAS, Cu and Cd) to load 93% correct assignations in spatial analysis. The FA/PCA identified six factors that were responsible for explaining the data structure of 68% of the total variance of the dataset, allowing grouping of selected parameters based on common characteristics and assessing the incidence of overall change in each group. This study proposes the necessity and practicality of multivariate statistical techniques for evaluating and interpreting large and complex data sets, with a view to obtaining better information about water quality and the design of monitoring networks to effectively manage water resources.

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Background: Western medicine has played an essential role in treating poststroke insomnia (PSI) in China, and traditional Chinese medicine therapy based on Chinese characteristics is also effective. Combined with China's national conditions, we plan to conduct this systematic review and meta-analysis to compare the efficacy of integrated traditional Chinese medicine and Western medicine (INTEGRATED TCM and WM) therapy and Western medicine alone for PSI. Methods: We will search the following 5 electronic databases: PubMed, Wanfang, Chinese biomedical literature database, the Chongqing VIP Chinese Science and Technology Periodical, and China national knowledge infrastructure. Randomized controlled trials that compared the efficacy of INTEGRATED TCM and WM with Western medicine alone in the treatment of PSI will be considered. Primary outcomes have Treatment effectiveness rate, and Pittsburgh sleep quality index. Secondary outcomes include traditional Chinese medicine syndrome score, Athens insomnia scale, the incidence of adverse reactions, and outcome follow-up. Based on the eligibility criteria, we will conduct literature screening and data extraction. The quality of the included literature will be evaluated using the Cochrane risk of bias tools. We will use Review Manager software (Version 5.3) for data synthesis and statistical analyses. If sources of heterogeneity exist, we will perform a subgroup analysis or sensitivity analysis. A funnel plot will be used to analyze publication bias. Results: This study will provide evidence-based medicine evidence for treatment of PSI with INTEGRATED TCM and WM in terms of its efficacy. Conclusion: This systematic review aims to provide new options for INTEGRATED TCM and WM treatment of PSI in terms of its efficacy.

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