Huangqi Guizhi Wuwu decoction in peripheral neurotoxicity treatment using network pharmacology and molecular docking.

In this study, we predicted the core active compounds of Huangqi Guizhi Wuwu decoction in treatment of oxaliplatin-induced peripheral neuropathy and the related potential mechanism. Corresponding database was used to complete the interaction (PPI) network of key targets and the enrichment analysis of corresponding genmes. Molecular docking of key targets and key compounds was carried out using relevant software. The 60 chemical components corresponding to the oral absorption of Huangqi Guizhi Wuwu decoction correspond to 157 unique targets, and the 233 chemical components corresponding to percutaneous absorption in vitro correspond to 155 unique targets. There were 1074 unique targets for chemotherapy-induced peripheral neuropathy. Finally, three common key targets (SLC6A2, SLC6A3, and SLC6A4) and two key compounds (6-Gingerol and nuciferin) were screened according to the above three target datasets. The results showed that The PPI network of common key targets involved 23 associated proteins. In the related GO enrichment results, there were 33 items related to biological processes, 13 items related to cell composition, 21 items related to molecular function, and four KEGG pathway enrichments. L1000 kinase and GPCR perturbation analysis showed that the associated protein had an effect on the expression of multiple groups of kinase genes. HPA revealed that the enrichment of three common key targets was tissue-specific. The docking results showed that the 6 groups were structurally stable. The oral and topical use of Huangqi Guizhi Wuwu decoction can prevent and control peripheral neurotoxicity. The prevention and control effects may be related to its participation in the regulation of neurotransmitter transport, sympathetic activity, and transport. The histological parts of the mechanism are mainly distributed in the adrenal gland, placenta, brain, intestine, and lung, the blood is not specific. According to the prediction results of molecular docking, 6-Gingerol and nuciferin can closely bind to three common key targets.

Cost-effectiveness of human papillomavirus vaccine in China: a systematic review of modelling studies.

OBJECTIVES: China suffers from high burdens of human papillomavirus (HPV) and cervical cancer, whereas the uptake of HPV vaccine remains low. The first Chinese domestic HPV vaccine was released in 2019. However, collective evidence on cost-effectiveness of HPV vaccination in China has yet to be established. We summarised evidence on the cost-effectiveness of HPV vaccine in China. DESIGN: Systematic review and narrative synthesis DATA SOURCES: PubMed, EMBASE, China National Knowledge Infrastructure and Wanfang Data were searched through 2 January 2021 ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Cost-effectiveness studies using a modelling approach focusing on HPV vaccination interventions in the setting of China were included for review. DATA EXTRACTION AND SYNTHESIS: We extracted information from the selected studies focusing on cost-effectiveness results of various vaccination programmes, key contextual and methodological factors influencing cost-effectiveness estimates and an assessment of study quality. RESULTS: A total of 14 studies were included for review. Considerable heterogeneity was found in terms of the methodologies used, HPV vaccination strategies evaluated and study quality. The reviewed studies generally supported the cost-effectiveness of HPV vaccine in China, although some reached alternative conclusions, particularly when assessed incremental to cervical cancer screening. Cost of vaccination was consistently identified as a key determinant for the cost-effectiveness of HPV vaccination programmes. CONCLUSIONS: Implementing HPV vaccination programmes should be complemented with expanded cervical cancer screening, while the release of lower-priced domestic vaccine offers more promising potential for initiating public HPV vaccination programmes. Findings of this study contributes important evidence for policies for cervical cancer prevention in China and methodological implications for future modelling efforts.

Extracting user influence from ratings and trust for rating prediction in recommendations.

The Collaborative Filtering (CF) algorithm based on trust has been the main method used to solve the cold start problem in Recommendation Systems (RSs) for the past few years. Nevertheless, the current trust-based CF algorithm ignores the implicit influence contained in the ratings and trust data. In this paper, we propose a new rating prediction model named the Rating-Trust-based Recommendation Model (RTRM) to explore the influence of internal factors among the users. The proposed user internal factors include the user reliability and popularity. The internal factors derived from the explicit behavior data (ratings and trust), which can help us understand the user better and model the user more accurately. In addition, we incorporate the proposed internal factors into the Singular Value Decomposition Plus Plus (SVD + +) model to perform the rating prediction task. Experimental studies on two common datasets show that utilizing ratings and trust data simultaneously to mine the factors that influence the relationships among different users can improve the accuracy of rating prediction and effectively relieve the cold start problem.