Potential Chemoprevention of Paeoniflorin in Colitis-Associated Colorectal Cancer by Network Pharmacology, Molecular Docking, and In Vivo Experiment.

Chronic inflammation plays a positive role in the development and progression of colitis-associated colorectal cancer (CAC). Medicinal plants and their extracts with anti-inflammatory and immunoregulatory properties may be an effective treatment and prevention strategy for CAC. This research aimed to explore the potential chemoprevention of paeoniflorin (PF) for CAC by network pharmacology, molecular docking technology, and in vivo experiments. The results showed that interleukin-6 (IL-6) is a key target of PF against CAC. In the CAC mouse model, PF increased the survival rate of mice and decreased the number and size of colon tumors. Moreover, reduced histological score of colitis and expression of Ki-67 and PCNA were observed in PF-treated mice. In addition, the chemoprevention mechanisms of PF in CAC may be associated with suppression of the IL-6/STAT3 signaling pathway and the IL-17 level. This research provides experimental evidence of potential chemoprevention strategies for CAC treatment.

Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility.

AIMS: As one of the most fundamental questions in modern science, "what causes schizophrenia (SZ)" remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies is found to be extremely low due to the incapability of available feature selection methods and the lack of measurement on validating signatures' robustness. These irreproducible results have significantly limited our understanding of the etiology of SZ. METHODS: In this study, a new feature selection strategy was developed, and a comprehensive analysis was then conducted to ensure a reliable signature discovery. Particularly, the new strategy (a) combined multiple randomized sampling with consensus scoring and (b) assessed gene ranking consistency among different datasets, and a comprehensive analysis among nine independent studies was conducted. RESULTS: Based on a first-ever evaluation of methods' reproducibility that was cross-validated by nine independent studies, the newly developed strategy was found to be superior to the traditional ones. As a result, 33 genes were consistently identified from multiple datasets by the new strategy as differentially expressed, which might facilitate our understanding of the mechanism underlying the etiology of SZ. CONCLUSION: A new strategy capable of enhancing the reproducibility of feature selection in current SZ research was successfully constructed and validated. A group of candidate genes identified in this study should be considered as great potential for revealing the etiology of SZ.