A Study Against Colon Cancer Mechanism of Xanthium Sibiricum Herba Based on Computer Simulation and Bioinformatics.

INTRODUCTION: Cancer is one of the leading causes of death worldwide, accounting for nearly one in six deaths in 2020. As a folk medicine, Xanthium sibiricum Herba (XSH) has been used many times in clinical practice for the treatment of various diseases. With the increasing number of cancer patients, there is a clinical need to find effective anti-cancer drugs. AIM: This study aims to explores the bioactivity and the anti-cancer mechanism of XSH. METHODS: In this study, bioinformatics, network pharmacology, molecular docking, molecular dynamics simulation techniques, and apoptosis assay were used to explore the bioactivity and the anti-cancer mechanism of XSH. RESULTS: Finally, seven active ingredients in XSH after the screening were obtained, the two most active compounds were ß-sitosterol and aloe-emodin, and good anti-cancer activity of XSH was predicted. DISCUSSION: Four core targets were obtained from the PPI network map, namely Caspase-3 (CASP3), Transcription factor AP-1 (JUN), Myc proto-oncogene protein (MYC), and cellular tumor antigen p53 (TP53). GO and KEGG analyses showed that the mechanism of XSH anti-cancer is mainly related to the apoptosis process, and the main signaling pathways are enriched in the p53 signaling pathway, Apoptosis, and MAPK signaling. The molecular docking and molecular dynamics simulation results showed that CASP3, JUN, MYC, and TP53 had a high affinity with ß-sitosterol and aloe-emodin. Bioinformatics analyses demonstrated the importance of core targets. Apoptosis assay showed that XSH could significantly promote the apoptosis of cancer cells, and inhibit their proliferation and migration, especially colon cancer cells. CONCLUSION: This study uncovered the main active components, bioactivities, and potential targets of XSH, and further revealed the multi-component, multi-target, and multi-pathway mechanism of XSH for cancer treatment and promoting apoptosis.

The traditional herb Polygonum hydropiper from China: a comprehensive review on phytochemistry, pharmacological activities and applications.

CONTEXT: Polygonum hydropiper L. (Polygonaceae) (PH) is a traditional Chinese traditional medicine with a pungent flavor and mild drug properties. PH is mainly distributed in the channel tropism in the stomach and large intestine. PH has multiple uses and can be used to treat a variety of diseases for a long time. OBJECTIVE: This review summarizes the phytochemical and pharmacological activities, and applications of PH from 1980 to 2022. We also provide suggestions for promoting further research and developing additional applications of PH. METHODS: The data and information on PH from 1980 to 2022 reviewed in this article were obtained from scientific databases, including Science Direct, PubMed, Science Citation Index, SciFinder Scholar (SciFinder), Springer, American Chemical Society (ACS) Publications, and China National Knowledge Infrastructure (CNKI), etc. Some information was obtained from classic literature on traditional Chinese medicines. The search terms were Polygonum hydropiper, phytochemistry compositions of Polygonum hydropiper, pharmacological activities of Polygonum hydropiper, and applications of Polygonum hydropiper. RESULTS: The comprehensive analysis of the literature resulted in 324 compounds being isolated, identified, and reported from PH. Regarding traditional uses, the majority of phytochemical and pharmacological studies have indicated the diverse bioactivities of PH extracts, flavonoids, and volatile oil elements, including antibacterial, antifungal, insecticidal, antioxidant, and anti-inflammatory. CONCLUSIONS: PH has a long history of diversified medicinal uses, some of which have been verified in modern pharmacological studies. Further detailed studies are required to establish scientific and reasonable quality evaluation standards and action mechanisms of active constituents from PH.

[Optimization of polysaccharide extraction from Hippocampus by deep neural network and Box-Behnken design-response surface methodology].

In this paper, the extraction rate of crude polysaccharides and the yield of polysaccharides from Hippocampus served as test indicators. The comprehensive evaluation indicators were assigned by the R language combined with the entropy weight method. The Box-Behnken design-response surface methodology(BBD-RSM) and the deep neural network(DNN) were employed to screen the optimal parameters for the polysaccharide extraction from Hippocampus. These two modeling methods were compared and verified experimentally for the process optimization. This study provides a reference for the industrialization of effective component extraction from Chinese medicinals and achieves the effective combination of modern technology and traditional Chinese medicine.