AI-assisted literature exploration of innovative Chinese medicine formulas.

Objective: Our study provides an innovative approach to exploring herbal formulas that contribute to the promotion of sustainability and biodiversity conservation. We employ data mining, integrating keyword extraction, association rules, and LSTM-based generative models to analyze classical Traditional Chinese Medicine (TCM) texts. We systematically decode classical Chinese medical literature, conduct statistical analyses, and link these historical texts with modern pharmacogenomic references to explore potential alternatives. Methods: We present a novel iterative keyword extraction approach for discerning diverse herbs in historical TCM texts from the Pu-Ji Fang copies. Utilizing association rules, we uncover previously unexplored herb pairs. To bridge classical TCM herbal pairs with modern genetic relationships, we conduct gene-herb searches in PubMed and statistically validate this genetic literature as supporting evidence. We have expanded on the present work by developing a generative language model for suggesting innovative TCM formulations based on textual herb combinations. Results: We collected associations with 7,664 PubMed cross-search entries for gene-herb and 934 for Shenqifuzheng Injection as a positive control. We analyzed 16,384 keyword combinations from Pu-Ji Fang's 426 volumes, employing statistical methods to probe gene-herb associations, focusing on examining differences among the target genes and Pu-Ji Fang herbs. Conclusion: Analyzing Pu-Ji Fang reveals a historical focus on flavor over medicinal aspects in TCM. We extend our work on developing a generative model from classical textual keywords to rapidly produces novel herbal compositions or TCM formulations. This integrated approach enhances our comprehension of TCM by merging ancient text analysis, modern genetic research, and generative modeling.

CCM111 prevents hepatic fibrosis via cooperative inhibition of TGF-ß, Wnt and STAT3 signaling pathways.

CCM111 is an aqueous extract of Antrodia cinnamomea (AC) that has exhibited anti-liver fibrosis functions. However, the detailed mechanisms of AC action against liver fibrosis have not been elucidated yet. The present research showed that CCM111 significantly lowered the levels of the hepatic enzyme markers glutamate oxaloacetate transaminase (GOT) and glutamic pyruvic transaminase (GPT), prevented liver damage and collagen deposition, and downregulated TGF-ß/Smad signaling in a dose-dependent manner compared with CCl4 treatment alone. CCM111 markedly inhibited TGF-ß, Wnt and STAT3 signaling pathway-regulated downstream genes in the liver by next-generation sequencing. The antifibrotic mechanisms of CCM111 were further demonstrated in HSC-T6 cells. Our data demonstrated for the first time that CCM111 can protect against CCl4-induced liver fibrosis by the cooperative inhibition of TGF-ß-, Wnt- and STAT3-dependent proinflammatory and profibrotic mediators, suggesting that CCM111 might be a candidate for preventing and treating chronic fibrotic liver diseases.