Modular characteristics and the mechanism of Chinese medicine's treatment of gastric cancer: a data mining and pharmacology-based identification

Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review

Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

Quality Consistency Evaluation of Traditional Chinese Medicines: Current Status and Future Perspectives

Quality consistency evaluation of traditional Chinese medicines (TCMs) is a crucial factor that determines the safe and effective application in clinical settings. However, TCMs exhibit diverse, heterogeneous, complex, and flexible chemical compositions, as well as variability in preparation processes. These characteristics pose greater challenges in researching the consistency of TCMs compared to chemically synthesized and biological drugs. Therefore, it is paramount to develop effective strategies for evaluating the quality consistency of TCMs. From the starting point of quality properties, this review explores the strategy used to evaluate quality consistency in terms of chemistry-based strategy (chemical consistency) and the biology-based strategy (bioequivalence). Among them, the chemistry-based strategy is the mainstream, and biology-based strategy complements the chemistry-based strategy each other. Furthermore, the emerging chemistry-biology strategies (overall evaluation) is discussed, including individually combining strategy and integration strategy. Finally, this review provides insights into the challenges and future perspectives in this field. By highlighting current status and trends in TCMs quality consistency, this review aims to contribute to establishment of generally applicable chemistry-biology integrated evaluation strategy for TCMs. This will facilitate the advancement toward a higher stage of overall quality evaluation.

Jianpi Yangzheng decoction suppresses gastric cancer progression via modulating the miR-448/CLDN18.2 mediated YAP/TAZ signaling

ETHNOPHARMACOLOGICAL RELEVANCE

Developing complementary and effective drugs with less toxicity is urgent for gastric cancer (GC) therapy. Jianpi Yangzheng Decoction (JPYZ) is a curative medical plants formula against GC in clinic while its molecular mechanism remains to be further elucidated.

AIM OF THE STUDY

To evaluate the in vitro and in vivo anticancer efficacy of JPYZ against GC and its potential mechanisms.

MATERIALS AND METHODS

The effect of JPYZ on regulating the candidate targets were screened and examined by RNA-Seq, qRT-PCR, luciferase reporter assay, and immunoblotting. Rescue experiment was conducted to authenticate the regulation of JPYZ on the target gene. Molecular interaction, intracellular localization and function of target genes were elucidated via Co-IP and cytoplasmic-nuclear fractionation. The impact of JPYZ on the abundance of target gene in clinical specimens of GC patients was evaluated by IHC.

RESULTS

JPYZ treatment suppressed the proliferation and metastasis of GC cells. RNA seq revealed JPYZ significantly downregulated miR-448. A reporter plasmid containing CLDN18 3'-UTR WT exhibited significant decrease in luciferase activity when co-transfected with miR-448 mimic in GC cells. CLDN18.2 deficiency promoted the proliferation and metastasis of GC cells in vitro, as well as intensified the growth of GC xenograft in mice. JPYZ reduced the proliferation and metastasis of GC cells with CLDN18.2 abrogation. Mechanically, suppressed activities of transcriptional coactivator YAP/TAZ and its downstream targets were observed in GC cells with CLDN18.2 overexpression and those under JPYZ treatment, leading to cytoplasmic retention of phosphorylated YAP at site Ser-127. High abundance of CLDN18.2 was detected in more GC patients who received chemotherapy combined with JPYZ.

CONCLUSION

JPYZ has an inhibitory effect on GC growth and metastasis partly by elevating CLDN18.2 abundance in GC cells, indicating more patients may benefit from combination therapy of JPYZ and the upcoming CLDN18.2 target agents.

An Analysis of the Clinical Medication Rules of Traditional Chinese Medicine for Polycystic Ovary Syndrome Based on Data Mining

Objective

The aim of the present study is to investigate the rules and characteristics of the clinical administration of traditional Chinese medicine (TCM) in the treatment of polycystic ovary syndrome (PCOS) using data mining methods.

Method

Medical cases of well-known contemporary TCM doctors treating PCOS were collected from the China National Knowledge Infrastructure, Chinese Biomedical Literature Service System, Wanfang, Chinese Scientific Journals Database, and PubMed; the data were then characterized, and a standardized database of medical cases was built. This database was used to (1) count the frequency of syndrome types and the herbs used in medical cases by data mining methods and (2) analyze drug association rules and systematic clustering methods.

Results

A total of 330 papers were included, involving 382 patients and a total of 1,427 consultations. The most common syndrome type was kidney deficiency; sputum stasis was the core pathological product and causative factor. A total of 364 herbs were used. Among them, 22 herbs were used >300 times, including Danggui (Angelicae Sinensis Radix), Tusizi (Semen Cuscutae), Fuling (Poria), Xiangfu (Nutgrass Galingale Rhizome), and Baizhu (Atractylodis Macrocephalae Rhizoma). Additionally, 22 binomial associations were obtained from the analysis of association rules; five clustering formulae were obtained via the analysis of high-frequency drug clusters; and 27 core combinations were obtained by k-means clustering of formula.

Conclusion

In the treatment of PCOS, TCM is primarily employed as a combination approach involving tonifying the kidneys, strengthening the spleen, eliminating damp and dissolving phlegm, activating blood circulation, and resolving blood stasis. The core prescription is primarily a compound intervention based on the Cangfu Daotan pill, Liuwei Dihuang pill, and Taohong Siwu decoction.

Deep learning and machine intelligence: New computational modeling techniques for discovery of the combination rules and pharmacodynamic characteristics of Traditional Chinese Medicine

It has been increasingly accepted that Multi-Ingredient-Based interventions provide advantages over single-target therapy for complex diseases. With the growing development of Traditional Chinese Medicine (TCM) and continually being refined of a holistic view, "multi-target" and "multi-pathway" integration characteristics of which are being accepted. However, its effector substances, efficacy targets, especially the combination rules and mechanisms remain unclear, and more powerful strategies to interpret the synergy are urgently needed. Artificial intelligence (AI) and computer vision lead to a rapidly expanding in many fields, including diagnosis and treatment of TCM. AI technology significantly improves the reliability and accuracy of diagnostics, target screening, and new drug research. While all AI techniques are capable of matching models to biological big data, the specific methods are complex and varied. Retrieves literature by the keywords such as "artificial intelligence", "machine learning", "deep learning", "traditional Chinese medicine" and "Chinese medicine". Search the application of computer algorithms of TCM between 2000 and 2021 in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Elsevier and Springer. This review concentrates on the application of computational in herb quality evaluation, drug target discovery, optimized compatibility and medical diagnoses of TCM. We describe the characteristics of biological data for which different AI techniques are applicable, and discuss some of the best data mining methods and the problems faced by deep learning and machine learning methods applied to Chinese medicine.