TCMSSD: A comprehensive database focused on syndrome standardization.

BACKGROUD: Quantitative and standardized research on syndrome differentiation has always been at the forefront of modernizing Traditional Chinese Medicine (TCM) theory. However, the majority of existing databases primarily concentrate on the network pharmacology of herbal prescriptions, and there are limited databases specifically dedicated to TCM syndrome differentiation. PURPOSE: In response to this gap, we have developed the Traditional Chinese Medical Syndrome Standardization Database (TCMSSD, http://tcmssd.ratcm.cn). METHODS: TCMSSD is a comprehensive database that gathers data from various sources, including TCM literature such as TCM Syndrome Studies (Zhong Yi Zheng Hou Xue) and TCM Internal Medicine (Zhong Yi Nei Ke Xue) and various public databases such as TCMID and ETCM. In our study, we employ a deep learning approach to construct the knowledge graph and utilize the BM25 algorithm for syndrome prediction. RESULTS: The TCMSSD integrates the essence of TCM with the modern medical system, providing a comprehensive collection of information related to TCM. It includes 624 syndromes, 133,518 prescriptions, 8,073 diseases (including 1,843 TCM-specific diseases), 8,259 Chinese herbal medicines, 43,413 ingredients, 17,602 targets, and 8,182 drugs. By analyzing input data and comparing it with the patterns and characteristics recorded in the database, the syndrome prediction tool generates predictions based on established correlations and patterns. CONCLUSION: The TCMSSD fills the gap in existing databases by providing a comprehensive resource for quantitative and standardized research on TCM syndrome differentiation and laid the foundation for research on the biological basis of syndromes.

Reporting guidelines for traditional Chinese medicine could be improved: a cross-sectional study.

OBJECTIVES: The aim of this study is to identify available reporting guidelines for traditional Chinese medicine (TCM), delineate their fundamental characteristics, assess the scientific rigor of their development process, and evaluate their dissemination. STUDY DESIGN AND SETTING: A search was conducted in Medline (via PubMed), China National Knowledge Infrastructure (CNKI), SinoMed, WANFANG DATA, and the EQUATOR Network to identify TCM reporting guidelines. A preprepared Excel database was used to extract information on the basic characteristics, development process, and dissemination information. The development process quality of TCM reporting guidelines was assessed by evaluating their compliance with the Guidance for Developers of Health Research Reporting Guidelines (GDHRRG). The extent of dissemination of these guidelines was analyzed by examining the number of citations received. RESULTS: A total of 26 reporting guidelines for TCM were obtained from 20 academic journals, with 61.5% of them published in English journals. Among the guidelines, 14 (53.8%) were registered in the EQUATOR Network. On average, the compliance rate of GDHRRG guidelines was reported to be 63.3% ranging from 22.2% to 94.4%. Three steps showed poor compliance, namely guideline endorsement (23.1%), translated guidelines (19.2%), and developing a publication strategy (19.2%). Furthermore, the compliance rate of GDHRRG guidelines published in English journals was higher than that in Chinese journals. In terms of the dissemination, 15.4% of the guidelines had been cited over 100 times, while 73.1% had been cited less than 50 times. CONCLUSION: The development of TCM reporting guidelines still has limitations in terms of regarding scientific rigor and follow-up dissemination. Therefore, it is important to ensure adherence to the scientific process in the development of TCM reporting guidelines and to strengthen their promotion, dissemination, and implementation.

Lipidomics Analysis Deepen Understanding the Molecular Mechanisms in a Gouty Model Induced by Combination of MSU Crystals Injection and High-Fat Diet Feeding and the Intervention Mechanisms of Allopurinol.

Background: Gouty arthritis (GA) is a common inflammatory disease caused by deposition of monosodium urate (MSU) crystals in diarthrodial joints. GA attacks commonly involved in joint with red, swollen, heat and pain, and often happened in unilateral foot-first metatarsophalangeal. Accumulated studies have proved that lipids play critical roles in biological processes and lipids biomarkers can substitute for the diagnosis of various diseases. Methods: Herein, shotgun lipidomics was used to quantitatively analyze serum lipidomes of a gouty model which was induced by injecting MSU crystals and feeding high-fat diet with/without treatment with allopurinol. Meanwhile, ELISA kit was used to detect mouse serum levels of inflammatory cytokines (eg, tumor necrosis factor-α, interleukin 1 beta) and HE staining was used to observe the infiltration of inflammatory cells in the foot pad. Results: A total of 9 types of serum lipids were detected in lipidomics by shotguns, and the result of NMDS' analysis demonstrated significant differences in lipids profiles between the control and model group. It is worth noting that lipid abnormality in GA (such as Ceramide (Cer), sphingomyelin (SM), 4-hydroxyalkenals (HNE), phosphatidylinositol (PI), ethanolamine glycerophospholipid (PE), etc.) is related with phospholipid and energy metabolism, and allopurinol treatment could correct the aberrant metabolism of lipid to some extent. Conclusion: Our results indicated that various aberrant lipid metabolisms were present in the established gouty model, and allopurinol treatment could relief this aberrant metabolism of lipids to some degree.