Compatibility Rules of Prescriptions of Tibetan Medicine Polygonatum cirrhifolium Based on Data Mining

[Objectives]To study the prescription compatibility rules of the Tibetan medicine Polygonatum cirrhifolium(Polygonati Rhizoma,Huangjing)based on data mining,so as to provide data support for clinical application and new drug development.[Methods]Prescriptions containing Tibetan medicine Huangjing were collected from Tibetan Medicine Prescriptions Encyclopedia and Tibetan Medicine Classic Literature Collection.The Traditional Chinese Medicine Inheritance Computing System(TCMICS 3.0)and R version 4.1.3 were used to mine and analyze the compatibility rules of prescriptions containing Tibetan medicinal material Huangjing,the rules of medication for high-frequency diseases,and the association rules of various medicinal materials.[Results]A total of 124 prescriptions were collected from the classic literature of Tibetan medicine,and the frequency statistical analysis showed that drugs compatible with Huangjing(≥15)included Tianmendong(Root of Cochinchinese Asparagus)(80),Mirabilis himalaica(Edgew.)Heimerl(Himalayan purple jasmine)(72),Jili(Tribuli Fructus)(70),Tibetan Aoruqin(Vicatia coniifolia)(58),Baidoukou(Round Cardamom Fruit)(47),Hezi(Chebulae Fructus)(45),Shouzhangshen(Rhizome of Conic Gymnadenia)(28),Yuganzi(Phyllanthi Fructus)(26),Pomegranate(25),Maohezi(Terminaliae Belliricae Fructus)(24),Zicaorong(Lacca)(23),Rougui(Cinnamomi Cortex)(15).The main diseases were yellow water disease(20),gynecological diseases(19),kidney cold disease(17),and other Tibetan medicine diseases.Association rule analysis showed that the drug combinations with the highest frequency were Huangjing—Tianmendong,Huangjing—Himalayan purple jasmine,and Huangjing—Jili.[Conclusions]The frequency of combined use of Tibetan medicine Huangjing with dry yellow water,tonifying kidney and diuresis,nourishing health,and treating gynecological diseases is relatively high.

Analysis of compatibility rules and mechanisms of traditional Chinese medicine for preventing and treating postoperative recurrence of bladder cancer

Backgroud:Summarize the formula rule of traditional Chinese medicine fOr preventing and treating bladder cancer recurrence after operation and explore the molecular mechanism of core medicines.Methods:Literatures collected from CNKI,Wanfang Med Online,CMJD,PUBMED and Elsiver databases were as prescription sources,and association rules and complex system entropy clustering analysis were carried out using the Traditional Chinese Medicine Inheritance Support System(TCMISSV2.5).BATMAN-TCM online analysis tool was used to construct target-pathway-disease correlation map to reveal the potential mechanism of action.Results:A total of 122 prescriptions were eligible for data analysis.The high-frequency traditional Chinese medicines are Poria,Radix et Rhizoma Rhei,Radix Astragali,Herba Hedyotidis Diffusae and Rhizoma Atractylodis Macrocephalae.The high-frequency drug pairs are Rhizoma Atractylodis MacrocephalaeIPoria,Poria/Rhizoma Alismatis,Radix Astragali/Rhizoma Atractylodis Macrocephalaeand and Herba Hedyotidis Diffusae/Herba Scutellariae Darbatae..There are 5 groups of drug pairs with high correlation strength.Cluster analysis shows 6 core drug combinations and 3 new prescriptions.In clinical practice,the core compatibility of traditional Chinese medicines for preventing postoperative recurrence of bladder cancer is Poria,Radix Astragali and Herba Hedyotidis Diffusae.The possible signaling pathways are the neuroactive ligand receptor interaction signaling pathway and calcium signaling pathway.Conclusion:Prevention and treatment of postoperative recurrence of bladder cancer mainly use medicines with effects of eliminating dampness and diuresis for removing edema,heat-clearing and detoxifying,and qi-invigorating.The potential mechanism of the compatibility of core drugs may be realized by interfering with the signal pathway of neuroactive ligand receptor interaction and calcium signal pathway.

Compatibility mechanism of Chinese medicine formula:state of the art and perspectives

Traditional Chinese medicine(TCM)has been practiced in China and surrounding countries for thousands of years and has gradually attracted the attention of Western countries.After reasonable compatibility,TCMs could play the key role of enhancing efficacy and reducing toxicity,which has significant therapeutic advantages in the treatment of complex diseases in clinical practice.While the TCM compatibility is not the simple addition of drugs.Under the appropriate dosage ratio,multiple TCMs can play a synergistic role to realize the overall regulation of TCM treatment.Therefore,it is of critical essential to study the compatibility of TCM formula to promote TCM modernization,new drug development and clinical application.Recently,under the guidance of TCM theory,many researches on the composition,pharmacodynamic activity and pharmacokinetic properties of TCM formula have emerged by integrating new technologies and new methods,revealing the scientific connotation of the compatibility of TCM formula from different perspectives and levels.This paper introduces the research progress of compatibility rules from different levels of compatibility,compatibility for synergistic enhancement and detoxification,and application of cutting-edge technology,with representative cases,in order to provide ideas and references for further study on TCM compatibility.

Research on Herb Pairs of Classical Formulae of ZHANG ZhongJing Using Big Data Technology

Objective To analyze various herbal combinations in Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》),seeking to identify fundamental rules dictating the selection of herbal combinations through probability models and big data technology.Methods A total of 252 formulae were collected from Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》)by ZHANG Zhong-Jing.Formulae were then preprocessed with all herb names standardized.The concepts of candidate herb pair and candidate herb pair probability were proposed to analyze the rules of combinations in classical formulae based on probability statistics.MapReduce parallel computing framework of distributed big data technology was adopted to analyze large data samples combined with inverted index algorithm.Results The results showed that the core herbs were Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Cinnamomi Ramulus(Gui Zhi,桂枝),Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Jujubae Fructus(Da Zao,大枣),Paeoniae Radix Alba(Bai Shao,白芍),etc.43 high-frequency pairs co-occurring 10 times or above were extracted,and 35 of these combinations were recognized as traditional herb pairs,such as Cinnamomi Ramulus(Gui Zhi,桂枝)-Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Jujubae Fructus(Da Zao,大枣),and Cinnamomi Ramulus(Gui Zhi,桂枝)-Ginseng Radix Et Rhizoma(Ren Shen,人参).The other 8 pairs of combinations,such as Paeoniae Radix Alba(Bai Shao,白芍)-Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Paeoniae Radix Alba(Bai Shao,白芍)-Jujubae Fructus(Da Zao,大枣),and Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Ginseng Radix Et Rhizoma(Ren Shen,人参),were not defined traditionally,but in connection with commonly used herbs.Classical formulae took the core herbs as principles,focusing on tonifying deficiency,strengthening the spleen and the stomach,strengthening the healthy Qi,and eliminating pathogenic factors.The compatibility pattern of properties involved was mainly acrid and sweet,which reflected the compatibility laws of benefiting Qi and tonifying Yang,replenishing Qi and nourishing blood,etc.Conclusions The research of classical formulae provides common understanding of some basic rules that have been adopted to tackle common illnesses/diseases using herbal medicine.The results help to reinforce theoretical understanding and development of traditional Chinese medicine(TCM),and revealing the hidden rules of combination in TCM data.Analyzing wider data samples of various herbal combinations through computation and big data technology can further optimize the use of TCM.