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OBJECTIVE To evaluate the safety and suitability of traditional Chinese medicine prescriptions generated by generative artificial intelligence （AIGC）， and to provide research ideas for empowering the traditional Chinese medicine industry with AIGC. METHODS Using the 2020 edition of Chinese Pharmacopoeia and the 5th edition of Traditional Chinese Medicine as corpus， GPT-4 and the real-time networking model developed based on GPT-4 （referred to as the “networking model”） were used for deep learning. The clinical cases included in the consensus of traditional Chinese medicine experts in recent years were extracted manually to regenerate prescriptions based on diagnosis using the GPT-4 model and networking model； traditional Chinese medicine experts conducted blind evaluation and scoring of GPT-4 generated prescriptions， networking model generated prescriptions， and expert consensus prescriptions. At the same time， Turing testing was used to evaluate whether the GPT-4 model and networking model had the same ability as human intelligence. RESULTS The average score of traditional Chinese medicine prescriptions generated by the GPT-4 model showed no statistically significant difference compared to manual prescriptions （P＞0.05）， while the average score of prescriptions generated by the networking model showed no statistically significant difference compared to traditional Chinese medicine prescriptions generated by the GPT-4 model （P＞0.05）. The proportion of model-generated prescriptions mistakenly judged as manual prescriptions in the Turing test was 51.11%. CONCLUSIONS The traditional Chinese medicine prescriptions generated by the GPT-4 model have reached a certain level of safety and suitability， and the GPT-4 model has passed the Turing test. The introduction of AIGC in the diagnosis and treatment process may provide technical support for the rational use of clinical traditional Chinese medicine.
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Integrative pharmacology (IP) is a discipline that studies the interaction, integration and principle of action of multiple components with the body, emphasizing the integrations of multi-level and multi-link, such as "whole and part", " and ", " process and activity evaluation". After four years of development and practice, the theory and method of IP has received extensive attention and application.In order to better promote the development of IP, this paper systematically reviews the concepts, research contents, research methods and application fields about IP.
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Traditional Chinese medicine (TCM) is widely used as a complementary approach for osteoarthritis treatment.This article is based on the real world.The implicit prescription patterns behind TCM formulae were examined by association rules mining and cluster analysis,so as to explore the Chinese medicinal compatibility patterns or rules in osteoarthritis treatment.This study was based on real-world data from the hospital information system (HIS).Chinese medicinal prescriptions of hospitalized patients with osteoarthritis from June 2012 to June 2016 were collected from the Department of Rheumatism and Immunology,the First Affiliated Hospital of Anhui University of Chinese Medicine.TCM was listed according to the selected medicinal formulae and the added information was organized to establish a database.The frequency and association rules of prescription patterns were analyzed using the SPSS Modeler 14.2 Data Mining System.Cluster analysis of prescription patterns was also analyzed.An initial statistical analysis was carried out to categorize herbs according to their natures,flavors,channel tropisms and functions.Based on categorization,frequencies of occurrence were computed.At the same time,the relationship between TCM and immune and inflammatory markers was analyzed.The results showed that the main prescriptive features from the selected formulae of the mining data were that,(1) warm or cold herbs,sweet or bitter herbs,and with the channel tropism of spleen channel are the most frequently prescribed herbs in 3609 medicinal formulae;(2) herbs with blood-activating and stasis-resolving,restoring vital energy,water-eliminating and damp-removing,heat-clearing and or expelling wind-damp functions are frequently prescribed;(3) association rule analysis extracted three frequently used pairs of herbs,which are Hong Hua & Tao Ren (98.90％),Pu Gong Ying & Bai Hua She She Cao (97.88％),Fu Ling & Ze Xie (92.63％);(4) association rule between TCM and immune-inflammation index showed that the pair of Du Huo and Chen Pi was associated with increased superoxide dismutase (SOD) enzyme.The pair of Mai Ya and Dan Shen was associated with decreased high-sensitivity C-reactive protein (hs-CRP),erythrocyte sedimentation rate (ESR),complement component 3 (C3),complement component 4 (C4),immunoglobulin A (IgA) and immunoglobulin G (IgG).The pair of Mai Ya and Fu Ling was associated with decreased immunoglobulin M (IgM).It was concluded that osteoarthritis was closely related to spleen deficiency.These prescriptions focus on herbs for qi-nourishing and spleen-invigorating,blood-activating and stasis-resolving,spleen-invigorating and dampness-eliminating,heat-clearing and detoxicating which seems to be the key element in the treatment process.Meanwhile,the use of restoring vital energy herbs and spleen-strengthening herbs also forms the basis of prescription patterns.
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This paper studied the correlation between traditional Chinese medicine (TCM) prescription and disease based on machine learning.This paper selected TCM literature abstract data in the TCM category of the China National Knowledge Infrastructure (CNKI) database by crawler technology.After data cleaning,lexicon building,word segmentation and other related basic pre-treatment work,it uses natural language processing technique to extract the feature of the web text data,constructs the Support Vector Machine (SVM) classification model,and extracts the relation between TCM prescription and disease.The results showed that among 1073581 abstracts,204780 sentences,which included both TCM prescription and the disease according to dictionaries,were filtered.The SVM classification model whose feature is constructed by constituency parser is in a better accuracy,which achieved 87％.Applying the SVM model in filtered sentences,this study obtained the relation triples between TCM prescription and the disease.It was concluded that by using the method of machine learning to extract relation on abstract data from the CNKI database,the extracted relation triples of TCM prescription and disease will take a positive effect on the research of disease treatment by TCM prescription.
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This study was aimed to use machine learning techniques for the prescription regularity of traditional Chinese medicine (TCM) in the treatment of liver diseases in order to provide a reference basis for clinical treatment as well as research and development of new drugs.According to the prescription data of liver disease treatment of the last two years in the hepatology department of a triple-A TCM hospital,the related structure between drugs was firstly found by the complex structure of drugs.And then,association rule,cluster analysis and other unsupervised machine learning methods were used.The prescription regularity of TCM in the treatment of cirrhosis was received through the comparison and analysis.The results showed that there were 589 prescriptions with 257 types of Chinese medicine herbs.The high frequency drug combination included 2 items of 12,3 items of 15,4 items of 14;support ＞ 10％,confidence ＞ 90％ of the association rule include "dried tangerine peel,medicated leaven → largehead atractylodes rhizome," "polyporus umbellatus,dried tangerine peel → largehead atractylodes rhizome" and other 34;through cluster analysis,it showed that Chinese medicine was mainly classified by 5 characteristics.The machine learning result was the same as the constructed complex network.It was concluded that the combination of complex network and machine learning methods in the exploration of prescription regularity of TCM in the treatment of cirrhosis were feasible.It provided clinical treatment of cirrhosis and clues for finding new prescription in the treatment of cirrhosis.
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In view of the industry lacking of sufficient analyses on the bases of project establishment about the new drugs of traditional Chinese medicine(TCM) during their applying for the clinical research, from the perspective of clinical evaluation, this paper reviewed and analyzed the present situation and development paths of new drugs of TCM in recent years. Through the analyses of the rationality of formulations, human use experiences and clinical studies, the paper puts forward the countermeasures to solve these difficulties during the technical evaluation of new drugs of TCM in order to improve the new drugs' clinical research.
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Objective To observe the protective effect of the traditional Chinese medicine prescription, Jiu Nao Yi Zhi water extract, on human neuroblastoma SH-SY5Y cell line, its effect on expression of insulin signal transduction pathway, and to explore the related mechanisms.Methods SH-SY5Y cells cultured in vitro, were divided into control group, Jiu Nao Yi Zhi No.1 prescription group and No.3 prescription group.The doses were 0.0625 mg/mL, 0.125 mg/mL, 0.25 mg/mL, 0.5 mg/mL and 1 mg/mL.The thiazolyl blue ( MTT) metabolic rate of each group was determined.The dose of 0.125 mg/mL was chosen for cell immunofluorescence analysis, and to observe the expression of insulin receptor substrates-1 ( IRS-1 ) , cAMP response element binding protein ( CREB ) , and the factors of insulin signal transduction pathway.Results Compared with the control group, MTT metabolic rates of the Jiu Nao Yi Zhi groups were significantly increased (P<0.05), and the cell morphology was much better in those groups, cell body more plump, well-adherent and neurite extensions were observed.The expressions of IRS-1 and CREB were higher than that in the control group.Conclusions The traditional Chinese medicine prescription Jiu Nao Yi Zhi water extract can protect neurons by promoting nerve cell growth, and improving the expression of IRS-1 and CREB, the factors of insulin signal transduction pathway.
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OBJECTIVE:To improve the writing quality prescriptions of traditional Chinese medicines and to facilitate the standardization of traditional Chinese medicine prescriptions.METHODS:A total of 15 000 prescriptions were sampled in our hospital in 2006 for an analysis of the problems in accordance with the related standards specified in Chinese Pharmacopoeia(CP,2005 edition)and the new "Prescription management method".RESULTS:The problems manifested as nonstandard in drug name and footnotes,or overdosage and so on.CONCLUSION:We should strengthen the management of the traditional Chinese drugs and improve our pharmaceutical care.
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Objective To study the mechanism of traditional Chinese medicine Compound Xueniaoting (CXNT) in treating glomerulus diseases with the main pathological changes of proliferation in mesangial cells. Methods CXNT and rat liver microsomes were incubated together, and then the incubated CXNT was added into cultured glomerular mesangial cells (GMC) in vitro. The proliferation of GMC was observed by MTT assay, the levels of interleukin-6 (IL-6) and endothelin-1 (ET-1) were determined by radioimmunoassay, and content of lactic dehydrogenase (LDH) was determined by velocity assay. ResultsCXNT (2, 4, 8 mg/mL) metobolized by rat liver microsomes could all inhibite the proliferation of GMC and production of IL-6 and ET-1 in a dose-dependent manner. Conclusion CXNT can inhibite the proliferation of GMC and restrain the secretion of IL-6 and ET-1, this function may be one of CXNT mechanisms in treating some mesangial proliferative glomerulonephritis.