ABSTRACT
Objective:To analyze the compatibility rules of prescriptions containing Forsythiae Fructus based on data mining and explore the anti-inflammatory mechanism of Forsythiae Fructus based on network pharmacology,so as to provide reference for the rational clinical application of Forsythiae Fructus and the development of health foods and new Chinese medicines. Method:The prescriptions containing Forsythiae Fructus in the<italic> Dictionary of Traditional Chinese Medicine Prescriptions</italic> were collected,based on which a clinical prescription database was constructed. The Chinese herbs combined with Forsythiae Fructus and the corresponding indications were subjected to frequency statistics,association rule analysis,and complex network analysis using SPSS Statistics 26,IBM SPSS Modeler 18.0,and Gephi 9.2. The active components and targets of Forsythiae Fructus for anti-inflammation were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP),BATMAN-TCM,and SEA,and the targets related to anti-inflammation from GeneCards,Online Mendelian Inheritance in Man (OMIM),CTD,and GenCLiP3. Following the analysis of protein-protein interactions (PPI) with STRING,a PPI network was constructed. The enrichment analysis was performed using Metascape,and the active component-anti-inflammation target-signaling pathway network of Forsythiae Fructus was constructed by Cytoscape 3.8.2. Result:According to the inclusion and exclusion criteria,2 245 prescriptions containing Forsythiae Fructus were harvested,involving 512 Chinese herbs,with a total usage frequency of 27 314. The Chinese herbs that were most frequently combined with Forsythiae Fructus (>800 times) were Glycyrrhizae Radix et Rhizoma (1 483 times),Scutellariae Radix (964 times),and Angelicae Sinensis Radix (842 times). Hence,the herbal pairs "Forsythiae Fructus-Scutellariae Radix" and "Forsythiae Fructus-Angelicae Sinensis Radix" were further explored. The prescriptions containing Forsythiae Fructus could be utilized for the treatment of 29 kinds of diseases,and three representative disease categories including "carbuncle,gangrene,sores and ulcers","ophthalmic diseases and syndromes" and "epidemic diseases" are selected for data mining. There were 19 association rules obtained with "Forsythiae Fructus-Glycyrrhizae Radix et Rhizoma-Lonicerae Japonicae Flos-Angelicae Sinensis Radix" as the core herb combination for "carbuncle,gangrene,sores and ulcers". The clustering analysis revealed one multi-herb clustering group,four herbal pairs,and single herb Lonicerae Japonicae Flos,the complex network analysis four herbal modules,and the factor analysis six common factors. There were 23 association rules obtained with "Forsythiae Fructus-Glycyrrhizae Radix et Rhizoma-Scutellariae Radix-Angelicae Sinensis Radix" as the core herb combination for "ophthalmic diseases and syndromes". The clustering analysis revealed two multi-herb clustering groups and four herbal pairs,the complex network analysis four herbal modules,and the factor analysis five common factors. There were 28 association rules obtained with "Forsythiae Fructus-Glycyrrhizae Radix et Rhizoma-Menthae Haplocalycis Herba-Lonicerae Japonicae Flos" as the core herb combination for "epidemic diseases". The clustering analysis revealed three multi-herb clustering groups,one herbal pair,and two single herbs Forsythiae Fructus and Glycyrrhizae Radix et Rhizoma,the complex network analysis four herbal modules,and the factor analysis five common factors. As demonstrated by network pharmacology-based analysis,the core anti-inflammation components of Forsythiae Fructus were quercetin,luteolin,and kaempferol,and the core targets were phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1),protein kinase B 1 (Akt1),and epidermal growth factor receptor(EGFR). The biological pathways were mainly concentrated in proteoglycans in cancer,pathways in cancer,and PI3K/Akt signaling pathway,with such functions as inhibition of transcription factors,regulation of enzyme activity,and inflammation-related gene expression involved. Conclusion:This study employed a variety of data mining techniques to objectively,intuitively,and scientifically uncover the compatibility rules of Forsythiae Fructus in the treatment of high-frequency diseases. It has been found that Forsythiae Fructus is often combined with heat-clearing herbs,tonifying herbs,exterior-releasing herbs,and blood-activating and stasis-resolving herbs for diverse diseases and syndromes. Under the premise of clearing heat and removing toxin,reinforcing healthy Qi and dredging stagnation are also emphasized. According to the degree of internal heat exuberance,the heat-clearing herbs with different merits are combined. This study has revealed the unique advantages of Forsythiae Fructus in the treatment of specific diseases and syndromes as well as its multi-component,multi-target,and multi-pathway mechanisms in anti-inflammation,breaking through the limitations in modern clinical and experimental research of Forsythiae Fructus. These findings are of great significance for guiding the rational clinical application of Forsythiae Fructus and the development of health foods and new Chinese medicines,thus better accelerating the development of Chinese medicine health industry.
ABSTRACT
Based on the database of "Dictionary of Traditional Chinese Medicine Prescriptions", high-frequency herbs of Xiaoke disease is mined by traditional Chinese medicine inheritance support system, and core herbs and combinations are discovered through association rules and cluster analysis. On this basis, based on the integrative pharmacology of traditional Chinese medicine to explore the herb-disease relationship, the "herb-compound-target" network is constructed and enriched for the analysis of key target gene functions, metabolic pathways, and their "core herb-target interactions". In order to explore the molecular mechanism of its prevention and treatment of diabetes, 341 diabetes prescriptions are collected, organized, and tapped in the Dictionary of Traditional Chinese Medicine Prescriptions. Herb frequency statistics show that Licorice was the most commonly used, followed by Ophiopogonis Radix, Poria, Ginseng Radix et Rhizoma, Coptidis Rhizoma, etc., the medicinal properties are mostly cold, warm and ping, and the medicinal taste tends to be pungent, bitter, and sour, and they were attributed to lung meridian, stomach meridian, spleen meridian, etc. Among them, the 17 herbs were closely related. Ginseng Radix et Rhizoma, Ophiopogonis Radix, Poria and Glycyrrhizae Radix et Rhizoma were the core Chinese herbs. Ophiopogonis Radix was the key node of Coptidis Rhizoma, Trichosanthis Radix and core Chinese medicine, and Ophiopogonis Radix was the key node for the connection between Coptidis Rhizoma and Trichosanthis Radix and the core Chinese herbs. Using integrated pharmacology platform analysis, 10 crucial core targets for the prevention and treatment of diabetes were obtained, including the known disease targets (PLCD1, PIK3R1, ENPP1), and potential herb targets(GNB1, ADCY1, AKT1, RAC1, PRKAA1, RHOA) , common target (GCK). There were seven similar targets in the 10 crucial core targets predicted with the combination of "Ophiopogonis Radix, Coptidis Rhizoma and Trichosanthis Radix", including PLCD1, PIK3R1, ENPP1, ADCY1, AKT1, PRKAA1, GCK. These genes were mainly located in the cytosol, plasma membrane, etc., involved in adenosine triphosphate binding, protein binding, platelet activation, etc., mainly involved in the endocrine system, signal transduction, chemokine signaling pathway, cancer pathway, and other metabolic pathways, and it is speculated that these genes were potentially associated with diabetes. In this study, Traditional Chinese Medicine Inheritance Support System and Integrative Pharmacology of Traditional Chinese Medicine are used to analyze the prescription law of Xiaoke prescription, and the correlation of "core herbs-functionary targets" is excavated, which provided the basis and reference for the screening and development of TCM prescriptions for the prevention and treatment of diabetes.
Subject(s)
Data Mining , Drug Prescriptions , Drugs, Chinese Herbal , Pharmacology , Medicine, Chinese Traditional , MeridiansABSTRACT
Gardeniae Fructus, which is widely used in health foods and clinical medicines, is a type of edible food and medicine. Dictionary of traditional Chinese medicine prescriptions provides good materials for prescription analysis and the R&D of traditional Chinese medicines. The composition regularity of formulae containing Gardeniae Fructus in dictionary of traditional Chinese medicine prescriptions was analyzed on the basis of the traditional Chinese medicine inheritance support system(TCMISS), in order to provide reference for clinical application and the R&D of new drugs. TCMISS was applied to establish a database of prescriptions containing Gardeniae Fructus. The software's frequency statistics and association rules and other date mining technologies were adopted to analyze commonly used drugs, combination rules and core combined formulae containing Gardeniae Fructus. Totally 3 523 prescriptions were included in this study and involved 1 725 Chinese herbs. With a support degree of 352(10%) and confidence coefficient of 90%, 57 most commonly used drug combinations were screened. Drugs adopted in core combinations were relatively concentrated and selected according to definite composition methods. They were used to mainly treat 18 diseases. Gardeniae Fructus have often been combined with herbs for heat-clearing and detoxification, expelling pathogenic wind, relieving exterior syndrome, invigorating the circulation of blood and gas and promoting blood circulation for removing blood stasis to mainly treat jaundice, typhoid, headache and other syndromes.
ABSTRACT
Objective To study the automatic word segmentation scheme suitable for traditional Chinese medical record literature. Methods Hierarchical Hidden Markov Model was used as segmentation model. Totally 300 ancient medical record literature and 300 modern medical record literature were set as experimental subjects to establish the dictionary of traditional Chinese medicine and the test corpus, with a purpose to segment the words and evaluate of the results. Results Without using dictionary of traditional Chinese medicine, the word segmentation accuracy of two kinds of medical record literature was about 75%;the part-of-speech tagging accuracy of ancient medical literature was 56.74%, the modern medical literature accuracy was 64.81%. By using dictionary of tradition Chinese medicine, the word segmentation accuracy of ancient medical record literature was 90.73%, the modern medical record literature accuracy was 95.66%;the part-of-speech tagging accuracy of ancient medical record literature was 78.47%, the modern medical record literature accuracy was 91.45%, which was obviously higher than that of ancient medical record literature. Conclusion The current word segmentation scheme has initially solved the problem of word segmentation of traditional Chinese medical record literature and part-of-speech tagging of modern medical record literature. Part of speech tagging is basically correct, but part-of-speech tagging of ancient medical record literature tagging needs further study for many influencing factors.