Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment.

BACKGROUND: Previous studies have demonstrated that high-density lipoprotein cholesterol (HDL-C) plays an anti-atherosclerosis role through reverse cholesterol transport. Several studies have validated the efficacy and safety of natural products in treating atherosclerosis (AS). However, the study of raising HDL-C levels through natural products to treat AS still needs to be explored. METHODS: The gene sets associated with AS were collected and identified by differential gene analysis and database query. By constructing a protein-protein interaction (PPI) network, the core submodules in the network are screened out. At the same time, by calculating node importance (Nim) in the PPI network of AS disease and combining it with Kyoto Encyclopedia of genes and genomes (KEGG) pathways enrichment analysis, the key target proteins of AS were obtained. Molecular docking is used to screen out small natural drug molecules with potential therapeutic effects. By constructing an in vitro foam cell model, the effects of small molecules on lipid metabolism and key target expression of foam cells were investigated. RESULTS: By differential gene analysis, 451 differential genes were obtained, and a total of 313 disease genes were obtained from 6 kind of databases, then 758 AS-related genes were obtained. The enrichment analysis of the KEGG pathway showed that the enhancement of HDL-C level against AS was related to Lipid and atherosclerosis, Cholesterol metabolism, Fluid shear stress and atherosclerosis, PPAR signaling pathway, and other pathways. Then we intersected 31 genes in the core module of the PPI network, the top 30 genes in Nims, and 32 genes in the cholesterol metabolism pathway, and finally found 3 genes. After the above analysis and literature collection, we focused on the following three related gene targets: APOA1, LIPC, and CETP. Molecular docking showed that Genistein has a good binding affinity for APOA1, CETP, and LIPC. In vitro, experiments showed that Genistein can up-regulated APOA1, LIPC, and CETP levels. CONCLUSIONS: Based on our research, Genistein may have the effects of regulating HDL-C and anti-atherosclerosis. Its mechanism of action may be related to the regulation of LIPC, CETP, and APOA1 to improve lipid metabolism.

Flavonoids and prenylhydroquinones from the prepared folium of Epimedium sagittatum Maxim. and their inhibition against phosphodiesterase5A.

An effort to identify novel active substances of the prepared folium of Epimedium sagittatum Maxim. (PFES) that was an important herb for male erectile dysfunction (ED) was taken. At present, phosphodiesterase-5A (PDE5A) is the most important target of new drugs for the treatment of ED. Therefore, the inhibition ingredients in PFES were systematically screened for the first time in this study. Eleven compounds, including eight new flavonoids and three prenylhydroquinones were isolated: sagittatosides DN (1-11), and their structures were elucidated by spectra and chemical analyses. Among them, a novel prenylflavonoid with oxyethyl group (1) was obtained and three prenylhydroquinones (9-11) were firstly isolated from Epimedium. All compounds were analyzed for the inhibition against PDE5A by molecular docking, and they all showed significant binding affinity as same as sildenafil. Their inhibitory activities were verified, and the results showed compound 6 had significant inhibition against PDE5A1. The isolation of new flavonoids and prenylhydroquinones with inhibitory activities of PDE5A from PFES implied that this herb might be a good source for the treatment of ED agents finding.

Discovery and Validation of Traditional Chinese and Western Medicine Combination Antirheumatoid Arthritis Drugs Based on Machine Learning (Random Forest Model).

The combination of traditional Chinese medicine (TCM) and Western medicine is a promising method for treating rheumatoid arthritis (RA). Combining the two fully exploits the advantages of Western and TCM to treat RA and has the potential to greatly improve the therapeutic effect on RA. In this study, we developed a combination drug training set by using 16 characteristic variables based on the characteristics of small molecules of TCM ingredients and Food and Drug Administration-certified combination drug data downloaded from the DrugCombDB database. Furthermore, we compared the prediction and classification abilities of five models: the k-nearest neighbors, naive Bayes, support vector machine, random forest, and AdaBoost algorithms. The random forest model was selected as the classification and prediction model for Western and TCM and Western combination drugs. We collected data for 41 small molecules of TCM ingredients from the Traditional Chinese Medicine Systems Pharmacology database and 10 small molecule drugs commonly used in anti-RA treatment from the DrugBank database. Combinations of Western and TCM for anti-RA treatment were screened. Finally, the CellTiter-Glo method was used to determine the synergy of these combinations, and the 15 most predicted drug combinations were carried out experimental verification. Myricetin, rhein, nobiletin, and fisetin had high synergy with celecoxib, and rhein had high synergy with hydroxychloroquine. The preliminary findings of this study can be further applied for practical clinical anti-RA combined treatment strategies and serve as a reference for clinical treatment of RA with integrated Western and TCM.

Identification of potential targets of cinnamon for treatment against Alzheimer's disease-related GABAergic synaptic dysfunction using network pharmacology.

Cinnamon aqueous extract's active substance base remains unclear and its mechanisms, mainly the therapeutic target of anti-Alzheimer's disease (AD)-related GABAergic synaptic dysfunction, remain unclear. Here, 30 chemical components were identified in the aqueous extract of cinnamon using LC/MS; secondly, we explored the brain-targeting components of the aqueous extract of cinnamon, and 17 components had a good absorption due to the blood-brain barrier (BBB) limitation; thirdly, further clustering analysis of active ingredient targets by network pharmacology showed that the GABA pathway with GABRG2 as the core target was significantly enriched; then, we used prominent protein-protein interactions (PPI), relying on a protein-metabolite network, and identified the GABRA1, GABRB2 and GABRA5 as the closest targets to GABRG2; finally, the affinity between the target and its cognate active compound was predicted by molecular docking. In general, we screened five components, methyl cinnamate, propyl cinnamate, ( +)-procyanidin B2, procyanidin B1, and myristicin as the brain synapse-targeting active substances of cinnamon using a systematic strategy, and identified GABRA1, GABRB2, GABRA5 and GABRG2 as core therapeutic targets of cinnamon against Alzheimer's disease-related GABAergic synaptic dysfunction. Exploring the mechanism of cinnamon' activities through multi-components and multiple targets strategies promise to reduce the threat of single- target and symptom-based drug discovery failure.

Disease Markers and Therapeutic Targets for Rheumatoid Arthritis Identified by Integrating Bioinformatics Analysis with Virtual Screening of Traditional Chinese Medicine.

OBJECTIVE: The aim of this study was to identify potentially important Rheumatoid arthritis (RA) targets related to immune cells based on bioinformatics analysis, and to identify small molecules of traditional Chinese medicine (TCM) associated with these targets that have potential therapeutic effects on RA. METHODS: Gene expression profile data related to RA were downloaded from the Gene Expression Omnibus (GSE55235, GSE55457, and GSE77298), and datasets were merged by the batch effect removal method. The RA key gene set was identified by protein-protein interaction network analysis and machine learning-based feature extraction. Furthermore, immune cell infiltration analysis was carried out on all DEGs to obtain key RA markers related to immune cells. Batch molecular docking of key RA markers was performed on our previously compiled dataset of small molecules in TCM using AutoDock Vina. Moreover, in vitro experiments were performed to examine the inhibitory effect of screened compounds on the synovial cells of an RA rat model. RESULTS: The PPI network and feature extraction with machine learning classifiers identified eight common key RA genes: MYH11, CFP, LY96, IGJ, LPL, CD48, RAC2, and CSK. RAC2 was significantly correlated with the infiltration and expression of five immune cells, with significant differences in these immune cells in the normal and RA samples. Molecular docking and in vitro experiments also showed that sanguinarine, sesamin, and honokiol could effectively inhibit the proliferation of RA rat synovial cells, also could all effectively inhibit the secretion of TNF-α and IL-1ß in synovial cells, and had a certain inhibitory effect on expression of the target protein RAC2. CONCLUSIONS: The core gene set of RA was screened from a new perspective, revealing biomarkers related to immune cell infiltration. Using molecular docking, we screened out TCM small molecules for the treatment of RA, providing methods and technical support for the treatment of RA with TCM.

Integrated network pharmacology and hepatic metabolomics to reveal the mechanism of Acanthopanax senticosus against major depressive disorder.

Objective: Acanthopanax senticosus (Rupr. et Maxim.) Harms (ASH) is a traditional herbal medicine widely known for its antifatigue and antistress effects, as well as tonifying qi, invigorating spleen and kidney, and tranquilizing the mind. Recent evidence suggests that ASH has a therapeutic effect on major depressive disorder (MDD), but its mechanism is still unclear. The current study aimed to investigate the effect of ASH on MDD and potential therapeutic mechanisms. Materials and Methods: The chemical compound potential target network was predicted based on network pharmacology. Simultaneously, chronic unpredictable mild stress (CUMS) model mice were orally administrated ASH with three dosages (400, 200, and 100 mg/kg) for 6 weeks, and hepatic metabolomics based on gas chromatography-mass spectrometry (GC-MS) was carried out to identify differential metabolites and related metabolic pathways. Next, the integrated analysis of metabolomics and network pharmacology was applied to find the key target. Finally, molecular docking technology was employed to define the combination of the key target and the corresponding compounds. Results: A total of 13 metabolites and four related metabolic pathways were found in metabolomics analysis. From the combined analysis of network pharmacology and metabolomics, six targets (DAO, MAOA, MAOB, GAA, HK1, and PYGM) are the overlapping targets and two metabolic pathways (glycine, serine, and threonine metabolism and starch and sucrose metabolism) are the most related pathways. Finally, DAO, MAOA, MAOB, GAA, HK1, and PYGM were verified bounding well to their corresponding compounds including isofraxidin, eleutheroside B1, eleutheroside C, quercetin, kaempferol, and acacetin. Conclusion: Based on these results, it was implied that the potential mechanism of ASH on MDD was related to the regulation of metabolism of several excitatory amino acids and carbohydrates, as well as the expression of DAO, MAOA, MAOB, GAA, HK1, and PYGM.

Computation-Based Discovery of Potential Targets for Rheumatoid Arthritis and Related Molecular Screening and Mechanism Analysis of Traditional Chinese Medicine.

This study is aimed at screening potential therapeutic ingredients in traditional Chinese medicine (TCM) and identifying the key rheumatoid arthritis (RA) targets using computational simulations. Data for TCM-active ingredients with clear pharmacological effects were collected. Absorption, distribution, metabolism, excretion, and toxicity were evaluated. Potential RA targets were identified using the Gene Expression Omnibus (GEO) database, protein-protein interaction network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and potential TCM ingredients using AutoDock Vina. To examine the mechanisms underlying small molecules, target prediction, Gene Ontology, KEGG, and network modeling analyses were conducted; the effects were verified in rat synovial cells using cell proliferation assay. The activities of tumor necrosis factor TNF-α and IL-1ß and alterations in cellular target protein levels were detected by ELISA and Western blotting, respectively. In total, data for 432 TCM active ingredients with clear pharmacological effects were obtained. Five critical RA-related genes were identified; CCL5 and CXCL10 were selected for molecular docking. Target prediction and network-based proximity analysis showed that dioscin could modulate 22 known RA clinical targets. Dioscin, asiaticoside, and ginsenoside Re could effectively inhibit in vitro cell proliferation and secretion of TNF-α and IL-1ß in RA rat synovial cells. Using bioinformatics and computer-aided drug design, the potential small anti-RA molecules and their mechanisms of action were comprehensively identified. Dioscin could significantly inhibit proliferation and induce apoptosis in RA rat synovial cells by reducing TNF-α and IL-1ß secretion and inhibiting abnormal CCL5, CXCL10, CXCR2, and IL2 expression.

Clinical Evidence and Potential Mechanisms of Complementary Treatment of Ling Gui Zhu Gan Formula for the Management of Serum Lipids and Obesity.

Objective: This study aims to evaluate the clinical effects of Ling Gui Zhu Gan formula (LGZG), a famous TCM formula, for the management of serum lipids and obesity and preliminarily elucidates the bioactive components and the potential mechanism. Methods: Cluster analysis was adopted to investigate the TCM herbs and their frequency of occurrence for treating hyperlipidemia and obesity in an academic experience database of Chinese famous TCM doctors (http://www.gjmlzy.com:83). Then, relevant randomized controlled trials (RCTs) about LGZG supplementation in improving lipid levels and obesity were retrieved and analyzed. Lastly, the integration of network pharmacology, as well as greedy algorithms, which are theoretically well founded for the set cover in computer science, was exploited to identify the bioactive components of LGZG and to reveal potential mechanisms for attenuation or reversal of hyperlipidemia and obesity. Results: Based on the cluster analysis of 104 cases in TCM academic experience database, four TCM herbs in LGZG showed high-use frequency for treating hyperlipidemia and obesity. Meta-analysis on 19 randomized controlled trials (RCTs) with 1716 participants indicated that LGZG supplementation significantly decreased the serum levels of total triglycerides, total cholesterol, low-density lipoprotein cholesterol, BMI, and body weight and increased high-density lipoprotein cholesterol, compared with clinical control groups. No serious adverse effect was detected in all studies. Twenty-one bioactive components of LGZG, mainly flavonoids (i.e., naringenin, kaempferol, and kumatakenin), saponins (i.e., hederagenin), and fatty acids (i.e., eicosenoic acid), had the potential benefits possibly by regulating multiple targets such as PTPN1, CYP19A1, and ESR2, as well as a few complex pathways including the TNF signaling pathway, PPAR signaling pathway, arachidonic acid metabolism, fat digestion, and absorption. Conclusion: The present study has proved the clinical value of LGZG as a complementary treatment for attenuation or reversal of hyperlipidemia and obesity. More high-quality clinical and experimental studies in the future are demanded to verify its effects and the precise mechanism of action.

Mechanism of Sanhua Decoction in the Treatment of Ischemic Stroke Based on Network Pharmacology Methods and Experimental Verification.

OBJECTIVE: The mechanism of action of Sanhua Decoction (SHD) in the treatment of ischemic stroke (IS) was analyzed based on the network pharmacology technology, and the pharmacodynamics and key targets were verified using the rat middle cerebral artery occlusion (MCAO) model. METHODS: The GEO database was used to collect IS-related gene set S D , and DrugBank and TTD databases were used to obtain the therapeutic drug target set S T . IS disease gene set S I was collected from DisGeNET, GeneCards, and OMIM databases. These three different gene sets obtained from various sources were merged, duplicates were removed, and the resulting IS disease gene set S IS was imported into the STRING database to establish the protein-protein interaction (PPI) network. Two methods were used to screen the key targets of IS disease based on the PPI network analysis. The TCMSP database and PubChem were applied to retrieve the main chemical components of SHD, and the ACD/Labs software and the SwissADME online system were utilized for ADMET screening. HitPick, SEA, and SwissTarget Prediction online systems were used to predict the set of potential targets for SHD to treat IS. The predicted set of potential targets and the IS disease gene set were intersected. Subsequently, the set of potential targets for SHD treatment of IS was identified, the target information was confirmed through the UniProt database, and finally, the component-target data set for SHD treatment of IS was obtained. clusterProfiler was used for GO function annotation and KEGG pathway enrichment analysis on the target set of SHD active ingredients. A rat MCAO model was established to evaluate the pharmacodynamics of SHD in the treatment of IS, and Western blot analysis assessed the level of proteins in the related pathways. RESULTS: This study obtained 1,009 IS disease gene sets. PPI network analysis identified 12 key targets: AGT, SAA1, KNG1, APP, GNB3, C3, CXCR4, CXCL12, CXCL8, CXCL1, F2, and EDN1. Database analyses retrieved 40 active ingredients and 47 target genes in SHD. The network proximity algorithm was used to optimize the six key components in SHD. KEGG enrichment showed that the signaling pathways related to IS were endocrine resistance, estrogen, TNF signal pathway, and AGEs/RAGE. Compound-disease-target regulatory network analysis showed that AKT1, IL-6, TNF-α, TP53, VEGFA, and APP were related to the treatment of IS with SHD. Animal experiments demonstrated that SHD significantly reduces the neurological function of rat defect symptoms (P < 0.05), the area of cerebral avascular necrosis, and neuronal necrosis while increasing the levels of IL-6 and APP proteins (P < 0.05) and reducing the levels of AKT1 and VEGFA proteins (P < 0.05). CONCLUSION: The effective components of SHD may regulate multiple signaling pathways through IL-6, APP, AKT1, and VEGFA to reduce brain damage and inflammatory damage and exert a neuroprotective role in the treatment of IS diseases. Thus, this study provides a feasible method to study the pharmacological mechanism of traditional Chinese medicine compound prescriptions and a theoretical basis for the development of SHD into a new drug for IS treatment.

Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology.

OBJECTIVE: Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. METHODS: The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. RESULTS: According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. CONCLUSIONS: In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

Evaluating the Therapeutic Mechanisms of Selected Active Compounds in Houttuynia cordata Thunb. in Pulmonary Fibrosis via Network Pharmacology Analysis.

Pulmonary fibrosis, a common outcome of pulmonary interstitial disease of various different etiologies, is one of the most important causes of respiratory failure. Houttuynia cordata Thunb. (family: Saururaceae) (H. cordata), as has been reported, is a Chinese herbal medicine commonly used to treat upper respiratory tract infection and bronchitis. Our previous study has proven that sodium houttuyfonate (an additional compound from sodium bisulfite and houttuynin) had beneficial effects in the prevention of pulmonary fibrosis (PF) induced by bleomycin (BLM) in mice. In the present study, network pharmacology was used to investigate the efficiency and potential mechanisms of H. cordata in PF treatment. Upon manual collection from the literature and databases such as TCMSP and TCM-ID, 10 known representative ingredients of H. cordata species were screened. Then, the prediction of the potential active ingredients, action targets, and signaling pathways were conducted through the Gene Ontology (GO), protein-protein interaction (PPI),and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The results of network pharmacology prediction suggested that H. cordata may act through multiple signaling pathways to alleviate PF, including the phosphatidylinositol 3-kinase-protein kinase B (PI3K/AKT) pathways, mitogen-activated protein kinase (MAPK) pathways, the tumor necrosis factor (TNF) pathways, and interleukin-17 (IL-17) signaling pathways. Molecular docking experiments showed that the chemical constituents of H. cordata had good affinity with TNF, MAPK1, and AKT1, and using lipopolysaccharide (LPS)-induced A549 cells, a model was established to verify the anti-pulmonary fibrosis effects and related mechanisms of H. cordata-relevant constituents. Finally, these evidences collectively suggest H. cordata may alleviate PF progression via PI3K/Akt, MAPK, and TNF signaling pathways and provide novel insights to verify the mechanism of H. cordata in the treatment of PF.

Interpreting the Molecular Mechanisms of Yinchenhao Decoction on Hepatocellular Carcinoma through Absorbed Components Based on Network Pharmacology.

To investigate the mechanisms through which Yinchenhao decoction (YCHD) inhibits hepatocellular carcinoma (HCC), we analyzed YCHD ingredients absorbed into the bloodstream by using network pharmacology. We conducted a weighted gene coexpression network analysis on gene expression data collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases to derive an HCC gene set; moreover, we used four online prediction system databases to predict the potential targets of YCHD ingredients absorbed into the bloodstream. We discovered that YCHD directly interfered with 17 HCC-related disease targets. Subsequent gene ontology enrichment analyses of these 17 disease targets revealed that YCHD exhibited effects through 17 biological processes, 7 molecular functions, and 9 cellular components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated 14 pathways through which YCHD inhibits HCC. We observed similar trends in how the 17 small molecules interfered with the key target set. We surmised that YCHD inhibits HCC by regulating inflammatory and metabolic pathways. Network pharmacological analysis of YCHD ingredients absorbed into the bloodstream may provide new insights and serve as a new method for discovering the molecular mechanisms through which YCHD inhibits HCC.

Research on the Mechanism of Qushi Huayu Decoction in the Intervention of Nonalcoholic Fatty Liver Disease Based on Network Pharmacology and Molecular Docking Technology.

OBJECTIVE: To use network pharmacology and molecular docking technology in predicting the main active ingredients and targets of Qushi Huayu Decoction (QHD) treatment in Nonalcoholic Fatty Liver Disease (NAFLD) and explore the potential mechanisms of its multi-component-multi-target-multi-pathway. MATERIALS AND METHODS: The main chemical components of QHD were searched using traditional Chinese medicine system pharmacology technology platform (TCMSP) and PubChem database. The main chemical components of the prescription were ADMET screened by the ACD/Labs software. The main active ingredient was screened by 60% oral bioavailability, and 60% of "bad" ingredients were removed from the drug-like group. Swiss Target Prediction, the SEA, and HitPick systems were sequentially used to search for the target of each active ingredient, and a network map of the QHD's target of the active ingredient was constructed. Genome annotation database platforms (GeneCards, OMIM, and DisGeNET) were used to predict action targets related to fatty liver disease. "Drug-Disease-Target" network diagram could be visualized with the help of Cytoscape (3.7.1) software. UniProt and STRING database platforms were used to build a protein interaction network. The KEGG signal pathway and DAVID platform were analyzed for biological process enrichment. RESULTS: A total of 128 active ingredients and 275 corresponding targets in QHD were discovered through screening. 55 key target targets and 27 important signaling pathways were screened, such as the cancer pathway, P13K-AKT signaling pathway, PPAR signaling pathway, and other related signaling pathways. CONCLUSIONS: The present study revealed the material basis of QHD and discussed the pharmacological mechanism of QHD in fatty liver, thus providing a scientific basis for the clinical application and experimental research of QHD in the future.

Therapeutic efficacy of fuzheng-huayu tablet based traditional chinese medicine syndrome differentiation on hepatitis-B-caused cirrhosis: a multicenter double-blind randomized controlled trail.

Aim. To evaluate and predict the therapeutic efficacy of Fuzheng-Huayu tablet (FZHY) based traditional Chinese Medicine (TCM) syndrome differentiation or TCM symptoms on chronic hepatitis B caused cirrhosis (HBC). Methods. The trial was designed according to CONSORT statement. It was a multi-center, double-blind, randomized, placebo-controlled trail. Several clinical parameters, Child-Pugh classification and TCM symptoms were detected and evaluated. The FZHY efficacy was predicted by an established Bayes forecasting method following the Bayes classification model. Results. The levels of HA and TCM syndrome score in FZHY group were significantly decreased (P < 0.05) compared to placebo group, respectively. The efficacy of FZHY on TCM syndrome score in HBC patients with some TCM syndromes was better. In TCM syndrome score evaluation, there were 53 effective and 22 invalid in FZHY group. TCM symptoms predicted FZHY efficacy on HBC were close to Child-Pugh score prediction. Conclusion. FZHY decreases the levels of HA and TCM syndrome scores, improves the life quality of HBC patients. Moreover, there were different therapeutic efficacies among different TCM syndromes, indicating that accurate TCM syndrome differentiation might guide the better TCM treatment. Furthermore, the FZHY efficacy was able to predict by Bayes forecasting method through the alteration of TCM symptoms.

[An evaluation method for analysis of correlation between traditional Chinese medicine syndrome and seasonal changes of weather based on information entropy].

OBJECTIVE: A method based on dubious condition of information entropy was introduced and applied to discuss a complexity problem in the analysis of correlation between traditional Chinese medicine (TCM) syndrome and season. METHODS: Eight hundred and seventy one cases of chronic virus hepatitis B (hepatitis B) with TCM clinical data were analyzed by information entropy method. RESULTS: It was found that hepatitis B with Yin deficiency of liver and kidney happened more often in summer than in other seasons. CONCLUSION: It is inferred that the difference of seasons may influence the variation of TCM syndromes.