[Identification of quality markers of Gei Herba based on analytic hierarchy process-entropy weight method and network pharmacology]

Analytic hierarchy process(AHP)-entropy weight method(EWM) and network pharmacology were employed to identify the potential quality markers(Q-markers) of Gei Herba. According to the new concept of Q-markers in traditional Chinese medicine(TCM), the AHP-EWM was applied to quantitatively identify the Q-markers of Gei Herba. The AHP was used for the weight analysis of primary indicators(factor layer), and the EWM for the analysis of literature and experimental data of secondary indicators(control layer). In addition, network pharmacology was employed to build the "component-target-disease-efficacy" network for Gei Herba, and the components showing strong associations with the Qi-replenishing, spleen-invigorating, blood-tonifying, Yin-nourishing, lung-moistening, and phlegm-resolving effects of Gei Herba were screened out. According to the results of AHP-EWM and network pharmacology, four components, i.e., ellagic acid, gallic acid, gemin G, and gemin C, were finally identified as potential Q-markers of Gei Herba. In this study, the AHP-EWM and network pharmacology were employed to screen the Q-markers of Gei Herba, which provided ideas for the quantitative evaluation and identification of Q-markers of TCM.

[Research on Q-markers of Polygoni Perfoliati Herba based on analytic hierarchy process-entropy weight method and fingerprints]

The potential quality markers(Q-markers) of Polygoni Perfoliati Herba were studied based on analytic hierarchy process(AHP)-entropy weight method(EWM), network pharmacology, and spectrum-effect relationship analysis. The AHP-EWM was used for quantitative identification of the Q-markers. To be specific, AHP was applied for the weight analysis of the validity, testability, and specificity of the first-level indexes, and EWM for the analysis of the second-level indexes supported by literature and experimental data. Based on literature and network pharmacology, the validity analysis was to study the component-target-disease-efficacy network, and select the components with the strongest correlation with the efficacy of clearing heat and removing toxin, diuresis and alleviating edema, and relieving cough. For the testability analysis, the high performance liquid chromatography(HPLC) and literature research were used to determine the 10 components in Polygoni Perfoliati Herba, and the fingerprints of Polygoni Perfoliati Herba were established at the same time. The specificity analysis was based on the statistics of the number of plants in which the components existed. Thereby, the 11 compounds: quercetin, oleanolic acid, ellagic acid, gallic acid, kaempferol, rutin, esculetin, quercetin-3-O-glucuronide, ursolic acid, protocatechuic acid, and ferulic acid, were identified as potential Q-markers. The 11 compounds were identified to have high anti-inflammatory activity, indicating that the 11 Q-markers may be the functional material basis. The result in this study is expected to serve as a reference for the quality control of Polygoni Perfoliati Herba.

[Research on Q-markers of Eupatorium lindleyanum based on analytic hierarchy process-entropy weight method and network pharmacology]

The potential quality markers( Q-markers) of Eupatorium lindleyanum were studied with analytic hierarchy process(AHP)-entropy weight method(EWM) and network pharmacological method. Based on the concept of Q-markers of traditional Chinese medicine, AHP-EWM was employed to quantitatively identify the Q-markers of E. lindleyanum. AHP method was applied to the weight analysis of the validity, testability, and specificity of the first-level indexes, and EWM method was used to analyze the secondlevel indexes supported by literature and experimental data. At the same time, based on the theory and method of network pharmacology, the component-target-disease-efficacy network of E. lindleyanum was built, and the components most closely related to the efficacy of resolving phlegm and relieving cough and asthma were screened out. Through the integrated analysis of the results obtained with AHP-EWM and network pharmacological method, 13 compounds including rutin, quercetin, nepetin, cirsiliol, luteolin, hyperoside,isoquercitrin, kaempferol, caffeic acid, eupalinolide K, eupalinolide A, eupalinolide B, and eupalinolide C were comprehensively identified as the potential Q-markers of E. lindleyanum. The results provide a basis for the quality control of E. lindleyanum.