ABSTRACT
OBJECTIVE To establish the fingerprint of Qiguiling mixture and the method for the content determination of 4 kinds of active components such as calycosin-7-glucoside， so as to control the quality of Qiguiling mixture. METHODS The fingerprints of 12 batches of Qiguiling mixture were established by HPLC. SPSS 25.0 software was used for cluster analysis and principal component analysis， and SIMCA 14.1 software was used for orthogonal partial least squares-discriminant analysis. The variable importance in projection （VIP） value greater than 1.0 was used as the index to screen the differential components. The contents of calycosin-7-glucoside， glycyrrhizin and glycyrrhizic acid were calculated by the quantitative analysis of multi- components by single marker （QAMS） with hesperidin as the internal reference， and the results were compared with external standard method. RESULTS In the fingerprints of 12 batches of samples， 17 common peaks were identified， and the similarities were more than 0.940. A total of 4 common peaks were identified， which were calycosin-7-glucoside （peak 6）， glycyrrhizin （peak 8）， hesperidin （peak 12）， and glycyrrhizic acid （peak 17）. The 12 batches of samples could be clustered into two categories， S4， S7-S9 and S11-S12 were clustered into one category， and the other batches of samples were clustered into one category. The cumulative variance contribution rate of the six principal components was 85.840%， and VIP values of peaks 15， 14， 4， 8 （glycyrrhizin） and 9 were all greater than 1.0. The relative error between the results of QAMS and external standard method was less than 5% （n＝3） for the contents of calycosin-7-glucoside， glycyrrhizin and glycyrrhizic acid. CONCLUSIONS Established HPLC fingerprint and content determination method in this study can be used for quality control of Qigiling mixture. Five components such as glycyrrhizin are the differential components.
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OBJECTIVE To optimize extraction technology of couplet medicinals of Astragalus membranaceus-Puerariae lobatae. METHODS With contents of puerarin，daidzin，calycosin-7-O-β-D-glucopyranoside，daidzein，calycosin and formononetin and the yield of dry extract as index，the analytic hierarchy method was used to determine the weight coefficient of each index and calculate the comprehensive score. The effects of solid-liquid ratio， extraction times and extraction time on the comprehensive score were investigated by single factor test. The level of each factor was determined. By multi-index comprehensive scoring method， using comprehensive scores of above 7 indexes as indexes，the extraction technology of couplet medicinals of A. membranaceus-P. lobata was optimized by orthogonal experiment，and the validation tests were conducted. RESULTS The weight coefficient for the contents of puerarin，daidzin，calycosin-7-O-β-D-glucopyranoside，daidzein，calycosin and formononetin and the yield of dry extract were respectively 0.304 7，0.065 2，0.185 8，0.185 8，0.107 8，0.107 8 and 0.042 7. The optimal extraction technology was determined as follows： solid-liquid of 1∶8（g/mL），extracting 3 times and for 1 h each time. RSD of each evaluation index in the validation test results was lower than 3.00% （n＝3）. CONCLUSIONS The optimized extraction technology for A. membranaceus-P. lobata is stable and feasible.
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OBJECT IVE To provide scientific evidence for the quality standard research of Qingyi mixture （QM）qualitatively and quantitatively. METHODS The high performance liquid chromatography （HPLC）fingerprint of QM was established ，and the chemical pattern recognition analysis was carried out. At the same time ，the contents of 8 components such as chlorogenic acid in the preparation were determined. The determination was performed on Agilent SB-C 18 column with 0.1％ phosphoric acid-acetonitrile as mobile phase （gradient elution ）at the flow rate of 0.6 mL/min. The column temperature was 35 ℃，and detection wavelength was set at 254 nm. Similarity Evaluation System of Chromatographic Fingerprint of Traditional Chinese Medicine（2012 edition），SPSS 20.0 and SIMCA 14.1 were used to perform similarity evaluation ，cluster analysis （CA），principle component analysis （PCA）and orthogonal partial least squares-discriminant analysis （OPLS-DA）of QM samples. RESULTS A total of 22 common peaks were calibrated by 15 batches of QM ，and the similarity was over 0.975. Twenty-two common peaks were assigned and 8 of them were identified. CA ，PCA and OPLS-DA divided the 15 batches of QM into two categories. Meanwhile，5 differential components were screened out ，i.e. peak 9（cichoric acid ），peak 14（baicalin），peak 18，peak 19 and peak 21 （baicalein）. The contents of 8 components，such as chlorogenic acid ，ferulic acid ，cichoric acid ，hesperidin， baicalin，salvianolic acid B ，baicalein and paeonol ，were 0.077-0.094，0.165-0.190，0.100-0.114，0.083-0.107，0.556-0.615，0.288-0.314，0.152-0.188 and 0.114-0.128 mg/g，respectively. CONCLUSIONS The established HPLC fingerprint and content determination method can provide reference for the quality standard research of QM.
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OBJECTIVE：To establish HPLC fingerprint of Schisandra sph enanthera and S. chinensis，and to analyze chemical pattern recognition. METHODS ：HPLC method was adopted. Using schizandrin A as reference ，HPLC fingerprints of 10 batches of S. sphenanthera and S. chinensis （N1-N10，S1-S10） were drawn. Similarity Evaluation System of TCM Chromatographic Fingerprint（2012 edition）was adopted for similarity evaluation to determine the common peaks. SPSS 20.0 and SIMCA 14.1 software were used for HCA ，unsupervised madel of PCA ，supervised model of OPLS-DA. Using variable importance projection （VIP）value greater than 1 as the standard ，the differential markers that affected the quality of S. sphenanthera and S. chinensis were screened. RESULTS ：S. sphenanthera and S. chinensis were identified 32 and 33 common peaks ，respectively. The similarity of 10 batches of S. sphenanthera and 10 batches of S. chinensis were all higher than 0.9，and the similarity of S. sphenanthera and S. chinensis was 0.05. A total of 19 characteristics peaks were identified ，among which five common peaks were identified as schisandraol A ，schisandraol B ，schisantherin A ，schizandrin A and schisandrin B by reference. HCA results showed that N 1-N10 were clustered into one category ，and S 1-S10 were clustered into one category ，of which N 1，N3，N8，and N 9 were clustered into one category ，and the rest were clustered into one category ；S1，S3，S6，and S 9 were grouped together ，and the rest were grouped together. The results unsupervised model of PCA showed that the cumulative variance contribution rate of the first two principal component factors was 87.20％. Supervised model of OPLS-DA showed that schizandrin A ，schisandraol A ，schisantherin A and schisandrin B were the differential markers that affected 、the quality of S. sphenanthera and S. chinensis （VIPs were 2.29，2.24，1.73，1.48，respectively）. CONCLUSIONS ：The established fingerprint is accurate ，scientific，simple and easy to use ，combined with multivariate statistical analysis can be 话：0395-3356116。E-mail：wangrui56116@163.com used to evaluate the quality of S. sphenantherae and S. chinensis. The components of S. sphenanthera and S. chinensis were different ，schisanolrin A is differential marker.