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ObjectiveTo study the potential quality marker （Q-marker） of Tinosporae Radix associated with efficacy of "relieving sore throat" based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF-MS）， multivariate statistical analysis （MSA）， and network pharmacology. MethodUPLC-Q-TOF-MS was used to identify the main chemical components in 18 batches of Tinosporae Radix. On this basis， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） were employed to screen out the main marker components that caused differences between groups. Moreover， network pharmacology technology was applied to predict the potential "sore throat-relieving" components， and the molecular docking between the common components resulting from MSA and network pharmacology and the core targets was carried out to verify the marker components. ResultA total of 17 compounds， including alkaloids， diterpenoid lactones， and sterols， were identified by UPLC-Q-TOF-MS. Five main differential components were found by MSA： Columbamine， jatrorrhizine， palmatine， menisperine， and columbin. Network pharmacology analysis yielded six compounds： tetrahydropalmatine， palmatine， menisperine， fibleucin， neoechinulin A， and columbin which were selected as potential "sore throat-relieving" components of Tinosporae Radix. They may relieve sore throat by acting on interleukin-6， epidermal growth factor receptor， prostaglandin G/H synthase 2， matrix metalloproteinase-9， proto-oncogene tyrosine-protein kinase Src and other targets， and regulating Hepatitis B， influenza A， human T-cell virus infection， human cytomegalovirus infection， coronavirus disease-2019， and other signaling pathways. The common active components in Tinosporae Radix resulting from MSA and network pharmacology analysis were palmatine， menisperine， and columbin， which had high binding affinity with six core targets and can be used as the Q-marker components of Tinosporae Radix in "relieving sore throat". ConclusionThis study predicts the "sore throat-relieving" Q-marker of Tinosporae Radix， which lays a basis for developing the quality standard of Tinosporae Radix based on the efficacy and improving the quality evaluation system of the medicinal.
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OBJECTIVE：To esta blish a method for determining the contents of lupenone and stigmasterol in the rhizome ，stem and leaf of Mosa basjoo from the same plant ，and to provide reference for the substitute resource for the effective components of M. basjoo . METHODS ：UPLC method was adopted. The determination was performed on Zorbax Rrhd Eclipse Plus C 18 column （100 mm×2.1 mm，1.8 μm）with mobile phase consisted of acetonitrile-methanol （78.5∶21.5，V/V）. The detection wavelength was set at 210 nm；the flow rate was 0.15 mL/min；the column temperature was 30 ℃ and the sample size was 1 μL. The results of content determination of lupinone and stigmasterol in the rhizome ，stem and leaf of 9 batches of M. basjoo from the same plant were analyzed by the methods of comparative analysis between groups ，principal component analysis and cluster analysis. RESULTS：The mass concentration of lupenone and stigmasterol had a good linear relationship with the corresponding peak area within the range of 11.16-357.10 and 8.83-160.40 g/mL（R2 were 0.999 2 and 0.999 1，respectively）. RSDs of precision ， repeatability and stability tests were all less than 3％. The average recovery rates of lupenone and stigmasterol were 101.44％ and 98.32％，and the RSDs were 1.77％ and 1.81％（n＝6），respectively. The average contents of lupenone and stigmasterol in stems of M. Basjoo were significantly higher than those of rhizome and leaves of M. basjoo （P＜0.05）. There was no statistical significance in the contents of lupenone and stigmasterol between stem and leaf of M. basjoo from same plant （P＞0.05）. Results of principal component analysis showed that the contents of lupanone and stigmasterol were different in rhizome ，stem and leaf of M. basjoo from the same plant. Rhizome ，stem and leaf of M. basjoo were divided into three types through cluster analysis ，among which the rhizome had significant difference with the other two parts. CONCLUSIONS ：The method is simple ，rapid，specific， reproducible and accurate. It can be used for the content determination of lupenone and stigmasterol in different parts of M. basjoo . The stem of M. basjoo can replace the rhizome of M. basjoo as the source of lupinone and stigmasterol.
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OBJECTIVE： To establish a UPLC fingerprint of Ficus tikoua. METHODS： UPLC method was adopted. The determination was performed on Waters ACQUITY UPLC BEF C18 column with mobile phase consisted of 0.2％ aqueous acetic acid-acetonitrile （gradient elution）； the detection wavelength was 254 nm； the flow rate was 0.1 mL/min； the column temperature was 25 ℃， and sample size was 2 μL. UPLC fingerprints of 10 batches of samples and 2 batches of adulterants were determined by using No. 14 peak as reference. The similarity evaluation was carried out by using the TCM Chromatographic Fingerprint Similarity Evaluation System （2012 edition） so as to determine common peak. The cluster analysis was performed by using SPSS 20.0 software. SIMCA 13.1 software was used to conduct the principal component analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）. RESULTS： There were 28 common peaks in UPLC fingerprint of 10 batches of F. tikoua. The similarity of 10 batches of F. tikoua was between 0.839 and 0.935， and the similarities of the 2 batches of adulterants were 0.503 and 0.173 respectively， which indicated that F. tikoua could be distinguished from adulterants. 10 batches of F. tikoua could be divided into 2 categories by cluster analysis and principle component analysis， and S3-S5， S9 and S10 were grouped into one category， and the remaining batches were grouped into one category. 7 components with a variable importance in projection （VIP） value ＞1 were screened by OPLS-DA analysis. These 7 components may be the main components that caused the quality difference of 10 batches of F. tikoua samples. CONCLUSIONS： Established fingerprint， cluster analysis， principle component analysis and OPLS-DA can be used for the identification and quality control of F. tikoua.