Magnolia officinalis Rehd. et Wils. and Magnolia officinalis Rehd. et Wils. var. biloba Rehd. et Wils, as the legal botanical origins of Magnoliae Officinalis Cortex, are almost impossible to distinguish according to their appearance traits with respect to medicinal bark. The application of AFLP molecular markers for differentiating the two origins has not yet been successful. In this study, a combination of e-nose measurements, e-tongue measurements, and chemical analyses coupled with multiple-source data fusion was used to differentiate the two origins. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were applied to compare the discrimination results. It was shown that the e-nose system presented a good discriminant ability with a low classification error for both LDA and QDA compared with e-tongue measurements and chemical analyses. In addition, the discriminating capacity of LDA for low-level fusion with original data, similar to a combined system, was superior or equal to that acquired individually with the three approaches. For mid-level fusion, the combination of different principals extracted by PCA and variables obtained on the basis of PLS-VIP exhibited an analogous discrimination ability for LDA (classification error 0.0%) and was significantly superior to QDA (classification error 1.67–3.33%). As a result, the combined e-nose, e-tongue, and chemical analysis approach proved to be a powerful tool for differentiating the two origins of Magnoliae Officinalis Cortex.

Background: Periplocae Cortex (PC), Acanthopanacis Cortex (AC), and Lycii Cortex (LC), as traditional Chinese medicines, are all dried root bark, presented in a roll, light and brittle, easy to break, have a fragrant scent, etc. Due to their similar appearances, it is tough to distinguish them, and they are often confused and adulterated in markets and clinical applications. To realize the identification and quality control of three herbs, in this paper, Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry Expression (UHPLC-QTOF-MS^E) combined with chemometric analysis was used to explore the different chemical compositions. Methods: LC, AC, and PC were analyzed by UHPLC-QTOF-MS^E, and the quantized MS data combined with Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were used to explore the different chemical compositions with Variable Importance Projection (VIP) > 1.0. Further, the different chemical compositions were identified according to the chemical standard substances, related literature, and databases. Results: AC, PC, and LC can be obviously distinguished in PCA and PLS-DA analysis with the VIP of 2661 ions > 1.0. We preliminarily identified 17 differential chemical constituents in AC, PC, and LC with significant differences (p < 0.01) and VIP > 1.0; for example, Lycium B and Periploside H2 are LC and PC’s proprietary ingredients, respectively, and 2-Hydroxy-4-methoxybenzaldehyde, Periplocoside C, and 3,5-Di-O-caffeoylquinic acid are the shared components of the three herbs. Conclusions: UHPLC-QTOF-MS^E combined with chemometric analysis is conducive to exploring the differential chemical compositions of three herbs. Moreover, the proprietary ingredients, Lycium B (LC) and Periploside H2 (PC), are beneficial in strengthening the quality control of AC, PC, and LC. In addition, limits on the content of shared components can be set to enhance the quality control of LC, PC, and AC.

Ginseng Radix et Rhizoma (GRR), Panacis Quinquefolii Radix (PQR), Notoginseng radix et rhizoma (NRR) and Platycodonis Radix (PR) are often confused in the material market because of similar appearances and characteristics. Moreover, chemical identification methods tend to characterize the whole herb with regard to a single or a few components, which is an inaccurate representation and does not demonstrate the effective utilization of unknown components, and the result is unconvincing. In order to strengthen quality control, improve identification efficiency, and realize digital identification at the individual level of traditional Chinese medicine (TCM), we have put forward the “matrix characteristics” of TCM, combined with a UHPLC-QTOF-MS analysis to explore and realize the digital identification of GRR, PQR, NRR, and PR. The mass spectrometry was quantized to extract common data from different batches of the same TCMs as their matrix characteristics, and the matching credibility (M) was given by matching the “matrix characteristics” with unknown Chinese medicines. The results show that within a reasonable parameter threshold range, the M of four TCMs was higher than 92.00% compared with their own “matrix characteristics”, which was significantly higher than the M ranked second. Furthermore, the digital identification of four TCMs can be successfully realized based on the UHPLC-QTOF-MS analysis and “matrix characteristics”. This has important reference significance for developing the digital identification of GRR at an individual level based on UPLC-QTOF-MS and “matrix characteristics”.

Background: As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals’ bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers’ rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MS^E and multivariate statistical analysis were used to explore the differences in XD and six other animals’ bile. Methods: XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MS^E, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. Results: The results showed that XD and six other animals’ bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals’ bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. Conclusions: The developed method was efficient and rapid in accurately distinguishing between XD and six other animals’ bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines.

In recent years, the hepatotoxicity of Polygoni Multiflora Radix (PMR) has attracted increased research interest. Some studies suggest that anthraquinone may be the main hepatotoxic component. Most of the relevant studies have focused on the mononuclear anthraquinone component rather than binuclear anthraquinones. The hepatotoxicity of dinuclear anthraquinone (dianthrone) was investigated in a cell-based model. Next, a method for the determination of six free and total dianthonones in PMR and PMR Praeparata (PMRP) was established using ultra-high-performance liquid chromatography triple quadrupole mass spectrometry (UPLC-QQQ-MS/MS), which was then used to analyze the collected samples. The data show that four binuclear anthraquinone compounds were hepatotoxic and may be potential toxicity indicators for the safety evaluation of PMR and PMRP. Herein, we provide a theoretical basis for the improvement of PMRP quality standards.