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: Mahuang Fuzi decoction (MGF) is composed of three herb medicines that has been clinically used to treat inflammatory diseases for a long history. At present, more and more active phytochemicals’ aggregations have been found during the thermodynamic process of herb medicine decoction, and revealing the clinical efficacy of herb medicine through supramolecular strategies is the focus of current research. However, it is not clear whether decoction induced supermolecules’ morphological changes to modify activity. Methods: Dynamic light scattering (DLS) and field emission scanning electron microscopy (FESEM) were used to analyze the micromorphology of MGF, MGF SA (MGF supermolecules), and MIX (physical mixture of MGF single decoction). The interaction and thermodynamic parameters of single herbs in a decoction were investigated by Isothermal titration calorimetry (ITC). The phytochemicals were systematically analyzed by ultra high performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS). Under the safe dose on RAW264.7 cells, NO, IL-6 and TNF-α were determined by Enzyme-Linked ImmunoSorbent Assay (ELISA) method. NF-κB p65 translocation from the cytoplasm into the nucleus was examined using the immunofluorescence assay and the western blot, respectively. Furthermore, Metabolomics was used to discover potential biomarkers and the associated metabolic pathways of MGF SA treatment. Results: There were nanoscale aggregations in MGF, and the micromorphology of the extracted MGF SA consisted of uniform particles; while the MIX micromorphology had no uniformity. ITC showed that the interaction MH-GC and FZ-GC were a spontaneous exothermic reaction, indicating that their phytochemicals had the property of self-assembly. Though the micromorphology between MGF, MGF SA, and MIX was obviously different, UHPLC-Q-Orbitrap HRMS results displayed that the main phytochemicals of MGF and MIX had nearly the same components. Interestingly, MGF and MGF SA could significantly inhibit the production of NO, and had better inhibition effect on the expression of nuclear protein NF-κB p65 than MIX, among which MGF SA had the best effect. Further investigation indicated that the perturbance of metabolic profiling in RAW264.7 inflammatory cells was obviously reversed by MGF SA. Conclusions: The decoction enriched the key active phytochemicals and regulated the formation of homogeneous nanoparticles in MGF SA. The supermolecules in MGF SA significantly enhanced its anti-inflammatory activity, primarily affecting the NF-κB signaling pathway and the biosynthesis and metabolism of arginine in RAW264.7 inflammatory cells. Current study displayed that co-decocting herbal medicine were beneficial to the treatment of diseases than the mixture of the single herbs’ extraction. Graphical

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”.