Mentha haplocalyx (mint) is a significant traditional Chinese medicine (TCM) listed in the Catalogue of 'Medicinal and Food Homology', therefore, its geographical origins (GOs) are critical to the medicinal and food value. Laser-induced breakdown spectroscopy (LIBS) is an advanced analytical technique for GOs certification, due to the fast multi-elemental analysis requiring minimal sample pretreatment. In this study, LIBS data of sampled mint from five GOs were investigated by LIBS coupled with multivariate statistical analyses. The spectral data was analyzed by two chemometric algorithms, i.e. principal component analysis (PCA) and least squares support vector machines (LS-SVM). Specifically, the performance of LS-SVM with least kernel and radial basis function (RBF) kernel was explored in sensitivity and robustness tests. Both LS-SVM algorithms exhibited excellent performance of classification in sensitive test and good performance (a little inferior) in robustness test. Generally, LS-SVM with linear kernel equally outperformed LS-SVM based on RBF kernel. The result indicated the potential for future applications in herbs and food, especially for in situ GOs applications of TCM authenticity rapidly.

A synergetic strategy was proposed to address the critical issue in the brand characterization of Colla corii asini (Ejiao, CCA), a precious traditional Chinese medicine (TCM). In all brands of CCA, Dong’e Ejiao (DEEJ) is an intangible cultural heritage resource. Seventy-eight CCA samples (including forty DEEJ samples and thirty-eight samples from other different manufacturers) were detected by laser-induced breakdown spectroscopy (LIBS) and near-infrared spectroscopy (NIR). Partial least squares discriminant analysis (PLS-DA) models were built first considering individual techniques separately, and then fusing LIBS and NIR data at low-level. The statistical parameters including classification accuracy, sensitivity, and specificity were calculated to evaluate the PLS-DA model performance. The results demonstrated that two individual techniques show good classification performance, especially the NIR. The PLS-DA model with single NIR spectra pretreated by the multiplicative scatter correction (MSC) method was preferred as excellent discrimination. Though individual spectroscopic data obtained good classification performance. A data fusion strategy was also attempted to merge atomic and molecular information of CCA. Compared to a single data block, data fusion models with SNV and MSC pretreatment exhibited good predictive power with no misclassification. This study may provide a novel perspective to employ a comprehensive analytical approach to brand discrimination of CCA. The synergetic strategy based on LIBS together with NIR offers atomic and molecular information of CCA, which could be exemplary for future research on the rapid discrimination of TCM.

Context Zuojin Pill (ZJP) has been used to treat gastrointestinal problems in China for hundreds of years. Objective To discover more potential active ingredients and evaluate the gastroprotective mechanisms of ZJP. Materials and methods An approach involving UPLC-Q-Orbitrap HRMS and serum pharmacochemistry was established to screen the multiple chemical constituents of ZJP. Male Sprague-Dawley (SD) rats were divided into six groups: normal control, ulcer control, omeprazole (30 mg/kg), and three ZJP groups (1.0, 2.0 and 4.0 g/kg). After oral treatment with ZJP or omeprazole for 7 days, all groups except the normal control group were orally administered 5 mL/kg ethanol to induce gastric ulceration. Histopathological assessment of gastric tissue was performed by haematoxylin and eosin staining. Antioxidant parameters and inflammatory mediators were determined using ELISA Kit and immunohistochemical analysis. Results Ninety components were identified in ZJP. Among them, 23 prototypes were found in rat serum after oral administration of ZJP. The ulcer inhibition was over 90.0% for all the ZJP groups. Compared with the ulcer control rats, ZJP (4.0 g/kg) enhanced the antioxidant capacity of gastric tissue: superoxide dismutase (1.33-fold), catalase (2.61-fold), glutathione (2.14-fold), and reduced the malondialdehyde level (0.48-fold). Simultaneously, the ZJP meaningfully lowered the content of tumour necrosis factor-α (0.76-fold), interleukin-6 (0.66-fold), myeloperoxidase (0.21-fold), and nuclear factor kappa B (p65) (0.62-fold). Discussion and conclusions This study showed ZJP could mitigate ethanol-induced rat gastric ulcers, which might benefit from the synergistic actions of multiple ingredients. The findings could support the quality control and clinical trials of ZJP.