RESUMO
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-MSE 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-MSE, 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.
Assuntos
Contaminação de Medicamentos , Animais , Cromatografia Líquida de Alta Pressão/métodos , Bile/química , Quimiometria/métodos , Coelhos , Bovinos , China , Suínos , Análise MultivariadaRESUMO
In the past few years, mass spectrometry imaging (MSI) has brought many new inspirations to plant research. However, current MSI experiments usually include only a single batch of samples, casting doubts on the reproducibility of phytochemical distribution across different batches. Consequently, MSI has seldom been applied to conduct species discrimination. In this experiment, MSI was employed to discriminate between two taxonomically similar plants, Scutellaria baicalensis Georgi and Scutellaria rehderiana Diels. A new concept termed a "spatial marker" was proposed in this article, which referred to the phytochemical marker that presented both intraspecies similarity and interspecies dissimilarity. Multiple batches of S. baicalensis and S. rehderiana were analyzed using MSI, proving that the authentication protocol using spatial markers was reliable and reproducible. The observed spatial markers were further identified using on-tissue tandem mass spectrometry and liquid chromatography coupled with mass spectrometry. Additionally, the spectral data collected from MSI were utilized to set up algorithm models for species discrimination. External validation confirmed that the established random forest model was extrapolated well to unknown samples. Overall, this investigation successfully explored the analytical applicability of MSI, facilitating rapid authentication of medicinal plants.