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Updated: Mar 17, 2026

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis
Published on: November 11, 2022
Integrated Ultra-High Performance Liquid Chromatography-High-Resolution Mass Spectrometry, Chromatographic
Chunhua Liu1,2, Yuyu Wang1,2, Jiali Xie1,2
1State Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Engineering Research Center for the Development and Application of Ethnic Medicine and TCM (Ministry of Education), Guizhou Key Laboratory of Modern Traditional Chinese Medicine Creation, Guizhou Provincial Engineering Research Center for the Development and Application of Ethnic Medicine and TCM, Guizhou Medical University, Guian New Area, China.
None:
Lysionotus pauciflorus Maxim. is a traditional Chinese medicinal herb with antitussive, antiasthmatic, and antioxidant activities. However, systematic studies on its quality control methods remain limited, which restricts its further development and application. In this study, an integrated strategy combining separation and analytical techniques with chemometric methods was established to screen quality markers related to the antiasthmatic activity of L. pauciflorus. The chemical constituents of the extracts were systematically characterized using ultra-high performance liquid chromatography coupled with Orbitrap high-resolution mass spectrometry, and plasma pharmacochemistry was employed to investigate potential in vivo bioactive constituents. In addition, high-performance liquid chromatography fingerprint profiles of samples from different batches were established. Principal component analysis and orthogonal partial least squares discriminant analysis were applied to identify key differential components. To evaluate antioxidant activity and link it with chemical constituents, radical scavenging assays combined with high-performance liquid chromatography with diode array detection were conducted to identify potential antioxidant-related components. Furthermore, network pharmacology and molecular docking were used to construct a compound-target interaction network, from which candidate components related to antiasthmatic effects were screened. By integrating all the above results, a multidimensional "spider-web model" was constructed, and the regression area of each component was calculated to evaluate its overall contribution. Ultimately, eight quality markers were identified: chlorogenic acid, neochlorogenic acid, nevadensin 5-gentiobioside, nevadensin 5-O-β-D-glucopyranoside, forsythoside B, paraboside B, acteoside, and lysionotin.
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