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Development of direct infusion quadrupole mass spectrometry database and intelligent identification system for 100 root herbs

文献类型：期刊论文

作者Wang, Jia-wei3,4; Liu, Xiao-kang3; Xu, Yan- bo3,4; Huang, Fei3; Xia, Ti-yu3,4; Jiang, Hui-ling3,4; Liu, Xiao- yu3; Zhang, Ming-jin3; An, Ya-ling3; Li, Zhen-wei3
刊名PHYTOMEDICINE
出版日期2025-10-01
卷号146页码:16
关键词DI-QDa-MS MS cosine similarity Root and rhizome traditional Chinese medicine Machine learning Automated authentication
ISSN号0944-7113
DOI10.1016/j.phymed.2025.157114
通讯作者Guo, De-an(daguo@simm.ac.cn)
英文摘要Background: Counterfeiting is widespread in the herbal medicine market, especially for roots and rhizomes. Current authentication methods for these herbs remain limited and subjective, posing challenges to quality assurance and authenticity verification. Purpose: To overcome the limitations of low efficiency and high subjectivity in traditional identification methods for root and rhizome traditional Chinese medicine (RRTCM), this study aims to develop a high-throughput intelligent identification system based on direct infusion QDa mass spectrometry (DI-QDa-MS) for the rapid and objective identification of 100 RRTCM, including 88 herbal medicines and 12 processed products. Methods: MS data of 100 RRTCM were acquired using DI-QDa-MS. An automated data processing pipeline was developed via machine learning and cosine similarity algorithms, alongside the establishment of a standardized DI-QDa-MS database and feature ion library. This study innovatively developed three intelligent identification methods: k-nearest neighbor (KNN) model, MS similarity analysis, and binary coding. Their accuracy and computational efficiency were systematically validated using 105 batches of blind samples. Results: All three methods achieved validation success rates >= 95 %, with MS similarity analysis performing optimally. This established a standardized workflow for intelligent identification of 100 RRTCM based on MS similarity. Inter-day and intra-day precision values were both <3 %, confirming the reliability of the methods. Conclusion: The identification technique proposed in this study, which leverages the cosine similarity algorithm, establishes a high-throughput approach for standardizing RRTCM quality. This method contributes to strengthening TCM market regulation and advancing TCM quality standards.
资助项目Sanming Project of Medicine in Shenzhen[SZZYSM202106004] ; Qi-Huang Chief Scientist Program of National Administration of Traditional Chinese Medicine (2020)
WOS研究方向Plant Sciences ; Pharmacology & Pharmacy ; Integrative & Complementary Medicine
语种英语
WOS记录号WOS:001580361800014
出版者ELSEVIER GMBH
源URL[http://119.78.100.183/handle/2S10ELR8/321570]  
专题中国科学院上海药物研究所
通讯作者Guo, De-an
作者单位1.Shanghai Univ Tradit Chinese Med, Shanghai 201203, Peoples R China
2.Shanghai Inst Mat Med, Chinese Acad Sci, Shanghai Res Ctr Modernizat Tradit Chinese Med, Natl Engn Res Ctr TCM Standardizat Technol, Shanghai 201203, Peoples R China
3.Chinese Acad Sci, Zhongshan Inst Drug Discovery, Shanghai Inst Mat Med, Zhongshan 582400, Peoples R China
4.Guangdong Pharmaceut Univ, Sch Pharm, Dept Pharmaceut, Guangzhou 510006, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Jia-wei,Liu, Xiao-kang,Xu, Yan- bo,et al. Development of direct infusion quadrupole mass spectrometry database and intelligent identification system for 100 root herbs[J]. PHYTOMEDICINE,2025,146:16.
APA Wang, Jia-wei.,Liu, Xiao-kang.,Xu, Yan- bo.,Huang, Fei.,Xia, Ti-yu.,...&Guo, De-an.(2025).Development of direct infusion quadrupole mass spectrometry database and intelligent identification system for 100 root herbs.PHYTOMEDICINE,146,16.
MLA Wang, Jia-wei,et al."Development of direct infusion quadrupole mass spectrometry database and intelligent identification system for 100 root herbs".PHYTOMEDICINE 146(2025):16.

入库方式： OAI收割

来源：上海药物研究所

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