LC-MS analysis of traditional medicines

Traditional medicines, including Chinese herbal medicine, Tibetan medicine, Mongolian medicine, and Indian Ayurveda, are chemically complex systems that adopt one or more plants and may also contain animal-derived materials, minerals, or microorganisms. Their therapeutic effects, safety profiles, and quality characteristics are influenced by numerous bioactive components, metabolites, impurities, additives, and toxic components. However, their comprehensive characterization remains challenging because of structural diversity, limited reference standards, as well as variability arising from species, geographic origin, processing, preparation, and storage. Conventional analytical approaches often lack the selectivity and high-efficiency. Recent advances in liquid chromatography–mass spectrometry (LC–MS), particularly high-resolution mass spectrometry, have enabled broader chemical profiling, improved detection of trace components, and more confident characterization of complex traditional medicine matrices. Nonetheless, challenges remain in the annotation of unknowns, discrimination of isomers, harmonization of workflows, use of appropriate reference libraries, and validation of quantitative methods. Further research is needed to establish reliable and comparable LC–MS strategies that support chemical, pharmacological, toxicological, and clinical investigations of traditional medicines.This Research Topic aims to advance the qualitative and quantitative analysis of bioactive components, impurities, additives, and toxins in traditional medicines using LC–MS technologies. It will address the development and application of robust analytical workflows for complex traditional medicine products and their preparations, while encouraging transparent reporting of identification confidence, validation procedures, and analytical limitations. Studies may investigate solvent extracts, solvent-free extracts, biological samples, and metabolites generated following treatment in humans, animals, cells, or microorganisms. Particular interest will be given to research that applies appropriate reference or standard libraries, clearly reports identification levels, follows fit-for-purpose principles for quantitative validation, and provides comprehensive MS-based structural elucidation, including the differentiation of isomers where possible.To offer insights into LC–MS-based characterization, authentication, quality control, safety evaluation, and metabolism of traditional medicines, this Research Topic welcomes articles addressing, but not limited to, the following themes:• LC–MS-based qualitative profiling and annotation of traditional medicine components• Targeted and untargeted quantification of bioactive components• Development and application of spectral, network, and standard-reference libraries• Structural elucidation and discrimination of isomeric components• Detection and characterization of impurities, adulterants, and additives• Screening and risk assessment of toxic components and contaminants• Metabolomic analysis of traditional medicine extracts and preparations• Biotransformation and metabolite profiling in humans, animals, cells, or microorganisms• Method development, optimization, and fit-for-purpose validation for LC–MS analysis• Quality control, authentication, consistency assessment, and batch-to-batch comparison• Comparative chemical analysis of traditional medicines from different regions, species, or processing methods• Integration of LC–MS data with pharmacological, toxicological, or clinical evidenceAppendix: The Research Topic welcomes original research, review, and short communication manuscripts. For qualitative analysis, submissions are encouraged to use realistic and highly comparable standard libraries to support confident identification, preferably at Level 1 where appropriate. Network-based libraries may also be used, provided that the identification level is clearly reported. Quantitative LC–MS studies may apply selected validation experiments according to the fit-for-purpose principle. Research involving comprehensive MS-based structural elucidation and isomer discrimination will be preferentially considered for acceptance. Topic editors: Xican Li, Rongxin Cai Source: https://www.frontiersin.org/research-topics/86674/lc-ms-analysis-of-traditional-medicines