Overview and limitations of database in global traditional medicines: A narrative review.

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

Medcheck: a novel software for automated de-formulation of traditional Chinese medicine (TCM) prescriptions by liquid chromatography-mass spectrometry.

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Comprehensive HRMS Screening and Risk Assessments of Aristolochic Acid Analogues in Asari Radix et Rhizoma and Related Commercial Health Products.

Aristolochic acid analogues (AAAs) are well-known toxins. We performed the first comprehensive screening on AAAs in Asari Radix et Rhizoma (underground part of Asarum heterotropoides Schmidt), the only Aristolochiaceae plant widely used in clinical practice. LC-HRMS revealed 70 trace AAAs using polygonal mass defect filtering and precursor ion list strategies, 38 of which were newly discovered in A. heterotropoides. UHPLC-QTrap-MS/MS was then utilized for quantitative/semiquantitative analysis of 26 abundant compounds. Seventeen AAAs were detected from 91 batches of A. heterotropoides and 20 AAAs from 166 consumable products. For 141 Asari-containing proprietary products, aristolactam I and aristolactam II-glucoside exhibited the widest distribution, present in 98% products. AA IVa was the most abundant, detected in 91%. Notably, 60% of the products contained AA I (0.03-0.79 ppm). The safety was assessed using linear extrapolation, permitted daily exposure, cumulative amount, and the margin of exposure. It is recommended that AA I content be limited to 3 ppm.

MATLAB language assisted data acquisition and processing in liquid chromatography Orbitrap mass spectrometry: Application to the identification and differentiation of Radix Bupleuri from its adulterants.

Comprehensive and rapid analysis of secondary metabolites like saponins remains challenging. This study aimed to establish a semi-automated workflow for filtration, identification, and characterization of saikosaponins in six Bupleurum species. Radix Bupleuri, a high-sales herbal medicine, is often adulterated, restricting its quality control and applications. Two authentic Radix Bupleuri species and four major adulterants were analyzed through UHPLC-LTQ-Orbitrap-MS for targeted saikosaponin analysis. To reveal trace saikosaponins and obtain quality fragment data, a MATLAB-based process automatically enumerating "sugar chain + aglycone + side chain" combinations and deduplicating generated a predicted saikosaponin database covering all possible saikosaponins as a precursor ion list for comprehensive targeted acquisition. To focus on informative ions and reduce MS analysis workload, we utilized MATLAB to automatically filtrate the false positive ions by MS1 and MS2 spectrometry. The newly established MATLAB-assisted data acquisition approach exhibited 50 % improvement in characterization of targeted saikosaponins. Furthermore, positive and negative ionization workflows were designed for accurate saikosaponins characterization based on fragmentation rules. In total, 707 saikosaponins were characterized, including over 500 potential new compounds and previously unreported C29 aglycones. We identified 25 saikosaponins present in both authentic species but absent in adulterants as potential markers. This unprecedented comprehensive multi-origin species differentiation demonstrates the promise of MATLAB-assisted acquisition and processing to advance saponin identification and standardize the Radix Bupleuri market.