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.