Systematical targeted multicomponent characterization and comparison of Arnebiae Radix and its three confusing species by offline two-dimensional liquid chromatography/LTQ-Orbitrap mass spectrometry.

Arnebiae Radix, commonly known as "Zicao," can be easily confused with other compounding species, posing challenges for its clinical use. Here, we developed a comprehensive strategy to systematically characterize the diverse components across Arnebiae Radix and its three confusing species. First, an offline two-dimensional liquid chromatography (2D-LC) system integrating hydrophilic interaction chromatography (HILIC) and reverse phase (RP) separations was established, enabling effective separation and detection of more trace constituents. Second, a polygonal mass defect filtering (MDF) workflow was implemented to screen target ions and generate a precursor ion list (PIL) to guide multistage mass (MSn) data acquisition. Third, a three-step characterization strategy utilizing diagnostic ions and neutral losses was developed for rapid determination of molecular formulas, structure classes, and compound identification. This approach enabled systematic characterization of Arnebiae Radix and its three confusing species, with 437 components characterized including 112 shikonins, 22 shikonfurans, 144 phenolic acids, 131 glycosides, 18 flavonoids, and 10 other compounds. Additionally, 361, 230, 340, and 328 components were identified from RZC, YZC, DZC, and ZZC, respectively, with 142 common components and 30 characteristic components that may serve as potential markers for distinguishing the four species. In summary, this is the first comprehensive characterization and comparison of the phytochemical profiles of Arnebiae Radix and its three confusing species, advancing our understanding of this herbal medicine for quality control.

DNA copy number gain-mediated lncRNA LINC01061 upregulation predicts poor prognosis and promotes papillary thyroid cancer progression.

Several DNA copy number amplifications (CNAs) have been reported in papillary thyroid cancer (PTC). However, the functional role of CNAs in PTC remains very unclear. And whether there is a correlation between long noncoding RNA (lncRNA) and CNA requires to be explored. Here, we identified a novel lncRNA LINC01061. The genomic copy number of LINC01061 is amplified, which leads to its elevated expression level in PTC tissues. Moreover, increased level of LINC01061 was correlated with aggressive clinicopathological characteristics. Functional study indicated that LINC01061 silence significantly inhibited the proliferation, cell-cycle and invasion of PTC cells in vitro and tumor growth in vivo. Mechanistically, we showed that LINC01061 interacted with miR-4316 to promote E2F6 expression. The expression of miR-4316 was downregulated in PTC tissues while that of E2F6 was upregulated. Through rescue assay, we demonstrated that LINC01061 promoted PTC cell proliferation, cell-cycle progression and invasion by regulating miR-4316/E2F6 signaling pathway. In conclusion, our research indicated that LINC01061 might be a target for PTC therapy.

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.