Background: Evaluating traditional Chinese medicine (TCM) quality is a powerful method to ensure TCM safety. TCM quality evaluation methods primarily include characterization evaluations and separate physical, chemical, and biological evaluations; however, these approaches have limitations. Nevertheless, researchers have recently integrated evaluation methods, advancing the emergence of frontier research tools, such as TCM quality markers (Q-markers). These studies are largely based on biological activity, with weak correlations between the quality indices and quality. However, these TCM quality indices focus on the individual efficacies of single bioactive components and, therefore, do not accurately represent the TCM quality. Conventionally, provenance, place of origin, preparation, and processing are the key attributes influencing TCM quality. In this study, we identified TCM-attribute-based quality indices and developed a comprehensive multiweighted multi-index-based TCM quality composite evaluation index (QCEI) for grading TCM quality. Methods: The area of origin, number of growth years, and harvest season are considered key TCM quality attributes. In this study, licorice was the model TCM to investigate the quality indicators associated with key factors that are considered to influence TCM quality using multivariate statistical analysis, identify biological-evaluation-based pharmacological activity indicators by network pharmacology, establish real quality indicators, and develop a QCEI-based model for grading TCM quality using a machine learning model. Finally, to determine whether different licorice quality grades differently reduced the inflammatory response, TNF-α and IL-1β levels were measured in RAW 264.7 cells using ELISA analysis. Results: The 21 quality indices are suitable candidates for establishing a method for grading licorice quality. A computer model was established using SVM analysis to predict the TCM quality composite evaluation index (TCM QCEI). The tenfold cross validation accuracy was 90.26%. Licorice diameter; total flavonoid content; similarities of HPLC chromatogram fingerprints recorded at 250 and 330 nm; contents of liquiritin apioside, liquiritin, glycyrrhizic acid, and liquiritigenin; and pharmacological activity quality index were identified as the key indices for constructing the model for evaluating licorice quality and determining which model contribution rates were proportionally weighted in the model. The ELISA analysis results preliminarily suggest that the inflammatory responses were likely better reduced by premium-grade than by first-class licorice. Conclusions: In the present study, traditional sensory characterization and modern standardized processes based on production process and pharmacological efficacy evaluation were integrated for use in the assessment of TCM quality. Multidimensional quality evaluation indices were integrated with a machine learning model to identify key quality indices and their corresponding weight coefficients, to establish a multiweighted multi-index and comprehensive quality index, and to construct a QCEI-based model for grading TCM quality. Our results could facilitate and guide the development of TCM quality control research.

In the regulatory market, it is not uncommon for ginseng radix et rhizoma (GR) to be adulterated with panacis quinquefolii radix (PR). Amid the digital transformation, this study puts forward a new method for the identification of GR adulterated with PR. Ultra-high-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used to detect multiple batches of GR and PR to obtain mass spectrometry data. The common ions were isolated from multiple batches of GR and PR, serving as GR and PR’s “ion matrices”. Furthermore, GR and PR’s “ion matrices” were used to eliminate intersecting ion data to extract the top-100 ions as GR and PR “matrix identity cards” (MICs). Then, GR and PR’s MICs were employed as a reference for identification, yielding contrast credibility (CC) as feedback. The results indicated that leveraging the MICs of GR and PR enables efficient and precise digital identification of the two herbs: pure GR showed CC ≥ 95% when matched with GR MIC (≤2% with PR MIC), pure PR showed CC ≥ 93% with PR MIC (≤3% with GR MIC), and non-parametric analysis confirmed significant differences between groups (p < 0.01). Even in 5% PR-adulterated samples, CC ranged from 24% to 28% (avg. 25.8%) when matched with PR MIC, leading to a 26% adulteration detection threshold. Moreover, two adulterated batches were identified among ten GR blind samples, which was consistent with verification via PR-specific pseudo-ginsenoside F₁₁. This research is practically valuable for distinguishing between GR and PR, combating adulteration, and reinforcing GR quality management. It also informs the digital identification of GR via UPLC-QTOF-MS and “MICs”, contributing to the digital quality control of traditional Chinese medicines (TCMs).

Natural compounds have experienced increasing clinical application, but their association with rapid-onset anaphylactoid reactions (ARs) present a significant challenge to their safe use. These ARs, clinically resembling Type I hypersensitivity, are non-IgE-mediated and involve direct mast cell activation, primarily through the human Mas-related G protein-coupled receptor X2 (MRGPRX2). We computationally screened a natural compound library for MRGPRX2 activation. A human MRGPRX2-expressing cell model was established. Cell viability assays (0–80 μM) were performed to determine appropriate drug concentrations. Compared to the controls, Baohuoside I (10 μM), along with Kaempferol-3-O-rutinoside, Epigallocatechin gallate (EGCG), Isochlorogenic Acid B, Baicalin, Andrographolide, Isorhamnetin, and Dehydroandrographolide (all at 20 μM), significantly increased intracellular calcium flux (p < 0.05) and boosted tryptase and β-hexosaminidase secretion (ELISA) (p < 0.05) in mast cells. Furthermore, the degranulation induced by these compounds was inhibited by the MRGPRX2 inhibitor Z3578 at 20 μM. Neutral red staining was employed to observe cellular morphological changes. Specific compounds capable of mediating ARs through MRGPRX2 activation on mast cells were identified. This contributes to safer and more effective drug use by elucidating the potential triggers of ARs.

This study aims to explore the anti-inflammatory pharmacological components and anti-inflammatory mechanisms of the alcohol extract of Saposhnikoviae Radix (SR). The components of the alcohol extract of SR were analyzed using the UPLC-MS/MS system. The anti-inflammatory efficacy of the alcohol extract and core components of SR was evaluated using the LPS-induced inflammation model of RAW264.7 cells. The anti-inflammatory mechanism of SR in a mouse model of rheumatoid arthritis was expounded by means of serum metabolomics, network pharmacology, and molecular docking. A total of 12 chromones and 13 coumarins were identified in the alcohol extract of SR. The alcohol extract of SR and its components all had good anti-inflammatory activities. In the mouse model of rheumatoid arthritis, the glycoside compounds of SR were transformed into aglycones, thereby exerting anti-inflammatory effects. Moreover, the alcohol extract of SR alleviated the inflammatory response by up-regulating the expression levels of metabolites such as phenylalanine and tyrosine. Network pharmacology and molecular docking results show that SR could exert an anti-inflammatory effect by regulating AGE-RAGE, PI3K-Akt, TNF, MAPK, and Toll-like signaling pathways. In this study, the anti-inflammatory efficacy and mechanisms of the alcohol extract of SR are explored, with the aim of providing a reference for subsequent research.

Puerariae Lobatae Radix (PLR) is a commonly used herbal medicine in traditional Chinese medicine, whereas Puerariae Lobatae Caulis (PLC), its aerial part, is frequently utilized as an adulterant due to similar morphological features. Conventional identification methods and pharmacopoeial criteria fail to effectively distinguish these two homologous herbs, creating a demand for a precise identification method. Therefore, a Digital ID method was established for their identification. UPLC-QE-Orbitrap-MS coupled with Progenesis QI software was applied to analyze multi-batch samples of PLR and PLC. Common ion information was extracted, and a differential ion matrix was constructed after eliminating blank ions and cross-shared components. High-intensity characteristic ions were defined as exclusive Digital ID for authenticity identification. The Matching Confidence (MC) values of both herbs matching their own Digital IDs were >85%, while cross-matching MC values were <4%. Unlike subjective macroscopic authentication, compendial TLC and single-marker quantification that fail to discriminate the two materials, and spectroscopic methods incompatible with powdered samples, this digital ID framework enables automated objective authentication via quantitative Matching Confidence without manual spectral comparison. This technique achieves accurate and efficient digital identification of the two herbs, facilitating the quality control of PLR and offering a new strategy for the quality assessment of traditional Chinese medicine (TCM).