Analysis reveals active compounds in Clinopodii Herba that improve anti-inflammatory activity in mouse models, suggesting a predictive approach for screening extracts.
Clinopodii Herba (CH) is a medicinal material from Anhui Province. In the study, high-performance liquid chromatography (HPLC) was used to build the fingerprint profiles of extracts from eight batches of CH with different processing methods. Similarity analysis, cluster analysis, and principal component analysis were performed on these extracts. A xylene-induced mouse ear edema model was used for pharmacodynamic evaluation of anti-inflammatory activity. Gray relational analysis (GRA) and partial least squares regression (PLSR) were employed to investigate the impact of CH extract components on ear edema and related inflammatory factors in mice. The experimental results demonstrated that 13 common peaks were identified in HPLC fingerprint profiles, and the eight batches of samples could be classified into three categories, with light exposure and temperature identified as the primary factors contributing to the variation among samples. GRA and PLSR analysis identified narirutin, hesperidin, and apigenin-7-O-glucuronide as the primary active components. The anti-inflammatory efficacy of the eight batches of CH extracts was confirmed, and a spectrum-effect relationship between the active components and the anti-inflammatory activity was established. This study provides an effective analytical approach for screening and forecasting the anti-inflammatory active ingredients of CH.
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Li et al. (2026) studied this question.
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