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Published on: December 23, 2022
Screening for anti-dysmenorrhea components of Wenjing decoction: spectrum-effect relationship analysis, and efficacy
Miaomiao Zhang1, Xiuying Chen2, Hongping Long3
1The First Hospital of Hunan University of Chinese Medicine, Changsha, 410007, China.
Ethnopharmacological Relevance:
Primary dysmenorrhea (PD) is common and has a major impact on women's daily activities and quality of life. Wenjing decoction (WD), a classic Chinese medicine formula, has been widely used for thousands of years in China to treat PD. However, the key pharmacodynamic substances in WD responsible for its anti-dysmenorrhea efficacy are still unclear.
Aim Of The Study:
This study aimed to screen WD for anti-dysmenorrhea components using the spectrum-effect relationship analysis and validate their efficacy equivalence.
Methods:
The chemical composition of WD was identified using ultra-high-performance liquid chromatography quadrupole-time-of-flight tandem mass spectrometry (UHPLC-Q-TOF-MS). Fingerprints for 10 batches of WD were established, yielding data for 70 common peaks in positive ion mode and 95 in negative ion mode. A mouse PD model was induced using estradiol benzoate and oxytocin. Mice were then treated with the 10 WD batches. Parameters recorded included writhe latency (WL) and writhe count (WC) within 30 min. Levels of prostaglandin F2α (PGF2α) and prostaglandin E2 (PGE2) in uterine tissue, as well as arginine vasopressin (AVP) and β-endorphin in serum, were measured using enzyme-linked immunosorbent assay (ELISA). Expression levels of estrogen receptor β (ERβ), progesterone receptor (PR), and oxytocin receptor 1 (OTR1) in uterine tissues were assessed via quantitative polymerase chain reaction (qPCR). Pathological changes were evaluated by hematoxylin and eosin (HE) staining. These assessments yielded data on the efficacy of anti-dysmenorrhea. Multiple efficacy indicators were integrated into a composite index using the entropy-weighted TOPSIS method. Pearson correlation analysis and partial least squares regression (PLSR) were applied to analyse the spectrum-effect relationship between fingerprint data and the composite anti-dysmenorrhea data, identifying potential active components. Finally, the anti-dysmenorrhea effect of the identified component complex was validated in a separate animal experiment.
Results:
UHPLC-Q-TOF-MS identified 87 chemical components in WD. Spectrum-effect relationship analysis indicated that 20 components-licoricesaponine A3, licoricesaponine B2, isoliquiritin, neoliquiritin, neoisoliquiritin, liquiritinapioside, isoliquiritin apioside, licoisoflavone A, paeoniflorin, albiflorin, benzoylpaeoniflorin, benzoylalbiflorin, benzoyloxypaeoniflorin, mudanpioside C, albiflorin R1, achyranthoside E, 25R-inokosterone, 25S-inokosterone, ginsenoside Rg1, and ginsenoside Rg2-significantly contributed to WD's anti-dysmenorrhea effect and are considered its key active components. Efficacy equivalence validation showed no statistically significant differences (all P > 0.05) in the efficacy parameters between the active complex group and the WD low-dose group, confirming that these 20 components collectively form WD's anti-dysmenorrhea component complex.
Conclusion:
This study clarified the key active components of WD against PD, providing valuable insights for the clinical application and pharmaceutical development of WD, as well as a methodological reference for exploring the pharmacodynamic material basis of other traditional Chinese medicines.
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