Abstract

AimTo verify the effects of modified Gengnianchun formula (MGNC), a traditional Chinese medicine, on a stressed diminished ovarian reserve (DOR) animal model and predict the underlying mechanisms through network pharmacology strategies.MethodsSexually mature female C57BL/6 mice were allocated to five groups, abbreviated as the control (C) group, stress manipulated model (M) group, stress with normal saline gavage (N) group, stress with low-dose MGNC gavage (L) group, and stress with high-dose MGNC gavage (H) group. Body weight and the estrous cycle were monitored during the stress and gavage process. Serum stress hormones and reproductive hormones were evaluated by ELISA. Ovarian follicle counts were calculated, and ovarian follicle-stimulating hormone receptor (FSHR) and anti-Müllerian hormone (AMH) expression were assessed by Western blotting and immunohistochemistry. Network pharmacology strategies included active compound screening, drug and disease target analysis, gene ontology analysis, pathway analysis, and visualization of results.ResultsMGNC treatment significantly decreased serum corticosterone (CORT) and follicle-stimulating hormone (FSH) levels and increased testosterone (T) levels in the H group compared with the M and N groups. Primordial and preantral follicle counts and ovarian AMH and FSHR expression were significantly increased in the H group compared to those in the M and N groups. Through pharmacokinetic screening, we found 244 active compounds in MGNC. A total of 186 candidate intersection target genes of disease and MGNC were further screened to construct the interaction network. Gene ontology and KEGG pathway enrichment analysis ultimately unveiled a series of key targets that mainly mediated the effects of MGNC on DOR induced by chronic stress. The PI3K-Akt pathway may serve as the critical pathway underlying this therapeutic mechanism.ConclusionMGNC is a promising formula to treat DOR induced by chronic stress, and the PI3K-Akt pathway may play an essential role in this effect.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call