2026-10-15T02:21:30Z https://www.scidb.cn/oai

10.57760/sciencedb.j00217.13788 2026-06-25T11:04:38Z

2026-06-25 Regulation of Ovarian Function by Macrophage Polarization and Research Progress of Traditional Chinese Medicine doi:10.57760/sciencedb.j00217.13788 en Macrophages, as a key component of the immune system, exhibit high plasticity and can polarize into pro-inflammatory M1 or anti-inflammatory M2 phenotypes in response to different microenvironmental signals. They play essential regulatory roles in ovarian physiological processes, including follicular development, ovulation, luteal formation, and luteal regression. Increasing evidence suggests that macrophage polarization imbalance is closely associated with ovarian diseases such as PCOS,POI, and ovarian cancer. In PCOS, excessive M1 polarization contributes to chronic inflammation and ovulatory dysfunction. In POI, M1 macrophages accelerate ovarian aging, whereas M2 macrophages exhibit dual roles: on the one hand, they exert anti-inflammatory and tissue-repairing effects that help preserve ovarian function; on the other hand, they may promote ovarian stromal fibrosis and thereby accelerate ovarian functional decline. In ovarian cancer, M2 polarization facilitates tumor progression, angiogenesis, and chemoresistance, while M1 macrophages exert anti-tumor effects. In addition, this review summarizes that multiple bioactive compounds and traditional Chinese medicine formulas can regulate macrophage polarization through key signaling pathways such as PI3K/AKT, NF-κB, and STAT3, thereby improving the ovarian immune microenvironment, delaying ovarian aging, and inhibiting tumor progression. This article aims to provide a comprehensive understanding of the role of macrophage polarization in ovarian biology and disease, and to offer theoretical support for developing novel immunomodulatory strategies targeting the ovarian microenvironment. macrophage polarization; Polycystic Ovary Syndrome; Premature Ovarian Insufficiency; Ovarian Cancer; Ovarian Function; Traditional Chinese Medicine MeifangWu Li Tang Yao Chen Pei Tang 雷磊 PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank