Object: Neuroinflammation mediated by microglia has emerged as a critical factor in ischemic stroke and neuronal damage. Gualou Guizhi Granule (GLGZG) has been shown to suppress inflammation in lipopolysaccharide (LPS)-activated microglia, though the underlying mechanisms and its protective effects against neuronal apoptosis remain unclear. This study aims to investigate how GLGZG regulates the Notch signaling pathway in microglia to reduce neuroinflammation and protect neurons from apoptosis.
Method: Using in vitro and in vivo models, we explored GLGZG's impact on microglia activation, pro-inflammatory cytokines, and neuronal apoptosis. Microglial cells were activated with LPS, and primary neuronal cells were exposed to LPS-activated microglia to simulate neuroinflammation. Additionally, we investigated the effects of GLGZG in combination with N-[N-[3,5-difluorophenacetyl]-L-alanyl]-S-phenylglycine t-butyl ester (DAPT) or siRNA-Notch1 to further elucidate the involvement of the Notch signaling pathway.
Results: GLGZG significantly inhibited microglia activation and reduced neuroinflammation by de-creasing the levels of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α in both in vitro and in vivo models. GLGZG also effectively protected against microglia-induced neuronal apoptosis. Mechanistically, GLGZG down-regulated key components of the Notch signaling pathway, in-cluding Notch-1, NICD, RBPSUH, and Hes-1, in activated microglia. Combined treatment with GLGZG and DAPT or siRNA-Notch1 demonstrated enhanced inhibition of microglial activation and neuroinflammation.
Conclusion: Our findings reveal that GLGZG exerts its protective effects through the suppression of the Notch signaling pathway, thereby inhibiting microglia activation, reducing neuroinflammation, and safeguarding neurons from neuroinflammation-induced damage, offering potential as a therapeutic agent for ischemic stroke-induced neuroinflammation.
Keywords: Gualou Guizhi Granule; Notch; ischemic stroke; microglia; neuroinflammation.
Copyright © 2025 Li, Huang, Li, Feng, Wang, Luo, Chen, Zhang, Yan and Nan.