Modeling Oxidative-Stress-Driven Alterations in Microglial Polarization and Astroglial State Dynamics

Neuroinflammation driven by microglia-astrocyte interactions is a central aspect in neurodegenerative diseases. Oxidative stress (OS) is known to intensify these inflammatory pathways; however, the specific ways in which increasing reactive oxygen species (ROS) alter cytokine signaling and glial-state transitions remain only partially understood. The purpose of this study is to develop a deterministic computational model to examine how different levels of ROS influence microglial polarization, astrocyte activation, cytokine production, and downstream damage signaling. It was hypothesized that higher ROS concentrations would shift microglia toward a pro-inflammatory M1-like state, amplify inflammatory cytokines, reduce regulatory pathway activations, and produce greater astrocytic reactivity and damage signaling outputs. A system of coupled ordinary differential equations (ODEs) is solved in python to represent microglial polarization transitions, astrocyte dynamics, cytokine interactions, and damage signal accumulation. The model was simulated under four fixed ROS conditions: control, minimal, mid-range, and extreme. The simulations showed that increasing ROS consistently elevated M1-like polarization, boosted pro-inflammatory cytokine signaling, suppressed anti-inflammatory cytokine expression, and increased early astrocytic activation followed by reduced proliferative stability. Extreme ROS concentration produced the fastest and most influential damage signaling across all conditions. These results supported the hypothesis and aligned with qualitative patterns described in microglial and astrocytic literature.