Nonlinear Redox-Immune Coupling Under Low-Dose-Rate Radiation: A Compartment-Specific Framework for Biological Responses-A Narrative Review

초록

Ionizing radiation induces reactive oxygen species (ROS) and inflammatory signaling that contribute to both therapeutic efficacy and normal tissue toxicity. While the effects of high-dose radiation are well characterized, responses to low-dose-rate radiation (LDRR) remain inconsistent and are not adequately explained by conventional linear dose-response models. To address this gap, we conducted a narrative review of recent experimental studies across multiple biological systems, including body fluids, joint microenvironments, and reproductive tissues, focusing on redox and immune-related responses under LDRR conditions (dose rates: 0.39-3.49 mGy/h). Literature was identified through PubMed/MEDLINE, Web of Science, and Google Scholar, with emphasis on studies published between 2015 and 2026. These studies demonstrate that LDRR elicits nonlinear, dose-dependent effects that vary across biological compartments and involve coordinated changes in oxidative stress, immune signaling, and metabolic regulation. Based on this synthesis, we propose a unifying framework of nonlinear redox-immune coupling, in which oxidative stress functions as a threshold-dependent regulator and immune responses follow a biphasic trajectory characterized by activation at lower dose rates and attenuation or adaptation at higher levels. These responses are strongly influenced by the local microenvironment, resulting in compartment-specific variability. This integrated perspective supports a shift from dose-centric to systems-level interpretations of radiation biology and provides a basis for improving biomarker development, risk assessment, and therapeutic strategies in chronic low-dose radiation exposure settings. Future research priorities include time-resolved mechanistic studies to define compartment-specific redox thresholds, validation of candidate biomarkers under identical multi-compartment experimental conditions (e.g., GSH/GSSG ratio, 8-OHdG, circulating cytokine panels including IL-10/TNF-alpha ratio), and integration of subject-specific biological variables (e.g., age, sex, and baseline redox capacity) into predictive models of LDRR response.

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