Oxidative stress arises when reactive oxygen species (ROS) production exceeds antioxidant and repair capacity, promoting lipid, protein, and DNA damage, mitochondrial dysfunction, inflammation, and regulated cell death. This review critically examined organ-specific oxidative injury induced by lipopolysaccharide (LPS), hydrogen peroxide (H2O2), or iron (Fe2+) in experimental brain, liver, kidney, and heart models. LPS primarily initiated oxidative damage through Toll-like receptor 4-dependent inflammatory signaling, cytokine release, mitochondrial impairment, and activation of apoptosis or ferroptosis-related pathways. H2O2 produced direct oxidant challenge disrupting redox homeostasis, damaging mitochondrial bioenergetics, and promoting oxidative injury in a concentration-, duration-, and cell type-dependent manner. Iron overload enhanced ROS formation through Fenton chemistry, lipid peroxidation, mitochondrial damage, and ferroptotic cell death. This reviewed aimed to demonstrate significant organ- and model-specific heterogeneity. Brain was especially susceptible attributed to high oxygen consumption, lipid-rich composition, and limited antioxidant reserve; the liver integrated xenobiotic metabolism, redox detoxification, and endoplasmic reticulum stress responses; the kidney was susceptible due to high mitochondrial demand and intercellular metabolic dependence within nephron–vascular niche; and heart was markedly sensitive to impaired electron-transport-chain function, calcium dysregulation, and contractile energy failure. Comparisons of in vivo and in vitro models indicated that each model captures complementary aspects of oxidative-induced pathology but may differ in dose, exposure duration, cellular complexity, and translational relevance. Overall, LPS, H2O2, or iron are useful but mechanistically distinct oxidative-stress inducers. Future studies need to integrate standardized exposure paradigms with spatial, single-cell, and multi-omics approaches to define intercellular redox regulation and improve translational value of experimental models.
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Ejjalti et al. (2026) studied this question.
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