Nutrigenetic reprogramming of oxidative stress
Bibliographic record
Abstract
Retinal disorders such as retinitis pigmentosa, age-related retinal degeneration, oxygen-induced retinopathy, and ischemia-reperfusion injury cause debilitating and irreversible vision loss. While the exact mechanisms underlying these conditions remain unclear, there has been a growing body of evidence demonstrating the pathological contributions of oxidative stress across different cell types within the eye. Nuclear factor erythroid-2-related factor (Nrf2), a transcriptional activator of antioxidative genes, and its regulator Kelch-like ECH-associated protein 1 (Keap1) have emerged as promising therapeutic targets. The purpose of this review is to understand the protective role of the Nrf2-Keap1 pathway in different retinal tissues and shed light on the complex mechanisms underlying these processes. In the photoreceptors, we highlight that Nrf2 preserves their survival and function by maintaining oxidation homeostasis. In the retinal pigment epithelium, Nrf2 similarly plays a critical role in oxidative stabilization but also maintains mitochondrial motility and autophagy-related lipid metabolic processes. In endothelial cells, Nrf2 seems to promote proper vascularization and revascularization through concurrent activation of antioxidative and angiogenic factors as well as inhibition of inflammatory cytokines. Finally, Nrf2 protects retinal ganglion cells against apoptotic cell death. Importantly, we show that Nrf2-mediated protection of the various retinal tissues corresponds to a preservation of functional vision. Altogether, this review underscores the potential of the Nrf2-Keap1 pathway as a powerful tool against retinal degeneration. Key insights into this elegant oxidative defense mechanism may ultimately pave the path toward a universal therapy for various inherited and environmental retinal disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".