Induction of the Nrf2-driven Antioxidant Response Confers Neuroprotection during Mitochondrial Stress in Vivo
Bibliographic record
Abstract
NF-E2 related factor (Nrf2) controls a pleiotropic cellular defense, where multiple antioxidant/detoxification pathways are up-regulated in unison. Although small molecule inducers of Nrf2 activity have been reported to protect neurons in vitro, whether similar pathways can be accessed in vivo is not known. We have investigated whether in vivo toxicity of the mitochondrial complex II inhibitor 3-nitropropionic acid (3-NP) can be attenuated by constitutive and inducible Nrf2 activity. The absence of Nrf2 function in Nrf2(-/-) mice resulted in 3-NP hypersensitivity that became apparent with time and increasing dose, causing motor deficits and striatal lesions on a more rapid time scale than identically treated Nrf2(+/+) and Nrf2(+/-) controls. Striatal succinate dehydrogenase activity, the target of 3-NP, was inhibited to the same extent in all genotypes by a single acute dose of 3-NP, suggesting that brain concentrations of 3-NP were similar. Dietary supplementation with the Nrf2 inducer tert-butylhydroquinone attenuated 3-NP toxicity in Nrf2(+/-) mice, but not Nrf2(-/-), confirming the Nrf2-specific action of the inducer in vivo. Increased Nrf2 activity alone was sufficient to protect animals from 3-NP toxicity because intrastriatal adenovirus-mediated Nrf2 overexpression significantly reduced lesion size compared with green fluorescent protein overexpressing controls. In cultured astrocytes, 3-NP was found to increase Nrf2 activity leading to antioxidant response element-dependent gene expression providing a potential mechanism for the increased sensitivity of Nrf2(-/-) animals to 3-NP toxicity in vivo. We conclude that Nrf2 may underlie a feedback system limiting oxidative load during chronic metabolic stress.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".