Dopamine activates Nrf2‐regulated neuroprotective pathways in astrocytes and meningeal cells
Bibliographic record
Abstract
The transcription factor Nrf2 controls inducible expression of multiple antioxidant/detoxification genes. We previously found that Nrf2-/- mice have increased sensitivity to in vivo mitochondrial stress and ischemia. Although Nrf2 regulated these forms of neuronal toxicity, it was unclear which injury-triggered signal(s) led to Nrf2 activation in vivo. In this study, we use primary cultures to test the hypothesis that excessive dopamine release can act as an endogenous Nrf2-inducing signal. We cultured two cell types that show increased Nrf2 activity during ischemia in vivo, astrocytes and meningeal cells. Cultures were infected with an adenovirus reporter of Nrf2 transcriptional activity. Dopamine-induced Nrf2 activity in both cell types by generating oxidative stressors, H2O2 and dopamine-quinones. Nrf2 activation in meningeal cells was significantly higher than astrocytes. The effect of dopamine was blocked by antioxidants, and by over-expression of either dominant-negative Nrf2 or Keap1. Nrf2 induction was specific to oxidative stress caused by catecholaminergic neurotransmitters as epinephrine also induced Nrf2, but the monoamine serotonin had no significant effect. These in vitro results suggest Nrf2 activity in astrocytes and meningeal cells link the neurotoxic actions of dopamine to neuroprotective pathways that may potentially modulate ischemic injury and neurodegeneration.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".