Neuroprotective effect of dimethyl fumarate in stroke: The role of nuclear factor erythroid 2-related factor 2
Bibliographic record
Abstract
Background: There is evidence that supports the neuroprotective effects of dimethyl fumarate (DMF) in stroke. Nuclear factor erythroid 2-related factor 2 (Nrf2) has both anti-oxidant and anti-inflammatory mechanisms. We investigated the neuroprotective effects of DMF via Nrf2 activation in the cortex, striatum, and diencephalon in a middle cerebral artery occlusion (MCAO) model of stroke. Methods: 22 Sprague-Dawley male rats were randomized into 3 groups. In DMF-treated group (n = 8), rats received 15 mg/kg oral DMF twice daily by gavage from day 0 to 14 after a 60-minute MCAO. The vehicle group (n = 7) underwent MCAO and were given methocel/H2O, using the same method and schedule. In the sham group (n = 7), neck was opened, but neither middle cerebral artery (MCA) was occluded nor any drug was administered. After 14 days, the animals were sacrificed. The infarct volume were assessed by stereology method. Nrf2 expression was evaluated in the cortex, striatum, and diencephalon by immunohistochemistry method. Results: Ratio of infarct to total brain volume was significantly lower in the DMF-treated group (5.76%) in comparison with the vehicle group (22.39%) (P < 0.0001). Nrf2 expression was higher in DMFtreated group in comparison with both the vehicle and sham groups in cortex, striatum, diencephalon, and total brain (P < 0.0001). In the DMF-treated group, significant negative correlation between Nrf2 expression and infarct volume was observed in cortex, striatum, diencephalon, and total brain. Conclusion: DMF induces Nrf2 expression and its neuroprotective effects in different brain anatomical regions.
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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".