Curcumin protects against stroke and increases levels of Notch intracellular domain
Bibliographic record
Abstract
OBJECTIVES: To investigate whether curcumin regulates Notch signaling to cause neuroprotection and neurogenesis after focal ischemia reperfusion injury. METHOD: Focal ischemia reperfusion injury was modeled in rats by occluding the middle cerebral artery. These animals were given either curcumin (300 mg/kg) or corn oil (vehicle) by intraperitoneal injection starting 1 h after stroke and continuing for 7 d. In parallel, sham-operated control animals received vehicle. All animals were killed on day 12. The different treatment groups were compared in terms of neurobehavioral deficits, BrdU incorporation, and levels of doublecortin (DCX) and Notch intracellular domain (NICD) using immunohistochemistry, immunofluorescence and Western blotting. RESULTS: Animals treated with curcumin showed significantly smaller neurobehavioral deficits than vehicle-treated animals after 3, 7, and 12 d of reperfusion (all p < 0.05). Tissue sections from curcumin-treated animals contained significantly greater numbers of BrdU-positive cells (p < 0.05) and BrdU/DCX-positive cells (p < 0.01), as well as significantly higher NICD levels (p < 0.01). CONCLUSION: Curcumin may protect from focal cerebral ischemia reperfusion injury as well as stimulate neurogenesis by activating the Notch signaling pathway.
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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) | 0.002 | 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".