Peroxisome proliferator-activated receptor γ promotes neuroprotection by modulating cyclic D1 expression after focal cerebral ischemia
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor gamma (PPARgamma) has been shown to protect against stroke and improve neurological outcome after cerebral ischemia. This study investigated whether activation of cerebral PPARgamma improves recovery from focal cerebral ischemia by reducing expression of cyclin D1, which is associated with programmed neuron death. Focal cerebral ischemia was induced by 90 min of middle cerebral artery occlusion (MCAO), followed by reperfusion. Intracerebroventricular (i.c.v.) infusion of the PPARgamma agonist ciglitazone, beginning 5 days before and continuing through 1 day after MCAO, reduced infarct size and cyclin D1 expression in the peri-infarct cortical region. Furthermore, primary cortical neurons treated with ciglitazone showed suppressed expression of cyclin D1 in response to hypoxia-reoxygenation. This protective effect was reversed after cotreatment with the selective PPAR-gamma antagonist GW 9662 (2-chloro-5-nitrobenzanilide), clearly demonstrating the involvement of a PPARgamma-dependent mechanism. Our data provide evidence that activation of neuronal PPARgamma makes a substantial contribution to neuroprotection by preventing cyclin D1 up-regulation in vitro and in vivo.
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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".