Neuroprotective Effect of Asiatic Acid in Rat Model of Focal Embolic Stroke
Bibliographic record
Abstract
Asiatic acid (AA) is a pleiotropic neuroprotective agent that has been shown to attenuate infarct volume in mouse and rat models of focal ischemia and has a long clinically relevant therapeutic time-window. Because in a future trial AA would be administered with tissue-plasminogen activator (t-PA), the only approved acute stroke therapy, we sought to determine the effect of AA when co-administered with t-PA in a rat focal embolic stroke model. Male rats were treated with AA (75 mg/kg) alone, low-dose t-PA (2.5 mg/kg) alone, or a combination of AA and low-dose t-PA at 3 h after inducing embolic stroke. AA significantly reduced infarct volume whereas low-dose t-PA alone did not reduce infarct volume compared with vehicle. Significantly, combination treatment further enhanced reduction of infarct volume versus AA alone. Treatment with AA reduced cytochrome c (CytoC) and apoptosis-inducing factor (AIF) release from brain mitochondria after ischemia. AA was also neuroprotective against L-glutamate-induced toxicity in primary cortical neurons. In summary, combination treatment with AA and low-dose t-PA at 3 h after embolic stroke reduces infarct volume, improves neurological outcome, and provides neuroprotection. The neuroprotective effects of AA were partially associated with reduction of AIF and CytoC release.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".