Virgin Coconut Oil Attenuates Deficits in Rats Undergoing Transient Cerebral Ischemia
Bibliographic record
Abstract
Background and Objectives. Neuroprotection agents may help improve the outcomes of large vessel ischemic stroke. This study aims to explore the role of Virgin Coconut Oil (VCO), with its well-documented anti-oxidant properties, in neuroprotection after transient occlusion of the extracranial internal carotid artery in a rat model of stroke. Methods. Twenty-three Sprague-Dawley rats were randomized into two groups: 1) control group (n=11) given distilled water, and 2) treatment group (n=12) given virgin coconut oil at 5.15 ml/kg body weight for seven days. Subsequently, the rats underwent transient right extracranial internal carotid artery occlusion (EICAO) for 5 minutes using non-traumatic aneurysm clips. At 4 and 24 hours after EICAO, the animals were examined for neurologic deficits by an observer blinded to treatment groups, then sacrificed. Eight brain specimens (4 from each group) were subjected to histopathologic examination (H & E staining) while the rest of the specimens were processed using triphenyltetrazolium chloride (TTC) staining to determine infarct size and area of hemispheric edema. Results. VCO treatment significantly improved the severity of neurologic deficit (1.42 ± 2.31) compared to the control distilled water group (4.09 ± 2.59) 24 hours after EICAO. Whereas, infarct size and percent hemispheric edema did not significantly differ between the two groups. Conclusion. Prophylactic treatment of VCO is protective against EICAO-induced neurologic deficits in a rat model. VCO shows great potential as a neuroprotective agent for large vessel ischemic stroke. However, more studies are necessary to elucidate the neuroprotective mechanisms of VCO therapy in ischemic stroke.
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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 | 0.000 | 0.001 |
| 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".