Evaluation of Hippocampal Injury and Cognitive Function Induced by Embolization in the Rat Brain
Bibliographic record
Abstract
Embolism is responsible for at least 20% of all stroke and half of cerebral infarctions. A number of animal models have been developed to mimic thromboembolic stroke. However, little aimed directly at hippocampal damage and cognitive function. In the present study, three sizes of emboli (150-178 μm, 74-124 μm, and 48-74 μm) were employed to induce thromboembolic stroke model in rats. Results showed that the diameter of the particle was critical for animal behavioral and histopathological consequences. Hematoxylin-eosin (HE) staining revealed that CA1 and CA2-3, which are two of the main hippocampal subdivisions were injured seriously, especially induced by emboli(48-74 μm) . At 24 hr, the neurological deficit scores showed that emboli injection could cause significant neurological deficit, and the increase of neurological deficit scores correlated well to the diameter of emboli. At 60 days, emboli(150-178 μm) and emboli(48-74 μm) lead to obvious cognitive impairment, which correlated well to the hippocampal CA1 injury. Our research might be helpful to choose suitable size of emboli to induce animal model to research subcortical ischemia and vascular dementia. However, cognitive alterations and cerebral injury following different sizes of emboli injection in rats remains a topic for future investigation.
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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) | 0.000 | 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".