Abstract TP253: Early Intense Rehabilitation Does Not Reduce Impairment After Intra-striatal Hemorrhagic Stroke In Rats
Bibliographic record
Abstract
Intracerebral hemorrhage (ICH) causes rapid mechanical damage and initiates secondary injury mechanisms, such as from toxic by-products of blood degradation, that cause extended cell death. Experimentally, several rehabilitative treatments (rehab) can mitigate late cell death, and one recent study suggests it is by accelerating hematoma clearance, thereby minimizing neurotoxicity. Here, we assessed whether early, intense, enriched rehab (ER) enhances functional benefit and reduces ICH injury. Methods: In experiment 1, rats (n=56) were randomly assigned to groups following collagenase-induced striatal ICH: ER-Dark, ER-Light, CONTROL-Dark, or CONTROL-Light. ER rats completed four reach training sessions and six hours of environmental enrichment daily for 10d (d5-14 after ICH), in either the dark or light phase of their housing cycle. Rats were euthanized on d14 and hematoma volume was assessed. In experiment 2 (n=72), rats were randomized to: ER-10, ER-20, or CONTROL. Using the same ER protocol, rats in ER-10 and ER-20 completed 10d (d5-14) or 20d (d5-14 and 19-28) of ER during the dark phase of their housing cycle. Rats were euthanized on d60, and brains were fixed for histological processing. In both experiments, rats completed behavioural assessments prior to ICH, pre-treatment (d4 post-ICH) and post treatment (experiment 1, d13-14; experiment 2, d16-17 and d30-31). Results: In experiment 1 there was no significant difference in reaching intensity between ER completed in light vs. dark (p=0.3318), and both groups reached extensively (3912±947 reaches). ER resulted in slightly better reaching success between d4 and d14 (p=0.0272) but did not significantly alter residual hematoma volume (p=0.9653). In experiment 2, ER duration did not significantly impact reaching success between d4 and d31 (p=0.0587) or reduce lesion size (p=0.6401). Conclusion: While similar rehab methods have been beneficial in other work, these findings suggest that slight variations in protocols (rehab initiation, intensity, time in enrichment) have a large impact on treatment efficacy. Additionally, these results underscore the importance of studying rehabilitation after ICH, as the use of comparable treatments appear to be far more efficacious for ischemic injury.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".