Early, Intense Rehabilitation Fails to Improve Outcome After Intra-Striatal Hemorrhage in Rats
Bibliographic record
Abstract
BACKGROUND: The formation and degradation of an intracerebral hemorrhage causes protracted cell death, and an extended window for intervention. Experimental studies find that rehabilitation mitigates late cell death, with accelerated hematoma clearance as a potential mechanism. OBJECTIVE: We assessed whether early, intense, enriched rehabilitation (ER, environmental enrichment and massed skills training) enhances functional benefit, reduces brain injury, and augments hematoma clearance. METHODS: In experiment 1, rats (n = 56) were randomized to intervention in the light (-L) or dark phase (-D) of their housing cycle, then to 10 days of ER or control (CON) treatment after collagenase-induced striatal intracerebral hemorrhage (ICH). ER rats were treated from 5 to 14 days after ICH. Behavior and residual hematoma volume was assessed on day 14. In experiment 2, rats (n = 72) were randomized to ER-D10, ER-D20, or CON-D. ER rats completed 10 or 20 days of training in the dark. Rats were euthanized on day 60 for histology. In both experiments, behavioral assessment was completed pre-ICH, pre-ER (day 4 post-ICH), and post-ER (experiment 1: days 13-14; experiment 2: days 16-17 and 30-31). RESULTS: Reaching intensity was high but similar between ER-D10 and ER-L10. Unlike previous work, rehabilitation did not alter skilled reaching or hematoma resolution. Varying ER duration also did not affect reaching success or lesion volume. CONCLUSIONS: In contrast to others, and under these conditions, our findings show that striatal ICH was generally unresponsive to rehabilitation. This highlights the difficulty of replicating and extending published work, perhaps owing to small inter-study differences.
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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 | 0.000 | 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 | 0.001 |
| 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".