Constraint-Induced Movement Therapy and Rehabilitation Exercises Lessen Motor Deficits and Volume of Brain Injury After Striatal Hemorrhagic Stroke in Rats
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Constraint-induced movement therapy (CIMT) promotes motor recovery after occlusive stroke in humans, but its efficacy after intracerebral hemorrhage (ICH) has not been investigated clinically or in the laboratory. In this study we tested whether CIMT and a rehabilitation exercise program would lessen motor deficits after ICH in rats. METHODS: Rats were subjected to striatal ICH (via infusion of collagenase) or sham stroke. Seven days later, treatment began with CIMT (8 h/d of ipsilateral forelimb restraint), rehabilitation exercises (eg, reaching, walking; 1 h/d), or both for 7 days. Some rats were not treated. Motor deficits were assessed up to the 60-day survival time, after which the volume of tissue lost was determined. RESULTS: Untreated ICH rats made more limb slips traversing a horizontal ladder and showed an asymmetry toward less use of the contralateral paw in the cylinder test of limb use asymmetry (day 28). These rats were also significantly less successful in the Montoya staircase test (days 55 to 59) of skilled reaching. Neither therapy alone provided much benefit. However, the combination of daily exercises and CIMT substantially and persistently improved recovery. Unexpectedly, this group had a statistically smaller volume of tissue lost than untreated ICH rats. CONCLUSIONS: The combination of focused rehabilitation exercises and CIMT effectively promotes functional recovery after ICH, while either therapy alone is less effective. This therapy may work in part by reducing the volume of tissue lost, likely through reducing atrophy while promoting remodeling.
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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 | 0.000 |
| 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".