A Critical Threshold of Rehabilitation Involving Brain-Derived Neurotrophic Factor Is Required for Poststroke Recovery
Bibliographic record
Abstract
BACKGROUND: Enriched rehabilitation (ER; environmental enrichment plus skilled reaching) improves recovery after middle cerebral artery occlusion (MCAo) in rats. Fundamental issues such as whether ER is effective in other models, optimal rehabilitation intensity, and underlying recovery mechanisms have not been fully assessed. OBJECTIVE: The authors tested whether the efficacy of ER varies with ischemia model and assessed the importance of rehabilitation intensity and brain-derived neurotrophic factor (BDNF) in recovery. METHODS: Rats in experiment 1 received 8 weeks of ER or remained in standard housing. Functional outcome was assessed with the staircase and cylinder tasks. Surprisingly, ER provided no functional benefit in any model. In this experiment, ER was delivered during the light phase, whereas other studies delivered ER in the dark phase of the light cycle. It was hypothesized that in the light, rats engaged in less rehabilitation or alternatively that BDNF was lower. Experiment 2 tested these hypotheses. Following MCAo, rats received ER in either the light or dark phase of the light cycle. Functional outcome was assessed and BDNF levels were measured in the motor cortex and hippocampus. RESULTS: Recovery was accompanied by increased BDNF. This occurred only in rats that received ER in the dark and these animals reached more than those in the light condition. CONCLUSIONS: Data suggest that there is a critical threshold of rehabilitation, below which recovery will not occur, and that BDNF mediates functional recovery. The use of intensive rehabilitation therapies for stroke patients is strongly supported.
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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) | 0.000 | 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 | 0.001 | 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".