Characterizing Spontaneous Motor Recovery Following Cortical and Subcortical Stroke in the Rat
Bibliographic record
Abstract
BACKGROUND: Stroke is a leading cause of neurological disability, often resulting in long-term motor impairments due to damage to cortical or subcortical motor areas. Despite the high prevalence of subcortical strokes in the clinical population, preclinical research has primarily focused on investigating and treating cortical strokes. Moreover, while both humans and animals show spontaneous recovery following stroke, little is known about how injury location affects this process. OBJECTIVE: To capture the heterogeneity of human stroke and examine how stroke location affects spontaneous motor recovery following damage to cortical, subcortical, or a combination of both areas. METHODS: Endothelin-1 (ET-1), a potent vasoconstrictor, was used to produce focal infarcts in the forelimb motor cortex (FMC), the dorsolateral striatum (DLS) or both the FMC and DLS in male Sprague-Dawley rats. The spontaneous recovery profile of animals was followed over an 8-week period using a battery of behavioral tasks assessing motor function and limb preference. RESULTS: All 3 groups showed significant impairments on the Montoya staircase, beam, and cylinder tests following stroke, with the combined group (FMC + DLS) having the largest and most persistent impairments. Importantly, spontaneous recovery was not simply dependent on lesion volume, but on location, and the behavioral test employed. CONCLUSIONS: Stroke location markedly and differentially influences the level of spontaneous functional recovery, which is only captured by using multiple outcome measures. These results illustrate the need for preclinical stroke models to align with the heterogeneity of human stroke, especially with respect to lesion location, size, and outcome measures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".