The Efficacy of Specific Activation of D1-class Dopamine Receptors to Enhance Motor Recovery in Mice Following Cortical Photothrombotic Stroke
Bibliographic record
Abstract
Stroke is a widespread condition, which often leaves survivors with lasting deficits in motor function, however, physical rehabilitation is the only treatment available after the acute period. A large body of preclinical literature suggests dopamine-augmenting drugs, could enhance motor recovery following stroke. Unfortunately, mixed clinical results have prevented the implementation of such treatments, possibly due to the wide variety of G protein-coupled receptors these drugs can activate. Using a mouse photothrombosis stroke model and a battery of motor and sensorimotor behavioural tests, the current study aims to demonstrate proof of principle for the use of D1-class dopamine receptor agonists to enhance poststroke motor recovery and to evaluate the role of aerobic exercise rehabilitation in an asynchronous study design. The effect of light-dark cycle on behavioural outcome (horizontal ladder test, adhesive removal test, cylinder test) and histological outcome (infarct size) in photothrombotic stroke was evaluated in order to optimize the stroke model, but no there was no evidence of differences between strokes occurring during the light or dark period of a mouse’s circadian rhythm. A bioactive, suboptimal dose of D1-agonist dihydrexidine, was determined by evaluating its effect on locomotor activity and its ability to increase expression of immediate early gene c-fos. Using the determined dose, studies evaluating the efficacy of 7-days and 2-days of dihydrexidine administration on poststroke motor recovery, were performed, indicating efficacy of a 7-days, but not of a 2-days, course of treatment. The 7-days dihydrexidine treatment resulted in accelerated recovery as compared to a control group receiving saline. This work demonstrates, for the first time, proof of principle for the use of specific activation of D1-class dopamine receptors to enhance motor recovery following stroke.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".