Facilitation of Locomotor Spinal Networks Activity by Buspirone after a Complete Spinal Cord Lesion in Mice
Bibliographic record
Abstract
Despite efforts to potentiate spinal cord lesioned (SCL) patients' functional recovery with multi-targeted therapy combining pharmacological treatment and training, consistent improvements in locomotor control by descending transmission or spinal network facilitation are still eluding clinicians and researchers. Lately, United States Food and Drug Administration-approved buspirone has shown promise and promoted locomotor-like movement occurrence in SCL patients, but evidence on how and where it exerts its effects is lacking. The objective of the present study was, first, to verify buspirone effect on locomotor spinal network and to evaluate if it promoted functional recovery when combined with training. Also, we evaluated buspirone impact on locomotion in mice that had recovered from a previous hemisection before sustaining the spinal transection. This dual lesion paradigm has allowed confirmation of spinal network involvement in recovery after an incomplete SCL. Buspirone acutely increased the number of steps taken, the coupling strength between hindlimbs, angular excursion of the hip joint during locomotion, and improved paw positioning at contact and paw drag (ps < 0.05). Moreover, it induced long-lasting improvements of paw positioning at contact and paw drag when combined with training in mice after a dual lesion paradigm. Altogether, the results indicate that buspirone exerts considerable acute facilitation of spinally mediated locomotion, and could be used in combination with training to promote functional recovery after SCL.
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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 | 0.001 |
| 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".