Effects on Locomotion, Muscle, Bone, and Blood Induced by a Combination Therapy Eliciting Weight-Bearing Stepping in Nonassisted Spinal Cord–Transected Mice
Bibliographic record
Abstract
BACKGROUND: The health benefits associated with physical activity-based rehabilitation in patients with no lower-extremity motor function after a spinal cord injury (SCI) is uncertain. METHODS: The authors assessed signs of efficacy, safety, and utility associated with a novel pharmacological combination therapy to activate central pattern generator (CPG) activity and corresponding locomotor activity in complete thoracic Th9/10-transected mice. RESULTS: Subcutaneous administration 4 times per week for 1 month of 1.5 mg/kg buspirone, 1.5 mg/kg apomorphine, 12.5 mg/kg benserazide, and 50 mg/kg L-DOPA induced episodes of weight-bearing stepping on a treadmill in nonassisted paraplegic mice for 45-minute sessions. Hindlimb muscle cross-sectional area and fiber area values as well as several blood cell constituent levels assessed at 30 days postinjury were positively affected by the combination therapy, as compared with controls. Episodes of locomotion remained effective on each treatment. Femoral bone mineral density loss was not prevented by triple therapy. CONCLUSION: Although translation of these findings needs further experimentation, similar pharmacological activation of the CPG offers a novel therapeutic target to provide some health benefits in motor-complete SCI patients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".