Atorvastatin is beneficial for muscle reinnervation after complete sciatic nerve section in rats
Bibliographic record
Abstract
Nerve regeneration and functional recovery are often incomplete after peripheral neurotmetic lesion. Atorvastatin has been shown to be neuroprotective after transient ischaemia or traumatic injury. The aim of this study was to establish if systemic administration of Atorvastatin could improve functional muscle reinnervation after complete sciatic nerve section. Sixteen female Sprague-Dawley rats were used in this study. After a complete right sciatic nerve section, end-to-end microsuture repair was performed and fibrin glue was added. Three groups were studied: (1) sutures (S) + fibrin glue (F) only + saline administration for 14 days; (2) S+F+Atorvastatin administration for 14 days; and (3) uninjured nerve. Five months later, the sciatic nerve and the gastrocnemius muscle were isolated to perform in vivo electrophysiological measurements. Better kinematics was observed in atorvastatin-treated rats 5 months after its administration. Indeed, a larger excursion of the hip-ankle-toe angle during walking was observed. This effect was associated with the preservation of electromyographic activity (2.91 mV vs 0.77 mV) and maximal muscle force (85.1 g vs 28.6 g) on stimulation of the proximal nerve section. Five months after a neurotmetic lesion, the recovery is incomplete when using suture and fibrin glue only. Furthermore, the systemic administration of Atorvastatin for 14 days after lesion was beneficial in improving locomotion capability associated with the re-establishment of muscle strength and EMG activity.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".