Neuroprotection by minocycline facilitates significant recovery from spinal cord injury in mice
Bibliographic record
Abstract
Acute spinal cord injury (SCI) produces tissue damage that continues to evolve days and weeks after the initial insult, with corresponding functional impairments. Reducing the extent of progressive tissue loss ('neuroprotection') following SCI should result in a better recovery from SCI, but treatment options have thus far been limited. In this study, we have tested the efficacy of minocycline in ameliorating damage following acute SCI in mice. This semi-synthetic tetracycline antibiotic has been reported to inhibit the expression and activity of several mediators of tissue injury, including inflammatory cytokines, free radicals and matrix metalloproteinases, making it a suitable candidate for study. Mice were subjected to extradural compression of the spinal cord using a modified aneurysm clip, following which they received treatment with either minocycline or vehicle beginning 1 h after injury. Behavioural testing of hindlimb function was initiated 3 days after injury using the Basso Beattie Bresnahan locomotor rating scale, and at 1 week using the inclined plane test. Functional assessments demonstrated that minocycline administration significantly improved both hindlimb function and strength from 3 to 28 days after injury compared with vehicle controls. Furthermore, gross lesion size in the spinal cord was significantly reduced by minocycline, and there was evidence of axonal sparing as determined using fluorogold labelling of the rubrospinal tract and by Bielchowsky silver stain. Finally, a comparison of minocycline against the currently approved treatment for acute SCI in humans, methylprednisolone, demonstrated superior behavioural recovery in the minocycline-treated animals.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".