An investigation into the potential for activity‐dependent regeneration of the rubrospinal tract after spinal cord injury
Bibliographic record
Abstract
We tested whether regeneration of transected rubrospinal tract (RST) axons is facilitated by a prolonged electrical stimulation of these axons. A peripheral nerve was grafted to the transected RST at the cervical level (C4/5) of adult rats, providing a permissive environment for regeneration of rubrospinal axons. Direct antidromic stimulation of the RST was applied immediately after grafting through a microwire inserted just rostral to the RST lesion, using a 1-h 20-Hz supramaximal stimulation protocol. Stimulation caused no direct damage to rubrospinal axons, and was sufficient to recruit the entire rubrospinal tract. In control animals that had a nerve graft and implanted microwire with no stimulation, there were 42.7 +/- 10.2 rubrospinal neurons regenerated into the graft at 8 weeks, as assessed by retrograde labelling. In test animals that were stimulated there were 28.2 +/- 7.4 back-labelled neurons, not significantly different from control, indicating that this stimulation did not improve the regenerative capacity of rubrospinal neurons. Furthermore, reverse-transcriptase polymerase chain reaction and in situ hybridization for brain-derived neurotrophic factor (BDNF) and/or growth-associated protein-43 (GAP-43) expression in rubrospinal neurons revealed no significant difference between stimulated and unstimulated groups at 48 h after injury, with either 1 or 8 h of stimulation. In summary, direct stimulation of the injured RST axons for the periods tested does not increase expression of GAP-43 and BDNF, and ultimately does not promote regeneration of these central nervous system axons.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".