An Examination of the Mechanisms by which Neural Precursors Augment Recovery following Spinal Cord Injury: A Key Role for Remyelination
Bibliographic record
Abstract
The mechanisms by which neural precursor cells (NPCs) enhance functional recovery from spinal cord injury (SCI) remain unclear. Spinal cord injured rats were transplanted with wild-type mouse NPCs, shiverer NPCs unable to produce myelin, dead NPCs, or media. Most animals also received minocycline, cyclosporine, and perilesional infusion of trophins. Motor function was graded according to the BBB scale. H&E/LFB staining was used to assess gray and white matter, cyst, and lesional tissue. Mature oligodendrocytes and ED1(+) inflammatory cells were quantitated. Confocal and electron microscopy were used to assess the relationship between the transplanted cells and axons. Pharmacotherapy and trophin infusion preserved gray matter, white matter, and oligodendrocytes. Trophin infusion also significantly increased cyst and lesional tissue volume as well as inflammatory infiltrate, and functional recovery was reduced. Animals transplanted with wild-type NPCs showed greatest functional recovery; animals transplanted with shiverer NPCs performed the worst. Wild-type NPCs remyelinated host axons. Shiverer NPCs ensheathed axons but did not produce MBP. These results suggest that remyelination by NPCs is an important contribution to functional recovery following SCI. Shiverer NPCs may prevent remyelination by endogenous cells capable of myelin formation. These findings suggest that remyelination is an important therapeutic target following SCI.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".