Combining Schwann Cell Bridges and Olfactory-Ensheathing Glia Grafts with Chondroitinase Promotes Locomotor Recovery after Complete Transection of the Spinal Cord
Bibliographic record
Abstract
Numerous obstacles to successful regeneration of injured axons in the adult mammalian spinal cord exist. Consequently, a treatment strategy inducing axonal regeneration and significant functional recovery after spinal cord injury has to overcome these obstacles. The current study attempted to address multiple impediments to regeneration by using a combinatory strategy after complete spinal cord transection in adult rats: (1) to reduce inhibitory cues in the glial scar (chondroitinase ABC), (2) to provide a growth-supportive substrate for axonal regeneration [Schwann cells (SCs)], and (3) to enable regenerated axons to exit the bridge to re-enter the spinal cord (olfactory ensheathing glia). The combination of SC bridge, olfactory ensheathing glia, and chondroitinase ABC provided significant benefit compared with grafts only or the untreated group. Significant improvements were observed in the Basso, Beattie, and Bresnahan score and in forelimb/hindlimb coupling. This recovery was accompanied by increased numbers of both myelinated axons in the SC bridge and serotonergic fibers that grew through the bridge and into the caudal spinal cord. Although prominent descending tracts such as the corticospinal and reticulospinal tracts did not successfully regenerate through the bridge, it appeared that other populations of regenerated fibers were the driving force for the observed recovery; there was a significant correlation between numbers of myelinated fibers in the bridge and improved coupling of forelimb and hindlimb as well as open-field locomotion. Our study tests how proven experimental treatments interact in a well-established animal model, thus providing needed direction for the development of future combinatory treatment regimens.
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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 | 0.000 | 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 | 0.001 |
| 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".