Peripheral olfactory ensheathing cells reduce scar and cavity formation and promote regeneration after spinal cord injury
Bibliographic record
Abstract
Bridging of a lesion site and minimizing local damage to create an environment permissive for regeneration are both primary components of a successful strategy to repair spinal cord injury (SCI). Olfactory ensheathing cells (OECs) are prime candidates for autologous transplantation to bridge this gap, but little is known currently about their mechanism of action. In addition, OECs from the accessible lamina propria (LP) of the olfactory mucosa are a more viable source in humans but have yet to be tested for their ability to promote regeneration in established SCI models. Here, mouse LP-OECs expressing green fluorescent protein (GFP) transplanted directly into both rat and mouse dorsolateral spinal cord lesion sites demonstrate limited migration but interact with host astrocytes to develop a new transitional zone at the lesion border. LP-OECs also promote extensive migration of host Schwann cells into the central nervous system repair zone and stimulate angiogenesis to provide a biological scaffold for repair. This novel environment created by transplanted and host glia within the spinal cord inhibits cavity and scar formation and promotes extensive sprouting of multiple sensory and motor axons into and through the lesion site. Sixty days after rat SCI, serotonin- and tyrosine hydroxylase-positive axons sprouted across the lesion into the distal cord, although axotomized rubrospinal axons did not. Thus, even in a xenotransplant paradigm, LP-OECs work collaboratively with host glial cells to create an environment to ameliorate local damage and simultaneously promote a regenerative response in multiple axonal populations.
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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 | 0.001 |
| 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".