Limited Myelination Capacity in Human Schwann Cells in Experimental Models in Comparison to Rodent and Porcine Schwann Cells
Bibliographic record
Abstract
Schwann cells (SCs) play a crucial role in peripheral nerve repair by supporting axonal regeneration and remyelination. While extensive research has been conducted using rodent SCs, increasing attention is being directed toward human SCs due to species-specific differences in phenotypical and functional properties, and accessibility of human SCs derived from diverse sources. A major challenge in translating SC-based therapies for nerve repair lies in the inability to replicate human SC myelination in vitro, posing a significant obstacle to drug discovery and preclinical research. In this study, we compared the myelination capacity of human, rodent, and porcine SCs in various co-culture conditions, including species-matched and cross-species neuronal environments in a serum-free medium. Our results confirmed that rodent and porcine SCs readily myelinate neurites under standard culture conditions after treatment with ascorbic acid for two weeks, whereas human SCs, at least within the four-week observation period, failed to show myelin staining in all co-cultures. Furthermore, we investigated whether cell culture manipulation impairs human SC myelination by transplanting freshly harvested and predegenerated human nerve segments into NOD-SCID mice for four weeks. Despite supporting host axonal regeneration into the grafts, human SCs exhibited very limited myelination, suggesting an intrinsic species-specific restriction rather than a cell culture-induced defect. These observations suggest fundamental differences between human and rodent SCs and highlight the need for human-specific models and protocols to advance our understanding of SC myelination.
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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 | 0.001 | 0.001 |
| 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".