Inter‐microcarrier transfer and phenotypic stability of stem cell‐derived Schwann cells in stirred suspension bioreactor culture
Bibliographic record
Abstract
Emerging bioreactor technologies offer an effective way for scaled-up production of large numbers of cells for cell therapy applications. One of the clinical paradigms where cell therapy can be an asset is restorative neurosciences. Nerve repair can benefit from the injections of stem cells and/or Schwann cells, acting as a source for axon myelination, myelin debris clearance, and trophic support. We have adapted microcarrier-based suspension bioreactor culture for Schwann cells (SCs) differentiated from a new stem cell source - skin-derived precursors (SKPs). SKP-derived SCs attach and grow on different types of microcarriers in both static and stirred culture, with Cytodex 3 and CultiSpher-S found most effective. Inter-microcarrier migration of SKP-SCs represents a key mechanism for rapid expansion and colonization in stirred suspension culture. We have shown that microcarrier-expanded SKP-SCs cells express Schwann cell markers p75-NTR, GFAP and S100 and retain their key ability to myelinate axons both in vitro and in vivo. Scaled-up microcarrier-based production of SKP-SCs in suspension bioreactors appears feasible for timely generation of sufficient cell numbers for nerve repair strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".