Human mesenchymal factors induce rat hippocampal‐ and human neural stem cell dependent oligodendrogenesis
Bibliographic record
Abstract
The generation of new oligodendrocytes is essential for adult brain repair in diseases such as multiple sclerosis. We previously identified the multifunctional p57kip2 protein as a negative regulator of myelinating glial cell differentiation and as an intrinsic switch of glial fate decision in adult neural stem cells (aNSCs). In oligodendroglial precursor cells (OPCs), p57kip2 protein nuclear exclusion was recently found to be rate limiting for differentiation to proceed. Furthermore, stimulation with mesenchymal stem cell (MSC)-derived factors enhanced oligodendrogenesis by yet unknown mechanisms. To elucidate this instructive interaction, we investigated to what degree MSC secreted factors are species dependent, whether hippocampal aNSCs respond equally well to such stimuli, whether apart from oligodendroglial differentiation also tissue integration and axonal wrapping can be promoted and whether the oligodendrogenic effect involved subcellular translocation of p57kip2. We found that CC1 positive oligodendrocytes within the hilus express nuclear p57kip2 protein and that MSC dependent stimulation of cultured hippocampal aNSCs was not accompanied by nuclear p57kip2 exclusion as observed for parenchymal OPCs after spontaneous differentiation. Stimulation with human MSC factors was observed to equally promote rat stem cell oligodendrogenesis, axonal wrapping and tissue integration. As forced nuclear shuttling of p57kip2 led to decreased CNPase- but elevated GFAP expression levels, this indicates heterogenic oligodendroglial mechanisms occurring between OPCs and aNSCs. We also show for the first time that dominant pro-oligodendroglial factors derived from human fetal MSCs can instruct human induced pluripotent stem cell-derived NSCs to differentiate into O4 positive oligodendrocytes.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".