Mitogen‐activated protein kinase p38 regulates krox‐20 to direct schwann cell differentiation and peripheral myelination
Bibliographic record
Abstract
We previously reported that addition of extracellular matrix (ECM) extracts to rat Schwann cell-dorsal root ganglion neuron (DRGN) co-cultures activated mitogen-activated protein kinase (MAPK) p38, whereas inhibition blocked myelination. Here, we used p38 pharmacological inhibitors and gene silencing to assess their effects on downstream kinases and key transcription factors. We show that p38α regulates expression of the master transcription factor, Krox-20, required for the onset of myelination in Schwann cell-DRGNs, as assessed by immunocytochemistry and qRT-PCR. p38 activity is also required for the expression of the cell cycle inhibitor p27(kip1) , associated with Schwann cell differentiation. Three potential effectors of p38 were explored: MAPK-activated protein kinase-2 (MK2), mitogen and stress-activated protein kinase-1 (MSK-1), and the transcription factor cAMP response element-binding protein (CREB). Inhibition of MK2 with CMPD1 or gene knockdown with siRNAs reduced numbers of Krox-20-positive Schwann cells and expression of myelin proteins MBP and MAG. ECM activated CREB and increased Krox-20 expression, whereas CREB1 gene silencing reduced Krox-20. Furthermore, two nonselective inhibitors of MSK-1 (H89 and R0-318820) decreased ECM-induced CREB phosphorylation and, similar to anti-MSK-1 siRNAs, reduced Krox-20-positive cells. In addition, p38 modulated the expression of two transcription factors involved in the regulation of Krox-20 [suppressed cAMP-inducible protein (SCIP) and Sox10], but not Sox2, an antagonist of Krox-20. Collectively, our results show that p38 primarily directs Schwann cell differentiation and peripheral myelination by regulating Krox-20 expression through its downstream effectors, MK2 and MSK-1/CREB, and transcription factors SCIP and Sox10.
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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".