Analysis of Signal Transduction Pathways Downstream M2 Receptor Activation: Effects on Schwann Cell Migration and Morphology
Bibliographic record
Abstract
BACKGROUND: Schwann cells (SCs) express cholinergic receptors, suggesting a role of cholinergic signaling in the control of SC proliferation, differentiation and/or myelination. Our previous studies largely demonstrated that the pharmacological activation of the M2 muscarinic receptor subtype caused an inhibition of cell proliferation and promoted the expression of pro-myelinating differentiation genes. In order to elucidate the molecular signaling activated downstream the M2 receptor activation, in the present study we investigated the signal transduction pathways activated by the M2 orthosteric agonist arecaidine propargyl ester (APE) in SCs. METHODS: Using Western blot we analyzed some components of the noncanonical pathways involving β1-arrestin and PI3K/AKT/mTORC1 signaling. A wound healing assay was used to evaluate SC migration. RESULTS: Our results demonstrated that M2 receptor activation negatively modulated the PI3K/Akt/mTORC1 axis, possibly through β1-arrestin downregulation. The involvement of the mTORC1 complex was also supported by the decreased expression of its specific target p-p70 S6KThr389. Then, we also analyzed the expression of p-AMPKαthr172, a negative regulator of myelination that resulted in reduced levels after M2 agonist treatment. The analysis of cell migration and morphology allowed us to demonstrate that M2 receptor activation caused an arrest of SC migration and modified cell morphology probably by the modulation of β1-arrestin/cofilin-1 and PKCα expression, respectively. CONCLUSIONS: The data obtained demonstrated that M2 receptor activation in addition to the canonical Gi protein-coupled pathway modulates noncanonical pathways involving the mTORC1 complex and other kinases whose activation may contribute to the inhibition of SC proliferation and migration and address SC differentiation.
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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 | 0.000 |
| 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".