Cooperation of Matrix Metalloproteinases with the RhoA/Rho Kinase and Mitogen‐Activated Protein Kinase Kinase‐1/Extracellular Signal‐Regulated Kinase Signaling Pathways Is Required for the Sphingosine‐1‐Phosphate‐Induced Mobilization of Marrow‐Derived Stromal Cells
Bibliographic record
Abstract
The ease of isolation and ex vivo culture of marrow-derived stromal cells (MSCs) from adult bone marrow renders them a very promising source of adult stem cells for gene transfer and cell therapy. However, little is known about the signaling pathways that control their in vivo mobilization and subsequent biodistribution. Platelet-derived sphingosine-1-phosphate (S1P), a bioactive lipid that acts via G-protein-coupled-receptors, exerts strong chemoattraction upon MSCs through yet-uncharacterized signaling pathways. We show that the S1P-induced migration and morphological changes of MSCs in vitro require the activities of extracellular signal-regulated kinase (ERK), Rho kinase (ROCK), and matrix metalloproteinase (MMP) signaling molecules. Specifically, S1P-induced remodeling of the MSC cytoskeleton led to the rapid (<1 minute) formation of actin stress fibers via activation of the RhoA/ROCK pathway and required the catalytic activity of MMPs. S1P-induced activation of the mitogen-activated protein kinase kinase-1 (MEK1)/ERK pathway also contributed to the induction of the actin stress fibers and to the redistribution of paxillin at the focal adhesions through tyrosine phosphorylation of focal adhesion kinase in an MMP-dependent manner. Moreover, MMP- and ROCK-dependent molecular events are implicated in the regulation of the S1P-induced activation of ERK. Our results demonstrate that MSC mobilization in response to S1P requires cooperation between MMP-mediated signaling events and the RhoA/ROCK and MEK1/ERK intracellular pathways. Therefore, the characterization of the cellular factors and the intracellular signaling pathways underlying MSC mobilization is crucial to achieve high efficacy in therapeutic use.
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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) | 0.001 | 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".