Abstract 16139: Mast Cells Promote Proliferation and Suppress Myogenic Differentiation of Mesenchymal Stem Cells
Bibliographic record
Abstract
Introduction: Efficient scar formation post-myocardial infarction (MI) depends on fibroblast/mesenchymal stem cell (MSC) accumulation and myofibroblast transdifferentiation. Mast cell (MC)-deficient mice exhibit reduced cardiac myofibroblast accumulation and undergo rapid left ventricular dilation post-MI. Thus, we sought to investigate how MCs modulate MSC proliferation and their myogenic differentiation into myofibroblasts. Methods: MC/MSC co-culture was used to examine MC effects on MSC proliferation and differentiation. MC granulate (MCG) was then used to further examine the mechanisms by which MCs exerted their effects on MSC proliferation, migration, and myogenic differentiation. The effects of MCs on MSC activity in vivo was evaluated by immunohistological analysis on MC- and saline-treated infarcted mouse hearts at 3 and 7 days post-MI Results: MC co-culture suppressed expression of the myogenic differentiation marker α-smooth muscle actin in MSCs. Similarly, MCG dose-dependently decreased myogenic differentiation by up to ~90% (P<0.01, n=4) and increased MSC proliferation ~two-fold (P<0.01, n=5) and migration by ~75% (P<0.01, n=4). Pharmacological antagonism of platelet-derived growth factor receptor (PDGFR) rescued MSC differentiation despite MCG treatment, suggesting MC suppression of MSC differentiation occurs through PDGFR. MCG treatment resulted in up to ~70% decreased miR-145 and -143 expression (P<0.05, n=4), as well as increased Klf4 (~25%) and decreased myocardin (~50%) protein expression in MSCs, indicating that the myocardin-Klf4 axis mediates MSC proliferation/differentiation. Finally, infarcted hearts from mice treated with MCs showed ~five-fold increased CD29+ MSC proliferation at day 3 vs saline-treated animals (P<0.05, n=3). This effect was absent by day 7 post-MI. Conclusions: MSCs can oscillate between proliferative and differentiated states. MCs promote proliferation at the expense of differentiation early after MI through PDGFR, downregulation of miR-145 and -143, and the Klf4-myocardin signalling axis to promote MSC accumulation. This in turn results in a larger cardiac MSC pool for later myofibroblast differentiation, facilitating improved wound healing.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".