Transforming growth factor‐β induces loss of epithelial character and smooth muscle cell differentiation in epicardial cells
Bibliographic record
Abstract
During embryogenesis, epicardial cells undergo epithelial-mesenchymal transformation (EMT), invade the myocardium, and differentiate into components of the coronary vasculature, including smooth muscle cells. We tested the hypothesis that transforming growth factor-beta (TGFbeta) stimulates EMT and smooth muscle differentiation of epicardial cells. In epicardial explants, TGFbeta1 and TGFbeta2 induce loss of epithelial morphology, cytokeratin, and membrane-associated Zonula Occludens-1 and increase the smooth muscle markers calponin and caldesmon. Inhibition of activin receptor-like kinase (ALK) 5 blocks these effects, whereas constitutively active (ca) ALK5 increases cell invasion by 42%. Overexpression of Smad 3 did not mimic the effects of caALK5. Inhibition of p160 rho kinase or p38 MAP kinase prevented the loss of epithelial morphology in response to TGFbeta, whereas only inhibition of p160 rho kinase blocked TGFbeta-stimulated caldesmon expression. These data demonstrate that TGFbeta stimulates loss of epithelial character and smooth muscle differentiation in epicardial cells by means of a mechanism that requires ALK5 and p160 rho kinase.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".