Identifying novel mechanisms of cardiac myofibroblast phenotype modulation
Bibliographic record
Abstract
Activation of TGF‐β 1 /Smad signaling plays a role in the phenoconversion of quiescent cardiac fibroblasts to secretory, contractile myofibroblasts. This event is associated with cardiac fibrosis, progressive cardiac dysfunction and heart failure. We have previously shown that c‐Ski, an endogenous inhibitor of TGF‐β 1 , is able to reduce myofibroblast contractility and collagen type I deposition. Further, c‐Ski overexpression was associated with a diminution of myofibroblastic phenotype. We have now determined that fibroblast ‐ myofibroblast differentiation is associated with a dramatic reduction in mRNA expression of homeobox proteins, Meox1 and Meox2. c‐Ski overexpression in first passage cardiac myofibroblasts was able to rescue Meox2 (but not Meox1) mRNA expression. The reduction of myofibroblast phenotype observed with c‐Ski was mirrored by Meox2 overexpression, while exogenous Meox1 had no significant effect on phenotype. To determine a putative mechanism of c‐Ski induction of Meox2, we examined expression of the Meox2 repressor protein, Zeb2 (eg, Smad‐interacting protein 1) in c‐Ski overexpressing cells. As c‐Ski caused a significant reduction of Zeb2 expression, we identified a putative mechanism for c‐Ski modulation of myofibroblast phenotype eg, that c‐Ski relieves Zeb2‐mediated inhibition of Meox2 thereby diminishing myofibroblast phenotype. Supported by the CIHR and HSFM.
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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 | 0.001 | 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".