Control of Cardiac Fibroblast Phenotype by the Meox2/Zeb2 Signalling Switch (LB47)
Bibliographic record
Abstract
The fibroblast to myofibroblast phenoconversion, which is induced by TGF‐β, is a crucial step during cardiac fibrosis. Activated myofibroblasts increase extracellular matrix (ECM) synthesis, which impairs contraction that results in myocardial stiffening, and eventually heart failure. Meox2, a regulator of cell proliferation and senescence, can block TGF‐β mediated epithelial to mesenchymal transition (EMT). In contrast, Zeb2, a repressor of Meox2, enhances EMT in concert with TGF‐β. However, their roles in the fibroblast to myofibroblast phenoconversion remain elusive. We have shown that Meox2 is more highly expressed in fibroblasts than in myofibroblasts. Conversely, Zeb2 expression is lower in fibroblasts but higher in myofibroblasts. This suggests that Meox2/Zeb2 may regulate the fibroblast phenotype during cardiac fibrosis. We have shown that ectopic expression of Meox2 represses a set of myofibroblast markers. We have successfully knocked down Meox2 protein in primary cells. By confocal microscopy, Meox2 protein was found to be confined to the nuclei of fibroblasts whereas a cytoplasmic distribution was seen in myofibroblasts. By immunoblotting, Zeb2 expression was found to be higher in the nuclei of myofibroblasts. To test if ectopic Zeb2 expression enhances this phenoconversion, we have recently generated an adenoviral Zeb2 expression construct. We anticipate that the Meox2/Zeb2 signalling switch plays a critical role in cardiac fibrosis and findings from this study may provide a basis for developing Meox2 or Zeb2 based novel anti‐fibrotic drugs in the future. Grant Funding Source : Supported by Canadian Institutes of Health Research & Heart and Stroke Foundation of Canada
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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) | 0.002 | 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".