The transcriptional regulation of periostin by scleraxis in cardiac myofibroblasts
Bibliographic record
Abstract
Extracellular matrix (ECM) remodeling resulting in cardiac fibrosis is a crucial factor in determining the severity of myocardial dysfunction during heart failure. In response to stress or damage, cardiac fibroblasts undergo phenotype conversion to myofibroblasts, the primary cell type responsible for ECM synthesis and remodeling in the heart. Periostin, a marker of the myofibroblast phenotype, is a matricellular secreted protein that contributes to cardiac remodeling. Periostin plays important roles in mediating cell–matrix signal transduction and in promoting pro‐fibrotic TGF‐β signaling via coupling with matrix associated lysyl oxidase; it is highly expressed in myofibroblasts, but is not expressed in fibroblasts. We have shown that the transcription factor scleraxis induces the phenotype conversion of cardiac fibroblasts to myofibroblasts by directly transactivating the expression of proteins highly up‐regulated in myofibroblasts, including collagen 1α2, fibronectin and α‐smooth muscle actin. Here we report that the treatment of primary adult rat cardiac myofibroblasts with angiotensin II significantly increases periostin gene expression in parallel with increased scleraxis expression. Over‐expression of scleraxis in myofibroblasts increased periostin expression nearly 19‐fold at the mRNA level. TGF‐b treatment induced periostin expression in cardiac myofibroblasts isolated from wild type mice, but failed to show a similar effect in cells isolated from scleraxis null mice. Using in silico analysis, we identified putative E‐box sites within the periostin gene promoter to which scleraxis may bind to potentially regulate promoter transactivation. Our data suggests that scleraxis is necessary and sufficient for TGF‐β mediated periostin expression. Our findings are consistent with a potential role for scleraxis in cardiac fibrosis, where periostin and fibrillar collagen gene expression are elevated in parallel with scleraxis. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".