Regulation of Twist1 and Snail1 Gene Expression in Cardiac Fibroblasts by Scleraxis
Bibliographic record
Abstract
Cardiac fibrosis causes progressive cardiac stiffening due to abnormal deposition of extracellular matrix (ECM) and alters electrical conduction of the action potential, resulting in heart failure and death. Cardiac fibroblasts largely arise from epithelial precursors during development via epithelial‐to‐mesenchymal transition (EMT), and upon injury or stress, are further converted to an activated state – myofibroblasts – which express a variety of pro‐fibrotic genes responsible for ECM synthesis and deposition. Our previous data suggested that the transcription factor scleraxis plays a key role in regulating cardiac fibroblast cell fate, including EMT and myofibroblast conversion. Here, we examined the role of scleraxis in transactivating expression of genes encoding key EMT regulators including the basic helix‐loop‐helix transcription factor Twist1 and the zinc finger transcription factor Snail1. Over‐expression of scleraxis in NIH3T3 fibroblasts up‐regulated Twist1 and Snail1 expression. Using luciferase reporter assays coupled with point mutagenesis, we found that scleraxis is sufficient to directly transactivate the Twist1 and Snail1 gene promoters, and identified the responsible scleraxis binding sites in each promoter. Loss of scleraxis conversely attenuated expression of these genes. Together, our data indicates that scleraxis controls EMT via direct upstream regulation of these key EMT regulatory genes. Support or Funding Information Supported by the Canadian Institutes of Health Research (MOP136862 to MPC), Research Manitoba (RSN) and the University of Manitoba GETS Program (HAS, DSA, RSN).
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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 | 0.000 |
| 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".