Gli2 and MEF2C activate each other's expression and function synergistically during cardiomyogenesis in vitro
Bibliographic record
Abstract
The transcription factors Gli2 (glioma-associated factor 2), which is a transactivator of Sonic Hedgehog (Shh) signalling, and myocyte enhancer factor 2C (MEF2C) play important roles in the development of embryonic heart muscle and enhance cardiomyogenesis in stem cells. Although the physiological importance of Shh signalling and MEF2 factors in heart development is well known, the mechanistic understanding of their roles is unclear. Here, we demonstrate that Gli2 and MEF2C activated each other's expression while enhancing cardiomyogenesis in differentiating P19 EC cells. Furthermore, dominant-negative mutant proteins of either Gli2 or MEF2C repressed each other's expression, while impairing cardiomyogenesis in P19 EC cells. In addition, chromatin immunoprecipitation (ChIP) revealed association of Gli2 to the Mef2c gene, and of MEF2C to the Gli2 gene in differentiating P19 cells. Finally, co-immunoprecipitation studies showed that Gli2 and MEF2C proteins formed a complex, capable of synergizing on cardiomyogenesis-related promoters containing both Gli- and MEF2-binding elements. We propose a model whereby Gli2 and MEF2C bind each other's regulatory elements, activate each other's expression and form a protein complex that synergistically activates transcription, enhancing cardiac muscle development. This model links Shh signalling to MEF2C function during cardiomyogenesis and offers mechanistic insight into their in vivo functions.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".