Dissociation of Cardiogenic and Postnatal Myocardial Activities of GATA4
Bibliographic record
Abstract
Transcription factor GATA4 is a critical regulator of the embryonic and postnatal heart, but the mechanisms and cofactors required for its diverse functions are not fully understood. Here, we show that whereas the N-terminal domain of GATA4 is required for inducing cardiogenesis and for promoting postnatal cardiomyocyte survival, distinct residues and domains therein are necessary to mediate these effects. Cardiogenic activity of GATA4 requires a 24-amino-acid (aa) region (aa 129 to 152) which is needed for transcriptional synergy and physical interaction with BAF60c. The same region is not essential for induction of endoderm or blood cell markers by GATA4, suggesting that it acts as a cell-type-specific transcriptional activation domain. On the other hand, a serine residue at position 105, which is a known target for mitogen-activated protein kinase (MAPK) phosphorylation, is necessary for GATA4-dependent cardiac myocyte survival and hypertrophy but is entirely dispensable for GATA4-induced cardiogenesis. We find that S105 is differentially required for transcriptional synergy between GATA4 and serum response factor (SRF) but not other cardiac cofactors such as TBX5 and NKX2.5. The findings provide new insight into GATA4 mechanisms of action and suggest that distinct regulatory pathways regulate activities of GATA4 in embryonic development and postnatal hearts.
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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".