Transcription factor GATA4 regulates cardiac BCL2 gene expression in vitro and in vivo
Bibliographic record
Abstract
The transcription factor GATA-4 protects cardiomyocytes against doxorubicin-induced cardiotoxicity. Here, we report the identification of Bcl2 as a direct target gene of GATA4 that may mediate the prosurvival function of GATA4 in cardiomyocytes. Bcl2 transcript and protein levels were reduced by doxorubicin in neonatal rat ventricular cardiomyocytes (NRVC) and in mouse heart as determined by RT-PCR and Western blot analysis. The reduction in Bcl2 was prevented by overexpression of GATA4 in NRVC and in transgenic mouse heart. Also, expression of GATA4 increased baseline Bcl2 levels by 30% in NRVC and 2.7-fold in transgenic heart, indicating the sufficiency of GATA4 to up-regulate Bcl2 gene expression. GATA4 knockdown by siRNA reduced Bcl2 levels by 48% in NRVC, suggesting that GATA4 is required for Bcl2 constitutive gene expression. Transfection of HEK cells with GATA4 plasmids activated Bcl2 promoter and elevated Bcl2 protein levels. Deletion and mutagenesis analysis revealed that a consensus GATA motif at base -266 on the promoter conserved across multiple species is partially responsible for the promoter activity. Electrophoretic mobility shift and chromatin immunoprecipitation assays demonstrate that GATA4 directly bound to this GATA site. Together, these results indicate that GATA4 positively regulates cardiac Bcl2 gene expression in vitro and in vivo.
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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".