GATA-4 Is a Nuclear Mediator of Mechanical Stretch-activated Hypertrophic Program
Bibliographic record
Abstract
In overloaded heart the cardiomyocytes adapt to increased mechanical and neurohumoral stress by activation of hypertrophic program, resulting in morphological changes of individual cells and specific changes in gene expression. Accumulating evidence suggests an important role for the zinc finger transcription factor GATA-4 in hypertrophic agonist-induced cardiac hypertrophy. However, its role in stretch-induced cardiomyocyte hypertrophy is not known. We employed an in vitro mechanical stretch model of cultured cardiomyocytes and used rat B-type natriuretic peptide promoter as stretch-sensitive reporter gene. Stretch transiently increased GATA-4 DNA binding activity and transcript levels, which was followed by increases in the expression of B-type natriuretic peptide as well as atrial natriuretic peptide and skeletal alpha-actin genes. The stretch inducibility mapped primarily to the proximal 520 bp of the B-type natriuretic peptide promoter. Mutational studies showed that the tandem GATA consensus sites of the proximal promoter in combination with an Nkx-2.5 binding element are critical for stretch-activated B-type natriuretic peptide transcription. Inhibition of GATA-4 protein production by adenovirus-mediated transfer of GATA-4 antisense cDNA blocked stretch-induced increases in B-type natriuretic peptide transcript levels and the sarcomere reorganization. The proportion of myocytes with assembled sarcomeres in control adenovirus-infected cultures increased from 14 to 59% in response to stretch, whereas the values for GATA-4 antisense-treated cells were 6 and 13%, respectively. These results show that activation of GATA-4, in cooperation with a factor binding on Nkx-2.5 binding element, is essential for mechanical stretch-induced cardiomyocyte hypertrophy.
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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) | 0.002 | 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".