Suppression of endothelin-1-induced cardiac myocyte hypertrophy by PPAR agonists: role of diacylglycerol kinase zeta
Bibliographic record
Abstract
AIMS: Ligand activation of peroxisome proliferator-activated receptors (PPARs) prevents cardiomyocyte hypertrophy, but the underlying signalling mechanisms remain unknown. We previously reported that the anti-hypertrophic effect of the dietary polyunsaturated fatty acid, conjugated linoleic acid (CLA), was associated with the upregulation of diacylglycerol (DAG) kinase (DGK). DGK catalyses phosphorylative conversion/attenuation of DAG, thereby modulating protein kinase C (PKC) and G-protein signalling. As the anti-hypertrophic effects of CLA were attenuated by inhibitors of PPARs, the present aim was to investigate the involvement of DGK in the anti-hypertrophic actions of bona fide selective PPAR agonists. METHODS AND RESULTS: Endothelin-1 (ET1)-induced hypertrophy of neonatal, and then adult, Sprague-Dawley rat cardiomyocytes served as experimental paradigms. Expression of DGKζ, the predominant DGK isoform in myocytes, was stimulated by ligands of PPARγ (troglitazone) or PPARα (fenofibrate) and was accompanied by increased DGK activity. Troglitazone or fenofibrate prevented hypertrophic indicators elicited by ET1, including myocyte size augmentation, de novo protein synthesis, hypertrophic gene expression, and activation of the pro-hypertrophic signal, PKCε. shRNA knockdown of DGKζ abolished the growth-inhibitory effects of PPARs and restored all ET1-induced aspects of hypertrophy. Importantly, the involvement of DGK in the ability of troglitazone and fenofibrate to block ET1-induced hypertrophy and PKCε signalling was verified in adult rat myocytes. CONCLUSION: Collectively, these findings show that the anti-hypertrophic actions of PPARs require DGKζ. Thus, within the cardiomyocyte, there exists a PPAR-DGK signalling axis that underpins the ability of PPAR ligands to inhibit ET1-dependent 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 | 0.001 |
| 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".