Adiponectin inhibits leptin‐induced cardiomyocyte hypertrophy by attenuation of calcineurin/NFAT activation
Bibliographic record
Abstract
Leptin and adiponectin are adipokines which exert opposite effects on cardiac pathology. Leptin induces cardiomyocyte hypertrophy and hyperleptinemia has been shown to be a risk factor for developing heart failure. In contrast adiponectin is antihypertrophic and reduced plasma adiponectin levels constitute a cardiovascular risk factor. In the present study we determined whether adiponectin can modify leptin‐induced hypertrophy in cultured rat ventricular myocytes. Leptin (3.1 nM) treatment for 24 h produced a robust hypertrophy as evidenced by significantly increased cell surface area, α‐skeletal actin gene expression and rate of protein synthesis. These effects were associated with significantly increased calcineurin activity and import of the transcriptional factor NFAT3 into nuclei. The leptin–induced calcineurin activation was paralleled by increased intracellular Na+ and Ca2+ concentrations. The pro‐hypertrophic effect of leptin was completely prevented in myocytes co‐treated with adiponectin (0.5 μM). These effects were associated with attenuation of leptin‐induced elevations in intracellular Na+ and Ca2+ concentrations, calcineurin activation and NFAT3 nuclear translocation. Thus, adiponectin may represent an endogenous factor mitigating the pro‐hypertrophic effect of leptin by preventing calcineurin activation. Supported by the Canadian Institutes of Health Research.
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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".