Angiotensin 1–7 Ameliorates Diabetic Cardiomyopathy and Diastolic Dysfunction in <i>db/db</i> Mice by Reducing Lipotoxicity and Inflammation
Bibliographic record
Abstract
BACKGROUND: The angiotensin-converting enzyme 2 and angiotensin-(1-7) (Ang 1-7)/MasR (Mas receptor) axis are emerging as a key pathway that can modulate the development of diabetic cardiomyopathy. We studied the effects of Ang 1-7 on diabetic cardiomyopathy in db/db diabetic mice to elucidate the therapeutic effects and mechanism of action. METHODS AND RESULTS: Ang 1-7 was administered to 5-month-old male db/db mice for 28 days via implanted micro-osmotic pumps. Ang 1-7 treatment ameliorated myocardial hypertrophy and fibrosis with normalization of diastolic dysfunction assessed by pressure-volume loop analysis and echocardiography. The functional improvement by Ang 1-7 was accompanied by a reduction in myocardial lipid accumulation and systemic fat mass and inflammation and increased insulin-stimulated myocardial glucose oxidation. Increased myocardial protein kinase C levels and loss of phosphorylation of extracellular signal-regulated kinase 1/2 were prevented by Ang 1-7. Furthermore, Ang 1-7 treatment decreased cardiac triacylglycerol and ceramide levels in db/db mice, concomitantly with an increase in myocardial adipose triglyceride lipase expression. Changes in adipose triglyceride lipase expression correlated with increased SIRT1 (silent mating type information regulation 2 homolog 1) levels and deacetylation of FOXO1 (forkhead box O1). CONCLUSIONS: We identified a novel beneficial effect of Ang 1-7 on diabetic cardiomyopathy that involved a reduction in cardiac hypertrophy and lipotoxicity, adipose inflammation, and an upregulation of adipose triglyceride lipase. Ang 1-7 completely rescued the diastolic dysfunction in the db/db model. Ang 1-7 represents a promising therapy for diabetic cardiomyopathy associated with type 2 diabetes mellitus.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".