ACE2 Deficiency Worsens Epicardial Adipose Tissue Inflammation and Cardiac Dysfunction in Response to Diet-Induced Obesity
Bibliographic record
Abstract
Obesity is increasing in prevalence and is strongly associated with metabolic and cardiovascular disorders. The renin-angiotensin system (RAS) has emerged as a key pathogenic mechanism for these disorders; angiotensin (Ang)-converting enzyme 2 (ACE2) negatively regulates RAS by metabolizing Ang II into Ang 1-7. We studied the role of ACE2 in obesity-mediated cardiac dysfunction. ACE2 null (ACE2KO) and wild-type (WT) mice were fed a high-fat diet (HFD) or a control diet and studied at 6 months of age. Loss of ACE2 resulted in decreased weight gain but increased glucose intolerance, epicardial adipose tissue (EAT) inflammation, and polarization of macrophages into a proinflammatory phenotype in response to HFD. Similarly, human EAT in patients with obesity and heart failure displayed a proinflammatory macrophage phenotype. Exacerbated EAT inflammation in ACE2KO-HFD mice was associated with decreased myocardial adiponectin, decreased phosphorylation of AMPK, increased cardiac steatosis and lipotoxicity, and myocardial insulin resistance, which worsened heart function. Ang 1-7 (24 µg/kg/h) administered to ACE2KO-HFD mice resulted in ameliorated EAT inflammation and reduced cardiac steatosis and lipotoxicity, resulting in normalization of heart failure. In conclusion, ACE2 plays a novel role in heart disease associated with obesity wherein ACE2 negatively regulates obesity-induced EAT inflammation and cardiac insulin resistance.
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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) | 0.000 | 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".