Role of angiotensin-converting enzyme 2 (ACE2) in diabetic cardiovascular complications
Bibliographic record
Abstract
Diabetes mellitus results in severe cardiovascular complications, and heart disease and failure remain the major causes of death in patients with diabetes. Given the increasing global tide of obesity and diabetes, the clinical burden of diabetes-induced cardiovascular disease is reaching epidemic proportions. Therefore urgent actions are needed to stem the tide of diabetes which entails new prevention and treatment tools. Clinical and pharmacological studies have demonstrated that AngII (angiotensin II), the major effector peptide of the RAS (renin-angiotensin system), is a critical promoter of insulin resistance and diabetes mellitus. The role of RAS and AngII has been implicated in the progression of diabetic cardiovascular complications and AT1R (AngII type 1 receptor) blockers and ACE (angiotensin-converting enzyme) inhibitors have shown clinical benefits. ACE2, the recently discovered homologue of ACE, is a monocarboxypeptidase which converts AngII into Ang-(1-7) [angiotensin-(1-7)] which, by virtue of its actions on the MasR (Mas receptor), opposes the effects of AngII. In animal models of diabetes, an early increase in ACE2 expression and activity occurs, whereas ACE2 mRNA and protein levels have been found to decrease in older STZ (streptozotocin)-induced diabetic rats. Using the Akita mouse model of Type 1 diabetes, we have recently shown that loss of ACE2 disrupts the balance of the RAS in a diabetic state and leads to AngII/AT1R-dependent systolic dysfunction and impaired vascular function. In the present review, we will discuss the role of the RAS in the pathophysiology and treatment of diabetes and its complications with particular emphasis on potential benefits of the ACE2/Ang-(1-7)/MasR axis activation.
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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 | 0.001 | 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".