Aldose reductase inhibition alleviates diabetic cardiomyopathy and is associated with a decrease in myocardial fatty acid oxidation
Bibliographic record
Abstract
BACKGROUND: Cardiovascular diseases, including diabetic cardiomyopathy, are major causes of death in people with type 2 diabetes. Aldose reductase activity is enhanced in hyperglycemic conditions, leading to altered cardiac energy metabolism and deterioration of cardiac function with adverse remodeling. Because disturbances in cardiac energy metabolism can promote cardiac inefficiency, we hypothesized that aldose reductase inhibition may mitigate diabetic cardiomyopathy via normalization of cardiac energy metabolism. METHODS: Male C57BL/6J mice (8-week-old) were subjected to experimental type 2 diabetes/diabetic cardiomyopathy (high-fat diet [60% kcal from lard] for 10 weeks with a single intraperitoneal injection of streptozotocin (75 mg/kg) at 4 weeks), following which animals were randomized to treatment with either vehicle or AT-001, a next-generation aldose reductase inhibitor (40 mg/kg/day) for 3 weeks. At study completion, hearts were perfused in the isolated working mode to assess energy metabolism. RESULTS: in the presence of insulin) but no change in glucose oxidation rates compared to the control group. In addition, cardiac fibrosis and hypertrophy were also mitigated via AT-001 treatment in mice with diabetic cardiomyopathy. CONCLUSIONS: Inhibiting aldose reductase activity ameliorates diastolic dysfunction in mice with experimental type 2 diabetes, which may be due to the decline in myocardial fatty acid oxidation, indicating that treatment with AT-001 may be a novel approach to alleviate diabetic cardiomyopathy in patients with diabetes.
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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 | 0.000 | 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".