Cardiac energy metabolism in diabetes: emerging therapeutic targets and clinical implications
Bibliographic record
Abstract
Patients with diabetes are at an increased risk for developing diabetic cardiomyopathy and other cardiovascular complications. Alterations in cardiac energy metabolism in patients with diabetes, including an increase in mitochondrial fatty acid oxidation and a decrease in glucose oxidation, are important contributing factors to this increase in cardiovascular disease. A switch from glucose oxidation to fatty acid oxidation not only decreases cardiac efficiency due to increased oxygen consumption but it can also increase reactive oxygen species production, increase lipotoxicity, and redirect glucose into other metabolic pathways that, combined, can lead to heart dysfunction. Currently, there is a lack of therapeutics available to treat diabetes-induced heart failure that specifically target cardiac energy metabolism. However, it is becoming apparent that part of the benefit of existing agents such as GLP-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors may be related to their effects on cardiac energy metabolism. In addition, direct approaches aimed at inhibiting cardiac fatty acid oxidation or increasing glucose oxidation hold future promise as potential therapeutic approaches to treat diabetes-induced cardiovascular disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".