Myocardial Energy Substrate Metabolism in Heart Failure : from Pathways to Therapeutic Targets
Bibliographic record
Abstract
Despite recent advances in therapy, heart failure remains a major cause of mortality and morbidity and is a growing healthcare burden worldwide. Alterations in myocardial energy substrate metabolism are a hallmark of heart failure, and are associated with an energy deficit in the failing heart. Previous studies have shown that a metabolic shift from mitochondrial oxidative metabolism to glycolysis, as well as an uncoupling between glycolysis and glucose oxidation, plays a crucial role in the development of cardiac inefficiency and functional impairment in heart failure. Therefore, optimizing energy substrate utilization, particularly by increasing mitochondrial glucose oxidation, can be a potentially promising approach to decrease the severity of heart failure by improving mechanical cardiac efficiency. One approach to stimulating myocardial glucose oxidation is to inhibit fatty acid oxidation. This review will overview the physiological regulation of both myocardial fatty acid and glucose oxidation in the heart, and will discuss what alterations in myocardial energy substrate metabolism occur in the failing heart. Furthermore, lysine acetylation has been recently identified as a novel post-translational pathway by which mitochondrial enzymes involved in all aspects of cardiac energy metabolism can be regulated. Thus, we will also discuss the effect of acetylation of metabolic enzymes on myocardial energy substrate preference in the settings of heart failure. Finally, we will focus on pharmacological interventions that target enzymes involved in fatty acid uptake, fatty acid oxidation, transcriptional regulation of fatty acid oxidation, and glucose oxidation to treat heart failure.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".