Increased ketone body oxidation provides additional energy for the failing heart without improving cardiac efficiency
Bibliographic record
Abstract
AIMS: The failing heart is energy-starved and inefficient due to perturbations in energy metabolism. Although ketone oxidation has been shown recently to increase in the failing heart, it remains unknown whether this improves cardiac energy production or efficiency. We therefore assessed cardiac metabolism in failing hearts and determined whether increasing ketone oxidation improves cardiac energy production and efficiency. METHODS AND RESULTS: C57BL/6J mice underwent sham or transverse aortic constriction (TAC) surgery to induce pressure overload hypertrophy over 4-weeks. Isolated working hearts from these mice were perfused with radiolabelled β-hydroxybutyrate (βOHB), glucose, or palmitate to assess cardiac metabolism. Ejection fraction decreased by 45% in TAC mice. Failing hearts had decreased glucose oxidation while palmitate oxidation remained unchanged, resulting in a 35% decrease in energy production. Increasing βOHB levels from 0.2 to 0.6 mM increased ketone oxidation rates from 251 ± 24 to 834 ± 116 nmol·g dry wt-1 · min-1 in TAC hearts, rates which were significantly increased compared to sham hearts and occurred without decreasing glycolysis, glucose, or palmitate oxidation rates. Therefore, the contribution of ketones to energy production in TAC hearts increased to 18% and total energy production increased by 23%. Interestingly, glucose oxidation, in parallel with total ATP production, was also significantly upregulated in hearts upon increasing βOHB levels. However, while overall energy production increased, cardiac efficiency was not improved. CONCLUSIONS: Increasing ketone oxidation rates in failing hearts increases overall energy production without compromising glucose or fatty acid metabolism, albeit without increasing cardiac efficiency.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".