Cardiac metabolite exchange measured in pigs during myocardial ischemia and reperfusion
Bibliographic record
Abstract
ABSTRACT Myocardial ischemia and reperfusion (I/R) injury are the primary contributors to death in patients with cardiovascular disease. While decades of research have elucidated the molecular players and biochemical mechanisms underlying I/R injury, how these pathologies influence the metabolic activities of the heart remains incompletely understood. Such a knowledge gap hampers the development of therapies aimed at mitigating the metabolic stresses of the heart during injury. Using comprehensive arteriovenous metabolomics in a highly relevant porcine I/R model, we report the metabolic landscape of cardiac metabolic changes after ischemia and during the reperfusion time course. Paradoxically, ischemia increases the cardiac uptake of circulating fatty acids while reperfusion for 60 minutes reverses this activity. By 120 minutes of reperfusion, the hearts resume the uptake of fatty acids, suggesting restoration of their metabolism. On the other hand, we found a strong release of amino acids by the heart only after 60-minute reperfusion, but not after 120-minute reperfusion, implicating I/R-induced transient protein degradation. In addition to these findings, we identified several previously unrecognized changes in cardiac metabolic inputs and outputs during I/R, including nucleotides, TCA cycle intermediates and creatine/creatinine. These data highlight the dynamic alterations in cardiac metabolism in response to I/R, providing insights into how to mitigate myocardial I/R injury.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".