Protein lysine acetylation does not contribute to the high rates of fatty acid oxidation seen in the post-ischemic heart
Bibliographic record
Abstract
High rates of cardiac fatty acid oxidation during reperfusion of ischemic hearts contribute to contractile dysfunction. This study aimed to investigate whether lysine acetylation affects fatty acid oxidation rates and recovery in post-ischemic hearts. Isolated working hearts from Sprague Dawley rats were perfused with 1.2 mM palmitate and 5 mM glucose and subjected to 30 min of ischemia and 40 min of reperfusion. Cardiac function, fatty acid oxidation, glucose oxidation, and glycolysis rates were compared between pre- and post-ischemic hearts. The acetylation status of enzymes involved in cardiac energy metabolism was assessed in both groups. Reperfusion after ischemia resulted in only a 41% recovery of cardiac work. Fatty acid oxidation and glycolysis rates increased while glucose oxidation rates decreased. The contribution of fatty acid oxidation to ATP production and TCA cycle activity increased from 90 to 93% and from 94.9 to 98.3%, respectively, in post-ischemic hearts. However, the overall acetylation status and acetylation levels of metabolic enzymes did not change in response to ischemia and reperfusion. These findings suggest that acetylation may not contribute to the high rates of fatty acid oxidation and reduced glucose oxidation observed in post-ischemic hearts perfused with high levels of palmitate substrate.
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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) | 0.000 | 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 | 0.000 |
| 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".