Regulation of Malonyl-CoA Concentration and Turnover in the Normal Heart
Bibliographic record
Abstract
The goal of this study was to test the relationship between malonyl-CoA concentration and its turnover measured in isolated rat hearts perfused with NaH(13)CO(3). This turnover is a direct measurement of the flux of acetyl-CoA carboxylation in the intact heart. It also reflects the rate of malonyl-CoA decarboxylation, i.e. the only known fate of malonyl-CoA in the heart. Conditions were selected to result in stable malonyl-CoA concentrations ranging from 1.5 to 5 nmol.g wet weight-(1). The malonyl-CoA concentration was directly correlated with the turnover of malonyl-CoA, ranging from 0.7 to 4.2 nmol.min(-) (1).g wet weight(-1) (slope = 0.98, r(2) = 0.94). The V(max) activities of acetyl-CoA carboxylase and of malonyl-CoA decarboxylase exceeded the rate of malonyl-CoA turnover by 2 orders of magnitude and did not correlate with either concentration or turnover of malonyl-CoA. However, conditions of perfusion that increased acetyl-CoA supply resulted in higher turnover and concentration, demonstrating that malonyl-CoA turnover is regulated by the supply of acetyl-CoA. The only condition where the activity of malonyl-CoA decarboxylase regulated malonyl-CoA kinetics was when the enzyme was pharmacologically inhibited, resulting in increased malonyl-CoA concentration and decreased turnover. Our data show that, in the absence of enzyme inhibitors, the rate of acetyl-CoA carboxylation is the main determinant of the malonyl-CoA concentration in the heart.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".