Peroxisomal Fatty Acid Oxidation Is a Substantial Source of the Acetyl Moiety of Malonyl-CoA in Rat Heart
Bibliographic record
Abstract
Little is known about the sources of acetyl-CoA used for the synthesis of malonyl-CoA, a key regulator of mitochondrial fatty acid oxidation in the heart. In perfused rat hearts, we previously showed that malonyl-CoA is labeled from both carbohydrates and fatty acids. This study was aimed at assessing the mechanisms of incorporation of fatty acid carbons into malonyl-CoA. Rat hearts were perfused with glucose, lactate, pyruvate, and a fatty acid (palmitate, oleate or docosanoate). In each experiment, substrates were (13)C-labeled to yield singly or/and doubly labeled acetyl-CoA. The mass isotopomer distribution of malonyl-CoA was compared with that of the acetyl moiety of citrate, which reflects mitochondrial acetyl-CoA. In the presence of labeled glucose or lactate/pyruvate, the (13)C labeling of malonyl-CoA was up to 2-fold lower than that of mitochondrial acetyl-CoA. However, in the presence of a fatty acid labeled in its first acetyl moiety, the (13)C labeling of malonyl-CoA was up to 10-fold higher than that of mitochondrial acetyl-CoA. The labeling of malonyl-CoA and of the acetyl moiety of citrate is compatible with peroxisomal beta-oxidation forming C(12) and C(14) acyl-CoAs and contributing >50% of the fatty acid-derived acetyl groups that end up in malonyl-CoA. This fraction increases with the fatty acid chain length. By supplying acetyl-CoA for malonyl-CoA synthesis, peroxisomal beta-oxidation may participate in the control of mitochondrial fatty acid oxidation in the heart. In addition, this pathway may supply some acyl groups used in protein acylation, which is increasingly recognized as an important regulatory mechanism for many biochemical processes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".