Etomoxir mediates differential metabolic channeling of fatty acid and glycerol precursors into cardiolipin in H9c2 cells
Bibliographic record
Abstract
We examined the effect of etomoxir treatment on de novo cardiolipin (CL) biosynthesis in H9c2 cardiac myoblast cells. Etomoxir treatment did not affect the activities of the CL biosynthetic and remodeling enzymes but caused a reduction in [1-14C]palmitic acid or [1-14C]oleic acid incorporation into CL. The mechanism was a decrease in fatty acid flux through the de novo pathway of CL biosynthesis via a redirection of lipid synthesis toward 1,2-diacyl-sn-glycerol utilizing reactions mediated by a 35% increase (P < 0.05) in membrane phosphatidate phosphohydrolase activity. In contrast, etomoxir treatment increased [1,3-3H]glycerol incorporation into CL. The mechanism was a 33% increase (P < 0.05) in glycerol kinase activity, which produced an increased glycerol flux through the de novo pathway of CL biosynthesis. Etomoxir treatment inhibited 1,2-diacyl-sn-glycerol acyltransferase activity by 81% (P < 0.05), thereby channeling both glycerol and fatty acid away from 1,2,3-triacyl-sn-glycerol utilization toward phosphatidylcholine and phosphatidylethanolamine biosynthesis. In contrast, etomoxir inhibited myo-[3H]inositol incorporation into phosphatidylinositol and the mechanism was an inhibition in inositol uptake. Etomoxir did not affect [3H]serine uptake but resulted in an increased formation of phosphatidylethanolamine derived from phosphatidylserine. The results indicate that etomoxir treatment has diverse effects on de novo glycerolipid biosynthesis from various metabolic precursors. In addition, etomoxir mediates a distinct and differential metabolic channeling of glycerol and fatty acid precursors into CL.
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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".