THE LINKING OF BETA‐OXIDATION TO CARDIOLIPIN REMODELING
Bibliographic record
Abstract
We previously identified a human linoleoyl‐Coenzyme A monolysocardiolipin (MLCL) acyltransferase activity (MLCL AT‐1) (Taylor and Hatch 2009 J. Biol. Chem. 284: 30360‐30371). This 59 kDa human protein was identical to the 74 kDa human α‐subunit of trifunctional protein (αTFP) minus the first 237 amino acids. Here we characterize the MLCL AT activity of αTFP. The 74 kDa αTFP exhibited MLCL AT activity and western blot analysis under non‐denaturing conditions revealed the presence of a 150 kDa protein indicative of the dimeric form of αTFP. NAD stimulated the MLCL AT activity of αTFP. Recombinant human αTFP exhibited specificity for linoleoyl‐CoA in the acylation of MLCL to cardiolipin (CL). Expression of αTFP increased MLCL AT activity and [1‐ 14 C]linoleate incorporation into CL in Hela cells, whereas, RNAi knock down had the opposite effect. RNAi knock down of the β‐subunit of trifunctional protein increased MLCL AT activity indicating that αTFP has MLCL AT activity and the β‐subunit is a negative regulator of activity. Thyroxine‐treatment of rats, which increases MLCL AT activity, increased αTFP mRNA expression compared to euthyroid controls, whereas, propylthiouracil‐treatment, which reduced MLCL AT activity, had the opposite effect. The results clearly indicate that the 74 kDa human αTFP has MLCL AT activity and thus linking an enzyme of CL remodeling with β‐oxidation.
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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".