Uncoupling Farnesol-induced Apoptosis from Its Inhibition of Phosphatidylcholine Synthesis
Bibliographic record
Abstract
Genetic inactivation of the synthesis of phosphatidylcholine, the most abundant membrane lipid in eukaryotic cells, induces apoptosis. Administration of farnesol, a catabolite within the isoprenoid/cholesterol pathway, also induces apoptosis. The mechanism by which farnesol induces apoptosis is currently believed to be by direct competitive inhibition with diacylglycerol for cholinephosphotransferase, the final step in the phosphatidylcholine biosynthetic pathway. Our recent isolation of the first mammalian cholinephosphotransferase cDNA has enabled us to more precisely assess how farnesol affects phosphatidylcholine synthesis and the induction of apoptosis. Induced over-expression of cholinephosphotransferase in Chinese hamster ovary cells prevented the block in phosphatidylcholine biosynthesis associated with exposure to farnesol. However, induced over-expression of cholinephosphotransferase was not sufficient for the prevention of farnesol-induced apoptosis. In addition, exogenous administration of diacylglycerol prevented farnesol-induced apoptosis but did not relieve the farnesol-induced block in phosphatidylcholine synthesis. We also developed an in vitro lipid mixed micelle cholinephosphotransferase enzyme assay, as opposed to the delivery of the diacylglycerol substrate in a detergent emulsion, and demonstrated that there was no direct inhibition of cholinephosphotransferase by farnesol or its phosphorylated metabolites. The execution of apoptosis by farnesol appears to be a separate and distinct event from farnesol-induced inhibition of phosphatidylcholine biosynthesis and instead likely occurs through a diacylglycerol-mediated process that is downstream of phosphatidylcholine synthesis.
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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 | 0.001 |
| 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".