Lipid- and phospho-regulation of CTP:Phosphocholine Cytidylyltransferase α association with nuclear lipid droplets
Bibliographic record
Abstract
Fatty acids stored in triacylglycerol-rich lipid droplets are assembled with a surface monolayer composed primarily of phosphatidylcholine (PC). Fatty acids stimulate PC synthesis by translocating CTP:phosphocholine cytidylyltransferase (CCT) α to the inner nuclear membrane, nuclear lipid droplets (nLD) and lipid associated promyelocytic leukemia (PML) structures (LAPS). Huh7 cells were used to identify how CCTα translocation onto these nuclear structures are regulated by fatty acids and phosphorylation of its serine-rich P-domain. Oleate treatment of Huh7 cells increased nLDs and LAPS that became progressively enriched in CCTα. In cells expressing the phosphatidic acid phosphatase Lipin1α or 1β, the expanded pool of nLDs and LAPS had a proportional increase in associated CCTα. In contrast, palmitate induced few nLDs and LAPS and inhibited the oleate-dependent translocation of CCTα without affecting total nLDs. Phospho-memetic or phospho-null mutations in the P-domain revealed that a 70% phosphorylation threshold, rather than site-specific phosphorylation, regulated CCTα association with nLDs and LAPS. In vitro candidate kinase and inhibitor studies in Huh7 cells identified cyclin-dependent kinase (CDK) 1 and 2 as putative P-domain kinases. In conclusion, CCTα translocation onto nLDs and LAPS is dependent on available surface area and fatty acid composition, as well as threshold phosphorylation of the P-domain potentially involving CDKs.
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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".