Conversion of Low Density Lipoprotein-associated Phosphatidylcholine to Triacylglycerol by Primary Hepatocytes
Bibliographic record
Abstract
We have studied the uptake and metabolism of phosphatidylcholine (PC), the major phospholipid of low density lipoproteins (LDL), by cultures of primary hepatocytes. Strikingly, in the absence of the LDL receptor, PC incorporation into hepatocytes was inhibited by only 30%, whereas cholesteryl ether uptake was inhibited by 60-70%. On the other hand, scavenger receptor class B, type I, the other important receptor for LDL in the liver, was found to be responsible for the uptake of the remaining 30-40% of LDL-cholesteryl ether. PC uptake was, however, only partially inhibited (30%) in scavenger receptor class B, type I, knock-out hepatocytes. Once LDL-PC was taken up by hepatocytes, approximately 50% of LDL-[(3)H]oleate-PC was converted to triacylglycerol rather than degraded in lysosomes as occurs for LDL-derived cholesteryl esters. The remainder of the LDL-derived PC was not significantly metabolized to other products. Triacylglycerol synthesis from LDL-PC requires a PC-phospholipase C activity as demonstrated by inhibition with the phospholipase C inhibitor D609 or activation with rattlesnake venom. Small interfering RNA-mediated suppression of acyl-CoA:diacylglycerol acyltransferase 2 (DGAT2), but not DGAT1, decreased the acylation of the LDL-derived diacylglycerol. These findings show that PC in LDL particles is taken up not only by the classical receptors but also by additional mechanism(s) followed by metabolism that is completely different from the cholesteryl esters or apoB100, the other main components of LDL.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".