Low- and High-Density Lipoprotein Metabolism in HepG2 Cells Expressing Various Levels of Apolipoprotein E
Bibliographic record
Abstract
To determine the importance of hepatic apolipoprotein (apo) E in lipoprotein metabolism, HepG2 cells were transfected with a constitutive expression vector (pRc/CMV) containing either the complete or the first 474 base pairs of the human apoE cDNA inserted in an antisense orientation, for apoE gene inactivation, or the full-length human apoE cDNA inserted in a sense orientation for overexpression of apoE. Stable transformants were obtained that expressed 15, 24, 226, and 287% the apoE level of control HepG2 cells. The metabolism of low-density lipoprotein (LDL) and high-density lipoprotein-3 (HDL(3)), two lipoprotein classes following both holoparticle and cholesteryl esters (CE)-selective uptake pathways, was compared between all these cells. LDL-protein degradation, an indicator of the holoparticle uptake, was greater in low apoE expressing cells than in control or high expressing cells, while HDL(3)-protein degradation paralleled the apoE levels of the cells (r(2) = 0.989). LDL- and HDL(3)-protein association was higher in low apoE expressing cells compared to control cells. In opposition, LDL- and HDL(3)-CE association was not different from control cells in low apoE expressing cells but rose in high apoE expressing cells. In consequence, the CE-selective uptake (CE/protein association ratio) was positively correlated with the level of apoE expression in all cells for both LDL (r(2) = 0.977) and HDL(3) (r(2) = 0.998). We also show that, although in normal and low apoE expressor cells, 92% of LDL- and 80% HDL(3)-CE hydrolysis is sensitive to chloroquine suggesting a pathway linked to lysosomes for both lipoproteins, cells overexpressing apoE lost 60% of chloroquine-sensitive HDL(3)-CE hydrolysis without affecting that of LDL-CE. Thus, the level of apoE expression in HepG2 cells determines the fate of LDL and HDL(3).
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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 | 0.001 |
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".