Modulation of hepG2 cell net apolipoprotein B secretion by the citrus polymethoxyflavone, tangeretin
Bibliographic record
Abstract
The purpose of the present study was to examine the role of tangeretin, a polymethoxylated flavone from citrus fruits, on the regulation of apolipoprotein B (apoB) and lipid metabolism in the human hepatoma cell-line HepG2. The marked reduction in apoB secretion observed in cells incubated with 72.8 microM tangeretin was rapid, apoB-specific, and partly reversible. The reduction also was observed under lipid-rich conditions and found to be insensitive to proteasomal degradation of nascent apoB. We followed our study by examining lipid synthesis and mass. A 24-h exposure of cells to 72.8 microM tangeretin decreased intracellular synthesis of cholesteryl esters, free cholesterol, and TAG by 82, 45, and 64%, respectively; tangeretin also reduced the mass of cellular TAG by 37%. The tangeretin-induced suppression of TAG synthesis and mass were associated with decreased activities of DAG acyltransferase (up to -39.0 +/- 3.0% vs. control) and microsomal triglyceride transfer protein (up to -35.5 +/- 2.5% vs. control). Tangeretin was also found to activate the peroxisome proliferator-activated receptor, a transcription factor with a positive regulatory impact on FA oxidation and TAG availability (up to 36% increase vs. control). The data suggest that tangeretin modulates apoB-containing lipoprotein metabolism through multiple mechanisms.
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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".