Modulation of Cholesterol and Triacylglycerol Biosynthesis by Citrus Polymethoxylated Flavones
Bibliographic record
Abstract
Citrus polymethoxylated flavones modulate the biosynthesis of cholesterol and triacylglycerols via multiple mechanisms. Tangeretin inhibits the activities of diacylglycerol acyltransferase and of microsomal triglyceride transfer protein, as well as activates the membrane peroxisome proliferator-activated receptor in human hepatoma HepG2 cells. These modulatory effects subsequently inhibit the assembly and secretion of apolipoprotein B-containing lipoproteins, such as the very low-density lipoprotein (VLDL) and the low-density lipoprotein (LDL). Nobiletin, but not tangeretin, inhibited macrophage acetylated LDL metabolism linked to the action of the specific class A scavenger receptor. This inhibitory effect blocked the formation of macrophage foam-cells, which are essential to atherosclerotic plaque formation. In hamster feeding trials the polymethoxylated flavones dramatically lowered serum total cholesterol, LDL+VLDL cholesterol, as well as the levels of serum triacylglycerols. Total liver concentrations of tangeretin derivatives corresponded to hypolipidemic concentrations of intact tangeretin in earlier in vitro studies. If similar actions occur in humans, these compounds may be viable alternatives to the statin drugs to combat elevated cholesterol and triacylglycerols.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".