Lack of stimulation of cholesteryl ester transfer protein by cholesterol in the presence of a high-fat diet
Bibliographic record
Abstract
Cholesteryl ester transfer protein (CETP) is a key protein involved in the reverse cholesterol transport pathway. The regulation of CETP by dietary fats is not clearly understood. Transgenic mice expressing human CETP under the control of its natural flanking region were fed low- or high-fat diets enriched in monounsaturated fatty acids (MUFAs) or saturated fatty acids in the presence or absence of cholesterol. Addition of cholesterol to the low-fat MUFA diet increased CETP activity and mRNA expression, whereas addition of cholesterol to the high-fat MUFA diet led to a decrease in CETP activity and mRNA expression. In SW 872 cells, oleic acid and cholesterol stimulated CETP gene expression when given alone. However, addition of fatty acids along with cholesterol interfered with the stimulatory effect of cholesterol on CETP gene regulation. Cholesterol-mediated stimulation of CETP involves the transcription factor liver X receptor alpha (LXRalpha). High-fat MUFA diets inhibited the expression of LXRalpha, and addition of cholesterol to the high-fat MUFA diet did not rescue LXRalpha expression. Therefore, we present evidence for the first time that inhibition of LXRalpha expression by a high-fat MUFA diet leads to inhibition of CETP stimulation by cholesterol.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".