The inhibition of the human cholesterol 7 -hydroxylase gene (CYP7A1) promoter by fibrates in cultured cells is mediated via the liver x receptor and peroxisome proliferator-activated receptor heterodimer
Bibliographic record
Abstract
In previous work, we showed that the binding of the liver x receptor alpha:peroxisome proliferator-activated receptor alpha (LXRalpha:PPARalpha) heterodimer to the murine Cyp7a1 gene promoter antagonizes the stimulatory effect of their respective ligands. In this study, we determined if LXRalpha:PPARalpha can also regulate human CYP7A1 gene promoter activity. Co-expression of LXRalpha and PPARalpha in McArdle RH7777 hepatoma cells decreased the activity of the human CYP7A1 gene promoter in response to fibrates and 25-hydroxycholesterol. In vitro, the human CYP7A1 Site I bound LXRalpha:PPARalpha, although with substantially less affinity compared with the murine Cyp7a1 Site I. The binding of LXRalpha:PPARalpha to human CYP7A1 Site I was increased in the presence of either LXRalpha or PPARalpha ligands. In HepG2 hepatoblastoma cells, fibrates and 25-hydroxycholesterol inhibited the expression of the endogenous CYP7A1 gene as well as the human CYP7A1 gene promoter when co-transfected with plasmids encoding LXRalpha and PPARalpha. However, a derivative of the human CYP7A1 gene promoter that contains a mutant form of Site I that does not bind LXRalpha:PPARalpha was not inhibited by WY 14,643 or 25-hydroxycholesterol in both McArdle RH7777 and HepG2 cells. The ligand-dependent recruitment of LXRalpha:PPARalpha heterodimer onto the human CYP7A1 Site I can explain the inhibition of the human CYP7A1 gene promoter in response to fibrates and 25-hydroxycholesterol.
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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 | 0.001 |
| 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".