Activation of farnesoid X receptor prevents atherosclerotic lesion formation in LDLR−/− and apoE−/− mice
Bibliographic record
Abstract
The role of farnesoid X receptor (FXR) in the development of atherosclerosis has been unclear. Here, LDL receptor (LDLR(-/-)) or apolipoprotein E (apoE(-/-)) female or male mice were fed a Western diet and treated with a potent synthetic FXR agonist, WAY-362450. Activation of FXR blocked diet-induced hypertriglyceridemia and elevations of non-HDL cholesterol and produced a near complete inhibition of aortic lesion formation. WAY-362450 also induced small heterodimer partner (SHP) expression and repressed cholesterol 7alpha-hydroxylase (CYP7A1) and sterol 12 alpha-hydroxylase (CYP8B1) expression. To determine if SHP was essential for these protective activities, LDLR(-/-)SHP(-/-) and apoE(-/-)SHP(-/-) mice were similarly treated with WAY-362450. Surprisingly, a notable sex difference was observed in these mice. In male LDLR(-/-)SHP(-/-) or apoE(-/-)SHP(-/-) mice, WAY-362450 still repressed CYP7A1 and CYP8B1 expression by 10-fold and still strongly reduced non-HDL cholesterol levels and aortic lesion area. In contrast, in the female LDLR(-/-)SHP(-/-) or apoE(-/-)SHP(-/-) mice, WAY-362450 only slightly repressed CYP7A1 and CYP8B1 expression and did not reduce non-HDL cholesterol or aortic lesion size. WAY-362450 inhibition of hypertriglyceridemia remained intact in LDLR(-/-) or apoE(-/-) mice lacking SHP of both sexes. These results suggest that activation of FXR protects against atherosclerosis in the mouse, and this protective effect correlates with repression of bile acid synthetic genes, with mechanistic differences between male and female mice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".