Loss of small heterodimer partner expression in the liver protects against dyslipidemia
Bibliographic record
Abstract
Multiple studies suggest increased conversion of cholesterol to bile acids by cholesterol 7alpha-hydroxylase (CYP7A1) protects against dyslipidemia and atherosclerosis. CYP7A1 expression is repressed by the sequential activity of two nuclear hormone receptors, farnesoid X receptor (FXR) and small heterodimer partner (SHP). Here we demonstrate 129 strain SHP(-/-) mice are protected against hypercholesterolemia resulting from either a cholesterol/cholic acid (chol/CA) diet or from hypothyroidism. In a mixed 129-C57Bl/6 background, LDLR(-/-) and LDLR(-/-)SHP(-/-) mice had nearly identical elevations in hepatic cholesterol content and repression of cholesterol regulated genes when fed a Western diet. However, the LDLR(-/-)SHP(-/-) mice had greatly reduced elevations in serum VLDL and LDL cholesterol levels and triglyceride (TG) levels as compared with LDLR(-/-) mice. Additionally, the hepatic inflammation produced by the Western diet in the LDLR(-/-) mice was abolished in the LDLR(-/-)SHP(-/-) mice. CYP7A1 expression was induced 10-fold by the Western diet in the LDLR(-/-)SHP(-/-) mice but not in the LDLR(-/-) mice. Finally, hepatocyte-specific deletion of SHP expression was also protective against dyslipidemia induced by either a chol/CA diet or by hypothyroidism. While no antagonist ligands have yet been identified for SHP, these results suggest selective inhibition of hepatic SHP expression may provide protection against dyslipidemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".