The Role of the Enterohepatic Circulation of Bile Salts and Nuclear Hormone Receptors in the Regulation of Cholesterol Homeostasis: Bile Salts as Ligands for Nuclear Hormone Receptors
Bibliographic record
Abstract
The coordinated effect of lipid activated nuclear hormone receptors; liver X receptor (LXR), bound by oxysterol ligands and farnesoid X receptor (FXR), bound by bile acid ligands, act as genetic transcription factors to cause feed-forward cholesterol catabolism to bile acids and feedback repression of bile acid synthesis, respectively. It is the coordinated action of LXR and FXR, each dimerized to retinoid X receptor, that signal nuclear DNA response elements to encode proteins that prevent excessive cholesterol accumulation and bile salt toxicity, respectively. LXR helps prevent hypercholesterolemia by enhancing transporters for cholesterol efflux that enhance reverse cholesterol transport, while FXR enhances intestinal reabsorption and preservation of bile salts by increasing the ileal bile acid binding protein. FXR also targets sodium taurocholate cotransport peptide and bile salt export pump (protein) genes to limit bile salt uptake and enhance export, respectively, which prevents bile salt toxicity. Other nuclear hormone receptors such as pregnan X receptor, which share the obligate partner, retinoid X receptor, and vitamin D receptor also function as bile acid sensors to signal detoxification by hydroxylation of toxic bile acids. Pharmacologically targeted receptor agonists (or antagonists) may be developed that alter cholesterol and bile salt concentrations by modulating nuclear hormone receptors and/or their coactivators or corepressors to positively affect cholesterol homeostasis and bile salt metabolism. It is the coordinated transcription factor action of LXR, which responds to ligand binding of circulating oxysterols in both liver and peripheral tissues, and FXR responding to bile salts within the enterohepatic circulation that make possible the regulation of cholesterol and bile acid homeostasis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".