The liver X-receptor alpha controls hepatic expression of the human bile acid–glucuronidating UGT1A3 enzyme in human cells and transgenic mice
Bibliographic record
Abstract
Glucuronidation, an important bile acid detoxification pathway, is catalyzed by enzymes belonging to the UDP-glucuronosyltransferase (UGT) family. Among UGT enzymes, UGT1A3 is considered the major human enzyme for the hepatic C24-glucuronidation of the primary chenodeoxycholic (CDCA) and secondary lithocholic (LCA) bile acids. We identify UGT1A3 as a positively regulated target gene of the oxysterol-activated nuclear receptor liver X-receptor alpha (LXRalpha). In human hepatic cells and human UGT1A transgenic mice, LXRalpha activators induce UGT1A3 mRNA levels and the formation of CDCA-24glucuronide (24G) and LCA-24G. Furthermore, a functional LXR response element (LXRE) was identified in the UGT1A3 promoter by site-directed mutagenesis, electrophoretic mobility shift assays and chromatin immunoprecipitation experiment. In addition, LXRalpha is found to interact with the SRC-1alpha and NCoR cofactors to regulate the UGT1A3 gene, but not with PGC-1beta. In conclusion, these observations establish LXRalpha as a crucial regulator of bile acid glucuronidation in humans and suggest that accumulation of oxysterols in hepatocytes during cholestasis favors bile acid detoxification as glucuronide conjugates. LXR agonists may be useful for stimulating both bile acid detoxification and cholesterol removal in cholestatic or hypercholesterolemic patients, respectively.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".