Human UDP-glucuronosyltransferase (UGT)1A3 enzyme conjugates chenodeoxycholic acid in the liver
Bibliographic record
Abstract
Chenodeoxycholic acid (CDCA) is a liver-formed detergent and plays an important role in the control of cholesterol homeostasis. During cholestasis, toxic bile acids (BA) accumulate in hepatocytes causing damage and consequent impairment of their function. Glucuronidation, a conjugation reaction catalyzed by UDP-glucuronosyltransferase (UGT) enzymes, is considered an important metabolic pathway for hepatic BA. This study identifies the human UGT1A3 enzyme as the major enzyme responsible for the hepatic formation of the acyl CDCA-24glucuronide (CDCA-24G). Kinetic analyses revealed that human liver and UGT1A3 catalyze the formation of CDCA-24G with similar K(m) values of 10.6 to 18.6 mumol/L, respectively. In addition, electrophoretic mobility shift assays and transient transfection experiments revealed that glucuronidation reduces the ability of CDCA to act as an activator of the nuclear farnesoid X-receptor (FXR). Finally, we observed that treatment of human hepatocytes with fibrates increases the expression and activity of UGT1A3, whereas CDCA has no effect. In conclusion, UGT1A3 is the main UGT enzyme for the hepatic formation of CDCA-24G and glucuronidation inhibits the ability of CDCA to act as an FXR activator. In vitro data also suggest that fibrates may favor the formation of bile acid glucuronides in cholestatic patients.
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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 | 0.000 | 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".