The UDP-glucuronosyltransferase 1A9 Enzyme Is a Peroxisome Proliferator-activated Receptor α and γ Target Gene
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor (PPAR) alpha and gamma are ligand-activated transcription factors belonging to the nuclear receptor family. PPAR alpha mediates the hypolipidemic action of the fibrates, whereas PPAR gamma is a receptor for the antidiabetic glitazones. In the present study, the UDP-glucuronosyltransferase (UGT) 1A9 enzyme is identified as a PPAR alpha and PPAR gamma target gene. UGTs catalyze the glucuronidation reaction, which is a major pathway in the catabolism and elimination of numerous endo- and xenobiotics. Among the UGT1A family enzymes, UGT1A9 metabolizes endogenous compounds, including catecholestrogens, and xenobiotics, such as fibrates and to a lesser extent troglitazone. Treatment of human hepatocytes and macrophages and murine adipocytes with activators of PPAR alpha or PPAR gamma resulted in an enhanced UGT1A9 expression and activity. In addition, disruption of the PPAR alpha gene in mice completely abolished the PPAR alpha agonist-induced UGT1A9 mRNA and activity levels. A PPAR response element was identified in the promoter of UGT1A9 at positions -719 to -706 bp by transient transfection and electromobility shift assays. Considering the role of UGT1A9 in catecholestrogen metabolism, PPAR alpha and PPAR gamma activation may contribute to the protection against genotoxic catecholestrogens by stimulating their inactivation in glucuronide derivatives. Furthermore, since UGT1A9 is involved in the catabolism of fibrates, these results suggest that PPAR alpha and PPAR gamma may control the intracellular level of active fibrates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".