Nuclear receptors and endobiotics glucuronidation: the good, the bad, and the UGT
Bibliographic record
Abstract
The recent progresses in molecular biology and pharmacology approaches allowed the characterization of a series of nuclear receptors (NRs) as efficient regulators of uridine diphosphate glucuronosyltransferase (UGT) genes activity. These regulatory processes ensure an optimized UGT expression in response to specific endo- and/or exogenous stimuli. Many of these NRs are activated by endobiotics that also are substrates for UGTs. Thus, by activating their receptors, these endogenous substances control their own conjugation, leading to the concept that glucuronidation is an important part of feed-forward/feedback mechanisms by which bioactive molecules control their own concentrations. On the other hand, numerous studies have established the pharmacological relevance of NR-UGT regulatory pathways in the response to therapeutic ligands. The present review article aims at providing a comprehensive view of the physiological and pharmacological importance of the NR regulation of the expression and activity of endobiotics-conjugating UGT enzymes. Selected examples will illustrate how the organism profits from the feed-forward/feedback mechanisms involving NR-UGT pathways, but also how such regulatory processes are involved in the initiation and/or progression of several pathological situations. Finally, we will discuss how the present pharmacopeia involves NR-dependent regulation of endobiotics glucuronidation, and whether the unexploited NR-UGT axes could serve as pharmacological targets for novel therapeutics to restore endobiotics 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".