Distribution of Uridine Diphosphate-Glucuronosyltransferase (UGT) Expression and Activity in Cynomolgus Monkey Tissues: Evidence for Differential Expression of Steroid-Conjugating UGT Enzymes in Steroid Target Tissues*
Bibliographic record
Abstract
Based on the similarity of pathways and enzymes involved in steroid metabolism, simians represent a relevant animal model to study steroid elimination by glucuronidation. In this study the tissue distribution of UDP-glucuronosyltransferase (UGT) transcripts, proteins, and enzymatic activities were examined in 24 different cynomolgus monkey tissues. RT-PCR and Western blot analysis on total RNA and microsomal proteins demonstrated the presence of UGT1A and UGT2B transcripts and proteins in a wide range of tissues including steroid target tissues. Glucuronidation activity on eugenol, 5alpha-androstane-3alpha,17beta-diol, androsterone, and 4-hydroxyestradiol was measured using tissue homogenates and radiolabeled [14C]UDP-glucuronic acid. All tissues contained conjugation activity on these substrates, but glucuronidation rates were significantly lower in steroid target tissues than in liver, kidney, or gut. However, the ratio of steroid glucuronidation vs. eugenol glucuronidation was higher in steroid target tissues, suggesting a differential expression of steroid-conjugating enzymes in these tissues. Taken together, these results clearly demonstrate the presence of steroid glucuronidation enzymes in extrahepatic steroid target tissues and support the hypothesis that steroid glucuronidation is an important intracrine pathway involved in termination of steroid signaling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".