Natural Product-Induced Modulation of Androstenone Metabolism in Porcine Hepatocytes
Bibliographic record
Abstract
The nuclear receptors pregnane X receptor (PXR), constitutive androstane receptor (CAR), and farnesoid X receptor (FXR) regulate the hepatic metabolism of androstenone, a testicular steroid that accumulates in the fat of intact male pigs and causes boar taint. This study evaluated natural product-derived compounds and conventional agonists targeting these nuclear receptors for their effects on androstenone metabolism in primary hepatocytes from slaughter-weight boars, to assess their potential as treatments for boar taint. Cells were incubated with natural products, conventional agonists, or dimethyl sulfoxide (DMSO; control), then being treated with androstenone. Culture media and cells were analyzed to assess changes in androstenone metabolism and gene expression. UGT1A6 was upregulated by treatments targeting both PXR and CAR and downregulated by FXR agonists. Additionally, PGC1α and NR2F1 were downregulated by compounds targeting PXR/CAR, while FXR and NR0B2 were upregulated and HNF4α downregulated by treatments acting on FXR. The natural products diallyl sulfide (DAS) and (Z)-guggulsterone (GUG) increased overall androstenone metabolism (DAS, GUG) and the production of Phase I androstenol metabolites (DAS), but only in hepatocyte culture replicates that responded positively to these treatments. Although gene expression was similar between positive-response and negative/non-responsive replicates following treatments, negative/non-responsive replicates for several treatments had higher basal expression of UGT2B31, UGT2A1, and SIRT1 and lower basal expression of FXR, PXR, and NR0B1 compared to positive-response replicates. These findings suggest that DAS and GUG may be promising treatments for boar taint, specifically in animals with lower basal rates of androstenone metabolism and higher expression of key nuclear receptors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".