Nuclear Receptor Pathways Mediating the Development of Boar Taint
Bibliographic record
Abstract
The nuclear receptors PXR, CAR, and FXR are activated by various ligands and function as transcription factors to control the expression of genes that regulate the synthesis and metabolism of androstenone and skatole. These compounds are produced in entire male pigs and accumulate in the fat to cause the development of a meat quality issue known as boar taint. The extent of this accumulation is influenced by the synthesis and hepatic clearance of androstenone and skatole. For this reason, PXR, CAR, and FXR-mediated signaling pathways have garnered interest as potential targets for specialized treatments designed to reduce the development of boar taint. Recent research has also identified several metabolites produced by gut microbes that act as ligands for these nuclear receptors (e.g., tryptophan metabolites, short-chain fatty acids, bile acids); however, the connection between the gut microbiome and boar taint development is not clear. In this review, we describe the nuclear receptor signaling pathways that regulate the synthesis and metabolism of boar taint compounds and outline the genes involved. We also discuss several microbial-derived metabolites and dietary additives that are known or suspected nuclear receptor ligands and suggest how these compounds could be used to develop novel treatments for boar taint.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".