Characterization of the aryl hydrocarbon receptor repressor and a comparison of its expression in Atlantic tomcod from resistant and sensitive populations
Bibliographic record
Abstract
Atlantic tomcod from the Hudson River, USA, are resistant to cytochrome P4501A1 (CYP1A1) mRNA induction and early life stage toxicities induced by coplanar polychlorinated biphenyls (PCBs) or tetrachlorodibenzo-p-dioxins but not polycyclic aromatic hydrocarbons. We sought to determine if basal expression or inducibility of aryl hydrocarbon receptor repressor (AHRR) mRNA is higher in tomcod from the resistant Hudson River population than in those from sensitive populations. Tomcod AHRR cDNA was characterized and its expression quantified in different tissues and life stages of tomcod from the Hudson River, Miramichi River, Canada (sensitive), and among environmentally exposed tomcod from these two sources and the St. Lawrence River, Canada. Phylogenetic analysis revealed that tomcod AHRR falls within the clade of other vertebrate aryl hydrocarbon receptors (AHRs) but is most closely related to the four previously identified AHRR genes. Induction of AHRR mRNA was observed in all tissues of PCB77-treated juvenile tomcod of Miramichi River descent, and expression differed among tissues and was significantly related to levels of CYPIAI mRNA expression. Aryl hydrocarbon receptor repressor mRNA was similarly inducible in F2 embryos of Miramichi and Hudson River descent by benzo[a]pyrene but less by PCB77 in Hudson River offspring. A significant, positive correlation was observed between CYP1A1 mRNA and AHRR mRNA concentrations in environmentally exposed tomcod from the three rivers. We conclude that differences in basal expression or inducibility of AHRR mRNA are not the mechanistic basis of resistance but that levels of AHRR often mirror those of CYP1A1, suggesting that a common AHR pathway-related mechanism may modulate expression of both genes.
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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) | 0.000 | 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".