The role of cytochrome P450‐dependent metabolism in the regulation of mouse hepatic growth hormone signaling components and target genes by 3‐methylcholanthrene
Bibliographic record
Abstract
State Department of Health, Albany, NY 3‐Methylcholanthrene (MC), a readily metabolized aryl hydrocarbon receptor (AHR) agonist, disrupts mouse hepatic growth hormone (GH) signaling and suppresses cytochrome P450 2D9 ( Cyp2d9 ), a male‐specific gene controlled by pulsatile GH via signal transducer and activator of transcription 5b (STAT5b). To determine if these effects depend on hepatic microsomal P450‐mediated activity, we examined MC responses in LCN mice with hepatocyte‐specific deletion of NADPH‐cytochrome P450 oxidoreductase (POR). MC caused mild induction of Por and a hepatic inflammatory marker in wild‐type mice whereas strong induction by MC of AHR target genes, Cyp1a1 , Cyp1a2 , and Cyp1b1 , occurred in wild‐type and LCN mice. Two STAT5b target genes, Cyp2d9 and major urinary protein 2 ( Mup2 ), were suppressed by MC in wild‐type mice and the CYP2D9 mRNA response was maintained in LCN mice. In wild‐type mice, MC decreased GH receptor (GHR) mRNA but increased GHR protein levels. There was a trend for impairment of STAT5 phosphorylation by MC in both mouse strains. Basal levels of MUP2 mRNA, GHR mRNA and protein, and the activation status of extracellular signal‐regulated kinase 2 and Akt were influenced by hepatic Por genetic status. The effects of MC on hepatic GH signaling components and target genes are complex, involving aspects that are both dependent and independent of hepatic microsomal P450‐mediated activity. [Support: CIHR, NIH‐NCI]
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 | 0.001 |
| 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".