Mercury and methylmercury differentially modulate hepatic cytochrome P450 1A1 and 1A2 in vivo and in vitro
Bibliographic record
Abstract
Abstract The cytochrome P450 1 A (CYP1A) subfamily enzymes are involved in the metabolic activation of several xenobiotics to toxic metabolites and reactive intermediates, resulting ultimately in carcinogenesis. Mercury and halogenated aromatic hydrocarbons (HAHs), typified by 2,3,7,8‐tetrachlorodibenzo‐p‐dioxin (TCDD), are persistent environmental pollutants involved in the modulation of aryl hydrocarbon receptor (AHR) gene battery, including cytochrome P450 (CYP) genes. We previously investigated the effect of coexposure to either inorganic or organic mercury (Hg+2 and MeHg) with TCDD on CYP1A1 in vitro. Thus, we examined the impact of coexposure to Hg+2 or MeHg and TCDD on AHR‐regulated genes (Cyp1a1/1a2) in vivo and in vitro. Therefore, male C57BL/6 mice were injected intraperitoneally with MeHg or Hg+2 (2.5 mg/kg) in the absence and presence of TCDD (15 μg/kg) for 6 or 24 h. The concentration‐dependent effect of MeHg was examined in murine hepatoma Hepa1c1c7 cells. In vivo, both MeHg and Hg2+ inhibited the TCDD‐mediated induction of Cyp1a1/1a2 mRNA levels. However, Only Hg2+ was able to inhibit the TCDD‐mediated induction at posttranscriptional levels of CYP1A1/1A2 protein and catalytic activity, suggesting differential modulation effects by Hg+2 and MeHg. In addition, the inhibitory role of HO‐1 (Heme oxygenase‐1) on CYP1A activity induced by TCDD was investigated using a HO‐1 competitive inhibitor, tin‐mesoporphyrin, that partially restored the MeHg‐mediated decrease in CYP1A1 activity. This study demonstrates that MeHg, alongside Hg2+, can differentially modulate the TCDD‐induced AHR‐regulated genes (Cyp1a1/1a2) at different expression levels in C57BL/6 mice liver and Hepa1c1c7 cells.
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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 | 0.000 | 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) | 0.002 | 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".