NF‐κB and AP‐1 are key signaling pathways in the modulation of NAD(P)H:Quinone oxidoreductase 1 gene by mercury, lead, and copper
Bibliographic record
Abstract
We have previously shown that Hg(2+), Pb(2+), and Cu(2+), significantly modulate the expression of NAD(P):quinone oxidoreductase 1 (Nqo1) in Hepa 1c1c7 cells through oxidative stress-dependent mechanisms. In the current study, we examined the role of redox-sensitive transcription factors, NF-kappaB and AP-1 signaling pathways in the modulation of Nqo1 by heavy metals. Our results show that the depletion of cellular GSH using L-buthionine-(S,R)-sulfoximine further potentiated the heavy metal-mediated induction of Nqo1 at the mRNA and activity levels. The NF-kappaB activator, PMA, significantly abolished the metal-mediated effects on Nqo1 mRNA and activity. In parallel, the NF-kappaB inhibitor, PDTC, further potentiated the Pb(2+)- and Hg(2+)-mediated induction of Nqo1 mRNA and activity levels, respectively. Inhibition of AP-1 upstream signaling pathway such as JNK by SP600125 significantly suppressed heavy metal-mediated induction of Nqo1 mRNA and activity levels. In contrast, inhibition of ERK by U0126 further potentiated heavy metal-mediated effects on Nqo1 mRNA, while only potentiated Hg(2+)-mediated induction of Nqo1 activity. Furthermore, p38 MAPK inhibitor, SB203580 further potentiated Pb(2+)- and Cu(2+)-mediated effects at the mRNA levels, whereas did not alter the activity levels. These results clearly demonstrate that activation of NF-kappaB negatively regulates the expression of Nqo1 by heavy metals, whereas AP-1 signaling pathways differentially modulates the heavy metal-mediated effects.
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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) | 0.000 | 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 | 0.001 |
| 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".