Induction of Endogenous Nrf2/Small Maf Heterodimers by Arsenic-Mediated Stress in Placental Choriocarcinoma Cells
Bibliographic record
Abstract
Exposure to inorganic arsenic has been associated with various forms of cancer, nervous system pathogenesis, and vascular diseases, as well as reproductive and developmental toxicity. Here, the effect of inorganic arsenic on placental JAR choriocarcinoma cells was assessed. The nuclear protein levels of the CNC transcription factor Nrf2 were strongly induced in the presence of arsenic. Dosage response experiments showed that 0.5 microM of arsenic is sufficient to augment Nrf2 levels. The expression of the Nrf2 dimerization partners MafG and MafK appeared not to be modulated by arsenic, whereas MafF protein levels were slightly increased. Arsenic also induced the binding of endogenous Nrf2/small Maf DNA-binding complexes to a stress response element (StRE) recognition site. In addition, arsenic caused oxidative stress in the choriocarcinoma cell model as evidenced by an increase in intracellular H2O2 levels. Expression of the enzyme heme oxygenase-1 (HO-1), a known Nrf2 target gene, was upregulated by exposure of JAR cells to arsenic. These results suggest that Nrf2/small Maf heterodimers may play an important role in the response to arsenic-mediated stress in placental cells.
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 | 0.000 | 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) | 0.001 | 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".