Impact of Trivalent Arsenicals on Selenoprotein Synthesis
Bibliographic record
Abstract
BACKGROUND: Exposure to arsenic has been associated with development of skin, lung, bladder, liver, and kidney cancer. Recent evidence suggests that an increase in oxidative stress in cells treated with arsenicals represents the molecular mechanism behind arsenic-induced carcinogenesis. Selenium, in the form of selenocysteine, is necessary for the activity of several enzymes with a role in defense against reactive oxygen species. A mutual sparing effect between arsenic and selenium has been shown in animal studies when both metalloids are present in high concentrations. OBJECTIVES: To determine whether changes in selenoprotein synthesis may be an underlying mechanism behind arsenic-induced carcinogenesis, we analyzed the new synthesis of selenoproteins within cells after exposure to inorganic or methylated arsenicals using a human keratinocyte cell model. RESULTS: Addition of arsenite to culture medium blocked new synthesis of selenoproteins when selenium was present in the form of selenite, and appeared to stimulate the use of serum-derived selenium. Monomethylarsonous acid (MMA(III)) treatment of cells, in contrast, did not block all new synthesis of selenoproteins but did result in an increase in cytosolic thioredoxin reductase (TrxR1) at both the mRNA and protein levels. MMA(III) also reduced the new synthesis of cellular glutatione peroxidase (cGpx) and other smaller selenoproteins. Dimethylarsinous acid (DMA(III)) stimulated selenoprotein synthesis by an as yet unknown mechanism. CONCLUSIONS: These results suggest that arsenite and MMA(III) are key metabolites that trigger higher levels of TrxR1, and both lead to a reduction in the expression of cGpx. Together these effects certainly could lead to carcinogenesis given the knowledge that many cancers have higher levels of TrxR, and reduced Gpx levels will reduce the cell's ability to defend against reactive oxygen species. Based on these results, the impact of the trivalent arsenicals arsenite and MMA(III) on selenoprotein synthesis may indeed represent a potential molecular mechanism for the higher rates of cancer observed in populations exposed to high levels of arsenic.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.005 | 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 teacher head, 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".