Do Arsenosugars Pose a Risk to Human Health? The Comparative Toxicities of a Trivalent and Pentavalent Arsenosugar
Bibliographic record
Abstract
Seafood frequently contains high concentrations of arsenic (approximately 10-100 mg/kg dry weight). In marine algae (seaweed), this arsenic occurs predominantly as ribose derivatives known collectively as arsenosugars. Although it is clear that arsenosugars are not acutely toxic, there is a possibility of arsenosugars having slight chronic toxicity. In general, trivalent arsenicals are more toxic than their pentavalent counterparts, so in this work we examine the hypothesis that trivalent arsenosugars might be significantly more toxic than pentavalent arsenosugars in vitro. We compared the in vitro toxicity of (R)-2,3-dihydroxypropyl-5-deoxy-5-dimethylarsinoyl-beta-D-riboside, a pentavalent arsenosugar, to that of its trivalent counterpart, (R)-2,3-dihydroxypropyl-5-deoxy-5-dimethylarsino-beta-D-riboside. The trivalent arsenosugar nicked plasmid DNA, whereas the pentavalent arsenosugar did not. The trivalent arsenosugar was more cytotoxic (IC50 = 200 microM, 48 h exposure) than its pentavalent counterpart (IC50 > 6000 microM, 48 h exposure) in normal human epidermal keratinocytes in vitro as determined via the neutral red uptake assay. However, both the trivalent and the pentavalent arsenosugars were significantly less toxic than MMA(III), DMA(III), and arsenate. Neither the pentavalent arsenosugar nor the trivalent arsenosugar were mutagenic in Salmonella TA104. The trivalent arsenosugar was readily formed by reaction of the pentavalent arsenosugar with thiol compounds, including, cysteine, glutathione, and dithioerythritol. This work suggests that the reduction of pentavalent arsenosugars to trivalent arsenosugars in biology might have environmental consequences, especially because seaweed consumption is a significant environmental source for human exposure to arsenicals.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".