Metabolism of a Phenylarsenical in Human Hepatic Cells and Identification of a New Arsenic Metabolite
Bibliographic record
Abstract
Abstract Environmental contamination and human consumption of chickens could result in potential exposure to Roxarsone (3-nitro-4-hydroxyphenylarsonic acid), an organic arsenical that has been used as a chicken feed additive in many countries. However, little is known about the metabolism of Roxarsone in humans. The objective of this research was to investigate the metabolism of Roxarsone in human liver cells and to identify new arsenic metabolites of toxicological significance. Human primary hepatocytes and hepatocellular carcinoma HepG2 cells were treated with 20 or 100 μM Roxarsone. Arsenic species were characterized using a strategy of complementary chromatography and mass spectrometry. The results showed that Roxarsone was metabolized to more than 10 arsenic species in human hepatic cells. A new metabolite was identified as a thiolated Roxarsone. The 24 h IC50 values of thiolated Roxarsone for A549 lung cancer cells and T24 bladder cancer cells were 380 ± 80 and 42 ± 10 μM, respectively, more toxic than Roxarsone, whose 24 h IC50 values for A549 and T24 were 9300 ± 1600 and 6800 ± 740 μM, respectively. The identification and toxicological studies of the new arsenic metabolite are useful for understanding the fate of arsenic species and assessing the potential impact of human exposure to Roxarsone.
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) | 0.002 | 0.001 |
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".