Determination of monomethylarsonous acid, a key arsenic methylation intermediate, in human urine.
Bibliographic record
Abstract
In this study we report on the finding of monomethylarsonous acid [MMA(III)] in human urine. This newly identified arsenic species is a key intermediate in the metabolic pathway of arsenic biomethylation, which involves stepwise reduction of pentavalent to trivalent arsenic species followed by oxidative addition of a methyl group. Arsenic speciation was carried out using ion-pair chromatographic separation of arsenic compounds with hydride generation atomic fluorescence spectrometry detection. Speciation of the inorganic arsenite [As(III)], inorganic arsenate [As(V)], monomethylarsonic acid [MMA(V)], dimethylarsinic acid [DMA(V)], and MMA(III) in a urine sample was complete in 5 min. Urine samples collected from humans before and after a single oral administration of 300 mg sodium 2,3-dimercapto-1-propane sulfonate (DMPS) were analyzed for arsenic species. MMA(III) was found in 51 out of 123 urine samples collected from 41 people in inner Mongolia 0-6 hr after the administration of DMPS. MMA(III )in urine samples did not arise from the reduction of MMA(V) by DMPS. DMPS probably assisted the release of MMA(III) that was formed in the body. Along with the presence of MMA(III), there was an increase in the relative concentration of MMA(V) and a decrease in DMA(V) in the urine samples collected after the DMPS ingestion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".