Occurrence of Monomethylarsonous Acid in Urine of Humans Exposed to Inorganic Arsenic
Bibliographic record
Abstract
Monomethylarsonous acid (MMA(III)) has been detected for the first time in the urine of some humans exposed to inorganic arsenic in their drinking water. Our experiments have dealt with subjects in Romania who have been exposed to 2.8, 29, 84, or 161 microg of As/L in their drinking water. In the latter two groups, MMA(III) was 11 and 7% of the urinary arsenic while the monomethylarsonic acid (MMA(V)) was 14 and 13%, respectively. Of our 58 subjects, 17% had MMA(III) in their urine. MMA(III) was not found in urine of any members of the group with the lowest level of As exposure. If the lowest-level As exposure group is excluded, 23% of our subjects had MMA(III) in their urine. Our results indicate that (a) future studies concerning urinary arsenic profiles of arsenic-exposed humans must determine MMA(III) concentrations, (b) previous studies of urinary profiles dealing with humans exposed to arsenic need to be re-examined and re-evaluated, and (c) since MMA(III) is more toxic than inorganic arsenite, a re-examination is needed of the two hypotheses which hold that methylation is a detoxication process for inorganic arsenite and that inorganic arsenite is the major cause of the toxicity and carcinogenicity of inorganic arsenic.
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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 | 0.000 | 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".