Synchrotron X-ray absorption spectroscopy analysis of arsenic chemical speciation in human nail clippings
Bibliographic record
Abstract
Environmental context Chronic ingestion of arsenic leads to its accumulation in keratinous tissues, which can represent a risk factor for developing cancer. We use synchrotron X-ray absorption spectroscopy to investigate chemical bonding of arsenic in the keratins from nail clippings of volunteers from areas in Atlantic Canada with low-to-moderate arsenic contamination of drinking water. The study helps our understanding of arsenic metabolism and its role in cancer development. Abstract Drinking water aquifers in many areas of the world have naturally elevated levels of inorganic arsenic exceeding the World Health Organization limit. Arsenic concentrations in human nail clippings are commonly used as a biomarker of exposure to this toxic element. However, the chemical form of arsenic accumulated in nail tissues is not well determined. We employed synchrotron microprobe and bulk X-ray absorption spectroscopy techniques to analyse the concentration and chemical speciation of arsenic in the finger- and toenail clippings of volunteers living in the vicinity of Sackville, New Brunswick, Canada. This area is known to have low-to-moderately elevated levels of arsenic in ground water. Arsenic species in clippings were represented by three main groups, distinguished by the As-K near-edge X-ray absorption fine structure spectra: (1) AsIII type, which can be fitted as a mixture of As bound to thiols, and also to oxygen or methyl groups, with a small contribution from AsV species, (2) AsV type, best represented by fitting arsenate in aqueous solution and (3) The AsIII + AsV mixture type. The high proportion (%) of sulfur-bound arsenic species most likely corresponds to binding between arsenic (in its trivalent and, to a lesser extent, pentavalent forms) and cysteine residues in the sulfur-rich fraction of keratin and keratin-associated proteins. Further work is needed to explore whether these chemical species could be used as toxicity biomarkers of human exposure to elevated levels of As in drinking water.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".