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Record W2001678352 · doi:10.1071/en13240

Synchrotron X-ray absorption spectroscopy analysis of arsenic chemical speciation in human nail clippings

2014· article· en· W2001678352 on OpenAlexaffabout
Olena Ponomarenko, Mihai R. Gherase, Mark S. LeBlanc, Chang‐Yong Kim, E. Desouza, Michael Farquharson, Fiona E. McNeill, Susan Nehzati, Ingrid J. Pickering, Graham N. George, David Fleming

Bibliographic record

VenueEnvironmental Chemistry · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsMcMaster UniversityMcMaster University Medical CentreCanadian Light Source (Canada)Mount Allison UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsArsenicArsenateChemistryArseniteEnvironmental chemistryArsenic contamination of groundwaterMetalloidContext (archaeology)MetalGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.003
GPT teacher head0.200
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2014
Admission routes2
Has abstractyes

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