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Record W2067128846 · doi:10.1155/2008/539082

Methylated Trivalent Arsenic‐Glutathione Complexes are More Stable than their Arsenite Analog

2008· article· en· W2067128846 on OpenAlexafffund
Andrew J. Percy, Jürgen Gailer

Bibliographic record

VenueBioinorganic Chemistry and Applications · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArseniteArsenicGlutathioneChemistryArsenateBiochemistryOrganic chemistryEnzyme

Abstract

fetched live from OpenAlex

The trivalent arsenic glutathione complexes arsenic triglutathione, methylarsonous diglutathione, and dimethylarsinous glutathione are key intermediates in the mammalian metabolism of arsenite and possibly represent the arsenic species that are transported from the liver to the kidney for urinary excretion. Despite this, the comparative stability of the arsenic-sulfur bonds in these complexes has not been investigated under physiological conditions resembling hepatocyte cytosol. Using size-exclusion chromatography and a glutathione-containing phosphate buffered saline mobile phase (5 or 10 mM glutathione, pH 7.4) in conjunction with an arsenic-specific detector, we chromatographed arsenite, monomethylarsonous acid, and dimethylarsinous acid. The on-column formation of the corresponding arsenic-glutathione complexes between 4 and 37 degrees C revealed that methylated arsenic-glutathione complexes are more stable than arsenic triglutathione. The relevance of these results with regard to the metabolic fate of arsenite in mammals is discussed.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.013
GPT teacher head0.213
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations28
Published2008
Admission routes2
Has abstractyes

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