MétaCan
Menu
Back to cohort
Record W2094911226 · doi:10.1021/tx0341714

Arsenic Speciation in Urine from Acute Promyelocytic Leukemia Patients undergoing Arsenic Trioxide Treatment

2003· article· en· W2094911226 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemical Research in Toxicology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsArsenicArsenic trioxideUrineArseniteAcute promyelocytic leukemiaArsenateChemistryGenetic algorithmArsenic poisoningPopulationEnvironmental chemistryChromatographyBiochemistryBiologyMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Arsenic has been used successfully in clinical trials for treating acute promyelocytic leukemia (APL). Although sublethal doses of inorganic arsenic are used, little is known about the pharmacokinetics and metabolism of the high levels of arsenic in APL patients. To fill this important gap, this study describes the speciation of arsenic in urine from four APL patients treated with arsenic. Each patient was injected daily with an arsenite (As(III)) solution that contained 10 mg of As(2)O(3) precursor. Speciation analysis of the patient urine samples collected consecutively for 48 h, encompassing two intravenous injections of arsenic, revealed the presence of monomethylarsonous acid (MMA(III)), dimethylarsinous acid (DMA(III)), monomethylarsonic acid (MMA(V)), and dimethylarsinic acid (DMA(V)). The intermediate methyl arsenic metabolites, MMA(III) and DMA(III), were detected in most urine samples from all of the patients when a preservative, diethyldithiocarbomate, was added to the urine samples to stabilize these trivalent arsenic species. The major arsenic species detected in the urine samples from the patients were As(III), MMA(V), and DMA(V), accounting for >95% of the total arsenic excreted. The relative proportions of As(III), As(V), MMA(V), and DMA(V) in urine samples collected 24 h after the injections of As(III) were 27.6 +/- 6.1, 2.8 +/- 2.0, 22.8 +/- 8.1, and 43.7 +/- 13.3%, respectively. The relatively lower fraction of the methylated arsenic species in these APL patients under arsenic treatment as compared with that from the general population exposed to much lower levels of arsenic suggests that the high levels of As(III) inhibit the methylation of arsenic (inhibits the formation of methyl arsenic metabolites). The arsenic species excreted into the urine accounted for 32-65% of the total arsenic injected. These results suggest that other pathways of excretion, such as through the bile, may play an important role in eliminating (removing) arsenic from the human body when challenged by high levels of As(III).

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.035
GPT teacher head0.331
Teacher spread0.296 · 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