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Record W2153018245 · doi:10.1093/chromsci/bmt106

Simultaneous Measurement of N-Acetyl-S-(2-cyanoethyl)-cysteine and N-Acetyl-S-(2-hydroxyethyl)-cysteine in Human Urine by Liquid Chromatography-Tandem Mass Spectrometry

2013· article· en· W2153018245 on OpenAlexfundno aff
H. Hongwei, Qingyuan Hu

Bibliographic record

VenueJournal of Chromatographic Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSulfur Compounds in Biology
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaEgg Farmers of CanadaNational Science Foundation
KeywordsChemistryChromatographyDetection limitTandem mass spectrometryMass spectrometryAcrylonitrileUrineElectrospray ionizationLiquid chromatography–mass spectrometryCysteineOrganic chemistryBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Acrylonitrile, possibly carcinogenic to humans, is mainly present in tobacco smoke and undergoes metabolism to form N-acetyl-S-(2-cyanoethyl)-cysteine (CEMA) and N-acetyl-S-(2-hydroxyethyl)-cysteine (HEMA). A method based on the direct dilution to simultaneously identify and quantify CEMA and HEMA in human urine by rapid resolution liquid chromatography-electrospray ionization tandem mass spectrometry (RRLC-MS-MS) was validated for assessing smoking-related acrylonitrile exposure. The recovery rates of the whole analytical procedure were 98.2-106.0% and 97.1-112.7% for HEMA and CEMA, respectively. The linear range of standard solutions was 0.5-100.0 ng/mL for CEMA and was 0.2-40.0 ng/mL for HEMA. RRLC using a small particle size column was combined with a tandem mass spectrometry system, which lowered the detection limit of analytes, reduced the ion suppression of mass and shortened the analysis time. The proposed method was successfully applied for the analysis of 126 urine samples from smokers and nonsmokers.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.244
Teacher spread0.235 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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