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Record W2908091646 · doi:10.1002/rcm.8380

A validated liquid chromatography/tandem mass spectrometry method for 4,4′‐methylenedianiline quantitation in human urine as a measure of 4,4′‐methylene diphenyl diisocyanate exposure

2019· article· en· W2908091646 on OpenAlexafffund
Maggy Lépine, Lekha Sleno, Jacques Lesage, Sébastien Gagné

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2019
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversité du Québec à MontréalInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsChemistryChromatographyDetection limitUrineSolid phase extractionLiquid chromatography–mass spectrometryMass spectrometryIsocyanatePolyurethaneOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

RATIONALE: 4,4'-Methylene diphenyl diisocyanate (MDI) is a highly reactive isocyanate used in the production of polyurethanes. Workers exposed to these products may develop sensitization to the diisocyanate compounds, leading to occupational asthma. Quantifying MDI levels is necessary to ensure workplace safety. MDI is metabolized by acetylation and/or conjugation to macromolecules for excretion into urine. All metabolites can be chemically hydrolyzed to form the free diamine 4,4'-methylenedianiline (MDA) as a urinary biomarker of MDI exposure. Current methods involve long sample preparation, or have been designed using costly automation. There is therefore a need to develop a new practical method for assessing exposure to MDI. METHODS: Urine samples were acidified and heated to form MDA, followed by neutralization and liquid-liquid extraction. Extracts were separated by reversed-phase chromatography on a HSS T3 column followed by analysis on a triple quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode. RESULTS: N-MDA was selected as the internal standard (IS) of choice following an investigation of internal standard stability. The hydrolysis efficiency, forming free MDA from conjugated metabolites in vivo, was evaluated using 4,4'-methylenebis(acetanilide) spiked into urine and complete hydrolysis occurred after 1 h. A dynamic range of 5 to 500 nM was achieved, and was useful for monitoring MDI exposure considering the biological guidance value (BGV) of 10 μg/L (~50 nM) proposed by the German Research Foundation (DFG). The limit of detection (LOD) and limit of quantification (LOQ) of the method were 0.8 and 2.7 nM, respectively. The intra-day and inter-day precisions were 4.33% and 4.27%, respectively. Finally, the method was tested with inter-laboratory samples from the German External Quality Assessment Scheme (G-EQUAS) program and the results submitted were all within the allowable tolerance range. CONCLUSIONS: A practical and validated method for the analysis of small- to medium-sized batches of samples has been developed for the biological monitoring of MDI exposure in human urine.

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)0.003
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 score0.368
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.343
Teacher spread0.316 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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