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Record W4405527268 · doi:10.1016/j.microc.2024.112525

Rapid non-separative determination of prevailing organophosphate flame retardants metabolites in urine by means of a restricted access material coupled to tandem mass spectrometry

2024· article· en· W4405527268 on OpenAlexaboutno aff
Gabriela Chango, Ana Ballester-Caudet, Diego García‐Gómez, Carmelo Garcı́a Pinto, Encarnación Rodríguez‐Gonzalo, José Luis Pérez Pavón

Bibliographic record

VenueMicrochemical Journal · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
FundersAgencia Estatal de InvestigaciónMinisterio de Economía y Competitividad
KeywordsOrganophosphateChemistryChromatographyUrineMass spectrometryTandem mass spectrometryFire retardantEnvironmental chemistryOrganic chemistryPesticide

Abstract

fetched live from OpenAlex

[EN]Organophosphate flame retardants (OPFRs) are used to reduce the flammability of various materials. Among these compounds, triphenyl phosphate (TPhP) and tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) are prominent OPFRs associated with reproductive and endocrine-disrupting effects. Monitoring their urinary metabolites, diphenyl phosphate (DPhP) and bis(1,3-dichloro-2-propyl) phosphate (BDCPP), are crucial for assessing bioaccumulation, toxicity, and exposure. This study presents a novel, non-separative analytical method combining restricted access material (RAM) with tandem mass spectrometry (MS/MS), eliminating the need for chromatographic separation. This innovation significantly reduces total analysis time down to less than five minutes per sample (12 samples per hour), compared to up to 37 min (only one sample per hour) required by state-of-the-art separative methods. The method achieves sub-ppb limits of quantification (LOQ ≤ 0.1 ng mL􀀀 1) that are equal or better than those achieved by separative methodologies. Matrix effects were minimized (≃20 %) with a conventional clean-up pretreatment based on SPE. The whole methodology was validated by analyzing certified urine samples provided by Centre de toxicologie du Qu´ebec and applied to the analysis of real urine samples from non-exposed individuals. The accuracy (86–108 %), precision (RSD < 20 %) and high recovery (98–109 %) confirm the robustness and suitability of this method in routine laboratory applications. This is the first report, to the best of our knowledge, to fully integrate RAM with direct MS/MS analysis for most prominent urinary OPFR metabolites without chromatographic separation. This methodological advance offers substantial advantages in speed, simplicity, and adaptability to high-throughput biomonitoring studies, setting a new benchmark for the determination of DPhP and BDCPP 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 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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.262
Teacher spread0.254 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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