Rapid non-separative determination of prevailing organophosphate flame retardants metabolites in urine by means of a restricted access material coupled to tandem mass spectrometry
Bibliographic record
Abstract
[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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".