A reliable method by ultra‐performance liquid chromatography coupled with tandem mass spectrometry to quantify and confirm simultaneously the presence of solvent metabolites in workers' urine
Bibliographic record
Abstract
Ultra-performance liquid chromatography coupled with tandem mass spectrometry was used for the biological monitoring of workers occupationally exposed to solvents. The method was developed using a triple quadrupole to investigate the relevant urinary metabolites of styrene, namely mandelic acid and phenylglyoxylic acid. The method provides quantitative and qualitative data to give additional assurance about the nature of the contaminant analyzed in workers' urine. A full scan and a product ion scan were acquired within the chromatographic peak acquired in MRM. For the two metabolites, the repeatability was 96%, the precision ≥97%, and the accuracy ≥93 ± 3%. The quantitative performances were not influenced by the inclusion of simultaneous full scan acquisition as compared to a usual quantitative approach. Footprints of each substance of interest were obtained at each injection, and full scan data can be interrogated for the presence of interferences and other contaminants. The method developed has been submitted to random real samples from both non-occupationally and occupationally exposed workers. The urines of non-occupationally exposed workers were all free of mandelic acid, phenylglyoxylic acid and putative interferences showing the high selectivity of the method. However, the urines of occupationally exposed workers were robustly quantified. The levels of mandelic acid and phenylglyoxylic acid ranged between 0.2 and 9 mM, and the footprints of each metabolite and structural information were acquired in parallel with the quantitative results, thus providing unquestionable data about the nature of the contaminant and the levels reported. The combination of qualitative information acquired simultaneously with quantitative results provides the structural information needed in case of questions, without any harmful effect on the robustness and throughput of the quantitative analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".