Investigating the robustness and extraction performance of a matrix‐compatible solid‐phase microextraction coating in human urine and its application to assess 2–6‐ring polycyclic aromatic hydrocarbons using GC–MS/MS
Bibliographic record
Abstract
In this work, a polydimethylsiloxane/divinylbenzene fiber overcoated with a layer of polydimethylsiloxane was evaluated as analytical sampling tool for the first time in human urine. Urinary polycyclic aromatic hydrocarbons with 2-6 aromatic rings were considered as target compounds. The analyte uptake in kinetic and thermodynamic regime was evaluated and compared to the performances of polydimethylsiloxane/divinylbenzene and polydimethylsiloxane fibers. The assessment of the robustness and endurance of the overcoated fiber was carried out by direct immersion solid-phase microextraction in undiluted urine performing up to 120 consecutive extractions. The overcoated fiber was then used to develop a fast and easy direct immersion solid-phase microextraction with gas chromatography and triple quadrupole mass spectrometry protocol for the quantification of the target polycyclic aromatic hydrocarbons. The attained values of accuracy and precision were 75-114% and 2-19%, respectively, while the limits of quantification ranged between 0.05 and 1 ng/L. The proposed protocol was applied to the screening of urine samples collected from smoking and nonsmoking volunteers. The successful results obtained by using the overcoated fiber create not only new alternatives for polycyclic aromatic hydrocarbon exposure assessment but also new perspectives for the application of direct immersion solid-phase microextraction to the analysis of bioclinical matrixes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".