Development of a Method to Detect Three Monohydroxylated Polycyclic Aromatic Hydrocarbons in Human Urine by Liquid Chromatographic Tandem Mass Spectrometry
Bibliographic record
Abstract
A liquid chromatographic tandem mass spectrometry method (LC-MS/MS) for the simultaneous determination of 1-hydroxypyrene (1-OHP), 3-hydroxybenzo[a]pyrene (3-OHBaP), and 3-hydroxybenz[a]anthracene (3-OHBaA) in human urine has been developed. With the exception of 3-OHBaP at a low spiking level, the average recoveries were greater than 80%. The method has good accuracy (72.1-107.7%) and reproducibility (1.8-11.4%) and was successfully used to study the uptake of pyrene, benzo[a]pyrene, and benzo[a]anthracene from cigarette smoke. The results indicated that urinary 1-OHP concentration in the smoking group (66.58 ± 70.91 ng/g creatinine) was higher than that observed in the nonsmoking group (58.16 ± 49.48 ng/g creatinine). Urinary 3-OHBaA concentrations in nonsmokers and smokers with 8 mg and 10 mg tar cigarettes were 10.98 ± 4.39 ng/g creatinine, 11.01 ± 13.30 ng/g creatinine, and 9.17 ± 12.89 ng/g creatinine, respectively. Urinary 3-OHBaP concentrations in nonsmokers and smokers with 8 mg and 13 mg tar cigarettes were 1.30 ± 0.20 ng/g creatinine, 2.83 ± 1.78 ng/g creatinine, and 6.00 ± 4.44 ng/g creatinine, respectively. Urinary 1-OHP levels exhibited a significant correlation with BaP yield in cigarette smoke under the Canadian intense smoking condition (y = 3.5563x + 30.171, R (2) = 0.9916, n = 227).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.001 |
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".