Determination of seven monoaromatic hydrocarbon metabolites by ultra performance liquid chromatography-tandem mass spectrometry
Bibliographic record
Abstract
<p id="p00005">Monoaromatic hydrocarbons (MAHs) such as benzene, toluene, and xylene are important anthropogenic pollutants in the urban atmosphere. The detection of urinary MAH metabolites are included in human biomonitoring programs in several countries, including Canada, the United States, Italy, and Germany, because their evaluation is vital to monitor the exposure of humans to MAHs. To this end, herein, a method was developed for the determination of seven MAH metabolites through ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). An aliquot of 0.5 mL urine was fortified with an isotopic labeled internal standard solution before being hydrolyzed by 40 μL of 6 mol/L HCl solution, followed by extraction using a 96-well EVOLUTE<sup>®</sup>EXPRESS ABN solid-phase extraction plate. The samples were washed with 1.0 mL of methanol-water (10∶90, v/v) and eluted with 1.0 mL methanol. The eluate was diluted four times with water prior to use in instrumental analysis. Chromatographic separation was achieved using an ACQUITY UPLC HSS T3 column (100 mm×2.1 mm, 1.8 μm), with gradient elution using 0.1% formic acid as mobile phase A and methanol as mobile phase B. The detection of seven analytes was performed using a triple-quadrupole mass spectrometer equipped with a negative electrospray ionization source in the multiple reaction monitoring mode. The linear ranges of the seven analytes varied from 0.1-20 μg/L to 2.5-500 mg/L, with correlation coefficients greater than 0.995. The method detection limits were 1.5, 0.02, 0.1, 900, 0.6, and 4 μg/L for <italic>trans</italic>,<italic>trans</italic>-muconic acid (MU), <italic>S</italic>-phenylmercapturic acid (PMA), <italic>S</italic>-benzylmercapturic acid (BMA), hippuric acid (HA), 2-methyl hippuric acid (2MHA), and 3-methyl hippuric acid (3MHA)+4-methyl hippuric acid (4MHA), respectively. The limits of quantification were 5, 0.05, 0.4, 3000, 2, and 12 μg/L for MU, PMA, BMA, HA, 2MHA, and 3MHA+4MHA, respectively. The method was verified by spiking urine samples at three different concentration levels, with recovery rates ranging from 84% to 123%. The intra- and inter-day precisions were 1.8%-8.6% and 1.9%-21.4%, respectively. The extraction efficiencies were 68%-99%, and the matrix effects ranged from -11% to -87%. The urine samples obtained from the German external quality assessment scheme (round 65) were used to assess the accuracy of this method. Both high and low concentrations of MU, PMA, HA, and methyl hippuric acid were within the tolerance range. All analytes in the urine samples were found to be stable for up to seven days at room temperature (20 ℃, absence of light), with less than 15% change in concentration. Analytes in urine samples were found to be stable for at least 42 d at 4 ℃ and -20 ℃, or for six freeze-thaw cycles and up to 72 h in an autosampler (8 ℃). The method was applied to the analysis of 16 non-smokers’ and 16 smokers’ urine samples. The detection rates of MU, BMA, HA, and 2MHA were 100% in both non-smokers’ and smokers’ urine samples. PMA was detected in 75% non-smokers’ and 100% smokers’ urine samples. 3MHA+4MHA was detected in 81% non-smokers’ urine and in all smokers’ urine samples. Statistical differences were found for MU, PMA, 2MHA, and 3MHA+4MHA between the two groups (<italic>p</italic><0.001). The established method has good robustness and can provide reliable results. The experiments were carried out in a high-throughput manner with large sample sizes, owing to the small sample volume, and allowed the successful detection of the seven MAH metabolites 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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".