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Record W2077652013 · doi:10.1155/2015/514320

Development of a Method to Detect Three Monohydroxylated Polycyclic Aromatic Hydrocarbons in Human Urine by Liquid Chromatographic Tandem Mass Spectrometry

2015· article· en· W2077652013 on OpenAlexaboutno aff
Xiaotao Zhang, Hongwei Hou, Wei Xiong, Qingyuan Hu

Bibliographic record

VenueJournal of Analytical Methods in Chemistry · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCreatinineChemistryChromatographyUrinePyreneTandem mass spectrometryLiquid chromatography–mass spectrometryMass spectrometryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

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).

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.348
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Analytical Methods in ChemistrySame topicToxic Organic Pollutants ImpactFrench-language works237,207