Matrix effects in analysis of dialkyl phosphate metabolites of organophosphate pesticides in urine by gas chromatography/tandem mass spectrometer

Urinary dialkyl phosphate metabolites (DAPs) are used as biomarkers to evaluate human exposure to organophosphate pesticides. The objective was to evaluate potential artifacts in urinary DAPs analysis during sample preparation and method calibration. Diluted urine pools were commonly used to prepare...

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Published inJournal of environmental science and health. Part B, Pesticides, food contaminants, and agricultural wastes Vol. 48; no. 3; pp. 177 - 182
Main Authors Wang, Dongli, Behniwal, Paramjit, Fan, Ruifang, Simon Ip, Ho Sai, She, Jianwen
Format Journal Article
LanguageEnglish
Published Philadelphia, PA Taylor & Francis Group 01.02.2013
Taylor & Francis
Taylor & Francis Ltd
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Summary:Urinary dialkyl phosphate metabolites (DAPs) are used as biomarkers to evaluate human exposure to organophosphate pesticides. The objective was to evaluate potential artifacts in urinary DAPs analysis during sample preparation and method calibration. Diluted urine pools were commonly used to prepare calibration standards to minimize the effects due to the complexity of urine matrix. Matrix effects on measurements of DAPs were evaluated by spiking known amount of standards into distilled water, synthetic urine and diluted urine pool. Different matrices resulted in similar concentrations detected for all target compounds, except dimethylphosphate (DMP) with the deviation of measurement as large as eight times the spiked amount. In this study, we also found that urinary particles, which usually appeared after thawing frozen human urine samples, could affect the measurements of DAPs, especially DMP and diethylthiophosphate (DETP). Results of DAPs measurements in three types of sample matrices, i.e. urine without particles, urine with particles and particles only were compared. DETP could be subject to large error during this preparation step. The use of deuterated and ¹³C₁₂-labeled DAPs as internal standards is also evaluated. Overall, these issues can cause misidentification and inaccuracies, which may significantly affect the data quality.
Bibliography:http://dx.doi.org/10.1080/03601234.2013.730021
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ISSN:1532-4109
0360-1234
1532-4109
DOI:10.1080/03601234.2013.730021