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Simultaneous determination of 12 antibacterial drugs in cream disinfection products with EMR-Lipid cleanup using ultra-high-performance liquid chromatography tandem mass spectrometry

Feng Zhu,a Xiaosong Wu,a Fang Li,a Wei Wang,a Wenliang Ji,a Zongli Huoa and Yan Xu*a

论文插图 封面设计 | First Published: 2019-08-16

The use of antibiotics and their occurrence in environmental samples, biological samples, meat, dairy products and cosmetics have attracted worldwide attention in recent years owing to the spread of antibiotic resistance genes. However, analysis of antibacterial drugs in disinfection products was rarely realized. Hence, we herein reported the development and validation of an effective multiresidue method for the analysis of 12 antibacterial drugs in cream disinfection products, in which enhanced matrix removal-lipid (EMR-Lipid) hyphenated with ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) was utilized. The method was optimized based on the extraction solvent composition and the amounts of EMR-Lipid for cleanup. Acceptable mean absolute recoveries were obtained at a spiked level of 20 μg kg−1 in blank matrix samples for all selected targets, ranging from 35.5% to 82.4%. The co-extractive removal rate (by weight) up to 69.4% with 1 g EMR-Lipid for cleanup resulted in an excellent matrix effect (60.6–113.7%). The method detection and quantification limits of 12 analytes were in the range of 0.02–0.9 μg kg−1 and 0.08–2.7 μg kg−1, respectively. The mean corrected recoveries using the isotopic labeled chemicals of blank matrix samples ranged from 84.6% to 121.4%, when spiked with 5, 20 and 50 μg kg−1 of 12 antibacterial drugs. The results of intra-day precision and inter-day precision for all antibacterial drugs showed excellent repeatability (relative standard deviation (RSD) < 9.96%). Finally, the optimized method was applied to analyze 12 antibacterial drugs in 15 cream disinfection samples, and ofloxacin at a concentration of 21.3 ± 1.8 mg kg−1 was found in one sample.

原文链接

https://pubs.rsc.org/en/content/articlelanding/2019/ay/c9ay00937j#!divAbstract

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