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A Simple and Rapid Method for Quantitative HPLC MS/MS Determination of Selected Perfluorocarboxylic Acids and Perfluorosulfonates in Human Serum
International Journal of Analytical Chemistry ( IF 1.5 ) Pub Date : 2020-10-16 , DOI: 10.1155/2020/8878618
Valentina Marra 1 , Annalisa Abballe 1 , Elena Dellatte 1 , Nicola Iacovella 1 , Anna Maria Ingelido 1 , Elena De Felip 1
Affiliation  

Per- and polyfluorinated alkyl substances (PFASs) are ubiquitous environmental contaminants, present in the environment and in the human body. They have raised global concern because of their diffusion in the environment, particularly in water, causing cases of human overexposure due to consumption of contaminated drinking water. Human biomonitoring is the most effective way to characterize human exposure to PFASs, and it is important that as many labs as possible could easily perform this kind of analysis. Analytical methods for quantitation of PFAS mixtures in human serum have been developed, but most of them required materials that are not always easily available in all the laboratories. This paper describes a very simple and accessible HPLC MS/MS method of analysis and quantification of 13 perfluorocarboxylic acids and perfluorosulfonate compounds (belonging to the class of per- and polyfluorinated alkyl substances (PFASs)) in human serum. Method development data provide detailed descriptions of the optimization process in terms of sample preparation, laboratory analysis of human serum samples, determination of analytes by HPLC MS/MS, and describing the pump gradient time, working conditions, and acquisition.

中文翻译:

一种简便快速的定量HPLC MS / MS方法测定人血清中选定的全氟羧酸和全氟磺酸盐

全氟和多氟烷基物质(PFAS)是普遍存在的环境污染物,存在于环境和人体中。由于它们在环境中的扩散,特别是在水中的扩散,引起了全球的关注,由于食用受污染的饮用水,导致了人类过度暴露的情况。人体生物监测是表征人体暴露于PFAS的最有效方法,因此重要的是,尽可能多的实验室可以轻松地进行此类分析。已经开发出定量分析人血清中PFAS混合物的分析方法,但是大多数方法都需要并非在所有实验室中都能轻易获得的材料。本文介绍了一种非常简单易用的HPLC MS / MS方法,用于分析和定量测定人血清中的13种全氟羧酸和全氟磺酸化合物(属于全氟和多氟烷基物质(PFAS)的类别)。方法开发数据提供了关于优化过程的详细说明,包括样品制备,人体血清样品的实验室分析,通过HPLC MS / MS确定分析物以及描述泵的梯度时间,工作条件和采集。
更新日期:2020-10-17
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