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FACTORS PREDICTIVE OF CONGENER PROFILES EXTRACTED BY POLYTOPIC VECTOR ANALYSIS IN HUMAN SERUM

机译:人类血清中多态矢量分析法提取同源基因的因素预测

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Introduction Polytopic vector analysis (PVA) is a multivariate statistical technique used to evaluate source contributions to complex chemical mixtures. PVA was applied to the University of Michigan Dioxin Exposure Study (UMDES) serum dataset to evaluate possible exposure sources of dioxin-like compounds and to compare exposure sources between the UMDES populations. Previous analysis demonstrated that two of the congener profiles extracted from the serum data varied by study population: This paper describes a bivariate analysis to evaluate whether selected region-specific parameters were predictive of levels of certain congener profiles in serum.
机译:简介多边形矢量分析(PVA)是一种多元统计技术,用于评估源对复杂化学混合物的贡献。 PVA被应用于密歇根大学二恶英暴露研究(UMDES)血清数据集,以评估二恶英样化合物的可能暴露源,并比较UMDES人群之间的暴露源。先前的分析表明,从血清数据中提取的两个同类物谱因研究人群而异:本文描述了一种双变量分析,以评估所选区域特定参数是否可预测血清中某些同类物谱的水平。

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