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首页> 外文期刊>Journal of breath research >Prediction of blood:air and fat:air partition coefficients of volatile organic compounds for the interpretation of data in breath gas analysis
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Prediction of blood:air and fat:air partition coefficients of volatile organic compounds for the interpretation of data in breath gas analysis

机译:挥发性有机化合物的血液:空气和脂肪:空气分配系数的预测,用于解释呼吸气体分析中的数据

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摘要

In this article, a database of blood: air and fat: air partition coefficients (lambda b:a and lambda f:a) is reported for estimating 1678 volatile organic compounds recently reported to appear in the volatilome of the healthy human. For this purpose, a quantitative structure-property relationship (QSPR) approach was applied and a novel method for Henry's law constants prediction developed. A random forest model based on Molecular Operating Environment 2D (MOE2D) descriptors based on 2619 literature-reported Henry's constant values was built. The calculated Henry's law constants correlate very well (R-test(2) = 0.967) with the available experimental data. Blood: air and fat: air partition coefficients were calculated according to the method proposed by Poulin and Krishnan using the estimated Henry's constant values. The obtained values correlate reasonably well with the experimentally determined ones for a test set of 90 VOCs (R-2 = 0.95). The provided data aim to fill in the literature data gap and further assist the interpretation of results in studies of the human volatilome.
机译:在本文中,报告了一个血液:空气和脂肪:空气分配系数(lambda b:a和lambda f:a)数据库,用于估计最近报道的1678种挥发性有机化合物出现在健康人的挥发油中。为此,应用了一种定量结构-性质关系(QSPR)方法,并开发了一种新的亨利定律常数预测方法。建立了基于2619年文献报道的亨利常数值的,基于Molecular Operating Environment 2D(MOE2D)描述符的随机森林模型。计算出的亨利定律常数与可用的实验数据具有很好的相关性(R-test(2)= 0.967)。血液:空气和脂肪:空气分配系数是根据Poulin和Krishnan提出的方法,使用估算的Henry常数值计算得出的。对于90个VOC的测试集(R-2 = 0.95),获得的值与实验确定的值具有很好的相关性。提供的数据旨在填补文献数据的空白,并进一步帮助解释人类挥发性组学的结果。

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