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Breath selection methods for compact mass spectrometry breath analysis

机译:紧凑型质谱呼吸分析呼吸选择方法

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摘要

Compactmass spectrometry (CMS) is a versatile and transportable analytical instrument that has the potential to be used in clinical settings to quickly and non-invasively detect a wide range of relevant conditions frombreath samples.The purpose of this study is to optimise data preprocessing protocols by three proposedmethods of breath sampling, using theCMS. It also lays out a general framework for which data processingmethods can be evaluated. Methods. This paper considers data fromthree previous studies, each using a different breath samplingmethod.These include a peppermintwashout study using continuous breath sampling with a purified air source, an exercise study using continuous breath sampling with anambient air source, and a single breath sampling study with an ambient air source. For each dataset, different breath selection (data preprocessing)methodswere compared and benchmarked according to predictive performance on a validation set and quantitative reliability ofm/z bin intensitymeasurements. Results. For both continuousmethods, the best breath selectionmethod improved the predictivemodel compared to no preselection, asmeasured by the 95%CI range for Youden’s index, from 0.68-0.86 to 0.86-0.97 for the exercise study and 0.69-0.82 to 1.00-1.00 for the peppermint study.The reliability of intensitymeasurements for both datasets (asmeasured bymedian relative standard deviation (RSD)),was improved slightly by the best selectionmethod compared to no preselection, from18%to 14%for the exercise study and 7%-5%for the peppermint study. For the single breath samples, all themodels resulted in perfect prediction, with a 95%CI range forYouden’s index of 1.00-1.00.The reliability of the proposedmethod was 38%. Conclusion. Themethod of selecting exhaled breath from CMS data can affect the reliability of themeasurement and the ability to distinguish between breath samples taken under different conditions. The application of appropriate data processingmethods can impr
机译:紧凑型光谱法(CMS)是一种通用和可转运的分析仪器,具有临床环境中使用的潜力,以快速和非侵入性地检测来自BREAL样本的广泛相关条件。本研究的目的是优化数据预处理协议使用THECMS的三个呼吸抽样方法。它还列出了可以评估数据处理方法的一般框架。方法。本文考虑了从三个先前研究的数据,每次使用不同的呼吸样本方法。这些方法包括使用连续呼吸抽样的薄荷动力学研究,使用纯化的空气来源,使用连续呼吸采样与纸币空气来源进行连续呼吸,以及单一呼吸取样研究环境空气源。对于每个数据集,不同的呼吸选择(数据预处理)比较和基准测试根据预测性能,并在验证集和数量可靠性的IN / Z BIN强度模糊。结果。对于两个连续的方法,最好的呼吸精选方法改善了预测的预测,而不是预先选择,因为Yens的指数的95%CI范围,从0.68-0.86到0.86-0.97为运动研究,薄荷为0.69-0.82至1.00-1.00。研究。两种数据集的强度模糊的可靠性(asmeasuceed bymedian相对标准偏差(RSD))与无需预选相比,略微改善,锻炼研究的18%至14%,薄荷为7%-5%学习。对于单呼吸样品,所有的主题都导致完美预测,95%CI范围Foroden的指数为1.00-1.00。拟议方法的可靠性为38%。结论。从CMS数据中选择呼出的呼气的Themethod可能会影响对不同条件下采取的呼吸样品之间的可靠性以及区分呼吸样品的能力。适当数据处理方法的应用程序可以使用

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