Ion mobility as an additional separation dimension can help to resolve and annotate metabolite and lipid biomarkers and provides important information about the components in a sample. Identifying relevant information in the resulting data is challenging because of the complexity of the data and data evaluation strategies for both targeted or nontargeted workflows. Frequently, feature analysis is used as a first step to search for differences between samples in discovery workflows. However, follow-up experimentation often leads to more targeted data extraction methods. In both cases, optimizing data sets for data extraction can make an important contribution to the overall results. In this work, we evaluate the effect of experimental conditions including acquisition sampling rate and data pretreatment on lipid standards and lipid extracts as examples of complex biological samples analyzed by liquid chromatography coupled to drift time ion mobility quadrupole time-of-flight mass spectrometry. The results show that a reduction of both peak variation and background noise can be achieved by optimizing the sampling rate. The use of data pretreatment including data smoothing, intensity thresholding, and spike removal also play an important role in improving detection and annotation of analytes from complex biological samples, whereas nonoptimal data sampling rates and preprocessing can lead to adverse effects including the loss or alternation of small, or closely eluting, low-abundant peaks.

中文翻译：

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采用液相色谱耦合漂移时间离子淌度四重飞行时间质谱法对目标和非目标分析的采样率和数据预处理的影响。

离子淌度作为额外的分离维度有助于解析和注释代谢物和脂质生物标志物，并提供有关样品中成分的重要信息。由于目标或非目标工作流的数据和数据评估策略的复杂性，识别结果数据中的相关信息具有挑战性。通常，特征分析被用作在发现工作流程中搜索样本之间差异的第一步。然而，后续的实验往往会导致更有针对性的数据提取方法。在这两种情况下，优化数据集以进行数据提取可以对整体结果做出重要贡献。在这项工作中，我们评估了实验条件的影响，包括采集采样率和数据预处理对脂质标准和脂质提取物的影响，作为通过液相色谱耦合漂移时间离子迁移四极杆飞行时间质谱分析的复杂生物样品的例子。结果表明，通过优化采样率可以降低峰值变化和背景噪声。使用数据预处理（包括数据平滑、强度阈值和尖峰去除）在改进复杂生物样品中分析物的检测和注释方面也发挥着重要作用，而非最佳数据采样率和预处理可能导致不利影响，包括丢失或交替小的或紧密洗脱的低丰度峰。