Mass-Dependent Critical Value Expressions for Particle Finding in Single-Particle ICP-TOFMS.
Mass-Dependent Critical Value Expressions for Particle Finding in Single-Particle ICP-TOFMS.
复制标题
单粒子 ICP-TOFMS 中粒子查找的质量相关临界值表达式。
DOI：
10.1021/acs.analchem.2c05243
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发表时间：
2023
影响因子：
7.4
通讯作者：
Richard Lancaster
中科院分区：
文献类型：
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作者：
Alexander Gundlach;Richard Lancaster
在飞行时间质谱（TOFMS）中，离子检测通常通过电子倍增和快速模数转换（ADC）来实现。选择这种检测方法进行时间-数字转换，因为它扩展了TOFMS测量的动态范围，特别是对于瞬态分析。然而，快速ADC检测也引入了电子倍增过程的基本测量噪声。在以前的研究中，我们证明了与快速ADC采集的飞行时间质谱信号遵循复合泊松分布，其中泊松分布的离子到达检测器的复合与电子倍增器的响应曲线。在这里，我们考虑的影响的质量-电荷（m/z）依赖的检测器的响应和它们的影响，在单粒子电感耦合等离子体飞行时间质谱仪（spICP-TOFMS）的粒子发现的准确性。在spICP-TOFMS中，记录高度时间分辨的离子信号，并且基于在m/z特定临界值处对数据进行阈值化来将粒子信号与背景信号区分开。通过蒙特卡洛建模与测量的m/z相关的检测器响应，我们生成复合泊松模型分布和临界值，准确地占测量信号的分散。我们测试的准确性，通过分析溶解元素的解决方案和比较的测量与预测的事件发生率高于临界值阈值的临界值。与基于正常或泊松统计的阈值标准相比，使用m/z依赖的复合泊松临界值将假阳性颗粒识别减少了一到两个数量级。复合泊松临界值的精度和鲁棒性的提高使得spICP-TOFMS中的自动多元素粒子发现成为可能。
In time-of-flight mass spectrometry (TOFMS), ion detection is often achieved via electron multiplication followed by fast analog-to-digital conversion (ADC). This detection approach is chosen over time-to-digital conversion because it extends the dynamic range of TOFMS measurements, especially for transient analyses. However, fast ADC detection also introduces measurement noise fundamental to the electron multiplication process. In previous research, we demonstrated that TOFMS signals acquired with fast ADC follow a compound Poisson distribution in which the Poisson-distributed arrival of ions at the detector is compounded with the response profile of the electron multiplier. Here, we consider the influence of mass-to-charge (m/z)-dependent detector responses and their impact on particle-finding accuracy in single-particle inductively coupled plasma TOFMS (spICP-TOFMS). In spICP-TOFMS, highly time-resolved ion signals are recorded and particle signals are distinguished from background signals based on thresholding the data at m/z-specific critical values. Through Monte Carlo modeling with measured m/z-dependent detector responses, we generate compound Poisson model distributions and critical values that accurately account for the dispersion of measured signals. We test the accuracy of critical values through the analysis of dissolved element solutions and comparison of measured versus predicted event rates above critical value thresholds. The use of m/z-dependent compound Poisson critical values reduces false-positive particle identifications by one to two orders of magnitude compared to thresholding criteria based on normal or Poisson statistics. The improved accuracy and robustness of compound Poisson critical values enables automated multi-element particle finding in spICP-TOFMS.