Mid Sweden University, Department of Natural Sciences, Engineering and Mathematics, SE-851 70 Sundsvall, Sweden.
J Chromatogr A. 2010 Dec 24;1217(52):8195-204. doi: 10.1016/j.chroma.2010.10.083. Epub 2010 Oct 30.
A method for tracking of sample components during liquid chromatography-mass spectrometry (LC-MS) method development has been proposed. The method manages to, fully automatically and without user intervention, find the chromatographic peaks in the data sets, discriminate them to sample components and track them when the separation conditions have been changed. The algorithm utilises the resolution obtained from all considered data sets and has the ability to discriminate the non informative parts. The technique has a great sensitivity even in cases where a majority of the tracked components cannot easily be spotted by means of traditional total ion chromatogram (TIC) or base peak chromatogram (BPC) representations. The method was tested on an experimental sample using six different columns and an average of 79% of the suggested sample components could be successfully tracked at a minimum area of 0.05% of the main component in the sample. 66 components with 79-92% of the total suggested component area were able to be tracked between all data sets. The method could be used to rapidly investigate selectivity during different types of separation conditions.
已经提出了一种在液相色谱-质谱（LC-MS）方法开发中跟踪样品成分的方法。该方法能够完全自动且无需用户干预地找到数据集的色谱峰，将其区分到样品成分，并在分离条件发生变化时对其进行跟踪。该算法利用从所有考虑的数据集中获得的分辨率，并具有区分非信息部分的能力。即使在大多数跟踪成分很难通过传统的总离子色谱（TIC）或基峰色谱（BPC）表示来识别的情况下，该技术也具有很高的灵敏度。该方法在一个实验样品上进行了测试，使用了六种不同的柱子，在样品中主要成分的 0.05%的最小面积下，平均有 79%的建议样品成分能够成功跟踪。在所有数据集中，能够跟踪到 66 个具有 79-92%的总建议成分面积的成分。该方法可用于快速研究不同类型分离条件下的选择性。
