Imaging mass spectrometry (IMS) is becoming an essential technique in lipidomics. Still, many questions remain open, precluding it from achieving its full potential. Among them, identification of species directly from the tissue is of paramount importance. However, it is not an easy task, due to the abundance and variety of lipid species, their numerous fragmentation pathways, and the formation of a significant number of adducts, both with the matrix and with the cations present in the tissue. Here, we explore the fragmentation pathways of 17 lipid classes, demonstrating that in-source fragmentation hampers identification of some lipid species. Then, we analyze what type of adducts each class is more prone to form. Finally, we use that information together with data from on-tissue MS/MS and MS3 to refine the peak assignment in a real experiment over sections of human nevi, to demonstrate that statistical analysis of the data is significantly more robust if unwanted peaks due to fragmentation, matrix, and other species that only introduce noise in the analysis are excluded.

中文翻译：

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脂质碎片化对成像质谱实验数据分析的影响。

成像质谱（IMS）成为脂质组学中必不可少的技术。尽管如此，许多问题仍然悬而未决，无法发挥其全部潜力。其中，直接从组织中鉴定物种至关重要。然而，由于脂质种类丰富且种类繁多，其众多的断裂途径以及与基质和组织中存在的阳离子形成大量的加合物，这并不是一件容易的事。在这里，我们探索了17种脂质类别的片段化途径，证明了源内片段化阻碍了某些脂质种类的鉴定。然后，我们分析每个班级更容易形成哪种类型的加合物。最后，