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Critical assessment of the Kendrick mass defect analysis as an innovative approach to process high resolution mass spectrometry data for environmental applications
Summary
Researchers reviewed how Kendrick mass defect analysis — a mathematical transformation of high-resolution mass spectrometry data — can efficiently group structurally related compounds such as PFAS, polymers, and natural organic matter, arguing this technique is underutilized in environmental science despite its power for untargeted screening.
The growing application of high resolution mass spectrometry (HRMS) over the last decades has dramatically improved our knowledge about the occurrence of environmental contaminants. However, most of the compounds detected remain unknown and the large volume of data generated requires specific processing approaches. Therefore, this study presents the concepts of mass defect (MD), Kendrick mass (KM) and Kendrick mass defect (KMD) to the expert and non-expert reader along with relevant examples of applications in environmental HRMS data processing. A preliminary bibliometric overview indicates that the potential benefits of KMD analysis are rather overlooked in environmental science. In practice, a simple calculation allows transforming a mass from the IUPAC system (normalized so that the mass of C is exactly 12) to its corresponding KM normalized on a specific moiety such as CH (the mass of CH is exactly 14). Then, plotting the KMD according to the nominal KM allows revealing groups of compounds that differ only by their number of CH moieties. For instance, data processing using KM and KMD was proven particularly useful to characterize natural organic matter in a sample, to reveal the occurrence of polymers as well as poly/perfluorinated alkylated substances (PFASs), and to search for transformation products (TPs) of a given chemical.
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