The effect of mass spectrometry tuning frequency and criteria on ion relative abundances of cathinones and cannabinoids
Autor: | Suzanne Bell, Kristin Kelly, Sydney Brooks |
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Rok vydání: | 2019 |
Předmět: |
010401 analytical chemistry
Mass spectrometry 01 natural sciences 0104 chemical sciences Pathology and Forensic Medicine Analytical Chemistry 03 medical and health sciences 0302 clinical medicine Materials Chemistry Mass spectrum Environmental science 030216 legal & forensic medicine Physical and Theoretical Chemistry Drug analysis Gas chromatography–mass spectrometry Biological system Law Spectroscopy |
Zdroj: | Forensic Chemistry. 12:58-65 |
ISSN: | 2468-1709 |
DOI: | 10.1016/j.forc.2018.12.001 |
Popis: | Gas chromatography mass spectrometry is the most common instrument used for compound identification in untargeted seized drug analysis. Compound identification using this technique relies on mass spectra where the relative abundances (RAs) of all m/z values are compared manually or searched against a library database. An often-unappreciated aspect to any mass spectral comparison or search is the inherent variation in RAs. To address this, decades ago the Environmental Protection Agency (EPA) established tune check compounds as a means to control variation across vendor platforms. The goal of this study was to evaluate whether the DFTPP criteria, as defined by the EPA, could be used to reduce the RA variation in mass spectra produced by novel psychoactive substances (NPSs). Instruments from two vendors were used to analyze 6 NPSs: 4 cannabinoids and 2 cathinones. Each NPS was analyzed 100 times per instrument; 10 replicates per tune repeated under 10 different tunes. Results showed that passing a DFTPP tune check was not correlated with reduced RA variation. Tuning algorithm differences between vendors impacted variation, but the frequency of instrument tuning was found to be the most critical factor for controlling RA variation. The results of this work suggest that forensic laboratories should develop quantitative metrics to evaluate autotuning results and define how these metrics will be used to dictate maintenance. This practice, coupled with tuning before each analytical batch, will reduce the variation of %RA values as much as practicable. |
Databáze: | OpenAIRE |
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