Welcome Emma to Kruvelab!
In the autumn, we were lucky to participate in an interlaboratory trial on non-target screening (NTS) with liquid chromatography high-resolution mass spectrometry (LC/HRMS) alongside other Swedish labs. We were able to test our ability to identify spiked chemicals in blind water samples as well as quantify the tentatively identified chemicals with our machine learning predicted ionization efficient-based quantification methods that do not require analytical standards. Including, MS2Quant, a recently launched package that allows quantification based on the MS2 spectra and does not require structural identification. Despite this success, some ends were left loose. For example, we were able to work only with the positive ESI ionization data for quantification.
Now Emma Apelgren has started her BSc thesis where she will investigate these samples further and compare the performance of the quantification methods in ESI positive and negative mode. As part of this, Emma will evaluate a calibration mixture for associating the predicted ionization efficiency values with the instrument-specific calibration graph slopes.
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