MassQL can be a powerful tool for polyphenols, as specific fragments can be queried, such as backbones of certain polyphenol classes. Additionally, MassQL can be used for neutral loss queries, such as sulfate and glucuronide loss as done here on the 24-h urine samples. These two biotransformation products were chosen because the suspect screening revealed that a large percentage of the features annotated were conjugated. The two queries yielded 502 features with a sulfate loss (Table ) and 160 features with a glucuronide loss (Table ). The relationship between the features detected from MassQL, suspect screening, and the other non-targeted analysis techniques is shown in Figure . The same queries were then applied to the raw mzML data to find potentially analytes lost during feature processing, e.g. with "non-ideal" peak shapes. These queries yielded an additional 1025 hits (Table ) for glucuronide loss and 10208 hits (Table ) for sulfate loss that were not previously determined. It has to be noted that the high number of hits is because these are not features yet but rather refer to an MS 2 scan. The number of hits were reduced by clustering and grouping the hits by their MS 1 and retention times. Another problem with MassQL is identification errors, such as e.g. false positive results, depending on the selected parameters, such as e.g. the ppm deviation.