@article{3057316,
    title = "Application of a novel prioritisation strategy using non-target screening for evaluation of temporal trends (1969–2017) of contaminants of emerging concern (CECs) in archived lynx muscle tissue samples",
    author = "Dürig, W. and Alygizakis, N.A. and Wiberg, K. and Ahrens, L.",
    journal = "Science of the Total Environment, The",
    year = "2022",
    volume = "817",
    publisher = "Elsevier B.V.",
    doi = "10.1016/j.scitotenv.2022.153035",
    keywords = "Feature extraction;  Muscle, Contaminants of emerging concerns;  Environmental specimen bank;  LC-QToF-MS;  Lynx;  Non-target analysis;  Non-target screenings;  Prioritization;  Temporal trend analyse;  Temporal trends;  Trend analysis, Screening, bioaccumulation;  felid;  liquid chromatography;  mass spectrometry;  muscle;  pollutant;  temporal analysis;  trend analysis, article;  biobank;  Lynx lynx;  matrix effect;  muscle tissue;  nonhuman;  predator;  terrestrial species;  time series analysis;  workflow;  animal;  chemistry;  environmental monitoring;  Lynx;  muscle;  water pollutant, Animals;  Environmental Monitoring;  Lynx;  Muscles;  Water Pollutants, Chemical",
    abstract = "Most environmental monitoring studies of contaminants of emerging concern (CECs) focus on aquatic species and target specific classes of CECs. Even with wide-scope target screening methods, relevant CECs may be missed. In this study, non-target screening (NTS) was used for tentative identification of potential CECs in muscle tissue of the terrestrial top predator Eurasian lynx (Lynx lynx). Temporal trend analysis was applied as a prioritisation tool for archived samples, using univariate statistical tests (Mann-Kendall and Spearman rank). Pooled lynx muscle tissue collected from 1969 to 2017 was analysed with an eight-point time series using a previously validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 12,941 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 104 and 61 features with statistically significant increasing and decreasing trends, respectively. Following probable molecular formula assignment and elucidation with MetFrag, two compounds with increasing trends, and one with a decreasing trend, were tentatively identified. These results show that, despite low expected concentration levels and high matrix effects in terrestrial species, it is possible to prioritise CECs in archived lynx samples using NTS and univariate statistical approaches. © 2022 The Authors"
}