ArticleACS measurement science au2026
Transformation-Aware Molecular Networking for Interpretation of Untargeted LC-HRMS Data.
Article in ACS measurement science au, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors.
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Abstract
The rapid emergence of new psychoactive substances (NPS) and their extensive biotransformation challenge the reliability and interpretability of chemical measurements in forensic toxicology. Targeted analytical workflows offer high selectivity but frequently fail when parent compounds are present at low concentrations or are absent from biological matrices, limiting metabolite coverage and evidential interpretation. In this study, an untargeted LC-HRMS measurement and data-analysis framework was evaluated to improve metabolite annotation and structural contextualization in complex forensic samples. Blood and urine collected from a suspected driving under the influence of drugs (DUID) case were analyzed using high-resolution full-scan and data-dependent MS/MS acquisition as a representative test system. Data were processed in Compound Discoverer using a customized workflow combining spectral library matching (
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