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March 28, 2026ACS Measurement Science AuOpen Access

Transformation-Aware Molecular Networking for Interpretation of Untargeted LC–HRMS Data

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Authors

EFE. FerriCCCristian CaprariMVMaria Angela Vandelli

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Overview

Demonstrates improved metabolite annotation in forensic samples, suggesting enhanced chemical analysis of new psychoactive substances.

Key Points

  • The research aims to enhance the interpretation and organization of untargeted LC–HRMS data for forensic toxicology.
  • Evaluated an untargeted LC–HRMS measurement and data-analysis framework.
  • Analyzed blood and urine samples from a suspected DUID case.
  • Used a customized workflow in Compound Discoverer for data processing.
  • Integrated spectral library matching and transformation-aware molecular networking.
  • The new approach increased the number of metabolite-related features detected.
  • Supported reconstruction of chemically consistent metabolic families even without parent compounds.
  • Enhanced contextual interpretation of metabolite features related to NPS in forensic analyses.

Cite This Study

Ferri et al. (2026) studied this question.

synapsesocial.com/papers/69c7724e8bbfbc51511e29d9https://doi.org/10.1021/acsmeasuresciau.6c00011
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