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Related Concept Videos

High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For example, the mass of helium...
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...

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Related Experiment Video

Updated: Jun 23, 2026

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

Published on: May 20, 2013

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

Elena Ferri1,2, Cristian Caprari1,3, Maria Angela Vandelli1

  • 1Department of Life Sciences, University of Modena and Reggio Emilia, Via Campi 103 41125, Modena, Italy.

ACS Measurement Science Au
|June 22, 2026
PubMed
Summary

Untargeted LC-HRMS with transformation-aware molecular networking improves identification of new psychoactive substances (NPS) and their metabolites in forensic toxicology. This method enhances metabolite coverage and interpretation, even when parent compounds are absent.

Keywords:
biotransformation pathwaysforensic toxicologymetabolite identificationnew psychoactive substancestransformation-aware molecular networkinguntargeted LC–HRMS

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Last Updated: Jun 23, 2026

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
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Published on: January 12, 2024

Area of Science:

  • Forensic Toxicology
  • Analytical Chemistry
  • Mass Spectrometry

Background:

  • New psychoactive substances (NPS) and their complex biotransformations pose challenges for forensic toxicology.
  • Targeted analytical methods often fail to detect low-concentration parent compounds or their metabolites, limiting interpretation.
  • Untargeted liquid chromatography-high-resolution mass spectrometry (LC-HRMS) offers a broader analytical scope.

Purpose of the Study:

  • To evaluate an untargeted LC-HRMS data-analysis framework for improved metabolite annotation and structural contextualization in forensic samples.
  • To assess the utility of transformation-aware molecular networking for organizing and interpreting complex xenobiotic data.
  • To enhance the reliability of chemical measurements in cases involving new psychoactive substances.

Main Methods:

  • Analysis of blood and urine samples from a suspected driving under the influence of drugs (DUID) case using untargeted LC-HRMS.
  • Data processing using Compound Discoverer with spectral library matching (mzCloud, HighResNPS.com), rule-based metabolite prediction (MetID), and transformation-aware molecular networking.
  • Integration of MS/MS spectral similarity with predicted phase I and phase II biotransformations.

Main Results:

  • Transformation-aware molecular networking successfully linked parent compounds, metabolites, and related features.
  • This approach increased the number of metabolite-related features associated with detected xenobiotics compared to rule-based prediction alone.
  • Chemically consistent metabolic families were reconstructed, including cases where parent compounds were not detected.

Conclusions:

  • Transformation-aware molecular networking effectively organizes and interprets untargeted LC-HRMS data by integrating spectral similarity and biotransformation relationships.
  • This framework provides a more contextual interpretation of metabolite-related features in forensic and toxicological investigations.
  • The method enhances the analysis of new psychoactive substances and other xenobiotics in complex biological matrices.