Headspace SPME GC–MS Analysis of Urinary Volatile Organic Compounds (VOCs) for Classification Under Sample-Limited Conditions
The optimized HS-SPME GC-MS method enables comprehensive, non-targeted urinary VOC profiling from limited sample volumes. This workflow provides a robust analytical foundation for exploratory volatilomics studies under sample-limited conditions and supports subsequent targeted method refinement once specific compounds or chemical classes have been prioritized.
Authors
- T. Illig
- Friederike Twele (ORCID: https://orcid.org/0000-0001-8160-6669)
- Sabine Kaltenhäuser
- Tushar H. More
- S. Meller
- Holger A. Volk (ORCID: https://orcid.org/0000-0002-7312-638X)
- Karolina Zacharias
- Lea Woyciechowski
- Georg M. N. Behrens
Institutions
- University of Veterinary Medicine Hannover, Foundation (DE)
- Medizinische Hochschule Hannover (DE)
- Technische Universität Braunschweig (DE)
Publication Details
- Journal
- Metabolites
- Published
- 2026-01-08
- DOI
- https://doi.org/10.3390/metabo16010057
- Citations
- 1
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 21.28