Matrix clean-up prior to extraction: a novel dispersive micro solid-phase strategy for determining some antidepressants in dam water, pharmaceutical wastewater, and follicular fluid

Abstract

For the first time, an analytical strategy was developed that prioritizes the removal of matrix interferences rather than directly preconcentrating analytes, enabling accurate extraction and quantification of antidepressants from complex real samples. A core–shell magnetic metal–organic framework (Cu-BTC@Fe3O4) was employed to effectively adsorb and eliminate matrix components, thereby cleaning up the sample matrix and facilitating analyte extraction. The integration of dispersive micro solid-phase extraction for matrix removal with vortex-assisted liquid–liquid microextraction and gas chromatography-flame ionization detection (GC-FID) resulted in excellent analytical performance. The method achieved low limits of detection (0.80–1.05 μg L−1) and limits of quantification (2.70–3.51 μg L−1), high enrichment factors (300–355), acceptable extraction recoveries (60–71%), and wide linear ranges (3.5–10 000 μg L−1). Additionally, the reusability of the adsorbent enhanced the method's environmental sustainability and cost-effectiveness. By prioritizing matrix cleanup as a crucial initial step, this innovative approach offers a robust and practical solution for the trace analysis of antidepressants in highly contaminated environments.

Graphical abstract: Matrix clean-up prior to extraction: a novel dispersive micro solid-phase strategy for determining some antidepressants in dam water, pharmaceutical wastewater, and follicular fluid

Supplementary files

Article information

Article type
Paper
Submitted
01 May 2025
Accepted
26 Jun 2025
First published
11 Jul 2025

Anal. Methods, 2025, Advance Article

Matrix clean-up prior to extraction: a novel dispersive micro solid-phase strategy for determining some antidepressants in dam water, pharmaceutical wastewater, and follicular fluid

S. Mohammad Mehri, M. A. Farajzadeh and M. R. Afshar Mogaddam, Anal. Methods, 2025, Advance Article , DOI: 10.1039/D5AY00741K

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