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    A poly(methacrylic acid-co-ethylene glycol dimethacrylate)-based magnetic sorbent was used for the rapid and sensitive determination of tricyclic antidepressants and their main active metabolites in human urine. This material was characterized by magnetism measurements, zeta potential, scanning electron microscopy, nitrogen adsorption-desorption isotherms, and thermogravimetric analysis. The proposed analytical method is based on stir bar sorptive-dispersive microextraction (SBSDME) followed by liquid chromatography-tandem mass spectrometry. The main parameters involved in the extraction step were optimized by using the response surface methodology as a multivariate optimization method, whereas a univariate approach was employed to study the desorption parameters. Under the optimized conditions, the proposed method was properly validated showing good linearity (at least up to 50 ng mL-1) and enrichment factors (13-22), limits of detection and quantification in the low ng L-1 range (1.4-7.0 ng L-1), and good intra- and inter-day repeatability (relative standard deviations below 15%). Matrix effects were observed for the direct analysis of urine samples, but they were negligible when a 1:1 v/v dilution with deionized water was performed. Finally, the method was successfully applied to human urine samples from three volunteers, one of them consuming a prescribed drug for depression that tested positive for clomipramine and its main active metabolite. Quantitative relative recoveries (80-113%) were obtained by external calibration. The present work expands the applicability of the SBSDME to new analytes and new types of magnetic sorbents. © 2022. The Author(s).

    Citation

    Víctor Vállez-Gomis, Sara Exojo-Trujillo, Juan L Benedé, Alberto Chisvert, Amparo Salvador. Stir bar sorptive-dispersive microextraction by a poly(methacrylic acid-co-ethylene glycol dimethacrylate)-based magnetic sorbent for the determination of tricyclic antidepressants and their main active metabolites in human urine. Mikrochimica acta. 2022 Jan 08;189(2):52

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    PMID: 35000010

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