Synthesis and Characterization of Electrospun Sorbent for the Solid-Phase Extraction of Fluoroquinolones in Human Plasma and Their UHPLC-PDA Determination

In this work we investigated the synthesis and the characterization of electrospun polyacrylonitrile (PAN) and polymethyl methacrylate (PMMA) stabilized in air, made in a 5:1 ratio, used as sorbent for the solid-phase extraction of fluoroquinolones in plasma samples and the following quantification in UHPLC-PDA. Preliminary analyses of viscosity were carried out on the polymer solution to be sure about the electrospinability. Characterizations were performed on the electrospun membrane to evaluate the morphology (SEM scanning electron microscopy and AFM atomic force microscopy), the thermal degradation behavior (TGA thermogravimetric analysis), the porosity and the surface area (BET, Brunauer Emmett Teller), and the quantitative and qualitative distribution of atomic structures (FTIR infrared analysis in Fourier transform and EDX Energy Dispersive X-ray analysis). A solid-phase extraction method was developed by studying parameters such as the amount of sorbent and the pH of the sample. Finally, a UHPLC-PDA method for the analysis of fluoroquinolones was developed and validated in accordance with the guidelines and successfully applied. The use of the prepared sorbent combined with UHPLC-PDA has allowed the development of a method whose strengths are its speed, accuracy, sensitivity, and high recoveries.

Automated summary

This work investigated the synthesis and characterization of electrospun PAN and PMMA stabilized in air, used as sorbent for solid-phase extraction of fluoroquinolones in plasma samples and subsequent quantification in UHPLC-PDA. Characterizations including morphology, thermal degradation behavior, porosity, surface area, and atomic structures distribution were performed on the electrospun membrane. A solid-phase extraction method was developed by studying parameters such as sorbent amount and sample pH. A UHPLC-PDA method for fluoroquinolones analysis was successfully developed and applied, showing advantages in terms of speed, accuracy, sensitivity, and high recoveries.