Akademik Veri Yönetim Sistemi
JOURNAL OF CHROMATOGRAPHY A, cilt.1730, 2024 (SCI-Expanded, Scopus)
Detecting and quantifying amino acids is vital in biochemical analyses, especially for diagnosing metabolic disorders. L-proline, among these amino acids, holds significant relevance for various metabolic disorders in living organisms, particularly in humans. hyperprolinemia arises when ineffective breakdown of L-proline occurs due to enzyme deficiencies, leading to its accumulation in the body and underscoring the need for precise monitoring. To address this challenge, molecular imprinting offers a reliable single-step technique for detecting target molecules like proteins, peptides, amino acids, or ions with high selectivity. Moreover, nanoparticles, with significant surface area-to-volume ratios, enable high-level mass transfer and binding kinetics, making them ideal for nano-scale sensitive applications. In this study, 2-hydroxyethyl methacrylate-based molecularly imprinted nanoparticles were synthesized via mini-emulsion polymerization, combining the advantages of molecular imprinting technique and nanoparticles for the specific recognition of L-proline, and were well-characterized by Scanning Electron Microscopy, zeta-sizer particle size analysis, and Fourier Transform Infrared Spectroscopy. Based on zeta-sizer analysis, the estimated diameters of L-proline-imprinted and non-imprinted nanoparticles (Pro-MIPs and NIPs) were determined to be approximately 27.51 nm and 20.66 nm, respectively. The adsorption of L-proline onto nanoparticles from aqueous solutions was investigated in a batch system, and the maximum Lproline adsorption capacity was determined to be 26.58 mg/g for Pro-MIPs and 4.65 mg/g for and NIPs. The selectivity of Pro-MIPs was assessed using Liquid Chromatography-Tandem Mass Spectrometry, even in human serum and in the presence of competing molecules (L-histidine and L-phenylalanine). Additionally, Pro-MIPs maintained their adsorption capacity through up to 10 adsorption-desorption cycles without significant decrease.