In this study, a new deep eutectic solvent (DES) consist of tetrabuthylammonium bromide (TBABr) and 1-octanol at 1:2 M ratio was prepared for the first time and characterized by Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (H NMR) and carbon nuclear magnetic resonance (C NMR) techniques. The new DES was used as an extraction solvent in the ultrasound assisted liquid-liquid microextraction (UA-LLME) of Erythrosine (E127) in blood, urine, pharmaceutical tablet and syrup samples. Accurate and sensitive determination of erythrosine was accomplished with the combination use of DES-UA-LLME and UV-Vis spectrophotometric detection. Before applying UA-LLME, while protein precipitation was applied to blood samples, pharmaceutical tablets were homogenized and dissolved in methanol. The proposed DES-UA-LLME/UV-VIS procedure was applied directly to urine, syrup sample and supernatant of blood and tablet samples with high recoveries in range of 90% and 100%. Erythrosine in the aqueous sample phase was extracted into 200 μL hydrophobic DES phase at pH 7.0. The effect of important analytical variables such as pH of sample solution, mol ratio of DES components, volume of DES, ultrasonic-based extraction time, sample volume and salt effect were optimized. The preconcentration factor (PF), limit of detection (LOD), intra-day and inter-day relative standard deviations (RSD, %) for the developed procedure were found as 40, 3.75 μg·L, 2.6% and 4.6%, respectively.
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http://dx.doi.org/10.1016/j.saa.2020.118842 | DOI Listing |
Food Res Int
February 2025
Hematology Laboratory, Shengjing Hospital of China Medical University, Shenyang 110004, China. Electronic address:
Background: Furfurals, key derivatives of Maillard reactions commonly found in everyday foods, have been identified as having significant toxic effects on human health. Excessive intake of furfurals can lead symptoms such as weight loss, poor nutrient metabolism which followed by disease occurrence. The severe carcinogenicity, mutagenicity and genotoxicity of furfurals were well recognized recently.
View Article and Find Full Text PDFJ Sep Sci
January 2025
Electroanalytical Chemistry Research Laboratory, Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
Herein, an amino-functionalized covalent organic framework was synthesized and accommodated in the pores of porous hollow fiber. In this context, tetra (4-aminophenyl) porphyrin was synthesized for preparing the desired covalent organic framework as the extracting sorbent and employed for hollow fiber solid-phase microextraction of tebuconazole and propiconazole. With respect to the amino groups of the as-synthesized porphyrin-based covalent organic framework, the extracting device has the ability of establishing a hydrogen bond with the selected model analytes.
View Article and Find Full Text PDFSe Pu
February 2025
School of Chemistry and Chemical Engineering, University of Jinan, Jinan 250022, China.
Solid-phase microextraction (SPME) is a fast and simple sample preparation technique that enables the enrichment of analytes, and it is used in combination with other detection techniques to provide accurate and sensitive analytical methods. SPME is widely used in environmental monitoring, food safety, life analysis, biomedicine, and other applications. The extractive coating is the core of the SPME technique, and the properties of the extractive coating greatly influence extraction selectivity and efficiency, as well as the enrichment effect.
View Article and Find Full Text PDFAnal Sci
January 2025
Department of Analytical Chemistry, Faculty of Pharmacy, Near East University, TRNC, Mersin 10, 99138, Nicosia, Turkey.
In this research, a green approach utilizing deep eutectic solvent liquid-liquid microextraction is combined with smartphone digital image colorimetry for the determination of boron in nut samples. A smartphone camera was used to capture the image of the analyte extract located in a custom-made colorimetric box. Using ImageJ software, the images were split into RGB channels, with the green channel identified as the optimum.
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