Ultrasensitive enantiomeric barbiturate analysis in body fluids through capillary electrophoresis with large volume sample stacking and ultrasound assisted dispersive liquid liquid microextraction.

Meng-Chin Chen,Ming-Mu Hsieh, Xin-Yu Huang

Journal of chromatography. A(2024)

Cited 0|Views0
No score
Abstract
A rapid, straightforward, and sensitive approach to quantifying enantiomeric barbiturates in serum was developed by integrating ultrasound-assisted dispersive liquid-liquid microextraction (UA-DLLME) with large-volume sample stacking (LVSS) in capillary electrophoresis (CE). UA-DLLME was employed for sample preparation, and on-column preconcentration by using LVSS with polarity switching was implemented to enhance sensitivity. We thoroughly investigated and optimized various parameters influencing extraction and stacking to achieve optimal detection performance with the highest enrichment efficiencies. Under optimal extraction conditions (injection of a mixed solution containing 40 μL of CHCl3 and 200 μL of tetrahydrofuran into 1 mL of a sample solution at pH 10.0), LVSS was performed using 600 mM Tris-boric acid (pH 9.5) containing 35 mM hydroxypropyl-β-cyclodextrin and sodium taurodeoxycholate hydrate. A voltage of 20 kV was applied and a preinjection water plug was loaded at a height of 25 cm for 10 s. Subsequently, the sample solution was injected at a height of 25 cm for 480 s, after which a voltage of -20 kV was applied and the sample stacking was initiated. The stacking process was completed when 95 % of the separation current was attained. Under optimized conditions, the contraction folds of the four barbiturate analytes (R, S-Secobarbital, R, S-pentobarbital) were improved by approximately 6400-fold, achieving detection limits of 0.1 ng/mL. The limits of quantification for all analyte enantiomers were 0.5-50 ng/mL, demonstrating good linearity (r > 0.997). Migration times exhibited a relative standard deviation of less than 1.7 %, whereas peak areas for the four analytes exhibited a deviation of 8.7 %. Finally, the established method was effectively applied to the analysis of human serum samples.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined