4.7 Article

Digital microfluidic platform assembled into a home-made studio for sample preparation and colorimetric sensing of S-nitrosocysteine

Journal

ANALYTICA CHIMICA ACTA
Volume 1254, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.aca.2023.341077

Keywords

Luminosity control; Digital microfluidics (DMF); On -chip decomposition; Colorimetric sensor; S-nitrosothiols

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Digital microfluidics (DMF) is a versatile lab-on-a-chip platform integrated with UV-LEDs for sample degradation and colorimetric detection, as demonstrated in the analysis of S-nitrosocysteine (CySNO). The proposed integration showed satisfactory correlation with the results from a desktop scanner, and the analytical parameters revealed linear behavior in the CySNO concentration range of 12.5-400 mu mol L-1, with a limit of detection of 2.8 mu mol L-1. Synthetic serum and human plasma samples were successfully analyzed with no statistical difference observed.
Digital microfluidics (DMF) is a versatile lab-on-a-chip platform that allows integration with several types of sensors and detection techniques, including colorimetric sensors. Here, we propose, for the first time, the integration of DMF chips into a mini studio containing a 3D-printed holder with previously fixed UV-LEDs to promote sample degradation on the chip surface before a complete analytical procedure involving reagent mixture, colorimetric reaction, and detection through a webcam integrated on the equipment. As a proof-of-concept, the feasibility of the integrated system was successfully through the indirect analysis of S-nitrosocysteine (CySNO) in biological samples. For this purpose, UV-LEDs were explored to perform the photolytic cleavage of CySNO, thus generating nitrite and subproducts directly on DMF chip. Nitrite was then colorimetrically detected based on a modified Griess reaction, in which reagents were prepared through a programable movement of droplets on DMF devices. The assembling and the experimental parameters were optimized, and the proposed integration exhibited a satisfactory correlation with the results acquired using a desktop scanner. Under the optimal experimental conditions, the obtained CySNO degradation to nitrite was 96%. Considering the analytical parameters, the proposed approach revealed linear behavior in the CySNO concentration range between 12.5 and 400 mu mol L-1 and a limit of detection equal to 2.8 mu mol L-1. Synthetic serum and human plasma samples were successfully analyzed, and the achieved results did not statistically differ from the data recorded by

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