Journal
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
Volume 207, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.jpba.2021.114399
Keywords
Trans-resveratrol; Point-of-care; Electrochemistry; Differential pulse voltammetry; Antioxidant; Screen-printed electrodes
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This study proposed a new method for detecting the natural polyphenolic antioxidant Resveratrol (t-RESV) using unmodified screen-printed electrodes and differential pulse voltammetry (DPV). The optimized parameters allowed for accurate and rapid quantification of t-RESV, suitable for detection in commercial drugs.
Trans-resveratrol (t-RESV) is an important and natural polyphenolic antioxidant generally found in grapes and in its derivatives such as red wine and grape juices. The t-RESV has been explored in the pharmaceutical industry for its anti-inflammatory, anti-cancer, and neuroprotective properties. The t-RESV electrochemical determination has basically been carried out using modified electrodes-based sensors. Although these devices show good analytical performance, the electrode preparation can be laborious, and the devices may lack reproducibility. In this sense, it was proposed here a new methodology for the t-RESV electrochemical detection using unmodified screen-printed electrodes and differential pulse voltammetry (DPV). The response of the anodic signal has optimized varying the most important parameters of DPV (pulse time, pulse potential, and pulse step) using the response surface methodology. We showed based on analysis of variance that the new mathematical model developed can predict responses for the t-RESV using DPV. Furthermore, the new analytical method was validated from the limits of detection and quantification. We have still shown that t-RESV can be quantified in commercial drug using DPV with the optimized parameters. The selectivity test also showed that the sensor can be used to determine the antioxidant in other more complex matrices. Additionally, the proposed electrochemical system is completely portable and can work with its own energy, which facilitates point-of-care analysis. (c) 2021 Elsevier B.V. All rights reserved.
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