ArticleACS measurement science au2024
Waveform Optimization for the
Article in ACS measurement science au, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
Caffeic acid is a polyphenol of critical importance in plants, involved in a variety of physiological processes including lignin formation, cellular growth, stress response, and external signaling. This small molecule also acts as a powerful antioxidant and thus has therapeutic potential for a variety of health conditions. Traditional methods of detecting caffeic acid lack appropriate temporal resolution to monitor real time concentration changes on a subsecond time scale with nM detection limits. Here we report on the first usage of fast-scan cyclic voltammetry with carbon fiber microelectrodes for the detection of caffeic acid. Through the use of flow injection analysis, the optimal waveform for its detection under acidic conditions at a scan rate of 400 V/s was determined to be sawtooth-shaped, from 0 to 1.4 to -0.4 to 0 V. Signal was linear with concentration up to 1 μM with a sensitivity of 44.8 ± 1.3 nA/μM and a detection limit of 2.3 ± 0.2 nM. The stability of its detection was exceptional, with an average of 0.96% relative standard deviation across 32 consecutive injections. This waveform was also successful in detecting other catechol-based plant antioxidants including 5-chlorogenic acid, oleuropein, rosmarinic acid, chicoric acid, and caffeic acid phenethyl ester. Finally, we show the successful use of fast-scan cyclic voltammetry in monitoring the degradation of caffeic acid by polyphenol oxidase on a subsecond time scale
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Registered trials
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