American Chemical Society
ao4c01169_si_001.pdf (367.83 kB)

Superlative and Selective Sensing of Serotonin in Undiluted Human Serum Using Novel Polystyrene Sulfonate Conductive Polymer

Download (367.83 kB)
journal contribution
posted on 2024-03-26, 08:43 authored by Victoria E. Coyle, Michael C. Brothers, Sarah McDonald, Steve S. Kim
In the past 5 years, real-time health monitoring has become ubiquitous with the development of watches and rings that can measure and report on the physiological state. As an extension, real-time biomarker sensors, such as the continuous glucose monitor, are becoming popular for both health and performance monitoring. However, few real-time sensors for biomarkers have been made commercially available; this is primarily due to problems with cost, stability, sensitivity, selectivity, and reproducibility of biosensors. Therefore, simple, robust sensors are needed to expand the number of analytes that can be detected in emerging and existing wearable platforms. To address this need, we present a simple but novel sensing material. In short, we have modified the already popular PEDOT/PSS conductive polymer by completely removing the PEDOT component and thus have fabricated a polystyrene sulfonate (PSS) sensor electrodeposited on a glassy carbon (GC) base (GC-PSS). We demonstrate that coupling the GC-PSS sensor with differential pulse voltammetry creates a sensor capable of the selective and sensitive detection of serotonin. Notably, the GC-PSS sensor has a sensitivity of 179 μA μM–1 cm–2 which is 36x that of unmodified GC and an interferent-free detection limit of 10 nM, which is below the concentrations typically found in saliva, urine, and plasma. Notably, the redox potential of serotonin interfacing with the GC-PSS sensor is at −0.188 V versus Ag/AgCl, which is significantly distanced from peaks produced by common interferants found in biofluids, including serum. Therefore, this paper reports a novel, simple sensor and polymeric interface that is compatible with emerging wearable sensor platforms.