The present review deals with the recent progress made in the field of the electrochemical detection of serotonin by means of electrochemical sensors based on various nanomaterials incorporated in the sensitive element. Due to the unique chemical and physical properties of these nanomaterials, it was possible to develop sensitive electrochemical sensors with excellent analytical performances, useful in the practice. The main electrochemical sensors used in serotonin detection are based on carbon electrodes modified with carbon nanotubes and various materials, such as benzofuran, polyalizarin red-S, poly(L-arginine), Nafion/Ni(OH)2, or graphene oxide, incorporating silver-silver selenite nanoparticles, as well as screen-printed electrodes modified with zinc oxide or aluminium oxide. Also, the review describes the nanocomposite sensors based on conductive polymers, tin oxide-tin sulphide, silver/polypyrole/copper oxide or a hybrid structure of cerium oxide-gold oxide nanofibers together with ruthenium oxide nanowires. The presentation focused on describing the sensitive materials, characterizing the sensors, the detection techniques, electroanalytical properties, validation and use of sensors in lab practice.

Levodopa is a precursor of dopamine, having important beneficial effects in the treatment of Parkinson’s disease. In this study, levodopa was accurately detected by means of cyclic voltammetry using carbon-based (C-SPCE), mesoporous carbon (MC-SPCE) and ordered mesoporous carbon (OMC-SPCE)-modified screen-printed sensors. Screen-printed carbon sensors were initially used for the electrochemical detection of levodopa in a 10−3 M solution at pH 7.0. The mesoporous carbon with an organized structure led to better electroanalysis results and to lower detection and quantification limits of the OMC-SPCE sensor as compared to the other two studied sensors. The range of linearity obtained and the low values of the detection (0.290 µM) and quantification (0.966 µM) limit demonstrate the high sensitivity and accuracy of the method for the determination of levodopa in real samples. Therefore, levodopa was detected by means of OMC-SPCE in three dietary supplements produced by different manufacturers and having various concentrations of the active compound, levodopa. The results obtained by cyclic voltammetry were compared with those obtained by using the FTIR method and no significant differences were observed. OMC-SPCE proved to be stable, and the electrochemical responses did not vary by more than 3% in repeated immersions in a solution with the same concentration of levodopa. In addition, the interfering compounds did not significantly influence the peaks related to the presence of levodopa in the solution to be analyzed.

Serotonin is a biogenic amine that has multiple roles in the human body and is mainly known as the happiness hormone. A new laccase (Lac)-based biosensor has been developed for the qualitative and quantitative determination of serotonin in three dietary supplements from three different manufacturers. The enzyme was immobilized on an organized mesoporous carbon-modified carbon screen-printed electrode (OMC-SPE) by the drop-and-dry method, the active surface being pretreated with glutaraldehyde. With the new biosensor, serotonin was selectively detected from different solutions. Square-wave voltammetry was the technique used for the quantitative determination of serotonin, obtaining a detection limit value of 316 nM and a quantification limit value of 948 nM in the linearity range of 0.1–1.2 µM. The pH for the determinations was 5.2; at this value, the biocatalytic activity of the laccase was optimal. At the same time, the electrochemical performance of the OMC-SPE/Lac biosensor was compared with that of the unmodified sensor, a performance that highlighted the superiority of the biosensor and the very important role of the enzyme in electrodetection. The results obtained from the quantitative determination of serotonin by square-wave voltammetry were compared with those from the FTIR method, revealing a very good correlation between the results obtained by the two quantitative determination methods.