1. Simultaneous Detection of Dopamine and Serotonin—A Comparative Experimental and Theoretical Study of Neurotransmitter Interactions
- Author
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Kevin E. Bennet, Katia Ochoa, Emma M. Sundin, Michael P. Eastman, William Durrer, John Ciubuc, Jose Guerrero, Mahendra Subedi, Brayant Lopez, Felicia S. Manciu, and Marian Manciu
- Subjects
Analyte ,Serotonin ,lcsh:Biotechnology ,Dopamine ,Clinical Biochemistry ,02 engineering and technology ,Chemical interaction ,Biosensing Techniques ,Spectrum Analysis, Raman ,Article ,neurotransmitters ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,lcsh:TP248.13-248.65 ,medicine ,Humans ,Pharmaceutical sciences ,Neurotransmitter ,Density Functional Theory ,Neurotransmitter Agents ,Chemistry ,General Medicine ,021001 nanoscience & nanotechnology ,surface-enhanced Raman spectroscopy ,label-free optical biosensors ,computational analysis ,Drug delivery ,simultaneous detection ,0210 nano-technology ,Biological system ,Biosensor ,030217 neurology & neurosurgery ,medicine.drug - Abstract
With the goal of accurately detecting and quantifying the amounts of dopamine (DA) and serotonin (5-HT) in mixtures of these neurotransmitters without using any labelling, we present a detailed, comparative computational and Raman experimental study. Although discrimination between these two analytes is achievable in such mixtures for concentrations in the millimolar range, their accurate quantification remains unattainable. As shown for the first time in this work, the formation of a new composite resulting from their interactions with each other is the main reason for this lack of quantification. While this new hydrogen-bonded complex further complicates potential analyte discrimination and quantification at concentrations characteristic of physiological levels (i.e., nanomolar concentrations), it can also open new avenues for its use in drug delivery and pharmaceutical research. This remark is based not only on chemical interactions analyzed here from both theoretical and experimental approaches, but also on biological relationship, with consideration of both functional and neural proximity perspectives. Thus, this research constitutes an important contribution toward better understanding of neural processes, as well as toward possible future development of label-free biosensors.
- Published
- 2018