Abstract
BackgroundDopamine (DA) is an important neurotransmitter in the hypothalamus and pituitary gland, which can produce a direct influence on mammals’ emotions in midbrain. Additionally, the level of DA is highly related with some important neurologic diseases such as schizophrenia, Parkinson, and Huntington’s diseases, etc. In light of the important roles that DA plays in the disease modulation, it is of considerable significance to develop a sensitive and reproducible approach for monitoring DA.PurposeThe objective of this study was to develop an efficient approach to quantitatively monitor the level of DA using Ag nanoparticle (NP) dimers and enhanced Raman spectroscopy.MethodsAg NP dimers were synthesized for the sensitive detection of DA via surface-enhanced Raman scattering (SERS). Citrate was used as both the capping agent of NPs and sensing agent to DA, which is self-assembled on the surface of Ag NP dimers by reacting with the surface carboxyl group to form a stable amide bond. To improve accuracy and precision, the multiplicative effects model for surface-enhanced Raman spectroscopy was utilized to analyze the SERS assays.ResultsA low limits of detection (LOD) of 20 pM and a wide linear response range from 30 pM to 300 nM were obtained for DA quantitative detection. The SERS enhancement factor was theoretically valued at approximately 107 by discrete dipole approximation. DA was self-assembled on the citrate capped surface of Ag NPs dimers through the amide bond. The adsorption energy was estimated to be 256 KJ/mol using the Langmuir isotherm model. The density functional theory was used to simulate the spectral characteristics of SERS during the adsorption of DA on the surface of the Ag dimers. Furthermore, to improve the accuracy and precision of quantitative analysis of SERS assays with a multiplicative effects model for surface-enhanced Raman spectroscopy.ConclusionA LOD of 20 pM DA-level was obtained, and the linear response ranged from 30 pM to 300 nM for quantitative DA detection. The absolute relative percentage error was 4.22% between the real and predicted DA concentrations. This detection scheme is expected to have good applications in the prevention and diagnosis of certain diseases caused by disorders in the DA level.
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