Abstract

With a rapidly ageing population, neurological diseases are becoming increasingly relevant in the design of public health policies and strategies in western societies. In the last decades, biochemical research has consistently shown the critical role that neurotransmitters and their associated metabolites play as biomarkers in tracking and diagnosis of different brain disorders and cancers. In particular, dopamine, an organic electrochemical neurotransmitter, has been shown to be paramount for the proper functioning of the neural system. Dopamine's dysfunction, has been shown to underlie the pathogenesis in several neurological disorders such as Parkinson's disease, depression, chronic schizophrenia and psychosis. Unfortunately, currently available diagnostic technologies require expensive equipment and trained personnel, thus slowing the process and increasing overall costs, consequently reducing the access to the general population. Ideal sensing alternatives should offer low-cost, fast, and reliable point-of-care diagnosis. In this work, we present a compact label-free plasmonic biosensors that exhibits sharp optical resonance shifts in response to varying dopamine concentrations. While the nanoimprinting of the optical cavity offers a nanofabrication process fully compatible with large-scale production, its small size ensures the suitability for integration on lab-on-a-chip platforms, hence making it a promising alternative to conventional diagnosis. The plasmonic nanostructures of the chips are functionalized with synthetic single-stranded oligonucleotide to ensure precise sensing selectivity. Particularly, we study the standard 57mer and the novel 44mer configurations, establishing the superior resolution offered by the latter. In contrast to other sensing alternatives, our platforms permit reliable detection with ultralow volumes (~6 µL) and exhibit robustness to interfering species. This work paves the way towards the first generation of low-cost, ultra-low volume, on-chip sensors for in-situ tracking of dopamine.

Notes

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Graduation Date

2022

Semester

Fall

Advisor

Chanda, Debashis

Degree

Master of Science (M.S.)

College

College of Graduate Studies

Department

Nanoscience Technology Center

Degree Program

Nanotechnology

Format

application/pdf

Identifier

CFE0009374; DP0027097

URL

https://purls.library.ucf.edu/go/DP0027097

Language

English

Release Date

12-15-2023

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Open Access)

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