UCF researchers develop optical sensor for dopamine detection

The plasmonic sensor utilises a gold pattern that causes electrons to create waves known as plasmons.

Archana Rani September 06 2024

Researchers at the University of Central Florida (UCF) in the US have developed an integrated optical sensor for dopamine detection directly from unprocessed blood samples.

Designed by the team at UCF NanoScience Technology Center, the low-cost sensor is intended for the diagnosis and monitoring of various neurological disorders and certain cancers.

The team was led by UCF NanoScience Technology Center professor Debashis Chanda.

UCF’s plasmonic sensor utilises a gold pattern that causes electrons to create waves known as plasmons.

These waves intensify with a special optical setup and can be altered by the presence of new molecules, such as dopamine, which in turn affects light reflection and enables detection.

Chanda said: “This plasmonic biosensor is extremely sensitive to low concentrations of biomolecules, which makes them a promising platform for specialised assays, point of care applications in remote locations.

“In this work, we demonstrated an all-optical, surface-functionalized plasmonic biosensing platform for the detection of low concentrations of neurotransmitter dopamine directly from diverse biological samples which includes protein solutions, artificial cerebrospinal fluid, and unprocessed whole blood.”

The sensor employs a synthetic DNA strand, or aptamer, to identify dopamine, bypassing the need for biological elements like antibodies or enzymes.

This not only reduces costs and simplifies storage but also allows for direct dopamine detection from blood without prior processing.

The aptamer-coated sensor targets specific molecules with high precision, demonstrating the potential of plasmonic "aptasensors" in developing diagnostic tools for monitoring diseases and medical diagnostics.

In 2021, UCF researchers developed a device to identify viruses such as Covid-19 in the human body as quickly as rapid detection tests.

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