Nano-multilayer structures open up new possibilities for disease detection

This method, loaded with light scattering dyes known as Raman reporters, is commonly used to detect biomarkers for disease in organic samples, and it can amplify and detect signals from different types of nanoprobes without the need for expensive machines or medical professionals to read the results

In a small proof-of-concept study, nanorattle accurately identified head and neck cancers through an AI-powered point-of-care device, which could revolutionize the way these and other diseases are detected in under-resourced settings, improving global health

The findings were published online Sept.

Duke University Biomedical Engineering R.

"Our team has developed a new type of probe with a precisely adjustable gap between the internal core and the housing, which allows us to load multiple types of Raman reporters and amplify their light emissions, called surface-enhanced Raman scattering," Vo-Dinh said

To make nano-cannonballs, the researchers started

The result is a nanosphere (or nanocube) about 60 nanometers wide with a structure similar to a rattle — a gold nucleus trapped in a larger silver-gold shell

These tight tolerances are essential to control the Raman signal enhancement produced by the nanorattle

When the laser hits the nano-shell, it passes through the extremely thin shell, hitting the Raman reporters inside, causing them to emit their own light

"Once we get the nanorobots working, we want to make biosensing devices that can detect infectious diseases or cancers before people even know they're sick," Vo-Dinh said

In the new paper, Voo-Dinh and his collaborators applied the nanorattle technique to a stick-on lab device capable of detecting head and neck cancers that occur anywhere between the shoulder and the brain, usually the mouth, nasal cavity and throat

Walter Lee, a professor of head and neck surgery, communications science, and radiation oncology at Duke University, said: "In low-resource settings, these cancers often occur in advanced stages with poor results, in part because of limited screening equipment, a lack of trained health care workers, and the large absence of screening programs

"The ability to detect these cancers early should lead to earlier treatment and improved outcomes, including survival and quality of life

The prototype device uses specific gene sequences, like the Velcro of the biomarkers the researchers are looking for — in this case, a specific type of mRNA

In the experiment, the test determined with 100% accuracy whether 20 samples were from head and neck cancer patients

"Many mRNA biomarkers are over-abundant in multiple types of cancer, while other biomarkers can be used to assess a patient's risk and future treatment outcomes," Vo-Dinh said

This study was supported
by the National Institutes of Health (R01-DE030455-01A1).

Journal Reference:

1. Joy Qiaoyi Li, Priya Vohra Dukes, Walter Lee, Michael Sarkis, Tuan Vo‐Dinh.
   Machine learning using convolutional neural networks for SERS analysis of biomarkers in medical diagnostics.
   Journal of Raman Spectroscopy, 2022; DOI: 10.
   1002/jrs.
   6447