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New sensors could lead to earlier lymphoma diagnosis

MedicalXpress Breaking News-and-Events Sep 24, 2019

CNBP researchers have developed a new method of detecting multiple cytokines—the body's messenger proteins—in very small volume samples, which could lead to earlier diagnosis of diseases such as lymphoma.

The work was published in a paper in the journal ACS Sensors.

"It could open the door to non-invasive diagnosis at early stage, as well as clinical applications such as monitoring treatments," says Dr. Lianmei Jang, one of the authors of the study and a biomedical engineer based at Macquarie University in Sydney.

Cytokines are a key part of the immune system which swing into action in the event of disease or injury.

That has made them a longstanding target by researchers keen to get a better understanding of how the body responds to infection.

It has always been a challenge, however, to simultaneously detect multiple cytokines in a single sample and this imposes significant limits on research.

Various cytokines perform different functions and can trigger other cytokines to realist in a complex network speaking a complex "language."

"When you look at just one type of cytokine it is very difficult to tell what is going on between the cells," Lianmei says. "If we can get to look at multiple cytokines we can understand better what is happening in the complex networks."

And being able to detect the cytokines in such low concentration—as low as 5 picograms per milliliter—allows for diagnosis at a very early stage, she says.

Lianmei, working with Dr. Yuling Wang's team (AI of CNBP) developed the alternative detection approach using gold nanoparticles with surface-enhanced Raman spectroscopy (SERS) nanotags to target the cytokines used as biomarkers for lymphoma.

Raman spectroscopy is widely used in chemistry to identify certain molecules. In this case the Raman readers on the nanoparticles picked up the signals from the cytokines.

"The sensitivity of this technique that allows it to work in such low concentrations is down to the SERS nanoparticles," says Lianmei.

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