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Michigan State University

Identifying patients most at risk from COVID-19

Morteza Mahmoudi

Identifying patients most at risk from COVID-19

What if doctors could not only diagnose a COVID-19 infection, but identify which patients are at the greatest risk of death before any major complications arise? One Michigan State University scientist believes nanotechnology may be the answer.

In a new paper, Morteza Mahmoudi, assistant professor in the Department of Radiology, Precision Health Program at MSU’s College of Human Medicine, proposed a point-of-care diagnostic platform that uses either nanoparticles or magnetic levitation to diagnose infection and assess future risk.

“Such technology would not only be useful in protecting health care centers from becoming overwhelmed,“ Mahmoudi said,

“but could also prevent severe shortages of health care resources, minimize death rates and improve management of future epidemics and pandemics.” The concept is based on the varying levels of infection and stages of disease which alter the composition of biological fluids such as tears, saliva, urine and plasma. Different infections and diseases create different patterns specific to the viral load and disease stage, somewhat akin to a fingerprint. Mahmoudi said that being able to identify and catalog those patterns would be key to any breakthrough in diagnostic technology. To begin, a patient’s biological fluid is introduced to a small collection of nanoparticles less than one-thousandth the diameter of a human hair. The unique surface of the particle collects proteins, lipids and other molecules from the fluids in a pattern that Mahmoudi refers to as a biomolecular corona, or crown. “By analyzing the composition of the crowns at the surface of tiny particles together with statistical approaches, the platform may provide a ‘fingerprint’ pattern for patients who may be at a death risk after being infected by COVID-19,”  Mahmoudi said.

This paper, Emerging Nanotechnologies to Assess Risk of Mortality from COVID-19 Infection, appears in Molecular Pharmaceutics.

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Contributing Writer(s): Adrian de Novato

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