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A service for global professionals · Thursday, January 9, 2025 · 775,454,461 Articles · 3+ Million Readers

Paper-based sensors may lead to rapid detection of heart attacks

When individuals experience acute myocardial infarction, also known as a heart attack, time is precious. Detection and diagnosis of a heart attack have typically required expensive laboratory equipment and quick access to advanced medical facilities. Now, researchers at the U.S. National Science Foundation Precise Advanced Technologies and Health Systems for Underserved Populations (NSF PATHS-UP) Engineering Research Center have developed a paper-based test which measures cardiac troponin I (cTnI), one of the biomarkers of a heart attack, in just 15 minutes, making testing less expensive and more readily available.

"We are excited to introduce this low-cost, portable solution that bridges the gap between central laboratory diagnostics and point-of-care testing," said Aydogan Ozcan, the Volgenau Chair for Engineering Innovation at UCLA who is part of the NSF PATHS-UP executive committee. "Our paper-based platform, powered by deep learning, offers an effective alternative to the bulky, expensive instruments currently used in hospitals. It holds the promise of bringing advanced cardiac diagnostics to underserved populations globally."

In research recently published in ACS Nano, the team demonstrated the use of a deep learning-enhanced, paper-based vertical flow assay capable of detecting cTnI with high sensitivity. These paper-based tests are both cost-effective and highly portable, costing only $4 per test and only $170 for the portable reader, which is designed using a Raspberry Pi computer and off-the-shelf components. The team anticipates that these sensing technologies will transition into commercial applications through licensing and/or spin-off efforts.

In experimental tests using small amounts of serum and whole blood, researchers have been able to benchmark the paper-based tests against current point-of-care devices and found that they not only meet the clinical requirements for testing but even surpass them in terms of sensitivity. Broadening access to this kind of diagnostic testing can improve health outcomes globally, reducing deaths due to cardiovascular diseases, which number 19 million fatalities worldwide. In particular, underserved populations that may not have access to medical facilities or testing in the limited window of cardiac event interventions would benefit from these highly sensitive rapid tests.

"The PATHS-UP researchers have achieved a highly effective solution by leveraging a paper-based platform to minimize costs and incorporating machine learning to enhance diagnostic accuracy," said Lan Wang, program director for the NSF Division of Engineering Education and Centers. "Moreover, the PATHS-UP Engineering Research Center trains diverse scientists and engineers to develop enabling technologies, like this one, aimed at improving health outcomes in communities with low access to medical care."

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