Researchers Develop Quantum Dot Smartphone to Diagnose and Track COVID-19



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Researchers Develop Quantum Dot Smartphone to Diagnose and Track COVID-19

Credit: University of Toronto

Researchers from the Donnelly Center in collaboration with the Sunnybrook Health Sciences Center, Public Health Ontario and Mt. Sinai Hospital have designed a diagnostic test that uses a smartphone camera to monitor and track COVID-19 patients.

This finding could dramatically improve the turnaround time and efficiency of infectious disease diagnostics, both for COVID-19 and beyond. The research is published in the latest issue of Nano letters.

“The aim of the study is to make COVID-19 antibody testing more accessible. Said Johnny Zhang, a Ph.D. candidate at the Institute of Biomedical Engineering and the Department of Chemistry, and one of the co-first authors of this publication. “The end result is that patients can self-diagnose for COVID-19 with their phones, and the data can be immediately viewed digitally by healthcare professionals. “

In a traditional infectious disease diagnostic testing workflow, the clinical sample is obtained from the patient, sent to a laboratory for diagnostic testing, and the result is distributed to clinical staff for decision making. These processes are often detached in operation and have a long lead time.

The researchers designed quantum dot barcode microbeads and a secondary marker to test for antibodies to the COVID-19 antigen in the patient’s blood. The discovery of the antibodies leads to a change in the emission color of the microbeads.

The beads are then loaded into the device, “activated” with a laser, and the signal is imaged using a smartphone camera. An application is designed to process the image to identify the change in emission of the ball. Finally, data is interpreted and transmitted remotely across the world for data collection and decision making.

“The beauty of the system is that everything is integrated into a portable unit.” Zhang said.

This technology, whereby quantum dot microbead detection can measure minute amounts of key biomarkers in the blood, has been in development for 10 years.

“We really wanted to improve the performance and usefulness of the technology this time around,” said Ayden Malekjahani (BME PhD candidate), the other co-first author of this study.

“Being able to detect target traces in patients is not enough. We wanted to add more functions to the device. We have designed the device to simultaneously detect multiple antibodies from different types of samples, so each test is rich in information. then uploaded to an online dashboard where healthcare professionals and the public can see trends in real time. “

The researchers tested this device with forty-nine blood samples from patients with varying degrees of COVID-19 infection, and were able to achieve a sensitivity of 84 to 88%. While this result is not as high as traditional tests, it is still about three times higher than lateral flow tests, which are currently the most commonly available portable antibody tests.

This result also means that detection of COVID-19 antibodies can now be performed outside of centralized facilities without a great drop in accuracy.

This research was a collaboration with Public Health Ontario, Sunnybrook Hospital and Mount Sinai Hospital, where clinical samples were provided to researchers to test and evaluate this new system.

“This device can be a game-changer in the way we monitor the spread of infectious diseases and a patient’s response to vaccines.” said Warren Chan, director of the Institute of Biomedical Engineering and the Donnelly Center researcher who led the research.


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More information:
Yuwei Zhang et al, Monitoring and Tracking COVID-19 Patients Using a Quantum Dot Wearable Smartphone, Nano letters (2021). DOI: 10.1021 / acs.nanolett.1c01280

Provided by the University of Toronto

Quote: Researchers are developing a quantum dot smartphone to diagnose and track COVID-19 (2021, July 1) retrieved July 1, 2021 from https://phys.org/news/2021-07-quantum-dot-smartphone-device -track.html

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