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Human urine sensing and deep learning-assisted cancer screening

Elsevier

Biosensors and Bioelectronics

Abstract

Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples, providing insights for disease diagnosis and finding of new biomarkers. Here, we introduce a label-free surface-enhanced Raman scattering sensor based on a three-dimensional plasmonic coral nanoarchitecture (3D-PCN), which has strong electromagnetic field enhancement through multiple hot spots. The 3D-PCN was synthesized on a paper substrate via direct one-step gold reduction, forming a coral-like nanoarchitecture with high absorption property for biofluids. This was fabricated as a urine test strip and then integrated with a handheld Raman system to develop an on-site urine diagnostic platform. The developed platform successfully classified the human prostate and pancreatic cancer urines in a label-free method supported by two types of deep learning networks, with high clinical sensitivity and specificity. Our technology has the potential to be utilized not only for urinary cancer diagnosis but also for various human biofluid sensing systems as a future point-of-care testing platform.

Keywords

Plasmonic materials

Nanoarchitecture

Urine sensor

Cancer diagnosis

On-site detection

Data availability

Data will be made available on request.

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© 2023 Published by Elsevier B.V.

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By |2023-02-17T23:19:04+00:00February 17th, 2023|Education|0 Comments

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