Highly Adsorptive Au-TiO(2) Nanocomposites for the SERS Face Mask Allow the Machine-Learning-Based Quantitative Assay of SARS-CoV-2 in Artificial Breath Aerosols

用于SERS口罩的高吸附性Au-TiO(2)纳米复合材料可实现基于机器学习的人工呼吸气溶胶中SARS-CoV-2的定量检测

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Abstract

Human respiratory aerosols contain diverse potential biomarkers for early disease diagnosis. Here, we report the direct and label-free detection of SARS-CoV-2 in respiratory aerosols using a highly adsorptive Au-TiO(2) nanocomposite SERS face mask and an ablation-assisted autoencoder. The Au-TiO(2) SERS face mask continuously preconcentrates and efficiently captures the oronasal aerosols, which substantially enhances the SERS signal intensities by 47% compared to simple Au nanoislands. The ultrasensitive Au-TiO(2) nanocomposites also demonstrate the successful detection of SARS-CoV-2 spike proteins in artificial respiratory aerosols at a 100 pM concentration level. The deep learning-based autoencoder, followed by the partial ablation of nondiscriminant SERS features of spike proteins, allows a quantitative assay of the 10(1)-10(4) pfu/mL SARS-CoV-2 lysates (comparable to 19-29 PCR cyclic threshold from COVID-19 patients) in aerosols with an accuracy of over 98%. The Au-TiO(2) SERS face mask provides a platform for breath biopsy for the detection of various biomarkers in respiratory aerosols.

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