Deep Learning-Assisted Nanocavity Sensor for Amphiphilic Biomarker Analysis.

Journal: Analytical chemistry
Published Date: Jul 1, 2025

Abstract

Fluorescence enhancement using nanocavity structures is a promising approach for rapid detection of amphiphilic biomarkers, which are essential for diagnosing diseases such as cancer and infections. This paper presents the use of a silver nanocube (AgNC)-gold mirror nanocavity integrated with a support lipid bilayer (SLB) for enhanced fluorescence detection. The SLB ensures optimal spacing, minimizing quenching and enhancing the fluorescence signal of amphiphilic biomarkers. A microfluidic platform allows precise and reproducible control of the detection environment, and the fluorescence enhancement factor is calculated using a deep learning-based semantic segmentation approach. This method achieves exceptional sensitivity, with the maximum enhancement factor reaching 868.64, detecting biomarkers down to the femtomolar level, demonstrating the platform's potential for clinical diagnostics. The nanocavity system combines high sensitivity, rapid detection, and low-cost preparation, making it an effective tool for advancing biological sensing applications in healthcare.

Authors

  • Bowen Fu
    Department of Automation, Tsinghua University, Main building, Haidian District, Beijing 100084, People's Republic of China.
  • Zhiyi Yuan
    School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
  • Dong Yang
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology Xi'an 710021 China yangdong@sust.edu.cn.
  • Zhongshu Xiong
    School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
  • Guocheng Fang
    School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
  • Tian Zhou
    Jingtai Technology Co. Ltd Floor 4, No. 9, Yifenghua Industrial Zone, 91 Huaning Road, Longhua District Shenzhen Guangdong Province 518109 China.
  • Xiyu Sun
    School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
  • Ningyuan Nie
    School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
  • Yu-Cheng Chen

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