Nanozyme-Enabled Multimodal Sensing: Visual and Rapid Profiling of Extracellular Vesicles.

Journal: Analytical chemistry
Published Date: Jul 14, 2025

Abstract

CD20, a transmembrane protein on the surface of lymphoma extracellular vesicles (EVs), is highly expressed and serves as an effective marker for monitoring lymphoma subtypes and evaluating the efficacy of antibody therapy. Therefore, there is an urgent need for methods to effectively enrich and accurately detect CD20 on EVs. To address these challenges, immunoaffinity magnetic bead adsorption and nanozyme-enabled multimodal sensing have been identified as effective strategies. This study demonstrates that phosphate groups in the phospholipid bilayer of EVs complex with Ti on FeO@TiO magnetic beads, enabling their separation from complex samples by using an external magnetic field. The signal label CuCo-ZIF/Pt with good oxidase activity can oxidize -phenylenediamine (OPD) into 2,3-diaminophenazine (DAP) with colorimetric and fluorescence signals, and the intensity of the signal is proportional to the concentration of CD20. Utilizing the Residual Network 18 with Data Augmentation (Resnet18-DA) neural network model, the artificial intelligence (AI) visual perception platform is capable of rapidly distinguishing the concentration of CD20 through color response, achieving an accuracy rate of nearly 100%. This multimodal sensing platform not only enhances the accuracy and convenience of detection but also has the potential to provide new strategies for evaluating the effectiveness of personalized tumor treatment.

Authors

  • Xiao Wang
    Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
  • Jing-Yuan Ma
    State Key Laboratory of Digital Medical Engineering, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering & Basic Medicine Research and Innovation Center of Ministry of Education, Southeast University, Nanjing 211189, P. R. China.
  • Xiaoli Wei
    Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL, USA.
  • Tianxia Zhao
    State Key Laboratory of Digital Medical Engineering, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering & Basic Medicine Research and Innovation Center of Ministry of Education, Southeast University, Nanjing 211189, P. R. China.
  • Xiaoping Zhang
    China Academy of Chinese Medicine Sciences, Beijing, 100070, China.
  • Xue Wu
    School of Civil Engineering, Southeast University, Nanjing 210096, China.
  • Yefei Zhu
    Central Laboratory, The Second Affiliated Hospital of Nanjing Medical University, Nanjing 210011, P. R. China.
  • Zhirui Guo
    School of Microelectronics and Communication Engineering, Chongqing University, 174 ShaPingBa District, Chongqing, 400044, China.
  • Yali Jiang
    The Friendship Hospital of Ili Kazakh Autonomous Prefecture Ili & Jiangsu Joint Institute of Health, Yining 835000, P. R. China.
  • Haoan Wu
    State Key Laboratory of Digital Medical Engineering, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering & Basic Medicine Research and Innovation Center of Ministry of Education, Southeast University, Nanjing 211189, P. R. China.
  • Ming Ma
    Department of Radiation Oncology, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305-5847, USA.
  • Zheng Ge
    Department of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing 210009, P. R. China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.

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