Related Experiment Video
Updated: Sep 15, 2025
Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
Published on: March 17, 2023
Nanozyme-Enabled Multimodal Sensing: Visual and Rapid Profiling of Extracellular Vesicles
Xiao Wang1, Jing-Yuan Ma1, Xiaoli Wei1
1State 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.
This study presents a novel method for detecting CD20 on lymphoma extracellular vesicles (EVs) using magnetic beads and nanozymes. The developed platform achieves nearly 100% accuracy for monitoring lymphoma and evaluating treatment effectiveness.
Area of Science:
- Biomedical Engineering
- Analytical Chemistry
- Nanotechnology
Background:
- CD20 is a key marker on lymphoma extracellular vesicles (EVs), crucial for monitoring disease and treatment efficacy.
- Existing methods for CD20 detection on EVs face challenges in enrichment and accurate quantification.
- There is a need for sensitive and reliable platforms for CD20 detection in complex biological samples.
Purpose of the Study:
- To develop an efficient method for enriching and detecting CD20 on lymphoma EVs.
- To create a multimodal sensing platform combining immunoaffinity capture and nanozyme-based detection.
- To leverage artificial intelligence for rapid and accurate CD20 concentration determination.
Main Methods:
- EVs were captured using Fe3O4@TiO2 magnetic beads via phosphate-Ti4+ complexation.
- A nanozyme (CuCo-ZIF/Pt) was employed for signal amplification, producing colorimetric and fluorescent outputs.
- The Resnet18-DA neural network model was integrated for AI-driven visual perception and quantification.
Main Results:
- The magnetic beads effectively separated EVs from complex samples.
- The nanozyme-based system generated signals proportional to CD20 concentration.
- The AI platform achieved nearly 100% accuracy in distinguishing CD20 concentrations via color response.
Conclusions:
- The developed multimodal sensing platform offers enhanced accuracy and convenience for CD20 detection on EVs.
- This approach provides a promising tool for personalized tumor treatment evaluation.
- The study highlights the potential of integrating nanotechnology, immunoaffinity, and AI for advanced diagnostics.
