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May 29, 2026Journal of the American Chemical Society

Label-Free Imaging of Single Proteins and Binding Dynamics via Deep Learning-Enhanced Plasmonic Scattering Microscopy

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Authors

JZJingbo ZhangJXJ Q XuYCYuehua Chen

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Overview

Randomized trial demonstrates label-free imaging of single proteins in complex environments, suggesting enhanced biosensing capabilities.

Key Points

  • This research aims to improve label-free imaging of single proteins and their binding dynamics using deep learning techniques.
  • Integrated plasmonic scattering microscopy with a deep learning framework for protein tracking.
  • Utilized a recurrent neural network to isolate and track unlabeled proteins.
  • Conducted analysis on the binding thermodynamics and residence times of proteins.
  • Achieved high-throughput label-free tracking of single proteins in complex backgrounds.
  • Resolved nanoscale protein motions and quantified binding thermodynamics.
  • Successfully distinguished between specific and nonspecific interactions with measurable metrics.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a192c67fab5b468c4415494https://doi.org/10.1021/jacs.6c04749
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