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Updated: Apr 28, 2026

Single-Molecule Diffusion and Assembly on Polymer-Crowded Lipid Membranes
Published on: July 19, 2022
Tailoring polymersome bilayer permeability improves enhanced permeability and retention effect for bioimaging
Mei-Hsiu Lai1, Sangmin Lee, Cartney E Smith
1Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Stabilizing self-assembled nanoparticles by decreasing bilayer permeability enhances their circulation time and improves tumor imaging in mice. This advancement offers better diagnostic capabilities and supports image-guided therapies.
Area of Science:
- Biomaterials Science
- Nanotechnology
- Medical Imaging
Background:
- Self-assembled nanoparticles are utilized for pathologic tissue imaging.
- Current nanoparticles disintegrate rapidly in circulation, limiting their efficacy.
- This instability hinders effective association with and imaging of target sites.
Purpose of the Study:
- To stabilize polymersomes by reducing bilayer permeability.
- To extend nanoparticle circulation lifetime for improved bioimaging.
- To enhance tumor detection and imaging quality in vivo.
Main Methods:
- Synthesized polymersomes from poly(2-hydroxyethyl-co-octadecyl aspartamide) with methacrylate groups.
- Decreased bilayer permeability via increased methacrylate packing density and chemical cross-linking.
- Evaluated particle stability in physiological media and tumor highlighting in mice using near-infrared (NIR) fluorescent probes.
Main Results:
- Polymersomes with decreased bilayer permeability exhibited enhanced particle stability.
- These stabilized polymersomes demonstrated improved tumor highlighting in mice over 2 days.
- Reduced bilayer permeability correlated with extended nanoparticle lifetime and superior imaging.
Conclusions:
- Decreasing polymersome bilayer permeability is an effective strategy for stabilizing nanoparticles.
- Enhanced nanoparticle stability improves in vivo bioimaging and tumor detection.
- This approach holds promise for advancing both diagnosis and image-guided therapies.
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