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Biomimetic block copolymer particles with gated nanopores and ultrahigh protein sorption capacity

Overview of attention for article published in Nature Communications, June 2014
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Title
Biomimetic block copolymer particles with gated nanopores and ultrahigh protein sorption capacity
Published in
Nature Communications, June 2014
DOI 10.1038/ncomms5110
Pubmed ID
Authors

Haizhou Yu, Xiaoyan Qiu, Suzana P. Nunes, Klaus-Viktor Peinemann

Abstract

The design of micro- or nanoparticles that can encapsulate sensitive molecules such as drugs, hormones, proteins or peptides is of increasing importance for applications in biotechnology and medicine. Examples are micelles, liposomes and vesicles. The tiny and, in most cases, hollow spheres are used as vehicles for transport and controlled administration of pharmaceutical drugs or nutrients. Here we report a simple strategy to fabricate microspheres by block copolymer self-assembly. The microsphere particles have monodispersed nanopores that can act as pH-responsive gates. They contain a highly porous internal structure, which is analogous to the Schwarz P structure. The internal porosity of the particles contributes to their high sorption capacity and sustained release behaviour. We successfully separated similarly sized proteins using these particles. The ease of particle fabrication by macrophase separation and self-assembly, and the robustness of the particles makes them ideal for sorption, separation, transport and sustained delivery of pharmaceutical substances.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 94 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 34%
Researcher 14 15%
Student > Master 14 15%
Student > Bachelor 6 6%
Student > Doctoral Student 4 4%
Other 8 8%
Unknown 17 18%
Readers by discipline Count As %
Chemistry 32 34%
Materials Science 12 13%
Engineering 10 11%
Chemical Engineering 7 7%
Environmental Science 5 5%
Other 8 8%
Unknown 21 22%