Issue 7, 2012
From the journal:

Journal of Materials Chemistry

Self-assembled chitin nanofiber templates for artificial neural networks†

Ashleigh Cooper,a   Chao Zhong,a   Yoshito Kinoshita,b   Richard S. Morrison,b   Marco Rolandia  and  Miqin Zhang*a  

* Corresponding authors

a Department of Materials Science and Engineering, University of Washington, 302L Roberts Hall, Seattle, WA, USA
E-mail: mzhang@uw.edu
Fax: +1 206-543-3100
Tel: +1 206-616-9356

b Department of Neurological Surgery, University of Washington, 1959 NE Pacific Street, Seattle, WA, USA

Abstract

Self-assembled chitin nanofibers were applied as a biomimetic extracellular matrix for the attachment of primary neuronsin vitro. Chitin nanofiber surfaces were deacetylated to form 4 nm and 12 nm diameter chitosan nanofibers that were coupled with poly-D-lysine (PDL) to examine combinatory effects and structurally analyzed by atomic force microscopy. The chitosan substrates were then employed for mouse cortical neuron cultures to examine their capabilities to support cell attachment, neurite coverage and survival. The 4 nm chitosan nanofibers improved single cortical neuron attachment compared to the 12 nm chitosan fibers and bare glass substrates, illustrating the improved adhesive properties of the surface. Importantly, the 4 nm chitosan nanofibers with PDL supported 37.9% neuron viability compared to only 13.5% on traditional PDL surfaces after a 7-day culture period, illustrating significantly improved long-term cell viability. The nanofibrillar chitosan surface could provide an alternative substrate for in vitroprimary neuron cultures to serve as artificial neural networks for diagnostics and therapeutics.

Graphical abstract: Self-assembled chitin nanofiber templates for artificial neural networks

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Article information

DOI
https://doi.org/10.1039/C2JM15487K
Article type
Paper
Submitted
27 Oct 2011
Accepted
05 Dec 2011
First published
05 Jan 2012

J. Mater. Chem., 2012,22, 3105-3109

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Self-assembled chitin nanofiber templates for artificial neural networks

A. Cooper, C. Zhong, Y. Kinoshita, R. S. Morrison, M. Rolandi and M. Zhang, J. Mater. Chem., 2012, 22, 3105 DOI: 10.1039/C2JM15487K

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