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Published Online: 10 September 2009

Neural Network Analysis Identifies Scaffold Properties Necessary for In Vitro Chondrogenesis in Elastin-like Polypeptide Biopolymer Scaffolds

Publication: Tissue Engineering Part A
Volume 16, Issue Number 1

Abstract

The successful design of biomaterial scaffolds for articular cartilage tissue engineering requires an understanding of the impact of combinations of material formulation parameters on diverse and competing functional outcomes of biomaterial performance. This study sought to explore the use of a type of unsupervised artificial network, a self-organizing map, to identify relationships between scaffold formulation parameters (crosslink density, molecular weight, and concentration) and 11 such outcomes (including mechanical properties, matrix accumulation, metabolite usage and production, and histological appearance) for scaffolds formed from crosslinked elastin-like polypeptide (ELP) hydrogels. The artificial neural network recognized patterns in functional outcomes and provided a set of relationships between ELP formulation parameters and measured outcomes. Mapping resulted in the best mean separation amongst neurons for mechanical properties and pointed to crosslink density as the strongest predictor of most outcomes, followed by ELP concentration. The map also grouped formulations together that simultaneously resulted in the highest values for matrix production, greatest changes in metabolite consumption or production, and highest histological scores, indicating that the network was able to recognize patterns amongst diverse measurement outcomes. These results demonstrated the utility of artificial neural network tools for recognizing relationships in systems with competing parameters, toward the goal of optimizing and accelerating the design of biomaterial scaffolds for articular cartilage tissue engineering.

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Information

Published In

cover image Tissue Engineering Part A
Tissue Engineering Part A
Volume 16Issue Number 1January 2010
Pages: 11 - 20
PubMed: 19754250

History

Published in print: January 2010
Published ahead of print: 15 September 2009
Published online: 10 September 2009
Published ahead of production: 15 July 2009
Accepted: 14 July 2009
Received: 26 February 2009

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Dana L. Nettles
Department of Biomedical Engineering, Duke University, Durham, North Carolina.
Mansoor A. Haider
Department of Mathematics, North Carolina State University, Raleigh, North Carolina.
Ashutosh Chilkoti
Department of Biomedical Engineering, Duke University, Durham, North Carolina.
Lori A. Setton
Department of Biomedical Engineering, Duke University, Durham, North Carolina.
Division of Orthopaedic Surgery, Department of Surgery, Duke University, Durham, North Carolina.

Notes

Address correspondence to:
Lori A. Setton, Ph.D.
Biomedical Engineering
136 Hudson Hall, Box 90281
Durham, NC 27708
E-mail: [email protected]

Disclosure Statement

No competing financial interests exist.

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