Combinatorial techniques, which overcome limitations of actual models of material research permitting to effectively address this large amount of variables, are utilized in this work to prepare combinatorial libraries of the blend of the biodegradable polymers Poly(e-caprolactone) and Poly(lactic acid). These libraries present continuous composition and temperature gradients in an orthogonal fashion that permit to obtain multiple surface morphologies with controllable microstructures due to the blends low critical solution phase behavior (LCST).
The goal of this study is to investigate the effect of surface morphology (surface chemical patterning and surface topography) on cell behavior. The varied surface topography of the libraries is used as a valuable tool that permits to assay the interaction between MC3T3-E1 cells and hundreds of different values of critical surface properties, namely, surface roughness and microstructure size. The outcome of this tool is a rapid screening of the effect of surface topography on cell behavior that is orders of magnitude faster than the standard 1-sample for 1 measurement techniques.
The results obtained show that cells are very sensitive to surface topography, and that the final effect of surface properties on cell function is intimately related with the stage of the cell developmental process. Meaning that, for example, areas with optimal characteristics to elicit enhancement of cell attachment is not necessarily the same that promotes cell proliferation.
This study imparts an improved understanding of an often neglected factor in biomaterials performance: surface morphology (particularly surface topography). The results provide a new insight into the importance of taking into consideration both chemistry and physical surface features for superior biomaterial design.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7265 |
Date | 12 July 2004 |
Creators | Zapata, Pedro JoseĢ |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Thesis |
Format | 7105300 bytes, application/pdf |
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