High-throughput cell culture is an emerging technology that shows promise as a tool for research in tissue engineering, drug discovery, and medical diagnostics. An important, but overlooked, challenge is the integration of experimental methods with information processing suitable for handling large databases of cell-cell and cell-substrate interactions. In this work the traditional global descriptions of cell behaviors and surface characteristics was shown insufficient for investigating short-distance cell-to-cell and cell-to-surface interactions.
This problem was addressed by introducing individual-cell based local metrics that emphasize cell local environment. An individual-cell based local data analysis method was established. Contact inhibition of cell proliferation was used as a benchmark for the effectiveness of the local metrics and the method. Where global, summary metrics were unsuccessful, the local metrics successfully and quantitatively distinguished the contact inhibition effects of MC3T3-E1 cells on PLGA, PCL, and TCPS surfaces.
In order to test the new metrics and analysis method, a model of cell contact inhibition was proposed. Monte Carlo simulation was performed for validating the individual-cell based local data analysis method as well as the cell model itself. The simulation results well matched with the experimental observations. The parameters used in the cell model provided new descriptions of both cell behaviors and surface characteristics.
Based on the viewpoint of individual cells, the local metrics and local data analysis method were extended to the investigation of cell-surface interactions, and a new high-throughput screening and knowledge discovery method on combinatorial libraries, local cell-feature analysis, was developed. PLGA/PCL combinatorial libraries were used as a prototype and a shaper and holder phenomenon involving MC3T3-E1 cells interacting with PCL islands was discovered.
In summary, the viewpoint of individual cells casts new light on the study of cell-cell and cell-surface interactions and represents a novel methodology for developing new data analysis and knowledge discovery methods.
The results of contact inhibition study and the shaper and holder model provide new knowledge, while the local data analysis method as well as the cell model of contact inhibition suggested novel approaches to study cell-cell and cell-surface interactions.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/22648 |
| Date | 01 April 2008 |
| Creators | Su, Jing |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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