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Genomic response, bioinformatics, and mechanics of the effects of forces on tissues and wound healing

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dc.contributor.advisor Isaac Kohane. en_US
dc.contributor.author Saxena, Vishal, 1971- en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US
dc.date.accessioned 2006-03-29T18:40:27Z
dc.date.available 2006-03-29T18:40:27Z
dc.date.copyright 2005 en_US
dc.date.issued 2005 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/32391
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005. en_US
dc.description Includes bibliographical references (leaves 162-167). en_US
dc.description.abstract The mechanical environment of the cell is important for changes in behavior. Cellular behavioral changes can be traced to gene expression profile changes. These effects were studied in the context of Micromechanical force therapy, a novel therapeutic treatment in the management of different types of wounds. The mechanism of therapies that work by applying suction pressures is still not completely understood. It is proposed that micromechanical forces are the dominant mechanism by which they obtain accelerated wound healing. However, these therapies don't only impose forces to (wounded) tissue. They also remove edematous tissue as well as applies hypobaric oxygen conditions to the tissue. Therefore, it was decided first to study only the effects of pure forces on normal tissue. 50g forces were applied to rat ears in vivo. The ears were then sampled over a period of time for their gene expression profiles on Affymetrix RAE 230 2.0 gene chips. 8 time points were obtained for each of control and stretch conditions. One rat ear was chosen to be control (and without stretch), the other was stretched. A modified Gene set enrichment analysis (GSEA) on the expression profiles was conducted using the paired difference t statistic squared as the ranking metric. A further refinement which didn't use the sign of the t statistic looked at expression changes in either direction (the combined analysis). Important genesets were obtained relevant to the differences seen between control and stretch conditions. In the combined GSEA analysis, hypoxia came to the top of the gene set list followed by 'response to mechanical stimulus'. To test the significance of this result, a permutation test was conducted on the dataset. en_US
dc.description.abstract (cont.) By shuffling the class (control versus stretch) labels randomly, different permutations were created and the GSEA was run to see if the occurrence was a chance event. The P values obtained were 0.001 and 0.014 showing that both were significant because they were not enriched randomly. The hypoxia geneset could be an important modulator of forces in wound healing. Future work will test in a biological model the validity of the importance of hypoxia in this system. en_US
dc.description.statementofresponsibility by Vishal Saxena. en_US
dc.format.extent 167 leaves en_US
dc.format.extent 8967520 bytes
dc.format.extent 8977203 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Mechanical Engineering. en_US
dc.title Genomic response, bioinformatics, and mechanics of the effects of forces on tissues and wound healing en_US
dc.type Thesis en_US
dc.description.degree Ph.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US
dc.identifier.oclc 61661275 en_US


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