{"id":{"repo_id":"gatech","oai_identifier":"oai:repository.gatech.edu:1853/61657"},"canonical_url":"https://search.dev.ndltd.org/etd/gatech/oai:repository.gatech.edu:1853/61657","repository":{"repo_id":"gatech","name":"Georgia Tech","base_url":"https://repository.gatech.edu/server/oai/request"},"display":{"title":"3D material cytometry (3DMaC): High-throughput, high replicate screening of materials using flow cytometry","abstract":"Biomaterials have become a common feature in everyday life ranging from disposable daily contact lenses to implanted devices engineered to outlast the patient. There is a great deal of unrealized commercial potential for biomaterials systems and ample interest in determining optimal biomaterials for applications such as tissue engineering (TE) and detection of biological analytes. Unlike past challenges in polymer selection, candidate biomaterials need to be tested while also accounting for the complexity of living cells and the variability in biological systems. These challenges can be partially addressed by analyzing a large number of biomaterials in a high-throughput manner with high replicate number; however, such methods are lacking. This thesis shows how flow cytometry can be adapted to the study of biomaterials. Flow cytometry allows for the automated collection of a large number of unique events in a short time period and is already widely used for cell analyses. Here, biomaterial, specifically hydrogel, constructs are fabricated and a combination of shape-, size-, and fluorescence-barcoding (SSF) enables high-throughput, high replicate, highly multiplexed analyses using imaging flow cytometry. This dissertation illustrates how this new method, 3D Material Cytometry (3DMaC), can be applied to tissue engineering and analyte detection, and discusses how the method can be extended to additional biomaterial studies.","abstract_html":"Biomaterials have become a common feature in everyday life ranging from disposable daily contact lenses to implanted devices engineered to outlast the patient. There is a great deal of unrealized commercial potential for biomaterials systems and ample interest in determining optimal biomaterials for applications such as tissue engineering (TE) and detection of biological analytes. Unlike past challenges in polymer selection, candidate biomaterials need to be tested while also accounting for the complexity of living cells and the variability in biological systems. These challenges can be partially addressed by analyzing a large number of biomaterials in a high-throughput manner with high replicate number; however, such methods are lacking. This thesis shows how flow cytometry can be adapted to the study of biomaterials. Flow cytometry allows for the automated collection of a large number of unique events in a short time period and is already widely used for cell analyses. Here, biomaterial, specifically hydrogel, constructs are fabricated and a combination of shape-, size-, and fluorescence-barcoding (SSF) enables high-throughput, high replicate, highly multiplexed analyses using imaging flow cytometry. 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