Date of Award
Open Access Thesis
College of Engineering and Computing
Cerebrovascular endothelial cells play a key part in the inflammatory response of the blood-brain barrier in pathological conditions such as Alzheimer’s disease. Specifically, the NF-κB signaling pathway plays a central role. Better understanding of the factors in inflammatory disease progression can lead to more effective treatments for such devastating illnesses like Alzheimer’s, asthma, arthritis, cancer, diabetes and many more inflammatory diseases. The proposed approach analyzes spatial NF-κB distribution contained in multispectral stacked micrograph images of cerebrovascular endothelial cells indexed based on dose of the activating protein and the length of activation. Image analysis code identifies the location of nuclear boundaries and quantifies NF-κB in relation to the closest nuclear boundary. This information is used to develop a mathematical model that describes the time and concentration dependence of NF-κB in response to the activating proteins. The proposed method allows for analysis and modeling of previously unexplored spatial behavior of NF-κB.
Catalfomo, K.(2016). Automated Image Analysis And Spatial Computational Modeling Of NF-kB In Cerebrovascular Endothelial Cells. (Master's thesis). Retrieved from https://scholarcommons.sc.edu/etd/3761