In this proposal, I will 1) develop image processing tools to quantify the spatial organization of coronary vessels and cardiac cells in the embryo then 2) quantify changes in coronary patterns and surrounding cells organization due to alcohol, and test a rescue compound (glutathione) in a mouse model of prenatal alcohol exposure. Our lab has developed an optical clearing and fluorescent dye perfusion technique that enables us to visualize the coronary microvasculature throughout the entire developing heart using confocal microscopy. I will create analysis algorithms to extract quantitative information from these large three-dimensional images to better understand coronary and cardiac cell patterning. More specifically, I will automatically segment the blood vessels and calculate their 3D orientation, I will use deep learning to automatically identify cell type based on nucleus morphology, and I will use spatial statistics to analyze the distribution of each cell type and correlate their position to the microvasculature. To test these newly developed analytical tools, I will apply them to a mouse model of prenatal alcohol exposure (PAE). Our lab has demonstrated that PAE disrupts microvasculature organization and alignment in the embryonic heart, and I will quantify such effects using the tools I will develop. Our lab has also tested glutathione as a rescue compound to reduce the impact of alcohol on the developing heart. In preliminary studies in quails, glutathione improved survival and reduced the rates of congenital heart defects. However, its effect on coronary microvasculature and cardiac cell patterning was not evaluated. I will test my hypothesis that glutathione will normalize coronary patterns and patterning of the other cardiac cell types, which will correlate with reduced mortality and fewer congenital heart defects in the embryos.
|Program type||Postdoctoral Fellowship|
|Effective start/end date||01/01/2020 → 12/31/2021|