Impact of Curvature-Induced Secondary Flows on Mechanotransduction and Cell Biochemical Signaling in 3D Bioprinted Artery Models with Physiological Inflow

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Heart disease is the leading cause of death for men and women in the United States and throughout the world. In addition to the detrimental effects on human health and loss of life, the economic impact of cardiovascular diseases is tens of billions of dollars annually in the US. Diseases associated with plaque formation, such as atherosclerosis, are triggered by the biochemical signals expressed by the arterial lining cells in direct contact with the blood, the endothelial cells. It is known that the endothelial cells transmit biochemical signals to adjacent smooth muscle cell layers that control the properties of the arteries, such as their stiffness and cross-sectional area through which the blood flows. These biochemical signals are, in part, the response of the cells to the mechanical forces that they see as the blood flows past. The objective of this project is to study how these cells respond to complex flows, such as those that occur in various parts of the vasculature (e.g. regions of curvature, constrictions, branching). This project will produce novel, 3D bioprinted blood vessel models with endothelial cells based on actual physiological arteries. These realistic bioreactors will then be subjected to blood flow that mimics the natural physiology. This study will improve the understanding of the interactions of blood flow and arterial lining cells under realistic conditions. This advancement in understanding may eventually translate to research to address the onset and progression of vascular diseases. The project also supports substantial outreach to enhance the participation of underrepresented students in STEM fields.This project includes a combination of experimental and computational modeling along with the development of realistic bioreactors for the assessment of endothelial response. Vascular structures are complex, and the combination of external and internal geometry, including curvature, tortuosity, and stenoses, leads to flow fields that are variable in both space and time. In the first aim, the research will use state-of-the-art, non-invasive laser-based techniques, such as Particle Image Velocimetry, to measure the entire flow field in patient-specific vascular geometries. This will be combined with the assessment of wall shear stress distributions determined from computational simulations. These realistic geometries will create the complex physiological and pathophysiological flows, including secondary flows and stenosis-induced flow separations, that are seen in natural vascular structures. In aim 2, the patient-specific geometries will be replicated through 3D bioprinted structures that include endothelial cells. These realistic bioreactors will be used to measure cellular biochemical signaling within these vessels under different flow conditions through cell staining, immunofluorescence imaging, and gene analysis. By integrating these two approaches from different disciplines, the project will be able to examine the cause and effect between the complex blood flow and the resulting cell response.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.