Structural Adaptation of Microvascular Networks To Mechanical Stimuli
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The objective of this research project is to develop and test a mathematical model of the microvasculature that includes adaptive rules characterizing how individual vessels respond to regional blood pressures and flows. The radii of microvessels determine blood pressure and blood flow. In turn, via the process of vascular adaptation, blood pressure and flow determine microvessel radii. This adaptive process is inherently complex, because each vessel responds to local mechanical stimuli, and yet all the microvessels in a network appear to adapt their radii in a coordinated manner to ensure blood supply matches tissue demand. The central hypothesis of this project is that the conventional assumptions of "set points" that predetermine equilibrium conditions are not necessary to accurately predict measured changes in vessel radii. This work will characterize the structure of intact microvascular networks in an animal model, construct a mathematical model based on fundamental principles, and test the predicted responses of the system to vascular occlusion. This work challenges the current understanding of the mechanisms that determine microvascular architecture. It builds upon established mathematical models, uses a unique animal model that allows noninvasive measurements, and is performed by participants of a large-scale multilevel research program based on a Research-Intensive Community model. Taken together, this work promises to extend the current understanding of how relatively simple adaptive rules lead to a coordinated response in the microvasculature. The Research Intensive Community model partners multidisciplinary teams of undergraduates, who want exposure to authentic scientific research, with graduate student mentors, who want exposure to authentic research management experience. This novel model radically increases the number of undergraduates participating in original research experiences, provides an environment conducive to recruiting underrepresented students to science and engineering careers, prepares graduate students to be leaders by providing opportunities to lead diverse multidisciplinary research teams, and efficiently implements the concepts of peer-teaching, interdisciplinary education, team-based problem solving, and learning communities.