Particle distribution dynamics in nonlinear bifurcating networks (BiNet)
Horizon Europe - ERC
2 000 000 EUR
University of Oulu
Unit and faculty
Faculty of Biochemistry and Molecular Medicine
- Professor of biosensorsCaglar Elbuken
Bifurcating networks are ubiquitous in nature such as vasculature/pulmonary networks, kidney urinary tract, and branching in plants. In addition to their role of transporting the carrying fluid, these networks distribute discrete particles suspended in the fluid leading to intricate spatiotemporal particle flow dynamics. The heterogenous distribution of red blood cells (RBC) in microcirculation is an example of this behaviour, consequences of which are not well-understood.
Our objective is to explain the fundamental principles and implications of nonuniform particle distributions in bifurcating networks using RBC flow in vasculature as a model system. Currently there is no systematic approach to study such complex particle distribution dynamics. We propose using droplet microfluidic as an analogue of the biological network. Microfluidics provide superb control of the droplets/particles, carrying fluid and network properties in highly engineered microfabricated devices. We aim to understand RBC distribution patterns in capillary network and the consequences during vascularization and organogenesis. Our approach is (i) to observe the in vivo RBC fractionation in chick embryo vasculature, (ii) to develop its in vitro analogue using droplet microfluidics, (iii) to develop in silico model and determine the governing parameters.
This project will discover the foundations of particle transport phenomena in nonlinear bifurcating networks and address the long-lasting question of RBC nonuniformity in microcirculation and its implications as a groundbreaking contribution. Another key outcome will be correlating RBC heterogeneity to corresponding organ growth by visualising two bifurcating networks simultaneously: vasculature and urinary tree, using kidney organoid xenotransplantation. The project will advance (i) the fundamental understanding of particle distribution in nonlinear bifurcating networks and (ii) the research in vascularization and artificial kidney development.