Abstract: The generation of thrombin by preassembled prothrombinase on phospholipid coated capillaries was studied under laminar flow at physiologic shear rates (100–1000 sec−1). When prothrombin (1.4μM) was perfused, thrombin levels reached a steady-state that decreased with increasing shear rate; however, generation was independent of shear rate when corrected for the velocity of the effluent. The ratio of α-thrombin to meizothrombin formed was 3:2 at shear rates of 250 and 500 sec−1. Kinetic constants determined at a shear rate of 250 sec−1 were in agreement with those obtained in closed systems, suggesting that the exchange between the bulk solution and the capillary wall region is limited by the competition between molecular diffusion of thrombin and flow convection. This results in the development of a diffusive boundary layer that spatially confines thrombin, yielding predicted concentrations of up to 1μM. The observation of extensive thrombin feedback cleavage of the phospholipid binding domain from prothrombin and meizothrombin is consistent with such high concentrations of thrombin. A flow transport model is presented for thrombin generation that estimates the development of the thrombin layer. Supported by NIH HL46703 and 5T32HL007594.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).