Physiology - Research Publications

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    Discrete network models of interacting nephrons
    The kidney is one of the major organs involved in whole-body homeostasis, and aexhibits many of the properties of a complex system. The functional unit of the kidney is the nephron, a complex, segmented tube into which blood plasma is filtered and its composition adjusted. Although the behaviour of individual nephrons can fluctuate widely and even chaotically, the behaviour of the kidney remains stable. In this paper, we investigate how the filtration rate of a multi-nephron system is affected by interactions between nephrons. We introduce a discrete-time multi-nephron network model. The tubular mechanisms that have the greatest effect on filtration rate are the transport of sodium and water, consequently our model attempts to capture these mechanisms. Multi-nephron systems also incorporate two competing coupling mechanisms-vascular and hemodynamic-that enforce in-phase and anti-phase synchronisations respectively. Using a two-nephron model, we demonstrate how changing the strength of the hemodynamic coupling mechanism and changing the arterial blood pressure have equivalent effects on the system. The same two-nephron system is then used to demonstrate the interactions that arise between the two coupling mechanisms. We conclude by arguing that our approach is scalable to large numbers of nephrons, based on the performance characteristics of the model.
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    A computational model for emergent dynamics in the kidney
    Moss, R ; Kazmierczak, E ; Kirley, M ; Harris, P (ROYAL SOC, 2009-06-13)
    In this paper, concepts from network automata are adapted and extended to model complex biological systems. Specifically, systems of nephrons, the operational units of the kidney, are modelled and the dynamics of such systems are explored. Nephron behaviour can fluctuate widely and, under certain conditions, become chaotic. However, the behaviour of the whole kidney remains remarkably stable and blood solute levels are maintained under a wide range of conditions even when many nephrons are damaged or lost. A network model is used to investigate the stability of systems of nephrons and interactions between nephrons. More sophisticated dynamics are explored including the observed oscillations in single nephron filtration rates and the development of stable ionic and osmotic gradients in the inner medulla which contribute to the countercurrent exchange mechanism. We have used the model to explore the effects of changes in input parameters including hydrostatic and osmotic pressures and concentrations of ions, such as sodium and chloride. The intrinsic nephron control, tubuloglomerular feedback, is included and the effects of coupling between nephrons are explored in two-, eight- and 72-nephron models.