The aim of this thesis is to provide a modelling approach and simulation framework that allows for emergent dynamics in multi-nephron systems to be studied. The ultimate intent of this research is to provide an approach to renal modelling that is capable of predicting whole-kidney function from the dynamics of individual nephrons, and can therefore be of practical use to clinicians. The contributions of this thesis are: / • A modelling approach—hierarchical dynamical networks—which combines complex networks and graph automata into a single modelling framework. This approach explicitly captures the structure and interactions in multi-nephron systems, and decouples the structure and behaviour of the model. This approach allows emergent dynamics to be easily explored and analysed. / • The development of a multi-nephron model that produces valid behaviour and renders the simulation of whole-kidney function from the dynamics of individual nephrons computationally tractable. Using this model, the emergent effects of the couplings and interactions between nephrons can be investigated. / • An investigation into the dynamics of multi-nephron systems that focuses on whole-system and hierarchical properties rather than the dynamics of individual nephrons. As part of this investigation, the dynamics of a 72-nephron system are analysed—a system significantly larger than existing multi-nephron models. / • A study of whole-system stability in response to localised impairments in nephron function. This is the first study of the emergent dynamics of impaired nephron function, and serves as an illustration of how the emergent dynamics produced by renal diseases may be predicted and analysed. The impaired multinephron systems are shown to exhibit very stable behaviour, which we contend is a feature of both the model and the kidney proper. / • The computational cost of the model is shown to be low enough that the simulation of whole-kidney function is feasible for the first time. It is also demonstrated that simulations can be easily distributed across multiple computers, resulting in a significant gain in performance. An implementation of the model that supports parallel and distributed execution is presented, based on the Join Calculus. / • In order to predict whole-kidney function, a whole-kidney model must be constructed. This thesis proposes two approaches for automatically generating such models. / I conclude that the modelling and analysis techniques presented in this thesis allow for emergent dynamics to be studied in large multinephron systems. This work demonstrates that, for the first time, simulation of whole-kidney function from the dynamics of individual nephrons is tractable. Furthermore, the work provides a basis for predicting emergent effects of localised renal disease. With the continued development of this model, we hope that significant insight will be gained into the onset, progression and treatment of renal diseases.
| Identifer | oai:union.ndltd.org:ADTP/245149 |
| Date | January 2008 |
| Creators | Moss, R. |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
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