Multi Agent Functional Bone Simulation: A theoretical study

In 200 A.D., Galen described bones as the fundamental system of body protection. Bones are highly dynamic, in constant renovation to preserve their properties. Understanding bone metabolism has become a relevant area of research. The most common bone disease is osteoporosis and is characterized by low bone mass and microarchitecture disturbances. The major consequence of osteoporosis are fragility fractures (fractures that occur with low impact trauma). Osteoporosis causes more than 8.9 million fractures each year worldwide. Several therapies are effective in preventing fractures and treating osteoporosis. However, there is an enormous difficulty in predicting osteoporosis related fractures and understanding who needs these therapies in order to prevent bone loss. In practical clinic, it becomes essential to have a model describing the bone remodeling process and the impact of the different cellular mediators in the bone metabolism. Although some mathematical models already describe the variation of the bone cells, they do it in a continuous and deterministic way with few cellular mediators. Many studies and experimental results have shown that cellular metabolism and birth-and-death processes in population dynamics are stochastic. Furthermore, mathematical models are reliable on describing a macro level, whereas multiagent simulation models are used to link micro and macro perspectives. In this thesis we have developed a multiagent stochastic model that simulates a timeline remodeling cycle. Our simulator reproduces the homeostatic process of remodeling with the different phases of it, which is time consistent with the real biological process. Our model includes the most relevant cellular mediators in the bone metabolism. Our model demonstrated to have great sensibility to predict bone loss caused by some chronic diseases such hyper and hypoparathyroidism, and excess of glucocorticoids, and also to the most known causes of osteoporosis: estrogen or vitamin D deficiency. Overall, this model provides a deeper understanding about bone metabolism and the pathologies associated with it.Em 200 A.D, Galen descreveu os ossos como o sistema fundamental de proteção do corpo. Os ossos são estruturas altamente dinâmicas e estão em constante remodelação para preservarem as suas propriedades. Compreender o metabolismo do osso tornou-se uma marcante área de pesquisa. A doença óssea mais comum é a osteoporose que causa mais de 8.9 milhões de fraturas em todo o mundo. Existem várias terapias eficazes em prevenir e tratar esta doença. Contudo, existe uma enorme dificuldade em prevê-la, bem como em entender quem necessita de terapêuticas para a retardar ou evitar a perda óssea. Na prática clínica, revelou-se importante existir um modelo que descreva o processo de remodelação óssea assim como o impacto dos diferentes mediadores celulares no metabolismo ósseo. Apesar de já existirem alguns modelos matemáticos que descrevem a variação das células ósseas na remodelação óssea, fazem-no de uma forma contínua e determinística e com poucos mediadores celulares. Bastantes estudos e resultados experimentais revelam que o metabolismo celular, bem como os processos de nascimento e morte em populações dinâmicas, são estocásticos. Para além disso, os modelos matemáticos são fidedignos em descrever um nível macro enquanto modelos de simulação de multiagentes são utilizados para conectar ambas as perspetivas, micro e macro. O modelo estocástico de multiagentes desenvolvido neste trabalho, simula um ciclo de remodelação ao longo do tempo. O nosso simulador reproduz o processo homeostático de remodelação com as diferentes fases deste, o que é consistente com o processo biológico real. Para além disso, o nosso modelo inclui os mediadores celulares mais relevantes no metabolismo ósseo. Os resultados do modelo demonstram ter sensibilidade em prever a perda óssea devido a algumas doenças crónicas como hiper e hipoparatiroidismo e o excesso de glucocorticoides, bem como das mais conhecidas causas de osteoporose: a deficiência de estrogénio e vitamina D. No geral, este modelo permite-nos ter um maior entendimento do metabolismo ósseo, bem como das patologias associadas a este

A hybrid cognitive architecture with primal affect and physiology

Though computational cognitive architectures have been used to study several processes associated with human behavior, the study of integration of affect and emotion in these processes has been relatively sparse. Theory from affective science and affective neuroscience can be used to systematically integrate affect into cognitive architectures, particularly in areas where cognitive system behavior is known to be associated with physiological structure and behavior. I introduce a unified theory and model of human behavior that integrates physiology and primal affect with cognitive processes in a cognitive architecture. This new architecture gives a more tractable, mechanistic way to simulate affect-cognition interactions to provide specific, quantitative predictions. It considers affect as a lower-level, functional process that interacts with cognitive processes (e.g., declarative memory) to result in emotional behavior. This formulation makes it more straightforward to connect these affective representations with other related moderating processes that may not specifically be considered as emotional (e.g., thirst or stress). An improved understanding of the architecture that constrains our behavior gives us a better opportunity to comprehend why we behave the way we do and how we can use this knowledge to recognize and construct a more ideal internal and external environment

The application of agent-based modeling and fuzzy-logic controllers for the study of magnesium biomaterials

Agent-based modeling (ABM) is a powerful approach for studying complex systems and their underlying properties by explicitly modeling the actions and interactions of individual agents. Over the past decade, numerous software programs have been developed to address the needs of the ABM community. However, these solutions often suffer from limitations in design, a lack of comprehensive documentation, or poor performance. As the first objective of this thesis, we introduce CppyABM-a general-purpose software for ABM that provides simulation tools in both Python and C++. CppyABM also enables ABM development using a combination of C++ and Python, taking advantage of the computational performance of C++ and the data analysis and visualization tools of Python. We demonstrate the capabilities of CppyABM through its application to various problems in ecology, virology, and computational biology. As the second objective of this thesis, we use ABM and fuzzy logic controllers (FLCs) to numerically study the effects of magnesium (Mg2+) ions on osteogenesis. Mg-based materials have emerged as the next generation of biomaterials that degrade in the body after implantation and eliminate the need for secondary surgery. We develop two computer models using ABM and FLC and calibrate them based on cell culture experiments. The models were able to capture the regulatory effects of Mg2+ ions and other important factors such as inflammatory cytokines on mesenchymal stem cells (MSC) activities. The models were also able to shed light on the fundamental differences in the cells cultured in different experiments such as proliferation capacity and sensitivity to environmental factors

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains