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• W2896861622 startingPage "78904" @default.
• W2896861622 abstract "The Internet of Bio-Nano-Things is a new paradigm that can bring novel remotely controlled actuation and sensing techniques inside the human body. Toward precise bionano sensing techniques in the brain, we investigate the challenges of modeling spatial distribution of astrocyte networks by developing a mathematical framework that lays the groundwork for future early detection techniques of the neurodegenerative disease. In this paper, we investigate the effect of the $beta $ -amyloid plaques in astrocytes with Alzheimer’s disease. We developed a computation model of healthy and Alzheimer’s diseases astrocytes networks from the state-of-the-art models and results that account for the intracellular pathways, IP3 dynamics, gap junctions, voltage-gated calcium channels, and astrocytes volumes. We also implemented different types of astrocytes network topologies, including shortcut networks, regular degree networks, Erdos Renyi networks, and link radius networks. A proposed multi-scale stochastic computational model captures the relationship between the intracellular and intercellular scales. Finally, we designed and evaluated a single-hop communication system with frequency modulation using metrics such as propagation extend, molecular delay, and channel gain. The results show that the more unstable but at the same time lower level oscillations of Alzheimer’s astrocyte networks can create a multi-scale effect on communication between astrocytes with increased molecular delay and lower channel gain compared to healthy astrocytes, with an elevated impact on Erdos Renyi network and link radius network topologies." @default.
• W2896861622 created "2018-10-26" @default.
• W2896861622 creator A5052766585 @default.
• W2896861622 creator A5082237578 @default.
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• W2896861622 date "2018-01-01" @default.
• W2896861622 modified "2023-09-26" @default.
• W2896861622 title "The Multi-Scale Impact of the Alzheimer’s Disease on the Topology Diversity of Astrocytes Molecular Communications Nanonetworks" @default.
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• W2896861622 doi "https://doi.org/10.1109/access.2018.2885518" @default.
• W2896861622 hasPublicationYear "2018" @default.
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