Modeling tumor disease and sepsis by networks of adaptively coupled phase oscillators
Jakub Sawicki, Rico Berner, Thomas L\"oser, Eckehard Sch\"oll

TL;DR
This paper introduces a network model of tumor and sepsis dynamics using coupled phase oscillators, explaining disease progression as a destabilization of healthy synchronized states.
Contribution
It presents a novel unified phase oscillator network model capturing carcinogenesis and sepsis through adaptive coupling dynamics between immune and parenchymal cells.
Findings
Disease states correspond to desynchronized oscillator states.
Model explains tumor progression and organ dysfunction.
Adaptive coupling captures immune response dynamics.
Abstract
In this study, we provide a dynamical systems perspective to the modelling of pathological states induced by tumors or infection. A unified disease model is established using the innate immune system as the reference point. We propose a two-layer network model for carcinogenesis and sepsis based upon the interaction of parenchymal cells and immune cells via cytokines, and the co-evolutionary dynamics of parenchymal, immune cells, and cytokines. Our aim is to show that the complex cellular cooperation between parenchyma and stroma (immune layer) in the physiological and pathological case can be qualitatively and functionally described by a simple paradigmatic model of phase oscillators. By this, we explain carcinogenesis, tumor progression, and sepsis by destabilization of the healthy homeostatic state (frequency synchronized), and emergence of a pathological state (desynchronized or…
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Taxonomy
TopicsGene Regulatory Network Analysis · Mathematical Biology Tumor Growth · Nonlinear Dynamics and Pattern Formation
