Modeling tumor disease and sepsis by networks of adaptively coupled phase oscillators

dc.contributor.authorSawicki, Jakub
dc.contributor.authorBerner, Rico
dc.contributor.authorLöser, Thomas
dc.contributor.authorSchöll, Eckehard
dc.date.accessioned2022-01-17T10:12:40Z
dc.date.available2022-01-17T10:12:40Z
dc.date.issued2022-01-17
dc.description.abstractIn 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 multifrequency cluster). The coupled dynamics of parenchymal cells (metabolism) and nonspecific immune cells (reaction of innate immune system) are represented by nodes of a duplex layer. The cytokine interaction is modeled by adaptive coupling weights between the nodes representing the immune cells (with fast adaptation time scale) and the parenchymal cells (slow adaptation time scale) and between the pairs of parenchymal and immune cells in the duplex network (fixed bidirectional coupling). Thereby, carcinogenesis, organ dysfunction in sepsis, and recurrence risk can be described in a correct functional context.en
dc.description.sponsorshipDFG, 429685422, Kontrollierte Synchronisation in heterogenen Multischicht-Netzwerkenen
dc.description.sponsorshipDFG, 440145547, Komplexe dynamische Netzwerke: Effekte von Heterogenität, Adaptivität und Topologie der Kopplungenen
dc.description.sponsorshipDFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berlinen
dc.identifier.eissn2674-0109
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/16128
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-14902
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc530 Physikde
dc.subject.otheradaptive networksen
dc.subject.othercluster synchronizationen
dc.subject.othercoupled oscillatorsen
dc.subject.otherpattern formationen
dc.subject.othersepsisen
dc.subject.othertumor diseaseen
dc.subject.othercytokine activityen
dc.titleModeling tumor disease and sepsis by networks of adaptively coupled phase oscillatorsen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber730385en
dcterms.bibliographicCitation.doi10.3389/fnetp.2021.730385en
dcterms.bibliographicCitation.journaltitleFrontiers in Network Physiologyen
dcterms.bibliographicCitation.originalpublishernameFrontiersen
dcterms.bibliographicCitation.originalpublisherplaceLausanneen
dcterms.bibliographicCitation.volume1en
tub.accessrights.dnbfreeen
tub.affiliationFak. 2 Mathematik und Naturwissenschaften>Inst. Theoretische Physik>FG Nichtlineare Dynamik und Kontrollede
tub.affiliation.facultyFak. 2 Mathematik und Naturwissenschaftende
tub.affiliation.groupFG Nichtlineare Dynamik und Kontrollede
tub.affiliation.instituteInst. Theoretische Physikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen
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