Publication:
Modeling and analysis of SCFA-Driven vagus nerve signaling in the gut-brain axis via molecular communication

dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.kuauthorOrtlek, Beyza Ezgi
dc.contributor.kuauthorAkan, Özgür Barış
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2026-01-16T08:46:29Z
dc.date.available2026-01-16
dc.date.issued2025
dc.description.abstractMolecular communication (MC) is a bio-inspired communication paradigm that utilizes molecules to transfer information and offers a robust framework for understanding biological signaling systems. This paper introduces a novel end-to-end MC framework for short-chain fatty acid (SCFA)-driven vagus nerve signaling within the gut-brain axis (GBA) to enhance our understanding of gut-brain communication mechanisms. SCFA molecules, produced by gut microbiota, serve as important biomarkers in physiological and psychological processes, including neurodegenerative and mental health disorders. The developed end-to-end model integrates SCFA binding to vagal afferent fibers, G protein-coupled receptor (GPCR)-mediated calcium signaling, and Hodgkin-Huxley-based action potential generation into a comprehensive vagus nerve signaling mechanism through GBA. Information-theoretic metrics such as mutual information and delay are used to evaluate the efficiency of this SCFA-driven signaling pathway model. Simulations demonstrate how molecular inputs translate into neural outputs, highlighting critical aspects that govern gut-brain communication. In this work, the integration of SCFA-driven signaling into the MC framework provides a novel perspective on gut-brain communication and paves the way for the development of innovative therapeutic advancements targeting neurological and psychiatric disorders.
dc.description.fulltextNo
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipAXA Research Fund, AXA Chair for Internet of Everything at Koc University
dc.identifier.doi10.1109/TMBMC.2025.3585798
dc.identifier.eissn2332-7804
dc.identifier.embargoNo
dc.identifier.endpage599
dc.identifier.issue4
dc.identifier.quartileQ3
dc.identifier.scopus2-s2.0-105009967231
dc.identifier.startpage588
dc.identifier.urihttps://doi.org/10.1109/TMBMC.2025.3585798
dc.identifier.urihttps://hdl.handle.net/20.500.14288/32092
dc.identifier.volume11
dc.identifier.wos001642142400013
dc.keywordsMolecular communication
dc.keywordsPhysiology
dc.keywordsDelays
dc.keywordsBiology
dc.keywordsAnalytical models
dc.keywordsNeurotransmitters
dc.keywordsImmune system
dc.keywordsAction potentials
dc.keywordsMutual information
dc.keywordsCalcium
dc.keywordsChannel modeling
dc.keywordsVagus nerve
dc.keywordsGut-brain axis
dc.keywordsNeural communication
dc.keywordsDiffusion modeling
dc.keywordsLigand-receptor interactions
dc.keywordsInformation theory
dc.keywordsMutual information
dc.keywordsSignal propagation
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofIEEE Transactions on Molecular Biological and Multi-Scale Communications
dc.relation.openaccessNo
dc.rightsCopyrighted
dc.subjectEngineering, Electrical & Electronic
dc.subjectTelecommunications
dc.titleModeling and analysis of SCFA-Driven vagus nerve signaling in the gut-brain axis via molecular communication
dc.typeJournal Article
dspace.entity.typePublication
person.familyNameOrtlek
person.familyNameAkan
person.givenNameBeyza Ezgi
person.givenNameÖzgür Barış
relation.isOrgUnitOfPublication21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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