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dc.date.accessioned2023-12-11T17:36:11Z
dc.date.created2023-05-30T09:15:52Z
dc.date.issued2023
dc.identifier.citationDamrath, Martin Zoofaghari, Mohammad Lekic, Milica Rudsari, Hamid Khoshfekr Pappalardo, Fabrizio Veletic, Mladen Balasingham, Ilangko . Computational estimation of chemical reaction rates in extracellular vesicle signaling. Nano Communication Networks. 2023, 37
dc.identifier.urihttp://hdl.handle.net/10852/106251
dc.description.abstractThe rates of chemical reactions involved in cell-to-cell communication can serve as a powerful tool for advanced theranostics and in establishing a molecular communication link between bio-transceivers. Reaction rates are usually experimentally measured by quantifying chemical products, which is challenging when several signal transduction mechanisms are involved in the signaling pathway. Without loss of generality, we focus on extracellular vesicle (EV) cell-to-cell signaling and propose a computational method to estimate the chemical reaction rates which characterize a process by which EVs are taken by cells. The method is based on measuring only the time-course of environmental EVs, and eliminates the need to measure either bound or internalized EVs which is usually essential for experimental evaluation of the rates by using advanced molecular imaging modalities. As an alternative to a proposed approximation by a linear system model, our computation exploits a nonlinear system model in which the impact of limited receptor sites on the recipient cell membrane is incorporated. The reaction rates are obtained through a suggested linear and iterative approach as well as a novel way of applying Michaelis–Menten kinetics in the frequency domain. The range of validity of each technique is evaluated by varying the number of free binding sites on the cell membrane in relation to the initial number of environmental EVs. In conclusion, the proposed methods are very effective in assessing the dynamics of the EV uptake using a simple in vitro platform.
dc.languageEN
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleComputational estimation of chemical reaction rates in extracellular vesicle signaling
dc.title.alternativeENEngelskEnglishComputational estimation of chemical reaction rates in extracellular vesicle signaling
dc.typeJournal article
dc.creator.authorDamrath, Martin
dc.creator.authorZoofaghari, Mohammad
dc.creator.authorLekic, Milica
dc.creator.authorRudsari, Hamid Khoshfekr
dc.creator.authorPappalardo, Fabrizio
dc.creator.authorVeletic, Mladen
dc.creator.authorBalasingham, Ilangko
dc.date.embargoenddate2025-04-24
cristin.unitcode185,50,0,0
cristin.unitnameDet medisinske fakultet
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.cristin2150038
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Nano Communication Networks&rft.volume=37&rft.spage=&rft.date=2023
dc.identifier.jtitleNano Communication Networks
dc.identifier.volume37
dc.identifier.pagecount0
dc.identifier.doihttps://doi.org/10.1016/j.nancom.2023.100455
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1878-7789
dc.type.versionAcceptedVersion
cristin.articleid100455


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