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A general relation between membrane potential, ion activities, and pump fluxes for symmetric cells in a steady state

dc.contributor.authorJacquez, John A.en_US
dc.contributor.authorSchultz, Stanley G.en_US
dc.date.accessioned2006-04-07T16:46:12Z
dc.date.available2006-04-07T16:46:12Z
dc.date.issued1974-06en_US
dc.identifier.citationJacquez, John A., Schultz, Stanley G. (1974/06)."A general relation between membrane potential, ion activities, and pump fluxes for symmetric cells in a steady state." Mathematical Biosciences 20(1-2): 19-25. <http://hdl.handle.net/2027.42/22337>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6VHX-45G0HSC-3F/2/f6311028ed79ca91b47be12a14797fd8en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/22337
dc.description.abstractFor steady states of cells that have uniform cell membranes, there must be zero net fluxes of each ion. This provides a set of conditions more restrictive than the condition of zero net current flow that is used to derive the Goldman equation. We show that this leads to a set of general relations between the membrane potential, ion activities, ion permeabilities, and pump fluxes and that the Goldman equation is but one of this set. Further, we demonstrate that the transmembrane potential is uniquely defined by the intracellular and extracellular activities, the permeability coefficients, and the ratio of the net mediated (nondiffusional) fluxes of any two ions of the same valence in a steady state, regardless of the behavior of other ions and without assumptions with respect to the electrical potential profile across the membrane. In the course of this, we also give an exact and general derivation of the Mullins-Noda relation.en_US
dc.format.extent368285 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleA general relation between membrane potential, ion activities, and pump fluxes for symmetric cells in a steady stateen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelNatural Resources and Environmenten_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbsecondlevelEcology and Evolutionary Biologyen_US
dc.subject.hlbsecondlevelBiological Chemistryen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Physiology, The University of Michigan, Medical School, Ann Arbor, Michigan 48104, USAen_US
dc.contributor.affiliationotherDepartment of Physiology, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania 15213, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/22337/1/0000782.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0025-5564(74)90065-0en_US
dc.identifier.sourceMathematical Biosciencesen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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