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      A biophysically constrained computational model of the action potential of mouse urinary bladder smooth muscle

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          Abstract

          Urinary incontinence is associated with enhanced spontaneous phasic contractions of the detrusor smooth muscle (DSM). Although a complete understanding of the etiology of these spontaneous contractions is not yet established, it is suggested that the spontaneously evoked action potentials (sAPs) in DSM cells initiate and modulate the contractions. In order to further our understanding of the ionic mechanisms underlying sAP generation, we present here a biophysically detailed computational model of a single DSM cell. First, we constructed mathematical models for nine ion channels found in DSM cells based on published experimental data: two voltage gated Ca 2+ ion channels, an hyperpolarization-activated ion channel, two voltage-gated K + ion channels, three Ca 2+-activated K + ion channels and a non-specific background leak ion channel. The ion channels’ kinetics were characterized in terms of maximal conductances and differential equations based on voltage or calcium-dependent activation and inactivation. All ion channel models were validated by comparing the simulated currents and current-voltage relations with those reported in experimental work. Incorporating these channels, our DSM model is capable of reproducing experimentally recorded spike-type sAPs of varying configurations, ranging from sAPs displaying after-hyperpolarizations to sAPs displaying after-depolarizations. The contributions of the principal ion channels to spike generation and configuration were also investigated as a means of mimicking the effects of selected pharmacological agents on DSM cell excitability. Additionally, the features of propagation of an AP along a length of electrically continuous smooth muscle tissue were investigated. To date, a biophysically detailed computational model does not exist for DSM cells. Our model, constrained heavily by physiological data, provides a powerful tool to investigate the ionic mechanisms underlying the genesis of DSM electrical activity, which can further shed light on certain aspects of urinary bladder function and dysfunction.

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          The standardisation of terminology of lower urinary tract function: report from the Standardisation Sub-committee of the International Continence Society.

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            Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell.

            The rules of synaptic integration in pyramidal cells remain obscure, in part due to conflicting interpretations of existing experimental data. To clarify issues, we developed a CA1 pyramidal cell model calibrated with a broad spectrum of in vitro data. Using simultaneous dendritic and somatic recordings and combining results for two different response measures (peak versus mean EPSP), two different stimulus formats (single shock versus 50 Hz trains), and two different spatial integration conditions (within versus between-branch summation), we found that the cell's subthreshold responses to paired inputs are best described as a sum of nonlinear subunit responses, where the subunits correspond to different dendritic branches. In addition to suggesting a new type of experiment and providing testable predictions, our model shows how conclusions regarding synaptic arithmetic can be influenced by an array of seemingly innocuous experimental design choices.
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              Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism.

              Markov kinetic models were used to synthesize a complete description of synaptic transmission, including opening of voltage-dependent channels in the presynaptic terminal, release of neurotransmitter, gating of postsynaptic receptors, and activation of second-messenger systems. These kinetic schemes provide a more general framework for modeling ion channels than the Hodgkin-Huxley formalism, supporting a continuous spectrum of descriptions ranging from the very simple and computationally efficient to the highly complex and biophysically precise. Examples are given of simple kinetic schemes based on fits to experimental data that capture the essential properties of voltage-gated, synaptic and neuromodulatory currents. The Markov formalism allows the dynamics of ionic currents to be considered naturally in the larger context of biochemical signal transduction. This framework can facilitate the integration of a wide range of experimental data and promote consistent theoretical analysis of neural mechanisms from molecular interactions to network computations.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 July 2018
                2018
                : 13
                : 7
                : e0200712
                Affiliations
                [1 ] Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
                [2 ] School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, England, United Kingdom
                Cinvestav-IPN, MEXICO
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-7383-3482
                Article
                PONE-D-17-42050
                10.1371/journal.pone.0200712
                6061979
                30048468
                87c3301f-4a4f-4710-af22-ac4db3f96cc8
                © 2018 Mahapatra et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 29 November 2017
                : 2 July 2018
                Page count
                Figures: 17, Tables: 3, Pages: 32
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001407, Department of Biotechnology, Ministry of Science and Technology;
                Award ID: BT/PR12973/MED/122/47/2016
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000732, UK-India Education and Research Initiative;
                Award ID: UKUTP 20110055
                Award Recipient :
                This work is supported in part by Department of Biotechnology (DBT), India (grant number BT/PR14326 /MED/30 /483/ 2010), BT/PR12973/MED/122/47/2016 and the UK-India Education and Research Initiative (UKIERI), UK (grant number UKUTP 20110055). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Electrophysiology
                Membrane Potential
                Action Potentials
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                Membrane Potential
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                Bladder
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                Custom metadata
                All relevant data are within the paper and its Supporting Information files. This model files are available at the ModelDB database: https://senselab.med.yale.edu/modeldb/ShowModel.cshtml?model=243842 and at github: https://github.com/cmahapatra97/Chitaranjan-Mahapatra.

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