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  • 1
    Online-Ressource
    Online-Ressource
    Cham :Springer International Publishing AG,
    Schlagwort(e): Neurosciences. ; Electronic books.
    Materialart: Online-Ressource
    Seiten: 1 online resource (453 pages)
    Ausgabe: 1st ed.
    ISBN: 9783319296470
    Serie: Interdisciplinary Applied Mathematics Series ; v.43
    DDC: 572.5160151
    Sprache: Englisch
    Anmerkung: Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- Part I Basic Theory -- 1 Some Background Physiology -- 1.1 Introduction -- 1.2 Common Features of Calcium Dynamics:The Calcium Toolbox -- 1.2.1 Agonists, Receptors, and Second Messengers -- 1.2.2 Internal Compartments -- 1.2.3 Internal Calcium Channels: IPR and RyR -- 1.2.4 IP3 Metabolism -- 1.2.5 Calcium Influx -- 1.2.6 Calcium Removal from the Cytoplasm -- 1.2.7 Calcium-Binding Proteins and Fluorescent Dyes -- 1.2.8 Microdomains and Nanodomains -- 1.3 Spatiotemporal and Hierarchical Organisation -- 1.4 Examples of Calcium Signalling -- 1.4.1 Cardiac Myocytes -- 1.4.2 Airway Smooth Muscle -- 1.4.3 Xenopus Oocytes -- 1.4.4 Pancreatic and Parotid Acinar Cells -- 1.4.5 Airway Epithelial Cells -- 2 The Calcium Toolbox -- 2.1 G Protein-Coupled Receptors -- 2.1.1 A Simple GPCR Model -- 2.1.2 More Complex Receptor Models -- 2.1.3 A Kinetic Model of GPCR Signalling -- 2.2 SERCA and PMCA -- 2.2.1 Unidirectional Models -- 2.2.2 Bidirectional Models -- 2.2.3 Coupling to ATP and pH -- 2.3 The Sodium/Calcium Exchanger -- 2.3.1 Unidirectional Enzyme Model -- 2.3.2 Bidirectional Markov Model -- 2.3.3 Modelling an Electrogenic Exchanger -- 2.3.4 Bidirectional Enzyme Model -- 2.3.5 A Model with Variable Stoichiometry -- 2.4 Mitochondria -- 2.4.1 The Mitochondrial Uniporter -- 2.4.2 The Mitochondrial Sodium/Calcium Exchanger -- 2.5 Voltage-Gated Calcium Channels -- 2.5.1 The Simplest Models -- 2.5.2 Permeation Models of Calcium Channels -- 2.5.3 Inactivation of Calcium Channels by Calcium -- 2.5.4 A Two-Mode Model of Calcium-InducedInactivation -- 2.6 Receptor-Operated and Store-Operated Channels -- 2.6.1 Receptor-Operated Channels -- 2.6.2 Store-Operated Channels -- 2.6.3 STIM-Orai Binding -- 2.7 Inositol Trisphosphate Receptors -- 2.7.1 An Eight-State Markov Model. , 2.7.2 Reduction of the Eight-State Markov Model -- 2.7.3 Gating Models -- 2.7.4 Modal Models -- 2.7.5 Simplifying the Modal Model -- 2.7.6 The Question of Local Calcium Concentration -- 2.7.7 Open Probability and Flux -- 2.8 Ryanodine Receptors -- 2.8.1 An Algebraic Model -- 2.8.2 A Markov Model of RyR Inactivation -- 2.8.3 Luminal Gating -- 2.8.4 Markov Models with Adaptation -- 2.8.5 Two-State Models -- 2.8.6 Modal Gating Model -- 2.9 Calcium Buffers -- 2.9.1 Fast Buffers or Excess Buffers -- 2.9.1.1 A Simplifying Transformation -- 2.10 Inositol Trisphosphate Metabolism -- 2.10.1 IP3 Production -- 2.10.2 IP3 Removal -- 3 Basic Modelling Principles: Deterministic Models -- 3.1 Types of Models -- 3.2 Spatially Homogeneous Models -- 3.2.1 A Model Based on IPR Dynamics -- 3.2.1.1 Steady States and Oscillations -- 3.2.2 A Model Based on ER Refilling -- 3.2.3 A Model That Incorporates MicrodomainsAround IPR -- 3.2.4 Calcium Excitability: Calcium-Induced CalciumRelease -- 3.2.5 Open-Cell and Closed-Cell Models -- 3.2.6 The Importance of Calcium Influx -- 3.2.7 IP3 Dynamics: Class I and Class II Models -- 3.2.7.1 Hybrid Models -- 3.2.7.2 Pulse Experiments -- 3.3 Spatially Distributed Models -- 3.3.1 A Brief Note on Terminology -- 3.3.2 Homogenisation -- 3.3.3 Membrane Fluxes -- 3.3.4 Closed-Cell Spatial Models -- 3.4 Microdomains -- 3.4.1 Calcium at the Mouth of an Open Channel -- 3.4.1.1 The Excess Buffer Approximation -- 3.4.1.2 The Rapid Buffer Approximation -- 3.4.2 Incorporating ER Depletion -- 3.4.3 The Channel as a Disk -- 3.4.4 Calcium Concentration Changes Quickly in Microdomains -- 3.4.5 Microdomains Between Organelles -- 3.4.6 Connecting a Microdomain to the Cell -- 3.4.7 Can Microdomains Be Modelled Deterministically? -- 3.5 Calcium Waves -- 3.5.1 The Fire-Diffuse-Fire Model -- 3.5.2 Continuous Release Sites. , 3.5.3 Waves in Multiple Dimensions -- 3.5.4 Phase Waves -- 3.6 Intercellular Waves -- 3.6.1 Mechanisms of Intercellular Wave Propagation -- 3.6.2 Propagation by Gap Junctions -- 3.6.2.1 An Example: Mechanically-Stimulated Waves in Airway Epithelial Cells -- 3.6.3 Regenerative and Partially Regenerative Waves -- 3.6.4 Paracrine Propagation -- 3.7 Connecting the Cytosol to the Membrane -- 3.8 The Effects of Buffers -- 3.8.1 Qualitative Effects -- 3.8.2 Quantitative Effects -- 4 Hierarchical and Stochastic Modelling -- 4.1 Introduction -- 4.1.1 Hierarchical Modelling Across Different Structural Levels -- 4.1.2 Distributions, Blips, and Puffs -- 4.2 Characteristics of Puffs -- 4.2.1 Interpuff Interval Distributions -- 4.2.2 The Coefficient of Variation -- 4.2.3 Puffs are not Periodic -- 4.3 Properties of Sequences of Cellular Spikes -- 4.3.1 Wave Nucleation -- 4.3.2 The Effects of Buffers on Wave Nucleation -- 4.3.3 Information Content and Signal Encoding -- 4.3.4 Summary -- 4.4 Appendix: An Incomplete Theory of Calcium Spiking -- 4.4.1 Semi-Markov Processes -- 4.4.2 Interpuff Interval Distributions, Puff Duration Distributions and Their Dependencies on Cellular Parameters -- 4.4.3 Detailed Derivation of the First Passage TimeDensity -- 4.4.3.1 Calculations Based on the Laplace Transform of Waiting Time Distributions -- 4.4.3.2 Resampling an IPI Distribution to Obtain an ISI Distribution -- 4.4.4 Some Formulae -- 4.4.5 Summary -- 5 Nonlinear Dynamics of Calcium -- 5.1 An Illustrative Model: The Hybrid Model -- 5.2 Bifurcation Analysis for ODE Models -- 5.3 Model Reduction -- 5.3.1 Identifying Time Scales -- 5.3.2 Reduction Based on Timescale Separation -- 5.4 Analysis Based on Timescale Separation -- 5.4.1 Freezing Slow Variables -- 5.4.2 Geometric Singular Perturbation Theory -- 5.5 Understanding Transient Dynamics. , 5.6 Coupled Voltage and Calcium Models -- 5.7 Calcium Waves -- 5.8 Calcium Excitability and the FitzHugh-Nagumo Equations -- Part II Specific Models -- 6 Nonexcitable Cells -- 6.1 Xenopus Oocytes -- 6.1.1 A Heuristic Model for Calcium Oscillationsand Waves -- 6.1.2 Mitochondria and Spiral Wave Stability -- 6.1.3 Bistability and the Fertilisation Calcium Wave -- 6.1.4 Increased IP3 Sensitivity During Egg Maturation -- 6.2 Hepatocytes -- 6.2.1 Effect of IP3 Metabolism on Calcium Oscillations -- 6.2.1.1 Simulation Results -- 6.2.1.2 Testing the Model Predictions -- 6.2.2 Deterministic Versus Stochastic Aspects of Calcium Oscillations -- 6.2.3 Phase Waves Coordinate Calcium Spiking Between Connected Hepatocytes -- 6.2.4 Amplitude-Coded Calcium Oscillations in Fish Hepatocytes -- 6.3 Pancreatic and Parotid Acinar Cells -- 6.3.1 Introduction -- 6.3.2 Calcium Oscillations and Waves in Acinar Cells -- 6.3.3 Calcium Waves and Water Secretion -- 6.3.4 Detailed Spatial Structure of an Acinus -- 6.4 Astrocytes -- 6.4.1 Introduction -- 6.4.2 Calcium Oscillations Induced by Stimulation of mGlu5 Receptors -- 6.4.3 Towards Modelling Calcium Oscillationsin Astrocytes -- 7 Muscle -- 7.1 Introduction -- 7.2 Cardiac Myocytes -- 7.2.1 Cardiac Excitation-Contraction Coupling -- 7.2.2 Common-Pool and Local-Control Models -- 7.2.3 Calcium Sparks -- 7.2.4 The Diadic Cleft Can Be Described by a Continuous and Deterministic Model -- 7.2.5 Integrative Models -- 7.2.6 Simplified Approaches -- 7.2.6.1 The Probability Density Approach -- 7.2.7 Atrial Myocytes -- 7.3 Skeletal Myocytes -- 7.4 Smooth Muscle -- 7.4.1 Airway Smooth Muscle -- 7.4.1.1 Stochastic or Deterministic? -- 7.4.1.2 The Cytosolic Oscillator -- 7.4.1.3 The Interplay Between IP3R and RyR -- 7.4.1.4 Periodic Waves in the Model -- 7.4.1.5 More Detailed Treatment of the Membrane Currents. , 7.4.2 Vascular Smooth Muscle -- 7.5 Calcium and the Generation of Force in Smooth Muscle -- 7.5.1 The Hai-Murphy Model -- 7.5.2 Calcium, Calmodulin, and MLCK -- 7.5.3 The Frequency Response of Airway Smooth Muscle -- 8 Neurons and Other Excitable Cells -- 8.1 Introduction -- 8.2 Pre-synaptic Calcium Dynamics -- 8.2.1 Facilitation -- 8.2.2 A Model of the Residual Bound Calcium Hypothesis -- 8.2.3 A More Complex Version -- 8.3 Post-Synaptic Plasticity -- 8.3.1 Calcium/Calmodulin-Dependent Protein Kinase II as a Bistable Switch -- 8.3.2 Phenomenological Models -- 8.3.3 CaMKII as a Frequency Decoder in the Absence of Dephosphorylation -- 8.4 Pancreatic Beta Cells -- 8.4.1 Bursting in the Pancreatic Beta Cell -- 8.4.1.1 Phase-Plane Analysis -- 8.4.2 ER Calcium as a Slow Controlling Variable -- 8.4.3 Other Models -- 8.5 Pancreatic Alpha Cells -- 8.5.1 Electrical Activity of Pancreatic Alpha Cells -- 8.5.2 Calcium Dynamics in Pancreatic Alpha Cells -- 8.6 Calcium-Mediated Secretion -- 8.6.1 Prototypic Model for Calcium-Mediated Secretion -- 8.6.2 Secretion of Insulin by Pancreatic Beta Cells -- 8.6.3 Secretion of Glucagon by Pancreatic Alpha Cells -- 8.7 Hypothalamic and Pituitary Cells -- 8.7.1 The Gonadotroph -- 8.7.1.1 The Membrane Model -- 8.7.1.2 The Calcium Model -- 8.7.1.3 Results -- 8.7.2 GnRH Neurons -- References -- Index.
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  • 2
    Digitale Medien
    Digitale Medien
    Woodbury, NY : American Institute of Physics (AIP)
    Chaos 11 (2001), S. 247-260 
    ISSN: 1089-7682
    Quelle: AIP Digital Archive
    Thema: Physik
    Notizen: We present an overview of mechanisms responsible for simple or complex oscillatory behavior in metabolic and genetic control networks. Besides simple periodic behavior corresponding to the evolution toward a limit cycle we consider complex modes of oscillatory behavior such as complex periodic oscillations of the bursting type and chaos. Multiple attractors are also discussed, e.g., the coexistence between a stable steady state and a stable limit cycle (hard excitation), or the coexistence between two simultaneously stable limit cycles (birhythmicity). We discuss mechanisms responsible for the transition from simple to complex oscillatory behavior by means of a number of models serving as selected examples. The models were originally proposed to account for simple periodic oscillations observed experimentally at the cellular level in a variety of biological systems. In a second stage, these models were modified to allow for complex oscillatory phenomena such as bursting, birhythmicity, or chaos. We consider successively (1) models based on enzyme regulation, proposed for glycolytic oscillations and for the control of successive phases of the cell cycle, respectively; (2) a model for intracellular Ca2+ oscillations based on transport regulation; (3) a model for oscillations of cyclic AMP based on receptor desensitization in Dictyostelium cells; and (4) a model based on genetic regulation for circadian rhythms in Drosophila. Two main classes of mechanism leading from simple to complex oscillatory behavior are identified, namely (i) the interplay between two endogenous oscillatory mechanisms, which can take multiple forms, overt or more subtle, depending on whether the two oscillators each involve their own regulatory feedback loop or share a common feedback loop while differing by some related process, and (ii) self-modulation of the oscillator through feedback from the system's output on one of the parameters controlling oscillatory behavior. However, the latter mechanism may also be viewed as involving the interplay between two feedback processes, each of which might be capable of producing oscillations. Although our discussion primarily focuses on the case of autonomous oscillatory behavior, we also consider the case of nonautonomous complex oscillations in a model for circadian oscillations subjected to periodic forcing by a light-dark cycle and show that the occurrence of entrainment versus chaos in these conditions markedly depends on the wave form of periodic forcing. © 2001 American Institute of Physics.
    Materialart: Digitale Medien
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  • 3
    ISSN: 1522-9602
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Biologie , Mathematik
    Notizen: Abstract We investigate the various types of complex Ca2+ oscillations which can arise in a model based on the mechanism of Ca2+-induced Ca2+ release (CICR), that takes into account the Ca2+-stimulated degradation of inositol 1,4,5-trisphosphate (InsP3) by a 3-kinase. This model was previously proposed in the course of an investigation of plausible mechanisms capable of generating complex Ca2+ oscillations (Borghans et al., 1997). Besides simple periodic behavior, this model for cytosolic Ca2+ oscillations in nonexcitable cells shows complex oscillatory phenomena like bursting or chaos. We show that the model also admits a coexistence between two stable regimes of sustained oscillations (birhythmicity). The occurrence of these various modes of oscillatory behavior is analysed by means of bifurcation diagrams. Complex oscillations are characterized by means of Poincaré sections, power spectra and Lyapounov exponents. The results point to the role of self-modulation of the InsP3 signal by 3-kinase as a possible source for complex temporal patterns in Ca2+ signaling.
    Materialart: Digitale Medien
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  • 4
    Digitale Medien
    Digitale Medien
    New York, NY : Wiley-Blackwell
    BioEssays 14 (1992), S. 485-493 
    ISSN: 0265-9247
    Schlagwort(e): Life and Medical Sciences ; Cell & Developmental Biology
    Quelle: Wiley InterScience Backfile Collection 1832-2000
    Thema: Biologie , Medizin
    Notizen: Oscillations in cytosolic Ca2+ occur in a wide variety of cells, either spontaneously or as a result of external stimulation. This process is often accompanied by intracellular Ca2+ waves. A number of theoretical models have been proposed to account for the periodic generation and spatial propagation of Ca2+ signals. These models are reviewed and their predictions compared with experimental observations. Models for Ca2+ oscillations can be distinguished according to whether or not they rely on the concomitant, periodic variation in inositol 1,4,5-trisphosphate. Such a variation, however, is not required in models based on Ca2+-induced Ca2+ release. When Ca2+diffusion is incorporated into these models, propagating waves of cytosolic Ca2+ arise, with profiles and rates comparable to those seen in the experiments.
    Zusätzliches Material: 4 Ill.
    Materialart: Digitale Medien
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