{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Tiina Manninen\n", "# X_IP3 constant\n", "# Implementation of astrocyte model by Riera et al. (2011)\n", "# Riera, J., Hatanaka, R., Ozaki, T., and Kawashima, R. (2011a). Modeling the spontaneous Ca2+ oscillations\n", "# in astrocytes: Inconsistencies and usefulness. J. Integr. Neurosci. 10, 439–473.\n", "# Riera, J., Hatanaka, R., Uchida, T., Ozaki, T., and Kawashima, R. (2011b). Quantifying the uncertainty\n", "# of spontaneous Ca2+ oscillations in astrocytes: Particulars of Alzheimer’s disease. Biophys. J. 101, 554–564.\n", "\n", "# Model implemented and ran using Jupyter Notebook.\n", "\n", "# Model code used in publication: Manninen, T., Havela, R., and Linne, M.-L. (2017). \n", "# Reproducibility and comparability of computational models for astrocyte calcium excitability.\n", "# Front. Neuroinform.\n", "\n", "import numpy as np\n", "\n", "class ModelSystem:\n", " def __init__(self, params):\n", " self.params = params\n", " \n", " def computeDeriv(self, state, t):\n", " Ca, Ca_free, h, IP3 = state\n", " modelPar = self.params\n", " \n", " # Intermediate variables\n", " alpha_h = modelPar.a * modelPar.d_2 * (IP3 + modelPar.d_1) / (IP3 + modelPar.d_3)\n", " beta_h = modelPar.a * Ca\n", " Ca_ER = (Ca_free - Ca) / modelPar.c_1\n", " m_infty = IP3 * Ca / ((IP3 + modelPar.d_1)*(Ca + modelPar.d_5))\n", " PLC_delta1 = modelPar.v_delta * Ca ** 2 / (Ca ** 2 + modelPar.K_deltaCa ** 2)\n", " v_CCE = modelPar.x_CCE * modelPar.H_CCE ** 2 / (modelPar.H_CCE ** 2 + Ca_ER ** 2)\n", " v_out = modelPar.k_out * Ca\n", " v_Rel = modelPar.c_1 * (modelPar.v_1 * m_infty ** 3 * h ** 3 + modelPar.v_2)\\\n", " * (Ca_ER - Ca) \n", " v_SERCA = modelPar.V_SERCA * Ca ** 2 / (Ca ** 2 + modelPar.K_p ** 2)\n", " \n", " # dx/dt \n", " dCa_per_dt = v_Rel - v_SERCA + modelPar.epsilon * (modelPar.j_in + v_CCE - v_out)\n", " dCa_free_per_dt = modelPar.epsilon * (modelPar.j_in + v_CCE - v_out)\n", " dh_per_dt = alpha_h * (1 - h) - beta_h * h # This equation corrected\n", " dIP3_per_dt = modelPar.X_IP3 + PLC_delta1 - modelPar.K_IP3 * IP3\n", " \n", " deriv = [dCa_per_dt, dCa_free_per_dt, dh_per_dt, dIP3_per_dt]\n", " return deriv " ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "class ModelParameters:\n", " a = 0.2 # 1/(uM s)\n", " c_1 = 0.185 # 1\n", " d_1 = 0.13 # uM\n", " d_2 = 1.049 # uM\n", " d_3 = 0.9434 # uM\n", " d_5 = 0.082 # uM\n", " epsilon = 0.01 # uM\n", " H_CCE = 10 # uM\n", " j_in = 0.065 # uM/s\n", " K_IP3 = 1.25 # 1/s\n", " K_deltaCa = 0.55 # uM \n", " k_out = 0.5 # 1/s\n", " K_p = 0.1 # uM\n", " v_1 = 6 # 1/s\n", " v_2 = 0.11 # 1/s\n", " v_delta = 0.152 # uM/s\n", " V_SERCA = 0.9 # uM/s\n", " x_CCE = 0.01 # uM/s\n", " X_IP3 = 0.43 # uM/s" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [], "source": [ "params = ModelParameters()\n", "\n", "mySys = ModelSystem(params)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from scipy.integrate import odeint\n", "initial = [0.09, 2, 0.79, 0.14] # uM, uM, 1, uM\n", "\n", "Tmax = 600\n", "dt = 0.1\n", "t = np.arange(0,Tmax,dt)\n", "\n", "data = odeint(mySys.computeDeriv, initial, t)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] }, { "data": { "image/png": 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55Nhmf/lLaXHmzXPfddfYD5x1lvvxx0ecK64oLU4qFd8XuO+2m/uAAfH/OeeU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\na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i0fptSrV5Rt4MDiZ2Z1j/3aqlV50LDLLtW7uj91avnskxDD26o7pOeGGyJQbNEiGvzV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\nb70VQd8rr8TMYXqQTBow1tTEjGH6tWpXV+RQ3LEj9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mnHZKRUA88D/4U4/KcPM7sJ+FPg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\nIiIiIjLBKNATERERERGZYP4/UpuD2PaZRdUAAAAASUVORK5CYII=\n", "text/plain": [ "<matplotlib.figure.Figure at 0x7f29972a65f8>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%pylab inline\n", "import matplotlib.pyplot as plt\n", "\n", "plt.figure(figsize=(9, 6), dpi=200)\n", "plt.subplot(4,1,1)\n", "plt.plot(t, data[:,0])\n", "plt.title('Calcium concentration')\n", "plt.ylabel('Ca (uM)')\n", "\n", "plt.subplot(4,1,2)\n", "plt.plot(t, data[:,3])\n", "plt.title('IP3 concentration')\n", "plt.ylabel('IP3 (uM)')\n", "\n", "plt.subplot(4,1,3)\n", "plt.plot(t, data[:,2])\n", "plt.title('Fraction of active IP3Rs')\n", "plt.ylabel('h')\n", "plt.xlabel('t (s)')\n", "\n", "plt.subplot(4,1,4)\n", "plt.plot(t, data[:,1])\n", "plt.title('Calcium concentration in the ER')\n", "plt.ylabel('CaER (uM)')\n", "\n", "plt.tight_layout()\n", "\n", "\n", "np.savetxt('Riera2011_Cafree_variable.csv', (t, data[:,0], data[:,1], data[:,2], data[:,3]), delimiter=',')" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [default]", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 1 }