但血糖-胰岛素响应模拟

sbioloadproject (“insulindemo”,“m1”)

warnSettings =警告(“关闭”,“SimBiology: DimAnalysisNotDone_MatlabFcn_Dimensionless”);

mealDose = sbioselect (m1,“名字”,“一餐”);get (mealDose)

configset = getconfigset (m1,“活跃”);configset。StopTime=7;

configset.TimeUnits

configset normalMealSim = sbiosimulate (m1, [], mealDose);

diabeticVar = sbioselect (m1,“名字”,“2型糖尿病”)

diabeticMealSim = sbiosimulate (m1, configset、diabeticVar mealDose);

outputNames = {“等离子Glu浓缩”,“血浆Ins浓缩的”,“Glu刺激”,…“Glu出现率”,“Glu Util”,“Ins Secr”};图;为i = 1:元素个数(outputNames)次要情节(2、3、我);[tNormal, yNormal] = normalMealSim.selectbyname (outputNames{我});[tDiabetic, yDiabetic] = diabeticMealSim.selectbyname (outputNames{我});情节(tNormal yNormal,“- - -”,…tDiabetic yDiabetic,“——”);%注释数据outputParam = sbioselect (m1,“名字”我,outputNames {});标题(outputNames{我});包含(的时间(小时));如果比较字符串(outputParam.Type“参数”)ylabel (outputParam.ValueUnits);其他的ylabel (outputParam.InitialAmountUnits);结束xlim ([0 7]);%添加传奇如果我= = 3({传奇“正常”,“糖尿病”},“位置”,“最佳”);结束结束

configset。StopTime=24;

dayDose = sbioselect (m1,“名字”,“日常生活”);

configset normalDaySim = sbiosimulate (m1, [], dayDose);

impairVars {1} = sbioselect (m1,“名字”,“低胰岛素敏感性”);(impairVars impairVars {2} = {1},…sbioselect (m1,“名字”,“高β细胞反应性”));impairVars {3} = sbioselect (m1,“名字”,“低β细胞反应性”);(impairVars impairVars {4} = {3},…sbioselect (m1,“名字”,“高胰岛素敏感性”));

为i = 1:4 impairSims (i) = sbiosimulate (m1, configset impairVars {}, dayDose);结束

图;outputNames = {“等离子Glu浓缩”,“血浆Ins浓缩的”};legendLabels = {{“正常”},…{“ins =β\ ',“ins +β\”},…{“β= Ins - \”,“+ Ins -β\”}};yLimits = (80 240;0 500];为i = 1:元素个数(outputNames) [tNormal yNormal] = selectbyname (normalDaySim, outputNames{我});[tImpair, yImpair] = selectbyname (impairSims outputNames{我});%绘制正常次要情节(2、3、3 *我2);情节(tNormal yNormal,“b -”);xlim (24 [0]);ylim (yLimits(我,:));包含(的时间(小时));传奇(legendLabels {1},“位置”,“西北”);%的阴谋低胰岛素次要情节(2、3、3张*);情节(tImpair {1}, yImpair {1},“g——”,tImpair {2}, yImpair {2},“:”);xlim (24 [0]);ylim (yLimits(我,:));包含(的时间(小时));传奇(legendLabels {2},“位置”,“西北”);标题(outputNames{我});%的阴谋低β次要情节(2、3、3 *我);情节(tImpair {3}, yImpair {3},c -。,tImpair {4}, yImpair {4},“m -”);xlim (24 [0]);ylim (yLimits(我,:));包含(的时间(小时));传奇(legendLabels {3},“位置”,“西北”);结束

%加载实验数据fitData = groupedData (readtable (“GlucoseData.csv”,“分隔符”,”、“));%设置单位的数据fitData.Properties。VariableUnits = {…“小时”,…%的时间单位毫克/分钟的,…% GluRate单位毫克/分升的,…% PlasmaGluConc单位毫克/分钟的,…% GluUtil单位};%确定哪些模型组件对应于观测数据变量。gastroFitObs =(Glu出现率)= GluRate ';%的价值估计以下参数:gastroFitEst = estimatedInfo ({“kmax”,“kmin”,“出租车”,“剂量”});%保证参数估计时总是积极的评估%使用对数变换参数。[gastroFitEst。变换]=交易(“日志”);%设置初始剂量的估算报告餐剂量。的%的初步估计将从参数值%的模型。gastroFitEst (4)。我nitialValue = mealDose.Amount;%生成仿真数据与初始参数估计configset。StopTime=7; gastroInitSim = sbiosimulate(m1, mealDose);使用| %合适数据nlinfit |,显示在每个迭代输出fitOptions = statset (“显示”,“通路”);[gastroFitResults, gastroFitSims] = sbiofit (m1, fitData…gastroFitObs gastroFitEst, [],“nlinfit”,fitOptions);

%配合数据,绘制在每个迭代的目标函数fitOptions2 = optimoptions (“fminunc”,“PlotFcns”,@optimplotfval);[gastroFitResults (2), gastroFitSims (2)] = sbiofit (m1, fitData…gastroFitObs gastroFitEst, [],“fminunc”,fitOptions2);

gastroSims = selectbyname ([gastroInitSim gastroFitSims),“Glu出现率”);图;情节(gastroSims (1)。时间,gastroSims (1)。数据,“- - -”,…gastroSims (2)。时间,gastroSims (2)。数据,“——”,…gastroSims (3)。时间,gastroSims (3)。数据,“-”。,…fitData。时间、fitData.GluRate“x”);包含(的时间(小时));ylabel (毫克/分钟的);传奇(“报告”,“估计(nlinfit)”,…“估计(fminunc)”,“实验”);标题(葡萄糖的外表适合的);

图;.ParameterEstimates.Estimate fitResults = [gastroFitResults (1)…gastroFitResults (2) .ParameterEstimates.Estimate];%的初始值kmax kmin,出租车来自模型。gastroFitInitValues = [get (sbioselect (m1,“名字”,“kmax”),“价值”)得到(sbioselect (m1,“名字”,“kmin”),“价值”)得到(sbioselect (m1,“名字”,“出租车”),“价值”)gastroFitEst (4)。InitialValue];relFitChange = fitResults。/ [gastroFitInitValues gastroFitInitValues] - 1;酒吧(relFitChange);甘氨胆酸ax =;斧子。XTickLabel = {gastroFitEst.Name};ylabel (估计的相对变化值的);标题(比较报告和胃肠道估计参数值);传奇({“nlinfit”,“fminunc”},“位置”,“北”)

%为“输入”:创建迫使功能%血浆胰岛素PlasmaInsRule = sbioselect (m1,“名字”,“血浆Ins浓缩的定义”);PlasmaInsForcingFcn = sbioselect (m1,“名字”,“血浆Ins浓缩的强制函数”)

PlasmaInsRule。积极= false;PlasmaInsForcingFcn。积极= true;%内源性葡萄糖生产(Glu刺激)GluProdRule = sbioselect (m1,“名字”,“Glu刺激定义”);GluProdForcingFcn = sbioselect (m1,“名字”,“Glu促使强制函数”)

GluProdRule。积极= false;GluProdForcingFcn。积极= true;%葡萄糖的外观(Glu出现率)GluRateRule = sbioselect (m1,“名字”,Glu出现率定义的);GluRateForcingFcn = sbioselect (m1,“名字”,“Glu出现率强制函数”)

GluRateRule。积极= false;GluRateForcingFcn。积极= true;%模拟的初始参数值muscleInitSim = sbiosimulate (m1);%确定哪些模型组件对应于观测数据变量。muscleFitObs = {(等离子体Glu浓缩的]= PlasmaGluConc ',…(Glu Util) = GluUtil '};%的价值估计以下参数:muscleFitEst = estimatedInfo ({“(等离子体体积(Glu))”,“k1”,“k2”,…“Vm0”,“Vmx”,“公里”,“p2U”});%保证参数估计时总是积极的评估%使用对数变换参数。[muscleFitEst。变换]=交易(“日志”);%配合数据,显示在每个迭代输出[muscleFitResults, muscleFitSim] = sbiofit (m1, fitData…muscleFitObs muscleFitEst, [],“nlinfit”,fitOptions);

图;muscleFitInitValues = [get (sbioselect (m1,“名字”,“等离子体体积(Glu)”),“价值”)得到(sbioselect (m1,“名字”,“k1”),“价值”)得到(sbioselect (m1,“名字”,“k2”),“价值”)得到(sbioselect (m1,“名字”,“Vm0”),“价值”)得到(sbioselect (m1,“名字”,“Vmx”),“价值”)得到(sbioselect (m1,“名字”,“公里”),“价值”)得到(sbioselect (m1,“名字”,“p2U”),“价值”));栏(muscleFitResults.ParameterEstimates。估计。/ muscleFitInitValues - 1);甘氨胆酸ax =;斧子。XTickLabel = {muscleFitEst.Name};ylabel (估计的相对变化值的);标题(比较报告和葡萄糖估计参数值);

PlasmaInsRule。积极= true;GluProdRule。积极= true;GluRateRule。积极= true;PlasmaInsForcingFcn。积极= false;GluProdForcingFcn。积极= false;GluRateForcingFcn。积极= false;

muscleSims = selectbyname ([muscleInitSim muscleFitSim),…{“等离子Glu浓缩”,“Glu Util”});图;情节(muscleSims (1)。时间,muscleSims (1) . data (: 1),“- - -”,…muscleSims (2)。时间,muscleSims (2) . data (: 1),“——”,…fitData。时间、fitData.PlasmaGluConc“x”);包含(的时间(小时));ylabel (“mg / dl”);传奇(“初始(模拟)”,“估计(模拟)”,“实验”);标题(“血浆葡萄糖配合”);

图;情节(muscleSims (1)。时间,muscleSims (1) . data (:, 2),“- - -”,…muscleSims (2)。时间,muscleSims (2) . data (:, 2),“——”,…fitData。时间、fitData.GluUtil“x”);包含(的时间(小时));ylabel (毫克/分钟的);传奇(“初始(模拟)”,“估计(模拟)”,“实验”);标题(葡萄糖利用合适的);

警告(warnSettings);