Caffeine Effects

Caffeine increase RyR opening sensitivity to luminal and subspace calcium.

In this model, we decrease the mid saturation sub-SR calcium concentration for the opening rate.

using ModelingToolkit
using OrdinaryDiffEq, SteadyStateDiffEq, DiffEqCallbacks
using Plots
using CSV
using DataFrames
using Dates
using CaMKIIModel
using CaMKIIModel: ms
Plots.default(lw=1.5)
@mtkcompile sys = build_neonatal_ecc_sys()
tend = 500* 1000ms
prob = ODEProblem(sys, [], tend)
stimstart = 100* 1000ms
stimend = 300* 1000ms
alg = KenCarp47()
function add_coffee_affect!(integrator)
    integrator.ps[sys.RyRsensitivity] = 10
end
Internal error: stack overflow in type inference of remake(SciMLBase.ODEProblem{Array{Float64, 1}, Tuple{Int64, Int64}, true, ModelingToolkitBase.MTKParameters{Array{Float64, 1}, Array{Float64, 1}, Tuple{}, Tuple{}, Tuple{}, Tuple{}}, SciMLBase.ODEFunction{true, SciMLBase.FullSpecialize, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x9286608c, 0xbd422303, 0x5105814a, 0xb02a1516, 0xa7001fd3), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x2e5e0cc9, 0x8e977946, 0x85221830, 0xe7d7fc02, 0x170cee2f), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkitBase.ObservedFunctionCache{ModelingToolkitBase.System, Nothing}, Nothing, ModelingToolkitBase.System, SciMLBase.OverrideInitData{SciMLBase.NonlinearProblem{Nothing, true, ModelingToolkitBase.MTKParameters{Array{Float64, 1}, StaticArraysCore.SArray{Tuple{0}, Float64, 1, 0}, Tuple{}, Tuple{}, Tuple{}, Tuple{}}, SciMLBase.NonlinearFunction{true, SciMLBase.FullSpecialize, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xea2adeae, 0xdd074767, 0x3d747877, 0x201a9f0c, 0x0aa4b45c), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x3d86c3f8, 0x8cb34fec, 0xe037f03b, 0xf83be1ef, 0xde7515e1), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkitBase.ObservedFunctionCache{ModelingToolkitBase.System, Nothing}, Nothing, ModelingToolkitBase.System, Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardNonlinearProblem, Nothing, Nothing}, typeof(ModelingToolkitBase.update_initializeprob!), Base.ComposedFunction{Base.ComposedFunction{typeof(Base.identity), typeof(ModelingToolkitBase.safe_float)}, SymbolicIndexingInterface.TimeIndependentObservedFunction{ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xee8d4739, 0x1ca06c92, 0x85e813d6, 0x8a4a39d1, 0x4151a370), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xc7e3524e, 0xba2eb296, 0x5a2249fe, 0x4aa94222, 0x59c2d215), Nothing}}}}, ModelingToolkitBase.var"#initprobpmap_split#724"{ModelingToolkitBase.var"#_getter#720"{Tuple{Base.ComposedFunction{ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xb4d5953c, 0x14b4fe81, 0x865f6123, 0xcdae70a1, 0x8a920745), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x5a0161f5, 0x0f1d38ae, 0x61e3cb5a, 0xcc8bd82d, 0xd2e6676d), Nothing}}}}, Base.ComposedFunction{ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x22566f93, 0xab23bab3, 0x38ef30c8, 0xcf441c87, 0xcb86ec35), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xf515ee68, 0x9b29b354, 0xe5f11990, 0xaecc6ec8, 0x2f59ebe5), Nothing}}}}, Base.Returns{Tuple{}}, Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x48e1dbff, 0x79659666, 0x247b7c0c, 0x74a21739, 0x061a95cf), Nothing}, Nothing}}}, Base.ComposedFunction{Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), typeof(Base.identity)}, Base.Fix1{Base.Broadcast.BroadcastFunction{typeof(ModelingToolkitBase.call)}, Tuple{}}}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x48e1dbff, 0x79659666, 0x247b7c0c, 0x74a21739, 0x061a95cf), Nothing}, Nothing}}}}}}, ModelingToolkitBase.InitializationMetadata{ModelingToolkitBase.ReconstructInitializeprob{ModelingToolkitBase.var"#_getter#720"{Tuple{Base.ComposedFunction{ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}, ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xb80930bc, 0x4260a78a, 0x379dc65c, 0x36796f11, 0xc57bcd0e), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x84e2a49f, 0x3f634732, 0x3e3c8d10, 0x8c840230, 0x1dce5821), Nothing}}}}, Base.Returns{StaticArraysCore.SArray{Tuple{0}, Float64, 1, 0}}, Base.Returns{Tuple{}}, Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}}, ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xc0224667, 0x9004e642, 0x7c32774c, 0xb06209e5, 0x97152e08), Nothing}, Nothing}}}, Base.ComposedFunction{Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), typeof(Base.identity)}, Base.Fix1{Base.Broadcast.BroadcastFunction{typeof(ModelingToolkitBase.call)}, Tuple{}}}, ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xc0224667, 0x9004e642, 0x7c32774c, 0xb06209e5, 0x97152e08), Nothing}, Nothing}}}}}, Base.ComposedFunction{typeof(Base.identity), ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x890c50cf, 0xf615c474, 0xf66b0b5a, 0xbd4f7816, 0x011c2e85), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xa9c78342, 0x78ca9315, 0xb8f9f851, 0x2ad3286d, 0x7e34e5e3), Nothing}}}}}, ModelingToolkitBase.GetUpdatedU0{SymbolicIndexingInterface.TimeIndependentObservedFunction{ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xe870e9b2, 0x5a3750d2, 0xc70838d3, 0x8d743208, 0x48aeb939), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x3e1c1569, 0xcfa9999e, 0x320c1624, 0xa9932029, 0x17f66ade), Nothing}}}, SymbolicIndexingInterface.MultipleParametersGetter{SymbolicIndexingInterface.IndexerNotTimeseries, Array{SymbolicIndexingInterface.GetParameterIndex{ModelingToolkitBase.ParameterIndex{SciMLStructures.Initials, Int64}}, 1}, Nothing}}, ModelingToolkitBase.SetInitialUnknowns{SymbolicIndexingInterface.MultipleSetters{Array{SymbolicIndexingInterface.ParameterHookWrapper{SymbolicIndexingInterface.SetParameterIndex{ModelingToolkitBase.ParameterIndex{SciMLStructures.Initials, Int64}}, SymbolicUtils.BasicSymbolicImpl.var"typeof(BasicSymbolicImpl)"{SymbolicUtils.SymReal}}, 1}}}}, Base.Val{true}}, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}).
This might be caused by recursion over very long tuples or argument lists.
add_coffee_affect! (generic function with 1 method)
@unpack Istim = sys
callback = build_stim_callbacks(Istim, stimend; period=1* 1000ms, starttime=stimstart)
SciMLBase.CallbackSet{Tuple{}, Tuple{SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}, SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}}}((), (SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}(100000:1000:300000, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim)), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim), DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}(100000:1000:300000, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim)), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ()), SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}(100000.5:1000.0:300000.5, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim)), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim), DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}(100000.5:1000.0:300000.5, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim)), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ())))

Add caffeine at t = 200 econd

callback_caf = CallbackSet(build_stim_callbacks(Istim, stimend; period=1* 1000ms, starttime=stimstart), PresetTimeCallback(200.0* 1000ms, add_coffee_affect!))
SciMLBase.CallbackSet{Tuple{}, Tuple{SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}, SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}, SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{Vector{Float64}, typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(Main.var"##225".add_coffee_affect!)}, typeof(Main.var"##225".add_coffee_affect!), DiffEqCallbacks.PresetTimeFunction{Vector{Float64}, typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(Main.var"##225".add_coffee_affect!)}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}}}((), (SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}(100000:1000:300000, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim)), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim), DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}(100000:1000:300000, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim)), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ()), SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}(100000.5:1000.0:300000.5, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim)), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim), DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}(100000.5:1000.0:300000.5, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim)), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ()), SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{Vector{Float64}, typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(Main.var"##225".add_coffee_affect!)}, typeof(Main.var"##225".add_coffee_affect!), DiffEqCallbacks.PresetTimeFunction{Vector{Float64}, typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(Main.var"##225".add_coffee_affect!)}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{Vector{Float64}, typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(Main.var"##225".add_coffee_affect!)}([200000.0], true, SciMLBase.INITIALIZE_DEFAULT, Main.var"##225".add_coffee_affect!), Main.var"##225".add_coffee_affect!, DiffEqCallbacks.PresetTimeFunction{Vector{Float64}, typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(Main.var"##225".add_coffee_affect!)}([200000.0], true, SciMLBase.INITIALIZE_DEFAULT, Main.var"##225".add_coffee_affect!), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ())))

Single-dose caffeine

@time sol = solve(prob, alg; callback)
@time sol_caf = solve(prob, alg; callback=callback_caf)
Internal error: stack overflow in type inference of kwcall(NamedTuple{(:callback,), Tuple{SciMLBase.CallbackSet{Tuple{}, Tuple{SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{Base.StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{Base.StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}, SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{Base.StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{Base.StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}}}}}, typeof(CommonSolve.solve), SciMLBase.ODEProblem{Array{Float64, 1}, Tuple{Int64, Int64}, true, ModelingToolkitBase.MTKParameters{Array{Float64, 1}, Array{Float64, 1}, Tuple{}, Tuple{}, Tuple{}, Tuple{}}, SciMLBase.ODEFunction{true, SciMLBase.FullSpecialize, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x9286608c, 0xbd422303, 0x5105814a, 0xb02a1516, 0xa7001fd3), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x2e5e0cc9, 0x8e977946, 0x85221830, 0xe7d7fc02, 0x170cee2f), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkitBase.ObservedFunctionCache{ModelingToolkitBase.System, Nothing}, Nothing, ModelingToolkitBase.System, SciMLBase.OverrideInitData{SciMLBase.NonlinearProblem{Nothing, true, ModelingToolkitBase.MTKParameters{Array{Float64, 1}, StaticArraysCore.SArray{Tuple{0}, Float64, 1, 0}, Tuple{}, Tuple{}, Tuple{}, Tuple{}}, SciMLBase.NonlinearFunction{true, SciMLBase.FullSpecialize, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xea2adeae, 0xdd074767, 0x3d747877, 0x201a9f0c, 0x0aa4b45c), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x3d86c3f8, 0x8cb34fec, 0xe037f03b, 0xf83be1ef, 0xde7515e1), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkitBase.ObservedFunctionCache{ModelingToolkitBase.System, Nothing}, Nothing, ModelingToolkitBase.System, Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardNonlinearProblem, Nothing, Nothing}, typeof(ModelingToolkitBase.update_initializeprob!), Base.ComposedFunction{Base.ComposedFunction{typeof(Base.identity), typeof(ModelingToolkitBase.safe_float)}, SymbolicIndexingInterface.TimeIndependentObservedFunction{ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xee8d4739, 0x1ca06c92, 0x85e813d6, 0x8a4a39d1, 0x4151a370), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xc7e3524e, 0xba2eb296, 0x5a2249fe, 0x4aa94222, 0x59c2d215), Nothing}}}}, ModelingToolkitBase.var"#initprobpmap_split#724"{ModelingToolkitBase.var"#_getter#720"{Tuple{Base.ComposedFunction{ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xb4d5953c, 0x14b4fe81, 0x865f6123, 0xcdae70a1, 0x8a920745), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x5a0161f5, 0x0f1d38ae, 0x61e3cb5a, 0xcc8bd82d, 0xd2e6676d), Nothing}}}}, Base.ComposedFunction{ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x22566f93, 0xab23bab3, 0x38ef30c8, 0xcf441c87, 0xcb86ec35), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xf515ee68, 0x9b29b354, 0xe5f11990, 0xaecc6ec8, 0x2f59ebe5), Nothing}}}}, Base.Returns{Tuple{}}, Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x48e1dbff, 0x79659666, 0x247b7c0c, 0x74a21739, 0x061a95cf), Nothing}, Nothing}}}, Base.ComposedFunction{Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), typeof(Base.identity)}, Base.Fix1{Base.Broadcast.BroadcastFunction{typeof(ModelingToolkitBase.call)}, Tuple{}}}, ModelingToolkitBase.ObservedWrapper{false, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x48e1dbff, 0x79659666, 0x247b7c0c, 0x74a21739, 0x061a95cf), Nothing}, Nothing}}}}}}, ModelingToolkitBase.InitializationMetadata{ModelingToolkitBase.ReconstructInitializeprob{ModelingToolkitBase.var"#_getter#720"{Tuple{Base.ComposedFunction{ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}, ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xb80930bc, 0x4260a78a, 0x379dc65c, 0x36796f11, 0xc57bcd0e), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x84e2a49f, 0x3f634732, 0x3e3c8d10, 0x8c840230, 0x1dce5821), Nothing}}}}, Base.Returns{StaticArraysCore.SArray{Tuple{0}, Float64, 1, 0}}, Base.Returns{Tuple{}}, Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), ModelingToolkitBase.PConstructorApplicator{typeof(Base.identity)}}, ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xc0224667, 0x9004e642, 0x7c32774c, 0xb06209e5, 0x97152e08), Nothing}, Nothing}}}, Base.ComposedFunction{Base.ComposedFunction{Base.Fix1{typeof(Base.Broadcast.broadcast), typeof(Base.identity)}, Base.Fix1{Base.Broadcast.BroadcastFunction{typeof(ModelingToolkitBase.call)}, Tuple{}}}, ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xc0224667, 0x9004e642, 0x7c32774c, 0xb06209e5, 0x97152e08), Nothing}, Nothing}}}}}, Base.ComposedFunction{typeof(Base.identity), ModelingToolkitBase.ObservedWrapper{true, ModelingToolkitBase.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x890c50cf, 0xf615c474, 0xf66b0b5a, 0xbd4f7816, 0x011c2e85), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xa9c78342, 0x78ca9315, 0xb8f9f851, 0x2ad3286d, 0x7e34e5e3), Nothing}}}}}, ModelingToolkitBase.GetUpdatedU0{SymbolicIndexingInterface.TimeIndependentObservedFunction{ModelingToolkitBase.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0xe870e9b2, 0x5a3750d2, 0xc70838d3, 0x8d743208, 0x48aeb939), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkitBase.var"#_RGF_ModTag", ModelingToolkitBase.var"#_RGF_ModTag", (0x3e1c1569, 0xcfa9999e, 0x320c1624, 0xa9932029, 0x17f66ade), Nothing}}}, SymbolicIndexingInterface.MultipleParametersGetter{SymbolicIndexingInterface.IndexerNotTimeseries, Array{SymbolicIndexingInterface.GetParameterIndex{ModelingToolkitBase.ParameterIndex{SciMLStructures.Initials, Int64}}, 1}, Nothing}}, ModelingToolkitBase.SetInitialUnknowns{SymbolicIndexingInterface.MultipleSetters{Array{SymbolicIndexingInterface.ParameterHookWrapper{SymbolicIndexingInterface.SetParameterIndex{ModelingToolkitBase.ParameterIndex{SciMLStructures.Initials, Int64}}, SymbolicUtils.BasicSymbolicImpl.var"typeof(BasicSymbolicImpl)"{SymbolicUtils.SymReal}}, 1}}}}, Base.Val{true}}, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEqSDIRK.KenCarp47{0, ADTypes.AutoForwardDiff{nothing, Nothing}, Nothing, OrdinaryDiffEqNonlinearSolve.NLNewton{Base.Rational{Int64}, Base.Rational{Int64}, Base.Rational{Int64}, Nothing}, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Base.Val{:forward}(), true, nothing}).
This might be caused by recursion over very long tuples or argument lists.
  6.965580 seconds (16.97 M allocations: 1.058 GiB, 3.35% gc time, 89.13% compilation time)
  2.296596 seconds (3.65 M allocations: 260.325 MiB, 14.38% gc time, 67.60% compilation time)
retcode: Success
Interpolation: 3rd order Hermite
t: 8775-element Vector{Float64}:
      0.0
      0.019333125036189135
      0.09098129266634847
      0.2073558192440938
      0.45611905918185225
      1.0472561699066012
      2.034266647380669
      3.451776427609829
      6.733791989961038
     12.450116263175316
      ⋮
 400587.17244288063
 410672.0368411475
 421716.443324556
 434008.4864986264
 450151.06172503775
 462974.2378146922
 480604.5598697531
 498234.88192481396
 500000.0
u: 8775-element Vector{Vector{Float64}}:
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 ⋮
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 [53.68969895555704, 52.45930821096362, 0.10375134702788089, 0.18018857979913805, 0.0004024511106289713, 0.0013824173214120861, 0.0017372505736557853, 0.0026890845193416053, 0.00184290284221071, 0.9996615022336891  …  0.12841809401114215, 0.12841793090933964, 0.1284177601271423, 0.12841758133926034, 0.12841739419941872, 0.12842054763459895, 0.12841719833863668, 151980.7498696428, 12898.096139985279, -69.04715408513664]
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i = (sys.t / 1000, sys.vm)
plot(sol, idxs=i, title="Action potential", lab="Ctl", tspan=(198* 1000ms, 205* 1000ms))
plot!(sol_caf, idxs=i, lab="Caf", tspan=(198* 1000ms, 205* 1000ms), ylabel="Voltage (mV)", xlabel="Time (s)")

i = (sys.t / 1000, sys.Cai_sub_SR * 1000)
plot(sol, idxs=i, title="Calcium transient (During caffeine addition)", lab="Ctl", tspan=(198* 1000ms, 205* 1000ms))
plot!(sol_caf, idxs=i, tspan=(198* 1000ms, 205* 1000ms), lab="Caf", ylabel="Subspace calcium (nM)", xlabel="Time (s)")

i = (sys.t / 1000, sys.PO1RyR)
plot(sol, idxs=i, title="RyR open (During caffeine addition)", lab="Ctl", tspan=(198* 1000ms, 205* 1000ms))
plot!(sol_caf, idxs=i, tspan=(198* 1000ms, 205* 1000ms), lab="Caf", ylabel="Open probability", ylims=(0, 1), xlabel="Time (s)")

i = (sys.t / 1000, sys.Cai_sub_SR * 1000)
plot(sol, idxs=i, title="Calcium transient (After caffeine addition)", lab="Ctl", ylabel="Subspace calcium (nM)", tspan=(198* 1000ms, 205* 1000ms))
plot!(sol_caf, idxs=i, lab="Caf", xlabel="Time (s)", tspan=(198* 1000ms, 205* 1000ms))

i = (sys.t / 1000, sys.CaJSR)
plot(sol, idxs=i, title="SR Calcium (During caffeine addition)", lab="Ctl", ylabel="SR calcium (μM)", tspan=(198* 1000ms, 205* 1000ms))
plot!(sol_caf, idxs=i, tspan=(198* 1000ms, 205* 1000ms), lab="Caf", ylims=(0, 850), xlabel="Time (s)")

i = (sys.t / 1000, sys.Jrel)
plot(sol, idxs=sys.Jrel, title="Ca flux", lab="Ctl  (Jrel)", tspan=(198* 1000ms, 205* 1000ms))
plot!(sol_caf, idxs=sys.Jrel, lab="Caf (Jrel)", tspan=(198* 1000ms, 205* 1000ms), ylabel="μM/ms", xlabel="Time (s)")

i = (sys.t / 1000, sys.CaMKAct * 100)
plot(sol, idxs=i, title="Active CaMKII", lab="Ctl")
plot!(sol_caf, idxs=i, lab="Caf", ylabel="CaMKII activity (%)", xlabel="Time (s)")

Caffeine and electrophysiology

  • Add caffeine in the beginning of the simulation.
  • Add caffeine and nifedipine in the beginning of the simulation (nifedipine blocks 90% of L-type calcium channel).
@mtkcompile sys = build_neonatal_ecc_sys()
tend = 205* 1000ms
stimstart = 30* 1000ms
stimend = 120* 1000ms
alg = KenCarp47()
@unpack Istim = sys
callback = build_stim_callbacks(Istim, stimend; period=1* 1000ms, starttime=stimstart)
SciMLBase.CallbackSet{Tuple{}, Tuple{SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}, SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}}}((), (SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}(30000:1000:120000, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim)), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim), DiffEqCallbacks.PresetTimeFunction{StepRange{Int64, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}}(30000:1000:120000, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#15#17"{Float64, Float64, Symbolics.Num}(-80.0, 0.5, Istim)), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ()), SciMLBase.DiscreteCallback{DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}, DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}, typeof(SciMLBase.FINALIZE_DEFAULT), Nothing, Tuple{}}(DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}(30000.5:1000.0:120000.5, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim)), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim), DiffEqCallbacks.PresetTimeFunction{StepRangeLen{Float64, Base.TwicePrecision{Float64}, Base.TwicePrecision{Float64}, Int64}, typeof(SciMLBase.INITIALIZE_DEFAULT), CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}}(30000.5:1000.0:120000.5, true, SciMLBase.INITIALIZE_DEFAULT, CaMKIIModel.var"#16#18"{Float64, Float64, Symbolics.Num}(0.0, 0.5, Istim)), SciMLBase.FINALIZE_DEFAULT, Bool[1, 1], nothing, ())))
prob = ODEProblem(sys, [], tend)
prob_caf = ODEProblem(sys, [sys.RyRsensitivity => 10], tend)
gCaL = prob.ps[sys.GCaL]
prob_nif_caf = ODEProblem(sys, [sys.RyRsensitivity => 10, sys.GCaL => 0.1 * gCaL], tend)
ODEProblem with uType Vector{Float64} and tType Int64. In-place: true
Initialization status: FULLY_DETERMINED
Non-trivial mass matrix: false
timespan: (0, 205000)
u0: 75-element Vector{Float64}:
    830.0
    830.0
      0.0026
      0.07192
      0.07831
      0.26081
      0.00977
      0.00188
      0.09243
      0.22156
      ⋮
      0.12113
      0.12113
      0.12113
      0.12113
      0.12113
      0.12113
 150952.75035000002
  13838.37602
    -68.79268
ssalg = DynamicSS(alg)
sprob_caf = SteadyStateProblem(prob_caf)
sssol = solve(sprob_caf, ssalg; abstol=1e-10, reltol=1e-10)
@time sol = solve(prob, alg; callback)
@time sol_caf = solve(remake(prob_caf, u0=sssol.u), alg; callback)
@time sol_nif_caf = solve(remake(prob_nif_caf, u0=sssol.u), alg; callback)
  0.403478 seconds (102.47 k allocations: 14.016 MiB, 15.85% compilation time)
  0.381286 seconds (141.83 k allocations: 16.395 MiB, 11.80% compilation time)
  0.202758 seconds (20.06 k allocations: 6.065 MiB)
retcode: Success
Interpolation: 3rd order Hermite
t: 2780-element Vector{Float64}:
      0.0
      0.18425349204908287
      0.9882055440931703
      4.071300209939429
     11.46900363127737
     25.163391754727833
     49.58670648890126
     83.36471305617223
    137.50492821590353
    206.18532698897792
      ⋮
 144181.39523015163
 149368.97852564527
 154556.56182113892
 161066.57434647472
 169004.00812550154
 178027.60932908955
 187359.8633948591
 196692.11746062865
 205000.0
u: 2780-element Vector{Vector{Float64}}:
 [57.618777388454895, 56.49644192239733, 0.08793893392655225, 0.14609625273663496, 0.0005608497572583467, 0.0017638178923786922, 0.001952324284451103, 0.003021867942239143, 0.0023071179389667178, 0.9995225713580512  …  0.12238816920442885, 0.12238816850764403, 0.12238816777947442, 0.12238816701857597, 0.1223881662235179, 0.12238818047047396, 0.12238816539277567, 152639.94664399358, 12238.9437256598, -67.47396690550634]
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 [57.61877620081261, 56.49644310744856, 0.08793799588573543, 0.14610370785432641, 0.0005597589794945528, 0.0017647644444420524, 0.001949034074709481, 0.0029937441080779715, 0.0023067836133336367, 0.9995225923330359  …  0.12238601235600448, 0.12238625655225205, 0.12238644892663932, 0.12238659202466935, 0.12238668744022282, 0.12223941379842311, 0.12238673577400197, 152639.94717546157, 12238.944264393487, -67.60292744527437]
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 [57.61637165104209, 56.49863060070004, 0.0872229136334266, 0.1463363480725024, 0.0005498662810307825, 0.001768360688259101, 0.001903568224353119, 0.002924472334438665, 0.0022970387267103685, 0.9995232165417219  …  0.12207192404915698, 0.12207377811184357, 0.12207519649096284, 0.1220761656693964, 0.12207667117042414, 0.12175533190103574, 0.12207669747921929, 152639.9593860722, 12238.96652572896, -67.91477834585092]
 [57.6152935693644, 56.50425641333213, 0.08638564264342871, 0.1465796710452761, 0.0005466777415151073, 0.0017641266469406282, 0.0018905542505776396, 0.0029146198109186983, 0.0022874146260824873, 0.9995238612620077  …  0.12174570438831185, 0.12174709334931855, 0.12174801848829155, 0.12174846474791351, 0.12174841611203917, 0.1214404404322544, 0.12174785552678653, 152639.9718974481, 12238.98817904568, -67.9596718937026]
 [57.6183675849662, 56.515999221746625, 0.08533788302524507, 0.14690182858038858, 0.0005436577969599425, 0.0017572312334396265, 0.0018848556557308626, 0.0029090189408789687, 0.0022753028081561348, 0.9995247197921024  …  0.12133823511590476, 0.12133887954724662, 0.12133905632895413, 0.12133874991465882, 0.12133794378236806, 0.12106210899295555, 0.12133662035412547, 152639.98859269003, 12239.013597497958, -67.98548412830179]
 ⋮
 [62.652573045605266, 61.646171958384635, 0.07224454834331336, 0.15847385742655354, 0.0004936479815544933, 0.001606262283470731, 0.0018663816076682628, 0.0028888395760127785, 0.0021163700003030616, 0.9989428072816653  …  0.11569574858502678, 0.11569574195593747, 0.11569573525040072, 0.1156957284617803, 0.11569572158295599, 0.11569598071491531, 0.11569571460628214, 152693.20692832794, 12185.542686077613, -68.08133078557987]
 [62.652026053739874, 61.645497932351745, 0.07225823163212733, 0.15848429880312256, 0.00049357276549257, 0.0016062007594112434, 0.0018662891886993692, 0.0028886876271675883, 0.0021161867256119958, 0.9994207212230524  …  0.11570167396211267, 0.11570167792047077, 0.11570168200664581, 0.11570168622380085, 0.11570169057518881, 0.11570159328054563, 0.11570169506415774, 152692.88964452266, 12185.859357540194, -68.08199155051913]
 [62.650571390509526, 61.644004408323845, 0.07226371295440556, 0.1584996327445595, 0.0004935092013158956, 0.0016059398591847754, 0.0018661851862416103, 0.00288853677748981, 0.0021159467509962817, 0.9995408847038849  …  0.1157040690997419, 0.11570407295085863, 0.11570407700540308, 0.1157040812721107, 0.11570408576029917, 0.11570402209171622, 0.11570409047991685, 152692.5794051068, 12186.16961162689, -68.08274146099022]
 [62.64725169044916, 61.640611758894046, 0.07227308389144373, 0.15851676544308105, 0.0004934070392277976, 0.0016056614763505657, 0.0018660706763621976, 0.0028883604230413714, 0.002115692401091527, 0.9995739077751089  …  0.11570831518315262, 0.11570831952271897, 0.1157083240458691, 0.11570832876055391, 0.11570833367523754, 0.11570823874696001, 0.11570833879893964, 152692.19978695372, 12186.549279787254, -68.08356930926975]
 [62.64357777180478, 61.636865645289625, 0.07228264570402333, 0.158538732899126, 0.0004933160284007041, 0.0016054706712633018, 0.0018659303887693546, 0.0028881405514758593, 0.0021153915001962766, 0.9995804494949742  …  0.11571259763548829, 0.11571260151387738, 0.11571260557307288, 0.11571260982083162, 0.11571261426541268, 0.11571253794393295, 0.11571261891561871, 152691.75031274336, 12186.998878132012, -68.08459222495891]
 [62.63935369975769, 61.63255468963983, 0.07229430277537911, 0.1585621747716218, 0.0004932531455123794, 0.0016051987378701302, 0.0018657789600968128, 0.002887912506723134, 0.0021150685069392214, 0.9995813979272802  …  0.1157176209122203, 0.11571762485176564, 0.11571762896133128, 0.11571763324830073, 0.11571763772054025, 0.11571755339895218, 0.11571764238643832, 152691.2590197215, 12187.490290484182, -68.08568810833474]
 [62.63538993988801, 61.62850209298028, 0.07230519863015906, 0.1585853894819076, 0.0004931055597387262, 0.0016049718240104393, 0.001865631394566626, 0.002887676403196989, 0.002114744611765609, 0.9995816509387273  …  0.11572290385089412, 0.11572290836469049, 0.11572291304205835, 0.11572291789019275, 0.11572292291675317, 0.11572281050672811, 0.11572292812990155, 152690.77037774093, 12187.978994630002, -68.08676043202512]
 [62.631397196703354, 61.62443799411353, 0.07231461568720514, 0.15860772507669016, 0.000492977389810494, 0.0016046603015617905, 0.0018654810507465036, 0.002887445736046455, 0.0021144115514490887, 0.999581609813376  …  0.11572721782012226, 0.11572722147481317, 0.11572722528537199, 0.1157272292585563, 0.1157272334015592, 0.11572715394258852, 0.11572723772204498, 152690.30174582274, 12188.44778457397, -68.08783649044501]
 [62.62807363842393, 61.62104717582852, 0.07232337778004111, 0.15862690685627776, 0.0004928828936758953, 0.0016044338678553882, 0.001865357080040347, 0.0028872544708061104, 0.002114138526294777, 0.9995817067155186  …  0.11573121099327205, 0.11573121442581198, 0.11573121800939021, 0.11573122175045313, 0.11573122565586122, 0.11573115377610446, 0.11573122973292282, 152689.9007672646, 12188.848851665687, -68.08873136379842]
i = (sys.t / 1000, sys.vm)
tspan = (100* 1000ms, 102* 1000ms)
plot(sol, idxs=i, title="Action potential", lab="Ctl"; tspan)
plot!(sol_caf, idxs=i, lab="Caf"; tspan)
plot!(sol_nif_caf, idxs=i, lab="Caf + Nif", tspan=tspan, ylabel="Voltage (mV)", xlabel="Time (s)")

savefig("caf-ap.pdf")
"/home/github/actions-runner-1/_work/camkii-cardiomyocyte-model/camkii-cardiomyocyte-model/docs/caf-ap.pdf"
i = (sys.t / 1000, sys.Cai_sub_SR * 1000)
tspan = (100* 1000ms, 102* 1000ms)
plot(sol, idxs=i, title="Calcium transient", lab="Ctl"; tspan)
plot!(sol_caf, idxs=i, lab="Caf"; tspan)
plot!(sol_nif_caf, idxs=i, lab="Caf + Nif", ylabel="Subspace calcium (nM)", xlabel="Time (s)"; tspan)

savefig("caf-cat.pdf")
"/home/github/actions-runner-1/_work/camkii-cardiomyocyte-model/camkii-cardiomyocyte-model/docs/caf-cat.pdf"
i = (sys.t / 1000, sys.CaJSR)
tspan = (100* 1000ms, 102* 1000ms)
plot(sol, idxs=i, title="SR Calcium", lab="Ctl", ylabel="SR calcium (μM)"; tspan)
plot!(sol_caf, idxs=i, lab="Caf"; tspan)
plot!(sol_nif_caf, idxs=i, lab="Caf + Nif", ylims=(0, 850), xlabel="Time (s)"; tspan)

CaMKII activities

Simulations

i = (sys.t / 1000, sys.CaMKAct * 100)
plot(sol, idxs=i, title="Simulation", lab="Ctl")
plot!(sol_caf, idxs=i, lab="Caf")
plot!(sol_nif_caf, idxs=i, lab="Caf + Nif", ylabel="CaMKII active fraction (%)", xlabel="Time (s)")

savefig("caf-camkact.pdf")
"/home/github/actions-runner-1/_work/camkii-cardiomyocyte-model/camkii-cardiomyocyte-model/docs/caf-camkact.pdf"

Experiments

chemicaldf = CSV.read(joinpath(@__DIR__, "data/CaMKAR-chemical.csv"), DataFrame)
ts = Dates.value.(chemicaldf[!, "Time"]) ./ 10^9
ctl = chemicaldf[!, "Ctrl Mean"]
ctl_error = chemicaldf[!, "Ctrl SD"] ./ sqrt.(chemicaldf[!, "Ctrl N"])

caf = chemicaldf[!, "caffeine 20mM Mean"]
caf_error = chemicaldf[!, "caffeine 20mM SD"] ./ sqrt.(chemicaldf[!, "caffeine 20mM N"])

plot(ts, ctl, yerr=ctl_error, lab="Control", color=:blue, markerstrokecolor=:blue)
plot!(ts, caf, yerr=caf_error, lab="Caffeine 20mM", color=:red, markerstrokecolor=:red)
plot!(xlabel="Time (s)", ylabel="CaMKII activity (A.U.)", title= "Experiment")

savefig("caf-exp.pdf")
"/home/github/actions-runner-1/_work/camkii-cardiomyocyte-model/camkii-cardiomyocyte-model/docs/caf-exp.pdf"

Runtime information

using InteractiveUtils
InteractiveUtils.versioninfo()
Julia Version 1.10.10
Commit 95f30e51f41 (2025-06-27 09:51 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 32 × Intel(R) Core(TM) i9-14900K
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, goldmont)
Threads: 2 default, 0 interactive, 1 GC (on 32 virtual cores)
Environment:
  JULIA_CONDAPKG_OFFLINE = true
  LD_LIBRARY_PATH = /home/github/actions-runner-1/_work/_tool/Python/3.14.3/x64/lib
  JULIA_PROJECT = /home/github/actions-runner-1/_work/camkii-cardiomyocyte-model/camkii-cardiomyocyte-model/Project.toml
  JULIA_CONDAPKG_BACKEND = Null
  JULIA_NUM_THREADS = 2
  JULIA_CI = true
  JULIA_DEPOT_PATH = /home/github/.julia:/home/github/actions-runner-1/_work/_tool/julia/1.10.10/x64/local/share/julia:/home/github/actions-runner-1/_work/_tool/julia/1.10.10/x64/share/julia
  JULIA_LOAD_PATH = @:@v#.#:@stdlib
using Pkg
Pkg.status()
Project CaMKIIModel v0.7.0
Status `~/actions-runner-1/_work/camkii-cardiomyocyte-model/camkii-cardiomyocyte-model/Project.toml`
  [336ed68f] CSV v0.10.16
⌃ [5a033b19] CurveFit v1.4.0
  [a93c6f00] DataFrames v1.8.1
  [459566f4] DiffEqCallbacks v4.12.0
  [f6369f11] ForwardDiff v1.3.2
  [682c06a0] JSON v1.4.0
  [23fbe1c1] Latexify v0.16.10
  [98b081ad] Literate v2.21.0
  [2fda8390] LsqFit v0.15.1
  [1862ce21] MarkdownTables v1.1.0
  [961ee093] ModelingToolkit v11.11.0
  [77ba4419] NaNMath v1.1.3
  [1dea7af3] OrdinaryDiffEq v6.108.0
  [91a5bcdd] Plots v1.41.6
  [0d7ed370] StaticArrayInterface v1.9.0
  [2913bbd2] StatsBase v0.34.10
  [9672c7b4] SteadyStateDiffEq v2.9.0
  [bd369af6] Tables v1.12.1
  [ea8e919c] SHA v0.7.0
Info Packages marked with ⌃ have new versions available and may be upgradable.

This notebook was generated using Literate.jl.

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