Doxorubicin addition test

Doxorubicin addition test#

using ProgressLogging
using OrdinaryDiffEq
using ModelingToolkit
using Plots
using DisplayAs: PNG
using ECMEDox
using ECMEDox: second, mM, Hz, μM, build_stim_callbacks
Plots.default(lw=1.5, size=(600, 600))

tend = 1000.0second
bcl = 1second
@named sys = build_model(; bcl=0, tend)
@unpack DOX = sys
sts = unknowns(sys)
u0 = build_u0(sys)
alg = KenCarp47()
stim = build_stim_callbacks(sys.iStim, tend)
opts = (; reltol=1e-6, abstol=1e-6, progress=true, callback=stim)
prob = ODEProblem(sys, u0, tend)

┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587
┌ Warning: Did not converge after `maxiters = 0` substitutions. Either there is a cycle in the rules or `maxiters` needs to be higher.
└ @ Symbolics ~/.julia/packages/Symbolics/sc64L/src/variable.jl:587

ODEProblem with uType Vector{Float64} and tType Float64. In-place: true
Initialization status: FULLY_DETERMINED
Non-trivial mass matrix: false
timespan: (0.0, 1.0e6)
u0: 63-element Vector{Float64}:
3553843722148506
59478245522047
9034833706153
892129267047379
65695610700525
9114480160471111
19409331392839435
8091362833657
9687795381885
 144753.168650273
      ⋮
87929617274456
91725390039272
3823360869799
3763898444155
024427237952508167
995660402659126
9070224132868452
0006449826277658302
000865771566630073

The collapse of MMP is between 290uM and 300uM of DOX

doxrange = 290μM:1μM:300μM
prob_func = (prob, i, repeat) -> begin
    prob.ps[DOX] = doxrange[i]
    prob
end

eprob = EnsembleProblem(prob; prob_func)
@time sim = solve(eprob, alg; trajectories=length(doxrange), opts...)

232.330315 seconds (57.50 M allocations: 9.650 GiB, 3.41% gc time, 4.27% compilation time)

EnsembleSolution Solution of length 11 with uType:
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Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.ObservedFunctionCache{ModelingToolkit.System}, Nothing, ModelingToolkit.System, Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardNonlinearProblem}, typeof(ModelingToolkit.update_initializeprob!), ComposedFunction{typeof(identity), SymbolicIndexingInterface.TimeIndependentObservedFunction{ModelingToolkit.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xde893636, 0x92a9e8b8, 0xcf745773, 0xda2db8ff, 0x691a956e), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x3d4ec4c7, 0x98b5a1a3, 0x3a82cad5, 0x4534d8bf, 0x775ed0ac), Nothing}}}}, 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RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xd797c90e, 0x1873d50b, 0x468ad65d, 0xfc61e11c, 0x4b93242b), Nothing}}}}, Returns{StaticArraysCore.SizedVector{0, Float64, Vector{Float64}}}, Returns{Tuple{}}, Returns{Tuple{}}, Returns{Tuple{}}}}, ComposedFunction{typeof(identity), SymbolicIndexingInterface.MultipleGetters{SymbolicIndexingInterface.ContinuousTimeseries, Vector{Any}}}}, ModelingToolkit.GetUpdatedU0{SymbolicIndexingInterface.MultipleGetters{SymbolicIndexingInterface.ContinuousTimeseries, Vector{SymbolicUtils.BasicSymbolic{Real}}}, SymbolicIndexingInterface.MultipleParametersGetter{SymbolicIndexingInterface.IndexerNotTimeseries, Vector{SymbolicIndexingInterface.GetParameterIndex{ModelingToolkit.ParameterIndex{SciMLStructures.Initials, Int64}}}, Nothing}}, 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:__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x3d4ec4c7, 0x98b5a1a3, 0x3a82cad5, 0x4534d8bf, 0x775ed0ac), Nothing}}}}, ModelingToolkit.var"#initprobpmap_split#896"{ModelingToolkit.var"#_getter#892"{Tuple{ComposedFunction{ModelingToolkit.PConstructorApplicator{typeof(identity)}, ModelingToolkit.ObservedWrapper{false, ModelingToolkit.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xa2d2f983, 0xc85e53cf, 0xf09b4da6, 0x06aaf466, 0x0ad6c697), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x5fe26b16, 0x07b3ce88, 0xe7f5efc1, 0x225ac943, 0xc3a22725), Nothing}}}}, ComposedFunction{ModelingToolkit.PConstructorApplicator{typeof(identity)}, ModelingToolkit.ObservedWrapper{false, ModelingToolkit.GeneratedFunctionWrapper{(2, 2, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x5a59d12d, 0x0637e393, 0x80a0d2f3, 0x7e5ca1c6, 0xc006c3c5), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x3ba61207, 0x702e54cc, 0x05ef03ea, 0x2419184a, 0xd5e7f3b1), Nothing}}}}, Returns{Tuple{}}, Returns{Tuple{}}, Returns{Tuple{}}}}}, ModelingToolkit.InitializationMetadata{ModelingToolkit.ReconstructInitializeprob{ModelingToolkit.var"#_getter#892"{Tuple{ComposedFunction{ModelingToolkit.PConstructorApplicator{typeof(identity)}, ModelingToolkit.ObservedWrapper{true, ModelingToolkit.GeneratedFunctionWrapper{(2, 3, true), RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x45428fc1, 0x6176196e, 0x4628f23e, 0x156e18cb, 0x9c65e18f), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :__mtk_arg_1, :___mtkparameters___, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xd797c90e, 0x1873d50b, 0x468ad65d, 0xfc61e11c, 0x4b93242b), Nothing}}}}, Returns{StaticArraysCore.SizedVector{0, Float64, Vector{Float64}}}, Returns{Tuple{}}, Returns{Tuple{}}, Returns{Tuple{}}}}, ComposedFunction{typeof(identity), SymbolicIndexingInterface.MultipleGetters{SymbolicIndexingInterface.ContinuousTimeseries, Vector{Any}}}}, ModelingToolkit.GetUpdatedU0{SymbolicIndexingInterface.MultipleGetters{SymbolicIndexingInterface.ContinuousTimeseries, Vector{SymbolicUtils.BasicSymbolic{Real}}}, SymbolicIndexingInterface.MultipleParametersGetter{SymbolicIndexingInterface.IndexerNotTimeseries, Vector{SymbolicIndexingInterface.GetParameterIndex{ModelingToolkit.ParameterIndex{SciMLStructures.Initials, Int64}}}, Nothing}}, ModelingToolkit.SetInitialUnknowns{SymbolicIndexingInterface.MultipleSetters{Vector{SymbolicIndexingInterface.ParameterHookWrapper{SymbolicIndexingInterface.SetParameterIndex{ModelingToolkit.ParameterIndex{SciMLStructures.Initials, Int64}}, SymbolicUtils.BasicSymbolic{Real}}}}}}, Val{true}}, Nothing}, Float64, ModelingToolkit.MTKParameters{Vector{Float64}, Vector{Float64}, Tuple{}, Tuple{}, Tuple{}, Tuple{}}}, jcType, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, LinearSolve.DefaultLinearSolver, LinearSolve.DefaultLinearSolverInit{LinearAlgebra.LU{Float64, Matrix{Float64}, Vector{Int64}}, LinearAlgebra.QRCompactWY{Float64, Matrix{Float64}, Matrix{Float64}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Tuple{LinearAlgebra.LU{Float64, Matrix{Float64}, Vector{Int64}}, Vector{Int64}}, Tuple{LinearAlgebra.LU{Float64, Matrix{Float64}, Vector{Int64}}, Vector{Int64}}, Nothing, Nothing, Nothing, LinearAlgebra.SVD{Float64, Float64, Matrix{Float64}, Vector{Float64}}, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}, Tuple{LinearAlgebra.LU{Float64, Matrix{Float64}, Vector{Int32}}, Base.RefValue{Int32}}, Tuple{LinearAlgebra.LU{Float64, Matrix{Float64}, Vector{Int64}}, Base.RefValue{Int64}}, LinearAlgebra.QRPivoted{Float64, Matrix{Float64}, Vector{Float64}, Vector{Int64}}, Nothing, Nothing}, LinearSolve.InvPreconditioner{LinearAlgebra.Diagonal{Float64, Vector{Float64}}}, LinearAlgebra.Diagonal{Float64, Vector{Float64}}, Float64, Bool, LinearSolve.LinearSolveAdjoint{Missing}}}, Float64} where jcType<:Tuple{DifferentiationInterfaceForwardDiffExt.ForwardDiffTwoArgJacobianPrep{Nothing, C, Tuple{}} where C<:(ForwardDiff.JacobianConfig{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, _A, <:Tuple{Array{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, _A}, 1} where _A, Array{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, _A}, 1} where _A}} where _A), DifferentiationInterfaceForwardDiffExt.ForwardDiffTwoArgJacobianPrep{Nothing, C, Tuple{}} where C<:(ForwardDiff.JacobianConfig{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, _A, <:Tuple{Array{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, _A}, 1} where _A, Array{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, Float64}, Float64, _A}, 1} where _A}} where _A)}))

fig = plot(title="MMP")
for (i, dox) in enumerate(doxrange)
    plot!(fig, sim[i], idxs=(sys.t/1000, sys.dpsi), lab="DOX = $(dox) μM")
end
plot!(fig, ylabel="mV", xlabel="Time (s)") |> PNG

_images/581d36355c9938fa2d052ca4a56e90385bbc6d46fff5db3fbc31e1f5b5a5a4e7.png

fig = plot(title="ATP")
for (i, dox) in enumerate(doxrange)
    plot!(fig, sim[i], idxs=(sys.t/1000, sys.atp_i), lab="DOX = $(dox) μM")
end
plot!(fig, ylabel="Conc. (μM)", xlabel="Time (s)", legend=:bottomright, ylim=(0, 8mM)) |> PNG

_images/b2dc128508cdadf8229e8b6b0fc9c1e57c3788d85224eaa70b6833559bb8413f.png

fig = plot(title="Cytosolic superoxide")
for (i, dox) in enumerate(doxrange)
    plot!(fig, sim[i], idxs=(sys.t/1000, sys.sox_i), lab="DOX = $(dox) μM")
end
plot!(fig, ylabel="Conc. (μM)", xlabel="Time (s)", legend=:right) |> PNG

_images/f3c8f10605acf2e88623a244940049beba964dac09a39d909b1f155ba9bdaeec.png

fig = plot(title="Mitochondrial superoxide")
for (i, dox) in enumerate(doxrange)
    plot!(fig, sim[i], idxs=(sys.t/1000, sys.sox_m), lab="DOX = $(dox) μM")
end
plot!(fig, ylabel="Conc. (μM)", xlabel="Time (s)", legend=:topright) |> PNG

_images/e183aa3c836706476156e4bdeafd06c28d93cd561df21180a7bf15de51282c6c.png

fig = plot(title="Superoxide production")
for (i, dox) in enumerate(doxrange)
    plot!(fig, sim[i], idxs=(sys.t/1000, sys.vROS), lab="DOX = $(dox) μM")
end
plot!(fig, ylabel="Rate (μM/ms)", xlabel="Time (s)", legend=:right) |> PNG

_images/fba094fe7b5c6a356385285d3f9bbdea8fe599a0e4ed171deb7ee053edc93562.png

fig = plot(title="O2 shunt")
for (i, dox) in enumerate(doxrange)
    plot!(fig, sim[i], idxs=(sys.t/1000, 100*sys.vROS / (sys.vO2 + sys.vROS)), lab="DOX = $(dox) μM")
end
plot!(fig, ylabel="Percentage (%)", xlabel="Time (s)", legend=:right) |> PNG

_images/17d9c202fed13a165e509e34252a40fa01416bca327694dca0d8ca347c5f87b2.png

@unpack Q_n, SQn, QH2_n, QH2_p, Q_p, fes_ox, fes_rd, cytc_ox, cytc_rd = sys
plot(sim[end], idxs=[Q_n + Q_p, SQn, QH2_n+QH2_p], title="Q cycle ", legend=:right) |> PNG

_images/a784e36f62ae3db9f4111e254aafc25cc9574096cd8d2e8b50c6cb66e263b678.png

plot(sim[end], idxs=[fes_ox, fes_rd, cytc_ox, cytc_rd], title="Q cycle (downstream)", legend=:right) |> PNG

_images/4ab49b560a63f8da27cb21ee4daee4f7b2c3132159038a675225d6661fca9a88.png

@unpack cit, isoc, oaa, akg, scoa, suc, fum, mal, nadh_m = sys
plot(sim[end], idxs=[cit, isoc, oaa, akg, scoa, suc, fum, mal, nadh_m], title="TCA cycle ", legend=:right) |> PNG

_images/dc72a1f03a6cd78b49056ddf71a4c01ab81158f3d0a51c635b33dfd37b387f11.png

This notebook was generated using Literate.jl.