Team:SUSTC-Shenzhen/Modeling/matlabcode
From 2014.igem.org
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{{SUSTC-Shenzhen/main-content-begin}} | {{SUSTC-Shenzhen/main-content-begin}} | ||
+ | |||
+ | |||
+ | ===main=== | ||
+ | |||
+ | % This document is the main file for simulate the multi-agent interaction | ||
+ | % of HIV, HSC and immune system. | ||
+ | |||
+ | % author: Rongpeng Li, Mingmeng Geng, Fan Jiang | ||
+ | % Date: September, 7, 2014 | ||
+ | %Version 1.0 | ||
+ | |||
+ | delete(gcf); | ||
+ | |||
+ | |||
+ | %Initialize variables and their explainations. | ||
+ | thymus = 0; % the stem cell generation capability. | ||
+ | hiv = 0; % the hiv counting. | ||
+ | high = 0; % the high-resistance T cell counting, | ||
+ | low = 0; % the low-resistance T cell counting. | ||
+ | interveneTime = 16000; % the intervene time of CRISPR mechanism | ||
+ | |||
+ | method = 0; % 1 for using CRISPR mechnism, 0 for not. At the beginning, start without CRISPR mechanism. | ||
+ | |||
+ | %Initialize parameters and their explainations. | ||
+ | |||
+ | t = 0.01; % the simulation time step. | ||
+ | T = 350; %the total time that the programs is going to simulate. | ||
+ | |||
+ | % parameter for thymus update. | ||
+ | global thymusGrowthRate; % the self-generation rate of stem cell | ||
+ | global N_thymus ; % the possible total thymus counting. | ||
+ | global thymusSelfPresure ; % the enviroment pressure for thymus growth in M-model. | ||
+ | global hiv2thymus ; % the hiv-caused thymus counting decreasing factor. | ||
+ | global highlow2thymus ; % the high and low immune cell induced increasing factor. | ||
+ | |||
+ | % parameter for hiv update. | ||
+ | global hivGrowthRate; %the self-generation rate of hiv virus. | ||
+ | global hivMutation ; % the mutation factor. | ||
+ | global N_hiv ; % the possible total hiv counting, can be set to be infinity. | ||
+ | global hivSelfPressure ; % Almost no self-pressure for hiv virus. | ||
+ | |||
+ | % parameter for high update. | ||
+ | global thymus2high ; %the generation rate by thymus counting. | ||
+ | global highResist ; % the resistance factor, can be invicible if CRISPR is 100% effective. | ||
+ | global decayHigh ; % the decay(death) rate from high resistant T cell to low ones. | ||
+ | global gainLow ; % the gain rate from low resistant T cell to high ones. | ||
+ | |||
+ | % parameter for low update. | ||
+ | global thymus2low; %generation rate from thymus counting. | ||
+ | global lowResist; % the resistance factor. | ||
+ | global hiv2low; % the death rate caused by hiv. | ||
+ | global gain4high % the gain rate by the immune decaying of high resistant T cells. | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | % choose parameter sets by user. | ||
+ | OK = 0; | ||
+ | while OK == 0 | ||
+ | % set = input('Please choose the initial parameter set. 1, 2 or 3?'); | ||
+ | set =1 ; | ||
+ | if set ==1 | ||
+ | [thymusGrowthRate, N_thymus,thymusSelfPresure, hiv2thymus, highlow2thymus] =deal(0.8,0.94,0.3,0.22,0.2); | ||
+ | [hivGrowthRate, hivMutation, N_hiv, hivSelfPressure] = deal(8,0.15,20,0.1); | ||
+ | [thymus2high, highResist, decayHigh , gainLow] = deal(0.2,0.6,0.4,0.1); | ||
+ | [thymus2low, lowResist, hiv2low, gain4high] = deal(0.2,0.2,0.8,0); | ||
+ | |||
+ | [thymus, hiv, high, low]= deal(1,0.2,0.0,0.1); | ||
+ | |||
+ | OK = 1; | ||
+ | elseif set ==2 | ||
+ | [thymusGrowthRate, N_thymus, thymusSelfPresure, hiv2thymus, highlow2thymus] =deal(); | ||
+ | [hivGrowthRate, hivMutation, N_hiv, hivSelfPressure] = deal(); | ||
+ | [thymus2high, highResist, decayHigh , gainLow] = deal(); | ||
+ | [thymus2low, lowResist, hiv2low, gain4high] = deal(); | ||
+ | |||
+ | [thymus, hiv, high, low]= deal(); | ||
+ | |||
+ | OK = 1; | ||
+ | elseif set ==3 | ||
+ | [thymusGrowthRate, N_thymus, thymusSelfPresure, hiv2thymus, highlow2thymus] =deal(); | ||
+ | [hivGrowthRate, hivMutation, N_hiv, hivSelfPressure] = deal(); | ||
+ | [thymus2high, highResist, decayHigh , gainLow] = deal(); | ||
+ | [thymus2low, lowResist, hiv2low, gain4high] = deal(); | ||
+ | |||
+ | [thymus, hiv, high, low]= deal(); | ||
+ | |||
+ | OK = 1; | ||
+ | else | ||
+ | OK = 0; | ||
+ | end | ||
+ | end | ||
+ | |||
+ | |||
+ | % Initialize zero-filled arrays to store the data generated. | ||
+ | Len = floor(T/t); | ||
+ | |||
+ | [Time,Thymus,HIV,High,Low] = deal(zeros(1,Len)); | ||
+ | |||
+ | |||
+ | %update the status | ||
+ | |||
+ | for i = 1:Len | ||
+ | if i < interveneTime | ||
+ | [Time(i),Thymus(i),HIV(i),High(i),Low(i)] = deal(t*i,thymus,hiv,high,low); | ||
+ | [thymus, high, low, hiv,hivMutation,highResist,lowResist ] = update(t,thymus, high, low, hiv, method ); | ||
+ | else | ||
+ | [Time(i),Thymus(i),HIV(i),High(i),Low(i)] = deal(t*i,thymus,hiv,high,low); | ||
+ | method = 1; | ||
+ | [thymus, high, low, hiv, hivMutation,highResist,lowResist] = update(t,thymus, high, low, hiv, method ); | ||
+ | end | ||
+ | % hivMutation | ||
+ | end | ||
+ | |||
+ | % Draw pictures | ||
+ | |||
+ | subplot(2,2,1) | ||
+ | plot(Time,Thymus,'*'); | ||
+ | xlabel('Time') | ||
+ | ylabel('Thymus counting') | ||
+ | title('Thymus counting versus Time'); | ||
+ | grid; | ||
+ | hold on; | ||
+ | |||
+ | subplot(2,2,2) | ||
+ | plot(Time,High,'+'); | ||
+ | xlabel('Time') | ||
+ | ylabel('High-resistance T cell counting') | ||
+ | title('High-resistance T cell counting versus Time'); | ||
+ | grid; | ||
+ | hold on; | ||
+ | |||
+ | subplot(2,2,3) | ||
+ | plot(Time,Low,'<'); | ||
+ | xlabel('Time') | ||
+ | ylabel('Low-resistance T cell counting') | ||
+ | title('Low-resistance T cell counting versus Time'); | ||
+ | grid; | ||
+ | hold on; | ||
+ | |||
+ | subplot(2,2,4) | ||
+ | plot(Time,HIV,'>'); | ||
+ | xlabel('Time') | ||
+ | ylabel('HIV counting') | ||
+ | title('HIV counting versus Time'); | ||
+ | grid; | ||
+ | |||
+ | saveas(gcf,'Trend Graph','bmp'); | ||
+ | %delete(gcf); | ||
+ | |||
+ | |||
+ | |||
+ | %Draw phase graph. | ||
+ | |||
+ | |||
+ | ===update=== | ||
+ | |||
+ | function [thymus, high, low, hiv,hivMutation,highResist,lowResist ] = update(t,thymus, high, low, hiv, method ) | ||
+ | % the function update all the status. | ||
+ | % Here are the key of the program. The following function handlers decribes | ||
+ | % the interaction details of the agents. You can modify them later to make | ||
+ | % them more physical and realistic. | ||
+ | |||
+ | global thymusGrowthRate; % the self-generation rate of stem cell | ||
+ | global N_thymus ; % the possible total thymus counting. | ||
+ | global thymusSelfPresure ; % the enviroment pressure for thymus growth in M-model. | ||
+ | global hiv2thymus ; % the hiv-caused thymus counting decreasing factor. | ||
+ | global highlow2thymus ; % the high and low immune cell induced increasing factor. | ||
+ | |||
+ | % parameter for hiv update. | ||
+ | global hivGrowthRate; %the self-generation rate of hiv virus. | ||
+ | global hivMutation ; % the mutation factor. | ||
+ | global N_hiv ; % the possible total hiv counting, can be set to be infinity. | ||
+ | global hivSelfPressure ; % Almost no self-pressure for hiv virus. | ||
+ | |||
+ | % parameter for high update. | ||
+ | global thymus2high ; %the generation rate by thymus counting. | ||
+ | global highResist ; % the resistance factor, can be invicible if CRISPR is 100% effective. | ||
+ | global decayHigh ; % the decay(death) rate from high resistant T cell to low ones. | ||
+ | global gainLow ; % the gain rate from low resistant T cell to high ones. | ||
+ | |||
+ | % parameter for low update. | ||
+ | global thymus2low; %generation rate from thymus counting. | ||
+ | global lowResist; % the resistance factor. | ||
+ | global hiv2low; % the death rate caused by hiv. | ||
+ | global gain4high % the gain rate by the immune decaying of high resistant T cells. | ||
+ | |||
+ | % To avoid duplicity of variables, I ignore the means of symbol. | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | f1a = @(hiv)(3*hiv); % HIV's existence,thymus counting is decreasing. | ||
+ | f1b = @(hiv)(3 * hiv); % HIV's existence,thymus counting is decreasing. CRISPR exsits. following 'b' means the same logic. | ||
+ | f2a = @(high,low)(0.01*high+0.01*low); % The high and low can boost the thymus increasing. | ||
+ | f2b = @(high,low)(0.01* high + 0.01*low); | ||
+ | |||
+ | f3a = @(low,high,hivMutation)((low + high) * hivMutation); % T cell as hosts can boost the increasing of HIV | ||
+ | f3b = @(low,high,hivMutation)(( low+ 0.3 * high)* hivMutation); | ||
+ | f4a = @(high,hiv,hivMutation)((1-hivMutation) * hiv * high );% high resistance ones can decrease HIV counting. | ||
+ | % f4a = @(high,hiv,hivMut)(0); | ||
+ | |||
+ | f4b = @(high,hiv,hivMutation)( 1.2* (1-hivMutation) * hiv * high); | ||
+ | |||
+ | f5a = @(thymus)(0.001*thymus); %high resistance ones increase due to thymus counting | ||
+ | f5b = @(thymus)(0.001*thymus); | ||
+ | f6a = @(hiv)((1- 0.4 * hiv));% HIV caused the high ones increasing slower than normal | ||
+ | f6b = @(hiv)(1- 0.2 * hiv); | ||
+ | f7a = @(high, highResist,hiv)(0.8*high*exp(-1*highResist)*hiv);% Immune decay rate for high ones due to mutation | ||
+ | f7b = @(high, highResist,hiv)(0.5*high*exp(-0.5*highResist)*hiv); | ||
+ | f8a = @(low,lowResist)(0.2*low*exp(lowResist));% high ones increase due to low ones that gain immune capacity | ||
+ | f8b = @(low,lowResist)(0.3*low*exp(lowResist)); | ||
+ | |||
+ | f9a = @(thymus)(0.2*thymus);% low ones increase due to thymus counting | ||
+ | f9b = @(thymus)(0.2*thymus); | ||
+ | f10a = @(hiv)(1- 0.5 * hiv);% HIV caused the high ones increasing slower than normal | ||
+ | f10b = @(hiv)(1- 0.5 * hiv); | ||
+ | f11a = @(low,lowResist,hiv)(1.5*low*exp(-1*lowResist)*hiv);% death formula for low ones due to HIV counting. | ||
+ | f11b = @(low,lowResist,hiv)(1.5*low*exp(-1*lowResist)*hiv); | ||
+ | f12a = @(high,decayHigh)(0);% growth rate due to decay from high ones. | ||
+ | f12b = @(high,decayHigh)(0); | ||
+ | |||
+ | |||
+ | |||
+ | if method == 1 % implement with CRISPR mechnism. | ||
+ | thymus = thymus + t* (thymusGrowthRate*thymus*(1-thymusSelfPresure*thymus/N_thymus) - hiv2thymus*f1b(hiv) + highlow2thymus*f2b(high,low)); | ||
+ | if thymus >1 | ||
+ | thymus = 1; | ||
+ | elseif thymus < 0 | ||
+ | %thymus =0.1; %thymus system should not be broken | ||
+ | end | ||
+ | |||
+ | hiv = hiv + t*(hivGrowthRate*hiv*(1-hivSelfPressure*hiv/N_hiv)*f3b(low,high,hivMutation) - f4b(high,hiv,hivMutation)); | ||
+ | if hiv >1 | ||
+ | hiv = 1; | ||
+ | elseif hiv < 0 | ||
+ | hiv =0.05; % hiv can not be extinguished becasue there are hiv in other tissues. | ||
+ | end | ||
+ | |||
+ | high = high + t*( thymus2high*f5b(thymus)*f6b(hiv) - decayHigh*f7b(high, highResist, hiv ) + gainLow*f8b(low,lowResist)); | ||
+ | if high >1 | ||
+ | high = 1; | ||
+ | elseif high < 0 | ||
+ | high =0; | ||
+ | end | ||
+ | |||
+ | low = low + t* ( thymus2low*f9b(thymus)*f10b(hiv) - hiv2low*f11b(low,lowResist,hiv) + gain4high*f12b(high,decayHigh) ); | ||
+ | if low >1 | ||
+ | low = 1; | ||
+ | elseif low < 0 | ||
+ | low =0; | ||
+ | end | ||
+ | highResist = 0.8 * thymus; | ||
+ | hivMutation = 0.1*(high/( high + low ) + 0.3*rand(1)); % update add random elements to the mutation level | ||
+ | |||
+ | elseif method ==0 %implement without CRISPR mechnism. | ||
+ | |||
+ | thymus = thymus + t* (thymusGrowthRate*thymus*(1-thymusSelfPresure*thymus/N_thymus) - hiv2thymus*f1a(hiv) + highlow2thymus*f2a(high,low)); | ||
+ | if thymus >1 | ||
+ | thymus = 1; | ||
+ | elseif thymus < 0 | ||
+ | thymus =0; | ||
+ | end | ||
+ | |||
+ | hiv = hiv + t*(hivGrowthRate*hiv*(1-hivSelfPressure*hiv/N_hiv)*f3a(low,high,hivMutation) - f4a(high,hiv,hivMutation) ); | ||
+ | if hiv >1 | ||
+ | hiv = 1; | ||
+ | elseif hiv < 0 | ||
+ | hiv =0; | ||
+ | end | ||
+ | |||
+ | % high = high + t*( thymus2high*f5a(thymus)*f6a(hiv) - decayHigh*f7a(high, highResist, hiv ) + gainLow*f8a(low,lowResist)); | ||
+ | high = 0; | ||
+ | if high >1 | ||
+ | high = 1; | ||
+ | elseif high < 0 | ||
+ | high =0; | ||
+ | end | ||
+ | |||
+ | low = low + t* ( thymus2low*f9a(thymus)*f10a(hiv) - hiv2low*f11a(low,lowResist,hiv) + gain4high*f12a(high,decayHigh) ); | ||
+ | if low >1 | ||
+ | low = 1; | ||
+ | elseif low < 0 | ||
+ | low =0; | ||
+ | end | ||
+ | |||
+ | hivMutation = 0.1*(high/( high + low ) + 0.3*rand(1)); % update add random elements to the mutation level | ||
+ | end | ||
+ | |||
+ | % update some important global factors. If necessary, many other global | ||
+ | % variables can be updated here. | ||
+ | |||
+ | end | ||
Revision as of 03:40, 18 October 2014
matlab code
a simple example
main
% This document is the main file for simulate the multi-agent interaction % of HIV, HSC and immune system.
% author: Rongpeng Li, Mingmeng Geng, Fan Jiang % Date: September, 7, 2014 %Version 1.0
delete(gcf);
%Initialize variables and their explainations.
thymus = 0; % the stem cell generation capability.
hiv = 0; % the hiv counting.
high = 0; % the high-resistance T cell counting,
low = 0; % the low-resistance T cell counting.
interveneTime = 16000; % the intervene time of CRISPR mechanism
method = 0; % 1 for using CRISPR mechnism, 0 for not. At the beginning, start without CRISPR mechanism.
%Initialize parameters and their explainations.
t = 0.01; % the simulation time step. T = 350; %the total time that the programs is going to simulate.
% parameter for thymus update. global thymusGrowthRate; % the self-generation rate of stem cell global N_thymus ; % the possible total thymus counting. global thymusSelfPresure ; % the enviroment pressure for thymus growth in M-model. global hiv2thymus ; % the hiv-caused thymus counting decreasing factor. global highlow2thymus ; % the high and low immune cell induced increasing factor.
% parameter for hiv update. global hivGrowthRate; %the self-generation rate of hiv virus. global hivMutation ; % the mutation factor. global N_hiv ; % the possible total hiv counting, can be set to be infinity. global hivSelfPressure ; % Almost no self-pressure for hiv virus.
% parameter for high update. global thymus2high ; %the generation rate by thymus counting. global highResist ; % the resistance factor, can be invicible if CRISPR is 100% effective. global decayHigh ; % the decay(death) rate from high resistant T cell to low ones. global gainLow ; % the gain rate from low resistant T cell to high ones.
% parameter for low update. global thymus2low; %generation rate from thymus counting. global lowResist; % the resistance factor. global hiv2low; % the death rate caused by hiv. global gain4high % the gain rate by the immune decaying of high resistant T cells.
% choose parameter sets by user.
OK = 0;
while OK == 0
% set = input('Please choose the initial parameter set. 1, 2 or 3?');
set =1 ;
if set ==1
[thymusGrowthRate, N_thymus,thymusSelfPresure, hiv2thymus, highlow2thymus] =deal(0.8,0.94,0.3,0.22,0.2); [hivGrowthRate, hivMutation, N_hiv, hivSelfPressure] = deal(8,0.15,20,0.1); [thymus2high, highResist, decayHigh , gainLow] = deal(0.2,0.6,0.4,0.1); [thymus2low, lowResist, hiv2low, gain4high] = deal(0.2,0.2,0.8,0); [thymus, hiv, high, low]= deal(1,0.2,0.0,0.1); OK = 1;
elseif set ==2
[thymusGrowthRate, N_thymus, thymusSelfPresure, hiv2thymus, highlow2thymus] =deal(); [hivGrowthRate, hivMutation, N_hiv, hivSelfPressure] = deal(); [thymus2high, highResist, decayHigh , gainLow] = deal(); [thymus2low, lowResist, hiv2low, gain4high] = deal(); [thymus, hiv, high, low]= deal(); OK = 1;
elseif set ==3
[thymusGrowthRate, N_thymus, thymusSelfPresure, hiv2thymus, highlow2thymus] =deal(); [hivGrowthRate, hivMutation, N_hiv, hivSelfPressure] = deal(); [thymus2high, highResist, decayHigh , gainLow] = deal(); [thymus2low, lowResist, hiv2low, gain4high] = deal(); [thymus, hiv, high, low]= deal(); OK = 1;
else
OK = 0;
end end
% Initialize zero-filled arrays to store the data generated.
Len = floor(T/t);
[Time,Thymus,HIV,High,Low] = deal(zeros(1,Len));
%update the status
for i = 1:Len
if i < interveneTime [Time(i),Thymus(i),HIV(i),High(i),Low(i)] = deal(t*i,thymus,hiv,high,low); [thymus, high, low, hiv,hivMutation,highResist,lowResist ] = update(t,thymus, high, low, hiv, method ); else [Time(i),Thymus(i),HIV(i),High(i),Low(i)] = deal(t*i,thymus,hiv,high,low); method = 1; [thymus, high, low, hiv, hivMutation,highResist,lowResist] = update(t,thymus, high, low, hiv, method ); end
% hivMutation end
% Draw pictures
subplot(2,2,1) plot(Time,Thymus,'*'); xlabel('Time') ylabel('Thymus counting') title('Thymus counting versus Time'); grid; hold on;
subplot(2,2,2) plot(Time,High,'+'); xlabel('Time') ylabel('High-resistance T cell counting') title('High-resistance T cell counting versus Time'); grid; hold on;
subplot(2,2,3) plot(Time,Low,'<'); xlabel('Time') ylabel('Low-resistance T cell counting') title('Low-resistance T cell counting versus Time'); grid; hold on;
subplot(2,2,4) plot(Time,HIV,'>'); xlabel('Time') ylabel('HIV counting') title('HIV counting versus Time'); grid;
saveas(gcf,'Trend Graph','bmp'); %delete(gcf);
%Draw phase graph.
update
function [thymus, high, low, hiv,hivMutation,highResist,lowResist ] = update(t,thymus, high, low, hiv, method ) % the function update all the status. % Here are the key of the program. The following function handlers decribes % the interaction details of the agents. You can modify them later to make % them more physical and realistic.
global thymusGrowthRate; % the self-generation rate of stem cell global N_thymus ; % the possible total thymus counting. global thymusSelfPresure ; % the enviroment pressure for thymus growth in M-model. global hiv2thymus ; % the hiv-caused thymus counting decreasing factor. global highlow2thymus ; % the high and low immune cell induced increasing factor.
% parameter for hiv update. global hivGrowthRate; %the self-generation rate of hiv virus. global hivMutation ; % the mutation factor. global N_hiv ; % the possible total hiv counting, can be set to be infinity. global hivSelfPressure ; % Almost no self-pressure for hiv virus.
% parameter for high update. global thymus2high ; %the generation rate by thymus counting. global highResist ; % the resistance factor, can be invicible if CRISPR is 100% effective. global decayHigh ; % the decay(death) rate from high resistant T cell to low ones. global gainLow ; % the gain rate from low resistant T cell to high ones.
% parameter for low update. global thymus2low; %generation rate from thymus counting. global lowResist; % the resistance factor. global hiv2low; % the death rate caused by hiv. global gain4high % the gain rate by the immune decaying of high resistant T cells.
% To avoid duplicity of variables, I ignore the means of symbol.
f1a = @(hiv)(3*hiv); % HIV's existence,thymus counting is decreasing.
f1b = @(hiv)(3 * hiv); % HIV's existence,thymus counting is decreasing. CRISPR exsits. following 'b' means the same logic.
f2a = @(high,low)(0.01*high+0.01*low); % The high and low can boost the thymus increasing.
f2b = @(high,low)(0.01* high + 0.01*low);
f3a = @(low,high,hivMutation)((low + high) * hivMutation); % T cell as hosts can boost the increasing of HIV f3b = @(low,high,hivMutation)(( low+ 0.3 * high)* hivMutation); f4a = @(high,hiv,hivMutation)((1-hivMutation) * hiv * high );% high resistance ones can decrease HIV counting. % f4a = @(high,hiv,hivMut)(0);
f4b = @(high,hiv,hivMutation)( 1.2* (1-hivMutation) * hiv * high);
f5a = @(thymus)(0.001*thymus); %high resistance ones increase due to thymus counting f5b = @(thymus)(0.001*thymus); f6a = @(hiv)((1- 0.4 * hiv));% HIV caused the high ones increasing slower than normal f6b = @(hiv)(1- 0.2 * hiv); f7a = @(high, highResist,hiv)(0.8*high*exp(-1*highResist)*hiv);% Immune decay rate for high ones due to mutation f7b = @(high, highResist,hiv)(0.5*high*exp(-0.5*highResist)*hiv); f8a = @(low,lowResist)(0.2*low*exp(lowResist));% high ones increase due to low ones that gain immune capacity f8b = @(low,lowResist)(0.3*low*exp(lowResist));
f9a = @(thymus)(0.2*thymus);% low ones increase due to thymus counting f9b = @(thymus)(0.2*thymus); f10a = @(hiv)(1- 0.5 * hiv);% HIV caused the high ones increasing slower than normal f10b = @(hiv)(1- 0.5 * hiv); f11a = @(low,lowResist,hiv)(1.5*low*exp(-1*lowResist)*hiv);% death formula for low ones due to HIV counting. f11b = @(low,lowResist,hiv)(1.5*low*exp(-1*lowResist)*hiv); f12a = @(high,decayHigh)(0);% growth rate due to decay from high ones. f12b = @(high,decayHigh)(0);
if method == 1 % implement with CRISPR mechnism.
thymus = thymus + t* (thymusGrowthRate*thymus*(1-thymusSelfPresure*thymus/N_thymus) - hiv2thymus*f1b(hiv) + highlow2thymus*f2b(high,low)); if thymus >1 thymus = 1; elseif thymus < 0 %thymus =0.1; %thymus system should not be broken end hiv = hiv + t*(hivGrowthRate*hiv*(1-hivSelfPressure*hiv/N_hiv)*f3b(low,high,hivMutation) - f4b(high,hiv,hivMutation)); if hiv >1 hiv = 1; elseif hiv < 0 hiv =0.05; % hiv can not be extinguished becasue there are hiv in other tissues. end high = high + t*( thymus2high*f5b(thymus)*f6b(hiv) - decayHigh*f7b(high, highResist, hiv ) + gainLow*f8b(low,lowResist)); if high >1 high = 1; elseif high < 0 high =0; end low = low + t* ( thymus2low*f9b(thymus)*f10b(hiv) - hiv2low*f11b(low,lowResist,hiv) + gain4high*f12b(high,decayHigh) ); if low >1 low = 1; elseif low < 0 low =0; end highResist = 0.8 * thymus; hivMutation = 0.1*(high/( high + low ) + 0.3*rand(1)); % update add random elements to the mutation level
elseif method ==0 %implement without CRISPR mechnism.
thymus = thymus + t* (thymusGrowthRate*thymus*(1-thymusSelfPresure*thymus/N_thymus) - hiv2thymus*f1a(hiv) + highlow2thymus*f2a(high,low)); if thymus >1 thymus = 1; elseif thymus < 0 thymus =0; end hiv = hiv + t*(hivGrowthRate*hiv*(1-hivSelfPressure*hiv/N_hiv)*f3a(low,high,hivMutation) - f4a(high,hiv,hivMutation) ); if hiv >1 hiv = 1; elseif hiv < 0 hiv =0; end % high = high + t*( thymus2high*f5a(thymus)*f6a(hiv) - decayHigh*f7a(high, highResist, hiv ) + gainLow*f8a(low,lowResist)); high = 0; if high >1 high = 1; elseif high < 0 high =0; end low = low + t* ( thymus2low*f9a(thymus)*f10a(hiv) - hiv2low*f11a(low,lowResist,hiv) + gain4high*f12a(high,decayHigh) ); if low >1 low = 1; elseif low < 0 low =0; end
hivMutation = 0.1*(high/( high + low ) + 0.3*rand(1)); % update add random elements to the mutation level
end
% update some important global factors. If necessary, many other global % variables can be updated here.
end