mass action rate law for first order irreversible reactions

Reaction scheme where the products are created from the reactants and the change of a product quantity is proportional to the product of reactant activities. The reaction scheme does not include any reverse process that creates the reactants from the products. The change of a product quantity is proportional to the quantity of one reactant.

k1*PRODUCT<substrate_i> mass action rate law for reversible reactions

Reaction scheme where the products are created from the reactants and the change of a product quantity is proportional to the product of reactant activities. The reaction scheme does include a reverse process that creates the reactants from the products.

k1*PRODUCT<substrate_i>-k2*PRODUCT<product_j> 2012-05-15T15:51:35Z kf*S*Act - kb*P 2012-05-15T16:01:51Z kf*S*(Act+1) 2012-05-16T11:53:02Z kf*Act*S 2012-05-25T10:00:36Z kf*S1*S2*Act - kb*P/1 2012-05-25T10:14:54Z kf*S*(0.01+Act) - kb*P 2012-05-25T15:44:15Z kf*ReductEqviv*O2*Act*ADP/(1+kUncouplProt*UncoplProt) 2013-04-03T16:48:06Z (kf*S1*S2*Act - kb*P)/(1+KUncouplProt*UncouplProt) 2014-04-07T14:11:36Z kf*S1*S2/(Kinh*Inh+1)-(kb*P1) 2014-04-07T16:52:43Z kf*S1/(Kinh*Inh+1) 2014-04-07T17:01:48Z kf*S1*Act/(Kinh*Inh+1) 2014-04-08T11:55:08Z kf*S1*S2*Act/(Kinh*Inh+1)-(kb*P1) 2017-11-29T11:28:20Z S*k1*kCellDeath*CytC 2019-11-13T16:01:31Z k*ROS^power 2013-04-02T14:44:50Z RUN the model for steady state. For the Menadione experiment set the initial concentration of 'Menadione' species to experimental dosing i.e. 100 000 nM (0.1 mM) and make the simulation type "reaction" for both the species i.e. 'Menadione' and 'Menadione_internal'. Then run for 24 hr i.e. 1500 minutes approx. Plot e.g. ATP. For H2O2 experimental data validation for repeated treatment at 50uM, 150uM, and 300uM. To run the model with different dosing scenarios, one has to set both the H2O2 initial concentration and the global parameter "H2O2 addition" from zero to the required dosage, and also change the species 'H2O2', 'H2O2_internal' and 'Damage' to ‘reaction’ type from ‘fixed’ type. For instance for the dosing amount of 50 uM (50000 nM), set the initial concentration i.e. H2O2 species to 50000 nM and select ‘reaction’ type simulation for both the H2O2 and H2O2_internal species . And also set the Global parameter H2O2 to 50 000nM, keeping the simulation type ‘fixed’. To run the single dose experiment one has to set the initial value of species H2O2 to corresponding dosage and simulation type to ‘reaction’ from ‘fixed’ for both the 'H2O2' and 'H2O2_internal' species. Note: global parameter "H2O2 addition" should be zero in case of single dose treatment. One can reproduce the aging phenomenon with the following step. Change the species 'Aging' simulation type from ‘fixed’ to ‘reaction’. To see the effects of coffee on aging one has to go to the global parameters and then select "coffee addition (fold activation of Nrf2 synt)" and set the value to 1.2. Then run the simulation. To see the effects of Antioxidant treatments on aging one has to go to the global parameters and then select "Antioxidant_treatment" and set the value to 1.2. Then run the simulation. To observe the mitohormesis effect in the aging model one can increase the ROS signal reception by the mitoptosis proteins by 50% (i.e., set the global parameter "Mitohormesis_factor" to 1.5 which will increase the rate constant of reaction 39 by 50%). This increased the lifetime by 80% in the aging model. To observe the KEAP1 deletion phenomenon we have created two global parameters namely 'KEAP_deletion" = 1 and "KEAP_reverse" = 0 in the original model. This should not affect the master model of aging or Steady state. Moreover events were created to knockout the KEPA1 from the 7th week (approx. 70560 minutes) onward and reverse it back at the 17th week (approx. 172800 minutes). To reproduce the phenomenon, one has to set both the 'KEAP_deletion" = 0 and "KEAP_reverse" = 22.61 (initial concentration of KEAP1) and then go to the species, then select KEAP1 and then change the simulation type to "fixed" from "reaction". Then the time course should run up to 300 000 mins with interval size of around 10-20. To reproduce the memory effect in the aging model, one has to set the global parameters both 'aging_reduction_during_memoryPulse' to 0.001, which has same events function as ROSpulse (another global parameter) and 'Aging_memory_pulse' to 12.5 or around that number. The idea is when you give high ROSpulse, it should not reduce the ATP OR MITOCHONDRIA levels via aging phenomena. As in our model both aging and Memory effect are done through ROSsynt rate constant. So to eliminate the effect of Aging_memory_pulse on normal aging, we made an 'event' where "Aging_rate_constant_re63" was reduced by a factor of 1000 only when there is addition of memory_pulse otherwise the rate constant will have its original value. This is also important to keep the model stable while giving a pulse of ROS. If we do not eliminate the ROS pulse, then damage via accelerating aging will occur. Then ROS grows exponentially high and model explodes. To see the memory effect clearly one has to set the simulation time of 3 500 000 with a step size of 20. And then in plotting select ATP, Healthy Mitochondria, and ROS. History of model changes We rename ‘O2’ in the model to O2_1/5th’. In the old model the P/O ratio was taken to equal 0.5 (the ATP per O2 ratio equal to 1). Now we replace the O2 which was 250000 by O2_1/5th which should then amount to 50000. We rename "RE" in the model to RE_4/5th. Hence the RE i.e. 5000000 (2.5 mM NADH; 5 mM ‘electrons’) would become RE_4/5th = 4000000 (initial value). To ensure that model SS values would not be change we increase the reaction rate constant by the factor 5 * 5/4 = 25/4 =6.25; the rate was mass action to first order in both O2 and RE. O2 is involved in re8 and re41; alternatively the rate constant of ATP synthesis was 8.10-14 and was divided by 0.16. The rate constant then became 5.10-13. The same for ROSsynCorrected i.e. the rate constant parameters was divided by 0.16. Then we should get the same steady state. Increase the rate constant of cytochrome c synthesis (Re49) by a factor of 50 and decrease the cell death rate constant re59 by 50. And then also increase the Cytc threshold by 50. Then run the steady state or just increase the initial steady state by a factor of 50. Mit_Damage and Mit_Healthy were both decreased by a factor of 40. Hence not to disturb the steady state for all the parameters except these two, we modified the reaction catalyzed by these two and also the synthesis rate of only the Healthy Mitochondria two in order to decrease their steady state concentrations: the re8, re14, re49 and re41 were modified. The synthesis rate was decreased by a factor of 40 i.e. re14. In order to compensate this the rate of reaction catalyzed of the other three were increased by a factor of 40 i.e. re8, re49, re41. This modulation should not changed the half life of the mitochondria but reduce the flux through the mitoptosis pathway 40 times. Mitochondrial turnover rate. We decreased the rate of reaction of Mitochondria by a factor 250 in order to increase the half life of mitochondria from approximately 2 h to 14 days. Therefore the rate constants of re14, re34, re35 and mitochondria recovery reactions were decreased by the same factor to slow the rate of mitochondria growth. ATP-consumption recalibration: to increase the stoichiometry of ATP consumption at the synthesis of 1 mitochondrion by a factor of 0.77e9, we created an additional reaction, which we named maintenance for ATP consumption in mitosynthesis. This new reaction had the same kinetics as the reaction of mitochondrial synthesis except that the mitochondrion was no longer mentioned as product. Its rate constant was taken to be 0.77e9 times the rate constant of the existing mitochondrial synthesis reaction (which consumed only 1 ATP per mitochondrion) and named it as k_maintenance_for_ ATP_ consumption_in_ mitosynthesis. Then we recalibrate the re29 (the maintenance reaction with rate constant 4 nmol/min) by changing the rate constant parameter such as re29 rate constant i.e. 4 nmol/min minus k_maintenance_for_ ATP_ consumption_in_ mitosynthesis. A new species named Aging was added. The Aging production follows the first order rate law depend on ROS concentration i.e. k*ROS^n, where n is the power and has a value of 4. This Aging variable will further increases the ROS concentration by increasing the synthesis rate of the latter. This is introduced in the model by changing the ROSsyntcoefficient from 1 to 1+Aging. When Aging is ‘fixed’ to zero, there is no aging. TO test the mitohormesis, we added global variable "Mitohormesis_factor". This global variable alters the rate constant of reaction39 (apoptotic machinery reaction). By increasing the value of this parameter one can increase the ROS signal reception by the mitoptosis proteins. One should expect increase in life-expectancy in the aging model if set the"Mitohormesis_factor" to 1.5 fold from 1. 2017-11-16T17:29:06Z 2017-11-16T16:28:45Z 2013-04-02T11:26:44Z 2013-04-02T11:19:40Z 2013-04-02T11:16:16Z 2013-04-02T11:30:36Z 2013-04-02T11:06:16Z 2013-04-02T11:26:42Z 2013-04-02T11:26:38Z 2013-04-02T11:30:29Z 2013-04-02T14:53:29Z 2013-04-02T11:19:47Z 2013-04-02T10:57:52Z 2013-04-02T11:28:50Z 2013-04-02T11:19:45Z 2013-04-02T11:30:41Z 2013-04-02T10:37:42Z 2013-04-02T11:32:16Z 2013-04-02T11:27:36Z 2013-04-02T11:27:34Z 2013-04-02T15:54:07Z 2013-04-02T14:53:33Z 2013-04-02T11:30:32Z 2013-04-02T11:16:14Z 2013-04-02T11:03:59Z 2013-04-02T11:32:21Z 2013-04-02T11:26:51Z 2013-04-02T11:31:22Z 2013-04-02T11:19:22Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Mit-Healthy],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Mit-Damaged],Reference=Concentration> 2013-04-02T11:19:12Z 2013-04-02T11:19:14Z 2013-04-03T12:52:03Z 2013-04-05T11:57:56Z 2014-04-07T17:15:11Z 2014-04-07T17:19:21Z 2014-04-07T17:07:38Z 2014-04-07T17:15:07Z 2017-11-15T08:46:50Z 2017-11-15T08:46:52Z 2017-11-15T09:05:31Z <CN=Root,Model=NoName,Vector=Compartments[nucleus],Vector=Metabolites[AntioxidantsRNA],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[nucleus],Vector=Metabolites[AntioxidantsRNA],Reference=InitialConcentration> 2017-11-15T09:07:11Z <CN=Root,Model=NoName,Vector=Compartments[nucleus],Vector=Metabolites[p62mRNA],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[nucleus],Vector=Metabolites[p62mRNA],Reference=InitialConcentration> 2017-11-15T09:10:10Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Bclxl],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Bclxl],Reference=InitialConcentration> 2017-11-15T09:11:22Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[NFkBsignal],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[NFkBsignal],Reference=InitialConcentration> 2017-11-15T09:12:33Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[ATP_measured],Reference=Concentration> 2017-11-16T16:26:14Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[ROS],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[ROS],Reference=InitialConcentration> 2013-04-02T10:59:19Z 2017-11-16T17:37:55Z 2017-11-16T17:37:56Z 2019-10-15T17:43:05Z 2017-11-29T10:59:27Z 2017-11-29T11:33:49Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[ATP],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[ATP],Reference=InitialConcentration>*(<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Ncells],Reference=Concentration>/<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Ncells],Reference=InitialConcentration>) 2018-12-12T20:46:02Z 2013-04-02T11:26:12Z 2013-04-02T10:54:00Z 2013-04-02T10:55:49Z 2013-04-02T11:08:51Z 2013-04-02T11:10:20Z 2013-04-02T11:10:25Z 2013-04-02T11:21:31Z 2013-04-02T10:37:38Z 2013-04-02T10:37:30Z 2013-04-02T11:06:40Z 2013-04-02T11:29:11Z 2019-11-13T15:55:28Z 2013-04-02T15:20:23Z 2013-04-02T15:27:29Z 2013-04-02T15:46:08Z (0.001*<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[ROS],Reference=Concentration>+0.00075283*<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[VDAC:p62],Reference=Concentration>)*<CN=Root,Model=NoName,Vector=Values[Mitohormesis_factor],Reference=InitialValue> 2013-04-02T15:57:27Z <CN=Root,Model=NoName,Vector=Values[ROSsyntCoeff],Reference=Value>*<CN=Root,Model=NoName,Vector=Values[ROSsynCorrected],Reference=Value>*<CN=Root,Model=NoName,Vector=Values[ROSPulse],Reference=Value> 2014-07-29T17:15:37Z 1.1-1*cos(1*<CN=Root,Model=NoName,Reference=Time>) 2014-08-05T16:43:16Z 2017-11-17T10:10:02Z 2017-11-17T11:06:26Z 2017-11-29T11:00:05Z 2017-11-29T11:06:04Z 165*50 2017-12-10T01:01:18Z 2017-12-10T01:02:27Z 1+<CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[Aging],Reference=Concentration> 2018-12-12T20:24:43Z <CN=Root,Model=NoName,Reference=Time> 2018-12-12T22:05:46Z 2018-12-16T18:04:54Z 2019-11-11T12:55:16Z 8e-14/(4/25) 2019-11-11T12:55:35Z <CN=Root,Model=NoName,Vector=Values[ROSsynt],Reference=Value>/(4/25) 2019-11-11T13:35:24Z 0.5*50 2019-11-11T13:41:32Z 2.5e-6/50 2019-11-11T15:14:16Z <CN=Root,Model=NoName,Vector=Values[re8_Kf_modified],Reference=Value>*40 2019-11-11T15:15:31Z 0.0000002/40 2019-11-11T15:17:03Z <CN=Root,Model=NoName,Vector=Values[re49_kf_modified],Reference=Value>*40 2019-11-11T15:17:33Z <CN=Root,Model=NoName,Vector=Values[re41_rosyN_modified],Reference=Value>*40 2019-11-11T15:36:07Z 2019-11-11T15:51:02Z <CN=Root,Model=NoName,Vector=Values[re14_k1_Mit_modified],Reference=Value>/<CN=Root,Model=NoName,Vector=Values[Mit_turnovertime],Reference=Value> 2019-11-11T15:52:19Z 0.01/<CN=Root,Model=NoName,Vector=Values[Mit_turnovertime],Reference=Value> 2019-11-11T15:53:30Z 0.0001/<CN=Root,Model=NoName,Vector=Values[Mit_turnovertime],Reference=Value> 2019-11-11T16:14:10Z 0.1/<CN=Root,Model=NoName,Vector=Values[Mit_turnovertime],Reference=Value> 2019-11-12T17:41:24Z <CN=Root,Model=NoName,Vector=Values[re14_k1_Mittrurnover_modified],Reference=Value>*0.77e9 2019-11-12T17:42:32Z 4-<CN=Root,Model=NoName,Vector=Values[re14_ATP_recalibrated],Reference=Value> 2019-11-13T12:33:43Z 2019-11-22T09:21:24Z 2019-11-22T09:23:02Z 2019-11-22T09:25:15Z 2019-11-22T09:27:59Z 2019-11-22T09:43:35Z 2019-11-22T09:46:34Z 2019-11-22T13:55:22Z 2019-11-22T14:12:45Z 2019-11-22T14:31:48Z 2013-04-02T14:44:55Z 2013-04-02T14:47:45Z 2013-04-02T14:48:54Z 2013-04-02T14:49:51Z 2013-04-02T14:50:25Z 2013-04-02T14:51:13Z 2013-04-02T14:56:44Z 2013-04-02T14:59:25Z 2013-04-02T15:00:20Z 2013-04-02T14:45:00Z 2013-04-02T14:45:02Z 2013-04-02T14:45:03Z 2013-04-02T14:45:05Z 2013-04-02T14:45:07Z 2013-04-02T14:45:07Z 2013-04-02T14:45:08Z 2013-04-02T14:45:10Z 2013-04-02T14:45:12Z 2013-04-02T14:45:14Z 2013-04-02T15:21:19Z 2013-04-02T15:22:20Z 2013-04-02T15:22:57Z 2013-04-02T15:23:39Z 2013-04-02T15:24:20Z 2013-04-02T15:24:47Z 2013-04-02T15:25:14Z 2013-04-02T15:25:36Z 2013-04-02T15:26:44Z 2013-04-02T14:49:49Z 2013-04-02T15:30:39Z 2013-04-02T15:31:03Z 2013-04-02T15:32:32Z 2013-04-02T15:33:44Z 2013-04-02T15:34:44Z 2013-04-02T15:35:51Z 2013-04-02T15:37:42Z 2013-04-02T15:39:52Z 2013-04-02T15:41:19Z 2013-04-02T15:43:21Z 2013-04-02T15:44:19Z 2013-04-02T15:55:50Z 2013-04-02T15:56:23Z 2014-04-07T16:48:01Z 2014-04-07T16:50:58Z 2014-04-07T16:55:39Z 2014-04-07T16:58:40Z 2014-04-07T17:00:34Z 2014-04-07T17:04:50Z 2014-06-13T15:42:04Z 2016-06-14T19:20:46Z 2017-11-15T08:43:39Z 2017-11-15T08:44:27Z 2017-11-16T17:33:29Z 2017-11-16T17:34:47Z 2017-11-16T17:35:22Z 2017-11-17T10:07:36Z 2017-11-24T12:53:12Z 2017-11-29T11:26:38Z 2018-12-12T20:12:27Z 2019-11-12T17:44:20Z 2019-11-13T13:08:28Z 2019-11-13T13:11:11Z 2019-11-13T16:03:04Z 2017-11-29T11:08:26Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[CytC],Reference=Concentration> > <CN=Root,Model=NoName,Vector=Values[CytCthreshold],Reference=InitialValue> 100 2017-11-29T11:20:01Z <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[CytC],Reference=Concentration> < <CN=Root,Model=NoName,Vector=Values[CytCthreshold],Reference=InitialValue> 0 2018-12-12T22:06:48Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 60 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[H2O2],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[H2O2addition],Reference=InitialValue> 2019-11-13T12:34:55Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 120 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[H2O2],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[H2O2addition],Reference=InitialValue> 2019-11-13T12:36:16Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 180 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[H2O2],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[H2O2addition],Reference=InitialValue> 2019-11-13T12:37:24Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 240 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[H2O2],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[H2O2addition],Reference=InitialValue> 2019-11-13T12:38:49Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 300 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[H2O2],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[H2O2addition],Reference=InitialValue> 2019-11-13T12:39:56Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 360 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[H2O2],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[H2O2addition],Reference=InitialValue> 2019-11-22T09:24:05Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 2728000 <CN=Root,Model=NoName,Vector=Values[ROSPulse],Reference=InitialValue>*<CN=Root,Model=NoName,Vector=Values[Aging_memory_pulse],Reference=InitialValue> 1.5e-6*<CN=Root,Model=NoName,Vector=Values[aging_reduction_during_memoryPulse],Reference=InitialValue> 2019-11-22T09:30:40Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 2748000 <CN=Root,Model=NoName,Vector=Values[ROSPulse],Reference=InitialValue>*1 1.5e-6 2019-11-22T09:32:28Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 2768000 <CN=Root,Model=NoName,Vector=Values[ROSPulse],Reference=InitialValue>*<CN=Root,Model=NoName,Vector=Values[Aging_memory_pulse],Reference=InitialValue> 1.5e-6*<CN=Root,Model=NoName,Vector=Values[aging_reduction_during_memoryPulse],Reference=InitialValue> 2019-11-22T09:34:18Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 2788000 <CN=Root,Model=NoName,Vector=Values[ROSPulse],Reference=InitialValue>*1 1.5e-6 2019-11-22T09:39:54Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 10512000 <CN=Root,Model=NoName,Vector=Values[Nrf2-Import],Reference=InitialValue>*<CN=Root,Model=NoName,Vector=Values[coffee_addition_(fold_activation_of_Nrf2_synt)],Reference=Value> 2019-11-22T09:41:31Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 10512000 <CN=Root,Model=NoName,Vector=Values[Antiox_synthesis_rate_re12],Reference=InitialValue>*<CN=Root,Model=NoName,Vector=Values[Antioxidant_treatment],Reference=InitialValue> 2019-11-22T14:22:38Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 70560 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[KEAP1],Reference=Concentration>*<CN=Root,Model=NoName,Vector=Values[KEAP_deletion],Reference=InitialValue> 2019-11-22T14:22:36Z <CN=Root,Model=NoName,Vector=Values[Factor_Time],Reference=Value> > 172800 <CN=Root,Model=NoName,Vector=Compartments[cyt],Vector=Metabolites[KEAP1],Reference=Concentration>+<CN=Root,Model=NoName,Vector=Values[KEAP_reverse],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re8_kf_Mit_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Antiox_synthesis_rate_re12],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re14_k1_Mittrurnover_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Nrf2synt],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Nrf2-Import],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[KEAP1synt],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re29_ATP_recalibrated],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re34_kf_Mittrurnover_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re35_kf__Mittrurnover_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Kf-Apoptosis],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re41_rosyN_Mit_modfied],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re49_kf_Mit_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Mitoch_recovery_kf_Mittrurnover_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[H2O2_transport],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[H2O2_transport],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Menadione_transport],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Menadione_transport],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re59_k1_modified],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[celldeathCoefficient],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[re14_ATP_recalibrated],Reference=InitialValue> <CN=Root,Model=NoName,Vector=Values[Aging_rate_constant_re63],Reference=InitialValue> 0 13619715983024580 1.4427137014656902e+17 2.2985366660395403e+21 247460351389990.56 41325949383129536 402395020269072.81 78001196184707680 41325949383129536 26218449416362132 171996582981372.5 3175694245085024.5 6351388490170049 3.9819536252179154e+18 39016624121040.805 15498353369280.699 13655442404355.273 5087799808409016 60213152710123.375 9399395372897466 736234706782463.38 32628493819606252 6146347387508.3457 844633244937763.88 7700601223328976 32924670017053644 218487078469.68436 120453541113691.11 596990095674.79468 22517962815970804 309967067647.00427 73449147563194272 78221193402444560 429182865341.20941 713797036652.99341 799254884040.31689 29645560224974080 24619670464935288 1.6459662064104636e+21 1247028265206836.8 602214179000000 602214179000000 602214179000000 602214179000000 602214179000000 602214179000000 602214179000000 0.02856069966120358 8e-14 0.10000000000000009 8250 1 0 4.9999999999999999e-13 4.9999999999999999e-13 25 5.0000000000000004e-08 1.9999999999999999e-11 5.0000000000000001e-09 1000 1.9999999999999999e-11 2.0000000000000002e-11 4.0000000000000003e-05 4.0000000000000003e-07 0.00040000000000000002 0.015400000000000002 3.9845999999999999 602214179000000 3.3422886934500002e+25 3.0110708950000001e+19 2.4088567160000002e+21 1806642537000000 602214179000000 0 0 0 0 0 60221417900000000 0.00028440736869695537 0 602214179000000 602214179000000 1 1 1 1 100 0.0007000000000000001 0.18934999999999999 0 8e-14 1 1 250 0 1.5e-06 1 1 1 100000 1 1 1 0 Automatically generated report.