/* * Guyton Model: non_muscle_autoregulatory_local_blood_flow_control * * Model Status * * This CellML model has been validated. Due to the differences * between procedural code (in this case C-code) and declarative * languages (CellML), some aspects of the original model were * not able to be encapsulated by the CellML model (such as the * damping of variables). This may effect the transient behaviour * of the model, however the steady-state behaviour would remain * the same. The equations in this file and the steady-state output * from the model conform to the results from the MODSIM program. * * Model Structure * * Arthur Guyton (1919-2003) was an American physiologist who became * famous for his 1950s experiments in which he studied the physiology * of cardiac output and its relationship with the peripheral circulation. * The results of these experiments challenged the conventional * wisdom that it was the heart itself that controlled cardiac * output. Instead Guyton demonstrated that it was the need of * the body tissues for oxygen which was the real regulator of * cardiac output. The "Guyton Curves" describe the relationship * between right atrial pressures and cardiac output, and they * form a foundation for understanding the physiology of circulation. * * The Guyton model of fluid, electrolyte, and circulatory regulation * is an extensive mathematical model of human circulatory physiology, * capable of simulating a variety of experimental conditions, * and contains a number of linked subsystems relating to circulation * and its neuroendocrine control. * * This is a CellML translation of the Guyton model of the regulation * of the circulatory system. The complete model consists of separate * modules each of which characterise a separate physiological * subsystems. The Circulation Dynamics is the primary system, * to which other modules/blocks are connected. The other modules * characterise the dynamics of the kidney, electrolytes and cell * water, thirst and drinking, hormone regulation, autonomic regulation, * cardiovascular system etc, and these feedback on the central * circulation model. The CellML code in these modules is based * on the C code from the programme C-MODSIM created by Dr Jean-Pierre * Montani. * * The circulatory system is divided into three separate parts * for blood flow control:(1) the kidneys which are presented in * an entirely separate CellML model; (2) non-muscle local blood * flow control; and (3) muscle local blood flow control. This * particular CellML model describes non-muscle autoregulatory * local blood flow control. This portion of the circulation has * three separate parallel autoregulatory processes, one of which * occurs in a matter of minutes, another over a period of tens * of minutes, and a third over a period of weeks. All of these * are considered to respond to changes in tissue oxygen level. * The first two are rapid metabolic feedback effects, one almost * instantaneous and the other occurring over a period of tens * of minutes to an hour or so. The third is considered to be structural * changes that result over a period of weeks and may be a consequence * of the vasodilation or vasoconstriction that occurs during the * two short-term metabolic stages. * * model diagram * * [[Image file: full_model.png]] * * A systems analysis diagram for the full Guyton model describing * circulation regulation. * * model diagram * * [[Image file: nm_blood_flow.png]] * * A schematic diagram of the components and processes described * in the current CellML model. * * There are several publications referring to the Guyton model. * One of these papers is cited below: * * Circulation: Overall Regulation, A.C. Guyton, T.G. Coleman, * and H.J. Granger, 1972, Annual Review of Physiology , 34, 13-44. * PubMed ID: 4334846 */ import nsrunit; unit conversion on; unit minute=60 second^1; unit per_minute=.01666667 second^(-1); //Warning: unit mmHg_ renamed from mmHg, as the latter is predefined in JSim with different fundamental units. unit mmHg_=133.322 kilogram^1*meter^(-1)*second^(-2); unit per_mmHg=.00750064 kilogram^(-1)*meter^1*second^2; unit per_mmHg2=5.6259564E-5 kilogram^(-2)*meter^2*second^4; unit mmHg3=2.369766E6 kilogram^3*meter^(-3)*second^(-6); unit monovalent_mEq=.001 mole^1; unit monovalent_mEq_per_minute=1.6666667E-5 second^(-1)*mole^1; unit monovalent_mEq_per_litre=1 meter^(-3)*mole^1; unit monovalent_mEq_per_litre_per_minute=.01666667 meter^(-3)*second^(-1)*mole^1; unit litre2_per_monovalent_mEq_per_minute=1.6666667E-5 meter^6*second^(-1)*mole^(-1); unit L_per_minute=1.6666667E-5 meter^3*second^(-1); unit mL=1E-6 meter^3; unit mL_per_L=.001 dimensionless; unit mL_per_L_per_mmHg=7.5006376E-6 kilogram^(-1)*meter^1*second^2; unit mL_per_L_per_minute=1.6666667E-5 second^(-1); unit mL_per_minute_per_mmHg=1.2501063E-10 kilogram^(-1)*meter^4*second^1; unit L_mL_per_minute_per_mmHg=1.2501063E-13 kilogram^(-1)*meter^7*second^1; unit L_per_mL=1E3 dimensionless; unit mL_per_minute=1.6666667E-8 meter^3*second^(-1); unit L_per_minute_per_mmHg=1.2501063E-7 kilogram^(-1)*meter^4*second^1; unit mmHg_per_mL=1.33322E8 kilogram^1*meter^(-4)*second^(-2); math main { realDomain time minute; time.min=0; extern time.max; extern time.delta; real POT mmHg_; POT=35.1148; real POD mmHg_; real POR mmHg_; POR=35; real POB mmHg_; real POK dimensionless; POK=0.1; real AR1(time) dimensionless; real A1K minute; A1K=0.5; real AR1T(time) dimensionless; when(time=time.min) AR1T=1.02127; real POA mmHg_; real PON dimensionless; PON=0.1; real AR2(time) dimensionless; real A2K minute; A2K=60; real AR2T(time) dimensionless; when(time=time.min) AR2T=1.01179; real POC mmHg_; real POZ dimensionless; POZ=2; real AR3(time) dimensionless; real A3K minute; A3K=40000; real AR3T(time) dimensionless; when(time=time.min) AR3T=1.1448; real ARM1(time) dimensionless; real ARM(time) dimensionless; real AUTOSN dimensionless; AUTOSN=0.9; // // // POD=(POT-POR); // // POB=(POD*POK+(1 mmHg_)); // AR1T:time=((POB*(1 per_mmHg)-AR1T)/A1K); AR1=(if (AR1T<.5) .5 else AR1T); // // POA=(PON*POD+(1 mmHg_)); // AR2T:time=((POA*(1 per_mmHg)-AR2T)/A2K); AR2=(if (AR2T<.5) .5 else AR2T); // // POC=(POZ*POD+(1 mmHg_)); // AR3T:time=((POC*(1 per_mmHg)-AR3T)/A3K); AR3=(if (AR3T<.3) .3 else AR3T); // ARM1=(AR1*AR2*AR3); // ARM=((ARM1-1)*AUTOSN+1); // }