/* * Guyton Model: pulmonary_fluid_dynamics * * 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. * * This particular CellML model describes a highly simplified analysis * of pulmonary fluid dynamics. In general, the gel portion of * the pulmonary fluid is ignored, so that the pulmonary fluid * volume (VPF) is in reality an approximation of the amount of * fluid that is relatively freely mobile. Though this fluid is * called "interstitial fluid," it includes fluid in the respiratory * passages. Likewise, the pressure-volume curve of the pulmonary * interstitium is highly simplified, as well as the control of * lymph flow. Nevertheless, for many purposes, this simplified * analysis serves quite well. * * model diagram * * [[Image file: full_model.png]] * * A systems analysis diagram for the full Guyton model describing * circulation regulation. * * model diagram * * [[Image file: pulm_fluid.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. * (A PDF version of the article are available to journal subscribers * on the Annual Review of Physiology website.) 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 mmHg_L=.133322 kilogram^1*meter^2*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 gram_per_L=1 kilogram^1*meter^(-3); unit L_mmHg_per_gram=133.322 meter^2*second^(-2); unit mmHg_minute_per_L=7999320 kilogram^1*meter^(-4)*second^(-1); unit gram_per_minute=1.6666667E-5 kilogram^1*second^(-1); 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 PPC mmHg_; PPC=29.9941; real PPA mmHg_; PPA=15.6376; real PLA mmHg_; PLA=2; real CPP gram_per_L; CPP=71.9719; real RPV mmHg_minute_per_L; RPV=1.55719; real RPA mmHg_minute_per_L; RPA=1.5683; real PCP mmHg_; real POS(time) mmHg_; real PPI(time) mmHg_; real PFI(time) L_per_minute; real CPF L_per_minute_per_mmHg; CPF=0.0003; real PLF(time) L_per_minute; real DFP(time) L_per_minute; real VPF(time) litre; real DFZ(time) L_per_minute; real VPF1(time) litre; when(time=time.min) VPF1=0.0123238; real PPO(time) gram_per_minute; real PPN(time) gram_per_minute; real PPD(time) gram_per_minute; real CPN(time) gram_per_L; real PPZ(time) gram_per_minute; real PPR1(time) gram; when(time=time.min) PPR1=0.419998; real PPR(time) gram; // // // PCP=((PPA-PLA)*RPV/(RPV+RPA)+PLA); // PFI=((PCP-PPI+POS-PPC)*CPF); // DFZ=(PFI-PLF); DFP=DFZ; VPF1:time=DFP; VPF=(if (VPF1<(.001 litre)) (.001 litre) else VPF1); // PPI=((2 mmHg_)-(.15 mmHg_L)/VPF); // PPZ=(PPN-PPO); PPD=PPZ; PPR1:time=PPD; PPR=(if (PPR1<(.025 gram)) (.025 gram) else PPR1); CPN=(PPR/VPF); // POS=(CPN*(.4 L_mmHg_per_gram)); // PPN=((CPP-CPN)*(2.25E-4 L_per_minute)); // PLF=((PPI+(11 mmHg_))*(3E-4 L_per_minute_per_mmHg)); PPO=(PLF*CPN); // }