Integrated modeling and simulation of recruitment of myocardial perfusion and oxygen delivery in exercise.

While exercise-mediated vasoregulation in the myocardium is understood to be governed by autonomic, myogenic, and metabolic-mediated mechanisms, we do not yet understand the spatial heterogeneity of vasodilation or its effects on microvascular flow patterns and oxygen delivery. This study uses a simulation and modeling approach to explore the mechanisms underlying the recruitment of myocardial perfusion and oxygen delivery in exercise. The simulation approach integrates model components representing: whole-body cardiovascular hemodynamics, cardiac mechanics and myocardial work; myocardial perfusion; and myocardial oxygen transport. Integrating these systems together, model simulations reveal: (1.) To match expected flow and transmural flow ratios at increasing levels of exercise, a greater degree of vasodilation must occur in the subendocardium compared to the subepicardium. (2.) Oxygen extraction and venous oxygenation are predicted to substantially decrease with increasing exercise level preferentially in the subendocardium, suggesting that an oxygen-dependent error signal driving metabolic mediated recruitment of flow would be operative only in the subendocardium. (3.) Under baseline physiological conditions approximately 4% of the oxygen delivered to the subendocardium may be supplied via retrograde flow from coronary veins.

Systems analysis of the mechanisms governing the cardiovascular response to changes in posture and in peripheral demand during exercise.

Blood flows and pressures throughout the human cardiovascular system are regulated in response to various dynamic perturbations, such as changes to peripheral demands in exercise, rapid changes in posture, or loss of blood from hemorrhage, via the coordinated action of the heart, the vasculature, and autonomic reflexes. To assess how the systemic and pulmonary arterial and venous circulation, the heart, and the baroreflex work together to effect the whole-body responses to these perturbations, we integrated an anatomically-based large-vessel arterial tree model with the TriSeg heart model, models capturing nonlinear characteristics of the large and small veins, and baroreflex-mediated regulation of vascular tone and cardiac chronotropy and inotropy. The model was identified by matching data from the Valsalva maneuver (VM), exercise, and head-up tilt (HUT). Thirty-one parameters were optimized using a custom parameter-fitting tool chain, resulting in an unique, high-fidelity whole-body human cardiovascular systems model. Because the model captures the effects of exercise and posture changes, it can be used to simulate numerous clinical assessments, such as HUT, the VM, and cardiopulmonary exercise stress testing. The model can also be applied as a framework for representing and simulating individual patients and pathologies. Moreover, it can serve as a framework for integrating multi-scale organ-level models, such as for the heart or the kidneys, into a whole-body model. Here, the model is used to analyze the relative importance of chronotropic, inotropic, and peripheral vascular contributions to the whole-body cardiovascular response to exercise. It is predicted that in normal physiological conditions chronotropy and inotropy make roughly equal contributions to increasing cardiac output and cardiac power output during exercise. Under upright exercise conditions, the nonlinear pressure-volume relationship of the large veins and sympathetic-mediated venous vasoconstriction are both required to maintain preload to achieve physiological exercise levels. The developed modeling framework is built using the open Modelica modeling language and is freely distributed.

Phenotyping heart failure using model-based analysis and physiology-informed machine learning.

To phenotype mechanistic differences between heart failure with reduced (HFrEF) and preserved (HFpEF) ejection fraction, a closed-loop model of the cardiovascular system coupled with patient-specific transthoracic echocardiography (TTE) and right heart catheterization (RHC) data was used to identify key parameters representing haemodynamics. Thirty-one patient records (10 HFrEF, 21 HFpEF) were obtained from the Cardiovascular Health Improvement Project database at the University of Michigan. Model simulations were tuned to match RHC and TTE pressure, volume, and cardiac output measurements in each patient. The underlying physiological model parameters were plotted against model-based norms and compared between HFrEF and HFpEF. Our results confirm the main mechanistic parameter driving HFrEF is reduced left ventricular (LV) contractility, whereas HFpEF exhibits a heterogeneous phenotype. Conducting principal component analysis, k -means clustering, and hierarchical clustering on the optimized parameters reveal (i) a group of HFrEF-like HFpEF patients (HFpEF1), (ii) a classic HFpEF group (HFpEF2), and (iii) a group of HFpEF patients that do not consistently cluster (NCC). These subgroups cannot be distinguished from the clinical data alone. Increased LV active contractility ( p<0.001 ) and LV passive stiffness ( p<0.001 ) at rest are observed when comparing HFpEF2 to HFpEF1. Analysing the clinical data of each subgroup reveals that elevated systolic and diastolic LV volumes seen in both HFrEF and HFpEF1 may be used as a biomarker to identify HFrEF-like HFpEF patients. These results suggest that modelling of the cardiovascular system and optimizing to standard clinical data can designate subgroups of HFpEF as separate phenotypes, possibly elucidating patient-specific treatment strategies. KEY POINTS: Analysis of data from right heart catheterization (RHC) and transthoracic echocardiography (TTE) of heart failure (HF) patients using a closed-loop model of the cardiovascular system identifies key parameters representing haemodynamic cardiovascular function in patients with heart failure with reduced and preserved ejection fraction (HFrEF and HFpEF). Analysing optimized parameters representing cardiovascular function using machine learning shows mechanistic differences between HFpEF groups that are not seen analysing clinical data alone. HFpEF groups presented here can be subdivided into three subgroups: HFpEF1 described as 'HFrEF-like HFpEF', HFpEF2 as 'classic HFpEF', and a third group of HFpEF patients that do not consistently cluster. Focusing purely on cardiac function consistently captures the underlying dysfunction in HFrEF, whereas HFpEF is better characterized by dysfunction in the entire cardiovascular system. Our methodology reveals that elevated left ventricular systolic and diastolic volumes are potential biomarkers for identifying HFrEF-like HFpEF patients.

Deep phenotyping of cardiac function in heart transplant patients using cardiovascular system models.

KEY POINTS: Right heart catheterization data from clinical records of heart transplant patients are used to identify patient-specific models of the cardiovascular system. These patient-specific cardiovascular models represent a snapshot of cardiovascular function at a given post-transplant recovery time point. This approach is used to describe cardiac function in 10 heart transplant patients, five of which had multiple right heart catheterizations allowing an assessment of cardiac function over time. These patient-specific models are used to predict cardiovascular function in the form of right and left ventricular pressure-volume loops and ventricular power, an important metric in the clinical assessment of cardiac function. Outcomes for the longitudinally tracked patients show that our approach was able to identify the one patient from the group of five that exhibited post-transplant cardiovascular complications. ABSTRACT: Heart transplant patients are followed with periodic right heart catheterizations (RHCs) to identify post-transplant complications and guide treatment. Post-transplant positive outcomes are associated with a steady reduction of right ventricular and pulmonary arterial pressures, toward normal levels of right-side pressure (about 20 mmHg) measured by RHC. This study shows that more information about patient progression is obtained by combining standard RHC measures with mechanistic computational cardiovascular system models. The purpose of this study is twofold: to understand how cardiovascular system models can be used to represent a patient's cardiovascular state, and to use these models to track post-transplant recovery and outcome. To obtain reliable parameter estimates comparable within and across datasets, we use sensitivity analysis, parameter subset selection, and optimization to determine patient-specific mechanistic parameters that can be reliably extracted from the RHC data. Patient-specific models are identified for 10 patients from their first post-transplant RHC, and longitudinal analysis is carried out for five patients. Results of the sensitivity analysis and subset selection show that we can reliably estimate seven non-measurable quantities; namely, ventricular diastolic relaxation, systemic resistance, pulmonary venous elastance, pulmonary resistance, pulmonary arterial elastance, pulmonary valve resistance and systemic arterial elastance. Changes in parameters and predicted cardiovascular function post-transplant are used to evaluate the cardiovascular state during recovery of five patients. Of these five patients, only one showed inconsistent trends during recovery in ventricular pressure-volume relationships and power output. At the four-year post-transplant time point this patient exhibited biventricular failure along with graft dysfunction while the remaining four exhibited no cardiovascular complications.

SemGen: a tool for semantics-based annotation and composition of biosimulation models.

SUMMARY: As the number and complexity of biosimulation models grows, so do demands for tools that can help users understand models and compose more comprehensive and accurate systems from existing models. SemGen is a tool for semantics-based annotation and composition of biosimulation models designed to address this demand. A key SemGen capability is to decompose and then integrate models across existing model exchange formats including SBML and CellML. To support this capability, we use semantic annotations to explicitly capture the underlying biological and physical meanings of the entities and processes that are modeled. SemGen leverages annotations to expose a model's biological and computational architecture and to help automate model composition. AVAILABILITY AND IMPLEMENTATION: SemGen is freely available at https://github.com/SemBioProcess/SemGen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Model annotation and discovery with the Physiome Model Repository.

BACKGROUND: Mathematics and Phy sics-based simulation models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form. Similarly, comprehensive descriptions of such models help to ensure that such models are accessible, discoverable, and reusable. To this end, researchers have developed tools and standards to encode mathematical models of biological systems enabling reproducibility and reuse, tools and guidelines to facilitate semantic description of mathematical models, and repositories in which to archive, share, and discover models. Scientists can leverage these resources to investigate specific questions and hypotheses in a more efficient manner. RESULTS: We have comprehensively annotated a cohort of models with biological semantics. These annotated models are freely available in the Physiome Model Repository (PMR). To demonstrate the benefits of this approach, we have developed a web-based tool which enables users to discover models relevant to their work, with a particular focus on epithelial transport. Based on a semantic query, this tool will help users discover relevant models, suggesting similar or alternative models that the user may wish to explore or use. CONCLUSION: The semantic annotation and the web tool we have developed is a new contribution enabling scientists to discover relevant models in the PMR as candidates for reuse in their own scientific endeavours. This approach demonstrates how semantic web technologies and methodologies can contribute to biomedical and clinical research. The source code and links to the web tool are available at https://github.com/dewancse/model-discovery-tool.

High salt diet impairs cerebral blood flow regulation via salt-induced angiotensin II suppression.

OBJECTIVES: This study sought to determine whether salt-induced ANG II suppression contributes to impaired CBF autoregulation. METHODS: Cerebral autoregulation was evaluated with LDF during graded reductions of blood pressure. Autoregulatory responses in rats fed HS (4% NaCl) diet vs LS (0.4% NaCl) diet were analyzed using linear regression analysis, model-free analysis, and a mechanistic theoretical model of blood flow through cerebral arterioles. RESULTS: Autoregulation was intact in LS-fed animals as MAP was reduced via graded hemorrhage to approximately 50 mm Hg. Short-term (3 days) and chronic (4 weeks) HS diet impaired CBF autoregulation, as evidenced by progressive reductions of laser Doppler flux with arterial pressure reduction. Chronic low dose ANG II infusion (5 mg/kg/min, i.v.) restored CBF autoregulation between the pre-hemorrhage MAP and 50 mm Hg in rats fed short-term HS diet. Mechanistic-based model analysis showed a reduced myogenic response and reduced baseline VSM tone with short-term HS diet, which was restored by ANG II infusion. CONCLUSIONS: Short-term and chronic HS diet lead to impaired autoregulation in the cerebral circulation, with salt-induced ANG II suppression as a major factor in the initiation of impaired CBF regulation.

Cardiovascular regulation in response to multiple hemorrhages: analysis and parameter estimation.

Mathematical models can provide useful insights explaining behavior observed in experimental data; however, rigorous analysis is needed to select a subset of model parameters that can be informed by available data. Here we present a method to estimate an identifiable set of parameters based on baseline left ventricular pressure and volume time series data. From this identifiable subset, we then select, based on current understanding of cardiovascular control, parameters that vary in time in response to blood withdrawal, and estimate these parameters over a series of blood withdrawals. These time-varying parameters are first estimated using piecewise linear splines minimizing the mean squared error between measured and computed left ventricular pressure and volume data over four consecutive blood withdrawals. As a final step, the trends in these splines are fit with empirical functional expressions selected to describe cardiovascular regulation during blood withdrawal. Our analysis at baseline found parameters representing timing of cardiac contraction, systemic vascular resistance, and cardiac contractility to be identifiable. Of these parameters, vascular resistance and cardiac contractility were varied in time. Data used for this study were measured in a control Sprague-Dawley rat. To our knowledge, this is the first study to analyze the response to multiple blood withdrawals both experimentally and theoretically, as most previous studies focus on analyzing the response to one large blood withdrawal. Results show that during each blood withdrawal both systemic vascular resistance and contractility decrease acutely and partially recover, and they decrease chronically across the series of blood withdrawals.

TNF-α increases endothelial progenitor cell adhesion to the endothelium by increasing bond expression and affinity.

Endothelial progenitor cells (EPCs) are a rare population of cells that participate in angiogenesis. To effectively use EPCs for regenerative therapy, the mechanisms by which they participate in tissue repair must be elucidated. This study focused on the process by which activated EPCs bind to a target tissue. It has been demonstrated that EPCs can bind to endothelial cells (ECs) through the tumore necrosis factor-α (TNF-α)-regulated vascular cell adhesion molecule 1/very-late antigen 4 (VLA4) interaction. VLA4 can bind in a high or low affinity state, a process that is difficult to experimentally isolate from bond expression upregulation. To separate these processes, a new parallel plate flow chamber was built, a detachment assay was developed, and a mathematical model was created that was designed to analyze the detachment assay results. The mathematical model was developed to predict the relative expression of EPC/EC bonds made for a given bond affinity distribution. EPCs treated with TNF-α/vehicle were allowed to bind to TNF-α/vehicle-treated ECs in vitro. Bound cells were subjected to laminar flow, and the cellular adherence was quantified as a function of shear stress. Experimental data were fit to the mathematical model using changes in bond expression or affinity as the only free parameter. It was found that TNF-α treatment of ECs increased adhesion through bond upregulation, whereas TNF-α treatment of EPCs increased adhesion by increasing bond affinity. These data suggest that injured tissue could potentially increase recruitment of EPCs for tissue regeneration via the secretion of TNF-α.

Enhanced effects of isoflurane on the long QT syndrome 1-associated A341V mutant.

BACKGROUND: The impact of volatile anesthetics on patients with inherited long QT syndrome (LQTS) is not well understood. This is further complicated by the different genotypes underlying LQTS. No studies have reported on the direct effects of volatile anesthetics on specific LQTS-associated mutations. We investigated the effects of isoflurane on a common LQTS type 1 mutation, A341V, with an unusually severe phenotype. METHODS: Whole cell potassium currents (IKs) were recorded from HEK293 and HL-1 cells transiently expressing/coexpressing wild-type KCNQ1 (α-subunit), mutant KCNQ1, wild-type KCNE1 (ß-subunit), and fusion KCNQ1 + KCNE1. Current was monitored in the absence and presence of clinically relevant concentration of isoflurane (0.54 ± 0.05 mM, 1.14 vol %). Computer simulations determined the resulting impact on the cardiac action potential. RESULTS: Isoflurane had significantly greater inhibitory effect on A341V + KCNE1 (62.2 ± 3.4%, n = 8) than on wild-type KCNQ1 + KCNE1 (40.7 ± 4.5%; n = 9) in transfected HEK293 cells. Under heterozygous conditions, isoflurane inhibited A341V + KCNQ1 + KCNE1 by 65.2 ± 3.0% (n = 13) and wild-type KCNQ1 + KCNE1 (2:1 ratio) by 32.0 ± 4.5% (n = 11). A341V exerted a dominant negative effect on IKs. Similar differential effects of isoflurane were also observed in experiments using the cardiac HL-1 cells. Mutations of the neighboring F340 residue significantly attenuated the effects of isoflurane, and fusion proteins revealed the modulatory effect of KCNE1. Action potential simulations revealed a stimulation frequency-dependent effect of A341V. CONCLUSIONS: The LQTS-associated A341V mutation rendered the IKs channel more sensitive to the inhibitory effects of isoflurane compared to wild-type IKs in transfected cell lines; F340 is a key residue for anesthetic action.

Diffusion coefficients of endogenous cytosolic proteins from rabbit skinned muscle fibers.

Efflux time courses of endogenous cytosolic proteins were obtained from rabbit psoas muscle fibers skinned in oil and transferred to physiological salt solution. Proteins were separated by gel electrophoresis and compared to load-matched standards for quantitative analysis. A radial diffusion model incorporating the dissociation and dissipation of supramolecular complexes accounts for an initial lag and subsequent efflux of glycolytic and glycogenolytic enzymes. The model includes terms representing protein crowding, myofilament lattice hindrance, and binding to the cytomatrix. Optimization algorithms returned estimates of the apparent diffusion coefficients, D(r,t), that were very low at the onset of diffusion (∼10(-10) cm(2) s(-1)) but increased with time as cytosolic protein density, which was initially high, decreased. D(r,t) at later times ranged from 2.11 × 10(-7) cm(2) s(-1) (parvalbumin) to 0.20 × 10(-7) cm(2) s(-1) (phosphofructose kinase), values that are 3.6- to 12.3-fold lower than those predicted in bulk water. The low initial values are consistent with the presence of complexes in situ; the higher later values are consistent with molecular sieving and transient binding of dissociated proteins. Channeling of metabolic intermediates via enzyme complexes may enhance production of adenosine triphosphate at rates beyond that possible with randomly and/or sparsely distributed enzymes, thereby matching supply with demand.

The importance of incorporating ventricular-ventricular interaction (VVI) in the study of pulmonary hypertension.

Ventricular ventricular interaction (VVI) affects blood volume and pressure in the right and left ventricles of the heart due to the location and balance of forces on the septal wall separating the ventricles. In healthy patients, the pressure of the left ventricle is considerably higher than the right, resulting in a septal wall that bows into the right ventricle. However, in patients with pulmonary hypertension, the pressure in the right ventricle increases significantly to a point where the pressure is similar to or surpasses that of the left ventricle during portions of the cardiac cycle. For these patients, the septal wall deviates towards the left ventricle, impacting its function. It is possible to study this effect using mathematical modeling, but existing models are nonlinear, leading to a system of algebraic differential equations that can be challenging to solve in patient-specific optimizations of clinical data. This study demonstrates that a simplified linearized model is sufficient to account for the effect of VVI and that, as expected, the impact is significantly more pronounced in patients with pulmonary hypertension.

Mechanical control of cation channels in the myogenic response.

Microcirculatory vessel response to changes in pressure, known as the myogenic response, is a key component of a tissue's ability to regulate blood flow. Experimental studies have not clearly elucidated the mechanical signal in the vessel wall governing steady-state reduction in vessel diameter upon an increase in intraluminal pressure. In this study, a multiscale computational model is constructed from established models of vessel wall mechanics, vascular smooth muscle (VSM) force generation, and VSM Ca(2+) handling and electrophysiology to compare the plausibility of vessel wall stress or strain as an effective mechanical signal controlling steady-state vascular contraction in the myogenic response. It is shown that, at the scale of a resistance vessel, wall stress, and not stretch (strain), is the likely physiological signal controlling the steady-state myogenic response. The model is then used to test nine candidate VSM stress-controlled channel variants by fitting two separate sets of steady-state myogenic response data. The channel variants include nonselective cation (NSC), supplementary Ca(2+) and Na(+), L-type Ca(2+), and large conductance Ca(2+)-activated K(+) channels. The nine variants are tested in turn, and model fits suggest that stress control of Ca(2+) or Na(+) influx through NSC, supplementary Ca(2+) or Na(+), or L-type Ca(2+) channels is sufficient to produce observed steady-state diameter changes with pressure. However, simulations of steady-state VSM membrane potential, cytosolic Ca(2+), and Na(+) with pressure show only that Na(+) influx through NSC channel also generates known trends with increasing pressure, indicating that stress-controlled Na(+) influx through NSC is sufficient to generate the myogenic response.

Candidate urinary biomarker discovery in ureteropelvic junction obstruction: a proteomic approach.

PURPOSE: Ureteropelvic junction obstruction may either worsen and require surgery, improve or remain stable. It may take upward of 3 years for the natural history to unfold. Urinary proteome analysis using capillary electrophoresis mass spectrometry has been shown to differentiate between normal infants and those with ureteropelvic junction obstruction. We sought to confirm these findings using liquid chromatography/nano-spray mass spectrometry to examine the urinary proteome in patients with unilateral grade IV ureteropelvic junction obstruction compared to age matched healthy infants. MATERIALS AND METHODS: Urine specimens were obtained from 21 healthy infants with normal maternal/fetal ultrasound and 25 infants with grade IV unilateral ureteropelvic junction obstruction. Specimens were prepared using standard methods and subjected to liquid chromatography/tandem mass spectrometry analysis. Normalized data were annotated using the IPA(R) knowledge platform. RESULTS: There were 31 proteins significantly different in their level of abundance at 1 to 6 months, and 18 at 7 to 12 months compared to age matched controls. These proteins clustered into major functional networks. All of the biomarkers previously reported in clinical studies of ureteropelvic junction obstruction were observed with the notable exception of transforming growth factor-beta1. CONCLUSIONS: These results confirm the presence of significant differences in the urinary proteome in unilateral ureteropelvic junction obstruction compared to age matched normal individuals. This study adds new information about levels of abundance of specific proteins and peptides in ureteropelvic junction obstruction, which may allow for better classification of disease subgroups and help to establish improved indications for the early selection of surgical candidates based on urinary protein biomarkers.

Potential role of intermittent functioning of baroreflexes in the etiology of hypertension in spontaneously hypertensive rats.

The spontaneously hypertensive rat (SHR) is a genetic model of primary hypertension with an etiology that includes sympathetic overdrive. To elucidate the neurogenic mechanisms underlying the pathophysiology of this model, we analyzed the dynamic baroreflex response to spontaneous fluctuations in arterial pressure in conscious SHRs, as well as in the Wistar-Kyoto (WKY), the Dahl salt-sensitive, the Dahl salt-resistant, and the Sprague-Dawley rat. Observations revealed the existence of long intermittent periods (lasting up to several minutes) of engagement and disengagement of baroreflex control of heart rate. Analysis of these intermittent periods revealed a predictive relationship between increased mean arterial pressure and progressive baroreflex disengagement that was present in the SHR and WKY strains but absent in others. This relationship yielded the hypothesis that a lower proportion of engagement versus disengagement of the baroreflex in SHR compared with WKY contributes to the hypertension (or increased blood pressure) in SHR compared with WKY. Results of experiments using sinoaortic baroreceptor denervation were consistent with the hypothesis that dysfunction of the baroreflex contributes to the etiology of hypertension in the SHR. Thus, this study provides experimental evidence for the roles of the baroreflex in long-term arterial pressure regulation and in the etiology of primary hypertension in this animal model.

A simulation study of left ventricular decompression using a double lumen arterial cannula prototype during a veno-arterial extracorporeal membrane oxygenation.

BACKGROUND: Veno-arterial extracorporeal membrane oxygenation can be vital to support patients in severe or rapidly progressing cardiogenic shock. In cases of left ventricular distension, left ventricular decompression during veno-arterial extracorporeal membrane oxygenation may be a crucial factor influencing the patient outcome. Application of a double lumen arterial cannula for a left ventricular unloading is an alternative, straightforward method for left ventricular decompression during extracorporeal membrane oxygenation in a veno-arterial configuration. OBJECTIVES: The purpose of this article is to use a mathematical model of the human adult cardiovascular system to analyze the left ventricular function of a patient in cardiogenic shock supported by veno-arterial extracorporeal membrane oxygenation with and without the application of left ventricular unloading using a novel double lumen arterial cannula. METHODS: A lumped model of cardiovascular system hydraulics has been coupled with models of non-pulsatile veno-arterial extracorporeal membrane oxygenation, a standard venous cannula, and a drainage lumen of a double lumen arterial cannula. Cardiogenic shock has been induced by decreasing left ventricular contractility to 10% of baseline normal value. RESULTS: The simulation results indicate that applying double lumen arterial cannula during veno-arterial extracorporeal membrane oxygenation is associated with reduction of left ventricular end-systolic volume, end-diastolic volume, end-systolic pressure, and end-diastolic pressure. CONCLUSIONS: A double lumen arterial cannula is a viable alternative less invasive method for left ventricular decompression during veno-arterial extracorporeal membrane oxygenation. However, to allow for satisfactory extracorporeal membrane oxygenation flow, the cannula design has to be revisited.

Modeling oxygen and carbon dioxide transport and exchange using a closed loop circulatory system.

The binding and buffering of O2 and CO2 in the blood influence their exchange in lung and tissues and their transport through the circulation. To investigate the binding and buffering effects, a model of blood-tissue gas exchange is used. The model accounts for hemoglobin saturation, the simultaneous binding of O2, CO2, H+, 2,3-DPG to hemoglobin, and temperature effects. Invertible Hill-type saturation equations facilitate rapid calculation of respiratory gas redistribution among the plasma, red blood cell and tissue that occur along the concentration gradients in the lung and in the capillary-tissue exchange regions. These equations are well-suited to analysis of transients in tissue metabolism and partial pressures of inhaled gas. The modeling illustrates that because red blood cell velocities in the flowing blood are higher than plasma velocities after a transient there can be prolonged differences between RBC and plasma oxygen partial pressures. The blood-tissue gas exchange model has been incorporated into a higher level model of the circulatory system plus pulmonary mechanics and gas exchange using the RBC and plasma equations to account for pH and CO2 buffering in the blood.

Practical identifiability and uncertainty quantification of a pulsatile cardiovascular model.

Mathematical models are essential tools to study how the cardiovascular system maintains homeostasis. The utility of such models is limited by the accuracy of their predictions, which can be determined by uncertainty quantification (UQ). A challenge associated with the use of UQ is that many published methods assume that the underlying model is identifiable (e.g. that a one-to-one mapping exists from the parameter space to the model output). In this study we present a novel workflow to calibrate a lumped-parameter model to left ventricular pressure and volume time series data. Key steps include using (1) literature and available data to determine nominal parameter values; (2) sensitivity analysis and subset selection to determine a set of identifiable parameters; (3) optimization to find a point estimate for identifiable parameters; and (4) frequentist and Bayesian UQ calculations to assess the predictive capability of the model. Our results show that it is possible to determine 5 identifiable model parameters that can be estimated to our experimental data from three rats, and that computed UQ intervals capture the measurement and model error.

Computational model-based assessment of baroreflex function from response to Valsalva maneuver.

Functional metrics of autonomic control of heart rate, including baroreflex sensitivity, have been shown to be strongly associated with cardiovascular risk. A decrease in baroreflex sensitivity with aging is hypothesized to represent a contributing causal factor in the etiology of primary hypertension. To assess baroreflex function in human subjects, two complementary methods to simulate the response in heart rate elicited by the Valsalva maneuver were developed and applied to data obtained from a cohort of healthy normal volunteers. The first method is based on representing the baroreflex arc as a simple linear filter, transforming changes in arterial pressure to changes in R-R interval. The second method invokes a physiologically based model for arterial mechanics, afferent baroreceptor strain-dependent firing, and control of heart rate via central autonomic response to changes in afferent inputs from aortic and carotid sensors. Analysis based on the linear filter model reveals that the effective response time of the baroreflex arc tends to increase with age in healthy subjects and that the response time/response rate is a predictor of resting systolic pressure. Similar trends were obtained based on the physiologically based model. Analysis of the Valsalva response using the physiologically based model further reveals that different afferent inputs from the carotid sinus and the aortic arch baroreceptors govern different parts of the heart rate response. The observed relationship between baroreflex sensitivity and systolic pressure is surprising because hypertensive subjects were excluded from the study, and there was no observed relationship between arterial pressure and age. NEW & NOTEWORTHY We introduce two methods to assess baroreflex function from data recorded from human subjects performing the Valsalva maneuver. Results demonstrate that the baroreflex response time tends to increase with age in healthy subjects, that response time represents a predictor of resting systolic pressure, and that the Valsalva response reveals different effects mediated by baroreceptors in the carotid sinus compared with those in the aortic arch.