A mechanistic physicochemical model of carbon dioxide transport in blood

Thermodynamic limitations on brain oxygen metabolism: physiological implications

Recent thermodynamic modelling indicates that maintaining the brain tissue ratio of O2 to CO2 (abbreviated tissue O2 /CO2 ) is critical for preserving the entropy increase available from oxidative metabolism of glucose, with a fall of that available entropy leading to a reduction of the phosphorylation potential and impairment of brain energy metabolism. This provides a novel perspective for understanding physiological responses under different conditions in terms of preserving tissue O2 /CO2 . To enable estimation of tissue O2 /CO2 in the human brain, a detailed mathematical model of O2 and CO2 transport was developed, and applied to reported physiological responses to different challenges, asking: how well is tissue O2 /CO2 preserved? Reported experimental results for increased neural activity, hypercapnia and hypoxia due to high altitude are consistent with preserving tissue O2 /CO2 . The results highlight two physiological mechanisms that control tissue O2 /CO2 : cerebral blood flow, which modulates tissue O2 ; and ventilation rate, which modulates tissue CO2 . The hypoxia modelling focused on humans at high altitude, including acclimatized lowlanders and Tibetan and Andean adapted populations, with a primary finding that decreasing CO2 by increasing ventilation rate is more effective for preserving tissue O2 /CO2 than increasing blood haemoglobin content to maintain O2 delivery to tissue. This work focused on the function served by particular physiological responses, and the underlying mechanisms require further investigation. The modelling provides a new framework and perspective for understanding how blood flow and other physiological factors support energy metabolism in the brain under a wide range of conditions. KEY POINTS: Thermodynamic modelling indicates that preserving the O2 /CO2 ratio in brain tissue is critical for preserving the entropy change available from oxidative metabolism of glucose and the phosphorylation potential underlying energy metabolism. A detailed model of O2 and CO2 transport was developed to allow estimation of the tissue O2 /CO2 ratio in the human brain in different physiological states. Reported experimental results during hypoxia, hypercapnia and increased oxygen metabolic rate in response to increased neural activity are consistent with maintaining brain tissue O2 /CO2 ratio. The hypoxia modelling of high-altitude acclimatization and adaptation in humans demonstrates the critical role of reducing CO2 with increased ventilation for preserving tissue O2 /CO2 . Preservation of tissue O2 /CO2 provides a novel perspective for understanding the function of observed physiological responses under different conditions in terms of preserving brain energy metabolism, although the mechanisms underlying these functions are not well understood.

Computed cardiopulmonography and the idealized lung clearance index, iLCI2.5, in early-stage cystic fibrosis

This study explored the use of computed cardiopulmonography (CCP) to assess lung function in early-stage cystic fibrosis (CF). CCP has two components. The first is a particularly accurate technique for measuring gas exchange. The second is a computational cardiopulmonary model where patient-specific parameters can be estimated from the measurements of gas exchange. Twenty-five participants (14 healthy controls, 11 early-stage CF) were studied with CCP. They were also studied with a standard clinical protocol to measure the lung clearance index (LCI2.5). Ventilation inhomogeneity, as quantified through CCP parameter σlnCl, was significantly greater (P < 0.005) in CF than in controls, and anatomical deadspace relative to predicted functional residual capacity (DS/FRCpred) was significantly more variable (P < 0.002). Participant-specific parameters were used with the CCP model to calculate idealized values for LCI2.5 (iLCI2.5) where extrapulmonary influences on the LCI2.5, such as breathing pattern, had all been standardized. Both LCI2.5 and iLCI2.5 distinguished clearly between CF and control participants. LCI2.5 values were mostly higher than iLCI2.5 values in a manner dependent on the participant's respiratory rate (r = 0.46, P < 0.05). The within-participant reproducibility for iLCI2.5 appeared better than for LCI2.5, but this did not reach statistical significance (F ratio = 2.2, P = 0.056). Both a sensitivity analysis on iLCI2.5 and a regression analysis on LCI2.5 revealed that these depended primarily on an interactive term between CCP parameters of the form σlnCL*(DS/FRC). In conclusion, the LCI2.5 (or iLCI2.5) probably reflects an amalgam of different underlying lung changes in early-stage CF that would require a multiparameter approach, such as potentially CCP, to resolve.NEW & NOTEWORTHY Computed cardiopulmonography is a new technique comprising a highly accurate sensor for measuring respiratory gas exchange coupled with a cardiopulmonary model that is used to identify a set of patient-specific characteristics of the lung. Here, we show that this technique can improve on a standard clinical approach for lung function testing in cystic fibrosis. Most particularly, an approach incorporating multiple model parameters can potentially separate different aspects of pathological change in this disease.

Integral assessment of gas exchange during veno-arterial ECMO: accuracy and precision of a modified Fick principle in a porcine model

Assessment of native cardiac output during extracorporeal circulation is challenging. We assessed a modified Fick principle under conditions such as dead space and shunt in 13 anesthetized swine undergoing centrally cannulated veno-arterial extracorporeal membrane oxygenation (V-A ECMO, 308 measurement periods) therapy. We assumed that the ratio of carbon dioxide elimination (V̇co₂) or oxygen uptake (V̇o₂) between the membrane and native lung corresponds to the ratio of respective blood flows. Unequal ventilation/perfusion (V̇/Q̇) ratios were corrected towards unity. Pulmonary blood flow was calculated and compared to an ultrasonic flow probe on the pulmonary artery with a bias of 99 mL/min (limits of agreement -542 to 741 mL/min) with blood content V̇o₂ and no-shunt, no-dead space conditions, which showed good trending ability (least significant change from 82 to 129 mL). Shunt conditions led to underestimation of native pulmonary blood flow (bias -395, limits of agreement -1,290 to 500 mL/min). Bias and trending further depended on the gas (O₂, CO₂) and measurement approach (blood content vs. gas phase). Measurements in the gas phase increased the bias (253 [LoA -1,357 to 1,863 mL/min] for expired V̇o₂ bias 482 [LoA -760 to 1,724 mL/min] for expired V̇co₂) and could be improved by correction of V̇/Q̇ inequalities. Our results show that common assumptions of the Fick principle in two competing circulations give results with adequate accuracy and may offer a clinically applicable tool. Precision depends on specific conditions. This highlights the complexity of gas exchange in membrane lungs and may further deepen the understanding of V-A ECMO.

Physicochemical properties of abnormal blood acid-base buffering

This paper describes two new features 1) development of physicochemically based, two-compartment models describing acid-base-state changes in normal and abnormal blood and 2) use of model results to view and describe physicochemical properties of blood, in terms of Pco₂ as the causative independent variable and effected [H⁺] changes as the dependent variable. Models were derived from an in vitro experimental study, where normal blood was made both hypoproteinemic and hyperalbuminemic and then equilibrated with CO₂. Strong-ion gap (SIG) values were selected to match model and experimental pH. The effect of individual physicochemical factors affecting blood acid-base-state were evaluated from their induced changes on buffer curve linearized slope (β_H+) and [H⁺] curve shift at 40 mmHg ([H⁺]₄₀). Model findings were: 1) in severe hypoproteinemia, hemoglobin enhances buffering (decreases β_H+), whereas albumin compromises it, resulting in an almost unchanged β_H+; [H⁺]₄₀ decreases (alkalemia) due to hypoalbuminemia. 2) Severe hyperalbuminemia greatly increases both β_H+ and [H⁺]₄₀, hence, compromising buffering and causing a severe acidemia. 3) Pco₂-induced changes in the electrical-charge concentration of hemoglobin are the principal factor responsible for maintaining normal buffering characteristics in hypoproteinemia and hyperalbuminemia. 4) SIG values are a third Pco₂-independent characteristic of blood acid-base state and 5) the quantities, β_H+, [H⁺]₄₀, and SIG, derived from a [H⁺] vs. Pco₂ perspective, are a more informative and intuitive way to characterize blood acid-base state.NEW & NOTEWORTHY This study represents the most up-to-date, physicochemical, multi-compartment computer model of the processes involved in determining the acid-base buffering state of blood. Previous models lack this capability, notably by being single compartment and/or lacking electroneutrality and osmotic constraints. Model results, analyzed from a different perspective of dependent [H⁺] changes resulting from independent Pco₂ changes, provide a new set of Pco₂-independent parameters, characteristic of blood buffering properties.

Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia

Busana et al. (doi.org/10.1152/japplphysiol.00871.2020) published 5 patients with COVID-19 in whom the fraction of non-aerated lung tissue had been quantified by computed tomography. They assumed that shunt flow fraction was proportional to the non-aerated lung fraction, and, by randomly generating 10⁶ different bimodal distributions for the ventilation-perfusion (V˙/Q˙) ratios in the lung, specified as sets of paired values {V˙i,Q˙i}, sought to identify as solutions those that generated the observed arterial partial pressures of CO₂ and O₂ (Pa_CO2 and Pa_O2). Our study sought to develop a direct method of calculation to replace the approach of randomly generating different distributions, and so provide more accurate solutions that were within the measurement error of the blood-gas data. For the one patient in whom Busana et al. did not find solutions, we demonstrated that the assumed shunt flow fraction led to a non-shunt blood flow that was too low to support the required gas exchange. For the other four patients, we found precise solutions (prediction error < 1x10^-3 mmHg for both Pa_CO2 and Pa_O2), with distributions qualitatively similar to those of Busana et al. These distributions were extremely wide and unlikely to be physically realisable, because they predict the maintenance of very large concentration gradients in regions of the lung where convection is slow. We consider that these wide distributions arise because the assumed value for shunt flow is too low in these patients, and we discuss possible reasons why the assumption relating to shunt flow fraction may break down in COVID-19 pneumonia.

The whole-cell kinetic metabolic model of the pH regulation mechanisms in human erythrocytes

Mathematical modeling in recent years helped to obtain answers to questions that were difficult or even impossible to answer experimentally, to predict several unexpected connections in cell metabolism and to understand and importance of certain biochemical reactions. Due to the complexity and variety of processes underlying the mechanisms of intracellular pH (pHi) regulation, mathematical modeling and metabolome analysis are powerful tools for their analysis. In this regard, a mathematical metabolic model for human erythrocytes was created, which combines cellular metabolism with acid-base processes and gas exchange. The model consists of the main metabolic pathways, such as glycolysis, the pentose phosphate pathway, some membrane transport systems, and interactions between hemoglobin and metabolites. The Jacobs-Stewart cycle, which is fundamental in gas exchange and pH regulation, was included to these pathways. The model was created in the COPASI environment, consisted of 85 reactions, the rate of which is based on accurate kinetic equations. The time dependences of reaction flows and metabolite concentrations, as an outcome of calculations, allowed us to reproduce the behaviour of the metabolic system after its disturbance in vitro and to establish the recovery mechanisms or approximation to stationary states. The COPASI simulation environment provides model flexibility by reproducing any experimental design by optimizing direct quantitative comparisons between measured and predicted results. Thus, the procedure of parameters optimization (Parameter Estimation) followed by the solution of the model’s differential equations (Time Course procedure) was used to predict the behaviour of all measured and unmeasured variables over time. The initial intracellular concentrations of CO2, HCO3– in human erythrocytes used for incubation in a phosphate buffer medium were calculated. Changes in CO2, HCO3– content over time were shown. It was established that the regulation of pH in erythrocytes placed in a buffer medium takes place with the participation of two types of processes – fast (takes place in 1.3 s) and slow. It is shown that fast processes are aimed at restoring the intracellular balance between CO2 and HCO3–, slow processes are aimed at establishing the balance of H+ between the cell and the extracellular environment. The role of carbonic anhydrase (CA) and hemoglobin in the processes of pH stabilization is shown and analyzed. The physiological role of the metabolon between band 3 protein (AE1), CA, aquaporin and hemoglobin in maintaining pH homeostasis in the conditions of in vitro experiments are discussed.

Stewart analysis unmasks acidifying and alkalizing effects of ionic shifts during acute severe respiratory alkalosis

PURPOSE

Although both the Henderson-Hasselbalch method and the Stewart approach can be used to analyze acid-base disturbances and metabolic and respiratory compensation mechanisms, the latter may be superior in detecting subtle metabolic changes.

MATERIALS AND METHODS

We analyzed acid-base disturbances using both approaches in six healthy male volunteers practicing extreme voluntary hyperventilation. Arterial blood gas parameters were obtained during a breathing exercise consisting of approximately 30 cycles of powerful hyperventilation followed by breath retention for approximately 2 min.

RESULTS

Hyperventilation increased pH from 7.39 ± 0.01 at baseline to 7.74 ± 0.06, PaCO₂ decreased from 34.1 ± 1.1 to 12.6 ± 0.7 mmHg, PaO₂ increased from 116 ± 4.6 to 156 ± 4.3 mmHg. Baseline apparent strong ion difference was 42.3 ± 0.5 mEq/L, which decreased to 37.1 ± 0.7 mEq/L following hyperventilation. The strong ion gap significantly decreased following hyperventilation, with baseline levels of 10.0 ± 0.9 dropping to 6.4 ± 1.1 mEq/L.

CONCLUSIONS

Henderson-Hasselbalch analysis indicated a profound and purely respiratory alkalosis with no metabolic compensation following extreme hyperventilation. The Stewart approach revealed metabolic compensation occurring within minutes. These results challenge the long-held axiom that metabolic compensation of acute respiratory acid-base changes is a slow process.

Estimating cardiac output based on gas exchange during veno-arterial extracorporeal membrane oxygenation in a simulation study using paediatric oxygenators

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) therapy is a rescue strategy for severe cardiopulmonary failure. The estimation of cardiac output during VA-ECMO is challenging. A lung circuit (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_Lung) and an ECMO circuit (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_ECMO) with oxygenators for CO₂ removal (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂) and O₂ uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.O₂) simulated the setting of VA-ECMO with varying ventilation/perfusion (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V./\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙) ratios and shunt. A metabolic chamber with a CO₂/N₂ blend simulated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.O₂. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_Lung was estimated with a modified Fick principle: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_Lung = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_ECMO × (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V. CO₂ or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.O_2Lung)/(\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂ or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.O_2ECMO). A normalization procedure corrected \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂ values for a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V./\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙ of 1. Method agreement was evaluated by Bland–Altman analysis. Calculated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_Lung using gaseous \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.O₂ correlated well with measured \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_Lung with a bias of 103 ml/min [− 268 to 185] ml/min; Limits of Agreement: − 306 ml/min [− 241 to − 877 ml/min] to 512 ml/min [447 to 610 ml/min], r² 0.85 [0.79–0.88]). Blood measurements of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂ showed an increased bias (− 260 ml/min [− 1503 to 982] ml/min), clinically not applicable. Shunt and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V./\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙ mismatch decreased the agreement of methods significantly. This in-vitro simulation shows that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.CO₂ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathop {\text{V}}\limits^{.}$$\end{document}V.O₂ in steady-state conditions allow for clinically applicable calculations of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{Q}}}$$\end{document}Q˙_Lung during VA-ECMO therapy.

A dynamic model of the body gas stores for carbon dioxide, oxygen, and inert gases that incorporates circulatory transport delays to and from the lung

Many models of the body’s gas stores have been generated for specific purposes. Here, we seek to produce a more general purpose model that: 1) is relevant for both respiratory (CO₂ and O₂) and inert gases; 2) is based firmly on anatomy and not arbitrary compartments; 3) can be scaled to individuals; and 4) incorporates arterial and venous circulatory delays as well as tissue volumes so that it can reflect rapid transients with greater precision. First, a “standard man” of 11 compartments was produced, based on data compiled by the International Radiation Protection Commission. Each compartment was supplied via its own parallel circulation, the arterial and venous volumes of which were based on reported tissue blood volumes together with data from a detailed anatomical model for the large arteries and veins. A previously published model was used for the blood gas chemistry of CO₂ and O₂. It was not permissible ethically to insert pulmonary artery catheters into healthy volunteers for model validation. Therefore, validation was undertaken by comparing model predictions with previously published data and by comparing model predictions with experimental data for transients in gas exchange at the mouth following changes in alveolar gas composition. Overall, model transients were fastest for O₂, intermediate for CO₂, and slowest for N₂. There was good agreement between model estimates and experimentally measured data. Potential applications of the model include estimation of closed-loop gain for the ventilatory chemoreflexes and improving the precision associated with multibreath washout testing and respiratory measurement of cardiac output.

NEW & NOTEWORTHY A model for the body gas stores has been generated that is applicable to both respiratory gases (CO₂ and O₂) and inert gases. It is based on anatomical details for organ volumes and blood contents together with anatomical details of the large arteries. It can be scaled to the body size and composition of different individuals. The model enables mixed venous gas compositions to be predicted from the systemic arterial compositions.

The differing physiology of nitrogen and tracer gas multiple-breath washout techniques

Background

Multiple-breath washout techniques are increasingly used to assess lung function. The principal statistic obtained is the lung clearance index (LCI), but values obtained for LCI using the nitrogen (N₂)-washout technique are higher than those obtained using an exogenous tracer gas such as sulfur hexafluoride. This study explored whether the pure oxygen (O₂) used for the N₂ washout could underlie these higher values.

Methods

A model of a homogenous, reciprocally ventilated acinus was constructed. Perfusion was kept constant, and ventilation adjusted by varying the swept volume during the breathing cycle. The blood supplying the acinus had a standard mixed-venous composition. Carbon dioxide and O₂ exchange between the blood and acinar gas proceeded to equilibrium. The model was initialised with either air or air plus tracer gas as the inspirate. Washouts were conducted with pure O₂ for the N₂ washout or with air for the tracer gas washout.

Results

At normal ventilation/perfusion (V′/Q′) ratios, the rate of washout of N₂ and exogenous tracer gas was almost indistinguishable. At low V′/Q′, the N₂ washout lagged the tracer gas washout. At very low V′/Q′, N₂ became trapped in the acinus. Under low V′/Q′ conditions, breathing pure O₂ introduced a marked asymmetry between the inspiratory and expiratory gas flow rates that was not present when breathing air.

Discussion

The use of pure O₂ to washout N₂ increases O₂ uptake in low V′/Q′ units. This generates a background gas flow into the acinus that opposes flow out of the acinus during expiration, and so delays the washout of N₂.

Differences in lung clearance index between nitrogen and exogenous tracer gas multiple-breath washout tests can be explained by the oxygen used to wash out nitrogen generating convective flows of gas into low ventilation/perfusion unitshttps://bit.ly/3l0xq0G

A quantitative method for estimating the adaptedness in a physiological study

Background

Existed mathematical models of individual adaptation are mostly reductionist by nature. Researchers usually a priori consider the subject adapted basing only on the fact of continued or prolonged influence of the harmful factor. This paper describes a method that allows assessing the physiological adaptedness to experimental challenges on the basis of holistic approach and quantitative criteria.

Methods

The suggested method comprises simple equations and incorporates into the model an indicator that differentiates functions in regard to their significance for determining physiological adaptedness considered as an outcome of the adaptive process.

Results

The proposed empirical model affords the possibility of comparing subjects in respect to their resistance to several loads. Physiological parameters were differentiated with regard to their significance for assessing adaptedness. Two examples of animal adaptation to exercise after physical training and plant adaptogen administration are considered.

Conclusion

The calculated index of adaptedness is useful in that it replaces wordy descriptions of large tables that reveal alterations in numerous parameters of many subjects under study.

Laser spectroscopy for breath analysis: towards clinical implementation

Detection and analysis of volatile compounds in exhaled breath represents an attractive tool for monitoring the metabolic status of a patient and disease diagnosis, since it is non-invasive and fast. Numerous studies have already demonstrated the benefit of breath analysis in clinical settings/applications and encouraged multidisciplinary research to reveal new insights regarding the origins, pathways, and pathophysiological roles of breath components. Many breath analysis methods are currently available to help explore these directions, ranging from mass spectrometry to laser-based spectroscopy and sensor arrays. This review presents an update of the current status of optical methods, using near and mid-infrared sources, for clinical breath gas analysis over the last decade and describes recent technological developments and their applications. The review includes: tunable diode laser absorption spectroscopy, cavity ring-down spectroscopy, integrated cavity output spectroscopy, cavity-enhanced absorption spectroscopy, photoacoustic spectroscopy, quartz-enhanced photoacoustic spectroscopy, and optical frequency comb spectroscopy. A SWOT analysis (strengths, weaknesses, opportunities, and threats) is presented that describes the laser-based techniques within the clinical framework of breath research and their appealing features for clinical use.

Potential for noninvasive assessment of lung inhomogeneity using highly precise, highly time-resolved measurements of gas exchange

Inhomogeneity in the lung impairs gas exchange and can be an early marker of lung disease. We hypothesized that highly precise measurements of gas exchange contain sufficient information to quantify many aspects of the inhomogeneity noninvasively. Our aim was to explore whether one parameterization of lung inhomogeneity could both fit such data and provide reliable parameter estimates. A mathematical model of gas exchange in an inhomogeneous lung was developed, containing inhomogeneity parameters for compliance, vascular conductance, and dead space, all relative to lung volume. Inputs were respiratory flow, cardiac output, and the inspiratory and pulmonary arterial gas compositions. Outputs were expiratory and pulmonary venous gas compositions. All values were specified every 10 ms. Some parameters were set to physiologically plausible values. To estimate the remaining unknown parameters and inputs, the model was embedded within a nonlinear estimation routine to minimize the deviations between model and data for CO₂, O₂, and N₂ flows during expiration. Three groups, each of six individuals, were studied: young (20-30 yr); old (70-80 yr); and patients with mild to moderate chronic obstructive pulmonary disease (COPD). Each participant undertook a 15-min measurement protocol six times. For all parameters reflecting inhomogeneity, highly significant differences were found between the three participant groups ( P < 0.001, ANOVA). Intraclass correlation coefficients were 0.96, 0.99, and 0.94 for the parameters reflecting inhomogeneity in deadspace, compliance, and vascular conductance, respectively. We conclude that, for the particular participants selected, highly repeatable estimates for parameters reflecting inhomogeneity could be obtained from noninvasive measurements of respiratory gas exchange. NEW & NOTEWORTHY This study describes a new method, based on highly precise measures of gas exchange, that quantifies three distributions that are intrinsic to the lung. These distributions represent three fundamentally different types of inhomogeneity that together give rise to ventilation-perfusion mismatch and result in impaired gas exchange. The measurement technique has potentially broad clinical applicability because it is simple for both patient and operator, it does not involve ionizing radiation, and it is completely noninvasive.