A Computational Biology Approach to Modelling and Identification of Human Physiology
Conference presentation sharing aspects of a computational biology approach to modelling and identification of human physiology.
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Conference presentation sharing aspects of a computational biology approach to modelling and identification of human physiology.
Analog-to-digital computer accepts physiological flight data as three basic analog input signals - the ECG signal, the flowmeter signal which is a respiration monitor, and the accelerometer signal which measures the normal-g-load on the subject.
A numerical model of the cardiovascular system was used to quantify the influences on cardiac function of intrathoracic pressure and intravascular and intraventricular hydrostatic pressure, which are fundamental biomechanical stimuli for orthostatic response. The model included a detailed arterial circulation with lumped parameter models of the atria, ventricles, pulmonary circulation, and venous circulation. The venous circulation was divided into cranial, central, and caudal regions with nonlinear compliance. Changes in intrathoracic pressure and the effects of hydrostatic pressure were simulated in supine, launch, sitting, and standing postures for 0, 1, and 1.8 G. Increasing intrathoracic pressure experienced with increasing gravity caused 12% and 14% decreases in cardiac output for 1 and 1.8 G supine, respectively, compared to 0 G. Similar results were obtained for launch posture, in which the effects of changing intrathoracic pressure dominated those of hydrostatic pressure. Compared to 0 G, cardiac output decreased 0.9% for 1 G launch and 15% for 1.8 G launch. In sitting and standing, the position of the heart above the hydrostatic indifference level caused the effects of changing hydrostatic pressure to dominate those of intrathoracic pressure. Compared to 0 G, cardiac output decreased 13% for 1 G sitting and 23% for 1.8 G sitting, and decreased 17% for 1 G standing and 31% for 1.8 G standing. For a posture change from supine to standing in 1 G, cardiac output decreased, consistent with the trend necessary to explain orthostatic intolerance in some astronauts during postflight stand tests. Simulated lower body negative pressure (LBNP) in 0 G reduced cardiac output and mean aortic pressure similar to I G standing, suggesting that LBNP provides at least some cardiovascular stimuli that may be useful in preventing postflight orthostatic intolerance. A unifying concept, consistent with the Frank-Starling mechanism of the heart, was that cardiac output was proportional to cardiac diastolic transmural pressure for all postures and gravitational accelerations.
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The invention is an apparatus and method of biofeedback training for attaining a physiological state optimally consistent with the successful performance of a task, wherein the probability of successfully completing the task is made is inversely proportional to a physiological difference value, computed as the absolute value of the difference between at least one physiological signal optimally consistent with the successful performance of the task and at least one corresponding measured physiological signal of a trainee performing the task. The probability of successfully completing the task is made inversely proportional to the physiological difference value by making one or more measurable physical attributes of the environment in which the task is performed, and upon which completion of the task depends, vary in inverse proportion to the physiological difference value.
Methane represents 34% of U.S. energy consumption and is a major greenhouse gas related to the global carbon cycle and energy production. However, current industrial practices significantly increase atmospheric methane levels, necessitating a deeper understanding of its biosynthesis and oxidation. Methyl-coenzyme M reductase (MCR) is central to biological methane metabolism, catalyzing the final step of methanogenesis and the first step in anaerobic methane oxidation. It is also a key target for strategies to capture and transform methane into value-added chemicals.The active site of MCR is a buried Ni-based cofactor only accessible by the substrates via a 50 Å long tunnel. Although the Ni(I) state is required to initiate catalysis, capturing this state remains a challenge for the current structural techniques. Recent advances in structural biology using X-ray Free-Electron Laser serial crystallography have provided insights into MCR's inactive Ni(II) state at room temperature and show promise for capturing its active Ni(I) form.Our team has established several critical aspects of the MCR mechanism using a combination of experimental and computational studies. MCR uses CH 3 -SCoM and CoBSH as substrates, producing methane and a disulfide product CoMSSCoB. Kinetic analysis showed that productive substrate binding requires CH 3 -SCoM to bind first, inducing conformational changes that optimize the active site for subsequent CoBSH binding. Following substrate binding, four proposed methane production/oxidation mechanisms were examined, establishing whether the reaction proceeds through an organometallic methyl-nickel(III), methyl anion ion, or methyl radical intermediate. Experimental measurements using CoBSH analogs successfully slowed the reaction, allowing for mechanistic insight that demonstrated the methyl radical pathway, where the initial interactions involve homolytic cleavage of the methyl-sulfur bond, generating a methyl radical that quickly abstracts the thiol hydrogen atom of CoBSH to form methane. Computational studies further confirmed that, compared to other mechanisms, the methyl radical mechanism is thermodynamically more favorable and accessible under physiological conditions.Spectroscopic and computational studies challenged the conventional understanding of substrate binding in MCR by proposing an alternative positioning of CH 3 -SCoM and CoMSSCoB in the active site pocket. The research suggested that CH 3 -SCoM (substrate) and CoMSSCoB (product) bind via their sulfonate groups to the Ni(I) center of cofactor F 430 . This binding allows for the reaction without substrate reorganization in the pocket but would require a long-range electron transfer. Altogether, the work summarized in this review reflects our current understanding of the enzyme's catalytic mechanism and structural dynamics. This is essential for developing efficient methane conversion technologies that could mitigate its environmental impact while harnessing energy-storage properties.
This paper summarizes several related research projects supported by NASA which seek to apply computer models to space medicine and physiology. These efforts span a wide range of activities, including mathematical models used for computer simulations of physiological control systems; power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and computer-aided diagnosis programs.
With the ambitious goals to send manned missions to asteroids and onto Mars, substantial work will be required to ensure the well being of the men and women who will undertake these difficult missions. Unlike current International Space Station or Shuttle missions, astronauts will be required to endure long-term exposure to higher levels of radiation, isolation and reduced gravity. These new operation conditions will pose health risks that are currently not well understood and perhaps unanticipated. Therefore, it is essential to develop and apply advanced tools to predict, assess and mitigate potential hazards to astronaut health. NASA s Digital Astronaut Project (DAP) is working to develop and apply computational models of physiologic response to space flight operation conditions over various time periods and environmental circumstances. The collective application and integration of well vetted models assessing the physiology, biomechanics and anatomy is referred to as the Digital Astronaut. The Digital Astronaut simulation environment will serve as a practical working tool for use by NASA in operational activities such as the prediction of biomedical risks and functional capabilities of astronauts. In additional to space flight operation conditions, DAP s work has direct applicability to terrestrial biomedical research by providing virtual environments for hypothesis testing, experiment design, and to reduce animal/human testing. A practical application of the DA to assess pre and post flight responses to exercise is illustrated and the difficulty in matching true physiological responses is discussed.
Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.
A canine model was used to study the effects of different environmental stresses on the heart and coronary circulation. The heart was surgically instrumented to measure coronary blood flow, left ventricular pressure, and other cardiovascular variables. Coronary flow was recorded by telemetry. Physiologic data were processed and analyzed by analog and digital computers. By these methods the physiologic response to altitude hypoxia, carbon monoxide, hypercapnia, acceleration, exercise, and the interaction of altitude hypoxia and carbon monoxide were described. The effects of some of these stresses on the heart and coronary circulation are discussed.
This book is a summary of interdisciplinary research (physiology, space medicine, engineering, computer science, mathematics) that spans two decades (1972-1992). The research was an attempt to use systems analysis, mathematical modeling, computer simulations, and database systems to integrate the biomedical spaceflight data that was being collected during this period. The goal of the effort was to achieve a better understanding of the human physiological response to short-term and long-term space travel. The activity was primarily devoted to analyzing the biomedical results of Skylab (1973-74), a series of three space missions which is still ranked as the most comprehensive of all long-term biomedical space studies to date. This work was begun as a coordinated effort between the National Aeronautics and Space Administration (Johnson Space Center) and the General Electric Company’s Space Division (Houston, TX). It was the intent that this multidisciplined, integrative approach could reveal aspects of the then-new science of microgravity adaptation that were not obvious by adhering to the traditional methodology of examining each organ system in isolation. Some joint work with the Russians, including the Apollo-Soyez test project and a joint bedrest study was also supported during this period. In the 1980’s the systems analysis group’s effort was redirected to support the science management of human and animal experiments on the Space Shuttle. A few examples from this era are also included in the book. Parts of this work have been published elsewhere, presented at technical meetings, and documented in reports with limited distribution. These publications will be referenced throughout the text and the interested reader is advised to use these as resource material where additional details are desired. The intent of this book is not to reproduce these documents but rather to present a coherent view of the integrative analysis under one cover. This volume contains the first detailed publication (other than in internal reports) of an extensive metabolic balance analysis of Skylab data, the development and validation of the “Whole-Body Algorithm,” and simulation studies of diverse hypogravic environments. An analysis of cardiovascular deconditioning and a description of the calcium regulatory model are also new. A long period has passed between the completion of the main body of work represented in this book and its publication in this form. It was inevitable that new research efforts would lead to developments related to the spaceflight problems addressed and thereby make some of our biomedical conclusions obsolete. Although in some cases reference to more recent work have been included, for the most part this book should be considered an historical summary demonstrating the approach and utility of systems analysis and computer modeling in the NASA Life Sciences program at the time the studies were conducted.
Computer program for processing data collected on physiological effects of bed rest - human engineering
The systems analysis approach to physiological research uses mathematical models and computer simulation. Major areas of concern during prolonged space flight discussed include fluid and blood volume regulation; cardiovascular response during shuttle reentry; countermeasures for orthostatic intolerance; and calcium regulation and bone atrophy. Potential contributions of physiologic math models to future flight experiments are examined.
Dr. Radhakrishnan, a researcher at the NASA Glenn Research Center, in collaboration with biomedical researchers at the Case Western Reserve University School of Medicine and Rainbow Babies and Children's Hospital, is developing computational models of human physiology that quantitate metabolism and its regulation, in both healthy and pathological states. These models can help predict the effects of stresses or interventions, such as drug therapies, and contribute to the development of customized medicine. Customized medical treatment protocols can give more comprehensive evaluations and lead to more specific and effective treatments for patients, reducing treatment time and cost. Commercial applications of this research may help the pharmaceutical industry identify therapeutic needs and predict drug-drug interactions. Researchers will be able to study human metabolic reactions to particular treatments while in different environments as well as establish more definite blood metabolite concentration ranges in normal and pathological states. These computational models may help NASA provide the background for developing strategies to monitor and safeguard the health of astronauts and civilians in space stations and colonies. They may also help to develop countermeasures that ameliorate the effects of both acute and chronic space exposure.
There are a variety of difficulties in evaluating clinical cardiac mapping systems, most notably the inability to record the transmembrane potential throughout the entire heart during patient procedures which prevents the comparison to a relevant “gold standard”. Cardiac mapping systems are comprised of hardware and software elements including sophisticated mathematical algorithms, both of which continue to undergo rapid innovation. The purpose of this study is to develop a computational modeling framework to evaluate the performance of cardiac mapping systems. The framework enables rigorous evaluation of a mapping system’s ability to localize and characterize (i.e., focal or reentrant) arrhythmogenic sources in the heart. The main component of our tool is a library of computer simulations of various dynamic patterns throughout the entire heart in which the type and location of the arrhythmogenic sources are known. Our framework allows for performance evaluation for various electrode configurations, heart geometries, arrhythmias, and electrogram noise levels and involves blind comparison of mapping systems against a “silver standard” comprised of computer simulations in which the precise transmembrane potential patterns throughout the heart are known. A feasibility study was performed using simulations of patterns in the human left atria and three hypothetical virtual catheter electrode arrays. Activation times (AcT) and patterns (AcP) were computed for three virtual electrode arrays: two basket arrays with good and poor contact and one high-resolution grid with uniform spacing. The average root mean squared difference of AcTs of electrograms and those of the nearest endocardial action potential was less than 1 ms and therefore appears to be a poor performance metric. In an effort to standardize performance evaluation of mapping systems a novel performance metric is introduced based on the number of AcPs identified correctly and those considered spurious as well as misclassifications of arrhythmia type; spatial and temporal localization accuracy of correctly identified patterns was also quantified. This approach provides a rigorous quantitative analysis of cardiac mapping system performance. Proof of concept of this computational evaluation framework suggests that it could help safeguard that mapping systems perform as expected as well as provide estimates of system accuracy.
Fluid electrolyte metabolism and renal endocrine control as it pertains to adaptation to weightlessness were studied. The mathematical models that have been particularly useful are discussed. However, the focus of the report is on the physiological meaning of the computer studies. A discussion of the major ground based analogs of weightlessness are included; for example, head down tilt, water immersion, and bed rest, and a comparison of findings. Several important zero g phenomena are described, including acute fluid volume regulation, blood volume regulation, circulatory changes, longer term fluid electrolyte adaptations, hormonal regulation, and body composition changes. Hypotheses are offered to explain the major findings in each area and these are integrated into a larger hypothesis of space flight adaptation. A conceptual foundation for fluid electrolyte metabolism, blood volume regulation, and cardiovascular regulation is reported.
Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. Computational Fluid Dynamic (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test is to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III space suit across a range of workload and flow rates. As a secondary objective, results will be compared to the predicted CO2 concentrations and used to refine existing CFD models. These CFD models will then be used to help design an inlet vent configuration for the Z-2 space suit, which maximizes oronasal CO2 washout. This test has not been completed, but is planned for January 2014. The results of this test will be incorporated into this paper. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES). Three subjects will be tested in the Mark-III space suit with each subject performing two test sessions to allow for comparison between tests. Six different helmet inlet vent configurations will be evaluated during each test session. Suit pressure will be maintained at 4.3 psid. Subjects will wear the suit while walking on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute (ACFM) will be tested at each workload. Subjects will wear an oronasal mask with an open port in front of the mouth and will be allowed to breathe freely. Oronasal ppCO2 will be monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate will be calculated from the total oxygen consumption and CO2 production measured by additional gas analyzers at the air outlet from the suit. Real-time metabolic rate measurements will be used to adjust the treadmill workload to meet target metabolic rates. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future inlet vent design and ground testing in the Mark-III.
Requirements for using a space suit during ground testing include providing adequate carbon dioxide (CO2) washout for the suited subject. Acute CO2 exposure can lead to symptoms including headache, dyspnea, lethargy and eventually unconsciousness or even death. Symptoms depend on several factors including inspired partial pressure of CO2 (ppCO2), duration of exposure, metabolic rate of the subject and physiological differences between subjects. Computational Fluid Dynamic (CFD) analysis has predicted that the configuration of the suit inlet vent has a significant effect on oronasal CO2 concentrations. The main objective of this test was to characterize inspired oronasal ppCO2 for a variety of inlet vent configurations in the Mark-III suit across a range of workload and flow rates. Data and trends observed during testing along with refined CFD models will be used to help design an inlet vent configuration for the Z-2 space suit. The testing methodology used in this test builds upon past CO2 washout testing performed on the Z-1 suit, Rear Entry I-Suit (REI) and the Enhanced Mobility Advanced Crew Escape Suit (EM-ACES). Three subjects performed two test sessions each in the Mark-III suit to allow for comparison between tests. Six different helmet inlet vent configurations were evaluated during each test session. Suit pressure was maintained at 4.3 psid. Suited test subjects walked on a treadmill to generate metabolic workloads of approximately 2000 and 3000 BTU/hr. Supply airflow rates of 6 and 4 actual cubic feet per minute (ACFM) were tested at each workload. Subjects wore an oronasal mask with an open port in front of the mouth and were allowed to breathe freely. Oronasal ppCO2 was monitored real-time via gas analyzers with sampling tubes connected to the oronasal mask. Metabolic rate was calculated from the total oxygen consumption and CO2 production measured by additional gas analyzers at the air outlet from the suit. Realtime metabolic rate measurements were used to adjust the treadmill workload to meet target metabolic rates. This paper provides detailed descriptions of the test hardware, methodology and results, as well as implications for future inlet vent designs and ground testing.