Reaction-diffusion informed approach to determine myocardial ischemia using stochastic in-silico ECGs and CNNs.

Every year, nine million people die globally from ischemic heart disease (IHD). There are many methods of early detection of IHD which can help prevent death, but few are able to determine the configuration and severity of this disease. Our study aims to determine the severity and configuration of ischemic zones by implementing the reaction-diffusion analysis of cardiac excitation in a model of the left ventricle of the human heart. Initially, this model is applied to compute twenty thousand in-silico ECG signals with stochastic distribution of ischemic parameters. Furthermore, generated data is effectively (r2=0.85) implemented for training a one-dimensional convolutional neural network to determine the severity and configuration of ischemia using only two lead surface ECG. Our results readily demonstrate that using a minimally configured portable ECG system can be instrumental for monitoring IHD and allowing early tracking of acute ischemic events.

Analytical Approach to Screen Semiconducting MOFs Using Bloch Mode Analysis and Spectroscopic Measurements.

A rapid and simple analytical approach is developed to screen the semiconducting properties of metal organic frameworks (MOFs) by modeling the band structure and predicting the density of state of isoreticular MOFs (IRMOFs). One can consider the periodic arrangement of metal nodes linked by organic subunits as a 1D periodic array crystal model, which can be aligned with any unit-cell axis included in the IRMOF's primitive cubic lattice. In such a structure, each valence electron of a metal atom feels the potential field of the entire periodic array. We allocate the 1D periodic array in a crystal unit cell to three IRMOFs-n (n = 1, 8, and 10) of the Zn4O(L)3 IRMOF series and apply the model to their crystal lattices with unit-cell constants a = 25.66, 30.09, and 34.28 Å, respectively. By solving Schrödinger's equation with a Kronig-Penney periodic potential and fitting the computed energy spectra to IRMOFs' experimental spectroscopic data, we model electronic band structures and obtain densities of state. The band diagram of each IRMOF reveals the nature of its electronic structures and density of state, allowing one to identify its n- or p-type semiconducting behavior. This novel analytical approach serves as a predictive and rapid screening tool to search the MOF database to identify potential semiconducting MOFs.

Reaction-diffusion memory unit: Modeling of sensitization, habituation and dishabituation in the brain.

We propose a novel approach to investigate the effects of sensitization, habituation and dishabituation in the brain using the analysis of the reaction-diffusion memory unit (RDMU). This unit consists of Morris-Lecar-type sensory, motor, interneuron and two input excitable cables, linked by four synapses with adjustable strength defined by Hebbian rules. Stimulation of the sensory neuron through the first input cable causes sensitization by activating two excitatory synapses, C1 and C2, connected to the interneuron and motor neuron, respectively. In turn, the stimulation of the interneuron causes habituation through the activation of inhibitory synapse C3. Likewise, dishabituation is caused through the activation of another inhibitory synapse C4. We have determined sensitization-habituation (BSH) and habituation-dishabituation (BHDH) boundaries as functions between synaptic strengths C2 and C3 at various strengths of C1 and C4. When BSH and BHDH curves shift towards larger values of C2, the RDMU can be easily inhibited. On the contrary, the RDMU can be easily sensitized or dishabituated if BSH and BHDH curves shift towards smaller values of C2. Our numerical simulations readily demonstrate that higher values of the Morris-Lecar relaxation parameter, greater leakage and potassium conductances, reduced length of the interneuron, and higher values of C1 all result in easier habituation of the RDMU. In contrast, we found that at higher values of C4 the RDMU becomes significantly more prone to dishabituation. Based on these simulations one can quantify BSH and BHDH curve shifts and relate them to particular neural outcomes.

Cardiac and gait rhythms in healthy younger and older adults during treadmill walking tasks.

BACKGROUND: Aging and pathology result in changes in the dynamics of several physiological subsystems. Often, these changes are concurrent, altering the dynamics between subsystems. Cardiac and gait rhythms are one example in which patterns change during physical activity. AIMS: The purpose of this research is to simultaneously monitor changes in cardiac and gait rhythms when participants complete various treadmill walking tasks-normal speed, fast speed, and while synchronizing steps with a blinking metronome. METHODS: The cardiac and gait rhythms of younger and older healthy adults were examined in this study during treadmill walking tasks. Pre-test and post-test walking at a preferred walking speed were compared to fast walking and walking with a gait synchronization test. Cardiac and gait rhythms were observed to calculate the mean, standard deviation, coefficient of variation, detrended fluctuation analysis scaling exponent alpha (DFA α), and sample entropy from each 15-min trial. Separate MANOVAs were used to examine the two experimental conditions for cardiac and gait rhythm variability. RESULTS: During the gait synchronization experiment, main effects for phase were exhibited for all gait variables, but none were shown during the fast walking task. Meanwhile, the cardiac rhythms demonstrated decreased mean and increased DFA α only during the synchronization condition. DISCUSSION: Participants, regardless of age, exhibited similar patterns of change in their cardiac and locomotor rhythms during the treadmill walking tasks. Cardiac rhythms were only altered during the gait synchronization task, suggesting it may be possible to simultaneously influence the variability and structure of cardiac and gait rhythms.

Diesel Exhaust Worsens Cardiac Conduction Instability in Dobutamine-Challenged Wistar-Kyoto and Spontaneously Hypertensive Rats.

Short-term exposure to air pollution, particularly from vehicular sources, increases the risk of acute clinical cardiovascular events. However, cardiotoxicity is not always clearly discernible under ambient conditions; therefore, more subtle measures of cardiac dysfunction are necessary to elucidate the latent effects of exposure. Determine the effect of whole diesel exhaust (DE) exposure on reserve of refractoriness (RoR), an intrinsic electrophysiological measure of the heart's minimum level of refractoriness relative to development of electrical conduction instability, in rats undergoing exercise-like stress. Wistar-Kyoto (WKY) and spontaneously hypertensive (SH) rats implanted with radiotelemeters to continuously collect electrocardiogram (ECG) and heart rate were exposed to 150 µg/m3 of DE and challenged with dobutamine 24 h later to mimic exercise-induced increases of the heart rate. The Chernyak-Starobin-Cohen (CSC) model was then applied to the ECG-derived QT and RR intervals collected during progressive increases in heart rate to calculate RoR for each rat. Filtered air-exposed WKY and SH rats did not have any decrease in RoR, which indicates increased risk of cardiac conduction instability; however, DE caused a significant decrease in both strains. Yet, the decrease in RoR in SH rats was eight times steeper when compared to WKY rats indicating greater cardiac conduction instability in the hypertensive strain. These data indicate that after exposure to DE, risk of cardiac instability increases during increasing stress, particularly in the presence of underlying cardiovascular disease. Furthermore, the CSC model, which was previously shown to reveal cardiac risk in humans, can be applied to rodent toxicology studies.

The relationship between nernst equilibrium variability and the multifractality of interspike intervals in the hippocampus.

Spatiotemporal patterns of action potentials are considered to be closely related to information processing in the brain. Auto-generating neurons contributing to these processing tasks are known to cause multifractal behavior in the inter-spike intervals of the output action potentials. In this paper we define a novel relationship between this multifractality and the adaptive Nernst equilibrium in hippocampal neurons. Using this relationship we are able to differentiate between various drugs at varying dosages. Conventional methods limit their ability to account for cellular charge depletion by not including these adaptive Nernst equilibria. Our results provide a new theoretical approach for measuring the effects which drugs have on single-cell dynamics.

Bursting regimes in a reaction-diffusion system with action potential-dependent equilibrium.

The equilibrium Nernst potential plays a critical role in neural cell dynamics. A common approximation used in studying electrical dynamics of excitable cells is that the ionic concentrations inside and outside the cell membranes act as charge reservoirs and remain effectively constant during excitation events. Research into brain electrical activity suggests that relaxing this assumption may provide a better understanding of normal and pathophysiological functioning of the brain. In this paper we explore time-dependent ionic concentrations by allowing the ion-specific Nernst potentials to vary with developing transmembrane potential. As a specific implementation, we incorporate the potential-dependent Nernst shift into a one-dimensional Morris-Lecar reaction-diffusion model. Our main findings result from a region in parameter space where self-sustaining oscillations occur without external forcing. Studying the system close to the bifurcation boundary, we explore the vulnerability of the system with respect to external stimulations which disrupt these oscillations and send the system to a stable equilibrium. We also present results for an extended, one-dimensional cable of excitable tissue tuned to this parameter regime and stimulated, giving rise to complex spatiotemporal pattern formation. Potential applications to the emergence of neuronal bursting in similar two-variable systems and to pathophysiological seizure-like activity are discussed.

Ordering and stability in lipid droplets with applications to low-density lipoproteins.

In this article, we present a framework for investigating the order-disorder transition in lipid droplets using the standard Ising model. While a single lipid droplet is itself a complex system whose constituent cholesteryl esters each possesses many degrees of freedom, we present justification for using this effective approach to isolate the underlying physics. It is argued that the behavior of the esters confined within lipid droplets is significantly different from that of a bulk system of similar esters, which is adequately described by continuum mean-field theory in the thermodynamic limit. When the droplet's shell is modeled as an elastic membrane, a simple picture emerges for a transition between two ordered phases within the core which is tuned by the strength of interactions between the esters. Triglyceride concentration is proposed as a variable which strongly influences the strength of interactions between cholesteryl esters within droplets. The possible relevance of this mechanism to the well known atherogenic nature of small low-density lipoprotein particles is discussed in detail.

Modeling order-disorder transition in Low-Density Lipoprotein.

Low Density Lipoproteins (LDL) undergo a reversible order-disorder thermal transition close to biological temperature due to cooperative melting of the cholesteryl esters (CE) in the core of the LDL particle. We have noticed that chain-chain interactions between CE molecules are responsible for the stability of the ordered smectic phase; thus, we formulated a simple "coarse-grained" two-state model to describe the melting process. In this model only nearest neighbor interactions are allowed. On the basis of these assumptions we performed Metropolis Monte Carlo (MC) simulation in order to obtain the heat capacity curve. The resulting profile reveals well-known features of the systems with a finite size.

Entrainment of marginally stable excitation waves by spatially extended sub-threshold periodic forcing.

We introduce a novel approach of stabilizing the dynamics of excitation waves by spatially extended sub-threshold periodic forcing. Entrainment of unstable primary waves has been studied numerically for different amplitudes and frequencies of additional sub-threshold stimuli. We determined entrainment regimes under which excitation blocks were transformed into consistent 1:1 responses. These responses were spatially homogeneous and synchronized in the entire excitable medium. Compared to primary pulses, pulses entrained by secondary stimulations were stable at considerably shorter periods which decreased at higher amplitudes and greater number of secondary stimuli. Our results suggest a practical methodology for stabilization of excitation in reaction-diffusion media such as nerve tissue with regions of reduced excitability.

Critical scale of propagation influences dynamics of waves in a model of excitable medium.

BACKGROUND: Duration and speed of propagation of the pulse are essential factors for stability of excitation waves. We explore the propagation of excitation waves resulting from periodic stimulation of an excitable cable to determine the minimal stable pulse duration in a rate-dependent modification of a Chernyak-Starobin-Cohen reaction-diffusion model. RESULTS: Various pacing rate dependent features of wave propagation were studied computationally and analytically. We demonstrated that the complexity of responses to stimulation and evolution of these responses from stable propagation to propagation block and alternans was determined by the proximity between the minimal level of the recovery variable and the critical excitation threshold for a stable solitary pulse. CONCLUSION: These results suggest that critical propagation of excitation waves determines conditions for transition to unstable rhythms in a way similar to unstable cardiac rhythms. Established conditions were suitably accurate regardless of rate dependent features and the magnitude of the slopes of restitution curves.

Identifying coronary artery flow reduction and ischemia using quasistationary QT/RR-interval hysteresis measurements.

Because myocardial ischemia induces QT/RR hysteresis, a correlation was hypothesized to exist between the extent of myocardial flow reduction and the magnitude of QT/RR hysteresis. Graded reductions in regional myocardial perfusion in the distribution of the left anterior descending coronary artery in open-chest pigs were used to model 1-vessel coronary artery disease. At each reduced level of left anterior descending coronary artery flow, the heart was electrically paced at progressively higher and lower rates between an initial control and maximum heart rate values. Digitized surface and intramyocardial electrograms and aortic pressure were used to measure QT/RR hysteresis, QT-interval adaptation, ST- and TQ-segment depression, and cardiac contractility. Intraexperimental blood samples were analyzed to assess inflammatory response (interleukin 6), oxidative stress (protein carbonyls), and myocyte injury (creatine kinase). Higher values of QT/RR hysteresis correlated with the severity of ischemia as assessed by TQ-segment depression in intramyocardial electrograms (P = .002). Lower flow rates were strongly associated with higher values of QT/RR hysteresis and slower QT-interval adaptation (P or= .02). Significant increases in systemic measures of inflammation, oxidative stress, and cardiac myocyte injury and major decrease in cardiac contractility preceded the most severe stages of flow reduction (30% and 20% of normal flow). We determined QT/RR hysteresis index thresholds corresponding to these mechanical and immunochemical responses. QT/RR hysteresis is a strong indicator of reduced myocardial perfusion and may provide information for noninvasive assessment of mechanical and immunochemical changes associated with early stages of coronary artery disease.

Exercise-induced QT/R-R-interval hysteresis as a predictor of myocardial ischemia.

OBJECTIVES: Exercise-induced QT/RR hysteresis exists when, for a given R-R interval, the QT interval duration is shorter during recovery after exercise than during exercise. We sought to assess the association between QT/RR hysteresis and imaging evidence of myocardial ischemia. BACKGROUND: Because ischemia induces cellular disturbances known to decrease membrane action potential duration, we hypothesized a correlation between QT/RR and myocardial ischemia. METHODS: We digitally analyzed 4-second samples of QT duration and R-R-interval duration in 260 patients referred for treadmill exercise stress and rest single photon emission computed tomography myocardial perfusion imaging; a cool-down period was used after exercise. None of the patients were in atrial fibrillation or used digoxin, and none had marked baseline electrocardiographic abnormalities. Stress and rest myocardial perfusion images were analyzed visually and quantitatively to define the extent and severity of stress-induced ischemia. QT/RR hysteresis was calculated using a computerized algorithm. RESULTS: There were 82 patients (32%) who manifested myocardial ischemia by single photon emission computed tomography myocardial perfusion imaging. The likelihood of ischemia increased with increasing QT/RR hysteresis, with prevalence according to quartiles of 20%, 30%, 26%, and 49% (P = .003 for trend). In analyses adjusting for ST-segment changes, exercise capacity, heart rate recovery, and other confounders, QT/RR hysteresis was independently predictive of presence of myocardial ischemia (adjusted odds ratio for 100-point increase of QT/RR hysteresis, 1.61; 95% confidence interval, 1.22-2.12; P = .0008). QT/RR hysteresis was also predictive of severe ischemia. CONCLUSION: Exercise-induced QT/RR hysteresis is a strong and independent predictor of myocardial ischemia and provides additional information beyond that afforded by standard ST-segment measures.