Are physiological oscillations physiological?

Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function. Here, we take a systems approach to argue that oscillations play critical physiological roles, such as enabling systems to avoid desensitization, to avoid chronically high and therefore toxic levels of chemicals, and to become more resistant to noise. Oscillation also enables complex physiological systems to reconcile incompatible conditions such as oxidation and reduction, by cycling between them, and to synchronize the oscillations of many small units into one large effect. In pancreatic ß-cells, glycolytic oscillations synchronize with calcium and mitochondrial oscillations to drive pulsatile insulin release, critical for liver regulation of glucose. In addition, oscillation can keep biological time, essential for embryonic development in promoting cell diversity and pattern formation. The functional importance of oscillatory processes requires a re-thinking of the traditional doctrine of homeostasis, holding that physiological quantities are maintained at constant equilibrium values, a view that has largely failed in the clinic. A more dynamic approach will initiate a paradigm shift in our view of health and disease. A deeper look into the mechanisms that create, sustain and abolish oscillatory processes requires the language of nonlinear dynamics, well beyond the linearization techniques of equilibrium control theory. Nonlinear dynamics enables us to identify oscillatory ('pacemaking') mechanisms at the cellular, tissue and system levels.

A novel geometric method for determining the time constant for oxygen uptake kinetics.

The kinetic response of oxygen uptake (V̇o2) to transitions of exercise intensity is one of the important parameters of aerobic function. The typical kinetic response between two steady states can be reasonably well fitted with a mono-exponential function that has a time constant τV̇o2. However, due to the variability of breath-by-breath measures of V̇o2 determination of τV̇o2 has usually required superimposition of repeated exercise protocols. We developed a novel geometric method of determining τV̇o2 from the analysis of slopes and intercepts of a plot of cumulative oxygen uptake (cumV̇o2) versus time for single exercise protocols. We used mathematical modeling to generate 3,600 series of breath-by-breath V̇o2 measures versus time for various exercise protocols. To test whether our geometric method was robust to the presence of real-life variability, we applied random (Gaussian) variation to both the interval between breaths and to the measured values of V̇o2. Our method derived values for τV̇o2 that were accurate to within 1.5-3.5 s for both on- and off-transits and for models that represented healthy normal subjects as well as persons with cardiovascular disease. The coefficient of variation for multiple iterations of the method was <10% as long as the signal-to-noise ratio was >20:1. We present a novel geometric method for deriving the τV̇o2 of oxygen uptake kinetics. This method uses analysis of the slopes and intercepts of a plot of cumulative V̇o2 versus time and does not require multiple repetitions of the exercise protocol but still gives accurate estimates of τV̇o2.NEW & NOTEWORTHY We present a novel geometric method for deriving the τV̇o2 of oxygen uptake kinetics. This method uses analysis of the slopes and intercepts of a plot of cumulative V̇o2 versus time and does not require multiple repetitions of the exercise protocol but still gives accurate estimates of τV̇o2.

A common pathway to cancer: Oncogenic mutations abolish p53 oscillations.

The tumor suppressor p53 oscillates in response to DNA double-strand breaks, a behavior that has been suggested to be essential to its anti-cancer function. Nearly all human cancers have genetic alterations in the p53 pathway; a number of these alterations have been shown to be oncogenic by experiment. These alterations include somatic mutations and copy number variations as well as germline polymorphisms. Intriguingly, they exhibit a mixed pattern of interactions in tumors, such as co-occurrence, mutual exclusivity, and paradoxically, mutual antagonism. Using a differential equation model of p53-Mdm2 dynamics, we employ Hopf bifurcation analysis to show that these alterations have a common mode of action, to abolish the oscillatory competence of p53, thereby, we suggest, impairing its tumor suppressive function. In this analysis, diverse genetic alterations, widely associated with human cancers clinically, have a unified mechanistic explanation of their role in oncogenesis.

R-on-T and the initiation of reentry revisited: Integrating old and new concepts.

Initiation of reentry requires 2 factors: (1) a triggering event, most commonly focal excitations such as premature ventricular complexes (PVCs); and (2) a vulnerable substrate with regional dispersion of refractoriness and/or excitability, such as occurs during the T wave of the electrocardiogram when some areas of the ventricle have repolarized and recovered excitability but others have not. When the R wave of a PVC coincides in time with the T wave of the previous beat, this timing can lead to unidirectional block and initiation of reentry, known as the R-on-T phenomenon. Classically, the PVC triggering reentry has been viewed as arising focally from 1 region and propagating into another region whose recovery is delayed, resulting in unidirectional conduction block and reentry initiation. However, more recent evidence indicates that PVCs also can arise from the T wave itself. In the latter case, the PVC initiating reentry is not a separate event from the T wave but rather is causally generated from the repolarization gradient that manifests as the T wave. We call the former an "R-to-T" mechanism and the latter an "R-from-T" mechanism, which are initiation mechanisms distinct from each other. Both are important components of the R-on-T phenomenon and need to be taken into account when designing antiarrhythmic strategies. Strategies targeting suppression of triggers alone or vulnerable substrate alone may be appropriate in some instances but not in others. Preventing R-from-T arrhythmias requires suppressing the underlying dynamic tissue instabilities responsible for producing both triggers and substrate vulnerability simultaneously. The same principles are likely to apply to supraventricular arrhythmias.

Teaching Dynamics to Biology Undergraduates: the UCLA Experience.

There is a growing realization that traditional "Calculus for Life Sciences" courses do not show their applicability to the Life Sciences and discourage student interest. There have been calls from the AAAS, the Howard Hughes Medical Institute, the NSF, and the American Association of Medical Colleges for a new kind of math course for biology students, that would focus on dynamics and modeling, to understand positive and negative feedback relations, in the context of important biological applications, not incidental "examples." We designed a new course, LS 30, based on the idea of modeling biological relations as dynamical systems, and then visualizing the dynamical system as a vector field, assigning "change vectors" to every point in a state space. The resulting course, now being given to approximately 1400 students/year at UCLA, has greatly improved student perceptions toward math in biology, reduced minority performance gaps, and increased students' subsequent grades in physics and chemistry courses. This new course can be customized easily for a broad range of institutions. All course materials, including lecture plans, labs, homeworks and exams, are available from the authors; supporting videos are posted online.

Circadian and ultradian rhythms in normal mice and in a mouse model of Huntington's disease.

Circadian rhythms in core body temperature (CBT) have been widely studied, but fewer studies have explored higher-frequency (ultradian) rhythms in detail. We analyzed CBT recordings from young and middle-aged wild-type mice as well as from the Q175 model of Huntington's disease (HD), at sufficient temporal resolution to address the question of ultradian rhythms. We used model selection methods to show that the overall circadian pattern was better fit by a square wave than a sine wave. Then, using Fourier analysis of the CBT rhythms, we identified the spectral signature of an 8-hour oscillation that occurs in the night but not the day, an observation that can be confirmed by direct inspection of the rhythms. This diurnal amplitude modulation of the 8-hour rhythm was lost with aging as well as in the HD model. Thus, the impact of aging and disease is seen here in the loss of the ability to separate rhythms into a daytime phase and a nighttime phase. These findings raise the possibility that ultradian rhythms in CBT may be a useful biomarker for the pathology within the central nervous system.

Reimagining the Introductory Math Curriculum for Life Sciences Students.

Calculus is typically one of the first college courses encountered by science, technology, engineering, and mathematics (STEM) majors. Calculus often presents major challenges affecting STEM student persistence, particularly for students from groups historically underrepresented in STEM. For life sciences majors, calculus courses may not offer content that is relevant to biological systems or connect with students' interests in biology. We developed a transformative approach to teaching college-level math, using a dynamical systems perspective that focuses first on demonstrating why students need math to understand living systems, followed by providing quantitative and computational skills, including concepts from calculus, that students need to build and analyze mathematical models representing these systems. We found that students who complete these new math courses perform better in subsequent science courses than their counterparts who take traditional calculus courses. We also provide evidence that the new math curriculum positively impacts students' academic performance, with data that show narrowing of the achievement gap, based on students' math grades, between student subgroups in the new math courses. Moreover, our results indicate that students' interest in the concepts and skills critical to the quantitative preparation of 21st-century life sciences majors increases after completing the new contextualized math curriculum.

Predicting wet age-related macular degeneration (AMD) using DARC (detecting apoptosing retinal cells) AI (artificial intelligence) technology.

OBJECTIVES: To assess a recently described CNN (convolutional neural network) DARC (Detection of Apoptosing Retinal Cells) algorithm in predicting new Subretinal Fluid (SRF) formation in Age-related-Macular-Degeneration (AMD). METHODS: Anonymized DARC, baseline and serial OCT images (n = 427) from 29 AMD eyes of Phase 2 clinical trial (ISRCTN10751859) were assessed with CNN algorithms, enabling the location of each DARC spot on corresponding OCT slices (n = 20,629). Assessment of DARC in a rabbit model of angiogenesis was performed in parallel. RESULTS: A CNN DARC count >5 at baseline was significantly (p = 0.0156) related to development of new SRF throughout 36 months. Prediction rate of eyes using unique DARC spots overlying new SRF had positive predictive values, sensitivities and specificities >70%, with DARC count significantly (p < 0.005) related to the magnitude of SRF accumulation at all time points. DARC identified earliest stages of angiogenesis in-vivo. CONCLUSIONS: DARC was able to predict new wet-AMD activity. Using only an OCT-CNN definition of new SRF, we demonstrate that DARC can identify early endothelial neovascular activity, as confirmed by rabbit studies. Although larger validation studies are required, this shows the potential of DARC as a biomarker of wet AMD, and potentially saving vision-loss.

Redundancy and multifunctionality among spinal locomotor networks.

c-Fos is used to identify system-wide neural activation with cellular resolution in vivo. However, c-Fos can only capture neural activation of one event. Targeted recombination in active populations (TRAP) allows the capture of two different c-Fos activation patterns in the same animal. So far, TRAP has only been used to examine brain circuits. This study uses TRAP to investigate spinal circuit activation during resting and stepping, giving novel insights of network activation during these events. The level of colabeled (c-Fos+ and TRAP+) neurons observed after performing two bouts of stepping suggests that there is a probabilistic-like phenomenon that can recruit many combinations of neural populations (synapses) when repetitively generating many step cycles. Between two 30-min bouts of stepping, each consisting of thousands of steps, only ∼20% of the neurons activated from the first bout of stepping were also activated by the second bout. We also show colabeling of interneurons that have been active during stepping and resting. The use of the FosTRAP methodology in the spinal cord provides a new tool to compare the engagement of different populations of spinal interneurons in vivo under different motor tasks or under different conditions.NEW & NOTEWORTHY The results are consistent with there being an extensive amount of redundancy among spinal locomotor circuits. Using the newly developed FosTRAP mouse model, only ∼20% of neurons that were active (labeled by Fos-linked tdTomato expression) during a first bout of 30-min stepping were also labeled for c-Fos during a second bout of stepping. This finding suggests variability of neural networks that enables selection of many combinations of neurons (synapses) when generating each step cycle.

Geochemical studies on rock varnish and petroglyphs in the Owens and Rose Valleys, California.

We investigated rock varnish, a thin, manganese- and iron-rich, dark surface crust, on basaltic lava flows and petroglyphs in the Owens and Rose Valleys (California) by portable X-ray fluorescence (pXRF) and femtosecond laser-ablation inductively-coupled-plasma mass spectrometry (fs-LA-ICPMS). The major element composition of the varnish was consistent with a mixture of Mn-Fe oxyhydroxides and clay minerals. As expected, it contained elevated concentrations of elements that are typically enriched in rock varnish, e.g., Mn, Pb, Ba, Ce, and Co, but also showed unusually high enrichments in U, Cu, and Th. The rare earth and yttrium (REY) enrichment pattern revealed a very strong positive cerium (Ce) anomaly and distinct negative europium (Eu) and Y anomalies. The light rare earth elements (REE) were much more strongly enriched than the heavy REY. These enrichment patterns are consistent with a formation mechanism by leaching of Mn and trace elements from aeolian dust, reprecipitation of Mn and Fe as oxyhydroxides, and scavenging of trace elements by these oxyhydroxides. We inferred accumulation rates of Mn and Fe in the varnish from their areal densities measured by pXRF and the known ages of some of the lava flow surfaces. The areal densities of Mn and Fe, as well as their accumulation rates, were comparable to our previous results from the desert of Saudi Arabia. There was a moderate dependence of the Mn areal density on the inclination of the rock surfaces, but no relationship to its cardinal orientation. We attempted to use the degree of varnish regrowth on the rock art surfaces as an estimate of their age. While an absolute dating of the petroglyphs was not possible because of the lack of suitable calibration surfaces and a considerable amount of variability, the measured degree of varnish regrowth on the various petroglyphs was consistent with chronologies based on archeological and other archaeometric techniques. In particular, our results suggest that rock art creation in the study area continued over an extended period of time, possibly starting around the Pleistocene/Holocene transition and extending into the last few centuries.

Shaping Waves of Bone Morphogenetic Protein Inhibition During Vascular Growth.

RATIONALE: The BMPs (bone morphogenetic proteins) are essential morphogens in angiogenesis and vascular development. Disruption of BMP signaling can trigger cardiovascular diseases, such as arteriovenous malformations. OBJECTIVE: A computational model predicted that BMP4 and BMP9 and their inhibitors MGP (matrix gamma-carboxyglutamic acid [Gla] protein) and CV2 (crossveinless-2) would form a regulatory system consisting of negative feedback loops with time delays and that BMP9 would trigger oscillatory expression of the 2 inhibitors. The goal was to investigate this regulatory system in endothelial differentiation and vascular growth. METHODS AND RESULTS: Oscillations in the expression of MGP and CV2 were detected in endothelial cells in vitro, using quantitative real-time polymerase chain reaction and immunoblotting. These organized temporally downstream BMP-related activities, including expression of stalk-cell markers and cell proliferation, consistent with an integral role of BMP9 in vessel maturation. In vivo, the inhibitors were located in distinct zones in relation to the front of the expanding retinal network, as determined by immunofluorescence. Time-dependent changes of the CV2 location in the retina and the existence of an endothelial population with signs of oscillatory MGP expression in developing vasculature supported the in vitro findings. Loss of MGP or its BMP4-binding capacity disrupted the retinal vasculature, resulting in poorly formed networks, especially in the venous drainage areas, and arteriovenous malformations as determined by increased cell coverage and functional testing. CONCLUSIONS: Our results suggest a previously unknown mechanism of temporal orchestration of BMP4 and BMP9 activities that utilize the tandem actions of the extracellular antagonists MGP and CV2. Disruption of this mechanism may contribute to vascular malformations and disease.

Model of Left Ventricular Contraction: Validation Criteria and Boundary Conditions.

Computational models of cardiac contraction can provide critical insight into cardiac function and dysfunction. A necessary step before employing these computational models is their validation. Here we propose a series of validation criteria based on left ventricular (LV) global (ejection fraction and twist) and local (strains in a cylindrical coordinate system, aggregate cardiomyocyte shortening, and low myocardial compressibility) MRI measures to characterize LV motion and deformation during contraction. These validation criteria are used to evaluate an LV finite element model built from subject-specific anatomy and aggregate cardiomyocyte orientations reconstructed from diffusion tensor MRI. We emphasize the key role of the simulation boundary conditions in approaching the physiologically correct motion and strains during contraction. We conclude by comparing the global and local validation criteria measures obtained using two different boundary conditions: the first constraining the LV base and the second taking into account the presence of the pericardium, which leads to greatly improved motion and deformation.

Microstructural Infarct Border Zone Remodeling in the Post-infarct Swine Heart Measured by Diffusion Tensor MRI.

Introduction: Computational models of the heart increasingly require detailed microstructural information to capture the impact of tissue remodeling on cardiac electromechanics in, for example, hearts with myocardial infarctions. Myocardial infarctions are surrounded by the infarct border zone (BZ), which is a site of electromechanical property transition. Magnetic resonance imaging (MRI) is an emerging method for characterizing microstructural remodeling and focal myocardial infarcts and the BZ can be identified with late gadolinium enhanced (LGE) MRI. Microstructural remodeling within the BZ, however, remains poorly characterized by MRI due, in part, to the fact that LGE and DT-MRI are not always available for the same heart. Diffusion tensor MRI (DT-MRI) can evaluate microstructural remodeling by quantifying the DT apparent diffusion coefficient (ADC, increased with decreased cellularity), fractional anisotropy (FA, decreased with increased fibrosis), and tissue mode (decreased with increased fiber disarray). The purpose of this work was to use LGE MRI in post-infarct porcine hearts (N = 7) to segment remote, BZ, and infarcted myocardium, thereby providing a basis to quantify microstructural remodeling in the BZ and infarcted regions using co-registered DT-MRI. Methods: Chronic porcine infarcts were created by balloon occlusion of the LCx. 6-8 weeks post-infarction, MRI contrast was administered, and the heart was potassium arrested, excised, and imaged with LGE MRI (0.33 × 0.33 × 0.33 mm) and co-registered DT-MRI (1 × 1 × 3 mm). Myocardium was segmented as remote, BZ, or infarct by LGE signal intensity thresholds. DT invariants were used to evaluate microstructural remodeling by quantifying ADC, FA, and tissue mode. Results: The BZ significantly remodeled compared to both infarct and remote myocardium. BZ demonstrated a significant decrease in cellularity (increased ADC), significant decrease in tissue organization (decreased FA), and a significant increase in fiber disarray (decreased tissue mode) relative to remote myocardium (all p < 0.05). Microstructural remodeling in the infarct was similar, but significantly larger in magnitude (all p < 0.05). Conclusion: DT-MRI can identify regions of significant microstructural remodeling in the BZ that are distinct from both remote and infarcted myocardium.

Memory-Induced Chaos in Cardiac Excitation.

Excitable systems display memory, but how memory affects the excitation dynamics of such systems remains to be elucidated. Here we use computer simulation of cardiac action potential models to demonstrate that memory can cause dynamical instabilities that result in complex excitation dynamics and chaos. We develop an iterated map model that correctly describes these dynamics and show that memory converts a monotonic first return map of action potential duration into a nonmonotonic one, resulting in a period-doubling bifurcation route to chaos.

A Dynamical Threshold for Cardiac Delayed Afterdepolarization-Mediated Triggered Activity.

Ventricular myocytes are excitable cells whose voltage threshold for action potential (AP) excitation is ∼-60 mV at which INa is activated to give rise to a fast upstroke. Therefore, for a short stimulus pulse to elicit an AP, a stronger stimulus is needed if the resting potential lies further away from the INa threshold, such as in hypokalemia. However, for an AP elicited by a long duration stimulus or a diastolic spontaneous calcium release, we observed that the stimulus needed was lower in hypokalemia than in normokalemia in both computer simulations and experiments of rabbit ventricular myocytes. This observation provides insight into why hypokalemia promotes calcium-mediated triggered activity, despite the resting potential lying further away from the INa threshold. To understand the underlying mechanisms, we performed bifurcation analyses and demonstrated that there is a dynamical threshold, resulting from a saddle-node bifurcation mainly determined by IK1 and INCX. This threshold is close to the voltage at which IK1 is maximum, and lower than the INa threshold. After exceeding this dynamical threshold, the membrane voltage will automatically depolarize above the INa threshold due to the large negative slope of the IK1-V curve. This dynamical threshold becomes much lower in hypokalemia, especially with respect to calcium, as predicted by our theory. Because of the saddle-node bifurcation, the system can automatically depolarize even in the absence of INa to voltages higher than the ICa,L threshold, allowing for triggered APs in single myocytes with complete INa block. However, because INa is important for AP propagation in tissue, blocking INa can still suppress premature ventricular excitations in cardiac tissue caused by calcium-mediated triggered activity. This suppression is more effective in normokalemia than in hypokalemia due to the difference in dynamical thresholds.

Electrophysiology of Heart Failure Using a Rabbit Model: From the Failing Myocyte to Ventricular Fibrillation.

Heart failure is a leading cause of death, yet its underlying electrophysiological (EP) mechanisms are not well understood. In this study, we use a multiscale approach to analyze a model of heart failure and connect its results to features of the electrocardiogram (ECG). The heart failure model is derived by modifying a previously validated electrophysiology model for a healthy rabbit heart. Specifically, in accordance with the heart failure literature, we modified the cell EP by changing both membrane currents and calcium handling. At the tissue level, we modeled the increased gap junction lateralization and lower conduction velocity due to downregulation of Connexin 43. At the biventricular level, we reduced the apex-to-base and transmural gradients of action potential duration (APD). The failing cell model was first validated by reproducing the longer action potential, slower and lower calcium transient, and earlier alternans characteristic of heart failure EP. Subsequently, we compared the electrical wave propagation in one dimensional cables of healthy and failing cells. The validated cell model was then used to simulate the EP of heart failure in an anatomically accurate biventricular rabbit model. As pacing cycle length decreases, both the normal and failing heart develop T-wave alternans, but only the failing heart shows QRS alternans (although moderate) at rapid pacing. Moreover, T-wave alternans is significantly more pronounced in the failing heart. At rapid pacing, APD maps show areas of conduction block in the failing heart. Finally, accelerated pacing initiated wave reentry and breakup in the failing heart. Further, the onset of VF was not observed with an upregulation of SERCA, a potential drug therapy, using the same protocol. The changes introduced at the cell and tissue level have increased the failing heart's susceptibility to dynamic instabilities and arrhythmias under rapid pacing. However, the observed increase in arrhythmogenic potential is not due to a steepening of the restitution curve (not present in our model), but rather to a novel blocking mechanism.

Stochastic pacing reveals the propensity to cardiac action potential alternans and uncovers its underlying dynamics.

KEY POINTS: Beat-to-beat alternation (alternans) of the cardiac action potential duration is known to precipitate life-threatening arrhythmias and can be driven by the kinetics of voltage-gated membrane currents or by instabilities in intracellular calcium fluxes. To prevent alternans and associated arrhythmias, suitable markers must be developed to quantify the susceptibility to alternans; previous theoretical studies showed that the eigenvalue of the alternating eigenmode represents an ideal marker of alternans. Using rabbit ventricular myocytes, we show that this eigenvalue can be estimated in practice by pacing these cells at intervals varying stochastically. We also show that stochastic pacing permits the estimation of further markers distinguishing between voltage-driven and calcium-driven alternans. Our study opens the perspective to use stochastic pacing during clinical investigations and in patients with implanted pacing devices to determine the susceptibility to, and the type of alternans, which are both important to guide preventive or therapeutic measures. ABSTRACT: Alternans of the cardiac action potential (AP) duration (APD) is a well-known arrhythmogenic mechanism. APD depends on several preceding diastolic intervals (DIs) and APDs, which complicates the prediction of alternans. Previous theoretical studies pinpointed a marker called λalt that directly quantifies how an alternating perturbation persists over successive APs. When the propensity to alternans increases, λalt decreases from 0 to -1. Our aim was to quantify λalt experimentally using stochastic pacing and to examine whether stochastic pacing allows discriminating between voltage-driven and Ca(2+) -driven alternans. APs were recorded in rabbit ventricular myocytes paced at cycle lengths (CLs) decreasing progressively and incorporating stochastic variations. Fitting APD with a function of two previous APDs and CLs permitted us to estimate λalt along with additional markers characterizing whether the dependence of APD on previous DIs or CLs is strong (typical for voltage-driven alternans) or weak (Ca(2+) -driven alternans). During the recordings, λalt gradually decreased from around 0 towards -1. Intermittent alternans appeared when λalt reached -0.8 and was followed by sustained alternans. The additional markers detected that alternans was Ca(2+) driven in control experiments and voltage driven in the presence of ryanodine. This distinction could be made even before alternans was manifest (specificity/sensitivity >80% for -0.4 > λalt  > -0.5). These observations were confirmed in a mathematical model of a rabbit ventricular myocyte. In conclusion, stochastic pacing allows the practical estimation of λalt to reveal the onset of alternans and distinguishes between voltage-driven and Ca(2+) -driven mechanisms, which is important since these two mechanisms may precipitate arrhythmias in different manners.

Delayed afterdepolarizations generate both triggers and a vulnerable substrate promoting reentry in cardiac tissue.

BACKGROUND: Delayed afterdepolarizations (DADs) have been well characterized as arrhythmia triggers, but their role in generating a tissue substrate vulnerable to reentry is not well understood. OBJECTIVE: The purpose of this study was to test the hypothesis that random DADs can self-organize to generate both an arrhythmia trigger and a vulnerable substrate simultaneously in cardiac tissue as a result of gap junction coupling. METHODS: Computer simulations in 1-dimensional cable and 2-dimensional tissue models were performed. The cellular DAD amplitude was varied by changing the strength of sarcoplasmic reticulum calcium release. Random DAD latency and amplitude in different cells were simulated using gaussian distributions. RESULTS: Depending on the strength of spontaneous sarcoplasmic reticulum calcium release and other conditions, random DADs in cardiac tissue resulted in the following behaviors: (1) triggered activity (TA); (2) a vulnerable tissue substrate causing unidirectional conduction block and reentry by inactivating sodium channels; (3) both triggers and a vulnerable substrate simultaneously by generating TA in regions next to regions with subthreshold DADs susceptible to unidirectional conduction block and reentry. The probability of the latter 2 behaviors was enhanced by reduced sodium channel availability, reduced gap junction coupling, increased tissue heterogeneity, and less synchronous DAD latency. CONCLUSION: DADs can self-organize in tissue to generate arrhythmia triggers, a vulnerable tissue substrate, and both simultaneously. Reduced sodium channel availability and gap junction coupling potentiate this mechanism of arrhythmias, which are relevant to a variety of heart disease conditions.

Targeting the late component of the cardiac L-type Ca2+ current to suppress early afterdepolarizations.

Early afterdepolarizations (EADs) associated with prolongation of the cardiac action potential (AP) can create heterogeneity of repolarization and premature extrasystoles, triggering focal and reentrant arrhythmias. Because the L-type Ca(2+) current (ICa,L) plays a key role in both AP prolongation and EAD formation, L-type Ca(2+) channels (LTCCs) represent a promising therapeutic target to normalize AP duration (APD) and suppress EADs and their arrhythmogenic consequences. We used the dynamic-clamp technique to systematically explore how the biophysical properties of LTCCs could be modified to normalize APD and suppress EADs without impairing excitation-contraction coupling. Isolated rabbit ventricular myocytes were first exposed to H2O2 or moderate hypokalemia to induce EADs, after which their endogenous ICa,L was replaced by a virtual ICa,L with tunable parameters, in dynamic-clamp mode. We probed the sensitivity of EADs to changes in the (a) amplitude of the noninactivating pedestal current; (b) slope of voltage-dependent activation; (c) slope of voltage-dependent inactivation; (d) time constant of voltage-dependent activation; and (e) time constant of voltage-dependent inactivation. We found that reducing the amplitude of the noninactivating pedestal component of ICa,L effectively suppressed both H2O2- and hypokalemia-induced EADs and restored APD. These results, together with our previous work, demonstrate the potential of this hybrid experimental-computational approach to guide drug discovery or gene therapy strategies by identifying and targeting selective properties of LTCC.

Perspective: a dynamics-based classification of ventricular arrhythmias.

Despite key advances in the clinical management of life-threatening ventricular arrhythmias, culminating with the development of implantable cardioverter-defibrillators and catheter ablation techniques, pharmacologic/biologic therapeutics have lagged behind. The fundamental issue is that biological targets are molecular factors. Diseases, however, represent emergent properties at the scale of the organism that result from dynamic interactions between multiple constantly changing molecular factors. For a pharmacologic/biologic therapy to be effective, it must target the dynamic processes that underlie the disease. Here we propose a classification of ventricular arrhythmias that is based on our current understanding of the dynamics occurring at the subcellular, cellular, tissue and organism scales, which cause arrhythmias by simultaneously generating arrhythmia triggers and exacerbating tissue vulnerability. The goal is to create a framework that systematically links these key dynamic factors together with fixed factors (structural and electrophysiological heterogeneity) synergistically promoting electrical dispersion and increased arrhythmia risk to molecular factors that can serve as biological targets. We classify ventricular arrhythmias into three primary dynamic categories related generally to unstable Ca cycling, reduced repolarization, and excess repolarization, respectively. The clinical syndromes, arrhythmia mechanisms, dynamic factors and what is known about their molecular counterparts are discussed. Based on this framework, we propose a computational-experimental strategy for exploring the links between molecular factors, fixed factors and dynamic factors that underlie life-threatening ventricular arrhythmias. The ultimate objective is to facilitate drug development by creating an in silico platform to evaluate and predict comprehensively how molecular interventions affect not only a single targeted arrhythmia, but all primary arrhythmia dynamics categories as well as normal cardiac excitation-contraction coupling.