Temperature-induced arousability during sleep is a missing piece in the puzzle for triggers of sudden infant death syndrome.

The ventricular tissue is activated in a stochastic rather than in a deterministic rhythm due to the inherent heart rate variability (HRV). Low HRV is a known predictor for arrhythmia events and traditionally is attributed to autonomic nervous system tone damage. Yet, there is no model that directly assesses the antiarrhythmic effect of pacing stochasticity per se. One-dimensional (1D) and two-dimensional (2D) human ventricular tissues were modeled, and both deterministic and stochastic pacing protocols were applied. Action potential duration restitution (APDR) and conduction velocity restitution (CVR) curves were generated and analyzed, and the propensity and characteristics of action potential duration (APD) alternans were investigated. In the 1D model, pacing stochasticity was found to sustain a moderating effect on the APDR curve by reducing its slope, rendering the tissue less arrhythmogenic. Moreover, stochasticity was found to be a significant antagonist to the development of concordant APD alternans. These effects were generally amplified with increased variability in the pacing cycle intervals. In addition, in the 2D tissue configuration, stochastic pacing exerted a protective antiarrhythmic effect by reducing the spatial APD heterogeneity and converting discordant APD alternans to concordant ones. These results suggest that high cardiac pacing stochasticity is likely to reduce the risk of cardiac arrhythmias in patients.

Illumination field inhomogeneity strongly affects the visual appearance of an image. It has a major influence on automatic information extraction within an image and its correction is critical for comparison or model learning across images. In this work a unique medical repository of cervicographic images ("cervigrams") collected by the National Center Institute (NCI), National Institute of Health (NIH) is being addressed. The large diversity of cervix shapes within this database, as well as the acquisition set-up, lead to varying illumination conditions among and within the cervigrams, which hamper their automatic analysis. Illumination correction is therefore one of the first preprocessing steps required prior to the image analysis task. This paper presents a method for illumination correction in cervigrams based on a generalized expectation maximization (GEM) algorithm that interleaves pixels classification with estimation of class distribution and illumination field parameters. For cross-image analysis a normalization of the image dynamic range is conducted, using prior knowledge on cervix tissue intensity distribution.Experimental results are provided and evaluated on a set of 110 cervigrams that were manually labeled by an NCI expert. Unsupervised segmentation as well as initial supervised tissue classification results are presented.

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Low pacing variability in the heart has been clinically reported as a risk factor for lethal cardiac arrhythmias and arrhythmic death. In ia previous simulation study, we demonstrated that stochastic pacing sustains an antiarrhythmic effect by moderating the slope of the action potential duration (APD) restitution curve, by reducing the propensity of APD alternans, converting discordant to concordant alternans, and ultimately preventing wavebreaks. However, the dynamic mechanisms relating pacing stochasticity to tissue stability are not yet known. In this work, we develop a mathematical framework to describe the APD signal using an autoregressive stochastic model, and we establish the interrelations between stochastic pacing, cardiac memory, and cardiac stability, as manifested by the degree of APD alternans. Employing stability analysis tools, we show that increased stochasticity in the ventricular tissue activation sequence works to lower the maximal absolute eigenvalues of the stochastic model, thereby contributing to increased stability. We also show that the memory coefficients of the autoregressive model are modulated by pacing stochasticity in a nonlinear, biphasic way, so that for exceedingly high levels of pacing stochasticity, the antiarrhythmic effect is hampered by increasing APD variance. This work may contribute to establishment of an optimal antiarrhythmic pacing protocol in a future study.

The physiological heart rate presents a stochastic behavior known as heart rate variability (HRV). In this framework the influence of HRV on the action potential duration (APD) of the atrial myocyte is analyzed in a computer model. We have found that introducing HRV into the myocyte action potential model decreases the APD of the extra beat S2 in an S1-S2 protocol compared to constant heart rate. A possible theoretical explanation for this is also presented and is derived from switched systems theory. It is suggested to consider the myocyte action potential phase 4 and phase 2 as two operation modes of a switching system and analyze the stability of switching between them. Since random switching is known to have a stabilization effect on a switching system, this might explain why HRV has a stabilization effect on the myocyte APD restitution. Implications of this finding include reduced system stability for conditions with low HRV. A possible application for this phenomenon regards artificial pacemakers, where a preset added HRV is predicted to reduce susceptibility to arrhythmias.

A single isolated sinoatrial pacemaker cell presents intrinsic interbeat interval (IBI) variability that is believed to result from the stochastic characteristics of the opening and closing processes of membrane ion channels. To our knowledge, a novel mathematical framework was developed in this work to address the effect of current fluctuations on the IBIs of sinoatrial pacemaker cells. Using statistical modeling and employing the Fokker-Planck formalism, our mathematical analysis suggests that increased stochastic current fluctuation variance linearly increases the slope of phase-4 depolarization, hence the rate of activations. Single-cell and two-dimensional computerized numerical modeling of the sinoatrial node was conducted to validate the theoretical predictions using established ionic kinetics of the rabbit pacemaker and atrial cells. Our models also provide, to our knowledge, a novel complementary or alternative explanation to recent experimental observations showing a strong reduction in the mean IBI of Cx30 deficient mice in comparison to wild-types, not fully explicable by the effects of intercellular decoupling.

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