Bose-Einstein condensation in dense quark matter

We consider the problem of Bose condensation of charged pions in QCD at finite isospin chemical potential $\mu_I$ using the O(4)-symmetric linear sigma model as an effective field theory for two-flavor QCD. Using the 2PI $1/N$-expansion, we determine the quasiparticle masses as well as the pion and chiral condensates as a function of the temperature and isospin chemical potential in the chiral limit and at the physical point. At T=0, Bose condensation takes place for chemical potentials larger than $m_{\pi}$. In the chiral limit, the chiral condensate vanishes for any finite value of $\mu_I$.Comment: Talk given at Strong and Electroweak matter 2008, Amsterdam August 25-29 2008. Four pages and two figures. 2nd version: typos fixed and updated list of ref

ECGdeli - An open source ECG delineation toolbox for MATLAB

The electrocardiogram (ECG) is a standard cost-efficient and non-invasive tool for the early detection of various cardiac diseases. Quantifying different timing and amplitude features of and in between the single ECG waveforms can reveal important information about the underlying (dys-)function of the heart. Determining these features requires the detection of fiducial points that mark the on- and offset as well as the peak of each ECG waveform (P wave, QRS complex, T wave). Manually setting these points is time-consuming and requires a physician’s expert knowledge. Therefore, the highly modular ECGdeli toolbox for MATLAB was developed, which is capable of filtering clinically recorded 12-lead ECG signals and detecting the fiducial points, also called delineation. It is one of the few open toolboxes offering ECG delineation for P waves, T Waves and QRS complexes. The algorithms provided were evaluated with the QT database, an ECG database comprising 105 signals with fiducial points annotated by clinicians. The median difference between the fiducial points set by the boundary detection algorithm and the clinical annotations serving as a ground truth is less than 4 samples (16 ms) for the P wave and the QRS complex markers. The T wave onset, peak and offset were detected with a median difference of 5, 2 and 7 samples, respectively. Results were compared to two free algorithms available on PhysioNet. Our results show that ECGdeli can reliably detect P waves, QRS complexes and T waves. Thus, it can contribute to diagnose specific cardiac diseases by analyzing the ECG signal. As ECGdeli is published under GNU GPLv3 and thanks to its modularity, it can be used to extend existing algorithms or as a benchmark for new algorithms

Observability of an induced electric dipole moment of the neutron from nonlinear QED

It has been shown recently that a neutron placed in an external quasistatic electric field develops an induced electric dipole moment $\mathbf{p}_{\mathrm{IND}}$ due to quantum fluctuations in the QED vacuum. A feasible experiment which could detect such an effect is proposed and described here. It is shown that the peculiar angular dependence of $\mathbf{p}_{\mathrm{IND}}$ on the orientation of the neutron spin leads to a characteristic asymmetry in polarized neutron scattering by heavy nuclei. This asymmetry can be of the order of $10^{-3}$ for neutrons with epithermal energies. For thermalized neutrons from a hot moderator one still expects experimentally accessible values of the order of $10^{-4}$. The contribution of the induced effect to the neutron scattering length is expected to be only one order of magnitude smaller than that due to the neutron polarizability from its quark substructure. The experimental observation of this scattering asymmetry would be the first ever signal of nonlinearity in electrodynamics due to quantum fluctuations in the QED vacuum

770-5 Chamber Specific Regulation of the Sarcoplasmic Reticulum Calcium ATPase Pump In Human Heart Failure

Alterations in the expression of Ca2+ channels have been described in failing human left ventricle, including down regulation of the ryanodine receptor (RyR)/Ca2+ release channel and the sarcoplasmic reticulum Ca2+ ATPase pump (SERCA) which are involved in excitation-contraction coupling and relaxation (Cir Res 71: 18, 1992). We previously reported chamber specific regulation of the RyR during end-stage human heart failure (Clin Res 42(2):166A. 1994). We investigated whether SERCA is also regulated in the other cardiac chambers during human heart failure. Total RNA and protein homogenates were isolated from the left and right atria (LA, RA) and left and right ventricles (LV, RV) obtained prospectively from 32 cardiac transplant patients and 4 normal controls. Messenger RNA (mRNA) levels of SERCA were quantified using Northern and slot blot hybridizations with a 1.6kb rat cardiac SERCA cDNA probe and normalized to 28S ribosomal levels. Protein levels of SERCA were quantified using enzyme-linked immunosorbent assays with monoclonal antibodies directed against dog cardiac SERCA. Northern analyses detected a single ≈4 kb mRNA in all regions. Compared to controls. SERCA mRNA expression in failing hearts was decreased in LV by 39% (p<0.005), unchanged in RV, and increased in LA by 255% (p<0.005) and in RA by 338% (p<0.025). Consistent with the mRNA data. immunodetectable levels of SERCA were also reduced in LV by 30% (p<0.05) and unchanged in RV; however, protein levels appeared unchanged or reduced in both atria in contrast to the mRNA. This is the first study reporting simultaneous measurements of SERCA mRNA and protein levels in the human heart. We conclude that chamber specific regulation of SERCA mRNA occurs during end-stage heart failure. corroborated by protein expression in the ventricles. Down regulations of SERCA may contribute to impaired relaxation and increased diastolic tone during heart failure

ECG-Based Detection of Early Myocardial Ischemia in a Computational Model: Impact of Additional Electrodes, Optimal Placement, and a New Feature for ST Deviation

In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2-11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold. © 2015 Axel Loewe et al

A computational framework to benchmark basket catheter guided ablation in atrial fibrillation

Catheter ablation is a curative therapeutic approach for atrial fibrillation (AF). Ablation of rotational sources based on basket catheter measurements has been proposed as a promising approach in patients with persistent AF to complement pulmonary vein isolation. However, clinically reported success rates are equivocal calling for a mechanistic investigation under controlled conditions. We present a computational framework to benchmark ablation strategies considering the whole cycle from excitation propagation to electrogram acquisition and processing to virtual therapy. Fibrillation was induced in a patient-specific 3D volumetric model of the left atrium, which was homogeneously remodeled to sustain reentry. The resulting extracellular potential field was sampled using models of grid catheters as well as realistically deformed basket catheters considering the specific atrial anatomy. The virtual electrograms were processed to compute phase singularity density maps to target rotor tips with up to three circular ablations. Stable rotors were successfully induced in different regions of the homogeneously remodeled atrium showing that rotors are not constrained to unique anatomical structures or locations. Density maps of rotor tip trajectories correctly identified and located the rotors (deviation < 10 mm) based on catheter recordings only for sufficient resolution (inter-electrode distance ≤3 mm) and proximity to the wall (≤10 mm). Targeting rotor sites with ablation did not stop reentries in the homogeneously remodeled atria independent from lesion size (1–7 mm radius), from linearly connecting lesions with anatomical obstacles, and from the number of rotors targeted sequentially (≤3). Our results show that phase maps derived from intracardiac electrograms can be a powerful tool to map atrial activation patterns, yet they can also be misleading due to inaccurate localization of the rotor tip depending on electrode resolution and distance to the wall. This should be considered to avoid ablating regions that are in fact free of rotor sources of AF. In our experience, ablation of rotor sites was not successful to stop fibrillation. Our comprehensive simulation framework provides the means to holistically benchmark ablation strategies in silico under consideration of all steps involved in electrogram-based therapy and, in future, could be used to study more heterogeneously remodeled disease states as well

Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches

Influence of ECG Lead reduction techniques for extracellular potassium and calcium concentration estimation

Chronic kidney disease (CKD) affects 13% of the worldwide population and end stage patients often receive haemodialysis treatment to control the electrolyte concentrations. The cardiovascular death rate increases by 10% - 30% in dialysis patients than in general population. To analyse possible links between electrolyte concentration variation and cardiovascular diseases, a continuous noninvasive monitoring tool enabling the estimation of potassium and calcium concentration from features of the ECG is desired. Although the ECG was shown capable of being used for this purpose, the method still needs improvement. In this study, we examine the influence of lead reduction techniques on the estimation results of serum calcium and potassium concentrations. We used simulated 12 lead ECG signals obtained using an adapted Himeno et al. model. Aiming at a precise estimation of the electrolyte concentrations, we compared the estimation based on standard ECG leads with the estimation using linearly transformed fusion signals. The transformed signals were extracted from two lead reduction techniques: principle component analysis PCA) and maximum amplitude transformation (MaxAmp). Five features describing the electrolyte changes were calculated from the signals. To reconstruct the ionic concentrations, we applied a first and a third order polynomial regression connecting the calculated features and concentration values. Furthermore, we added 30 dB white Gaussian noise to the ECGs to imitate clinically measured signals. For the noise-free case, the smallest estimation error was achieved with a specific single lead from the standard 12 lead ECG. For example, for a first order polynomial regression, the error was 0.0003±0.0767 mmol/l (mean±standard deviation) for potassium and -0.0036±0.1710 mmol/l for calcium (Wilson lead V1). For the noisy case, the PCA signal showed the best estimation performance with an error of -0.003±0.2005 mmol/l for potassium and -0.0002±0.2040 mmol/l for calcium (both first order fit). Our results show that PCA as ECG lead reduction technique is more robust against noise than MaxAmp and standard ECG leads for ionic concentration reconstruction

Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable

Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration