The ability to generate human pluripotent stem cell-derived cell types at sufficiently high numbers and in a reproducible manner is fundamental for clinical and biopharmaceutical applications. Current experimental methods for the differentiation of pluripotent cells such as human embryonic stem cells (hESC) rely on the generation of heterogeneous aggregates of cells, also called "embryoid bodies" (EBs), in small scale static culture. These protocols are typically (1) not scalable, (2) result in a wide range of EB sizes and (3) expose cells to fluctuations in physicochemical parameters. With the goal of establishing a robust bioprocess we first screened different scalable suspension systems for their ability to support the growth and differentiation of hESCs. Next homogeneity of initial cell aggregates was improved by employing a micro-printing strategy to generate large numbers of size-specified hESC aggregates. Finally, these technologies were integrated into a fully controlled bioreactor system and the impact of oxygen concentration was investigated. Our results demonstrate the beneficial effects of stirred bioreactor culture, aggregate size-control and hypoxia (4% oxygen tension) on both cell growth and cell differentiation towards cardiomyocytes. QRT-PCR data for markers such as Brachyury, LIM domain homeobox gene Isl-1, Troponin T and Myosin Light Chain 2v, as well as immunohistochemistry and functional analysis by response to chronotropic agents, documented the impact of these parameters on cardiac differentiation. This study provides an important foundation towards the robust generation of clinically relevant numbers of hESC derived cells.

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Ventricular arrhythmias arise from abnormal electrical activity of the lower chambers (ventricles) of the heart. Ventricular tachycardia (VT) and ventricular fibrillation (VF) are the two major subclasses of ventricular arrhythmias. While VT has treatment options that can be performed in catheterization labs, VF is a lethal cardiac arrhythmia, often when detected the patient receives an implantable defibrillator which restores the normal heart rhythm by the application of electric shocks whenever VF is detected. The classification of these two subclasses are important in making a decision on the therapy performed. As in the case of all real world process the boundary between VT and VF is ill defined which might lead to many of the patients experiencing arrhythmias in the overlap zone (that might be predominately VT) to receive shocks by the an implantable defibrillator. There may also be a small population of patients who could be treated with anti-arrhythmic drugs or catheterization procedure if they can be diagnosed to suffer from predominately VT after objectively analyzing their intracardiac electrogram data obtained from implantable defibrillator. The proposed work attempts to arrive at a quantifiable way to scale the ventricular arrhythmias into VT, VF, and the overlap zone arrhythmias as VT-VF candidates using features extracted from the wavelet analysis of surface electrograms. This might eventually lead to an objective way of analyzing arrhythmias in the overlap zone and computing their degree of affinity towards VT or VF. A database of 24 human ventricular arrhythmia tracings obtained from the MIT-BIH arrhythmia database was analyzed and wavelet-based features that demonstrated discrimination between the VT, VF, and VT-VF groups were extracted. An overall accuracy of 75% in classifying the ventricular arrhythmias into 3 groups was achieved.