Rickert Christian, Proenza Catherine
Department of Physiology and Biophysics, University of Colorado-Anschutz Medical Campus, Aurora, Colorado.
Department of Physiology and Biophysics, University of Colorado-Anschutz Medical Campus, Aurora, Colorado.
Biophys J. 2017 Aug 22;113(4):765-769. doi: 10.1016/j.bpj.2017.07.001.
Sinoatrial node myocytes act as cardiac pacemaker cells by generating spontaneous action potentials (APs). Much information is encoded in sinoatrial AP waveforms, but both the analysis and the comparison of AP parameters between studies is hindered by the lack of standardized parameter definitions and the absence of automated analysis tools. Here we introduce ParamAP, a standalone cross-platform computational tool that uses a template-free detection algorithm to automatically identify and parameterize APs from text input files. ParamAP employs a graphic user interface with automatic and user-customizable input modes, and it outputs data files in text and PDF formats. ParamAP returns a total of 16 AP waveform parameters including time intervals such as the AP duration, membrane potentials such as the maximum diastolic potential, and rates of change of the membrane potential such as the diastolic depolarization rate. ParamAP provides a robust AP detection algorithm in combination with a standardized AP parameter analysis over a wide range of AP waveforms and firing rates, owing in part to the use of an iterative algorithm for the determination of the threshold potential and the diastolic depolarization rate that is independent of the maximum upstroke velocity, a parameter that can vary significantly among sinoatrial APs. Because ParamAP is implemented in Python 3, it is also highly customizable and extensible. In conclusion, ParamAP is a powerful computational tool that facilitates quantitative analysis and enables comparison of sinoatrial APs by standardizing parameter definitions and providing an automated work flow.
窦房结心肌细胞通过产生自发性动作电位(APs)充当心脏起搏器细胞。窦房结AP波形中编码了许多信息,但由于缺乏标准化的参数定义以及缺少自动化分析工具,研究之间AP参数的分析和比较受到了阻碍。在此,我们介绍ParamAP,这是一个独立的跨平台计算工具,它使用无模板检测算法从文本输入文件中自动识别AP并对其进行参数化。ParamAP采用具有自动和用户可定制输入模式的图形用户界面,并以文本和PDF格式输出数据文件。ParamAP总共返回16个AP波形参数,包括诸如AP持续时间等时间间隔、诸如最大舒张电位等膜电位以及诸如舒张期去极化速率等膜电位变化率。ParamAP结合了强大的AP检测算法以及在广泛的AP波形和发放率范围内进行标准化的AP参数分析,部分原因是使用了一种迭代算法来确定阈值电位和舒张期去极化速率,该算法独立于最大上升速度,而最大上升速度是一个在窦房结AP之间可能有显著差异的参数。由于ParamAP是用Python 3实现的,它还具有高度的可定制性和可扩展性。总之,ParamAP是一个强大的计算工具,通过标准化参数定义并提供自动化工作流程,便于进行定量分析并能够比较窦房结AP。