Department of Endodontics, University of Texas Health San Antonio, TX, USA.
Department of Mathematics, University of Texas at San Antonio, TX, USA.
J Neurosci Methods. 2021 Oct 1;362:109312. doi: 10.1016/j.jneumeth.2021.109312. Epub 2021 Aug 8.
Electrophysiological recordings of isolated sensory afferents are commonly used in the field of pain research to investigate peripheral mechanisms of nociception in various pain models. The method involves skillful and tedious recordings of teased fibers from nerve preparations as well as time-consuming post-recording analyses. To increase efficiency and productivity of data analyses of recorded action potentials, we developed and validated a novel, easy-to-use Microsoft Excel-based application using Visual Basic Programming.
A code for the novel program, shigraspike1.0, was written to create a module to include customizable subroutines for analyses for electrical and mechanical responses. Using previously recorded action potentials with tongue-lingual nerve preparations, the program was validated for appropriate execution, ease-of-use, accuracy of the output data and time taken for analyses.
We observed appropriate execution of shigraspike1.0 on Windows and iOS desktop platforms that included computation of response latency of the spike of interest using electrical stimulus as well as estimation of the number of impulses at each force with a step-and-hold mechanical ramp of 10-200mN. Output data obtained by shigrapsike1.0 for both stimulus types were accurate and statistically insignificant from manual analyses.
The novel application shigraspike1.0, allows for rapid analyses for single-fiber recordings and takes less than half the time to analyze electrical and mechanical responses compared to manual analyses.
The newly developed shigraspike1.0 application can be a very productive tool to be routinely used for efficient analyses of single-fiber electrophysiology in pain research.
在疼痛研究领域,分离感觉传入纤维的电生理学记录常用于研究各种疼痛模型中的外周伤害感受机制。该方法涉及从神经制剂中巧妙而繁琐地记录梳理纤维,以及耗时的记录后分析。为了提高记录动作电位分析数据的效率和生产力,我们使用 Visual Basic 编程开发并验证了一种新颖的、易于使用的基于 Microsoft Excel 的应用程序。
编写了一个新程序 shigraspike1.0 的代码,创建了一个模块,其中包含用于电和机械响应分析的可定制子程序。使用舌神经制剂中以前记录的动作电位,验证程序的正确执行、易用性、输出数据的准确性和分析所需的时间。
我们观察到 shigraspike1.0 在 Windows 和 iOS 桌面平台上的正确执行,包括使用电刺激计算感兴趣的尖峰的响应潜伏期,以及使用 10-200mN 的步长保持机械斜坡估计每个力的脉冲数。shigrapsike1.0 为两种刺激类型获得的输出数据准确,与手动分析相比无统计学意义。
新的应用程序 shigraspike1.0 允许对单纤维记录进行快速分析,与手动分析相比,分析电和机械响应所需的时间不到一半。
新开发的 shigraspike1.0 应用程序可以成为疼痛研究中单纤维电生理学高效分析的非常有成效的工具。