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线扫描和帧扫描图像中钙释放事件的自动检测和分类。

Automatic Detection and Classification of Ca Release Events in Line- and Frame-Scan Images.

机构信息

Department of Physiology, University of Bern, Bern, Switzerland.

Department of Physiology, University of Bern, Bern, Switzerland.

出版信息

Biophys J. 2019 Feb 5;116(3):383-394. doi: 10.1016/j.bpj.2018.12.013. Epub 2018 Dec 25.

Abstract

Analysis of Ca signals obtained in various cell types (i.e., cardiomyocytes) is always a tradeoff between acquisition speed and signal/noise ratio of the fluorescence signal. This becomes especially apparent during fast two- or three-dimensional confocal imaging when local intracellular fluorescence signals originating from Ca release from intracellular Ca stores (e.g., sarcoplasmic reticulum) need to be examined. Mathematical methods have been developed to remedy a high noise level by fitting each pixel with a transient function to "denoise" the image. So far, current available analytical approaches have been impaired by a number of constraints (e.g., inability to fit local, concurrent, and consecutive events) and the limited ability to customize implementation. Here, we suggest a, to our knowledge, novel approach for detailed analysis of subcellular micro-Ca events based on pixel-by-pixel denoising of confocal frame- and line-scan images. The algorithm enables spatiotemporally overlapping events (e.g., a Ca spark occurring during the decaying phase of a Ca wave) to be extracted so that various types of Ca events can be detected at a pixel time level of precision. The method allows a nonconstant baseline to be estimated for each pixel, foregoing the need to subtract fluorescence background or apply self-ratio methods before image analysis. Furthermore, by using a clustering algorithm, identified single-pixel events are grouped into "physiologically relevant" Ca signaling events spanning multiple pixels (sparks, waves, puffs, transients, etc.), from which spatiotemporal event parameters (e.g., full duration at half maximal amplitude, full width at half maximal amplitude, amplitude, wave speed, rise, and decay times) can be easily extracted. The method was implemented with cross-platform open source software, providing a comprehensive and easy-to-use graphical user interface enabling rapid line-scan images and rapid frame-scan image sequences (up to 150 frames/s) to be analyzed and repetitive Ca events (Ca sparks and Ca puffs) originating from clusters of Ca release channels located in the sarcoplasmic reticulum membrane (ryanodine receptors and inositol 1,4,5-trisphosphate receptors) of isolated cardiomyocytes to be examined with a high level of precision.

摘要

对各种细胞类型(即心肌细胞)中的 Ca 信号进行分析,总是需要在采集速度和荧光信号的信噪比之间进行权衡。当需要检查源自细胞内 Ca 释放的局部细胞内荧光信号时,这种情况在快速二维或三维共焦成像中尤为明显,例如肌浆网)。已经开发了数学方法通过为每个像素拟合瞬态函数来“降噪”图像,以弥补高噪声水平。到目前为止,当前可用的分析方法受到许多限制的影响(例如,无法拟合局部、并发和连续事件),并且实现的定制能力有限。在这里,我们提出了一种新颖的方法,用于基于共焦帧和线扫描图像中每个像素的去噪对亚细胞微 Ca 事件进行详细分析。该算法能够提取时空重叠事件(例如,Ca 波衰减阶段发生的 Ca 火花),从而能够以像素级时间精度检测各种类型的 Ca 事件。该方法允许为每个像素估计非恒定基线,无需在图像分析之前减去荧光背景或应用自比方法。此外,通过使用聚类算法,将识别的单像素事件分组为跨越多个像素的“生理相关”Ca 信号事件(火花、波、爆发、瞬变等),从中可以轻松提取时空事件参数(例如,半最大幅度的全持续时间,半最大幅度的全宽度,幅度,波速,上升和下降时间)。该方法使用跨平台开源软件实现,提供了一个全面且易于使用的图形用户界面,能够快速分析线扫描图像和快速帧扫描图像序列(高达 150 帧/秒),并能够重复分析源自肌浆网膜中 Ca 释放通道簇的 Ca 事件(Ca 火花和 Ca 爆发)(ryanodine 受体和肌醇 1,4,5-三磷酸受体)具有高精度。

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