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ColocZStats:一款用于3D Slicer的Z轴堆叠信号共定位扩展工具。

ColocZStats: a z-stack signal colocalization extension tool for 3D slicer.

作者信息

Chen Xiang, Thakur Teena, Jeyasekharan Anand D, Benoukraf Touati, Meruvia-Pastor Oscar

机构信息

Division of BioMedical Sciences, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada.

Department of Computer Science, Faculty of Science, Memorial University of Newfoundland, St. John's, NL, Canada.

出版信息

Front Physiol. 2024 Sep 4;15:1440099. doi: 10.3389/fphys.2024.1440099. eCollection 2024.

Abstract

Confocal microscopy has evolved to be a widely adopted imaging technique in molecular biology and is frequently utilized to achieve accurate subcellular localization of proteins. Applying colocalization analysis on image z-stacks obtained from confocal fluorescence microscopes is a dependable method of revealing the relationship between different molecules. In addition, despite the established advantages and growing adoption of 3D visualization software in various microscopy research domains, there have been few systems that can support colocalization analysis within a user-specified region of interest (ROI). In this context, several broadly employed biological image visualization platforms are meticulously explored in this study to understand the current landscape. It has been observed that while these applications can generate three-dimensional (3D) reconstructions for z-stacks, and in some cases transfer them into an immersive virtual reality (VR) scene, there is still little support for performing quantitative colocalization analysis on such images based on a user-defined ROI and thresholding levels. To address these issues, an extension called ColocZStats (pronounced Coloc-Zee-Stats) has been developed for 3D Slicer, a widely used free and open-source software package for image analysis and scientific visualization. With a custom-designed user-friendly interface, ColocZStats allows investigators to conduct intensity thresholding and ROI selection on imported 3D image stacks. It can deliver several essential colocalization metrics for structures of interest and produce reports in the form of diagrams and spreadsheets.

摘要

共聚焦显微镜已发展成为分子生物学中广泛采用的成像技术,并经常用于实现蛋白质的精确亚细胞定位。对从共聚焦荧光显微镜获得的图像z轴堆栈进行共定位分析是揭示不同分子之间关系的可靠方法。此外,尽管3D可视化软件在各种显微镜研究领域具有既定优势且应用越来越广泛,但很少有系统能够支持在用户指定的感兴趣区域(ROI)内进行共定位分析。在此背景下,本研究精心探索了几种广泛使用的生物图像可视化平台,以了解当前的情况。据观察,虽然这些应用程序可以为z轴堆栈生成三维(3D)重建,并且在某些情况下将其转换为沉浸式虚拟现实(VR)场景,但对于基于用户定义的ROI和阈值水平对此类图像进行定量共定位分析的支持仍然很少。为了解决这些问题,已为3D Slicer开发了一个名为ColocZStats(发音为Coloc-Zee-Stats)的扩展程序,3D Slicer是一个广泛使用的免费开源软件包,用于图像分析和科学可视化。通过定制设计的用户友好界面,ColocZStats允许研究人员对导入的3D图像堆栈进行强度阈值处理和ROI选择。它可以为感兴趣的结构提供几个重要的共定位指标,并以图表和电子表格的形式生成报告。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5437/11408364/19366b474f5f/fphys-15-1440099-g001.jpg

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