Suppr超能文献

一种用于自动定量斑马鱼幼体细菌负荷的图像处理工具。

An Image Processing Tool for Automated Quantification of Bacterial Burdens in Zebrafish Larvae.

作者信息

Yamaguchi Naoya, Otsuna Hideo, Eisenberg-Bord Michal, Ramakrishnan Lalita

机构信息

Department of Medicine, Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, University of Cambridge, Cambridge, UK.

MRC Laboratory of Molecular Biology, Cambridge, UK.

出版信息

Zebrafish. 2025 Feb;22(1):11-14. doi: 10.1089/zeb.2024.0170. Epub 2024 Dec 24.

Abstract

Zebrafish larvae are used to model the pathogenesis of multiple bacteria. This transparent model offers the unique advantage of allowing quantification of fluorescent bacterial burdens (fluorescent pixel counts [FPC]) by facile microscopical methods, replacing enumeration of bacteria using time-intensive plating of lysates on bacteriological media. Accurate FPC measurements require laborious manual image processing to mark the outside borders of the animals so as to delineate the bacteria inside the animals from those in the culture medium that they are in. Here, we have developed an automated ImageJ/Fiji-based macro that accurately detects the outside borders of -infected larvae.

摘要

斑马鱼幼体被用于多种细菌致病机制的建模。这种透明模型具有独特优势,可通过简便的显微镜方法对荧光细菌载量(荧光像素计数 [FPC])进行定量,取代了在细菌培养基上对裂解物进行耗时平板培养来计数细菌的方法。准确的 FPC 测量需要费力的手动图像处理来标记动物的外部边界,以便将动物体内的细菌与它们所处培养基中的细菌区分开来。在此,我们开发了一种基于 ImageJ/Fiji 的自动化宏程序,可准确检测受感染幼体的外部边界。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验