EA4294, Agents Infectieux, Résistance et Chimiothérapie, Centre Universitaire de Recherche en Santé, Centre Hospitalier Universitaire et Université de Picardie Jules Verne, 80054 Amiens, France.
University of Lille, CNRS, INSERM, CHU Lille, Pasteur Institute of Lille, U1019-UMR8204-CIIL-Center for Infection and Immunity of Lille, 59019 Lille, France.
Viruses. 2019 Feb 19;11(2):165. doi: 10.3390/v11020165.
Counting labeled cells, after immunofluorescence or expression of a genetically fluorescent reporter protein, is frequently used to quantify viral infection. However, this can be very tedious without a high content screening apparatus. For this reason, we have developed QuantIF, an ImageJ macro that automatically determines the total number of cells and the number of labeled cells from two images of the same field, using DAPI- and specific-stainings, respectively. QuantIF can automatically analyze hundreds of images, taking approximately one second for each field. It is freely available as online at MDPI.com and has been developed using ImageJ, a free image processing program that can run on any computer with a Java virtual machine, which is distributed for Windows, Mac, and Linux. It is routinely used in our labs to quantify viral infections in vitro, but can easily be used for other applications that require quantification of labeled cells.
对免疫荧光或遗传荧光报告蛋白表达后的标记细胞进行计数，常用于量化病毒感染。然而，如果没有高通量筛选设备，这会非常繁琐。因此，我们开发了 QuantIF，这是一个 ImageJ 宏，它可以分别使用 DAPI 和特定染色，自动从同一场景的两个图像中确定总细胞数和标记细胞数。QuantIF 可以自动分析数百张图像，每张图像大约需要一秒钟。它可以在 MDPI.com 上免费获得，并且是使用 ImageJ 开发的，ImageJ 是一个免费的图像处理程序，可以在任何带有 Java 虚拟机的计算机上运行，它的 Windows、Mac 和 Linux 版本都有分发。它在我们的实验室中常用于体外量化病毒感染，但也可以轻松用于其他需要定量标记细胞的应用。
