Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT

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title = "Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT",
abstract = "Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. Immunofluorescence microscopy and image-based quantification methods remain important tools to quantitate neutrophil extracellular trap formation. However, there are key limitations to the immunofluorescence-based methods that are currently available for quantifying NETs. Manual methods of image-based NET quantification are often subjective, prone to error and tedious for users, especially non-experienced users. Also, presently available software options for quantification are either semi-automatic or require training prior to operation. Here, we demonstrate the implementation of an automated immunofluorescence-based image quantification method to evaluate NET formation called NETQUANT. The software is easy to use and has a user-friendly graphical user interface (GUI). It considers biologically relevant parameters such as an increase in the surface area and DNA:NET marker protein ratio, and nuclear deformation to define NET formation. Furthermore, this tool is built as a freely available app, and allows for single-cell resolution quantification and analysis.",
author = "Tirthankar Mohanty and Pontus Nordenfelt",
year = "2019",
month = nov,
day = "27",
doi = "10.3791/58528",
language = "English",
journal = "Journal of Visualized Experiments",
issn = "1940-087X",
publisher = "JoVE",
number = "153",