Automated, high-throughput quantification of EGFP-expressing neutrophils in zebrafish by machine learning and a highly-parallelized microscope

• Published in: PloS one Vol. 18; no. 12; p. e0295711
• Main Authors: Efromson, John, Ferrero, Giuliano, Bègue, Aurélien, Doman, Thomas Jedidiah Jenks, Dugo, Clay, Barker, Andi, Saliu, Veton, Reamey, Paul, Kim, Kanghyun, Harfouche, Mark, Yoder, Jeffrey A.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07.12.2023; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Animal genetic engineering; Artificial intelligence; Automation; Cameras; Computer vision; Danio rerio; Data transmission; Disease resistance; Enhanced green fluorescent protein; Fertilization; Fluorescence; Genetic analysis; Health aspects; Image analysis; Image processing; Immune response; Immune system; In vivo methods and tests; Larvae; Learning algorithms; Leukocytes (neutrophilic); Machine learning; Mechanization; Microscopes; Neutropenia; Neutrophils; Open source software; Optics; Public software; Segmentation; Software packages; Statistical analysis; Statistical models; Zebra fish; Zebrafish; United States; United States > US

Normal development of the immune system is essential for overall health and disease resistance. Bony fish, such as the zebrafish ( Danio rerio ), possess all the major immune cell lineages as mammals and can be employed to model human host response to immune challenge. Zebrafish neutrophils, for exa...