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Neutrophils are innate immune cells that are key to protecting the host against infection and maintaining body homeostasis. However, if dysregulated, they can contribute to disease, such as in cancer or chronic autoinflammatory disorders. Recent studies have highlighted the heterogeneity in the neutrophil compartment and identified the presence of immature neutrophils and their precursors in these pathologies. Therefore, understanding neutrophil maturity and the mechanisms through which they contribute to disease is critical. Neutrophils were first characterized morphologically by Ehrlich in 1879 using microscopy, and since then, different technologies have been used to assess neutrophil maturity. The advances in the imaging field, including state-of-the-art microscopy and machine learning algorithms for image analysis, reinforce the use of neutrophil nuclear morphology as a fundamental marker of maturity, applicable for objective classification in clinical diagnostics. New emerging approaches, such as the capture of changes in chromatin topology, will provide mechanistic links between the nuclear shape, chromatin organization, and transcriptional regulation during neutrophil maturation.

Original publication

DOI

10.1093/jleuko/qiad084

Type

Journal

J leukoc biol

Publication Date

24/11/2023

Volume

114

Pages

585 - 594

Keywords

cell differentiation, chromatin topology, machine learning, microscopy, neutrophil, nuclear morphology, Neutrophils, Chromatin, Gene Expression Regulation