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</script>Structured models of ontogenic, phenotypic and functional diversity have been instrumental for a renewed understanding of the biology of immune cells, such as macrophages and lymphoid cells. However, there are no established models that can be used to define the diversity of neutrophils, the most abundant myeloid cells. This lack of an established model is largely due to the uniquely short lives of neutrophils, a consequence of their inability to divide once terminally differentiated, which has been perceived as a roadblock to functional diversity. This perception is rapidly evolving as multiple phenotypic and functional variants of neutrophils have been found, both in homeostatic and disease conditions. In this Opinion article, we present an overview of neutrophil heterogeneity and discuss possible mechanisms of diversification, including genomic regulation. We suggest that neutrophil heterogeneity is an important feature of immune pathophysiology, such that co-option of the mechanisms of diversification by cancer or other disorders contributes to disease progression.
Animals; Cell Differentiation; Humans; Immune System Diseases; Myeloid Cells; Neoplasms; Neutrophils, Immune System Diseases, Neutrophils, Neoplasms, Animals, Humans, Cell Differentiation, Myeloid Cells
Animals; Cell Differentiation; Humans; Immune System Diseases; Myeloid Cells; Neoplasms; Neutrophils, Immune System Diseases, Neutrophils, Neoplasms, Animals, Humans, Cell Differentiation, Myeloid Cells
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 535 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
