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This mechanism is summarized in Figure 3

A greater understanding of the correlates of protection against infection and disease is needed, particularly for T-cell responses, which are understudied due to the requirement for large sample volumes and the use of low-throughput assays

This compromise means accurate fully automated segmentation and complete tissue reconstruction is difficult, but the development of deep learning segmentation tools, such as PlantSeg (Wolny et al., Reference Wolny, Cerrone, Vijayan, Tofanelli, Barro, Louveaux, Wenzl, Strauss, Wilson-Snchez, Lymbouridou, Steigleder, Pape, Bailoni, Duran-Nebreda, Bassel, Lohmann, Tsiantis, Hamprecht, Schneitz and Kreshuk2020) and Stardist (Weigert et al., Reference Weigert, Schmidt, Haase, Sugawara and Myers2020), may help increase segmentation accuracy and overcome some of these bottlenecks

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