10 research outputs found

    CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

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    Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery

    A γ-secretase-like intramembrane cleavage of TNFα by the GxGD aspartyl protease SPPL2b

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    Gamma-secretase and signal peptide peptidase (SPP) are unusual GxGD aspartyl proteases, which mediate intramembrane proteolysis. In addition to SPP, a family of SPP-like proteins (SPPLs) of unknown function has been identified. We demonstrate that SPPL2b utilizes multiple intramembrane cleavages to liberate the intracellular domain of tumor necrosis factor alpha (TNFalpha) into the cytosol and the carboxy-terminal counterpart into the extracellular space. These findings suggest common principles for regulated intramembrane proteolysis by GxGD aspartyl proteases
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