Cancer-on-a-chip model shows that the adenomatous polyposis coli mutation impairs T cell engagement and killing of cancer spheroids.

Evaluating the ability of cytotoxic T lymphocytes (CTLs) to eliminate tumor cells is crucial, for instance, to predict the efficiency of cell therapy in personalized medicine. However, the destruction of a tumor by CTLs involves CTL migration in the extra-tumoral environment, accumulation on the tumor, antigen recognition, and cooperation in killing the cancer cells. Therefore, identifying the limiting steps in this complex process requires spatio-temporal measurements of different cellular events over long periods.

Spatiotemporal dynamics of cytokines expression dictate fetal liver hematopoiesis.

During embryogenesis, yolk-sac and intra-embryonic-derived hematopoietic progenitors, comprising the precursors of adult hematopoietic stem cells, converge into the fetal liver. With a new staining strategy, we defined all non-hematopoietic components of the fetal liver and found that hepatoblasts are the major producers of hematopoietic growth factors. We identified mesothelial cells, a novel component of the stromal compartment, producing Kit ligand, a major hematopoietic cytokine.

Apical size and expression predict adult neural stem cell decisions along lineage progression.

The maintenance of neural stem cells (NSCs) in the adult brain depends on their activation frequency and division mode. Using long-term intravital imaging of NSCs in the zebrafish adult telencephalon, we reveal that apical surface area and expression of the Notch ligand DeltaA predict these NSC decisions. -negative NSCs constitute a bona fide self-renewing NSC pool and systematically engage in asymmetric divisions generating a self-renewing daughter, which regains the size and behavior of its mother, and a neurogenic daughter, eventually engaged in neuronal production following further quiescence-division phases.

Griottes: a generalist tool for network generation from segmented tissue images.

Background: Microscopy techniques and image segmentation algorithms have improved dramatically this decade, leading to an ever increasing amount of biological images and a greater reliance on imaging to investigate biological questions. This has created a need for methods to extract the relevant information on the behaviors of cells and their interactions, while reducing the amount of computing power required to organize this information.

Results: This task can be performed by using a network representation in which the cells and their properties are encoded in the nodes, while the neighborhood interactions are encoded by the links.