Interacting mast cells and eosinophils acquire an enhanced activation state in vitro.

BACKGROUND: Mast cells (MCs) and eosinophils (Eos), the key effector cells in allergy, are abundantly co-localized particularly in the late and chronic stages of allergic inflammation. Recent evidence has outlined a specialized 'allergic effector unit' in which MCs and Eos communicate via both soluble mediators and physical contact. However, the functional impact of this bi-directional crosstalk on the cells' effector activities has not yet been revealed. We aimed to investigate whether MC/eosinophil interactions can influence the immediate and late activation phenotypes of these cells. METHODS: Human and murine MCs and Eos were co-cultured under various conditions for 1-2 h or 1-3 days, and in selected experiments cell-cell contact was blocked. Cell migration and mediator release were examined, and flow cytometry was applied to stain intracellular signaling molecules and surface receptors. RESULTS: Eosinophils enhanced basal MCs mediator release and co-stimulated IgE-activated MCs through physical contact involving CD48-2B4 interactions. Reciprocally, resting and IgE-stimulated MCs led to eosinophil migration and activation through a paracrine-dependent mechanism. Increased phosphorylation of activation-associated signaling molecules, and enhanced release of tumor necrosis factor α, was observed in long-term co-cultures. Eosinophils also showed enhanced expression of intercellular adhesion molecule 1, which depended on direct contact with MCs. CONCLUSIONS: Our findings reveal a new role for MC/eosinophil interplay in augmenting short- and long-term activation in both cells, in a combined physical/paracrine manner. This enhanced functional activity may thus critically contribute to the perpetuation of the inflammatory response in allergic conditions.

Physical interactions between mast cells and eosinophils: a novel mechanism enhancing eosinophil survival in vitro.

BACKGROUND: Mast cells (MCs) and eosinophils (Eos) are the key effector cells of the allergic reaction. Although classically associated with different stages of the response, the cells co-exist in the inflamed tissue in the late and chronic phases in high numbers and are likely to cross-talk. While some mediators of MCs are known to affect Eos biology and vice versa, paracrine and physical interplay between the two cells has not been described yet. We aimed to investigate whether intercellular MC-Eos communication could take place in the allergic response and exert functional bidirectional changes on the cells. METHODS: Tissue sections from various allergic disorders were specifically stained for both cells. Human cord blood-derived MCs and peripheral blood Eos, co-cultured under different conditions, were studied by advanced microscopy and flow cytometry. RESULTS: Several co-localized MC-Eos pairs were detected in human nasal polyps and asthmatic bronchi, as well in mouse atopic dermatitis. In vitro, MCs and Eos formed stable conjugates at high rates, with clear membrane contact. In the presence of MCs, Eos were significantly more viable under several co-culture conditions and at both IgE-activated and steroid-inhibited settings. MC regulation of Eos survival required communication through soluble mediators but was even more dependent on physical cell-cell contact. CONCLUSIONS: Our findings provide the first evidence for a complex network of paracrine and membrane interactions between MCs and Eos. The prosurvival phenotype induced by this MC-Eos interplay may be critical for sustaining chronic allergic inflammation.

A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis.

Population modeling of tumor size dynamics has recently emerged as an important tool in pharmacometric research. A series of new mixed-effects models have been reported recently, and we present herein a synthetic view of models with published mathematical equations aimed at describing the dynamics of tumor size in cancer patients following anticancer drug treatment. This selection of models will constitute the basis for the Drug Disease Model Resources (DDMoRe) repository for models on oncology.