Galectin-3-null mice display defective neutrophil clearance during acute inflammation

Galectin-3 has been associated with a plethora of proinflammatory functions because of its ability, among others, to promote neutrophil activation and because of the reduction in neutrophil recruitment in models of infection in Gal-3-null mice. Conversely, it has also been linked to resolution of inflammation through its actions as an opsonin and its ability to promote efferocytosis of apoptotic neutrophils. Using a self-resolving model of peritonitis, we have addressed the modulation and role of Gal-3 in acute inflammation. We have shown that Gal-3 expression is increased in neutrophils that travel to the inflamed peritoneum and that cellular localization of this lectin is modulated during the course of the inflammatory response. Furthermore, neutrophil recruitment to the inflamed peritoneum is increased in Gal-3–null mice during the course of the response, and that correlates with reduced numbers of monocytes/macrophages in the cavities of those mice, as well as reduced apoptosis and efferocytosis of Gal-3–null neutrophils. These data indicate a role for endogenous Gal-3 in neutrophil clearance during acute inflammation

A study on the friendship paradox – quantitative analysis and relationship with assortative mixing

The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the strength of the paradox and the direction of the paradox from the perspective of individual nodes, i.e., an indication of whether the individual is more or less popular than its friends. These local metrics are aggregated, and global metrics are proposed to express the phenomenon on a network-wide level. Theoretical results show that the defined metrics are well-behaved enough to capture the friendship paradox. We also theoretically analyze the behavior of the friendship paradox for popular network models in order to understand regimes where friendship paradox occurs. These theoretical findings are complemented by experimental results on both network models and real-world networks. By conducting a correlation study between the proposed metrics and degree assortativity, we experimentally demonstrate that the phenomenon of the friendship paradox is related to the well-known phenomenon of assortative mixing

A study on the friendship paradox – quantitative analysis and relationship with assortative mixing

The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first develop local metrics that quantify the strength and the direction of the paradox from the perspective of individual nodes, i.e., is the individual more or less popular than its friends. We aggregate the local measures to define global metrics that capture the friendship paradox at the network scale. Theoretical results are shown that support the global metrics to be well-behaved enough to capture the friendship paradox. Furthermore, through experiments, we identify regimes in network models, and real networks, where the friendship paradox is prominent. By conducting a correlation study between the proposed metrics and assortativity, we experimentally demonstrate that the phenomenon of the friendship paradox is related to the well-known phenomenon of homophily or assortative mixing

Mapping Out Emerging Network Structures in Dynamic Network Models Coupled with Epidemics

We consider the susceptible – infected – susceptible (SIS) epidemic on a dynamic network model with addition and deletion of links depending on node status. We analyse the resulting pairwise model using classical bifurcation theory to map out the spectrum of all possible epidemic behaviours. However, the major focus of the chapter is on the evolution and possible equilibria of the resulting networks. Whereas most studies are driven by determining system-level outcomes, e.g., whether the epidemic dies out or becomes endemic, with little regard for the emerging network structure, here, we want to buck this trend by augmenting the system-level results with mapping out of the structure and properties of the resulting networks. We find that depending on parameter values the network can become disconnected and show bistable-like behaviour whereas the endemic steady state sees the emergence of networks with qualitatively different degree distributions. In particular, we observe de-phased oscillations of both prevalence and network degree during which there is role reversal between the level and nature of the connectivity of susceptible and infected nodes. We conclude with an attempt at describing what a potential bifurcation theory for networks would look like