The role of topology on the dynamics of the Naming Game

The Naming Game captures the essential features leading a population to agree on the use of a semiotic convention (or, more in general, an opinion). Consensus emerges through local negotiations between pairs of agents, in the absence of any central co-ordination. Thus, it is natural that topology, identifying the set of possible interactions, plays a central role in the dynamics of the model. Here, we review the role of different topological properties, pointing out that finite connectivity, combined with the small-world property, ensure the best performances in terms of memory usage and time to reach convergence

Optimality in self-organized molecular sorting

We introduce a simple physical picture to explain the process of molecular sorting, whereby specific proteins are concentrated and distilled into submicrometric lipid vesicles in eukaryotic cells. To this purpose, we formulate a model based on the coupling of spontaneous molecular aggregation with vesicle nucleation. Its implications are studied by means of a phenomenological theory describing the diffusion of molecules towards multiple sorting centers that grow due to molecule absorption and are extracted when they reach a sufficiently large size. The predictions of the theory are compared with numerical simulations of a lattice-gas realization of the model and with experimental observations. The efficiency of the distillation process is found to be optimal for intermediate aggregation rates, where the density of sorted molecules is minimal and the process obeys simple scaling laws. Quantitative measures of endocytic sorting performed in primary endothelial cells are compatible with the hypothesis that these optimal conditions are realized in living cells

Bootstrapping communication in language games

Semiotic dynamics is a fast growing field according to which language can be seen as an evolving and self-organizing system. In this paper we present a simple multi-agent framework able to account for the emergence of shared conventions in a population. Agents perform pairwise games and final consensus is reached without any outside control nor any global knowledge of the system. In particular we discuss how embedding the population in a non trivial interaction topology affects the behavior of the system and forces to carefully consider agents selection strategies. These results cast an interesting framework to address and study more complex issues in semiotic dynamics

Agreement dynamics on interaction networks with diverse topologies

We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence

Algebraic coarsening in voter models with intermediate states

The introduction of intermediate states in the dynamics of the voter model modifies the ordering process and restores an effective surface tension. The logarithmic coarsening of the conventional voter model in two dimensions is eliminated in favour of an algebraic decay of the density of interfaces with time, compatible with Model A dynamics at low temperatures. This phenomenon is addressed by deriving Langevin equations for the dynamics of appropriately defined continuous fields. These equations are analyzed using field theoretical arguments and by means of a recently proposed numerical technique for the integration of stochastic equations with multiplicative noise. We find good agreement with lattice simulations of the microscopic model.Comment: 11 pages, 5 figures; minor typos correcte

Intrapartum cardiotocography patterns observed in suspected clinical and subclinical chorioamnionitis in term fetuses.

AIM: To evaluate the cardiotocography (CTG) features observed in suspected intrapartum chorioamnionitis in term fetuses according to the recently suggested criteria for the pathophysiological interpretation of the fetal heart rate and their correlation with perinatal outcomes. METHODS: Retrospective analysis of nonconsecutive CTG traces. 'CTG chorioamnionitis' was diagnosed either based on a persistent rise in the baseline for the given gestation or on a persistent increase in the baseline fetal heart rate during labor >10% without preceding CTG signs of hypoxia and in the absence of maternal pyrexia. Perinatal outcomes were compared among cases with no sign of chorioamnionitis, in those with only CTG features suspicious for chorioamnionitis and in those who developed clinical chorioamnionitis. RESULTS: Two thousand one hundred and five CTG traces were analyzed. Of these, 356 fulfilled the criteria for "CTG chorioamnionitis". Higher rates of Apgar <7 at 1 and 5 min (21.6% vs 9.0% and 9.8% vs 2.0%, respectively, P < 0.01 for both) and lower umbilical artery pH (7.14 ± 0.11 vs 7.19 ± 0.11, P < 0.01) and an over fivefold higher rate of neonatal intensive care unit admission (16.6% vs 2.9%, P < 0.01) were noted in the 'CTG chorioamnionitis' group. Differences in the incidence of abnormal CTG patterns were noted between cases who eventually had clinical evidence of chorioamnionitis (89/356) and those showing CTG features suspicious for chorioamnionitis in the absence of clinical evidence of chorioamnionitis (267/356). CONCLUSION: Intrapartum CTG features of suspected chorioamnionitis are associated with adverse perinatal outcomes

Microscopic activity patterns in the Naming Game

The models of statistical physics used to study collective phenomena in some interdisciplinary contexts, such as social dynamics and opinion spreading, do not consider the effects of the memory on individual decision processes. On the contrary, in the Naming Game, a recently proposed model of Language formation, each agent chooses a particular state, or opinion, by means of a memory-based negotiation process, during which a variable number of states is collected and kept in memory. In this perspective, the statistical features of the number of states collected by the agents becomes a relevant quantity to understand the dynamics of the model, and the influence of topological properties on memory-based models. By means of a master equation approach, we analyze the internal agent dynamics of Naming Game in populations embedded on networks, finding that it strongly depends on very general topological properties of the system (e.g. average and fluctuations of the degree). However, the influence of topological properties on the microscopic individual dynamics is a general phenomenon that should characterize all those social interactions that can be modeled by memory-based negotiation processes.Comment: submitted to J. Phys.

Endothelial cell activation by SARS-CoV-2 spike S1 protein: A crosstalk between endothelium and innate immune cells

Background. Emerging evidences suggest that in severe COVID-19, multi-organ failure is associated with a hyperinflammatory state (the so-called “cytokine storm”) in combination with the development of a prothrombotic state. The central role of endothelial dysfunction in the pathogenesis of the disease is to date accepted, but the precise mechanisms underlying the associated coagulopathy remain unclear. Whether the alterations in vascular homeostasis directly depend upon the SARS-CoV-2 infection of endothelial cells or, rather, occur secondarily to the activation of the inflammatory response is still a matter of debate. Here, we address the effect of the SARS-CoV-2 spike S1 protein on the activation of human lung microvascular endothelial cells (HLMVEC). In particular, the existence of an endothelium-macrophage crosstalk in the response to the spike protein has been explored. Methods and Results. The effect of the spike protein is addressed in human lung microvascular endothelial cells (HLMVEC), either directly or after incubation with a conditioned medium (CM) of human monocyte-derived macrophages (MDM) previously activated by the spike S1 protein (CM-MDM). Both MDM and HLMVEC are activated in response to the S1 protein, with an increased expression of pro-inflammatory mediators. However, when HLMVEC are exposed to CM-MDM, an enhanced cell activation occurs in terms of the expression of adhesion molecules, pro-coagulant markers, and chemokines. Under this experimental condition, ICAM-1 and VCAM-1, the chemokines CXCL8/IL-8, CCL2/MCP1, and CXCL10/IP-10 as well as the protein tissue factor (TF) are markedly induced. Instead, a decrease of thrombomodulin (THBD) is observed. Conclusion. Our data suggest that pro-inflammatory mediators released by spike-activated macrophages amplify the activation of endothelial cells, likely contributing to the impairment of vascular integrity and to the development of a pro-coagulative endothelium

Optimality in Self-Organized Molecular Sorting

We introduce a simple physical picture to explain the process of molecular sorting, whereby specific proteins are concentrated and distilled into submicrometric lipid vesicles in eukaryotic cells. To this purpose, we formulate a model based on the coupling of spontaneous molecular aggregation with vesicle nucleation. Its implications are studied by means of a phenomenological theory describing the diffusion of molecules toward multiple sorting centers that grow due to molecule absorption and are extracted when they reach a sufficiently large size. The predictions of the theory are compared with numerical simulations of a lattice-gas realization of the model and with experimental observations. The efficiency of the distillation process is found to be optimal for intermediate aggregation rates, where the density of sorted molecules is minimal and the process obeys simple scaling laws. Quantitative measures of endocytic sorting performed in primary endothelial cells are compatible with the hypothesis that these optimal conditions are realized in living cells