Experimental pig yersiniosis to assess attenuation of Yersinia enterocolitica O:8 mutant strains

An experimental oral pig model was used to assess the pathogenic and immunogenic potential of Yersinia enterocolitica serotype O:8 wild-type strain 8081-L2 and its lipopolysaccharide (LPS) mutant derivatives: a spontaneous rough mutant 8081-R2, strain 8081-DeltawzzGB expressing O-antigen with uncontrolled chain lengths, and strain 8081-wbcEGB expressing semirough LPS with only one O-unit. Microbiological and immunological parameters of the infected pigs were followed from day 7 to 60 postinfection. The wild-type and all LPS mutant strains persisted in the lymphoid tissue of tonsils and small intestines, causing asymptomatic infection without any pathological changes. Although the pig is known as a reservoir of Yersiniae, a precise analysis of pathogenic and immunogenic parameters based on different in vitro tests (hematological response, killing ability of leukocytes and blood sera, antibody response, hydrogen peroxide production by macrophages, classical and alternative pathways of complement activation), revealed significant attenuation in the pathogenicity of the LPS mutant strains but not the loss of immunogenic potential. In comparison with the other strains, strain 8081-DeltawzzGB demonstrated more continuous leucocytosis with monocytosis, higher invasive potential, significant activation of hydrogen peroxide production by macrophages and an effective immunoglobulin G immune response accompanied by relevant histological immunomorphological rearrangements.

Exact and heuristic methods for solving Boolean games

Boolean games are a framework for reasoning about the rational behavior of agents whose goals are formalized using propositional formulas. Compared to normal form games, a well-studied and related game framework, Boolean games allow for an intuitive and more compact representation of the agents’ goals. So far, Boolean games have been mainly studied in the literature from the Knowledge Representation perspective, and less attention has been paid on the algorithmic issues underlying the computation of solution concepts. Although some suggestions for solving specific classes of Boolean games have been made in the literature, there is currently no work available on the practical performance. In this paper, we propose the first technique to solve general Boolean games that does not require an exponential translation to normal-form games. Our method is based on disjunctive answer set programming and computes solutions (equilibria) of arbitrary Boolean games. It can be applied to a wide variety of solution concepts, and can naturally deal with extensions of Boolean games such as constraints and costs. We present detailed experimental results in which we compare the proposed method against a number of existing methods for solving specific classes of Boolean games, as well as adaptations of methods that were initially designed for normal-form games. We found that the heuristic methods that do not require all payoff matrix entries performed well for smaller Boolean games, while our ASP based technique is faster when the problem instances have a higher number of agents or action variables.

Decentralized Computation of Pareto Optimal Pure Nash Equilibria of Boolean Games with Privacy Concerns

In Boolean games, agents try to reach a goal formulated as a Boolean formula. These games are attractive because of their compact representations. However, few methods are available to compute the solutions and they are either limited or do not take privacy or communication concerns into account. In this paper we propose the use of an algorithm related to reinforcement learning to address this problem. Our method is decentralized in the sense that agents try to achieve their goals without knowledge of the other agents’ goals. We prove that this is a sound method to compute a Pareto optimal pure Nash equilibrium for an interesting class of Boolean games. Experimental results are used to investigate the performance of the algorithm.