No abstract

Outer membrane vesicles (OMVs) containing various bacterial compounds are released from mainly gram-negative bacteria. Secreted OMVs play important roles in the ability of a bacterium to defend itself, and thus contribute to the survival of bacteria in a community. In this study, we collected OMVs from β-lactam antibiotic-resistant Escherichia coli established by conjugation assay and the parental β-lactam antibiotic-susceptible strain, and performed comparative proteomic analysis to examine whether these OMVs carried β-lactam-resistant compounds. We also investigated whether both types of OMVs could protect susceptible cells from β-lactam-induced death and/or directly degrade β-lactam antibiotics. Several proteins that can be involved in degrading β-lactam antibiotics were more abundant in OMVs from β-lactam-resistant E. coli, and thus OMVs from β-lactam resistant E. coli could directly and dose-dependently degrade β-lactam antibiotics and fully rescue β-lactam-susceptible E. coli and other bacterial species from β-lactam antibiotic-induced growth inhibition. Taken together, present study demonstrate that OMVs from β-lactam-resistant E. coli play important roles in survival of antibiotic susceptible bacteria against β-lactam antibiotics. This finding may pave the way for new efforts to combat the current global spread of antibiotic resistances, which is considered to be a significant public health threat.

No abstract

Content-centric networking (CCN) is designed for efficient dissemination of information. Several architectures are proposed for CCN recently, but mobility issues are not considered sufficiently. We classify traffic types of CCN into real-time and non real-time. We examine mobility problems for each type, and suggest the possible hand-off schemes over CCN. Then, we analyze the delay performance in terms of simulation study. We believe that the proposed schemes can be merged as a part of the CCN easily, since they comply with the inherent nature and rules of the CCN.

This paper proposes a novel evolutionary algorithm inspired by quantum computing, called a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Like other evolutionary algorithms, QEA is also characterized by the representation of the individual, the evaluation function, and the population dynamics. However, instead of binary, numeric, or symbolic representation, QEA uses a Q-bit, defined as the smallest unit of information, for the probabilistic representation and a Q-bit individual as a string of Q-bits. A Q-gate is introduced as a variation operator to drive the individuals toward better solutions. To demonstrate its effectiveness and applicability, experiments are carried out on the knapsack problem, which is a well-known combinatorial optimization problem. The results show that QEA performs well, even with a small population, without premature convergence as compared to the conventional genetic algorithm.Index Terms-Evolutionary algorithm, knapsack problem, probabilistic representation, quantum computing.