To investigate the exact effects of different origins of Newcastle disease virus (NDV) hemagglutinin-neuraminidase (HN) protein to the biological characteristics of the virus, we systematically studied the correlation between the HN protein and NDV virulence by exchanging the HN of velogenic or lentogenic NDV strains with the HN from other strains of different virulence. The results revealed that the rSG10 or rLaSota derivatives bearing the HN gene of other viruses exhibited decreased or increased hemadsorption (HAd), neuraminidase and fusion promotion activities. In vitro and in vivo tests further showed that changes in replication level, tissue tropism and virulence of the chimeric viruses were also consistent with these biological activities. These findings demonstrated that the balance among three biological activities caused variation in replication and pathogenicity of the virus, which was closely related to the origin of the HN protein. Our study highlights the importance of the HN glycoprotein in modulating the virulence of NDV and contributes to a more complete understanding of the virulence of NDV.

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Summary Agent-based Evolutionary Search (AES) has attracted a growing interest from the evolutionary computation community in recent years due to its robust ability in solving large scale problems, ranging from online trading, disaster response, modeling social structures to financial investment planning. In order to solve these problems, a great variety of intelligent techniques have been developed to improve the framework and efficiency of AES. This chapter investigates an agent based evolutionary search algorithm in which the agents are updated and co-evolve to track dynamic optimum by imitating the exhibited feature of living organism. In the proposed algorithm, all agents live in a lattice like environment, where each agent is fixed on a lattice point. In order to increase the predefined energy function, individual agent can compete with its neighbors and also can acquire knowledge through cumulative information. For the purpose of maintaining the diversity of the population, random immigrants and adaptive primal dual mapping schemes are incorporated. Simulation experiments on a set of dynamic benchmark problems show the proposed AES algorithm can yield a better performance on dynamic optimization problems (DOPs) in comparison with several peer algorithms.

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