This article presents PANGEA, an agent platform to develop open multiagent systems, specifically those including organizational aspects such as virtual agent organizations. The platform allows the integral management of organizations and offers tools to the end user. Additionally, it includes a communication protocol based on the IRC standard, which facilitates implementation and remains robust even with a large number of connections. The introduction of a CommunicationAgent and a Sniffer make it possible to offer web services for the distributed control of interaction.

MicroRNAs are known to inhibit gene expression by binding to the 3′UTR of the target transcript. Downregulation of miR-223 has been recently reported to have prognostic significance in CLL. However, there is no evidence of the pathogenetic mechanism of this miRNA in CLL patients. By applying next-generation sequencing techniques we have detected a common polymorphism (rs2307842), in 24% of CLL patients, which disrupts the binding site for miR-223 in HSP90B1 3′UTR. We investigated whether miR-223 directly targets HSP90B1 through luciferase assays and ectopic expression of miR-223. Quantitative real-time polymerase chain reaction and western blot were used to determine HSP90B1 expression in CLL patients. The relationship between rs2307842 status, HSP90B1 expression and clinico-biological data were assessed. HSP90B1 is a direct target for miR-223 by interaction with the putative miR-223 binding site. The analysis in paired samples (CD19+ fraction cell and non-CD19+ fraction cell) showed that the presence of rs2307842 and IGHV unmutated genes determined HSP90B1 overexpression in B lymphocytes from CLL patients. These results were confirmed at the protein level by western blot. Of note, HSP90B1 overexpression was independently predictive of shorter time to the first therapy in CLL patients. By contrast, the presence of rs2307842 was not related to the outcome. HSP90B1 is a direct target gene of miR-223. Our results provide a plausible explanation of why CLL patients harboring miR-223 downregulation are associated with a poor outcome, pointing out HSP90B1 as a new pathogenic mechanism in CLL and a promising therapeutic target.

When working in conjunction with multiagent systems, virtual organizations attempt to simulate the functions and interactions of entities in different environments. Recent studies have addressed the problem of assigning roles to agents that form part of the organization, and incorporating new agents to carry out certain tasks. However, these studies are limited to defining the norms and rules that determine the behavior of the organization. The present study proposes a virtual organization model for egovernment environments to assign resources and minimize the required personnel by forecasting workloads. To this end, a neural network, queuing theory, and CBR are used to obtain an efficient distribution. Queuing theory can establish the number of agents with a specific role that are necessary to maximize profits, while the network distributes roles among agents according to their respective efficiency. The final part of the paper is focused on validating the plan developed inside a case study centered on e-government in order to obtain empirical results. (C) 2012 Elsevier Ltd. All rights reserved.

E-healthcare has acquired great importance in recent years and requires the development of innovative solutions. This paper presents a telemonitoring system aimed at enhancing remote healthcare for dependent people at their homes. The system deploys a Service-Oriented Architecture based platform over a heterogeneous Wireless Sensor Networks infrastructure. Furthermore, the information obtained by telemonitoring systems must be managed by intelligent and self-adaptable technologies to provide an adequate interaction between the users and their environment. In the proposed system, the WSNs platform is integrated with a multi-agent architecture so that information gathered by WSN nodes is managed by intelligent agents with reasoning mechanisms.

This paper presents an agent platform called PANGEA (Platform for Automatic construction of orGanizations of intElligent Agents). This platform allows to developed multiagent systems modeled as Virtual Organizations. The concepts of roles, organizations and norms are fully supported by the platform assuring flexibility and scalability. Moreover, a communication protocol based on IRC gives high performance and reliability to this kind of distributed systems.

Currently, the allocation of tasks is a problem in many different areas such as e-Goverment. Traditionally, the assignment is done manually; therefore it is necessary to anticipate workloads and employee characteristics. This article describes a system based on virtual organizations of agents that allows recommendations about planning of tasks to minimize the resources necessary for their accomplishment and to obtain the maximum profit. For this purpose, a hybrid artificial intelligence system with genetic algorithm, queuing theory and case-based reasoning is used to obtain an efficient distribution. The final part of the article is focused on validating the plan developed inside a case of study centered in the e-Government in order to obtain empirical results.