DNA-based analysis of protein variants reveals different genetic variability of the paralogous equine ß-lactoglobulin genes LGB1 and LGB2

The genetic variability of milk protein genes may influence the nutritive value or processing and functional properties of the milk. While numerous protein variants are known in ruminants, knowledge about milk protein variability in horses is still limited. Mare's milk is, however, produced for human consumption in many countries. Beta-lactoglobulin belonging to the protein family of lipocalins, which are known as common food- and airborne allergens, is a major whey protein. It is absent from human milk and thus a key agent in provoking cow's milk protein allergy. Mare's milk is, however, usually better tolerated by most affected people. Several functions of β-lactoglobulin have been discussed, but its ultimate physiological role remains unclear. In the current study, the open reading frames of the two equine β-lactoglobulin paralogues LGB1 and LGB2 were re-sequenced in 249 horses belonging to 14 different breeds in order to predict the existence of protein variants at the DNA-level. Thereby, only a single signal peptide variant of LGB1, but 10 different putative protein variants of LGB2 were identified. In horses, both genes are expressed and in such this is a striking previously unknown difference in genetic variability between the two genes. It can be assumed that LGB1 is the ancestral paralogue, which has an essential function causing a high selection pressure. As horses have very low milk fat content this unknown function might well be related to vitamin-uptake. Further studies are, however, needed, to elucidate the properties of the different gene products.

STAT3 activation by the ErbB2 receptor and development of peptide-based STAT3 inhibitors

Stats (s&barbelow;ignal t&barbelow;ransducer and a&barbelow;ctivator of t&barbelow;ranscription) are latent transcription factors that translocate from the cytoplasm to nucleus. Constitutive activation of Stat3α by upstream oncoproteins and receptor tyrosine kinases has been found in many human tumors and tumor-derived cell lines and it is often correlated with the activation of ErbB-2. In order to explore the involvement of ErbB-2 in the activation of Stat3 and the mechanisms underlying this event, an erbB-2 point mutant was used as a model of a constitutively activated receptor. Phenylalanine mutations (Y-F) were made in the receptor's autophosphorylation sites and their ability to activate Stat3α was evaluated. Our results suggest that Stat3α and Janus tyrosine kinase 2 associates with ErbB-2 prior to tyrosine phosphorylation of the receptor and that full activation of Stat3α by ErbB-2 requires the participation of other non-receptor tyrosine kinases. Both Src and Jak2 kinases contribute to the activation of Stat3α while only Src binds to ErbB-2 only when the receptor is tyrosine phosphorylated. Our results also suggest that tyrosine 1139 may be important for Src SH2 domain association since a mutant lacking this tyrosine reduces the ability of the Src SH2 domain to bind to ErbB-2 and significantly decreases its ability to activate Stat3α. ^ In order to disrupt aberrant STAT3α activation which contributes to tumorigenesis, we sought small molecules which can specifically bind to the STAT3 SH2 domain, thereby abolishing its ability of being recruited into receptors, and also blocking the dimer formation required for STAT3α activation. A phosphopeptide derived from gp130 was found to have a high affinity to STAT3 SH2 domain, and we decided to use this peptide as the base for further modifications. A series of peptide based compounds were designed and tested using electrophoretic mobility shift assay and fluorescence polarization assay to evaluate their affinity to the STAT3 SH2 domain. Two promising compounds, DRIV-73C and BisPOM, were used for blocking STAT3α activity in cell culture. Either can successfully impair STAT3α activation induced by IL-6 stimulation in HepG2 cells. BisPOM proved to be the more effective in blocking STAT3α tyrosine phosphorylation in induced cells and tumor cell lines, and was the more potent in inhibiting STAT3 dependent cell growth. ^

OXIDATIVE STRESS BASED STRATEGIES FOR ENHANCING THE EFFICACY OF HISTONE DEACETYLASE INHIBITORS (HDACi)

Histone deacetylase inhibitors (HDACi) are anti-cancer drugs that primarily act upon acetylation of histones, however they also increase levels of intracellular reactive oxygen species (ROS). We hypothesized that agents that cause oxidative stress might enhance the efficacy of HDACi. To test this hypothesis, we treated acute lymphocytic leukemia cells (ALL) with HDACi and adaphostin (ROS generating agent). The combination of two different HDACi (vorinostat or entinostat) with adaphostin synergistically induced apoptosis in ALL. This synergistic effect was blocked when cells were pre-treated with the caspase-9 inhibitor, LEHD. In addition, we showed that loss of the mitochondrial membrane potential is the earliest event observed starting at 12 h. Following this event, we observed increased levels of superoxide at 16 h, and ultimately caspase-3 activation. Pre-treatment with the antioxidant N-acetylcysteine (NAC) blocked ROS generation and reversed the loss of mitochondrial membrane potential for both combinations. Interestingly, DNA fragmentation and caspase-3 activity was only blocked by NAC in cells treated with vorinostat-adaphostin; but not with entinostat-adaphostin. These results suggest that different redox mechanisms are involved in the induction of ROS-mediated apoptosis. To further understand these events, we studied the role of the antioxidants glutathione (GSH) and thioredoxin (Trx). We found that the combination of entinostat-adaphostin induced acetylation of the antioxidant thioredoxin (Trx) and decreased intracellular levels of GSH. However, no effect on Trx activity was observed in either combination. In addition, pre-treatment with GSH ethyl ester, a soluble form of GSH, did not block DNA fragmentation. Together these results suggested that GSH and Trx are not major players in the induction of oxidative stress. Array data examining the expression of genes involved in oxidative stress demonstrated a differential regulation between cells treated with vorinostat-adaphostin and entinostat-adaphostin. Some of the genes differentially expressed between the combinations include aldehyde oxidase 1, glutathione peroxidase-5, -6, peroxiredoxin 6 and myeloperoxidase. Taken together, these experimental results indicate that the synergistic activity of two different HDACi with adaphostin is mediated by distinct redox mechanisms in ALL cells. Understanding the mechanism involved in these combinations will advance scientific knowledge of how the action of HDACi could be augmented in leukemia models. Moreover, this information could be used for the development of effective clinical trials combining HDACi with other anticancer agents.

A Model-Based Monitoring Architecture for Heterogeneous Enterprise Services and Information Systems

Runtime management of distributed information systems is a complex and costly activity. One of the main challenges that must be addressed is obtaining a complete and updated view of all the managed runtime resources. This article presents a monitoring architecture for heterogeneous and distributed information systems. It is composed of two elements: an information model and an agent infrastructure. The model negates the complexity and variability of these systems and enables the abstraction over non-relevant details. The infrastructure uses this information model to monitor and manage the modeled environment, performing and detecting changes in execution time. The agents infrastructure is further detailed and its components and the relationships between them are explained. Moreover, the proposal is validated through a set of agents that instrument the JEE Glassfish application server, paying special attention to support distributed configuration scenarios.

Multi-agent Architecture for Heterogeneous Reasoning under Uncertainty Combining MSBN and Ontologies in Distributed Network Diagnosis

This article proposes a MAS architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypothesis generation and hypothesis confirmation. The first process is distributed among several agents based on a MSBN, while the second one is carried out by agents using semantic reasoning. A diagnosis ontology has been defined in order to combine both inference processes. To drive the deliberation process, dynamic data about the influence of observations are taken during diagnosis process. In order to achieve quick and reliable diagnoses, this influence is used to choose the best action to perform. This approach has been evaluated in a P2P video streaming scenario. Computational and time improvements are highlight as conclusions.

Games based learning for Exploring Cultural Conflict

In this paper we discuss the early stage design of MIXER, a technology enhance educational application focused at supporting children in learning about cultural conflict, achieved through the use of a game with an effective embodied AI agent. MIXER is being developed re-using existing technology applied to a different context and purpose with the aim of creating an educational and enjoyable experience for 9-11 year olds. This paper outlines MIXER’s underpinning technology and theory. It presents early stage design and development, highlighting current research directions.

A Multi-agent System for Emergency Decision Support

This paper describes the multi-agent organization of a computer system that was designed to assist operators in decision making in the presence of emergencies. The application was developed for the case of emergencies caused by river floods. It operates on real-time receiving data recorded by sensors (rainfall, water levels, flows, etc.) and applies multi-agent techniques to interpret the data, predict the future behavior and recommend control actions. The system includes an advanced knowledge based architecture with multiple symbolic representation with uncertainty models (bayesian networks). This system has been applied and validated at two particular sites in Spain (the Jucar basin and the South basin).

Engineering Agent Systems for Decision Support

This paper discusses how agent technology can be applied to the design of advanced Information Systems for Decision Support. In particular, it describes the different steps and models that are necessary to engineer Decision Support Systems based on a multiagent architecture. The approach is illustrated by a case study in the traffic management domain.

A Satisfaction-based Model for Affect Recognition from Conversational Features in Spoken Dialog Systems

Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

Behaviour Driven Development for Multi-Agent Systems

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MAS), so called BEhavioural Agent Simple Testing (BEAST) methodology. It is supported by the developed open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios specifications. The developed framework allows testing MASs based on JADE or JADEX platforms and offers a set of configurable Mock Agents which allow the execution of tests while the system is under development. BEAST tool has been validated in the development of a MAS for fault diagnosis in FTTH (Fiber To The Home) networks.

An Agent Architecture to fulfill Real-Time Requirements

In this paper we present AMSIA, an agent architecture that combines the possibility of using di erent reasoning methods with a mechanism to control the resources needed by the agent to ful ll its high level objectives. The architecture is based on the blackboard paradigm which o ers the possibility of combining di erent reasoning techniques and opportunistic behavior. The AMSIA architecture adds a representation of plans of objectives allowing di erent reasoning activities to create plans to guide the future behavior of the agent. The opportunism is in the acquisition of high-level objectives and in the modi cation of the predicted activity when something doesn't happen as expected. A control mechanism is responsible for the translation of plans of objectives to concrete activities, considering resource-boundedness. To do so, all the activity in the agent (including control) is explicitly scheduled, but allowing the necessary exibility to make changes in the face of contingencies that are expected in dynamic environments. Experimental work is also presented.

Multi-agent location system in wireless networks

In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks. The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization. The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer. In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building. Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room.

Application of the agency theory for the analysis of performance-based mechanisms in road management

El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte, y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper develops a model based on agency theory to analyze road management systems (under the different contract forms available today) that employ a mechanism of performance indicators to establish the payment of the agent. The base assumption is that of asymmetric information between the principal (Public Authorities) and the agent (contractor) and the risk aversion of this latter. It is assumed that the principal may only measure the agent?s performance indirectly and by means of certain performance indicators that may be verified by the authorities. In this model there is presumed to be a relation between the efforts made by the agent and the performance level measured by the corresponding indicators, though it is also considered that there may be dispersion between both variables that gives rise to a certain degree of randomness in the contract. An analysis of the optimal contract has been made on the basis of this model and in accordance with a series of parameters that characterize the economic environment and the particular conditions of road infrastructure. As a result of the analysis made, it is considered that an optimal contract should generally combine a fixed component and a payment in accordance with the performance level obtained. The higher the risk aversion of the agent and the greater the marginal cost of public funds, the lower the impact of this performance-based payment. By way of conclusion, the system of performance indicators should be as broad as possible but should not overweight those indicators that encompass greater randomness in their results.

MAIA: an event-based modular architecture for intelligent agents

Online services are no longer isolated. The release of public APIs and technologies such as web hooks are allowing users and developers to access their information easily. Intelligent agents could use this information to provide a better user experience across services, connecting services with smart automatic. behaviours or actions. However, agent platforms are not prepared to easily add external sources such as web services, which hinders the usage of agents in the so-called Evented or Live Web. As a solution, this paper introduces an event-based architecture for agent systems, in accordance with the new tendencies in web programming. In particular, it is focused on personal agents that interact with several web services. With this architecture, called MAIA, connecting to new web services does not involve any modification in the platform.

Thermoplastic Polymer Nanocomposites Based on Inorganic Fullerene-like Nanoparticles and Inorganic Nanotubes

Using inorganic fullerene-like (IF) nanoparticles and inorganic nanotubes (INT) in organic-inorganic hybrid composite, materials provide the potential for improving thermal, mechanical, and tribological properties of conventional composites. The processing of such high-performance hybrid thermoplastic polymer nanocomposites is achieved via melt-blending without the aid of any modifier or compatibilizing agent. The incorporation of small quantities (0.1-4 wt.%) of IF/INTs (tungsten disulfide, IF-WS2 or molybdenum disulfide, MoS2) generates notable performance enhancements through reinforcement effects and excellent lubricating ability in comparison with promising carbon nanotubes or other inorganic nanoscale fillers. It was shown that these IF/INT nanocomposites can provide an effective balance between performance, cost effectiveness, and processability, which is of significant importance for extending the practical applications of diverse hierarchical thermoplastic-based composites.