Augmented myocardial methionine-enkephalin in a murine model of cardiac angiotensin II-overexpression.

INTRODUCTION: The endogenous opioid system has been reported to interact with both the cardiac sympathetic and renin-angiotensin systems in exerting a local regulatory action on the heart. The goal of this investigation was to examine how cardiac levels of enkephalin production are altered in the development of normotensive primary hypertrophy due to elevated intra-cardiac angiotensin II (Ang II) production. METHODS: Atrial and ventricular methionine-enkephalin (ME) levels were measured by quantitative radioimmunoassay in 14 and 28-week-old male transgenic mice (TG1306/1R) and control mice. The TG1306/1R exhibit cardiac specific Ang II overexpression and cardiac hypertrophy, but not hypertension. RESULTS: TG1306/1R mice had significantly higher heart/body weight ratios (15-20%) than control littermates at both 14 (p=0.02) and 28 weeks (p=0.04). Relative to controls, ME content was significantly elevated (approximately two-fold) in atria and ventricles in the older 28-week TG1306/1R mice only. A significant inverse correlation between heart size and ME level was observed for 28-week TG1306/1R only. CONCLUSIONS: We have provided evidence that a marked elevation of myocardial enkephalin level is observed in the established (but not early) phase of cardiac hypertrophy associated with cardiac-specific Ang II-overexpression. This study identifies a potentially important relationship between two endogenous peptidergic signalling systems involved in the regulation of growth and function of the hypertrophic heart.

Bristle pattern formation in the thorax formation of Drosophila: a systems level approach

A fundamental question in developmental biology is how tissues are patterned to give rise to differentiated body structures with distinct morphologies. The Drosophila wing disc offers an accessible model to understand epithelial spatial patterning. It has been studied extensively using genetic and molecular approaches. Bristle patterns on the thorax, which arise from the medial part of the wing disc, are a classical model of pattern formation, dependent on a pre-pattern of trans-activators and –repressors. Despite of decades of molecular studies, we still only know a subset of the factors that determine the pre-pattern. We are applying a novel and interdisciplinary approach to predict regulatory interactions in this system. It is based on the description of expression patterns by simple logical relations (addition, subtraction, intersection and union) between simple shapes (graphical primitives). Similarities and relations between primitives have been shown to be predictive of regulatory relationships between the corresponding regulatory factors in other Systems, such as the Drosophila egg. Furthermore, they provide the basis for dynamical models of the bristle-patterning network, which enable us to make even more detailed predictions on gene regulation and expression dynamics. We have obtained a data-set of wing disc expression patterns which we are now processing to obtain average expression patterns for each gene. Through triangulation of the images we can transform the expression patterns into vectors which can easily be analysed by Standard clustering methods. These analyses will allow us to identify primitives and regulatory interactions. We expect to identify new regulatory interactions and to understand the basic Dynamics of the regulatory network responsible for thorax patterning. These results will provide us with a better understanding of the rules governing gene regulatory networks in general, and provide the basis for future studies of the evolution of the thorax-patterning network in particular.

Dialogic learning and interactive groups: an IMS LD template integrated in runtime systems

Dialogic learning and interactive groups have proved to be a useful methodological approach appliedin educational situations for lifelong adult learners. The principles of this approach stress theimportance of dialogue and equal participation also when designing the training activities. This paperadopts these principles as the basis for a configurable template that can be integrated in runtimesystems. The template is formulated as a meta-UoL which can be interpreted by IMS Learning Designplayers. This template serves as a guide to flexibly select and edit the activities at runtime (on the fly).The meta-UoL has been used successfully by a practitioner so as to create a real-life example, withpositive and encouraging results

A new hybrid summarizer based on vector Space model, statistical physics and linguistics

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Not one odour but two: A new model for nestmate recognition.

Recognition systems play a key role in a range of biological processes, including mate choice, immune defence and altruistic behaviour. Social insects provide an excellent model for studying recognition systems because workers need to discriminate between nestmates and non-nestmates, enabling them to direct altruistic behaviour towards closer kin and to repel potential invaders. However, the level of aggression directed towards conspecific intruders can vary enormously, even among workers within the same colony. This is usually attributed to differences in the aggression thresholds of individuals or to workers having different roles within the colony. Recent evidence from the weaver ant Oecophylla smaragdina suggests that this does not tell the whole story. Here I propose a new model for nestmate recognition based on a vector template derived from both the individual's innate odour and the shared colony odour. This model accounts for the recent findings concerning weaver ants, and also provides an alternative explanation for why the level of aggression expressed by a colony decreases as the diversity within the colony increases, even when odour is well-mixed. The model makes additional predictions that are easily tested, and represents a significant advance in our conceptualisation of recognition systems.

It's parties that choose electoral systems (or Duverger's Law upside down)

This article presents, discusses and tests the hypothesis that it is the number of parties what can explain the choice of electoral systems, rather than the other way round. Already existing political parties tend to choose electoral systems that, rather than generate new party systems by themselves, will crystallize, consolidate or reinforce previously existing party configurations. A general model develops the argument and presents the concept of 'behavioral-institutional equilibrium' to account for the relation between electoral systems and party systems. The most comprehensive dataset and test of these notions to date, encompassing 219 elections in 87 countries since the 19th century, are presented. The analysis gives strong support to the hypotheses that political party configurations dominated by a few parties tend to establish majority rule electoral systems, while multiparty systems already existed before the introduction of proportional representation. It also offers the new theoretical proposition that strategic party choice of electoral systems leads to a general trend toward proportional representation over time.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

On the origins of electoral systems and political parties. The role of elections in multi-member districts

The old, understudied electoral system composed of multi-member districts, open ballot and plurality rule is presented as the most remote scene of the origin of both political parties and new electoral systems. A survey of the uses of this set of electoral rules in different parts of the world during remote and recent periods shows its wide spread. A model of voting by this electoral system demonstrates that, while it can produce varied and pluralistic representation, it also provides incentives to form factional or partisan candidacies. Famous negative reactions to the emergence of factions and political parties during the 18th and 19th centuries are reinterpreted in this context. Many electoral rules and procedures invented since the second half of the 19th century, including the Australian ballot, single-member districts, limited and cumulative ballots, and proportional representation rules, derived from the search to reduce the effects of the originating multi-member district system in favor of a single party sweep. The general relations between political parties and electoral systems are restated to account for the foundational stage here discussed.

Multi-period vendor managed inventory systems

In this paper we develop two models for an inventory system in which the distributormanages the inventory at the retailers location. These type of systems correspondto the Vendor Managed Inventory (VMI) systems described ib the literature. Thesesystems are very common in many different types of industries, such as retailingand manufacturing, although assuming different characteristics.The objective of our model is to minimize total inventory cost for the distributorin a multi-period multi-retailer setting. The inventory system includes holdingand stock-out costs and we study the case whre an additional fixed setup cost ischarged per delivery.We construct a numerical experiment to analyze the model bahavior and observe theimpact of the characteristics of the model on the solutions.

A low dimensional Kalman filter for systems with lagged observables

This note describes how the Kalman filter can be modified to allow for thevector of observables to be a function of lagged variables without increasing the dimensionof the state vector in the filter. This is useful in applications where it is desirable to keepthe dimension of the state vector low. The modified filter and accompanying code (whichnests the standard filter) can be used to compute (i) the steady state Kalman filter (ii) thelog likelihood of a parameterized state space model conditional on a history of observables(iii) a smoothed estimate of latent state variables and (iv) a draw from the distribution oflatent states conditional on a history of observables.

Hierarchical location-allocation models for congested systems

In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and theirlocations that will cover a given region with a distance or time standard. The second model is cast as a Maximal Covering Location formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered.

The efficiency of a novel delivery system (PEI600-Tat) in development of potent DNA vaccine using HPV16 E7 as a model antigen.

DNA vaccination is a promising approach for inducing both humoral and cellular immune responses. The mode of plasmid DNA delivery is critical to make progress in DNA vaccination. Using human papillomavirus type 16 E7 as a model antigen, this study evaluated the effect of peptide-polymer hybrid including PEI600-Tat conjugate as a novel gene delivery system on the potency of antigen-specific immunity in mice model. At ratio of 10:50 PEI-Tat/E7DNA (w/w), both humoral and cellular immune responses were significantly enhanced as compared with E7DNA construct and induced Th1 response. Therefore, this new delivery system could have promising applications in gene therapy.

Search for very high energy gamma-ray emission from pulsar-pulsar wind nebula systems with the MAGIC telescope

The MAGIC collaboration has searched for high-energy gamma-ray emission of some of the most promising pulsar candidates above an energy threshold of 50 GeV, an energy not reachable up to now by other ground-based instruments. Neither pulsed nor steady gamma-ray emission has been observed at energies of 100 GeV from the classical radio pulsars PSR J0205+6449 and PSR J2229+6114 (and their nebulae 3C58 and Boomerang, respectively) and the millisecond pulsar PSR J0218+4232. Here, we present the flux upper limits for these sources and discuss their implications in the context of current model predictions.