Immune cells and oxidative stress in the endotoxin tolerance mouse model

Sepsis is a systemic inflammatory response that can lead to tissue damage and death. In order to increase our understanding of sepsis, experimental models are needed that produce relevant immune and inflammatory responses during a septic event. We describe a lipopolysaccharide tolerance mouse model to characterize the cellular and molecular alterations of immune cells during sepsis. The model presents a typical lipopolysaccharide tolerance pattern in which tolerance is related to decreased production and secretion of cytokines after a subsequent exposure to a lethal dose of lipopolysaccharide. The initial lipopolysaccharide exposure also altered the expression patterns of cytokines and was followed by an 8- and a 1.5-fold increase in the T helper 1 and 2 cell subpopulations. Behavioral data indicate a decrease in spontaneous activity and an increase in body temperature following exposure to lipopolysaccharide. In contrast, tolerant animals maintained production of reactive oxygen species and nitric oxide when terminally challenged by cecal ligation and puncture (CLP). Survival study after CLP showed protection in tolerant compared to naive animals. Spleen mass increased in tolerant animals followed by increases of B lymphocytes and subpopulation Th1 cells. An increase in the number of stem cells was found in spleen and bone marrow. We also showed that administration of spleen or bone marrow cells from tolerant to naive animals transfers the acquired resistance status. In conclusion, lipopolysaccharide tolerance is a natural reprogramming of the immune system that increases the number of immune cells, particularly T helper 1 cells, and does not reduce oxidative stress.

Model-based testing of software systems : functionality and performance

Software is a key component in many of our devices and products that we use every day. Most customers demand not only that their devices should function as expected but also that the software should be of high quality, reliable, fault tolerant, efficient, etc. In short, it is not enough that a calculator gives the correct result of a calculation, we want the result instantly, in the right form, with minimal use of battery, etc. One of the key aspects for succeeding in today's industry is delivering high quality. In most software development projects, high-quality software is achieved by rigorous testing and good quality assurance practices. However, today, customers are asking for these high quality software products at an ever-increasing pace. This leaves the companies with less time for development. Software testing is an expensive activity, because it requires much manual work. Testing, debugging, and verification are estimated to consume 50 to 75 per cent of the total development cost of complex software projects. Further, the most expensive software defects are those which have to be fixed after the product is released. One of the main challenges in software development is reducing the associated cost and time of software testing without sacrificing the quality of the developed software. It is often not enough to only demonstrate that a piece of software is functioning correctly. Usually, many other aspects of the software, such as performance, security, scalability, usability, etc., need also to be verified. Testing these aspects of the software is traditionally referred to as nonfunctional testing. One of the major challenges with non-functional testing is that it is usually carried out at the end of the software development process when most of the functionality is implemented. This is due to the fact that non-functional aspects, such as performance or security, apply to the software as a whole. In this thesis, we study the use of model-based testing. We present approaches to automatically generate tests from behavioral models for solving some of these challenges. We show that model-based testing is not only applicable to functional testing but also to non-functional testing. In its simplest form, performance testing is performed by executing multiple test sequences at once while observing the software in terms of responsiveness and stability, rather than the output. The main contribution of the thesis is a coherent model-based testing approach for testing functional and performance related issues in software systems. We show how we go from system models, expressed in the Unified Modeling Language, to test cases and back to models again. The system requirements are traced throughout the entire testing process. Requirements traceability facilitates finding faults in the design and implementation of the software. In the research field of model-based testing, many new proposed approaches suffer from poor or the lack of tool support. Therefore, the second contribution of this thesis is proper tool support for the proposed approach that is integrated with leading industry tools. We o er independent tools, tools that are integrated with other industry leading tools, and complete tool-chains when necessary. Many model-based testing approaches proposed by the research community suffer from poor empirical validation in an industrial context. In order to demonstrate the applicability of our proposed approach, we apply our research to several systems, including industrial ones.

Warfarin-induced vitamin K deficiency is associated with cognitive and behavioral perturbations, and alterations in brain sphingolipids in rats

La Vitamine K (VK) est largement reconnue pour son rôle dans la coagulation sanguine toutefois, de plus en plus de travaux indiquent son implication dans la fonction cérébrale. La VK est requise pour l'activation de différentes protéines, par exemple la protéine Gas6, et la ménaquinone-4 (MK-4), le principal vitamère K dans le cerveau, est impliquée dans le métabolisme des sphingolipides. Dans un rapport précédent, nous avons montré qu'un régime alimentaire faible en VK tout au long de la vie était associé à des déficits cognitifs chez des rats âgés. La warfarine sodique est un puissant antagoniste de la VK qui agit en bloquant le cycle de la VK, provoquant un «déficit relatif de VK » au niveau cellulaire. À la lumière du rôle émergent de la VK dans le cerveau, la warfarine pourrait représenter un facteur de risque pour la fonction cérébrale. Ce travail est donc pertinente en raison de la forte proportion d'adultes traîtés à la warfarine sodique. Dans la présente étude, 14 rats mâles Wistar ont été traités avec 14 mg de warfarine/kg /jour (dans l'eau potable) et des injections sous-cutanées de VK (85 mg/kg), 3x/sem, pendant 10 semaines. Quatorze rats témoins ont été traités avec de l'eau normale et injectés avec une solution saline. Les rats ont été soumis à différents tests comportementaux après quoi les niveaux de phylloquinone, MK-4, sphingolipides (cérébroside, sulfatide, sphingomyéline, céramide et gangliosides), et les sous-types de gangliosides (GT1b, GD1a, GM1, GD1b), ont été évalués dans différentes régions du cerveau. Comparativement aux rats du groupe contrôle, les rats traités à la warfarine présentaient des latences plus longues au test de la piscine de Morris (p <0,05) ainsi qu'une hypoactivité et un comportement exploratoire plus faible au test de « l’open field » (p <0,05). Le traitement par warfarine a également entraîné une diminution spectaculaire du niveau de MK-4 dans toutes les régions du cerveau (p <0,001), une altération des concentrations de sphingolipidiques, en particulier dans le cortex frontal et le mésencéphale (p <0,05), et une perte de différences régionales sphingolipidiques, notamment pour les gangliosides. Le traitement par warfarine a été associé à un niveau inférieur de GD1a dans l'hippocampe et un niveau supérieur de GT1b dans le cortex préfrontal et le striatum. En conclusion, la déficience en VK induite par warfarine altère les niveaux de VK et sphingolipides dans le cerveau, avec de potentiels effets néfastes sur les fonctions cérébrales.

CAPM und Behavioral Finance - Versuch einer Synthese

Seit Etablierung der ersten Börsen als Marktplatz für fungible Güter sind Marktteilnehmer und die Wissenschaft bemüht, Erklärungen für das Zustandekommen von Marktpreisen zu finden. Im Laufe der Zeit wurden diverse Modelle entwickelt. Allen voran ist das neoklassische Capital Asset Pricing Modell (CAPM) zu nennen. Die Neoklassik sieht den Akteur an den Finanzmärkten als emotionslosen und streng rationalen Entscheider, dem sog. homo oeconomicus. Psychologische Einflussfaktoren bei der Preisbildung bleiben unbeachtet. Mit der Behavioral Finance hat sich ein neuer Zweig zur Erklärung von Börsenkursen und deren Bewegungen entwickelt. Die Behavioral Finance sprengt die enge Sichtweise der Neoklassik und geht davon aus, dass psychologische Effekte die Entscheidung der Finanzakteure beeinflussen und dabei zu teilweise irrational und emotional geprägten Kursänderungen führen. Eines der Hauptprobleme der Behavioral Finance liegt allerdings in der fehlenden formellen Ermittelbarkeit und Testbarkeit der einzelnen psychologischen Effekte. Anders als beim CAPM, wo die einzelnen Parameter klar mathematisch bestimmbar sind, besteht die Behavioral Finance im Wesentlichen aus psychologischen Definitionen von kursbeeinflussenden Effekten. Die genaue Wirkrichtung und Intensität der Effekte kann, mangels geeigneter Modelle, nicht ermittelt werden. Ziel der Arbeit ist es, eine Abwandlung des CAPM zu ermitteln, die es ermöglicht, neoklassische Annahmen durch die Erkenntnisse des Behavioral Finance zu ergänzen. Mittels der technischen Analyse von Marktpreisen wird versucht die Effekte der Behavioral Finance formell darstellbar und berechenbar zu machen. Von Praktikern wird die technische Analyse dazu verwendet, aus Kursverläufen die Stimmungen und Intentionen der Marktteilnehmer abzuleiten. Eine wissenschaftliche Fundierung ist bislang unterblieben. Ausgehend von den Erkenntnissen der Behavioral Finance und der technischen Analyse wird das klassische CAPM um psychologische Faktoren ergänzt, indem ein Multi-Beta-CAPM (Behavioral-Finance-CAPM) definiert wird, in das psychologisch fundierte Parameter der technischen Analyse einfließen. In Anlehnung an den CAPM-Test von FAMA und FRENCH (1992) werden das klassische CAPM und das Behavioral-Finance-CAPM getestet und der psychologische Erklärungsgehalt der technischen Analyse untersucht. Im Untersuchungszeitraum kann dem Behavioral-Finance-CAPM ein deutlich höherer Erklärungsgehalt gegenüber dem klassischen CAPM zugesprochen werden.

Some theoretical and methodological considerations for the development of a critical competences model (CCM): an operant approach

This paper develops some theoretical and methodological considerations for the development of a critical competence model (CCM). The model is defined as a set of skills and knowledge functionally organized allowing measurable results with positive consequences for the strategic business objectives. The theoretical approaches of classical model of competences, the contemporary model of competencies and human competencies model were revised for the proposal development. implementation of the model includes 5 steps: 1) conducting a job analysis considering which dimensions or facets are subject to revision, 2) identify people with the opposite performance (the higher performance and lower performance); 3) identify critical incidents most relevant to the job position, 4) develop behavioral expectation scales (bes) and 5) validate BES obtained for experts in the field. As a final consideration, is determined that the competence models require accurate measurement. Approaches considering excessive theoreticism may cause the issue of competence become a fashion business with low or minimal impact, affecting its validity, reliability and deployment in organizations.

Behavioral differences in violence: the case of intra-group differences of paramilitaries and guerrillas in Colombia

In most studies on civil wars, determinants of conflict have been hitherto explored assuming that actors involved were either unitary or stable. However, if this intra-group homogeneity assumption does not hold, empirical econometric estimates may be biased. We use Fixed Effects Finite Mixture Model (FE-FMM) approach to address this issue that provides a representation of heterogeneity when data originate from different latent classes and the affiliation is unknown. It allows to identify sub-populations within a population as well as the determinants of their behaviors. By combining various data sources for the period 2000-2005, we apply this methodology to the Colombian conflict. Our results highlight a behavioral heterogeneity in guerrilla’s armed groups and their distinct economic correlates. By contrast paramilitaries behave as a rather homogenous group.

Understanding Demographic and Behavioral Mechanisms that Guide Responses of Neotropical Migratory Birds to Urbanization: a Simulation Approach

Although studies often report that densities of many forest birds are negatively related to urbanization, the mechanisms guiding this pattern are poorly understood. Our objective was to use a population simulation to examine the relative influence of six demographic and behavioral processes on patterns of avian abundance in urbanizing landscapes. We constructed an individual-based population simulation model representing the annual cycle of a Neotropical migratory songbird. Each simulation was performed under two landscape scenarios. The first scenario had similar proportions of high- and low-quality habitat across the urban to rural gradient. Under the first scenario, avian density was negatively related to urbanization only when rural habitats were perceived to be of higher quality than they actually were. The second landscape scenario had declining proportions of high-quality habitat as urbanization increased. Under the second scenario, each mechanism generated a negative relationship between density and urbanization. The strongest effect on density resulted when birds preferentially selected habitats in landscapes from which they fledged or were constrained from dispersing. The next strongest patterns occurred when birds directly evaluated habitat quality and accurately selected the highest-quality available territories. When birds selected habitats based on the presence of conspecifics, the density–urbanization relationship was only one-third the strength of other habitat selection mechanisms and only occurred under certain levels of population survival. Although differences in adult or nest survival in the face of random habitat selection still elicited reduced densities in urban landscapes, the relationships between urbanization and density were weaker than those produced by the conspecific attraction mechanism. Results from our study identify key predictions and areas for future research, including assessing habitat quality in urban and rural areas in order to determine if habitats in urban areas are underutilized.

Eyes, amygdala, and other models of face processing: Questions for the SIMS model

This commentary raises general questions about the parsimony and generalizability of the SIMS model, before interrogating the specific roles that the amygdala and eye contact play in it. Additionally, this situates the SIMS model alongside another model of facial expression processing, with a view to incorporating individual differences in emotion perception.

Experimental analysis of the Reynolds flocking model

The classic Reynolds flocking model is formally analysed, with results presented and discussed. Flocking behaviour was investigated through the development of two measurements of flocking, flock area and polarisation, with a view to applying the findings to robotic applications. Experiments varying the flocking simulation parameters individually and simultaneously provide new insight into the control of flock behaviour.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Is behavioral ecology important for understanding and predicting population dynamics?

Population ecology is a discipline that studies changes in the number and composition (age, sex) of the individuals that form a population. Many of the mechanisms that generate these changes are associated with individual behavior, for example how individuals defend their territories, find mates or disperse. Therefore, it is important to model population dynamics considering the potential influence of behavior on the modeled dynamics. This study illustrates the diversity of behaviors that influence population dynamics describing several methods that allow integrating behavior into population models and range from simpler models that only consider the number of individuals to complex individual-based models that capture great levels of detail. A series of examples shows the importance of explicitly considering behavior in population modeling to avoid reaching erroneous conclusions. This integration is particularly relevant for conservation, as incorrect predictions regarding the dynamics of populations of conservation interest can lead to inadequate assessment and management. Improved predictions can favor effective protection of species and better use of the limited financial and human conservation resources.

Temporal lobe epilepsy and social behavior: An animal model

Social behavior depends on the integrity of social brain circuitry. The temporal lobe is an important part of the social brain, and manifests morphological and functional alterations in autism spectrum disorders (ASD). Rats with temporal lobe epilepsy (TLE), induced with pilocarpine, were subjected to a social discrimination test that has been used to investigate potential animal models of ASD, and the results were compared with those for the control group. Rats with TLE exhibited fewer social behaviors than controls. No differences were observed in nonsocial behavior between groups. The results suggest an important role for the temporal lobe in regulating social behaviors. This animal model might be used to explore some questions about ASD pathophysiology. (c) 2008 Elsevier Inc. All rights reserved.

Bayesian Estimation of the Logistic Positive Exponent IRT Model

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric ICC treats both correct and incorrect answers symmetrically, which results in a logical contradiction in ordering examinees on the ability scale. A data set corresponding to a mathematical test applied in Peruvian public schools is analyzed, where comparisons with other parametric IRT models also are conducted. Several model comparison criteria are discussed and implemented. The main conclusion is that the LPE and RLPE IRT models are easy to implement and seem to provide the best fit to the data set considered.

Investigating the Effects of Mifepristone (RU486) in the Behavioral, Hormonal and Central Responses to Acute Stress

Depression is associated with glucocorticoid hypersecretion, due to dysfunction of the hypothalamo-pituitary-adrenocorticol axis (HPA-axis). Because excess glucocorticoids are associated with depressive-like features in humans, glucocorticoid receptor antagonists are currently being tested for antidepressant efficacy in clinical trials. In the current study the hypothesis that mifepristone (RU486), a glucocorticoid receptor antagonist, would decrease the neuroendocrine and central HPA-axis responses to an acute stressor and attentuate depressive like behavior in an animal model of behavioral helplessness (forced swim test) was tested. Adult male rats were treated with 10 mglkg RU486 (subcutaneous) for five days and then exposed to a IO-minute forced swim test (FST), conducted in Plexiglas cylinders. FST sessions were videotaped for later analysis of behavioral immobility. Plasma ACTH and corticosterone CORT were measured at 15min and 90min after FST cessation. Animals were perfused and brains were collected for immunocytochemical assessment of c-Fos expression in the medial prefrontal cortex (mPFC), a brain region implicated in both depression and central control of the HPA axis. RU486 significantly decreased peak ACTH and CORT concentrations following FST exposure. In addition, glucocorticoid negative feedback was at1enuated in RU486-treated animals exposed to the FST. Exposure to FST alone induced c-FOS expression in the mPFC, as measured by the number of c-Fos positive neurons. Treatment with RU486 significantly increased the number of rnPFC c-Fos positive cell following FST exposure. The behavioral data obtained from FST paradigm, demonstrated that RU486 decreased immobility in the FST illustrating the potential efficacy of this drug as an antidepressant. Collectively these data suggest that RU486 dampens HPA-axis responses to stress, possibly by enhancing the excitability of stress-inhibitory neurons in the mPFC. This is particularly exciting, given the fact that this neural region is associated with decreased neural activity during depression in humans.