Analysis of the chronic intake of and withdrawal from diazepam on emotional reactivity and sensory information processing in rats

It has been demonstrated that, on abrupt withdrawal, patients with chronic exposure can experience a number of symptoms indicative of a dependent state. In clinical patients, the earliest to arise and most persistent signal of withdrawal from chronic benzodiazepine (Bzp) treatment is anxiety. In laboratory animals, anxiety-like effects following abrupt interruption of chronic Bzp treatment can also be reproduced. In fact, signs that oscillate from irritability to extreme fear behaviours and seizures have been described already. As anxiety remains one of the most important symptoms of Bzp withdrawal, in this study we evaluated the anxiety levels of rats withdrawn from diazepam. Also studied were the effects on the motor performance and preattentive sensory gating process of rats under diazepam chronic treatment and upon 48-h withdrawal on three animal models of anxiety, the elevated plus-maze (EPM), ultrasonic vocalizations (USV) and startle + prepulse inhibition tests. Data obtained showed an anxiolytic- and anxiogenic-like profile of the chronic intake of and withdrawal from diazepam regimen in the EPM test, 22-KHz USV and startle reflex. Diazepam chronic effects or its withdrawal were ineffective in promoting any alteration in the prepulse inhibition (PPI). However, an increase of PPI was achieved in both sucrose and diazepam pretreated rats on 48-h withdrawal, suggesting a procedural rather than a specific effect of withdrawal on sensory gating processes. It is also possible that the prepulse can function as a conditioned stimulus to informing the delivery of an aversive event, as the auditory startling-eliciting stimulus. All these findings are indicative of a sensitization of the neural substrates of aversion in diazepam withdrawn animals without concomitant changes on the processing of sensory information

Stability and convergence analysis of a neural model applied in nonlinear systems optimization

A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

Astrocytes and human cognition: Modeling information integration and modulation of neuronal activity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A disease evolution model with uncertain parameters

In this study we consider the SIS epidemiological model (susceptible-infected-susceptible) in which the transmission and recuperation rates are considered fuzzy sets. The concepts of possibility measures and fuzzy expectancy value are used to obtain the basic reproduction value for infected groups with different viral charge.

Usage of enterprise modeling processes and information systems design to forecast demand

Managing the great complexity of enterprise system, due to entities numbers, decision and process varieties involved to be controlled results in a very hard task because deals with the integration of its operations and its information systems. Moreover, the enterprises find themselves in a constant changing process, reacting in a dynamic and competitive environment where their business processes are constantly altered. The transformation of business processes into models allows to analyze and redefine them. Through computing tools usage it is possible to minimize the cost and risks of an enterprise integration design. This article claims for the necessity of modeling the processes in order to define more precisely the enterprise business requirements and the adequate usage of the modeling methodologies. Following these patterns, the paper concerns the process modeling relative to the domain of demand forecasting as a practical example. The domain of demand forecasting was built based on a theoretical review. The resulting models considered as reference model are transformed into information systems and have the aim to introduce a generic solution and be start point of better practical forecasting. The proposal is to promote the adequacy of the information system to the real needs of an enterprise in order to enable it to obtain and accompany better results, minimizing design errors, time, money and effort. The enterprise processes modeling are obtained with the usage of CIMOSA language and to the support information system it was used the UML language.

Recent advances in brain physiology and cognitive processing

The discovery of participation of astrocytes as active elements in glutamatergic tripartite synapses (composed by functional units of two neurons and one astrocyte) has led to the construction of models of cognitive functioning in the human brain, focusing on associative learning, sensory integration, conscious processing and memory formation/retrieval. We have modelled human cognitive functions by means of an ensemble of functional units (tripartite synapses) connected by gap junctions that link distributed astrocytes, allowing the formation of intra- and intercellular calcium waves that putatively mediate large-scale cognitive information processing. The model contains a diagram of molecular mechanisms present in tripartite synapses and contributes to explain the physiological bases of cognitive functions. It can be potentially expanded to explain emotional functions and psychiatric phenomena. © MSM 2011.

Estatuto biológico do processamento de informação mental

Raciocinando no contexto do programa neomecanicista para a Biologia, estudamos a natureza do processamento de informação no sistema vivo em geral, e no cérebro humano em particular, onde uma aplicação do modelo da Auto-Organização nos conduz à hipótese do Supercódigo. Este seria um programa mental, molecularmente codificado, responsável pelas competências inatas, como a competência lingüística. Fazemos também uma comparação entre nossa hipótese e a da Linguagem do Pensamento, proposta por Jerry Fodor.

Perceptual Information Integration: Hypothetical Role of Astrocytes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

Biomolecular information, brain activity and cognitive functions

Molecular neurobiology has provided an explanation of mechanisms supporting mental functions as learning, memory, emotion and consciousness. However, an explanatory gap remains between two levels of description: molecular mechanisms determining cellular and tissue functions, and cognitive functions. In this paper we review molecular and cellular mechanisms that determine brain activity, and then hypothetize about their relation with cognition and consciousness. The brain is conceived of as a dynamic system that exchanges information with the whole body and the environment. Three explanatory hypotheses are presented, stating that: a) brain tissue function is coordinated by macromolecules controlling ion movements, b) structured (amplitude, frequency and phase-modulated) local field potentials generated by organized ionic movement embody cognitive information patterns, and c) conscious episodes are constructed by a large-scale mechanism that uses oscillatory synchrony to integrate local field patterns. © by São Paulo State University.

PAR-COM: A new methodology for post-processing association rules

The post-processing of association rules is a difficult task, since a huge number of rules that are generated are of no interest to the user. To overcome this problem many approaches have been developed, such as objective measures and clustering. However, objective measures don't reduce nor organize the collection of rules, therefore making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, therefore making the search for relevant knowledge not so easy. In this context this paper presents the PAR-COM methodology that, by combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. An experimental study demonstrates the potential of PAR-COM to minimize the user's effort during the post-processing process. © 2012 Springer-Verlag.

A success in Toxinology translational research in Brazil: Bridging the gap

Basic research is fundamental for discovering potential diagnostic and therapeutic tools, including drugs, vaccines and new diagnostic techniques. On this basis, diagnosis and treatment methods for many diseases have been developed. Presently, discovering new candidate molecules and testing them in animals are relatively easy tasks that require modest resources and responsibility. However, crossing the animal-to-human barrier is still a great challenge that most researchers tend to avoid. Thus, bridging this current gap between clinical and basic research must be encouraged and elucidated in training programmes for health professionals. This project clearly shows the challenges faced by a group of Brazilian researchers who, after discovering a new fibrin sealant through 20 years of painstaking basic work, insisted on having the product applied clinically. The Brazilian government has recently become aware of this challenge and has accordingly defined the product as strategic to the public health of the country. Thus, in addition to financing research and development laboratories, resources were invested in clinical trials and in the development of a virtual platform termed the Virtual System to Support Clinical Research (SAVPC); this platform imparts speed, reliability and visibility to advances in product development, fostering interactions among sponsors, physicians, students and, ultimately, the research subjects themselves. This pioneering project may become a future model for other public institutions in Brazil, principally in overcoming neglected diseases, which unfortunately continue to afflict this tropical country. © 2013 Elsevier Ltd.

Contribuições ao estudo da ambiguidade da linguagem: uma proposta linguístico-educacional

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)