The prima donna of epigenetics: the regulation of gene expression by DNA methylation

This review focuses on the mechanisms of DNA methylation, DNA methylation pattern formation and their involvement in gene regulation. Association of DNA methylation with imprinting, embryonic development and human diseases is discussed. Furthermore, besides considering changes in DNA methylation as mechanisms of disease, the role of epigenetics in general and DNA methylation in particular in transgenerational carcinogenesis, in memory formation and behavior establishment are brought about as mechanisms based on the cellular memory of gene expression patterns.

Transfection of newt blastema mesenchyme using the techniques of lipofection and direct gene transfer

The regenerating amphibian limb provides a useful system for studying genes involved in the establishment of positional information. While a number of candidate genes that may playa role in pattern formation have been identified, their function in vivo is unknown in this system. To better ascertain the role of these genes, it would be useful to be able to alter their normal patterns of expression in vivo and to assess the effects of this misexpression on limb pattern. In order to achieve this, a method of introducing a plasmid containing the eDNA of a gene of interest into a newt blastema (a growth zone of mesenchymal progenitor cells) is needed. Unfortunately, most commonly used transfection techniques cannot be used with newt blastema cells. In this study, I have used the techniques of lipofection and direct gene transfer to introduce plasmid DNA containing reporter genes into the cells of a regenerating newt limb. The technique of lipofection was most effective when the blastema cells were transfected in vitro. The optimal ratio for transfection was shown to be 1:3 DNA:Lipofectin (W/w) , and an increase in the amount of DNA present in the mixture (1:3 ratio maintained) resulted in a corresponding increase in gene expression. The technique of direct gene transfer was used to transfect newt blastema cells with and without prior complex formation with Lipofectin. Injection of plasmid DNA alone provided the most 3 promising results. It was possible to introduce plasmid DNA containing the reporter gene ~-galactosidase and achieve significant gene expression in cells associated with the injection site. In the future, it would be interesting to use this technique to inject plasmid DNA containing a gene which may have a role in pattern formation into specific areas of the newt blastema and to analyze the resulting limb pattern that emerges.

Analyse fonctionnelle du gène BMP-2 lors de la régénération du membre chez l’axolotl

Les amphibiens urodèles (e.g. les axolotls) possèdent la remarquable capacité de régénérer plusieurs parties de leur corps. Ils peuvent, entre autres, régénérer parfaitement un membre amputé par épimorphose, un processus biphasique comprenant une phase de préparation, spécifique à la régénération, et une phase de redéveloppement, commune à l’épimorphose et au développement embryonnaire. Durant la phase de préparation, les cellules du moignon se dédifférencient en cellules pseudo-embryonnaires, prolifèrent et migrent distalement au plan d’amputation pour former un blastème de régénération. Parmi les vertébrés, la dédifférenciation est unique aux urodèles. Afin de mieux comprendre le contrôle moléculaire de la régénération chez les urodèles, nous avons choisi d’étudier BMP-2, un facteur de croissance, en raison de son implication dans la régénération des phalanges distales chez les mammifères. Le facteur de transcription MSX-1 a également été sélectionné en raison de sa capacité à induire la dédifférenciation cellulaire in vitro et de son interaction potentielle avec la signalisation des BMPs. Les résultats présentés dans cette thèse démontrent que BMP-2 et MSX-1 sont exprimés lors des phases de préparation et de redéveloppement de l’épimorphose, et que leur profil d'expression spatio-temporel est très semblable, ce qui suggère une interaction de leurs signaux. En outre, chez les tétrapodes amniotes, l’expression de Shh est restreinte au mésenchyme postérieur des membres en développement et chevauche l’expression de BMP-2. Toutefois, l’expression de BMP-2 n’est pas restreinte à la région postérieure mais forme un gradient postéro-antérieur. Shh est le principal régulateur de la formation du patron de développement antéro-postérieur du ii membre. Étant donné les domaines d’expression chevauchants de BMP-2 et Shh et la restriction postérieure d’expression de Shh, on croit que Shh régule la formation du patron de développement de postérieur à antérieur par l’activation de l’expression de BMP-2. Fait intéressant, l’axolotl exprime également Shh dans la région postérieure, mais le développement des pattes se fait de la région antérieure à la région postérieure au lieu de postérieur à antérieur comme chez les autres tétrapodes, et ceci durant le développement et la régénération. Nous avons utilisé cette caractéristique de l’axolotl pour démontrer que la signalisation Shh ne structure pas l’autopode via BMP-2. En effet, l’expression de BMP-2 n'est pas régulée par l'inhibition de la signalisation Shh, et son expression est du côté opposé à celle de Shh durant le développement et la régénération des pattes de l’axolotl. Il a été observé durant le développement du membre chez la souris que MSX-1 est régulé par la signalisation Shh. Nos résultats ont démontrés que chez l’axolotl, MSX-1 ne semble pas régulé par l'inhibition de la signalisation Shh au cours de la régénération du membre. De plus, nous avons démontré que contrairement à l’expression de Shh, l’expression de BMP-2 est corrélée avec l’ordre de formation des phalanges, est impliquée dans la condensation cellulaire et dans l'apoptose précédant la chondrogenèse. L’ensemble de ces résultats suggère un rôle de BMP-2 dans l’initiation de l’ossification endochondrale. Enfin, nous avons démontré que la signalisation BMP est indispensable pour l’épimorphose du membre durant la phase de redéveloppement.

Studies on the Effect of Randomness on the Synchronization of Coupled Systems and on the Dynamics of Intermittently driven systems

Nonlinear dynamics has emerged into a prominent area of research in the past few Decades.Turbulence, Pattern formation,Multistability etc are some of the important areas of research in nonlinear dynamics apart from the study of chaos.Chaos refers to the complex evolution of a deterministic system, which is highly sensitive to initial conditions. The study of chaos theory started in the modern sense with the investigations of Edward Lorentz in mid 60's. Later developments in this subject provided systematic development of chaos theory as a science of deterministic but complex and unpredictable dynamical systems. This thesis deals with the effect of random fluctuations with its associated characteristic timescales on chaos and synchronization. Here we introduce the concept of noise, and two familiar types of noise are discussed. The classifications and representation of white and colored noise are introduced. Based on this we introduce the concept of randomness that we deal with as a variant of the familiar concept of noise. The dynamical systems introduced are the Rossler system, directly modulated semiconductor lasers and the Harmonic oscillator. The directly modulated semiconductor laser being not a much familiar dynamical system, we have included a detailed introduction to its relevance in Chaotic encryption based cryptography in communication. We show that the effect of a fluctuating parameter mismatch on synchronization is to destroy the synchronization. Further we show that the relation between synchronization error and timescales can be found empirically but there are also cases where this is not possible. Studies show that under the variation of the parameters, the system becomes chaotic, which appears to be the period doubling route to chaos.

Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience

In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced

Expresión del factor de crecimiento fibroblastico tipo 8 en el desarrollo temprano del pez cebra

Dentro del estudio de la expresión de diferentes genes, el teleósteo Danio rerio (Pez cebra) ha sido modelo de estudio del desarrollo de los vertebrados. Esta especie es ventajosa para este fin por diferentes razones, entre- ellas están la producción de grandes camadas durante todo el año, son fácilmente mantenidos, sus embriones son transparentes y se desarrollan fuera de la madre, tienen un desarrollo rápido, ya que en las 24 horas post -fecundación ya están formados la mayor parte de tejidos y primordios de los órganos, se pueden generar mutantes que se pueden propagar y estudiar muy fácilmente. Este trabajo pretende mostrar la relación entre la expresión temprana del Factor de Crecimiento Fibroblástico tipo 8 (FGF8) y el desarrollo del Sistema Nervioso Central de esta especie.

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller-Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated.

On the spectra of certain integro-differential-delay problems with applications in neurodynamics

We investigate the spectrum of certain integro-differential-delay equations (IDDEs) which arise naturally within spatially distributed, nonlocal, pattern formation problems. Our approach is based on the reformulation of the relevant dispersion relations with the use of the Lambert function. As a particular application of this approach, we consider the case of the Amari delay neural field equation which describes the local activity of a population of neurons taking into consideration the finite propagation speed of the electric signal. We show that if the kernel appearing in this equation is symmetric around some point a= 0 or consists of a sum of such terms, then the relevant dispersion relation yields spectra with an infinite number of branches, as opposed to finite sets of eigenvalues considered in previous works. Also, in earlier works the focus has been on the most rightward part of the spectrum and the possibility of an instability driven pattern formation. Here, we numerically survey the structure of the entire spectra and argue that a detailed knowledge of this structure is important within neurodynamical applications. Indeed, the Amari IDDE acts as a filter with the ability to recognise and respond whenever it is excited in such a way so as to resonate with one of its rightward modes, thereby amplifying such inputs and dampening others. Finally, we discuss how these results can be generalised to the case of systems of IDDEs.

A mathematical model, implementation and study of a swarm system

The work reported in this paper is motivated towards the development of a mathematical model for swarm systems based on macroscopic primitives. A pattern formation and transformation model is proposed. The pattern transformation model comprises two general methods for pattern transformation, namely a macroscopic transformation method and a mathematical transformation method. The problem of transformation is formally expressed and four special cases of transformation are considered. Simulations to confirm the feasibility of the proposed models and transformation methods are presented. Comparison between the two transformation methods is also reported.

Axonal velocity distributions in neural feld equations

By modelling the average activity of large neuronal populations, continuum mean field models (MFMs) have become an increasingly important theoretical tool for understanding the emergent activity of cortical tissue. In order to be computationally tractable, long-range propagation of activity in MFMs is often approximated with partial differential equations (PDEs). However, PDE approximations in current use correspond to underlying axonal velocity distributions incompatible with experimental measurements. In order to rectify this deficiency, we here introduce novel propagation PDEs that give rise to smooth unimodal distributions of axonal conduction velocities. We also argue that velocities estimated from fibre diameters in slice and from latency measurements, respectively, relate quite differently to such distributions, a significant point for any phenomenological description. Our PDEs are then successfully fit to fibre diameter data from human corpus callosum and rat subcortical white matter. This allows for the first time to simulate long-range conduction in the mammalian brain with realistic, convenient PDEs. Furthermore, the obtained results suggest that the propagation of activity in rat and human differs significantly beyond mere scaling. The dynamical consequences of our new formulation are investigated in the context of a well known neural field model. On the basis of Turing instability analyses, we conclude that pattern formation is more easily initiated using our more realistic propagator. By increasing characteristic conduction velocities, a smooth transition can occur from self-sustaining bulk oscillations to travelling waves of various wavelengths, which may influence axonal growth during development. Our analytic results are also corroborated numerically using simulations on a large spatial grid. Thus we provide here a comprehensive analysis of empirically constrained activity propagation in the context of MFMs, which will allow more realistic studies of mammalian brain activity in the future.

Design of associative memories using cellular neural networks

Cellular neural networks (CNNs) have locally connected neurons. This characteristic makes CNNs adequate for hardware implementation and, consequently, for their employment on a variety of applications as real-time image processing and construction of efficient associative memories. Adjustments of CNN parameters is a complex problem involved in the configuration of CNN for associative memories. This paper reviews methods of associative memory design based on CNNs, and provides comparative performance analysis of these approaches.

Time Evolution of the Activation Energy in a Batch Chemical Oscillator

The batch-operated bromate/phosphate/acetone/dual catalyst system was studied at four temperatures between 5 and 35 degrees C. The dynamics was simultaneously followed by potential measurements with platinum and bromide selective electrodes, and spectroscopically at two different wavelengths. By simultaneously recording these four time series it was possible to characterize the dynamics of the sequential oscillations that evolve in time. The existence of three sequential oscillatory patterns at each temperature allowed estimating the activation energies in each case. Along with the activation energy of the induction period, it was possible to trace the time evolution of the overall activation energy at four different stages as the reaction proceeds. The study was carried out for two different sets of initial concentrations and it was observed that the overall activation energy increases as reactants turn into products. This finding was propounded as a result of the decrease in the driving force, or the system`s affinity, of the catalytic oxidative bromination of acetone with acidic bromate, as the closed system evolves toward the thermodynamic equilibrium.

Parametric analyses of anxiety in zebrafish scototaxis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fenologia e dendrocronologia de duas espécies de Fabaceae em uma área de cerrado no sudeste do Brasil

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

Using complex networks to quantify consistency in the use of words

In this paper we have quantified the consistency of word usage in written texts represented by complex networks, where words were taken as nodes, by measuring the degree of preservation of the node neighborhood. Words were considered highly consistent if the authors used them with the same neighborhood. When ranked according to the consistency of use, the words obeyed a log-normal distribution, in contrast to Zipf's law that applies to the frequency of use. Consistency correlated positively with the familiarity and frequency of use, and negatively with ambiguity and age of acquisition. An inspection of some highly consistent words confirmed that they are used in very limited semantic contexts. A comparison of consistency indices for eight authors indicated that these indices may be employed for author recognition. Indeed, as expected, authors of novels could be distinguished from those who wrote scientific texts. Our analysis demonstrated the suitability of the consistency indices, which can now be applied in other tasks, such as emotion recognition.