The role of MYCN-mediated transcriptional repression in neuronal physiopathology

MYC is a transcription factor that can activate transcription of several targets by direct binding to their promoters at specific DNA sequences (E-box). Recent findings have also shown that it can exert its biological role by repressing transcription of other set of genes. C-MYC can mediate repression on its target genes through interaction with factors bound to promoter regions but not through direct recognition of typical E-Boxes. In this thesis, we investigated whether MYCN can also repress gene transcription and how this is mechanistically achieved. Moreover, expression of TRKA, P75NTR and ABCC3 is attenuated in aggressive MYCN-amplified tumors, suggesting a causal link between elevated MYCN activity and transcriptional repression of these three genes. We found that MYCN is physically associated with gene promoters in vivo in proximity of the transcriptional start sites and this association requires interactions with SP1 and/or MIZ-1. Furthermore, we show that this interaction could interfere with SP1 and MIZ-1 activation functions by recruiting co-repressors such as DNMT3a or HDACs. Studies in vitro suggest that MYCN interacts through distinct domains with SP1, MIZ-1 and HDAC1 supporting the idea that MYCN may form different complexes by interacting with different proteins. Re-expression of endogenous TRKA and P75NTR with exposure to the TSA sensitizes neuroblastoma to NGF-mediated apoptosis, whereas ectopic expression of ABCC3 decreases cell motility without interfering with growth. Finally, using shRNA whole genome library, we dissected the P75NTR repression trying to identify novel factors inside and/or outside MYCN complex for future therapeutic approaches. Overall, our results support a model in which MYCN can repress gene transcription by direct interaction with SP1 and/or MIZ-1, and provide further lines of evidence on the importance of transcriptional repression induced by Myc in tumor biology.

Polynomial approximation using particle swarm optimization of lineal enhanced neural networks with no hidden layers.

This paper presents some ideas about a new neural network architecture that can be compared to a Taylor analysis when dealing with patterns. Such architecture is based on lineal activation functions with an axo-axonic architecture. A biological axo-axonic connection between two neurons is defined as the weight in a connection in given by the output of another third neuron. This idea can be implemented in the so called Enhanced Neural Networks in which two Multilayer Perceptrons are used; the first one will output the weights that the second MLP uses to computed the desired output. This kind of neural network has universal approximation properties even with lineal activation functions. There exists a clear difference between cooperative and competitive strategies. The former ones are based on the swarm colonies, in which all individuals share its knowledge about the goal in order to pass such information to other individuals to get optimum solution. The latter ones are based on genetic models, that is, individuals can die and new individuals are created combining information of alive one; or are based on molecular/celular behaviour passing information from one structure to another. A swarm-based model is applied to obtain the Neural Network, training the net with a Particle Swarm algorithm.

Transformación del espacio cinemático Laban para la evaluación del movimiento

Este proyecto tiene como objetivo la implementación de un sistema capaz de analizar el movimiento corporal a partir de unos puntos cinemáticos. Estos puntos cinemáticos se obtienen con un programa previo y se captan con la cámara kinect. Para ello el primer paso es realizar un estudio sobre las técnicas y conocimientos existentes relacionados con el movimiento de las personas. Se sabe que Rudolph Laban fue uno de sus mayores exponentes y gracias a sus observaciones se establece una relación entre la personalidad, el estado anímico y la forma de moverse de un individuo. Laban acuñó el término esfuerzo, que hace referencia al modo en que se administra la energía que genera el movimiento y de qué manera se modula en las secuencias, es una manera de describir la intención de las expresiones internas. El esfuerzo se divide en 4 categorías: peso, espacio, tiempo y flujo, y cada una de estas categorías tiene una polaridad denominada elemento de esfuerzo. Con estos 8 elementos de esfuerzo un movimiento queda caracterizado. Para poder cuantificar los citados elementos de esfuerzo se buscan movimientos que representen a alguno de ellos. Los movimientos se graban con la cámara kinect y se guardan sus valores en un archivo csv. Para el procesado de estos datos se establece que el sistema más adecuado es una red neuronal debido a su flexibilidad y capacidad a la hora de procesar entradas no lineales. Para la implementación de la misma se requiere un amplio estudio que incluye: topologías, funciones de activación, tipos de aprendizaje, algoritmos de entrenamiento entre otros. Se decide que la red tenga dos capas ocultas, para mejor procesado de los datos, que sea estática, siga un proceso de cálculo hacia delante (Feedforward) y el algoritmo por el que se rija su aprendizaje sea el de retropropagación (Backpropagation) En una red estática las entradas han de ser valores fijos, es decir, no pueden variar en el tiempo por lo que habrá que implementar un programa intermedio que haga una media aritmética de los valores. Una segunda prueba con la misma red trata de comprobar si sería capaz de reconocer movimientos que estuvieran caracterizados por más de un elemento de esfuerzo. Para ello se vuelven a grabar los movimientos, esta vez en parejas de dos, y el resto del proceso es igual. ABSTRACT. The aim of this project is the implementation of a system able to analyze body movement from cinematic data. This cinematic data was obtained with a previous program. The first step is carrying out a study about the techniques and knowledge existing nowadays related to people movement. It is known that Rudolf Laban was one the greatest exponents of this field and thanks to his observations a relation between personality, mood and the way the person moves was made. Laban coined the term effort, that refers to the way energy generated from a movement is managed and how it is modulated in the sequence, this is a method of describing the inner intention of the person. The effort is divided into 4 categories: weight, space, time and flow, and each of these categories have 2 polarities named elements of effort. These 8 elements typify a movement. We look for movements that are made of these elements so we can quantify them. The movements are recorded with the kinect camera and saved in a csv file. In order to process this data a neural network is chosen owe to its flexibility and capability of processing non-linear inputs. For its implementation it is required a wide study regarding: topology, activation functions, different types of learning methods and training algorithms among others. The neural network for this project will have 2 hidden layers, it will be static and follow a feedforward process ruled by backpropagation. In a static net the inputs must be fixed, this means they cannot vary in time, so we will have to implement an intermediate program to calculate the average of our data. A second test for our net will be checking its ability to recognize more than one effort element in just one movement. In order to do this all the movements are recorded again but this time in pairs, the rest of the process remains the same.

Thyroid hormone receptor-associated proteins and general positive cofactors mediate thyroid hormone receptor function in the absence of the TATA box-binding protein-associated factors of TFIID

Coactivators previously implicated in ligand-dependent activation functions by thyroid hormone receptor (TR) include p300 and CREB-binding protein (CBP), the steroid receptor coactivator-1 (SRC-1)-related family of proteins, and the multicomponent TR-associated protein (TRAP) complex. Here we show that two positive cofactors (PC2 and PC4) derived from the upstream stimulatory activity (USA) cofactor fraction act synergistically to mediate thyroid hormone (T3)-dependent activation either by TR or by a TR-TRAP complex in an in vitro system reconstituted with purified factors and DNA templates. Significantly, the TRAP-mediated enhancement of activation by TR does not require the TATA box-binding protein-associated factors of TFIID. Furthermore, neither the pleiotropic coactivators CBP and p300 nor members of the SRC-1 family were detected in either the TR-TRAP complex or the other components of the in vitro assay system. These results show that activation by TR at the level of naked DNA templates is enhanced by cooperative functions of the TRAP coactivators and the general coactivators PC2 and PC4, and they further indicate a potential functional redundancy between TRAPs and TATA box-binding protein-associated factors in TFIID. In conjunction with earlier studies on other nuclear receptor-interacting cofactors, the present study also suggests a multistep pathway, involving distinct sets of cofactors, for activation of hormone responsive genes.

Analysis of estrogen receptor transcriptional enhancement by a nuclear hormone receptor coactivator.

The estrogen receptor (ER), a member of a large superfamily of nuclear hormone receptors, is a ligand-inducible transcription factor that regulates the expression of estrogen-responsive genes. The ER, in common with other members of this superfamily, contains two transcription activation functions (AFs)--one located in the amino-terminal region (AF-1) and the second located in the carboxyl-terminal region (AF-2). In most cell contexts, the synergistic activity of AF-1 and AF-2 is required for full estradiol (E2)-stimulated activity. We have previously shown that a ligand-dependent interaction between the two AF-containing regions of ER was promoted by E2 and the antiestrogen trans-hydroxytamoxifen (TOT). This interaction, however, was transcriptionally productive only in the presence of E2. To explore a possible role of steroid receptor coactivators in transcriptional synergism between AF-1 and AF-2, we expressed the amino terminal (AF-1-containing) and carboxyl-terminal (AF-2-containing) regions of ER as separate polypeptides in mammalian cells, along with the steroid receptor coactivator-1 protein (SRC-1). We demonstrate that SRC-1, which has been shown to significantly increase ER transcriptional activity, enhanced the interaction, mediated by either E2 or TOT, between the AF-1-containing and AF-2-containing regions of the ER. However, this enhanced interaction resulted in increased transcriptional effectiveness only with E2 and not with TOT, consistent with the effects of SRC-1 on the full-length receptor. Our results suggest that after ligand binding, SRC-1 may act, in part, as an adapter protein that promotes the integration of amino- and carboxyl-terminal receptor functions, allowing for full receptor activation. Potentially, SRC-1 may be capable of enhancing the transcriptional activity of related nuclear receptor superfamily members by facilitating the productive association of the two AF-containing regions in these receptors.

Ligand-dependent, transcriptionally productive association of the amino- and carboxyl-terminal regions of a steroid hormone nuclear receptor.

The estrogen receptor (ER), a 66-kDa protein that mediates the actions of estrogens in estrogen-responsive tissues, is a member of a large superfamily of nuclear hormone receptors that function as ligand-activated transcription factors. ER shares a conserved structural and functional organization with other members of this superfamily, including two transcriptional activation functions (AFs), one located in its amino-terminal region (AF-1) and the second located in its carboxyl-terminal, ligand-binding region (AF-2). In most promoter contexts, synergism between AF-1 and AF-2 is required for full ER activity. In these studies, we demonstrate a functional interaction of the two AF-containing regions of ER, when expressed as separate polypeptides in mammalian cells, in response to 17 beta-estradiol (E2) and antiestrogen binding. The interaction was transcriptionally productive only in response to E2, and was eliminated by point or deletion mutations that destroy AF-1 or AF-2 activity or E2 binding. Our results suggest a definitive mechanistic role for E2 in the activity of ER--namely, to alter receptor conformation to promote an association of the amino- and carboxyl-terminal regions, leading to transcriptional synergism between AF-1 and AF-2. The productive re assembly of two portions of ER expressed in cells as separate polypeptides demonstrates the evolutionarily conserved modular structural and functional organization of the nuclear hormone receptors. The ligand-dependent interaction of the two AF-containing regions of ER allows for the assembly of a complete activation function from two distinct regions within the same protein, providing a mechanism for hormonally regulated transcription.

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

New inequality-based approach to passivity analysis of neural networks with interval time-varying delay

This paper is concerned with the problem of passivity analysis of neural networks with an interval time-varying delay. Unlike existing results in the literature, the time-delay considered in this paper is subjected to interval time-varying without any restriction on the rate of change. Based on novel refined Jensen inequalities and by constructing an improved Lyapunov-Krasovskii functional (LKF), which fully utilizes information of the neuron activation functions, new delay-dependent conditions that ensure the passivity of the network are derived in terms of tractable linear matrix inequalities (LMIs) which can be effectively solved by various computational tools. The effectiveness and improvement over existing results of the proposed method in this paper are illustrated through numerical examples.

Linear gramicidin activates neutrophil functions and the activation is blocked by chemotactic peptide receptor antagonist

The activation of functional responses in rabbit peritoneal neutrophils by gramicidin and the chemotactic peptide, N-formyl-methionyl-leucyl-phenylalanine methyl ester, was studied. Gramicidin activated superoxide generation, lysosomal enzyme release and a decrease in fluorescence of chlortetracycline-loaded cells, as for the chemotactic peptide. The maximum intensities of the responses by gramicidin were lower than that by chemotactic peptide. Responses by both these peptides could be inhibited by t-butyloxycarbonyl-methionyl-leucyl-phenylalanine, a chemotactic peptide receptor antagonist. Gramicidin gave responses at low doses comparable to that of the chemotactic peptide.

Estimation of variables at ungaged locations by empirical orthogonal functions

A technique based on empirical orthogonal functions is used to estimate hydrologic time-series variables at ungaged locations. The technique is applied to estimate daily and monthly rainfall, temperature and runoff values. The accuracy of the method is tested by application to locations where data are available. The second-order characteristics of the estimated data are compared with those of the observed data. The results indicate that the method is quick and accurate.

Role of the protein tyrosine phosphatase DEP-1 in Src activation and the mediation of biological cell functions of endothelial and breast cancer cells

L’implication des protéines tyrosines phosphatases (PTPs) dans la régulation de la signalisation et la médiation des fonctions cellulaires a été bien établie dans les dernières années. Cependant, les mécanismes moléculaires par lesquels les PTPs régulent les processus fondamentaux tels que l’angiogenèse demeurent méconnus. Il a été rapporté que l’expression de la PTP DEP-1 (Density-enhanced phosphatase 1) augmente avec la densité cellulaire et corrèle avec la déphosphorylation du récepteur VEGFR2. Cette déphosphorylation contribue à l’inhibition de contact dans les cellules endothéliales à confluence et diminue l’activité du VEGFR2 en déphosphorylant spécifiquement ses résidus catalytiques Y1054/1059. De plus, la plupart des voies de signalisation en aval du VEGFR2 sont diminuées sauf la voie Src-Gab1-AKT. DEP-1 déphosphoryle la Y529 de Src et contribue à la promotion de la survie dans les cellules endothéliales. L’objectif de cette thèse est de mieux définir le rôle de DEP-1 dans la régulation de l’activité de Src et les réponses biologiques dans les cellules endothéliales. Nous avons identifié les résidus Y1311 et Y1320 dans la queue C-terminale de DEP-1 comme sites majeurs de phosphorylation en réponse au VEGF. La phosphorylation de ces résidus est requise pour l’activation de Src et médie le remodelage des jonctions cellules-cellules dépendantes de Src. Ce remodelage induit la perméabilité, l’invasion et la formation de capillaires en réponse au VEGF. Nos résultats démontrent que la phosphorylation de DEP-1 sur résidu tyrosine est requise pour diriger la spécificité de DEP-1 vers son substrat Src. Les travaux révèlent pour la première fois un rôle positif de DEP-1 sur l’induction du programme angiogénique des cellules endothéliales. En plus de la phosphorylation sur tyrosine, DEP-1 est constitutivement phosphorylé sur la thréonine 1318 situé à proximité de la Y1320 en C-terminal. Cette localisation de la T1318 suggère que ce résidu pourrait être impliqué dans la régulation de la Y1320. En effet, nous avons observé que la T1318 de DEP-1 est phosphorylée potentiellement par CK2, et que cette phosphorylation régule la phosphorylation de DEP-1 sur tyrosine et sa capacité de lier et d’activer Src. En accord avec ces résultats, nos travaux révèlent que la surexpression du mutant DEP-1 T1318A diminue le remodelage des jonctions cellules-cellules et par conséquent la perméabilité. Nos résultats suggèrent donc que la T1318 de DEP-1 constitue un nouveau mécanisme de contrôle de la phosphorylation sur tyrosine et que ceci résulte en l’activation de Src et l’induction des fonctions biologiques des cellules endothéliales en réponse au VEGF. Suite à ces travaux dans les cellules endothéliales qui démontrent un rôle positif de DEP-1 dans la médiation des réponses angiogéniques, nous avons voulu approfondir nos connaissances sur l’implication potentielle de DEP-1 dans les cellules cancéreuses où l’activité de Src est requise pour la progression tumorale. Malgré le rôle connu de DEP-1 comme suppresseur tumoral dans différents types de cancer, nous avons émis l’hypothèse que DEP-1 pourrait promouvoir les fonctions biologiques dépendantes de Src telles que la migration et l’invasion dans les cellules cancéreuses. Ainsi, nous avons observé que l’expression de DEP-1 est plus élevée dans les lignées basales de cancer du sein qui sont plus invasives comparativement aux lignées luminales peu invasives. Dans les lignées basales, DEP-1 active Src, médie la motilité cellulaire dépendante de Src et régule la localisation des protéines impliquées dans l’organisation du cytosquelette. L’analyse d’un micro-étalage de tissu a révélé que l’expression de DEP-1 est associée avec une réduction tendencielle de survie des patients. Nos résultats proposent donc, un rôle de promoteur tumoral pour DEP-1 dans la progression du cancer du sein. Les travaux présentés dans cette thèse démontrent pour la première fois que DEP-1 peut agir comme promoteur des réponses angiogéniques et du phénotype pro-invasif des lignées basales du cancer du sein probablement du à sa capacité d’activer Src. Nos résultats suggèrent ainsi que l’expression de DEP-1 pourrait contribuer à la progression tumorale et la formation de métastases. Ces découvertes laissent donc entrevoir que DEP-1 représente une nouvelle cible thérapeutique potentielle pour contrer l’angiogenèse et le développement du cancer.

Families of orthogonal functions defined by the Weyl groups of compact Lie groups

Plusieurs familles de fonctions spéciales de plusieurs variables, appelées fonctions d'orbites, sont définies dans le contexte des groupes de Weyl de groupes de Lie simples compacts/d'algèbres de Lie simples. Ces fonctions sont étudiées depuis près d'un siècle en raison de leur lien avec les caractères des représentations irréductibles des algèbres de Lie simples, mais également de par leurs symétries et orthogonalités. Nous sommes principalement intéressés par la description des relations d'orthogonalité discrète et des transformations discrètes correspondantes, transformations qui permettent l'utilisation des fonctions d'orbites dans le traitement de données multidimensionnelles. Cette description est donnée pour les groupes de Weyl dont les racines ont deux longueurs différentes, en particulier pour les groupes de rang $2$ dans le cas des fonctions d'orbites du type $E$ et pour les groupes de rang $3$ dans le cas de toutes les autres fonctions d'orbites.

Variability of the Atlantic thermohaline circulation described by three-dimensional empirical orthogonal functions

We describe the use of bivariate 3d empirical orthogonal functions (EOFs) in characterising low frequency variability of the Atlantic thermohaline circulation (THC) in the Hadley Centre global climate model, HadCM3. We find that the leading two modes are well correlated with an index of the meridional overturning circulation (MOC) on decadal timescales, with the leading mode alone accounting for 54% of the decadal variance. Episodes of coherent oscillations in the sub-space of the leading EOFs are identified; these episodes are of great interest for the predictability of the THC, and could indicate the existence of different regimes of natural variability. The mechanism identified for the multi-decadal variability is an internal ocean mode, dominated by changes in convection in the Nordic Seas, which lead the changes in the MOC by a few years. Variations in salinity transports from the Arctic and from the North Atlantic are the main feedbacks which control the oscillation. This mode has a weak feedback onto the atmosphere and hence a surface climatic influence. Interestingly, some of these climate impacts lead the changes in the overturning. There are also similarities to observed multi-decadal climate variability.