224 resultados para COLLABORATION NETWORK


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PURPOSE: The aim of this study was to assess the outcome of patients with primary spinal myxopapillary ependymoma (MPE). MATERIALS AND METHODS: Data from a series of 85 (35 females, 50 males) patients with spinal MPE were collected in this retrospective multicenter study. Thirty-eight (45%) underwent surgery only and 47 (55%) received postoperative radiotherapy (RT). Median administered radiation dose was 50.4 Gy (range, 22.2-59.4). Median follow-up of the surviving patients was 60.0 months (range, 0.2-316.6). RESULTS: The 5-year progression-free survival (PFS) was 50.4% and 74.8% for surgery only and surgery with postoperative low- (<50.4 Gy) or high-dose (>or=50.4 Gy) RT, respectively. Treatment failure was observed in 24 (28%) patients. Fifteen patients presented treatment failure at the primary site only, whereas 2 and 1 patients presented with brain and distant spinal failure only. Three and 2 patients with local failure presented with concomitant spinal distant seeding and brain failure, respectively. One patient failed simultaneously in the brain and spine. Age greater than 36 years (p = 0.01), absence of neurologic symptoms at diagnosis (p = 0.01), tumor size >or=25 mm (p = 0.04), and postoperative high-dose RT (p = 0.05) were variables predictive of improved PFS on univariate analysis. In multivariate analysis, only postoperative high-dose RT was independent predictors of PFS (p = 0.04). CONCLUSIONS: The observed pattern of failure was mainly local, but one fifth of the patients presented with a concomitant spinal or brain component. Postoperative high-dose RT appears to significantly reduce the rate of tumor progression.

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Modern urban lifestyle encourages the prolongation of wakefulness, leaving less and less time for sleep. Although the exact functions of sleep remain one of the biggest mysteries in neuroscience, the society is well aware of the negative consequences of sleep loss on human physical and mental health and performance. Enhancing sleep's recuperative functions might allow shortening sleep duration while preserving the beneficial effects of sleep. During sleep, brain activity oscillates across a continuum of frequencies. Individual oscillations have been suggested to underlie distinct functions for sleep and cognition. Gaining control about individual oscillations might allow boosting their specific functions. Sleep spindles are 11 - 15 Hz oscillations characteristic for light non-rapid-eye-movement sleep (NREMS) and have been proposed to play a role in memory consolidation and sleep protection against environmental stimuli. The reticular thalamic nucleus (nRt) has been identified as the major pacemaker of spindles. Intrinsic oscillatory burst discharge in nRt neurons, arising from the interplay of low-threshold (T-type) Ca2+ channels (T channels) and small conductance type 2 (SK2) K+ channels (SK2 channels), underlies this pacemaking function. In the present work we investigated the impact of altered nRt bursting on spindle generation during sleep by studying mutant mice for SK2 channels and for CaV3.3 channels, a subtype of T channels. Using in vitro electrophysiology I showed that nRt bursting was abolished in CaV3.3 knock out (CaV3.3 KO) mice. In contrast, in SK2 channel over-expressing (SK2-OE) nRt cells, intrinsic repetitive bursting was prolonged. Compared to wildtype (WT) littermates, altered nRt burst discharge lead to weakened thalamic network oscillations in vitro in CaV3.3 KO mice, while oscillatory activity was prolonged in SK2-OE mice. Sleep electroencephalographic recordings in CaV3.3 KO and SK2-OE mice revealed that reduced or potentiated nRt bursting respectively weakened or prolonged sleep spindle activity at the NREMS - REMS transition. Furthermore, SK2-OE mice showed more consolidated NREMS and increased arousal thresholds, two correlates of good sleep quality. This thesis work suggests that CaV3.3 and SK2 channels may be targeted in order to modulate sleep spindle activity. Furthermore, it proposes a novel function for spindles in NREMS consolidation. Finally, it provides evidence that sleep quality may be improved by promoting spindle activity, thereby supporting the hypothesis that sleep quality can be enhanced by modulating oscillatory activity in the brain. Le style de vie moderne favorise la prolongation de l'éveil, laissant de moins en moins de temps pour le sommeil. Même si le rôle exact du sommeil reste un des plus grands mystères des neurosciences, la société est bien consciente des conséquences négatives que provoque un manque de sommeil, à la fois sur le plan de la santé physique et mentale ainsi qu'au niveau des performances cognitives. Augmenter les fonctions récupératrices du sommeil pourrait permettre de raccourcir la durée du sommeil tout en en conservant les effets bénéfiques. Durant le sommeil, on observe des oscillations à travers un continuum de fréquences. Il a été proposé que chaque oscillation pourrait être à l'origine de fonctions spécifiques pour le sommeil et la cognition. Pouvoir de contrôler les oscillations individuelles permettrait d'augmenter leurs fonctions respectives. Les fuseaux sont des oscillations de 11 à 15 Hz caractéristiques du sommeil à ondes lentes léger et il a été suggéré qu'elles jouent un rôle majeur pour la consolidation de la mémoire ainsi que dans la protection du sommeil contre les stimuli environnementaux. Le nucleus réticulaire du thalamus (nRt) a été identifié en tant que générateur de rythme des fuseaux. Les bouffées oscillatoires intrinsèques des neurones du nRt, provenant de l'interaction de canaux calciques à bas seuil de type T (canaux T) et de canaux potassiques à faible conductance de type 2 (canaux SK2), sont à l'origine de la fonction de générateur de rythme. Dans ce travail, j'ai étudié l'impact de la modulation de bouffées de nRT sur la génération des fuseaux pendant le sommeil en investiguant des souris génétiquement modifiées pour les canaux SK2 et les canaux CaV3.3, un sous-type de canaux T. En utilisant l'électrophysiologie in vitro j'ai démontré que les bouffées du nRT étaient abolies dans les souris knock-out du type CaV3.3 (CaV3.3 KO). D'autre part, dans les cellules nRT sur-exprimant les canaux SK2 (SK2-OE), les bouffées oscillatoires intrinsèques étaient prolongées. Par rapport aux souris wild type, les souris CaV3.3 KO ont montré un affaiblissement des oscillations thalamiques en réponse à un changement des bouffées de nRT, alors que l'activité oscillatoire était prolongée dans les souris SK2-OE. Des enregistrements EEG du sommeil dans des souris de type CaV3.3 KO et SK2-OE ont révélé qu'une réduction ou augmentation des bouffées nRT ont respectivement affaibli ou prolongé l'activité des fuseaux durant les transitions du sommeil à ondes lentes au sommeil paradoxal. De plus, les souris SK2-OE ont montré des signes de consolidation du sommeil à ondes lentes et un seuil augmenté pour le réveil, deux mesures qui corrèlent avec une bonne qualité du sommeil. Le travail de cette thèse propose que les canaux CaV3.3 et SK2 pourrait être ciblés pour moduler l'activité des fuseaux. De plus, je propose une fonction nouvelle pour les fuseaux dans la consolidation du sommeil à ondes lentes. Finalement je suggère que la qualité du sommeil peut être améliorée en promouvant l'activité des fuseaux, soutenant ainsi l'idée que la qualité du sommeil peut être améliorée en modulant l'activité oscillatoire dans le cerveau.

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Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.

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For self-pollinating plants to reproduce, male and female organ development must be coordinated as flowers mature. The Arabidopsis transcription factors AUXIN RESPONSE FACTOR 6 (ARF6) and ARF8 regulate this complex process by promoting petal expansion, stamen filament elongation, anther dehiscence, and gynoecium maturation, thereby ensuring that pollen released from the anthers is deposited on the stigma of a receptive gynoecium. ARF6 and ARF8 induce jasmonate production, which in turn triggers expression of MYB21 and MYB24, encoding R2R3 MYB transcription factors that promote petal and stamen growth. To understand the dynamics of this flower maturation regulatory network, we have characterized morphological, chemical, and global gene expression phenotypes of arf, myb, and jasmonate pathway mutant flowers. We found that MYB21 and MYB24 promoted not only petal and stamen development but also gynoecium growth. As well as regulating reproductive competence, both the ARF and MYB factors promoted nectary development or function and volatile sesquiterpene production, which may attract insect pollinators and/or repel pathogens. Mutants lacking jasmonate synthesis or response had decreased MYB21 expression and stamen and petal growth at the stage when flowers normally open, but had increased MYB21 expression in petals of older flowers, resulting in renewed and persistent petal expansion at later stages. Both auxin response and jasmonate synthesis promoted positive feedbacks that may ensure rapid petal and stamen growth as flowers open. MYB21 also fed back negatively on expression of jasmonate biosynthesis pathway genes to decrease flower jasmonate level, which correlated with termination of growth after flowers have opened. These dynamic feedbacks may promote timely, coordinated, and transient growth of flower organs.

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The focus of this review is to highlight the need for improved communication between medical and dental professionals in order to deliver more effective care to patients. The need for communication is increasingly required to capitalise on recent advances in the biological sciences and in medicine for the management of patients with chronic diseases. Improvements in longevity have resulted in populations with increasing special oral-care needs, including those who have cancer of the head and neck, those who are immunocompromised due to HIV/AIDS, advanced age, residence in long-term care facilities or the presence of life-long conditions, and those who are receiving long-term prescription medications for chronic conditions (e.g., anti-hypertensives, anticoagulants, immunosuppressants, antidepressants). These medications can cause adverse reactions in the oral cavity, such as xerostomia and ulceration. Patients with xerostomia are at increased risk of tooth decay, periodontal disease and infection. The ideal management of such individuals should involve the collaborative efforts of physicians, nurses, dentists and dental hygienists, thus optimising treatment and minimising secondary complications deriving from the oral cavity.

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This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

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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.

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The regulation of the immune system is controlled by many cell surface receptors. A prominent representative is the 'molecular switch' HVEM (herpes virus entry mediator) that can activate either proinflammatory or inhibitory signaling pathways. HVEM ligands belong to two distinct families: the TNF-related cytokines LIGHT and lymphotoxin-α, and the Ig-related membrane proteins BTLA and CD160. HVEM and its ligands have been involved in the pathogenesis of various autoimmune and inflammatory diseases, but recent reports indicate that this network may also be involved in tumor progression and resistance to immune response. Here we summarize the recent advances made regarding the knowledge on HVEM and its ligands in cancer cells, and their potential roles in tumor progression and escape to immune responses. Blockade or enhancement of these pathways may help improving cancer therapy.

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Substance user adolescents were asked to report on each contact they had had with any type of care providers since they had begun to use alcohol or illegal drugs regularly. Primary care doctors and social workers represent the main access to the care network. In one out of two contacts substance use was not discussed.

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Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.