45 resultados para networks in organization
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Recent studies have reported specific executive and attentional deficits in preterm children. However, the majority of this research has used multidetermined tasks to assess these abilities, and the interpretation of the results lacks an explicit theoretical backdrop to better understand the origin of the difficulties observed. In the present study, we used the Child Attention Network Task (Child ANT; Rueda et al. 2004) to assess the efficiency of the alerting, orienting and executive control networks. We compared the performance of 25 preterm children (gestational age < or = 32 weeks) to 25 full-term children, all between 5(1/2) and 6(1/2) years of age. Results showed that, as compared to full-term children, preterm children were slower on all conditions of the Child ANT and had a specific deficit in executive control abilities. We also observed a significantly higher correlation between the orienting and executive control networks in the preterm group, suggesting less differentiation of these two networks in this population.
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Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.
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La présente thèse s'intitule "Développent et Application des Méthodologies Computationnelles pour la Modélisation Qualitative". Elle comprend tous les différents projets que j'ai entrepris en tant que doctorante. Plutôt qu'une mise en oeuvre systématique d'un cadre défini a priori, cette thèse devrait être considérée comme une exploration des méthodes qui peuvent nous aider à déduire le plan de processus regulatoires et de signalisation. Cette exploration a été mue par des questions biologiques concrètes, plutôt que par des investigations théoriques. Bien que tous les projets aient inclus des systèmes divergents (réseaux régulateurs de gènes du cycle cellulaire, réseaux de signalisation de cellules pulmonaires) ainsi que des organismes (levure à fission, levure bourgeonnante, rat, humain), nos objectifs étaient complémentaires et cohérents. Le projet principal de la thèse est la modélisation du réseau de l'initiation de septation (SIN) du S.pombe. La cytokinèse dans la levure à fission est contrôlée par le SIN, un réseau signalant de protéines kinases qui utilise le corps à pôle-fuseau comme échafaudage. Afin de décrire le comportement qualitatif du système et prédire des comportements mutants inconnus, nous avons décidé d'adopter l'approche de la modélisation booléenne. Dans cette thèse, nous présentons la construction d'un modèle booléen étendu du SIN, comprenant la plupart des composantes et des régulateurs du SIN en tant que noeuds individuels et testable expérimentalement. Ce modèle utilise des niveaux d'activité du CDK comme noeuds de contrôle pour la simulation d'évènements du SIN à différents stades du cycle cellulaire. Ce modèle a été optimisé en utilisant des expériences d'un seul "knock-out" avec des effets phénotypiques connus comme set d'entraînement. Il a permis de prédire correctement un set d'évaluation de "knock-out" doubles. De plus, le modèle a fait des prédictions in silico qui ont été validées in vivo, permettant d'obtenir de nouvelles idées de la régulation et l'organisation hiérarchique du SIN. Un autre projet concernant le cycle cellulaire qui fait partie de cette thèse a été la construction d'un modèle qualitatif et minimal de la réciprocité des cyclines dans la S.cerevisiae. Les protéines Clb dans la levure bourgeonnante présentent une activation et une dégradation caractéristique et séquentielle durant le cycle cellulaire, qu'on appelle communément les vagues des Clbs. Cet évènement est coordonné avec la courbe d'activation inverse du Sic1, qui a un rôle inhibitoire dans le système. Pour l'identification des modèles qualitatifs minimaux qui peuvent expliquer ce phénomène, nous avons sélectionné des expériences bien définies et construit tous les modèles minimaux possibles qui, une fois simulés, reproduisent les résultats attendus. Les modèles ont été filtrés en utilisant des simulations ODE qualitatives et standardisées; seules celles qui reproduisaient le phénotype des vagues ont été gardées. L'ensemble des modèles minimaux peut être utilisé pour suggérer des relations regulatoires entre les molécules participant qui peuvent ensuite être testées expérimentalement. Enfin, durant mon doctorat, j'ai participé au SBV Improver Challenge. Le but était de déduire des réseaux spécifiques à des espèces (humain et rat) en utilisant des données de phosphoprotéines, d'expressions des gènes et des cytokines, ainsi qu'un réseau de référence, qui était mis à disposition comme donnée préalable. Notre solution pour ce concours a pris la troisième place. L'approche utilisée est expliquée en détail dans le dernier chapitre de la thèse. -- The present dissertation is entitled "Development and Application of Computational Methodologies in Qualitative Modeling". It encompasses the diverse projects that were undertaken during my time as a PhD student. Instead of a systematic implementation of a framework defined a priori, this thesis should be considered as an exploration of the methods that can help us infer the blueprint of regulatory and signaling processes. This exploration was driven by concrete biological questions, rather than theoretical investigation. Even though the projects involved divergent systems (gene regulatory networks of cell cycle, signaling networks in lung cells), as well as organisms (fission yeast, budding yeast, rat, human), our goals were complementary and coherent. The main project of the thesis is the modeling of the Septation Initiation Network (SIN) in S.pombe. Cytokinesis in fission yeast is controlled by the SIN, a protein kinase signaling network that uses the spindle pole body as scaffold. In order to describe the qualitative behavior of the system and predict unknown mutant behaviors we decided to adopt a Boolean modeling approach. In this thesis, we report the construction of an extended, Boolean model of the SIN, comprising most SIN components and regulators as individual, experimentally testable nodes. The model uses CDK activity levels as control nodes for the simulation of SIN related events in different stages of the cell cycle. The model was optimized using single knock-out experiments of known phenotypic effect as a training set, and was able to correctly predict a double knock-out test set. Moreover, the model has made in silico predictions that have been validated in vivo, providing new insights into the regulation and hierarchical organization of the SIN. Another cell cycle related project that is part of this thesis was to create a qualitative, minimal model of cyclin interplay in S.cerevisiae. CLB proteins in budding yeast present a characteristic, sequential activation and decay during the cell cycle, commonly referred to as Clb waves. This event is coordinated with the inverse activation curve of Sic1, which has an inhibitory role in the system. To generate minimal qualitative models that can explain this phenomenon, we selected well-defined experiments and constructed all possible minimal models that, when simulated, reproduce the expected results. The models were filtered using standardized qualitative ODE simulations; only the ones reproducing the wave-like phenotype were kept. The set of minimal models can be used to suggest regulatory relations among the participating molecules, which will subsequently be tested experimentally. Finally, during my PhD I participated in the SBV Improver Challenge. The goal was to infer species-specific (human and rat) networks, using phosphoprotein, gene expression and cytokine data and a reference network provided as prior knowledge. Our solution to the challenge was selected as in the final chapter of the thesis.
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Podocytes are essential for the function of the kidney glomerular filter. A highly differentiated cytoskeleton is requisite for their integrity. Although much knowledge has been gained on the organization of cortical actin networks in podocyte's foot processes, less is known about the molecular organization of the microtubular cytoskeleton in primary processes and the cell body. To gain an insight into the organization of the microtubular cytoskeleton of the podocyte, we systematically analyzed the expression of microtubule associated proteins (Maps), a family of microtubules interacting proteins with known functions as regulator, scaffold and guidance proteins. We identified microtubule associated protein 1b (MAP1B) to be specifically enriched in podocytes in human and rodent kidney. Using immunogold labeling in electron microscopy, we were able to demonstrate an enrichment of MAP1B in primary processes. A similar association of MAP1B with the microtubule cytoskeleton was detected in cultured podocytes. Subcellular distribution of MAP1B HC and LC1 was analyzed using a double fluorescent reporter MAP1B fusion protein. Subsequently we analyzed mice constitutively depleted of MAP1B. Interestingly, MAP1B KO was not associated with any functional or structural alterations pointing towards a redundancy of MAP proteins in podocytes. In summary, we established MAP1B as a specific marker protein of the podocyte microtubular cytoskeleton.
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Systemic hypertension increases cardiac workload and subsequently induces signaling networks in heart that underlie myocyte growth (hypertrophic response) through expansion of sarcomeres with the aim to increase contractility. However, conditions of increased workload can induce both adaptive and maladaptive growth of heart muscle. Previous studies implicate two members of the AP-1 transcription factor family, junD and fra-1, in regulation of heart growth during hypertrophic response. In this study, we investigate the function of the AP-1 transcription factors, c-jun and c-fos, in heart growth. Using pressure overload-induced cardiac hypertrophy in mice and targeted deletion of Jun or Fos in cardiomyocytes, we show that c-jun is required for adaptive cardiac hypertrophy, while c-fos is dispensable in this context. c-jun promotes expression of sarcomere proteins and suppresses expression of extracellular matrix proteins. Capacity of cardiac muscle to contract depends on organization of principal thick and thin filaments, myosin and actin, within the sarcomere. In line with decreased expression of sarcomere-associated proteins, Jun-deficient cardiomyocytes present disarrangement of filaments in sarcomeres and actin cytoskeleton disorganization. Moreover, Jun-deficient hearts subjected to pressure overload display pronounced fibrosis and increased myocyte apoptosis finally resulting in dilated cardiomyopathy. In conclusion, c-jun but not c-fos is required to induce a transcriptional program aimed at adapting heart growth upon increased workload.
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BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.
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BACKGROUND: The cerebellum is a complex structure that can be affected by several congenital and acquired diseases leading to alteration of its function and neuronal circuits. Identifying the structural bases of cerebellar neuronal networks in humans in vivo may provide biomarkers for diagnosis and management of cerebellar diseases. OBJECTIVES: To define the anatomy of intrinsic and extrinsic cerebellar circuits using high-angular resolution diffusion spectrum imaging (DSI). METHODS: We acquired high-resolution structural MRI and DSI of the cerebellum in four healthy female subjects at 3T. DSI tractography based on a streamline algorithm was performed to identify the circuits connecting the cerebellar cortex with the deep cerebellar nuclei, selected brainstem nuclei, and the thalamus. RESULTS: Using in-vivo DSI in humans we were able to demonstrate the structure of the following cerebellar neuronal circuits: (1) connections of the inferior olivary nucleus with the cerebellar cortex, and with the deep cerebellar nuclei (2) connections between the cerebellar cortex and the deep cerebellar nuclei, (3) connections of the deep cerebellar nuclei conveyed in the superior (SCP), middle (MCP) and inferior (ICP) cerebellar peduncles, (4) complex intersections of fibers in the SCP, MCP and ICP, and (5) connections between the deep cerebellar nuclei and the red nucleus and the thalamus. CONCLUSION: For the first time, we show that DSI tractography in humans in vivo is capable of revealing the structural bases of complex cerebellar networks. DSI thus appears to be a promising imaging method for characterizing anatomical disruptions that occur in cerebellar diseases, and for monitoring response to therapeutic interventions.
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This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.
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BACKGROUND: Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. RESULTS: The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite) and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. CONCLUSION: The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial populations if competition occurs among clusters.
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Aims and objectives This study aimed to determine the discriminant validity and the test-retest reliability of a questionnaire testing the impact of evidence-based medicine (EBM) training on doctors' knowledge and skills. Methods Questionnaires were sent electronically to all doctors working as residents and chief residents in two French speaking hospital networks in Switzerland. Participants completed the questionnaire twice, within a 4-week interval. The discriminant validity was examined in comparing doctors' performance according to their reported EBM previous training. Proportion of agreement between both sessions of the questionnaire, Cohen's kappa and 'uniform kappa' determined its test-retest reliability. Results The participation rate was 9.8%/7.1% to first/second session. Performance increased according to the level of doctors' previous training in EBM. The observed proportion of agreement between both sessions was over 70% for 14/19 questions, and the 'uniform kappa' was superior to 0.60 for 15/19 questions. Conclusion The discriminant validity and test-retest reliability of the questionnaire were satisfying. The low participation rate did not prevent the study from achieving its aims.
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Cardiovascular diseases and in particular heart failure are major causes of morbidity and mortality in the Western world. Recently, the notion of promoting cardiac regeneration as a means to replace lost cardiomyocytes in the damaged heart has engendered considerable research interest. These studies envisage the utilization of both endogenous and exogenous cellular populations, which undergo highly specialized cell fate transitions to promote cardiomyocyte replenishment. Such transitions are under the control of regenerative gene regulatory networks, which are enacted by the integrated execution of specific transcriptional programs. In this context, it is emerging that the non-coding portion of the genome is dynamically transcribed generating thousands of regulatory small and long non-coding RNAs, which are central orchestrators of these networks. In this review, we discuss more particularly the biological roles of two classes of regulatory non-coding RNAs, i.e. microRNAs and long non-coding RNAs, with a particular emphasis on their known and putative roles in cardiac homeostasis and regeneration. Indeed, manipulating non-coding RNA-mediated regulatory networks could provide keys to unlock the dormant potential of the mammalian heart to regenerate. This should ultimately improve the effectiveness of current regenerative strategies and discover new avenues for repair. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.
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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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ABSTRACT The network of actin cytoskeleton is composed of actin filaments (F-actin) that are made by polymerisation of actin monomers and actin binding proteins. It is required for growth and morphogenesis of eukaryotic cells. The labelling of F-actin with constitutively expressed GFP-Talin (Kost et al., 1998) reveals the organisation of cellular actin networks in plants. Due to the lack of information on actin cytoskeleton through gametophytic development of the model moss plant Physcornitrella patens, stable transgenic lines overexpressing GFP-Talin were generated to detect F-actin structures. It is shown that the 35S promoter driven expression is not suitable for F-actin labelling in all cells. When it is replaced by the inducible heat-shock promoter Gmhsp17.3 from soybean, one hour mild heat stress at 37°C followed by recovery at 25°C is enough to induce efficient and transient labelling in all tissues without altering cellular morphology. The optimal observations of F-actin structures at different stages of moss development can be done between 12-18 hours after the induction. By using confocal microscopy, we demonstrate that stellated actin arrays were densely accumulated at the growing tip in regenerating protoplasts, apical protonemal cells and rhizoids and connected with a fine dispersed F-actin mesh. Following three-dimensional growth, the cortical star-like structures are widespread in the meristematic cells of developing bud and young gametophores. On the contrary, undulating networks of actin cables are found at the final stage of cell differentiation. During redifferentiation of mature leaf cells into protonemal filaments the rather stagnant web of actin cables is replaced by diffuse actin meshwork. In eukaryotes, nucleation of the actin monomers prior to their polymerization is driven by the seven-subunit ARP2/3 complex and formins. We cloned the gene encoding the ARP3 subunit of P. patens and generated arp3 mutants of the moss through gene disruption. The knockout of ARP3 affects the elongation of chloronemal cells and blocks further differentiation of caulonemal cells and rhizoids, and the gametophores are slightly stunted compared to wild-type. The arp mutants were created in the heat-shock inducible GFP-Talin strains allowing us to visualise a disorganised actin network and a lack of star-like actin cytoskeleton arrays. We conclude that ARP2/3 dependent nucleation of actin filaments is critical for the growth of filamentous cells, which in turn influences moss colonization. In complementation assays, the overexpression of Physcomitrella and Arab idopsis ARP3 genes in the moss arp3 mutant results in full recovery of wild type phenotype. In contrast the ARP3 subunit of fission yeast is not able to complement the moss arp3 mutant of moss indicating that regulation of the ARP2/3 dependent actin nucleation diverged in different kingdoms. RESUME Le réseau d'actine est composé de filaments de F-actine et d'un ensemble de protéines s'y attachant (Actin binding proteins). Le réseau d'actine est nécessaire à la croissance et à la morphogenèse de toutes les cellules eucaryotes. Chez les plantes, le marquage ainsi que l'étude de l'organisation du réseau d'actine ont été réalisés en utilisant une fusion GFP-Talin (Kost et al., 1998) exprimée sous le control d'un promoteur constitutif. Afin d'étudier les structures F-actine dans les cellules de Physcomitrella Patens et pour combler le manque d'information sur le développement des gamétophores, des lignées transgéniques stables surexprimant GFP-Talin ont été crées. Nous avons démontré que l'utilisation du promoteur 35S est inadéquate pour le marquage complet et homogène des filaments d'actine dans toutes les cellules de P. patens. Par contre, l'utilisation du promoteur inductible Gmhsp17.3 nous a permis de réaliser un marquage transitoire et général dans tous les tissus de la mousse. Une heure de choc thermique à 37°C suivis d'un temps de récupération de 12-18h à 25°C sont les conditions optimales (sans dommages cellulaires) pour l'observation des structures F-actine à différentes étapes de développement de la mousse. En utilisant la microscopie confocale, nous avons observé l'existence de structures F-actine accumulées en forme d'étoiles. Ces structures, qui sont liées au réseau de microfilaments d'actine, ont été observées dans les protoplastes en régénération, les cellules des protonema apicales ainsi que dans les rhizoïdes. En suivant la croissance tridimensionnelle, ces structures en étoiles ont été observées dans les cellules meristématiques des bourgeons et des jeunes gamétophores. Par contre, dans les cellules différentiées ces structures laissent place à des réseaux de câbles épais. Nous avons également remarqué que durant la redifferentiation des cellules foliaires le réseau de câbles de F-actine est remplacé par un réseau de F-actine diffus. Dans les cellules eucaryotes, la nucléation des filaments d'actirie précédant leur polymérisation est contrôlé par sept sous unités du complexe ARP2/3 et par des formines. Nous avons isolé le gène codant pour la sous unité ARP3 de P. patens et nous avons crée des mutants arp3 par intégration ciblée (Knockout). L'élongation des cellules chloronema est clairement affectée dans les mutants arp3. La différentiation des caulonemata et des rhizoïdes est bloquée et les gametophores sont légèrement plus courts comparé au type sauvage. A fin d'étudier l'organisation des filaments d'actines dans les mutants arp3, nous avons aussi réalisé un arp3-knockout dans la lignée Hsp-GFP-Talin. La nouvelle lignée générée nous a permis de visualiser une désorganisation du réseau d'actine et une absence complète de structures de F-actine accumulée en forme d'étoiles. Les résultats obtenus nous amènent à conclure que la nucléation (ARP2/3 dépendante) des filaments d'actine est indispensable à la croissance des cellules filamenteuses. Par conséquent, les filaments d'actine semblent avoir un rôle dans la colonisation des milieux par les mousses. Nous avons également procédé à des essais de complémentation du mutant arp3. La surexpression des gènes ARP3 de Physcomitrella et d'Arabidopsis dans les cellules du mutant arp3 rétabli complètement le phénotype WT. Par contre, le gène ARP3 des levures n'est pas suffisant pour complémenter la même mutation dans les cellules de mousses. Ce résultat démontre que les mécanismes de régulation de la nucléation des filaments d'actine (ARP2/3 dépendante) sont différents entre les différents groupes d'eucaryotes.
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This paper advocates the adoption of a mixed-methods research design to describe and analyze ego-centered social networks in transnational family research. Drawing on the experience of the Social Networks Influences on Family Formation project (2004-2005), I show how the combined use of network generators and semistructured interviews (N = 116) produces unique data on family configurations and their impact on life course choices. A mixed-methods network approach presents specific advantages for research on children in transnational families. On the one hand, quantitative analyses are crucial for reconstructing and measuring the potential and actual relational support available to children in a context where kin interactions may be hindered by temporary and prolonged periods of separation. On the other hand, qualitative analyses can address strategies and practices employed by families to maintain relationships across international borders and geographic distance, as well as the implications of those strategies for children's well-being.
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Malignant gliomas, including the most common and fatal form glioblastoma (GBM, WHO grade IV astrocytoma), remain a challenge to treat. In the United States and Europe, more than 30,000 patients per year are newly diagnosed with GBM. Despite ongoing trials, the best currently available multimodal treatment approaches include surgical resection followed by concomitant and adjuvant radiation (RT) and temozolomide (TMZ) therapy, resulting in a low median overall survival (OS) rate ranging from 12.2 - 15.9 months. The important role of genetic and epigenetic changes in DNA, RNA, and protein alteration as well as epigenetic changes secondary to the tumor microenvironment and outside selection pressure (therapeutic interventions), are increasingly being recognized. In GBM treatment, the focus is shifting toward a more patient-centered (personalized) therapy. In this regard, in particular, microRNAs are being increasingly studied. MicroRNAs are non¬protein coding small RNAs that serve as negative gene regulators by binding to a specific sequence in the promoter region of a target gene, thus regulating gene expression. A single microRNA potentially targets hundreds of genes; thus, microRNAs and their cognate target genes have important roles as tumor suppressors and oncogenes as well as regulators of various cancer- specific cellular features, such as proliferation, apoptosis, invasion, and metastasis. The identification of distinct microRNA-gene regulatory networks in GBM patients can be expected to provide novel therapeutic insights by identifying candidate patients for targeted therapies. To this end, in this work we identified and validated clinically relevant and meaningful novel gene- microRNA regulatory networks that correlated with MR tumor phenotypes, histopathology, and patient survival and response rates to therapy. - Le traitement des gliomes malins, y compris sous leur forme la plus commune et meurtrière, le glioblastome (GBM, ou astrocytome de grade IV selon l'OMS), demeure à ce jour un défi. Aux États-Unis et en Europe, un nouveau diagnostic de GBM est prononcé dans plus de 30Ό00 cas par an. En dépit de tests en cours, les meilleures approches thérapeutiques combinées actuellement disponibles comprennent la résection chirurgicale de la tumeur, suivie d'une radiothérapie adjuvante ainsi que d'un traitement au temozolomide (RT/TMZ), thérapies dont résulte une médiane de survie globale basse (overall survival, OS), comprise entre 12.2 et 15.9 mois. On reconnaît de plus en plus le rôle majeur de l'ADN, de l'ARN et de l'altération des protéines ainsi que des modifications épigénétiques, secondaires par rapport au microenvironnement de la tumeur et à la pression de sélection extérieure (les interventions thérapeutiques). Dans le traitement du GBM, le centre d'intérêt se déplace vers une thérapie centrée sur le cas individuel du patient. Dans ce but, en particulier les microARN sont de plus en plus analysés. Les microARN sont de petits ARN non-codants (les protéines) qui servent de régulateurs négatifs de gènes en s'attachant à une séquence spécifique dans la région promotrice d'un gène-cible, régulant ainsi l'expression du gène. Un seul microARN cible potentiellement des centaines de gènes; on a ainsi découvert que les microARN et leurs gènes-cibles apparentés ont une fonction importante en tant que suppresseurs de tumeurs et d'oncogènes, ainsi que comme régulateurs de diverses caractéristiques cellulaires spécifiques du cancer, comme la prolifération, l'apoptose, l'invasion et la métastase. On peut s'attendre à ce que l'identification de réseaux microARN régulateurs de gènes, distincts selon les patients de GBM, fournisse une approche thérapeutique inédite par la détermination des patients susceptibles de réagir favorablement à des thérapies ciblées.