955 resultados para COMPLEX NETWORK


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Peripheral T-cell lymphomas (PTCLs) are heterogeneous and uncommon malignancies characterized by an aggressive clinical course and a mostly poor outcome with current treatment strategies. Despite novel insights into their pathobiology provided by recent genome-wide molecular studies, several entities remain poorly characterized. In addition to the neoplastic cell population, PTCLs have a microenvironment component, composed of non-tumor cells and stroma, which is quantitatively and qualitatively variable, and which may have an effect on their pathological and clinical features. The best example is provided by angioimmunoblastic T-cell lymphoma (AITL), a designation reflecting the typical vascularization and reactive immunoblastic content of the tumor tissues. In this disease, a complex network of interactions between the lymphoma cells and the microenvironment exists, presumably mediated by the neoplastic T cells with follicular helper T-cell properties. A better understanding of the crosstalk between neoplastic T or NK cells and their microenvironment may have important implications for guiding the development of novel therapies.

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The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

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Ocular development is controlled by a complex network of transcription factors, cell cycle regulators, and diffusible signaling molecules. Together, these molecules regulate cell proliferation, apoptosis and specify retinal fate. In the zebrafish (Danio rerio), hmx1 is a homeobox transcription factor implicated in eye and brain development. Hmx1 transcripts were detected in the nasal retina and lens as well as otic vesicles and pharyngeal arches by 24-32 hpf. Before this stage, transcripts were more uniformly expressed in the optic vesicle. Knockdown of hmx1 led to microphthalmia. Delayed withdrawal of retinal progenitors from the cell cycle resulting in retarded retinal differentiation was observed in morphant. The retina and brain also showed an increased cell death at 24 hpf. The polarized expression of hmx1 to the nasal part in the zebrafish retina strongly suggested an involvement in the nasal-temporal patterning. However, the key patterning genes tested so far were not regulated by hmx1. Altogether, these results suggest an important role for hmx1 in retinogenesis.

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Economy, and consequently trade, is a fundamental part of human social organization which, until now, has not been studied within the network modeling framework. Here we present the first, to the best of our knowledge, empirical characterization of the world trade web, that is, the network built upon the trade relationships between different countries in the world. This network displays the typical properties of complex networks, namely, scale-free degree distribution, the small-world property, a high clustering coefficient, and, in addition, degree-degree correlation between different vertices. All these properties make the world trade web a complex network, which is far from being well described through a classical random network description.

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THE COMBINATION OF ADVANCED NEUROIMAGING TECHNIQUES AND MAJOR DEVELOPMENTS IN COMPLEX NETWORK SCIENCE, HAVE GIVEN BIRTH TO A NEW FRAMEWORK FOR STUDYING THE BRAIN: "connectomics." This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.

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Early ocular development is controlled by a complex network of transcription factors, cell cycle regulators, and diffusible signalling molecules. Together, these molecules regulate cell proliferation and apoptosis, and specify retinal fate. NKX5-3 is a homeobox transcription factor implicated in eye development. The analysis of the 5'-flanking region of the mouse Nkx5-3 gene revealed a predicted TATA-less promoter sequence between -416 and -166 of the translation start site. To functionally characterise Nkx5-3 promoter activity, serial deletions of the promoter sequence were introduced in pGL-3 basic vector and promoter activity of these 5'- and 3'-deleted constructions was tested in HeLa and CHO cells. Transactivation assays identified a region between -350 and -296 exhibiting promoter-like activity. Combined analysis by deletions and point mutations showed that this sequence, containing multiple Sp1 binding sites was necessary to promote transcriptional activity. Binding of Sp1 to this region was confirmed by electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation, using an antibody specific for Sp1. Altogether, these results demonstrated that the immediate upstream region of Nkx5-3 gene possessed a strong intrinsic promoter activity in vitro, suggesting a potential role in Nkx5-3 transcription in vivo.

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Pseudomonas fluorescens CHA0 protects various crop plants against root diseases caused by pathogenic fungi. Among a range of exoproducts excreted by strain CHA0, the antifungal compounds 2,4-diacetylphloroglucinol (DAPG) and pyoluteorin (PLT) are particularly relevant to the strain's biocontrol potential. Here, we report on the characterization of MvaT and MvaV as novel regulators of biocontrol activity in strain CHA0. We establish the two proteins as further members of an emerging family of MvaT-like regulators in pseudomonads that are structurally and functionally related to the DNA-binding protein H-NS. In mvaT and mvaV in frame-deletion mutants of strain CHA0, PLT production was enhanced about four- and 1.5-fold, respectively, whereas DAPG production remained at wild-type levels. Remarkably, PLT production was increased up to 20-fold in an mvaT mvaV double mutant. DAPG biosynthesis was almost completely repressed in this mutant. The effects on antibiotic production could be confirmed by following expression of gfp-based reporter fusions to the corresponding biosynthetic genes. MvaT and MvaV also influenced levels of other exoproducts, motility, and physicochemical cell-surface properties to various extents. Compared with the wild type, mvaT and mvaV mutants had an about 20% reduced capacity (in terms of plant fresh weight) to protect cucumber from a root rot caused by Pythium ultimum. Biocontrol activity was nearly completely abolished in the double mutant Our findings indicate that MvaT and MvaV act together as further global regulatory elements in the complex network controlling expression of biocontrol traits in plant-beneficial pseudomonads.

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Phosphate is a crucial and often limiting nutrient for plant growth. To obtain inorganic phosphate (P(i) ), which is very insoluble, and is heterogeneously distributed in the soil, plants have evolved a complex network of morphological and biochemical processes. These processes are controlled by a regulatory system triggered by P(i) concentration, not only present in the medium (external P(i) ), but also inside plant cells (internal P(i) ). A 'split-root' assay was performed to mimic a heterogeneous environment, after which a transcriptomic analysis identified groups of genes either locally or systemically regulated by P(i) starvation at the transcriptional level. These groups revealed coordinated regulations for various functions associated with P(i) starvation (including P(i) uptake, P(i) recovery, lipid metabolism, and metal uptake), and distinct roles for members in gene families. Genetic tools and physiological analyses revealed that genes that are locally regulated appear to be modulated mostly by root development independently of the internal P(i) content. By contrast, internal P(i) was essential to promote the activation of systemic regulation. Reducing the flow of P(i) had no effect on the systemic response, suggesting that a secondary signal, independent of P(i) , could be involved in the response. Furthermore, our results display a direct role for the transcription factor PHR1, as genes systemically controlled by low P(i) have promoters enriched with P1BS motif (PHR1-binding sequences). These data detail various regulatory systems regarding P(i) starvation responses (systemic versus local, and internal versus external P(i) ), and provide tools to analyze and classify the effects of P(i) starvation on plant physiology.

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The continuous production of vascular tissues through secondary growth results in radial thickening of plant organs and is pivotal for various aspects of plant growth and physiology, such as water transport capacity or resistance to mechanical stress. It is driven by the vascular cambium, which produces inward secondary xylem and outward secondary phloem. In the herbaceous plant Arabidopsis thaliana (Arabidopsis), secondary growth occurs in stems, in roots and in the hypocotyl. In the latter, radial growth is most prominent and not obscured by parallel ongoing elongation growth. Moreover, its progression is reminiscent of the secondary growth mode of tree trunks. Thus, the Arabidopsis hypocotyl is a very good model to study basic molecular mechanisms of secondary growth. Genetic approaches have succeeded in the identification of various factors, including peptides, receptors, transcription factors and hormones, which appear to participate in a complex network that controls radial growth. Many of these players are conserved between herbaceous and woody plants. In this review, we will focus on what is known about molecular mechanisms and regulators of vascular secondary growth in the Arabidopsis hypocotyl.

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The hypothesis that constitutive and inducible plant resistance against herbivores should trade-off because they use the same resources and impose costs to plant fitness has been postulated for a long time. Negative correlations between modes of deployment of resistance and defences have been observed across and within species in common garden experiments. It was therefore tested whether that pattern of resistance across genotypes follows a similar variation in patterns of gene expression and chemical defence production. Using the genetically tractable model Arabidopsis thaliana and different modes of induction, including the generalist herbivore Spodoptera littoralis, the specialist herbivore Pieris brassicae, and jasmonate application, constitutive and inducibility of resistance was measured across seven A. thaliana accessions that were previously selected based on constitutive levels of defence gene expression. According to theory, it was found that modes of resistance traded-off among accessions, particularly against S. littoralis, in which accessions investing in high constitutive resistance did not increase it substantially after attack and vice-versa. Accordingly, the average expression of eight genes involved in glucosinolate production negatively predicted larval growth across the seven accessions. Glucosinolate production and genes related to defence induction on healthy and herbivore-damaged plants were measured next. Surprisingly, only a partial correlation between glucosinolate production, gene expression, and the herbivore resistance results was found. These results suggest that the defence outcome of plants against herbivores goes beyond individual molecules or genes but stands on a complex network of interactions.

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The analysis of the activity of neuronal cultures is considered to be a good proxy of the functional connectivity of in vivo neuronal tissues. Thus, the functional complex network inferred from activity patterns is a promising way to unravel the interplay between structure and functionality of neuronal systems. Here, we monitor the spontaneous self-sustained dynamics in neuronal cultures formed by interconnected aggregates of neurons (clusters). Dynamics is characterized by the fast activation of groups of clusters in sequences termed bursts. The analysis of the time delays between clusters' activations within the bursts allows the reconstruction of the directed functional connectivity of the network. We propose a method to statistically infer this connectivity and analyze the resulting properties of the associated complex networks. Surprisingly enough, in contrast to what has been reported for many biological networks, the clustered neuronal cultures present assortative mixing connectivity values, meaning that there is a preference for clusters to link to other clusters that share similar functional connectivity, as well as a rich-club core, which shapes a"connectivity backbone" in the network. These results point out that the grouping of neurons and the assortative connectivity between clusters are intrinsic survival mechanisms of the culture.

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How do processes of power shape the urban environment in small Indian cities? On a day-to-day basis, who actually controls access to and the use of environmental resources? How is this done? Answering these questions contributes to our ability to develop a nuanced understanding the urban condition. In order to investigate these questions an actor-oriented approach is developed, drawing on the anthropological literatures on everyday governance and the everyday state. This conceptual framework informs an urban political ecology approach oriented towards everyday practices and the micro-politics of the (re)production of urban socio-natures. This thesis employs a mixed methods approach to qualitative research. Three cases are presented to explore: para (neighbourhood) clubs as governance actors, the governance of the urban pondscape, and the urban political ecology of solid waste management. These case studies serve to highlight how power shapes the (re)production of urban socio-natures through the everyday environmental governance practices of a complex network of governance actors. This work further demonstrates how multiple intersectionalities, including class, caste and access to political and social authority, shape these practices and their outcomes. Finally, the manner in which balances of power, place making and the formation of subject positions may both result from and shape everyday environmental governance practices and their outcomes is explored. This empirical investigation makes a number of contributions to the literature. It has explores the hereto-understudied topics of environmental governance in small cities in India, the urban political ecologies of non-piped water and of solid waste, and the role of clubs as governance actors. It further contributes to conversations within the literature on how to deepen and broaden Urban Political Ecology by engaging with everyday practices, and cases of ordinary, not-openly contested socio-natures. -- Comment les processus de pouvoir influencent-ils l'environnement urbain dans les petites villes indiennes ? Au quotidien, qui contrôle l'accès et l'utilisation des ressources environnementales ? Comment ce contrôle s'exerce-t-il ? Répondre à ces questions contribue au développement d'une compréhension nuancée de la condition urbaine. Afin d'explorer ces questions une approche actor-oriented de la gouvernance quotidienne est développée, faisant appel aux littératures anthropologiques de la gouvernance quotidienne et de l'everyday state. Ce cadre conceptuel établit ainsi une approche d'Urban Political Ecology orientée vers les pratiques quotidiennes et la micro- politique de la (re) production des socio-natures urbaines. Cette thèse emploie des méthodes qualitatives mixtes. Trois cas sont présentés afin d'étudier : les clubs para (quartier) comme acteurs de la gouvernance; la gouvernance de la pondscape urbaine; et l'urban political ecology de la gestion des déchets solides. Ces études de cas permettent de mettre en lumière la façon dont le pouvoir influence la (re)production des socio-natures urbaines par le biais des pratiques quotidiennes de gouvernance environnementale d'un réseau complexe d'acteurs. Ce travail démontre également comment plusieurs intersectionnalités, y compris la classe, la caste et l'accès au pouvoir politique et social, façonnent ces pratiques de gouvernance et leurs produits. Finalement, cette recherche explore la manière dont les équilibres de pouvoir, la fabrication de lieux et la formation de la position du sujet peuvent à la fois résulter de et contribuer à façonner les pratiques quotidiennes de gouvernance environnementale et leurs produits. Cette investigation empirique fait ainsi plusieurs contributions à la littérature. Elle explore les questions jusque-là sous-étudiées de la gouvernance environnementale dans les petites villes en Inde, de l'urban political ecology de l'eau non courante et des déchets solides, ainsi que du rôle des clubs comme acteurs de la gouvernance. Celle-ci contribue également à des débats sur la façon d'approfondir et d'élargir l'urban political ecology en travaillant sur les pratiques quotidiennes, et sur des cas de socio-natures ordinaires, pas ouvertement contestées.

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Cell division (mitosis) is a fundamental process in the life cycle of a cell. Equal distribution of chromosomes between the daughter cells is essential for the viability and well-being of an organism: loss of fidelity of cell division is a contributing factor in human cancer and also gives rise to miscarriages and genetic birth defects. For maintaining the proper chromosome number, a cell must carefully monitor cell division in order to detect and correct mistakes before they are translated into chromosomal imbalance. For this purpose an evolutionarily conserved mechanism termed the spindle assembly checkpoint (SAC) has evolved. The SAC comprises a complex network of proteins that relay and amplify mitosis-regulating signals created by assemblages called kinetochores (KTs). Importantly, minor defects in SAC signaling can cause loss or gain of individual chromosomes (aneuploidy) which promotes tumorigenesis while complete failure of SAC results in cell death. The latter event has raised interest in discovery of low molecular weight (LMW) compounds targeting the SAC that could be developed into new anti-cancer therapeutics. In this study, we performed a cell-based, phenotypic high-throughput screen (HTS) to identify novel LMW compounds that inhibit SAC function and result in loss of cancer cell viability. Altogether, we screened 65 000 compounds and identified eight that forced the cells prematurely out of mitosis. The flavonoids fisetin and eupatorin, as well as the synthetic compounds termed SACi2 and SACi4, were characterized in more detail utilizing versatile cell-based and biochemical assays. To identify the molecular targets of these SAC-suppressing compounds, we investigated the conditions in which SAC activity became abrogated. Eupatorin, SACi2 and SACi4 preferentially abolished the tensionsensitive arm of the SAC, whereas fisetin lowered also the SAC activity evoked by lack of attachments between microtubules (MTs) and KTs. Consistent with the abrogation of SAC in response to low tension, our data indicate that all four compounds inhibited the activity of Aurora B kinase. This essential mitotic protein is required for correction of erratic MT-KT attachments, normal SAC signaling and execution of cytokinesis. Furthermore, eupatorin, SACi2 and SACi4 also inhibited Aurora A kinase that controls the centrosome maturation and separation and formation of the mitotic spindle apparatus. In line with the established profound mitotic roles of Aurora kinases, these small compounds perturbed SAC function, caused spindle abnormalities, such as multi- and monopolarity and fragmentation of centrosomes, and resulted in polyploidy due to defects in cytokinesis. Moreover, the compounds dramatically reduced viability of cancer cells. Taken together, using a cell-based HTS we were able to identify new LMW compounds targeting the SAC. We demonstrated for the first time a novel function for flavonoids as cellular inhibitors of Aurora kinases. Collectively, our data support the concept that loss of mitotic fidelity due to a non-functional SAC can reduce the viability of cancer cells, a phenomenon that may possess therapeutic value and fuel development of new anti-cancer drugs.

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Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.

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As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.