145 resultados para trans-Golgi Network
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trans-Resveratrol (trans-3,5,4'-trihydroxystilbene) is a natural polyphenol that occurs in grapes, berries, peanuts, and several traditional medicines. A number of studies have demonstrated that this polyphenol holds promise against numerous age-associated diseases including cancer, diabetes, Alzheimer, cardiovascular and pulmonary diseases. In view of these studies, resveratrol's prospects for use in the clinics are rapidly accelerating. This review summarizes our work on the mechanisms involved in the intestinal absorption and its population pharmacokinetics. Finally, various targets of resveratrol and its therapeutic potential are described.
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Newly synthesized glucose transporter 4 (GLUT4) enters into the insulin-responsive storage compartment in a process that is Golgi-localized γ-ear-containing Arf-binding protein (GGA) dependent, whereas insulin-stimulated translocation is regulated by Akt substrate of 160 kDa (AS160). In the present study, using a variety of GLUT4/GLUT1 chimeras, we have analyzed the specific motifs of GLUT4 that are important for GGA and AS160 regulation of GLUT4 trafficking. Substitution of the amino terminus and the large intracellular loop of GLUT4 into GLUT1 (chimera 1-441) fully recapitulated the basal state retention, insulin-stimulated translocation, and GGA and AS160 sensitivity of wild-type GLUT4 (GLUT4-WT). GLUT4 point mutation (GLUT4-F5A) resulted in loss of GLUT4 intracellular retention in the basal state when coexpressed with both wild-type GGA and AS160. Nevertheless, similar to GLUT4-WT, the insulin-stimulated plasma membrane localization of GLUT4-F5A was significantly inhibited by coexpression of dominant-interfering GGA. In addition, coexpression with a dominant-interfering AS160 (AS160-4P) abolished insulin-stimulated GLUT4-WT but not GLUT4-F5A translocation. GLUT4 endocytosis and intracellular sequestration also required both the amino terminus and large cytoplasmic loop of GLUT4. Furthermore, both the FQQI and the SLL motifs participate in the initial endocytosis from the plasma membrane; however, once internalized, unlike the FQQI motif, the SLL motif is not responsible for intracellular recycling of GLUT4 back to the specialized compartment. Together, we have demonstrated that the FQQI motif within the amino terminus of GLUT4 is essential for GLUT4 endocytosis and AS160-dependent intracellular retention but not for the GGA-dependent sorting of GLUT4 into the insulin-responsive storage compartment.
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Conjugated linoleic acid (CLA) has been reported to exert beneficial physiological effects on body composition and the immune system. However, little information is available on the influence of CLA on immune function during early life periods. The present study evaluates the effect of feeding an 80:20 mixture of cis-9,trans-11- and trans-10,cis-12-CLA isomers duringgestation, suckling and early infancy on the systemic and mucosal immune responses of Wistar rats at three different time points: at the end of the suckling period (21-day-old rats), in early infancy (28-day-old rats), and later in life (adulthood). Cis-9,trans-11- and trans-10,cis-12-CLA isomers were detected in the milk of CLA-fed dams and in the plasma of all CLA-supplemented pups, and the highest content was achieved in those rats supplemented over the longest period. Dietary supplementation with that CLA mix enhances the systemic production of the main in vivo and ex vivo immunoglobulin (Ig) isotypes in 21- and 28-day-old rats. Moreover, CLA supplementation during suckling and early infancy also enhances the humoral immune defenses at intestinal level, by means of mucosal IgA increase, whereas down-regulates thesystemic lymphoproliferative response. Finally, we described herein how feeding a diet enriched with the same isomer mix of cis9,trans11- and trans10,cis12-CLA from gestation to adulthood improves the capacity of adult rats to achieve a specific systemic and mucosal immune responses. All these data support the immunomodulatory effects of dietary supplementation of CLA, particularly of the cis9,trans11-CLA isomer, during early stages of life on immune system development, as well as the long-term effects on the specific immune response in adult age.
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AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download
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The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.
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Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom+ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod+ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom+ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom+ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.
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Using combined emotional stimuli, combining photos of faces and recording of voices, we investigated the neural dynamics of emotional judgment using scalp EEG recordings. Stimuli could be either combioned in a congruent, or a non-congruent way.. As many evidences show the major role of alpha in emotional processing, the alpha band was subjected to be analyzed. Analysis was performed by computing the synchronization of the EEGs and the conditions congruent vs. non-congruent were compared using statistical tools. The obtained results demonstrate that scalp EEG ccould be used as a tool to investigate the neural dynamics of emotional valence and discriminate various emotions (angry, happy and neutral stimuli).
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This master thesis presents a research on the analysis of film tourism stakeholders in Catalonia applying the network analysis approach. The research aims to provide an analysis of the relations between local tourism stakeholders with local film offices through their websites. Therefore, the development of the present work involved the review of literature on the themes of film tourism and network analysis. Then the main stakeholders of film and tourism of Catalonia were identified and their websites analyzed. The measures indicators for network analysis such as centrality, closeness and betweenness degree have been applied on the analysis of the websites to determine the extent of the relations of film and tourism stakeholders in Catalonia. Results and conclusions are presented on the referred sections
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working paper
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Resum en anglès del projecte de recerca L'empresa xarxa a Catalunya. TIC, productivitat, competitivitat, salaris i beneficis a l'empresa catalana té com a objectiu principal constatar que la consolidació d'un nou model estratègic, organitzatiu i d'activitat empresarial, vinculat amb la inversió i l'ús de les TIC (o empresa xarxa), modifica substancialment els patrons de comportament dels resultats empresarials, en especial la productivitat, la competitivitat, les retribucions dels treballadors i el benefici. La contrastació empírica de les hipòtesis de treball l'hem feta per mitjà de les dades d'una enquesta a una mostra representativa de 2.038 empreses catalanes. Amb la perspectiva de l'impacte de la inversió i l'ús de les TIC no s'aprecia una relació directa entre els processos d'innovació digital i els resultats de l'activitat de l'empresa catalana. En aquest sentit, hem hagut de segmentar el teixit productiu català per a buscar les organitzacions en què el procés de coinnovació tecnològica digital i organitzativa és més present i en què la intensitat de l'ús del coneixement és un recurs molt freqüent per a poder copsar impactes rellevants en els principals resultats empresarials. Això és així perquè l'economia catalana, avui, presenta una estructura productiva dual.
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We investigate contributions to the provision of public goods on a network when efficient provision requires the formation of a star network. We provide a theoretical analysis and study behavior is a controlled laboratory experiment. In a 2x2 design, we examine the effects of group size and the presence of (social) benefits for incoming links. We find that social benefits are highly important. They facilitate convergence to equilibrium networks and enhance the stability and efficiency of the outcome. Moreover, in large groups social benefits encourage the formation of superstars: star networks in which the core contributes more than expected in the stage-game equilibrium. We show that this result is predicted by a repeated game equilibrium.
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We present a new asymptotic formula for the maximum static voltage in a simplified model for on-chip power distribution networks of array bonded integrated circuits. In this model the voltage is the solution of a Poisson equation in an infinite planar domain whose boundary is an array of circular pads of radius ", and we deal with the singular limit Ɛ → 0 case. In comparison with approximations that appear in the electronic engineering literature, our formula is more complete since we have obtained terms up to order Ɛ15. A procedure will be presented to compute all the successive terms, which can be interpreted as using multipole solutions of equations involving spatial derivatives of functions. To deduce the formula we use the method of matched asymptotic expansions. Our results are completely analytical and we make an extensive use of special functions and of the Gauss constant G
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Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.
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The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.
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We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.