956 resultados para Interaction network
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Objective To compare the effectiveness and safety of three types of stents (sirolimus eluting, paclitaxel eluting, and bare metal) in people with and without diabetes mellitus. Design Collaborative network meta-analysis. Data sources Electronic databases (Medline, Embase, the Cochrane Central Register of Controlled Trials), relevant websites, reference lists, conference abstracts, reviews, book chapters, and proceedings of advisory panels for the US Food and Drug Administration. Manufacturers and trialists provided additional data. Review methods Network meta-analysis with a mixed treatment comparison method to combine direct within trial comparisons between stents with indirect evidence from other trials while maintaining randomisation. Overall mortality was the primary safety end point, target lesion revascularisation the effectiveness end point. Results 35 trials in 3852 people with diabetes and 10 947 people without diabetes contributed to the analyses. Inconsistency of the network was substantial for overall mortality in people with diabetes and seemed to be related to the duration of dual antiplatelet therapy (P value for interaction 0.02). Restricting the analysis to trials with a duration of dual antiplatelet therapy of six months or more, inconsistency was reduced considerably and hazard ratios for overall mortality were near one for all comparisons in people with diabetes: sirolimus eluting stents compared with bare metal stents 0.88 (95% credibility interval 0.55 to 1.30), paclitaxel eluting stents compared with bare metal stents 0.91 (0.60 to 1.38), and sirolimus eluting stents compared with paclitaxel eluting stents 0.95 (0.63 to 1.43). In people without diabetes, hazard ratios were unaffected by the restriction. Both drug eluting stents were associated with a decrease in revascularisation rates compared with bare metal stents in people both with and without diabetes. Conclusion In trials that specified a duration of dual antiplatelet therapy of six months or more after stent implantation, drug eluting stents seemed safe and effective in people both with and without diabetes.
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The transmembrane ligand ephrinB2 and its cognate Eph receptor tyrosine kinases are important regulators of embryonic blood vascular morphogenesis. However, the molecular mechanisms required for ephrinB2 transduced cellular signaling in vivo have not been characterized. To address this question, we generated two sets of knock-in mice: ephrinB2DeltaV mice expressed ephrinB2 lacking the C-terminal PDZ interaction site, and ephrinB2(5F) mice expressed ephrinB2 in which the five conserved tyrosine residues were replaced by phenylalanine to disrupt phosphotyrosine-dependent signaling events. Our analysis revealed that the homozygous mutant mice survived the requirement of ephrinB2 in embryonic blood vascular remodeling. However, ephrinB2DeltaV/DeltaV mice exhibited major lymphatic defects, including a failure to remodel their primary lymphatic capillary plexus into a hierarchical vessel network, hyperplasia, and lack of luminal valve formation. Unexpectedly, ephrinB2(5F/5F) mice displayed only a mild lymphatic phenotype. Our studies define ephrinB2 as an essential regulator of lymphatic development and indicate that interactions with PDZ domain effectors are required to mediate its functions.
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Tracking user’s visual attention is a fundamental aspect in novel human-computer interaction paradigms found in Virtual Reality. For example, multimodal interfaces or dialogue-based communications with virtual and real agents greatly benefit from the analysis of the user’s visual attention as a vital source for deictic references or turn-taking signals. Current approaches to determine visual attention rely primarily on monocular eye trackers. Hence they are restricted to the interpretation of two-dimensional fixations relative to a defined area of projection. The study presented in this article compares precision, accuracy and application performance of two binocular eye tracking devices. Two algorithms are compared which derive depth information as required for visual attention-based 3D interfaces. This information is further applied to an improved VR selection task in which a binocular eye tracker and an adaptive neural network algorithm is used during the disambiguation of partly occluded objects.
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Using the relational dyad as unit of analysis this study examines the effects of perceived influence and friendship ties on the formation and maintenance of cooperative relationships between corporate top executives. Specifically, it is argued that perceived influence as well as friendship ties between any two managers will enhance the likelihood that these managers collaborate with each other. Additionally, a negative interaction effect between perceived influence and friendship on cooperation is proposed. The empirical analyses draw on network data that have been collected among all members of the top two organizational levels for the strategy-making process in two multinational firms headquartered in Germany. Applying logistic regression based on QAP the empirical results support our hypotheses on the direct effects between perceived influence, friendship ties, and cooperative relationships in both companies. In addition, we find at least partial support for our assumption that perceived influence and friendship interact negatively with respect to their effect on cooperation. Seemingly, perceived influence is partially substituted by managerial friendship ties.
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Plectin is a versatile cytolinker of the plakin family conferring cell resilience to mechanical stress in stratified epithelia and muscles. It acts as a critical organizer of the cytoskeletal system by tethering various intermediate filament (IF) networks through its C-terminal IF-binding domain (IFBD). Mutations affecting the IFBD cause devastating human diseases. Here, we show that serine 4642, which is located in the extreme C-terminus of plectin, is phosphorylated in different cell lines. Phosphorylation of S4642 decreased the ability of plectin IFBD to associate with various IFs, as assessed by immunofluorescence microscopy and cell fractionation studies, as well as in yeast two-hybrid assays. Plectin phosphorylated at S4642 was reduced at sites of IF network anchorage along cell-substrate contacts in both skin and cultured keratinocytes. Treatment of SK-MEL-2 and HeLa cells with okadaic acid increased plectin S4642 phosphorylation, suggesting that protein phosphatase 2A dephosphorylates this residue. Moreover, plectin S4642 phosphorylation was enhanced after cell treatment with EGF, phorbol ester, sorbitol and 8-bromo-cyclic AMP, as well as during wound healing and protease-mediated cell detachment. Using selective protein kinase inhibitors, we identified two different kinases that modulate the phosphorylation of plectin S4642 in HeLa cells: MNK2, which is downstream of the ERK1/2-dependent MAPK cascade, and PKA. Our study indicates that phosphorylation of S4642 has an important regulatory role in the interaction of plectin with IFs and identifies a novel link between MNK2 and the cytoskeleton.
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Plectin, a cytolinker of the plakin family, anchors the intermediate filament (IF) network formed by keratins 5 and 14 (K5/K14) to hemidesmosomes, junctional adhesion complexes in basal keratinocytes. Genetic alterations of these proteins cause epidermolysis bullosa simplex (EBS) characterized by disturbed cytoarchitecture and cell fragility. The mechanisms through which mutations located after the documented plectin IF-binding site, composed of the plakin-repeat domain (PRD) B5 and the linker, as well as mutations in K5 or K14, lead to EBS remain unclear. We investigated the interaction of plectin C terminus, encompassing four domains, the PRD B5, the linker, the PRD C, and the C extremity, with K5/K14 using different approaches, including a rapid and sensitive fluorescent protein-binding assay, based on enhanced green fluorescent protein-tagged proteins (FluoBACE). Our results demonstrate that all four plectin C-terminal domains contribute to its association with K5/K14 and act synergistically to ensure efficient IF binding. The plectin C terminus predominantly interacted with the K5/K14 coil 1 domain and bound more extensively to K5/K14 filaments compared with monomeric keratins or IF assembly intermediates. These findings indicate a multimodular association of plectin with K5/K14 filaments and give insights into the molecular basis of EBS associated with pathogenic mutations in plectin, K5, or K14 genes.Journal of Investigative Dermatology advance online publication, 10 July 2014; doi:10.1038/jid.2014.255.
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Recent experiments suggest that humans can form and later retrieve new semantic relations unconsciously by way of hippocampus - the key structure thought to support conscious relational (episodic) memory. Given that the hippocampus subserves both conscious and unconscious relational encoding/retrieval, we expected the hippocampus to be place of unconscious-conscious interactions. This hypothesis was tested in an fMRI experiment on the interaction between the unconscious retrieval of face-associated occupations and the subsequent conscious retrieval of celebrities’ occupations. For subliminal encoding, masked combinations of an unfamiliar face and a written occupation (“actor” or “politician”) were subliminally presented. At test, we presented the former subliminal faces again, without occupations and masks, as conscious retrieval cues. We hypothesized that faces would trigger the unconscious reactivation of the associated occupation - actor or politician -, which in turn would facilitate or inhibit the subsequent conscious recollection of a celebrity’s occupation. Following the presentation of a former subliminal face, we presented the portrait of a celebrity that participants were required to sort according to “actor” or “politician”. Depending on whether the triggered unconscious occupation was congruent or incongruent with the celebrity’s occupation, we expected an expedited or retarded conscious retrieval process as reflected in reaction times. Conscious retrieval was expedited in the congruent condition, but there was no effect in the incongruent condition. fMRI data collected during subliminal relational encoding confirmed that the hippocampus was interacting with neocortical semantic storage sites. fMRI data collected at test indicated that the facilitated conscious retrieval of celebrity-associated occupations was related to deactivations in this same network spanning hippocampus and neocortical semantic storage sites. Hence, unconscious retrieval likely preactivated this network, which allowed for a sparing recruitment of additional neural resources to assist conscious retrieval. This finding supports the notion that consciously and unconsciously acquired relational memories are stored in a single, cohesive hippocampal-neocortical memory space.
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AIM To describe structural covariance networks of gray matter volume (GMV) change in 28 patients with first-ever stroke to the primary sensorimotor cortices, and to investigate their relationship to hand function recovery and local GMV change. METHODS Tensor-based morphometry maps derived from high-resolution structural images were subject to principal component analyses to identify the networks. We calculated correlations between network expression and local GMV change, sensorimotor hand function and lesion volume. To verify which of the structural covariance networks of GMV change have a significant relationship to hand function, we performed an additional multivariate regression approach. RESULTS Expression of the second network, explaining 9.1% of variance, correlated with GMV increase in the medio-dorsal (md) thalamus and hand motor skill. Patients with positive expression coefficients were distinguished by significantly higher GMV increase of this structure during stroke recovery. Significant nodes of this network were located in md thalamus, dorsolateral prefrontal cortex, and higher order sensorimotor cortices. Parameter of hand function had a unique relationship to the network and depended on an interaction between network expression and lesion volume. Inversely, network expression is limited in patients with large lesion volumes. CONCLUSION Chronic phase of sensorimotor cortical stroke has been characterized by a large scale co-varying structural network in the ipsilesional hemisphere associated specifically with sensorimotor hand skill. Its expression is related to GMV increase of md thalamus, one constituent of the network, and correlated with the cortico-striato-thalamic loop involved in control of motor execution and higher order sensorimotor cortices. A close relation between expression of this network with degree of recovery might indicate reduced compensatory resources in the impaired subgroup.
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Adherens junctions (AJs) and basolateral modules are important for the establishment and maintenance of apico-basal polarity. Loss of AJs and basolateral module members lead to tumor formation, as well as poor prognosis for metastasis. Recently, in mammalian studies it has been shown that loss of either AJ or basolateral module members deregulate Yorkie activity, the downstream transcriptional effector of the Hippo pathway. Importantly, it is unclear if AJ and basolateral components act through the same or parallel mechanisms to regulate Yorkie activity. Here, we dissect how loss of AJ and basolateral components affects Hippo signaling in Drosophila. Surprisingly, while scrib knock-down tissue displays increased reporter activity autonomously, α-cat knock-down tissue shows a cell autonomous decrease and a cell non-autonomous increase of Hippo reporter activity. We provided several lines of evidence to show the differential regulation in polarity protein localizations and oncogenic cooperative overgrowth by AJs and basolateral complexes. Finally, we show that Hippo pathway activity is induced in α-cat and scrib double knocked-down tissue. Taken together, our results provide evidence to show that basolateral modules and AJs act in parallel to modulate Hippo pathway activity. Non-muscle myosin II is an actomyosin component that interacts with the actin. Non-muscle myosin II also interacts with lgl, though the function of this interaction is not clear. Our lab demonstrated that modulating F-actin regulates Hippo pathway activity, and lgl also has been described as a Hippo pathway regulator. Therefore we suspect that myosin II is also involved in Hippo pathway regulation. We first characterized non-muscle Myosin II as a novel tumor suppressor gene by affecting Hippo pathway activity. Upstream regulators of Myosin II, members in the Rho signaling pathway, also displayed similar phenotypes as the Myosin II knock-down tissues. Apoptosis is also induced in myosin II knock-down tissues, however, blocking cell death does not affect myosin II knock-down induced Hippo activation. Our data suggested hyperactivating myosin II induced F-actin accumulation so therefore induces Hippo target activation. Unexpectedly, we also observed that reducing F-actin activity induced Hippo target activation in vivo. These controversial data indicated that actomyosin may regulate the Hippo pathway through multiple mechanisms.
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Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^
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My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.
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The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^
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Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD
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A heterogeneous network, mainly based on nodes that use harvested energy to self-energize is presented and its use demonstrated. The network, mostly kinetically powered, has been used for the localization of herds in grazing areas under extreme climate conditions. The network consists of secondary and primary nodes. The former, powered by a kinetic generator, take advantage of animal movements to broadcast a unique identifier. The latter are battery-powered and gather secondarynode transmitted information to provide it, along with position and time data, to a final base station in charge of the animal monitoring. Because a limited human interaction is desirable, the aim of this network is to reduce the battery count of the system.
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The effect caused by ground fault current in a complex system of interacting electrodes is theoretically studied. The calculation applies to a specific case in which a set of interconnected electrodes, which are part of a grounding facility network, are activated by a ground fault current. Transferred potentials to adjacent passive electrodes are calculated and the most relevant parameters of the electrode system are evaluated. Finally, the convenience of connecting the grounding electrodes is discussed.