972 resultados para Interaction network
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Introduction: Coordination is a strategy chosen by the central nervous system to control the movements and maintain stability during gait. Coordinated multi-joint movements require a complex interaction between nervous outputs, biomechanical constraints, and pro-prioception. Quantitatively understanding and modeling gait coordination still remain a challenge. Surgeons lack a way to model and appreciate the coordination of patients before and after surgery of the lower limbs. Patients alter their gait patterns and their kinematic synergies when they walk faster or slower than normal speed to maintain their stability and minimize the energy cost of locomotion. The goal of this study was to provide a dynamical system approach to quantitatively describe human gait coordination and apply it to patients before and after total knee arthroplasty. Methods: A new method of quantitative analysis of interjoint coordination during gait was designed, providing a general model to capture the whole dynamics and showing the kinematic synergies at various walking speeds. The proposed model imposed a relationship among lower limb joint angles (hips and knees) to parameterize the dynamics of locomotion of each individual. An integration of different analysis tools such as Harmonic analysis, Principal Component Analysis, and Artificial Neural Network helped overcome high-dimensionality, temporal dependence, and non-linear relationships of the gait patterns. Ten patients were studied using an ambulatory gait device (Physilog®). Each participant was asked to perform two walking trials of 30m long at 3 different speeds and to complete an EQ-5D questionnaire, a WOMAC and Knee Society Score. Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. The outcomes of the eight patients undergoing total knee arthroplasty, recorded pre-operatively and post-operatively at 6 weeks, 3 months, 6 months and 1 year were compared to 2 age-matched healthy subjects. Results: The new method provided coordination scores at various walking speeds, ranged between 0 and 10. It determined the overall coordination of the lower limbs as well as the contribution of each joint to the total coordination. The difference between the pre-operative and post-operative coordination values were correlated with the improvements of the subjective outcome scores. Although the study group was small, the results showed a new way to objectively quantify gait coordination of patients undergoing total knee arthroplasty, using only portable body-fixed sensors. Conclusion: A new method for objective gait coordination analysis has been developed with very encouraging results regarding the objective outcome of lower limb surgery.
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Background Alzheimer's disease (AD) is the leading form of dementia worldwide. The Aß-peptide is believed to be the major pathogenic compound of the disease. Since several years it is hypothesized that Aß impacts the Wnt signaling cascade and therefore activation of this signaling pathway is proposed to rescue the neurotoxic effect of Aß. Findings Expression of the human Aß42 in the Drosophila nervous system leads to a drastically shortened life span. We found that the action of Aß42 specifically in the glutamatergic motoneurons is responsible for the reduced survival. However, we find that the morphology of the glutamatergic larval neuromuscular junctions, which are widely used as the model for mammalian central nervous system synapses, is not affected by Aß42 expression. We furthermore demonstrate that genetic activation of the Wnt signal transduction pathway in the nervous system is not able to rescue the shortened life span or a rough eye phenotype in Drosophila. Conclusions Our data confirm that the life span is a useful readout of Aß42 induced neurotoxicity in Drosophila; the neuromuscular junction seems however not to be an appropriate model to study AD in flies. Additionally, our results challenge the hypothesis that Wnt signaling might be implicated in Aß42 toxicity and might serve as a drug target against AD.
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This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.
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In this article, we analyze a multilingual interaction in a students' working group and hypothesize a correlation between management of languages in interaction and leadership. We consider Codeswitching as one of the most relevant observables in multilingual interaction and attempt to analyze how it is used by speakers. After a brief presentation of three theoretical and analytical conceptions of Code-switching in interaction (Auer, Mondada & Myers Scotton), we define Code-switching as an interactional, strategical, multilingual resource exploited by speakers to achieve various interactionaland non interactional goals. We then show in two CA-like analysis how multilingual strategical resources occur in the interactional practices of the analyzed working group, and how they are exploited by speakers in order to organize interaction, work, tasks, and to construct one's leadership.We also consider the metadiscourses of the students about their own practices and multilingualism in general, in order to confront them to their actual multilingual practices. We draw the hypothesis that discrepancies observed between metadiscourses and practices can be explained through the development of (meta)discourses showing a unilingual conception in describing multilingual practices.
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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.
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In this paper we examine whether variations in the level of public capital across Spain‟s Provinces affected productivity levels over the period 1996-2005. The analysis is motivated by contemporary urban economics theory, involving a production function for the competitive sector of the economy („industry‟) which includes the level of composite services derived from „service‟ firms under monopolistic competition. The outcome is potentially increasing returns to scale resulting from pecuniary externalities deriving from internal increasing returns in the monopolistic competition sector. We extend the production function by also making (log) labour efficiency a function of (log) total public capital stock and (log) human capital stock, leading to a simple and empirically tractable reduced form linking productivity level to density of employment, human capital and public capital stock. The model is further extended to include technological externalities or spillovers across provinces. Using panel data methodology, we find significant elasticities for total capital stock and for human capital stock, and a significant impact for employment density. The finding that the effect of public capital is significantly different from zero, indicating that it has a direct effect even after controlling for employment density, is contrary to some of the earlier research findings which leave the question of the impact of public capital unresolved.
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B cells are the primary targets of infection for mouse mammary tumor virus (MMTV). However, for productive retroviral infection, T cell stimulation through the virally-encoded superantigen (SAG) is necessary. It activates B cells and leads to cell division and differentiation. To characterize the role of B cell differentiation for the MMTV life cycle, we studied the course of infection in transgenic mice deficient for CD28/CTLA4-B7 interactions (mCTLA4-H gamma 1 transgenic mice). B cell infection occurred in CTLA4-H gamma 1 transgenic mice as integrated proviral DNA could be detected in draining lymph node cells early after infection by polymerase chain reaction analysis. In mice expressing I-E, B cells were able to present the viral SAG efficiently to V beta 6+ T cells. These cells expanded specifically and were triggered to express the activation marker CD69. Further stages of progression of infection appeared to be defective. Kinetics experiments indicated that T and B cell stimulation stopped more rapidly than in control mice. B cells acquired an activated CD69+ phenotype, were induced to produce IgM but only partially switched to IgG secretion. Finally, the dissemination of infected cells to other lymph nodes and spleen was reduced and the peripheral deletion of V beta 6+ T cells was minimal. In contrast, in mice lacking I-E, T cell stimulation was also impaired and B cell activation undetectable. These data implicate B7-dependent cellular interactions for superantigenic T cell stimulation by low-affinity TCR ligands and suggest a role of B cell differentiation in viral dissemination and peripheral T cell deletion.
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Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.
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Two published case reports showed that addition of risperidone (1 and 2 mg/d) to a clozapine treatment resulted in a strong increase of clozapine plasma levels. As clozapine is metabolized by cytochrome P450 isozymes, a study was initiated to assess the in vivo interaction potential of risperidone on various cytochrome P450 isozymes. Eight patients were phenotyped with dextromethorphan (CYP2D6), mephenytoin (CYP2C19), and caffeine (CYP1A2) before and after the introduction of risperidone. Before risperidone, all eight patients were phenotyped as being extensive metabolizers of CYP2D6 and CYP2C19. Risperidone at dosages between 2 and 6 mg/d does not appear to significantly inhibit CYP1A2 and CYP2C19 in vivo (median plasma paraxanthine/caffeine ratios before and after risperidone: 0.65, 0.69; p = 0.89; median urinary (S)/(R) mephenytoin ratios before and after risperidone:0.11, 0.12; p = 0.75). Although dextromethorphan metabolic ratio is significantly increased by risperidone (median urinary dextromethorphan/dextrorphan ratios before and after risperidone: 0.010, 0.018; p = 0.042), risperidone can be considered a weak in vivo CYP2D6 inhibitor, as this increase is modest and none of the eight patients was changed from an extensive to a poor metabolizer. The reported increase of clozapine concentrations by risperidone can therefore not be explained by an inhibition of CYP1A2, CYP2D6, CYP2C19 or by any combination of the three.
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OBJECTIVE: To assess the relationships and possible interactions between polymorphisms related to HDL levels and alcohol consumption. METHODS: Cross-sectional population-based study including 2863 women and 2546 men aged 35-75 years (CoLaus study). Alcohol intake was assessed by the reported alcohol consumption of the last 7 days. Nineteen candidate genes known to influence HDL levels were studied. RESULTS: Alcohol consumption increased HDL cholesterol levels in both genders. After multivariate adjustment for gender, age, body mass index, smoking, hypolipidaemic drug treatment, physical activity and alcohol consumption, APOA5, CETP, LIPC and LPL gene polymorphisms were significantly (10(-5) threshold) related with HDL cholesterol levels, while no genexalcohol intake interaction was found for all SNPs studied. ABCA1 polymorphisms were related to HDL cholesterol levels on bivariate analysis but the relationship was no longer significant after multivariate analysis. CONCLUSION: Our data confirm the association of alcohol consumption and of APOA5, CETP, LIPC and LPL gene polymorphisms with HDL cholesterol levels. Conversely, no genexalcohol consumption interactions were found, suggesting that the effect of alcohol consumption on HDL cholesterol levels is not mediated via a modulation of HDL related genes.
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Colistin is a last resort's antibacterial treatment in critically ill patients with multi-drug resistant Gram-negative infections. As appropriate colistin exposure is the key for maximizing efficacy while minimizing toxicity, individualized dosing optimization guided by therapeutic drug monitoring is a top clinical priority. Objective of the present work was to develop a rapid and robust HPLC-MS/MS assay for quantification of colistin plasma concentrations. This novel methodology validated according to international standards simultaneously quantifies the microbiologically active compounds colistin A and B, plus the pro-drug colistin methanesulfonate (colistimethate, CMS). 96-well micro-Elution SPE on Oasis Hydrophilic-Lipophilic-Balanced (HLB) followed by direct analysis by Hydrophilic Interaction Liquid Chromatography (HILIC) with Ethylene Bridged Hybrid - BEH - Amide phase column coupled to tandem mass spectrometry allows a high-throughput with no significant matrix effect. The technique is highly sensitive (limit of quantification 0.014 and 0.006μg/mL for colistin A and B), precise (intra-/inter-assay CV 0.6-8.4%) and accurate (intra-/inter-assay deviation from nominal concentrations -4.4 to +6.3%) over the clinically relevant analytical range 0.05-20μg/mL. Colistin A and B in plasma and whole blood samples are reliably quantified over 48h at room temperature and at +4°C (<6% deviation from nominal values) and after three freeze-thaw cycles. Colistimethate acidic hydrolysis (1M H2SO4) to colistin A and B in plasma was completed in vitro after 15min of sonication while the pro-drug hydrolyzed spontaneously in plasma ex vivo after 4h at room temperature: this information is of utmost importance for interpretation of analytical results. Quantification is precise and accurate when using serum, citrated or EDTA plasma as biological matrix, while use of heparin plasma is not appropriate. This new analytical technique providing optimized quantification in real-life conditions of the microbiologically active compounds colistin A and B offers a highly efficient tool for routine therapeutic drug monitoring aimed at individualizing drug dosing against life-threatening infections.