78 resultados para multi-modal interaction


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The oxalatecarbonate pathway involves the oxidation of calcium oxalate to low-magnesium calcite and represents a potential long-term terrestrial sink for atmospheric CO2. In this pathway, bacterial oxalate degradation is associated with a strong local alkalinization and subsequent carbonate precipitation. In order to test whether this process occurs in soil, the role of bacteria, fungi and calcium oxalate amendments was studied using microcosms. In a model system with sterile soil amended with laboratory cultures of oxalotrophic bacteria and fungi, the addition of calcium oxalate induced a distinct pH shift and led to the final precipitation of calcite. However, the simultaneous presence of bacteria and fungi was essential to drive this pH shift. Growth of both oxalotrophic bacteria and fungi was confirmed by qPCR on the frc (oxalotrophic bacteria) and 16S rRNA genes, and the quantification of ergosterol (active fungal biomass) respectively. The experiment was replicated in microcosms with non-sterilized soil. In this case, the bacterial and fungal contribution to oxalate degradation was evaluated by treatments with specific biocides (cycloheximide and bronopol). Results showed that the autochthonous microflora oxidized calcium oxalate and induced a significant soil alkalinization. Moreover, data confirmed the results from the model soil showing that bacteria are essentially responsible for the pH shift, but require the presence of fungi for their oxalotrophic activity. The combined results highlight that the interaction between bacteria and fungi is essential to drive metabolic processes in complex environments such as soil.

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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

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Normal visual perception requires differentiating foreground from background objects. Differences in physical attributes sometimes determine this relationship. Often such differences must instead be inferred, as when two objects or their parts have the same luminance. Modal completion refers to such perceptual "filling-in" of object borders that are accompanied by concurrent brightness enhancement, in turn termed illusory contours (ICs). Amodal completion is filling-in without concurrent brightness enhancement. Presently there are controversies regarding whether both completion processes use a common neural mechanism and whether perceptual filling-in is a bottom-up, feedforward process initiating at the lowest levels of the cortical visual pathway or commences at higher-tier regions. We previously examined modal completion (Murray et al., 2002) and provided evidence that the earliest modal IC sensitivity occurs within higher-tier object recognition areas of the lateral occipital complex (LOC). We further proposed that previous observations of IC sensitivity in lower-tier regions likely reflect feedback modulation from the LOC. The present study tested these proposals, examining the commonality between modal and amodal completion mechanisms with high-density electrical mapping, spatiotemporal topographic analyses, and the local autoregressive average distributed linear inverse source estimation. A common initial mechanism for both types of completion processes (140 msec) that manifested as a modulation in response strength within higher-tier visual areas, including the LOC and parietal structures, is demonstrated, whereas differential mechanisms were evident only at a subsequent time period (240 msec), with amodal completion relying on continued strong responses in these structures.

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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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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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In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

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INTRODUCTION/OBJECTIVES: Detection rates for adenoma and early colorectal cancer (CRC) are insufficient due to low compliance towards invasive screening procedures, like colonoscopy.Available non-invasive screening tests have unfortunately low sensitivity and specificity performances.Therefore, there is a large unmet need calling for a cost-effective, reliable and non-invasive test to screen for early neoplastic and pre-neoplastic lesions AIMS & Methods: The objective is to develop a screening test able to detect early CRCs and adenomas.This test is based on a nucleic acids multi-gene assay performed on peripheral blood mononuclear cells (PBMCs).A colonoscopy-controlled feasibility study was conducted on 179 subjects.The first 92 subjects was used as training set to generate a statistical significant signature.Colonoscopy revealed 21 subjects with CRC,30 with adenoma bigger than 1 cm and 41 with no neoplastic or inflammatory lesions.The second group of 48 subjects (controls, CRC and polyps) was used as a test set and will be kept blinded for the entire data analysis.To determine the organ and disease specificity 38 subjects were used:24 with inflammatory bowel disease (IBD),14 with other cancers than CRC (OC).Blood samples were taken from each patient the day of the colonoscopy and PBMCs were purified. Total RNA was extracted following standard procedures.Multiplex RT-qPCR was applied on 92 different candidate biomarkers.Different univariate and multivariate statistical methods were applied on these candidates and among them 60 biomarkers with significant p-values (<0.01) were selected.These biomarkers are involved in several different biological functions as cellular movement,cell signaling and interaction,tissue and cellular development,cancer and cell growth and proliferation.Two distinct biomarker signatures are used to separate patients without lesion from those with cancer or with adenoma, named COLOX CRC and COLOX POL respectively.COLOX performances were validated using random resampling method, bootstrap. RESULTS: COLOX CRC and POL tests successfully separate patients without lesions from those with CRC (Se 67%,Sp 93%,AUC 0.87) and from those with adenoma bigger than 1cm (Se 63%,Sp 83%,AUC 0.77),respectively. 6/24 patients in the IBD group and 1/14 patients in the OC group have a positive COLOX CRC CONCLUSION: The two COLOX tests demonstrated a high sensitivity and specificity to detect the presence of CRCs and adenomas bigger than 1 cm.A prospective, multicenter, pivotal study is underway in order to confirm these promising results in a larger cohort.

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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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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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In this paper we unify, simplify, and extend previous work on the evolutionary dynamics of symmetric N-player matrix games with two pure strategies. In such games, gains from switching strategies depend, in general, on how many other individuals in the group play a given strategy. As a consequence, the gain function determining the gradient of selection can be a polynomial of degree N-1. In order to deal with the intricacy of the resulting evolutionary dynamics, we make use of the theory of polynomials in Bernstein form. This theory implies a tight link between the sign pattern of the gains from switching on the one hand and the number and stability of the rest points of the replicator dynamics on the other hand. While this relationship is a general one, it is most informative if gains from switching have at most two sign changes, as is the case for most multi-player matrix games considered in the literature. We demonstrate that previous results for public goods games are easily recovered and extended using this observation. Further examples illustrate how focusing on the sign pattern of the gains from switching obviates the need for a more involved analysis.