299 resultados para complex emergence


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In vertebrates, the RAD51 protein is required for genetic recombination, DNA repair, and cellular proliferation. Five paralogs of RAD51, known as RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3, have been identified and also shown to be required for recombination and genome stability. At the present time, however, very little is known about their biochemical properties or precise biological functions. As a first step toward understanding the roles of the RAD51 paralogs in recombination, the human RAD51C and XRCC3 proteins were overexpressed and purified from baculovirus-infected insect cells. The two proteins copurify as a complex, a property that reflects their endogenous association observed in HeLa cells. Purified RAD51C--XRCC3 complex binds single-stranded, but not duplex DNA, to form protein--DNA networks that have been visualized by electron microscopy.

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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

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Although various foot models were proposed for kinematics assessment using skin makers, no objective justification exists for the foot segmentations. This study proposed objective kinematic criteria to define which foot joints are relevant (dominant) in skin markers assessments. Among the studied joints, shank-hindfoot, hindfoot-midfoot and medial-lateral forefoot joints were found to have larger mobility than flexibility of their neighbour bonesets. The amplitude and pattern consistency of these joint angles confirmed their dominancy. Nevertheless, the consistency of the medial-lateral forefoot joint amplitude was lower. These three joints also showed acceptable sensibility to experimental errors which supported their dominancy. This study concluded that to be reliable for assessments using skin markers, the foot and ankle complex could be divided into shank, hindfoot, medial forefoot, lateral forefoot and toes. Kinematics of foot models with more segments must be more cautiously used.

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Utilization behavior (UB) consists of reaching out and using objects in the environment in an automatic manner and out of context. This behavior has been correlated to frontal lobe dysfunction, especially of the right hemisphere. We describe a 60-year-old woman, affected by a glioblastoma located in the right frontal region, who presented with intermittent UB of the mobile phone as the main clinical manifestation of partial complex status epilepticus. Video/EEG studies showed a striking correlation between mobile phone utilization and ictal epileptic activity. Clinical and EEG findings were markedly reduced after the introduction of antiepileptic drugs. This case study suggests that UB may be added to the symptoms described for partial seizures originating from frontal areas.

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OBJECTIVE: To emphasize that complex regional pain syndrome (CRPS), a disabling disorder with the implication of aberrant inflammation, vasomotor dysfunction, and maladaptive neuroplasticity, might be treated with a high dose of intravenous immunoglobulin infusions (IVIG). METHODS: We describe a patient who presented with CRPS in the acute phase of the disease. RESULTS: The CRPS developed secondary to sciatic compression in a young patient and was treated within 10 days by high-dose IVIG (2 g/kg). It resolved completely within days after infusions. DISCUSSION: This observational study emphasizes that high-dose IVIG may be a treatment option in the acute phase of CRPS.

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25 patients with acute myocardial infarction pain lasting more than 20 minutes which was not relieved by nitrates, whose ECGs showed ST segment elevations of 1 mm or more in 2 or more ECG leads, and who presented less than 3 hours after onset of their symptoms were randomly assigned to one of 2 thrombolytic treatment groups: a single intravenous bolus of anisoylated plasminogen streptokinase activator complex (APSAC) 30U in 5 minutes or an intravenous infusion of streptokinase 1,500,000U over 60 minutes. 3 to 4 hours after the administration of the thrombolytic agent, all patients received intravenous heparin at full dosage for 24 hours. The patency of the infarct-related coronary vessels was assessed by angiography 1 to 4 hours after administration of the thrombolytic agent. Clinical signs, ECGs, pulse, blood pressure and temperature were monitored regularly for 24 hours after treatment or as clinically appropriate. APSAC seemed to be at least as effective as streptokinase in terms of patency of the infarct-related vessel (92% vs 63%, respectively). The adverse events were similar and none was life-threatening. APSAC and streptokinase caused similar falls in blood fibrinogen levels. APSAC, given as a bolus injection over 5 minutes, was easier to administer than streptokinase, which was given as an infusion during 60 minutes.

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In the past decade, many studies have been conducted to determine the health effects induced by exposure to engineered nanomaterials (NMs). Specifically for exposure via inhalation, numerous in vitro and animal in vivo inhalation toxicity studies on several types of NMs have been published. However, these results are not easily extrapolated to judge the effects of inhaling NMs in humans, and few published studies on the human response to inhalation of NMs exist. Given the emergence of more industries utilizing iron oxide nanoparticles as well as more nanomedicine applications of superparamagnetic iron oxide nanoparticles (SPIONs), this review presents an overview of the inhalation studies that have been conducted in humans on iron oxides. Both occupational exposure studies on complex iron oxide dusts and fumes, as well as human clinical studies on aerosolized, micron-size iron oxide particles are discussed. Iron oxide particles have not been described to elicit acute inhalation response nor promote lung disease after chronic exposure. The few human clinical studies comparing inhalation of fine and ultrafine metal oxide particles report no acute changes in the health parameters measured. Taken together existing evidence suggests that controlled human exposure to iron oxide nanoparticles, such as SPIONs, could be conducted safely.

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Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.

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It has been suggested that determination of the neutrophil elastase alpha1-proteinase inhibitor complex (E-alpha1PI) improves the diagnosis of bacterial infection in newborns. We evaluated the use of E-alpha1PI measurements in 143 newborns, consecutively admitted to a tertiary intensive care unit, employing a new random access assay and a sampling procedure that minimises post-collection artefacts. The 95% range for noninfected newborns was 20-110 microg/l up to the 5th day of life and 20-85 microg/l thereafter. The sensitivity as to the diagnosis of culture-proven bloodstream infection was 80% for E-alpha1PI, 86% for the immature to total neutrophil ratio, 64% for C-reactive protein and 37% for the total white blood cell count. The corresponding specificity amounted to 97%, 85%, 85% and 86%, respectively. E-alpha1PI increases preceded elevations of C-reactive protein by 18 h. Like C-reactive protein, E-alpha1PI levels did not distinguish between bloodstream infection and non-bacterial inflammatory responses. Results of E-alpha1PI became available within 1 h of collection and usually 2-3 h before manual leucocyte counts. CONCLUSION: Determination of neutrophil elastase alpha1-proteinase inhibitor levels yields diagnostic advantages comparable to those of manual differential counts but provide faster turnaround times.

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BACKGROUND AND METHODS:: The objectives of this article were to systematically describe and examine the novel roles and responsibilities assumed by nurses in a forensic consultation for victims of violence at a University Hospital in French-speaking Switzerland. Utilizing a case study methodology, information was collected from two main sources: (a) discussion groups with nurses and forensic pathologists and (b) a review of procedures and protocols. Following a critical content analysis, the roles and responsibilities of the forensic nurses were described and compared with the seven core competencies of advanced nursing practice as outlined by Hamric, Spross, and Hanson (2009). RESULTS:: Advanced nursing practice competencies noted in the analysis included "direct clinical practice," "coaching and guidance," and "collaboration." The role of the nurse in terms of "consultation," "leadership," "ethics," and "research" was less evident in the analysis. DISCUSSION AND CONCLUSION:: New forms of nursing are indeed practiced in the forensic clinical setting, and our findings suggest that nursing practice in this domain is following the footprints of an advanced nursing practice model. Further reflections are required to determine whether the role of the forensic nurse in Switzerland should be developed as a clinical nurse specialist or that of a nurse practitioner.

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A significant number of environmental microorganisms can cause serious, even fatal, acute and chronic infections in humans. The severity and outcome of each type of infection depends on the expression of specific bacterial phenotypes controlled by complex regulatory networks that sense and respond to the host environment. Although bacterial signals that contribute to a successful acute infection have been identified in a number of pathogens, the signals that mediate the onset and establishment of chronic infections have yet to be discovered. We identified a volatile, low molecular weight molecule, 2-amino acetophenone (2-AA), produced by the opportunistic human pathogen Pseudomonas aeruginosa that reduces bacterial virulence in vivo in flies and in an acute mouse infection model. 2-AA modulates the activity of the virulence regulator MvfR (multiple virulence factor regulator) via a negative feedback loop and it promotes the emergence of P. aeruginosa phenotypes that likely promote chronic lung infections, including accumulation of lasR mutants, long-term survival at stationary phase, and persistence in a Drosophila infection model. We report for the first time the existence of a quorum sensing (QS) regulated volatile molecule that induces bistability phenotype by stochastically silencing acute virulence functions in P. aeruginosa. We propose that 2-AA mediates changes in a subpopulation of cells that facilitate the exploitation of dynamic host environments and promote gene expression changes that favor chronic infections.

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PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.