994 resultados para Spatial Light Modulators


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The ring sulfoxidation of thioridazine (THD), a widely used neuroleptic agent, yields two diastereoisomeric pairs, fast- and slow-eluting (FE and SE) thioridazine 5-sulfoxide (THD 5-SO). Until now, studies in which concentrations of these metabolites were measured in THD-treated patients have revealed no significant differences in their concentrations. Preliminary experiments in our laboratory had shown that sunlight and, to a lesser extent, dim daylight led to racemization and probably also to photolysis of the diastereoisomeric pairs as measured by high-performance liquid chromatography. Similar results were also obtained with direct UV light (UV lamp). In appropriate light-protected conditions, THD, northioridazine, mesoridazine, sulforidazine, and FE and SE THD 5-SO were measured in 11 patients treated with various doses of THD for at least 1 week. Significantly higher concentrations of the FE stereoisomeric pair were found. The concentration ratios THD 5-SO (FE)/THD 5-SO (SE) ranged from 0.89 to 1.75 in plasma and from 1.15 to 2.05 in urine. Because it is known that the ring sulfoxide contributes to the cardiotoxicity of the drug even more potently than the parent compound does, these results justify further studies to determine whether there is stereoselectivity in the cardiotoxicity of THD 5-SO.

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MR structural T1-weighted imaging using high field systems (>3T) is severely hampered by the existing large transmit field inhomogeneities. New sequences have been developed to better cope with such nuisances. In this work we show the potential of a recently proposed sequence, the MP2RAGE, to obtain improved grey white matter contrast with respect to conventional T1-w protocols, allowing for a better visualization of thalamic nuclei and different white matter bundles in the brain stem. Furthermore, the possibility to obtain high spatial resolution (0.65 mm isotropic) R1 maps fully independent of the transmit field inhomogeneities in clinical acceptable time is demonstrated. In this high resolution R1 maps it was possible to clearly observe varying properties of cortical grey matter throughout the cortex and observe different hippocampus fields with variations of intensity that correlate with known myelin concentration variations.

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Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.

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This study assesses gender differences in spatial and non-spatial relational learning and memory in adult humans behaving freely in a real-world, open-field environment. In Experiment 1, we tested the use of proximal landmarks as conditional cues allowing subjects to predict the location of rewards hidden in one of two sets of three distinct locations. Subjects were tested in two different conditions: (1) when local visual cues marked the potentially-rewarded locations, and (2) when no local visual cues marked the potentially-rewarded locations. We found that only 17 of 20 adults (8 males, 9 females) used the proximal landmarks to predict the locations of the rewards. Although females exhibited higher exploratory behavior at the beginning of testing, males and females discriminated the potentially-rewarded locations similarly when local visual cues were present. Interestingly, when the spatial and local information conflicted in predicting the reward locations, males considered both spatial and local information, whereas females ignored the spatial information. However, in the absence of local visual cues females discriminated the potentially-rewarded locations as well as males. In Experiment 2, subjects (9 males, 9 females) were tested with three asymmetrically-arranged rewarded locations, which were marked by local cues on alternate trials. Again, females discriminated the rewarded locations as well as males in the presence or absence of local cues. In sum, although particular aspects of task performance might differ between genders, we found no evidence that women have poorer allocentric spatial relational learning and memory abilities than men in a real-world, open-field environment.

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The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

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Describimos la distribución espacial de individuos de Pinus uncinata clasificados según su forma de crecimiento y tamaño en dos ecotonos poco perturbados del límite altitudinal del árbol situados en los Pirineos Centrales españoles (Ordesa, O; Tessó, T). En cada sitio situamos una parcela rectangular (30 140 m), que incluía los límites del árbol y del bosque, y cuyo lado mayor seguía el gradiente altitudinal. En ambos sitios, los individuos vivos eran más grandes y tenían un mayor número de cohortes de acículas pendiente abajo. La distribución de las clases de individuos según su forma de crecimiento y tamaño en el sitio O seguía una secuencia de mayor tamaño pendiente abajo, desde abundantes individuos policórmicos arbustivos (krummholz) con pocas cohortes de acículas (1-3) hasta individuos arbóreos mayores unicórmicos con varias cohortes de acículas (4-12). Por el contrario, los cambios estructurales en el ecotono del sitio T fueron graduales y no siguieron de forma tan clara dicha secuencia

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Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

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This work aims to characterise the current autotrophic compartment of the Albufera des Grau coastal lagoon (Menorca, Balearic Islands) and to assess the relationship between the submerged macrophytes and the limnological parameters of the lagoon. During the study period the submerged vegetation was dominated by the macrophyte Ruppia cirrhosa, which formed dense extensive meadows covering 79% of the surface. Another macrophyte species, Potamogeton pectinatus, was also observed but only forming small stands near the rushing streams. Macroalgae were only occasionally observed. Macrophyte biomass showed a clear seasonal trend, with maximum values in July. The biomass of R. cirrhosa achieved 1760 g DW m-2, the highest biomass ever reported for this species in the literature. The seasonal production-decomposition cycle of the macrophyte meadows appears to drive the nutrient dynamics and carbon fluxes in the lagoon. Despite the significant biomass accumulation and the absence of a washout of nutrients and organic matter to the sea, the lagoon did not experience a dystrophic collapse. These results indicate that internal metabolism is more important than exchange processes in the lagoon.

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SUMMARY : Phytochromes constitute a family of red/far-red photoreceptors regulating all the major transitions during the life cycle of plants. In Arabidopsis, five members: phyA,_ B, C, D and E, were identified. Phytochromes are synthesized in their inactive red-light absorbing form called Pr. Upon light absorbance they convert to the far-red light absorbing Pfr form. The Pfr form is the active conformer which converts back to the Pr form either rapidly upon far-red perception or in a slower process called dark reversion. ph~A represents an exception, in that it does not significantly dark-revert and two specific processes have been developed by the plants to decrease the amount of biologically active phyA. The first one is alight-dependent repression of the PHYA gene expression and the second one is alight-dependent degradation of the phyA protein. The latter is the most efficient process to rapidly decrease the level of active phyA. The ability of plants to regulate the amount of active phyA is critical in a far-red rich environment, a situation observed under a canopy. In these conditions, phyA is essential to induce the germination and the deetiolation of the young seedling. Later in the development the ability of phyA to repress growth counteracts the shade avoidance response. Therefore decreasing the amount of phyA allows stem growth and to compete with neighbours for the light. In this thesis, I investigate the light-dependent degradation of phyA. I developed a reverse genetic approach based on the systematic analysis of the light-dependent accumulation of phyA in the different cullin mutant cull, cul3a; cul3b and cul4. This analysis allowed me to show that CUL1 and CUL3A-based E3 ligase complexes are involved in the regulation of phyA degradation. Surprisingly, our results also demonstrate that cu14 is not affected in the degradation of phyA whereas constitutive Photomorphogenic 1 (COP1) a subunit of one CUL4based E3 complex was reported to be involved. Further investigations showed that the phenotype of cop1 is conditional, the mutant being defective in phyA degradation only in the presence of metabolisable sugars. I also showed that phyA is degraded by a proteasome-dependent mechanism both in the cytoplasm and in the nucleus using mutants and transgenic lines affected in the localization of phyA. Interestingly, I observed that phyA degradation was faster in the nucleus than in the cytosol and that rapid degradation of Pr also occurred in the nucleus suggesting that cytosolic accumulation of phyA in the dark is a way to regulate its proteolysis. Finally, we identify a short region similar to a PEST sequence required for phyA stability and we developed a unbiased genetic screen to identify new components involved in the regulation of the light-dependent degradation of phyA. The significance of these results are discussed. RESUME : Les phytochromes (phy) constituent une famille de photorécepteurs absorbant la lumière rouge et rouge lointaine et régulant toutes les étapes de transitions majeures dans la vie des plantes. Chez Arabidopsis, cinq membres : phyA, B, C, D et E ont été identifiés. Les phytochromes sont synthétisés sous une forme inactive appelée Pr absorbant la lumière rouge. Après perception de lumière ils passent sous une forme active Pfr absorbant dans le rouge lointain. La forme Pfr peut retourner sous la forme Pr après absorption de lumiëre rouge lointaine ou dans un processus lent appelé «réversion à l'obscurité ». phyA représente une exception à cette règle car il ne retoune pas significativement sous sa forme inactive dans le noir. Deux processus spécifiques ont donc été développés pour diminuer le taux de phyA actif. Le premier consiste en la répression du gène PHYA en condition de lumière et le second en une dégradation induite par la lumière de la protéine phyA. Ce dernier processus est le plus efficace pour diminuer rapidement le niveau de phyA. La capacité des plantes à réguler le taux de phyA actifs est critique dans un environnement riche en lumière rouge lointaine, une situation observée sous une canopée. Sous une canopée, phyA est essentiel pour induire la germination et la dé-étiolation de la jeune pousse. Plus tard dans le développement la capacité de phyA de réprimer la croissance freine la «réponse à l'évitement de l'ombre ». Par conséquent diminuer le taux de phyA permet la croissance de la tige et donc de rentrer en compétition pour la lumière avec les plantes avoisinantes. Dans cette thèse, j'ai étudié la dégradation de phyA. J'ai développé une approche génétique inverse basée sur l'analyse systématique de l'accumulation de phyA en condition de lumière dans les différents mutants cullin, cul1, cul3a, cul3b et cul4. Ces analyses nous ont permis d'identifier qu'un complexe E3 ligase CUL1 et un complexe E3 ligase CUL3A sont impliqués dans la régulation de la dégradation de phyA. Mes résultats démontrent aussi que le mutant cul4 n'est pas affecté dans la dégradation de phyA alors que Çonstitutive Photomorphogenic 1 (COPI) une sous unité d'un complexe CUL4 à été identifier dans la régulation de cette dégradation. Des analyses supplémentaires suggèrent que l'effet de la mutation cop1 est dépendante dë la présence de sucres métabolisables. J'ai aussi montré que phyA est dégradé dans le noyau et dans le cytoplasme par un mécanisme dépendant du protéasome et que la dégradation dans le.noyau est non seulement aspécifique de la forme Pr ou Pfr mais aussi est plus rapide que dans le cytoplasme. Ceci suggère que l'accumulation de phyA dans le cytoplasme permet son accumulation à des niveaux élevés à l'obscurité. Enfin j'ai identifié une région similaire à un motif PEST requise pour la stabilité de phyA et j'ai aussi développé un criblage génétique non biaisé pour identifier de nouveaux composants impliqués dans la régulation de la dégradation de phyA. L'importance de ces résultats est discutée dans le dernier chapitre de cette thèse.

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Light-emitting diodes (LEDs) are taking an increasing place in the market of domestic lighting because they produce light with low energy consumption. In the EU, by 2016, no traditional incandescent light sources will be available and LEDs may become the major domestic light sources. Due to specific spectral and energetic characteristics of white LEDs as compared to other domestic light sources, some concerns have been raised regarding their safety for human health and particularly potential harmful risks for the eye. To conduct a health risk assessment on systems using LEDs, the French Agency for Food, Environmental and Occupational Health & Safety (ANSES), a public body reporting to the French Ministers for ecology, for health and for employment, has organized a task group. This group consisted physicists, lighting and metrology specialists, retinal biologist and ophthalmologist who have worked together for a year. Part of this work has comprised the evaluation of group risks of different white LEDs commercialized on the French market, according to the standards and found that some of these lights belonged to the group risk 1 or 2. This paper gives a comprehensive analysis of the potential risks of white LEDs, taking into account pre-clinical knowledge as well as epidemiologic studies and reports the French Agency's recommendations to avoid potential retinal hazards.

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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

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Proper division plane positioning is essential to achieve faithful DNA segregation and to control daughter cell size, positioning, or fate within tissues. In Schizosaccharomyces pombe, division plane positioning is controlled positively by export of the division plane positioning factor Mid1/anillin from the nucleus and negatively by the Pom1/DYRK (dual-specificity tyrosine-regulated kinase) gradients emanating from cell tips. Pom1 restricts to the cell middle cortical cytokinetic ring precursor nodes organized by the SAD-like kinase Cdr2 and Mid1/anillin through an unknown mechanism. In this study, we show that Pom1 modulates Cdr2 association with membranes by phosphorylation of a basic region cooperating with the lipid-binding KA-1 domain. Pom1 also inhibits Cdr2 interaction with Mid1, reducing its clustering ability, possibly by down-regulation of Cdr2 kinase activity. We propose that the dual regulation exerted by Pom1 on Cdr2 prevents Cdr2 assembly into stable nodes in the cell tip region where Pom1 concentration is high, which ensures proper positioning of cytokinetic ring precursors at the cell geometrical center and robust and accurate division plane positioning.