994 resultados para spatiotemporal patterns


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Background: Macrophage migration inhibitory factor (MIF) has special pro-inflammatory roles, affecting the functions of macrophages and lymphocytes and counter-regulating the effects of glucocorticoids on the immune response. The conspicuous expression of MIF during human implantation and early embryonic development also suggests this factor acts in reproductive functions. The overall goal of this study was to evaluate Mif expression by trophoblast and embryo placental cells during mouse pregnancy. Methods: Mif was immunolocalized at implantation sites on gestation days (gd) 7.5, 10.5, 13.5 and 17.5. Ectoplacental cones and fetal placentas dissected from the maternal tissues were used for Western blotting and qRT-PCR assays on the same gestation days. Results: During the post-implantation period (gd7.5), trophoblast giant cells showed strong Mif reactivity. In later placentation phases (gds 10.5-17.5), Mif appeared to be concentrated in the junctional zone and trophoblast giant cells. Mif protein expression increased significantly from gd7.5 to 10.5 (p = 0.005) and from gd7.5 to 13.5 (p = 0.03), remaining at high concentration as gestation proceeded. Higher mRNA expression was found on gd10.5 and was significantly different from gd13.5 (p = 0.048) and 17.5 (p = 0.009). Conclusions: The up-regulation of Mif on gd10.5 coincides with the stage in which the placenta assumes its three-layered organization (giant cells, spongiotrophoblast and labyrinth zones), fetal blood circulation begins and population of uNK cells reaches high proportions at the maternal counter part of the placenta, suggesting that Mif may play a role in either the placentation or in the adaptation of the differentiated placenta to the uterus or still in gestational immunomodulatory responses. Moreover, it reinforces the possibility of specific activities for Mif at the maternal fetal interface.

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Calcareous floating periphyton mats in the southern Everglades provide habitat for a diverse macroinvertebrate community that has not been well characterized. Our study described this community in an oligotrophic marsh, compared it with the macroinvertebrate community associated with adjacent epiphytic algae attached to macrophytes in the water column, and detected spatial patterns in density and community structure. The floating periphyton mat (floating mat) and epiphytic algae in the water column (submerged epiphyton) were sampled at 4 sites (1 km apart) in northern Shark River Slough, Everglades National Park (ENP), in the early (July) and late (November) wet season. Two perpendicular 90-m transects were established at each site and 100 samples were taken in a nested design. Sites were located in wet-prairie spikerush-dominated sloughs with similar water depths and emergent macrophyte communities. Floating mats were sampled by taking cores (6-cm diameter) that were sorted under magnification to enumerate infauna retained on a 250-μm-mesh sieve and with a maximum dimension >1 mm. Our results showed that floating mats provide habitat for a macroinvertebrate community with higher densities (no. animals/g ash-free dry mass) of Hyalella azteca, Dasyhelea spp., and Cladocera, and lower densities of Chironomidae and Planorbella spp. than communities associated with submerged epiphyton. Densities of the most common taxa increased 3× to 15× from early to late wet season, and community differences between the 2 habitat types became more pronounced. Floating-mat coverage and estimated floating-mat biomass increased 20 to 30% and 30 to 110%, respectively, at most sites in the late wet season. Some intersite variation was observed in individual taxa, but no consistent spatial pattern in any taxon was detected at any scale (from 0.2 m to 3 km). Floating mats and their resident macroinvertebrate communities are important components in the Everglades food web. This community should be included in environmental monitoring programs because degradation and eventual loss of the calcareous periphyton mat is associated with P enrichment in this ecosystem.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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In order to harness the computational capacity of dissociated cultured neuronal networks, it is necessary to understand neuronal dynamics and connectivity on a mesoscopic scale. To this end, this paper uncovers dynamic spatiotemporal patterns emerging from electrically stimulated neuronal cultures using hidden Markov models (HMMs) to characterize multi-channel spike trains as a progression of patterns of underlying states of neuronal activity. However, experimentation aimed at optimal choice of parameters for such models is essential and results are reported in detail. Results derived from ensemble neuronal data revealed highly repeatable patterns of state transitions in the order of milliseconds in response to probing stimuli.

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Spatiotemporal pattern formation in the electrocatalytic oxidation of sulfide on a platinum disk is investigated using electrochemical methods and a charge-coupled device (CCD) camera simultaneously. The system is characterized by different oscillatory regions spread over a wide potential range. An additional series resistor and a large electrode area facilitate observation of multiple regions of kinetic instabilities along the current/potential curve. Spatiotemporal patterns on the working electrode, such as fronts, pulses, spirals, twinkling eyes, labyrinthine stripes, and alternating synchronized deposition and dissolution, are observed at different operating conditions of series resistance and sweep rate.

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Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.

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We present a theoretical framework and a case study for reusing the same conceptual and computational methodology for both temporal abstraction and linear (unidimensional) space abstraction, in a domain (evaluation of traffic-control actions) significantly different from the one (clinical medicine) in which the method was originally used. The method, known as knowledge-based temporal abstraction, abstracts high-level concepts and patterns from time-stamped raw data using a formal theory of domain-specific temporal-abstraction knowledge. We applied this method, originally used to interpret time-oriented clinical data, to the domain of traffic control, in which the monitoring task requires linear pattern matching along both space and time. First, we reused the method for creation of unidimensional spatial abstractions over highways, given sensor measurements along each highway measured at the same time point. Second, we reused the method to create temporal abstractions of the traffic behavior, for the same space segments, but during consecutive time points. We defined the corresponding temporal-abstraction and spatial-abstraction domain-specific knowledge. Our results suggest that (1) the knowledge-based temporal-abstraction method is reusable over time and unidimensional space as well as over significantly different domains; (2) the method can be generalized into a knowledge-based linear-abstraction method, which solves tasks requiring abstraction of data along any linear distance measure; and (3) a spatiotemporal-abstraction method can be assembled from two copies of the generalized method and a spatial-decomposition mechanism, and is applicable to tasks requiring abstraction of time-oriented data into meaningful spatiotemporal patterns over a linear, decomposable space, such as traffic over a set of highways.

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Plant cells can respond qualitatively and quantitatively to a wide range of environmental signals. Ca2+ is used as an intracellular signal for volume regulation in response to external osmotic changes. We show here that the spatiotemporal patterns of hypo-osmotically induced Ca2+ signals vary dramatically with stimulus strength in embryonic cells of the marine alga Fucus. Biphasic or multiphasic Ca2+ signals reflect Ca2+ elevations in distinct cellular domains. These propagate via elemental Ca2+ release in nuclear or peripheral regions that are rich in endoplasmic reticulum. Cell volume regulation specifically requires Ca2+ elevation in apical peripheral regions, whereas an altered cell division rate occurs only in response to stimuli that cause Ca2+ elevation in nuclear regions.

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The abundance of calcareous green algae was recorded quarterly at 28 sites within the Florida Keys National Marine Sanctuary (FKNMS) for a period of 7 years as part of a sea grass monitoring program. To evaluate the validity of using the functional-form group approach, we designed a sampling method that included the functional-form group and the component genera. This strategy enabled us to analyze the spatiotemporal patterns in the abundance of calcareous green algae as a group and to describe synchronous behavior among its genera through the application of a nonlinear regression model to both categories of data. Spatial analyses revealed that, in general, all genera displayed long-term trends of increasing abundance at most sites; however, at some sites the long-term trends for genera opposed one another. Strong synchrony in the timing of seasonal changes was found among all genera, possibly reflecting similar reproductive and seasonal growth pattern, but the variability in the magnitude of seasonal changes was very high among genera and sites. No spatial patterns were found in long-term or seasonal changes; the only significant relation detected was for slope, with sites closer to land showing higher values, suggesting that some factors associated with land proximity are affecting this increase. We conclude that the abundances of genera behaved differently from the functional-form group, indicating that the use of the functionalform group approach may be unsuitable to detect changes in sea grass community structure in the FKNMS at the existing temporal and spatial scale of the monitoring program.

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The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.

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We analyze the physical mechanisms leading either to synchronization or to the formation of spatiotemporal patterns in a lattice model of pulse-coupled oscillators. In order to make the system tractable from a mathematical point of view we study a one-dimensional ring with unidirectional coupling. In such a situation, exact results concerning the stability of the fixed of the dynamic evolution of the lattice can be obtained. Furthermore, we show that this stability is the responsible for the different behaviors.

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ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.

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Spatiotemporal pattern formation in reaction-transport systems takes place spontaneously when the system is kept far from thermodynamic equilibrium. Targets, reaction fronts, waves, spirals, spots and stripes are some typical examples of selforganized structuring. In electrochemical systems, monitoring spatiotemporal patterns of potential in the solid/liquid interface can be done by the use of equally distributed microprobes located close to the working electrode. However, the physical size of each probe can limit the spatial resolution and alter mass transport properties. In contrast, the direct measurement of discrete electrodes does not suffer from this limitation and allows the accurate manipulation of the spatial coupling through changes in resistors connected to the electric circuit. In this paper, the development of an electrochemical setup for multichannel data acquisition with spatiotemporal resolution is described, especially to monitor low levels of currents usually observed in the electro-oxidation of small organic molecules.