133 resultados para TEMPORAL ARTERITIS
Resumo:
Gesneriaceae are represented in the New World (NW) by a major clade (c. 1000 species) currently recognized as subfamily Gesnerioideae. Radiation of this group occurred in all biomes of tropical America and was accompanied by extensive phenotypic and ecological diversification. Here we performed phylogenetic analyses using DNA sequences from three plastid loci to reconstruct the evolutionary history of Gesnerioideae and to investigate its relationship with other lineages of Gesneriaceae and Lamiales. Our molecular data confirm the inclusion of the South Pacific Coronanthereae and the Old World (OW) monotypic genus Titanotrichum in Gesnerioideae and the sister-group relationship of this subfamily to the rest of the OW Gesneriaceae. Calceolariaceae and the NW genera Peltanthera and Sanango appeared successively sister to Gesneriaceae, whereas Cubitanthus, which has been previously assigned to Gesneriaceae, is shown to be related to Linderniaceae. Based on molecular dating and biogeographical reconstruction analyses, we suggest that ancestors of Gesneriaceae originated in South America during the Late Cretaceous. Distribution of Gesneriaceae in the Palaeotropics and Australasia was inferred as resulting from two independent long-distance dispersals during the Eocene and Oligocene, respectively. In a short time span starting at 34 Mya, ancestors of Gesnerioideae colonized several Neotropical regions including the tropical Andes, Brazilian Atlantic forest, cerrado, Central America and the West Indies. Subsequent diversification within these areas occurred largely in situ and was particularly extensive in the mountainous systems of the Andes, Central America and the Brazilian Atlantic forest. Only two radiations account for 90% of the diversity of Gesneriaceae in the Brazilian Atlantic forest, whereas half of the species richness in the northern Andes and Central America originated during the last 10 Myr from a single radiation.
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Capsule We report a review of the occurrence of bats in the Barn Owl diet Tyto alba in Europe. Based on 802 studies reporting 4.02 million prey items identified in pellets, 4949 were bats (0.12%). We found that bat predation decreased during the last 150 years, is more frequent on islands than mainland, and is higher in eastern than western Europe and in southern than northern Europe. Although Barn Owls usually capture bats opportunistically, they can sometimes specialize on them.
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Optimal behavior relies on flexible adaptation to environmental requirements, notably based on the detection of errors. The impact of error detection on subsequent behavior typically manifests as a slowing down of RTs following errors. Precisely how errors impact the processing of subsequent stimuli and in turn shape behavior remains unresolved. To address these questions, we used an auditory spatial go/no-go task where continual feedback informed participants of whether they were too slow. We contrasted auditory-evoked potentials to left-lateralized go and right no-go stimuli as a function of performance on the preceding go stimuli, generating a 2 × 2 design with "preceding performance" (fast hit [FH], slow hit [SH]) and stimulus type (go, no-go) as within-subject factors. SH trials yielded SH trials on the following trials more often than did FHs, supporting our assumption that SHs engaged effects similar to errors. Electrophysiologically, auditory-evoked potentials modulated topographically as a function of preceding performance 80-110 msec poststimulus onset and then as a function of stimulus type at 110-140 msec, indicative of changes in the underlying brain networks. Source estimations revealed a stronger activity of prefrontal regions to stimuli after successful than error trials, followed by a stronger response of parietal areas to the no-go than go stimuli. We interpret these results in terms of a shift from a fast automatic to a slow controlled form of inhibitory control induced by the detection of errors, manifesting during low-level integration of task-relevant features of subsequent stimuli, which in turn influences response speed.
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OBJECTIVE: Motor changes in major depression (MD) may represent potential markers of treatment response. Physiological rhythms (heart rate/gait cycle/hand movements) have been recently shown to be neither random nor regular but to display a fractal temporal organisation, possibly reflecting a unique central "internal clock" control. Sleep and mood circadian rhythm modifications observed in MD also suggest a role for this "internal clock". We set out to examine the fractal pattern of motor activity in MD. METHODS: Ten depressed patients (46±20 years) and ten age- and gender-matched healthy controls (48±21 years) underwent a 6-h ambulatory monitoring of spontaneous hand activity with a validated wireless device. Fractal scaling exponent (α) was analysed. An α value close to 1 means the pattern is fractal. RESULTS: Healthy controls displayed a fractal pattern of spontaneous motor hand activity (α: 1.0±0.1), whereas depressed patients showed an alteration of that pattern (α:1.2±0.15, p<0.01), towards a smoother organisation. CONCLUSION: The alteration of fractal pattern of hand activity by depression further supports the role of a central internal clock in the temporal organisation of movements. This novel way of studying motor changes in depression might have an important role in the detection of endophenotypes and potential predictors of treatment response.
Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity.
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Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.
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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.
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Islet-brain 1 (IB1) was recently identified as a DNA-binding protein of the GLUT2 gene promoter. The mouse IB1 is the rat and human homologue of the Jun-interacting protein 1 (JIP-1) which has been recognized as a key player in the regulation of c-Jun amino-terminal kinase (JNK) mitogen-activated protein kinase (MAPK) pathways. JIP-1 is involved in the control of apoptosis and may play a role in brain development and aging. Here, IB1 was studied in adult and developing mouse brain tissue by in situ hybridization, Northern and Western blot analysis at cellular and subcellular levels, as well as by immunocytochemistry in brain sections and cell cultures. IB1 expression was localized in the synaptic regions of the olfactory bulb, retina, cerebral and cerebellar cortex and hippocampus in the adult mouse brain. IB1 was also detected in a restricted number of axons, as in the mossy fibres from dentate gyrus in the hippocampus, and was found in soma, dendrites and axons of cerebellar Purkinje cells. After birth, IB1 expression peaks at postnatal day 15. IB1 was located in axonal and dendritic growth cones in primary telencephalon cells. By biochemical and subcellular fractionation of neuronal cells, IB1 was detected both in the cytosolic and membrane fractions. Taken together with previous data, the restricted neuronal expression of IB1 in developing and adult brain and its prominent localization in synapses suggest that the protein may be critical for cell signalling in developing and mature nerve terminals.
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Petrositis is a rare and severe complication of acute otitis media and mastoiditis. Although the extension of the inflammatory process from the petrous apex to the adjacent Meckel cave can lead to trigeminal pain, an irritation of the trigeminal nerve roots resulting in acute or chronic hyperactivity of masticatory muscles has never been reported. We report here the unusual case of an 86-year-old man who presented with a handicapping myofascial pain and dysfunction syndrome of the right temporal muscle as a heralding manifestation of an unusual form of petrositis. The patient progressively developed a retropharyngeal abscess, a right sphenoid sinusitis, and fatal meningitis. This case demonstrated that (1) myofascial pain and dysfunction syndrome that does not respond to conventional treatments may suggest an unusual etiology and warrant further medical investigations and a detailed medical history and that (2) petrositis can manifest itself with atypical clinical symptoms and radiologic signs. (Quintessence Int 2011;42:419-422).
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Background: We aimed to analyze the rate and time distribution of pre- and post-morbid cerebrovascular events in a single ischemic stroke population, and whether these depend on the etiology of the index stroke. Methods: In 2,203 consecutive patients admitted to a single stroke center registry (ASTRAL), the ischemic stroke that led to admission was considered the index event. Frequency distribution and cumulative relative distribution graphs of the most recent and first recurrent event (ischemic stroke, transient ischemic attack, intracranial or subarachnoid hemorrhage) were drawn in weekly and daily intervals for all strokes and for all stroke types. Results: The frequency of events at identical time points before and after the index stroke was mostly reduced in the first week after (vs. before) stroke (1.0 vs. 4.2%, p < 0.001) and the first month (2.7 vs. 7.4%, p < 0.001), and then ebbed over the first year (8.4 vs. 13.1%, p < 0.001). On daily basis, the peak frequency was noticed at day -1 (1.6%) with a reduction to 0.7% on the index day and 0.17% 24 h after. The event rate in patients with atherosclerotic stroke was particularly high around the index event, but 1-year cumulative recurrence rate was similar in all stroke types. Conclusions: We confirm a short window of increased vulnerability in ischemic stroke and show a 4-, 3- and 2-fold reduction in post-stroke events at 1 week, 1 month and 1 year, respectively, compared to identical pre-stroke periods. This break in the 'stroke wave' is particularly striking after atherosclerotic and lacunar strokes.
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The ability to discriminate conspecific vocalizations is observed across species and early during development. However, its neurophysiologic mechanism remains controversial, particularly regarding whether it involves specialized processes with dedicated neural machinery. We identified spatiotemporal brain mechanisms for conspecific vocalization discrimination in humans by applying electrical neuroimaging analyses to auditory evoked potentials (AEPs) in response to acoustically and psychophysically controlled nonverbal human and animal vocalizations as well as sounds of man-made objects. AEP strength modulations in the absence of topographic modulations are suggestive of statistically indistinguishable brain networks. First, responses were significantly stronger, but topographically indistinguishable to human versus animal vocalizations starting at 169-219 ms after stimulus onset and within regions of the right superior temporal sulcus and superior temporal gyrus. This effect correlated with another AEP strength modulation occurring at 291-357 ms that was localized within the left inferior prefrontal and precentral gyri. Temporally segregated and spatially distributed stages of vocalization discrimination are thus functionally coupled and demonstrate how conventional views of functional specialization must incorporate network dynamics. Second, vocalization discrimination is not subject to facilitated processing in time, but instead lags more general categorization by approximately 100 ms, indicative of hierarchical processing during object discrimination. Third, although differences between human and animal vocalizations persisted when analyses were performed at a single-object level or extended to include additional (man-made) sound categories, at no latency were responses to human vocalizations stronger than those to all other categories. Vocalization discrimination transpires at times synchronous with that of face discrimination but is not functionally specialized.
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Because the magnitude of selection can vary between sexes and in space and time, sexually antagonistic selection is difficult to demonstrate. In a Swiss population of barn owls (Tyto alba), a heritable eumelanic colour trait (size of black spots on ventral feathers) was positively selected with respect to yearling survival only in females. It remains unclear whether the absence of negative selection in males is typical in this species. To tackle this issue indirectly, we measured the size of black spots in 1733 skin specimens collected by museums from 1816 to 2001 in seven European countries and in the Middle-East. The temporal change in spot size was sex- and country-specific. In males, spots became smaller particularly in three countries (Middle-East, Italy and Switzerland). In females, the size of spots increased significantly in two countries (UK and Spain) and decreased in two others (Germany and Switzerland). Because migration and phenotypic plasticity cannot explain these results, selection is the most likely cause. The weaker temporal change in spot size in females than males may be because of the combined effect of strong genetic correlation between the sexes and stronger negative selection in males than positive selection in females. We thus suggest that in the barn owl, spot size (or genetically correlated traits) is sexually antagonistically selected and that its pattern of selection may account for the maintenance of its variation and sexual dimorphism.