366 resultados para Sites of interest


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Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

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Understanding how the brain matures in healthy individuals is critical for evaluating deviations from normal development in psychiatric and neurodevelopmental disorders. The brain's anatomical networks are profoundly re-modeled between childhood and adulthood, and diffusion tractography offers unprecedented power to reconstruct these networks and neural pathways in vivo. Here we tracked changes in structural connectivity and network efficiency in 439 right-handed individuals aged 12 to 30 (211 female/126 male adults, mean age=23.6, SD=2.19; 31 female/24 male 12 year olds, mean age=12.3, SD=0.18; and 25 female/22 male 16 year olds, mean age=16.2, SD=0.37). All participants were scanned with high angular resolution diffusion imaging (HARDI) at 4 T. After we performed whole brain tractography, 70 cortical gyral-based regions of interest were extracted from each participant's co-registered anatomical scans. The proportion of fiber connections between all pairs of cortical regions, or nodes, was found to create symmetric fiber density matrices, reflecting the structural brain network. From those 70 × 70 matrices we computed graph theory metrics characterizing structural connectivity. Several key global and nodal metrics changed across development, showing increased network integration, with some connections pruned and others strengthened. The increases and decreases in fiber density, however, were not distributed proportionally across the brain. The frontal cortex had a disproportionate number of decreases in fiber density while the temporal cortex had a disproportionate number of increases in fiber density. This large-scale analysis of the developing structural connectome offers a foundation to develop statistical criteria for aberrant brain connectivity as the human brain matures.

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Studies of cerebral asymmetry can open doors to understanding the functional specialization of each brain hemisphere, and how this is altered in disease. Here we examined hemispheric asymmetries in fiber architecture using diffusion tensor imaging (DTI) in 100 subjects, using high-dimensional fluid warping to disentangle shape differences from measures sensitive to myelination. Confounding effects of purely structural asymmetries were reduced by using co-registered structural images to fluidly warp 3D maps of fiber characteristics (fractional and geodesic anisotropy) to a structurally symmetric minimal deformation template (MDT). We performed a quantitative genetic analysis on 100 subjects to determine whether the sources of the remaining signal asymmetries were primarily genetic or environmental. A twin design was used to identify the heritable features of fiber asymmetry in various regions of interest, to further assist in the discovery of genes influencing brain micro-architecture and brain lateralization. Genetic influences and left/right asymmetries were detected in the fiber architecture of the frontal lobes, with minor differences depending on the choice of registration template.

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Brain asymmetry has been a topic of interest for neuroscientists for many years. The advent of diffusion tensor imaging (DTI) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. Even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. We fluidly registered 4 Tesla DTI scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. We computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (FA, GA). Quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. We studied how these heritability estimates varied with the type of registration target (T1- or T2-weighted) and with sample size. All methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.

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This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.

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Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

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We report the synthesis of new protic ionic liquids (PILs) based on aniline derivatives and the use of high-throughput (HT) techniques to screen possible candidates. In this work, a simple HT method was applied to rapidly screen different aniline derivatives against different acids in order to identify possible combinations that produce PILs. This was followed by repeating the HT process with Chemspeed robotic synthesis platform for more accurate results. One of the successful combinations were then chosen to be synthesised on full scale for further analysis. The new PILs are of interest to the fields of ionic liquids, energy storage and especially, conducting polymers as they serve as solvents, electrolytes and monomers in the same time for possible electropolymerisation (i.e. a self-contained polymer precursor).

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This study aimed to take existing anatomical models of pregnant women, currently used for radiation pro-tection and nuclear medicine dose calculations, and adapt them for use in the calculation of fetal dose from external beam radiotherapy (EBRT). The models investigated were ‘KATJA’, which was provided as an MCNPX geometry file, and ‘RPI-P6’, which was provided in a simple, voxelized bina-ry format. In-house code was developed, to convert both mod-els into an `egsphant’ format, suitable for use with DOSXYZnrc. The geometries and densities of the resulting phantoms were evaluated and found to accurately represent the source data. As an example of the use of the phantoms, the delivery of a cranial EBRT treatment was simulated using the BEAMnrc and DOSXYZnrc Monte Carlo codes and the likely out-of-field doses to the fetus in each model was calculated. The results of these calculations showed good agreement (with-in one standard deviation) between the doses calculated in KATJA and PRI-P6, despite substantial anatomical differ-ences between the two models. For a 36 Gy prescription dose to a 233.2 cm3 target in the right brain, the mean doses calcu-lated in a region of interest covering the entire uterus were 1.0 +/- 0.6 mSv for KATJA and 1.3 +/- 0.9 mSv for RPI-P6. This work is expected to lead to more comprehensive studies of EBRT treatment plan design and its effects on fetal dose in the future.

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NBC's failed attempt to remake the BBC's Coupling generated a significant amount of press coverage in summer 2003. At the core of the debate was a struggle to reconcile an increasingly integrated transatlantic television market with traditional assumptions about culture and its authentic connection to space and place. The interest in the remake not only created a space where certain national differences were played out and performed but also facilitated an equally compelling transatlantic dialogue about creative ownership, appropriation, and a network's responsibility to its audiences. In doing so, the media attention highlighted how television formats are best understood not as innocuous commodities of international trade but as potential sites of articulation, contestation, and community in an increasingly transnational television environment.

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Piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest as smart materials for novel space-based telescope applications. Dimensional adjustments of adaptive thin polymer films are achieved via controlled charge deposition. Predicting their long-term performance requires a detailed understanding of the piezoelectric property changes that develop during space environmental exposure. The overall materials performance is governed by a combination of chemical and physical degradation processes occurring in low Earth orbit as established by our past laboratory-based materials performance experiments (see report SAND 2005-6846). Molecular changes are primarily induced via radiative damage, and physical damage from temperature and atomic oxygen exposure is evident as depoling, loss of orientation and surface erosion. The current project extension has allowed us to design and fabricate small experimental units to be exposed to low Earth orbit environments as part of the Materials International Space Station Experiments program. The space exposure of these piezoelectric polymers will verify the observed trends and their degradation pathways, and provide feedback on using piezoelectric polymer films in space. This will be the first time that PVDF-based adaptive polymer films will be operated and exposed to combined atomic oxygen, solar UV and temperature variations in an actual space environment. The experiments are designed to be fully autonomous, involving cyclic application of excitation voltages, sensitive film position sensors and remote data logging. This mission will provide critically needed feedback on the long-term performance and degradation of such materials, and ultimately the feasibility of large adaptive and low weight optical systems utilizing these polymers in space.

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Review Objectives: This systematic review seeks to establish what best practice is for: Interventions which promote self-management for patients with End Stage Renal Disease (ERSD) undergoing Haemodialysis. Review questions: 1) Do education interventions improve self-management for patients with end stage renal disease? 2) Do psychosocial interventions such as Cognitive Behavioural Therapy, behavioural therapy or other counselling therapies and social support, improve self-management for patients with end stage renal disease? Criteria for considering studies for this review: Types of participants: This component of the review will consider studies with: • All adults over the age of 18 years • Patients with end stage renal disease • Undergoing haemodialysis Types of interventions/Phenomena of Interest: All studies evaluating the following interventions will be considered for inclusion in the review such as: Interventions which promote self management including: • Education interventions. • Psychosocial interventions such as cognitive behavioural therapy and other behavioural therapies, counselling and social support. Types of outcome measures/anticipated outcomes: This component of the review will consider studies that include the following outcomes: • Adherence with haemodialysis treatment, • Depression and/or anxiety, • Quality of life, • Carer burnout, • Social support • Patient satisfaction • Adverse events potentially attributable to the intervention or control treatment • Cost effectiveness of home haemodialysis Keywords chronic kidney failure; renal failure; end stage renal disease; chronic kidney disease

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Aerosol deposition in cylindrical tubes is a subject of interest to researchers and engineers in many applications of aerosol physics and metrology. Investigation of nano-particles in different aspects such as lungs, upper airways, batteries and vehicle exhaust gases is vital due the smaller size, adverse health effect and higher trouble for trapping than the micro-particles. The Lagrangian particle tracking provides an effective method for simulating the deposition of nano-particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. In this paper, the deposition of nano-particles in cylindrical tubes under laminar condition is studied using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different flow rates are examined. The point analysis in a uniform flow is performed for validating the Brownian motion. The results show good agreement between the calculated deposition efficiency and the analytic correlations in the literature. Furthermore, for the nano-particles with the diameter more than 40 nm, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.

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Objective. To undertake a systematic wholegenome screen to identify regions exhibiting genetic linkage to rheumatoid arthritis (RA). Methods. Two hundred fifty-two RA-affected sibling pairs from 182 UK families were genotyped using 365 highly informative microsatellite markers. Microsatellite genotyping was performed using fluorescent polymerase chain reaction primers and semiautomated DNA sequencing technology. Linkage analysis was undertaken using MAPMAKER/SIBS for single-point and multipoint analysis. Results. Significant linkage (maximum logarithm of odds score 4.7 [P = 0.000003] at marker D6S276, 1 cM from HLA-DRB1) was identified around the major histocompatibility complex (MHC) region on chromosome 6. Suggestive linkage (P < 7.4 × 10-4) was identified on chromosome 6q by single- and multipoint analysis. Ten other sites of nominal linkage (P < 0.05) were identified on chromosomes 3p, 4q, 7p, 2 regions of 10q, 2 regions of 14q, 16p, 21q, and Xq by single-point analysis and on 3 sites (1q, 14q, and 14q) by multipoint analysis. Conclusion. Linkage to the MHC region was confirmed. Eleven non-HLA regions demonstrated evidence of suggestive or nominal linkage, but none reached the genome-wide threshold for significant linkage (P = 2.2 × 10-5). Results of previous genome screens have suggested that 6 of these regions may be involved in RA susceptibility.

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Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

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Phage display is an advanced technology that can be used to characterize the interactions of antibody with antigen at the molecular level. It provides valuable data when applied to the investigation of IgE interaction with allergens. The aim of this rostrum article is to provide an explanation of the potential of phage display for increasing the understanding of allergen- IgE interaction, the discovery of diagnostic reagents, and the development of novel therapeutics for the treatment of allergic disease. The significance of initial studies that have applied phage display technology in allergy research will be highlighted. Phage display has been used to clone human IgE to timothy grass pollen allergen Phl p 5, to characterize the epitopes for murine and human antibodies to a birch pollen allergen Bet v 1, and to elucidate the epitopes of a murine mAb to the house dust mite allergen Der p 1. The technology has identified peptides that functionally mimic sites of human IgE constant domains and that were used to raise antiserum for blocking binding of IgE to the FcεRI on basophils and subsequent release of histamine. Phage display has also been used to characterize novel peanut and fungal allergens. The method has been used to increase our understanding of the molecular basis of allergen-IgE interactions and to develop clinically relevant reagents with the pharmacologic potential to block the effector phase of allergic reactions. Many advances from these early studies are likely as phage display technology evolves and allergists gain expertise in its research applications.