973 resultados para Resonance Raman Spectrum


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Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

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Cerebral responses to alternating periods of a control task and a selective letter generation paradigm were investigated with functional Magnetic Resonance Imaging (fMRI). Subjects selectively generated letters from four designated sets of six letters from the English language alphabet, with the instruction that they were not to produce letters in alphabetical order either forward or backward, repeat or alternate letters. Performance during this condition was compared with that of a control condition in which subjects recited the same letters in alphabetical order. Analyses revealed significant and extensive foci of activation in a number of cerebral regions including mid-dorsolateral frontal cortex, inferior frontal gyrus, precuneus, supramarginal gyrus, and cerebellum during the selective letter generation condition. These findings are discussed with respect to recent positron emission tomography (PET) and fMRI studies of verbal working memory and encoding/retrieval in episodic memory.

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Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes-PRDM16, PAX3, TP63, C5orf50, and COL17A1-in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

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Pharmacological MRI (phMRI) techniques can be used to monitor the neurophysiological effects of central nervous system (CNS) active drugs. In this study, we investigated whether dynamic susceptibility contrast (DSC) perfusion imaging employing the use of superparamagnetic iron oxide nanoparticles (Resovist) could be used to measure hemodynamic response to d-amphetamine challenge in human subjects at both 1.5 and 4 T. Significant changes in cerebral blood flow (CBF) were found in focal regions associated with the nigrostriatal circuit and mesolimbic and mesocortical dopaminergic pathways. More significant CBF responses were found at higher field strength, mainly within striatal structures. The results from this study indicate that DSC perfusion imaging using Resovist can be used to assess the efficacy of CNS-active drugs and may play a role in the development of novel psychiatric therapies at the preclinical level. © 2005 Wiley-Liss, Inc.

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Background: Magnetic resonance diffusion tensor imaging (DTI) shows promise in the early detection of microstructural pathophysiological changes in the brain. Objectives: To measure microstructural differences in the brains of participants with amnestic mild cognitive impairment (MCI) compared with an age-matched control group using an optimised DTI technique with fully automated image analysis tools and to investigate the correlation between diffusivity measurements and neuropsychological performance scores across groups. Methods: 34 participants (17 participants with MCI, 17 healthy elderly adults) underwent magnetic resonance imaging (MRI)-based DTI. To control for the effects of anatomical variation, diffusion images of all participants were registered to standard anatomical space. Significant statistical differences in diffusivity measurements between the two groups were determined on a pixel-by-pixel basis using gaussian random field theory. Results: Significantly raised mean diffusivity measurements (p<0.001) were observed in the left and right entorhinal cortices (BA28), posterior occipital-parietal cortex (BA18 and BA19), right parietal supramarginal gyrus (BA40) and right frontal precentral gyri (BA4 and BA6) in participants with MCI. With respect to fractional anisotropy, participants with MCI had significantly reduced measurements (p<0.001) in the limbic parahippocampal subgyral white matter, right thalamus and left posterior cingulate. Pearson's correlation coefficients calculated across all participants showed significant correlations between neuropsychological assessment scores and regional measurements of mean diffusivity and fractional anisotropy. Conclusions: DTI-based diffusivity measures may offer a sensitive method of detecting subtle microstructural brain changes associated with preclinical Alzheimer's disease.

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The capabilities of the mechanical resonator-based nanosensors in detecting ultra-small mass or force shifts have driven a continuing exploration of the palette of nanomaterials for such application purposes. Based on large-scale molecular dynamics simulations, we have assessed the applicability of a new class of carbon nanomaterials for nanoresonator usage, i.e. the single-wall carbon nanotube (SWNT) network. It is found that SWNT networks inherit excellent mechanical properties from the constituent SWNTs, possessing a high natural frequency. However, although a high quality factor is suggested from the simulation results, it is hard to obtain an unambiguous Q-factor due to the existence of vibration modes in addition to the dominant mode. The nonlinearities resulting from these extra vibration modes are found to exist uniformly under various testing conditions including different initial actuations and temperatures. Further testing shows that these modes can be effectively suppressed through the introduction of axial strain, leading to an extremely high quality factor in the order of 109 estimated from the SWNT network with 2% tensile strain. Additional studies indicate that the carbon rings connecting the SWNTs can also be used to alter the vibrational properties of the resulting network. This study suggests that the SWNT network can be a good candidate for applications as nanoresonators.

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Increasing worldwide terrorist attacks involving explosives presents a growing need for a rapid and ranged explosive detection method that can safely be deployed in the field. Stand-off Raman spectroscopy shows great promise; however, the radiant exposures of lasers required for adequate signal generation are often much greater than what is safe for the eye or the skin, restricting use of the technique to un-populated areas. Here, by determining the safe exposure levels for lasers typically used in Raman spectroscopy, optimal parameter values are identified, which produce the largest possible detection range using power densities that do not exceed the eye-safe limit. It is shown that safe ultraviolet pulse energies can be more than three orders of magnitude greater than equivalent safe visible pulse energies. Coupling this to the 16-fold increase in Raman signal obtained in the ultraviolet at 266 nm over that at 532 nm results in a 131 times larger detection range for the eye-safe 266-nm system over an equivalent eye-safe 532-nm laser system. For the Raman system described here, this translates to a maximum range of 42 m for detecting Teflon with a 266-nm laser emitting a 100-mm diameter beam of 23.5-mJ nanosecond pulses.

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Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

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Best practice dictates that the Autism Spectrum Disorder (ASD) diagnostic process is informed by experienced professionals from at least two disciplines, for example psychology or speech pathology, with the diagnosis ultimately provided by a specialist medical practitioner e.g. child psychiatrist, neurologist or paediatrician. Irrespective of a child’s age, diagnosis relies upon information about their early development. Current information and observations on a child’s behaviour, communication and socialisation are considered by the specialist medical practitioner against the signs and symptoms detailed in one of several diagnostic systems. Two recently used classification systems in Australia have been the fourth edition of the Diagnostic Statistical Manual of Mental Disorders (DSM-IV) published by the American Psychiatric Association (1994) and the tenth edition of the International Classification of Disease (ICD-10), published by the World Health Organisation (2003).

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Objective: To evaluate the presence of spinal inflammation with and without sacroiliac (SI) joint inflammation on magnetic resonance imaging (MRI) in patients with active nonradiographic axial spondyloarthritis (SpA), and to compare the disease characteristics of these subgroups. Methods: ABILITY-1 is a multicenter, randomized, controlled trial of adalimumab versus placebo in patients with nonradiographic axial SpA classified using the Assessment of SpondyloArthritis international Society axial SpA criteria. Baseline MRIs were centrally scored independently by 2 readers using the Spondyloarthritis Research Consortium of Canada (SPARCC) method for the SI joints and the SPARCC 6-discovertebral unit method for the spine. Positive evidence of inflammation on MRI was defined as a SPARCC score of >2 for either the SI joints or the spine. Results: Among patients with baseline SPARCC scores, 40% had an SI joint score of >2 and 52% had a spine score of >2. Forty-nine percent of patients with baseline SI joint scores of <2, and 58% of those with baseline SI joint scores of >2, had a spine score of >2. Comparison of baseline disease characteristics by baseline SI joint and spine scores showed that a greater proportion of patients in the subgroup with a baseline SPARCC score of >2 for both SI joints and spine were male, and patients with spine and SI joint scores of <2 were younger and had shorter symptom duration. SPARCC spine scores correlated with baseline symptom duration, and SI joint scores correlated negatively with the baseline Bath Ankylosing Spondylitis Disease Activity Index, but neither correlated with the baseline Ankylosing Spondylitis Disease Activity Score, total back pain, the patient's global assessment of disease activity, the Bath Ankylosing Spondylitis Functional Index, morning stiffness, nocturnal pain, or C-reactive protein level. Conclusion: Assessment by experienced readers showed that spinal inflammation on MRI might be observed in half of patients with nonradiographic axial SpA without SI joint inflammation.

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The availability of population-specific normative data regarding disease severity measures is essential for patient assessment. The goals of the current study were to characterize the pattern of ankylosing spondylitis (AS) in Portuguese patients and to develop reference centile charts for BASDAI, BASFI, BASMI and mSASSS, the most widely used assessment tools in AS. AS cases were recruited from hospital outpatient clinics, with AS defined according to the modified New York criteria. Demographic and clinical data were recorded. All radiographs were evaluated by two independent experienced readers. Centile charts for BASDAI, BASFI, BASMI and mSASSS were constructed for both genders, using generalized linear models and regression models with duration of disease as independent variable. A total of 369 patients (62.3% male, mean ± (SD) age 45.4 ± 13.2 years, mean ± (SD) disease duration 11.4 ± 10.5 years, 70.7% B27-positive) were included. Family history of AS in a first-degree relative was reported in 17.6% of the cases. Regarding clinical disease pattern, at the time of assessment 42.3% had axial disease, 2.4% peripheral disease, 40.9% mixed disease and 7.1% isolated enthesopatic disease. Anterior uveitis (33.6%) was the most common extra-articular manifestation. The centile charts suggest that females reported greater disease activity and more functional impairment than males but had lower BASMI and mSASSS scores. Data collected through this study provided a demographic and clinical profile of patients with AS in Portugal. The development of centile charts constitutes a useful tool to assess the change of disease pattern over time and in response to therapeutic interventions.

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A miniaturized flow-through system consisting of a gold coated silicon substrate based on enhanced Raman spectroscopy has been used to study the detection of vapour from model explosive compounds. The measurements show that the detectability of the vapour molecules at room temperature depends sensitively on the interaction between the molecule and the substrate. The results highlight the capability of a flow system combined with Raman spectroscopy for detecting low vapour pressure compounds with a limit of detection of 0.2 ppb as demonstrated by the detection of bis(2-ethylhexyl)phthalate, a common polymer additive emitted from a commercial polyvinyl chloride (PVC) tubing at room temperature.

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A novel, highly selective resonance light scattering (RLS) method was researched and developed for the analysis of phenol in different types of industrial water. An important aspect of the method involved the use of graphene quantum dots (GQDs), which were initially obtained from the pyrolysis of citric acid dissolved in aqueous solutions. The GQDs in the presence of horseradish peroxidase (HRP) and H2O2 were found to react quantitatively with phenol such that the RLS spectral band (310 nm) was quantitatively enhanced as a consequence of the interaction between the GQDs and the quinone formed in the above reaction. It was demonstrated that the novel analytical method had better selectivity and sensitivity for the determination of phenol in water as compared to other analytical methods found in the literature. Thus, trace amounts of phenol were detected over the linear ranges of 6.00×10−8–2.16×10−6 M and 2.40×10−6–2.88×10−5 M with a detection limit of 2.20×10−8 M. In addition, three different spiked waste water samples and two untreated lake water samples were analysed for phenol. Satisfactory results were obtained with the use of the novel, sensitive and rapid RLS method.

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Supported nanoparticles (NPs) of nonplasmonic transition metals (Pd, Pt, Rh, and Ir) are widely used as thermally activated catalysts for the synthesis of important organic compounds, but little is known about their photocatalytic capabilities. We discovered that irradiation with light can significantly enhance the intrinsic catalytic performance of these metal NPs at ambient temperatures for several types of reactions. These metal NPs strongly absorb the light mainly through interband electronic transitions. The excited electrons interact with the reactant molecules on the particles to accelerate these reactions. The rate of the catalyzed reaction depends on the concentration and energy of the excited electrons, which can be increased by increasing the light intensity or by reducing the irradiation wavelength. The metal NPs can also effectively couple thermal and light energy sources to more efficiently drive chemical transformations.