973 resultados para emerging disease


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Qualitative aspects of verbal fluency may be more useful in discerning the precise cause of any quantitative deficits in phonetic or category fluency, especially in the case of mild cognitive impairment (MCI), a possible intermediate stage between normal performance and Alzheimer's disease (AD). The aim of this study was to use both quantitative and qualitative (switches and clusters) methods to compare the phonetic and category verbal fluency performance of elderly adults with no cognitive impairment (n = 51), significant memory impairment (n = 16), and AD (n = 16). As expected, the AD group displayed impairments in all quantitative and qualitative measures of the two fluency tasks relative to their age- and education-matched peers. By contrast, the amnestic MCI group produced fewer animal names on the semantic fluency task than controls and showed normal performance on the phonetic fluency task. The MCI group's inferior category fluency performance was associated with a deficit in their category-switching rate rather than word cluster size. Overall, the results indicate that a semantic measure such as category fluency when used in conjunction with a test of episodic memory may increase the sensitivity for detecting preclinical AD. Future research using external cues and other measures of set shifting capacity may assist in clarifying the origin of the amnestic MCI-specific category-switching deficiency. Copyright

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In order to evaluate the capability of 1H MRS to monitor longitudinal changes in subjects with probable Alzheimer's disease (AD), the temporal stability of the metabolite measures N-acetylaspartate and N- acetylaspartylglutamate (NA), total Creatine (Cr), myo-Inositol (mI), total Choline (Chol), NA/Cr, mI/Cr, Chol/Cr and NA/mI were investigated in a cohort of normal older adults. Only the metabolite measures NA, mI, Cr, NA/Cr, mI/Cr, and NA/mI were found to be stable after a mean interval of 260 days. Relative and absolute metabolite measures from a cohort of patients with probable AD were subsequently compared with data from a sample of normal older adult control subjects, and correlated with mental status and the degree of atrophy in the localized voxel. Concentrations of NA, NA/Cr, and NA/mI were significantly reduced in the AD group with concomitant significant increases in mI and mI/Cr. There were no differences between the two groups in measures of Cr, Chol, or Chol/Cr. Significant correlations between mental status as measured by the Mini-Mental State Examination and NA/mI, mI/Cr and NA were found. These metabolite measures were also significantly correlated with the extent of atrophy (as measured by CSF and GM composition) in the spectroscopy voxel.

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We detected and mapped a dynamically spreading wave of gray matter loss in the brains of patients with Alzheimer's disease (AD). The loss pattern was visualized in four dimensions as it spread over time from temporal and limbic cortices into frontal and occipital brain regions, sparing sensorimotor cortices. The shifting deficits were asymmetric (left hemisphere > right hemisphere) and correlated with progressively declining cognitive status (p < 0.0006). Novel brain mapping methods allowed us to visualize dynamic patterns of atrophy in 52 high-resolution magnetic resonance image scans of 12 patients with AD (age 68.4 ± 1.9 years) and 14 elderly matched controls (age 71.4 ± 0.9 years) scanned longitudinally (two scans; interscan interval 2.1 ± 0.4 years). A cortical pattern matching technique encoded changes in brain shape and tissue distribution across subjects and time. Cortical atrophy occurred in a well defined sequence as the disease progressed, mirroring the sequence of neurofibrillary tangle accumulation observed in cross sections at autopsy. Advancing deficits were visualized as dynamic maps that change over time. Frontal regions, spared early in the disease, showed pervasive deficits later (< 15% loss). The maps distinguished different phases of AD and differentiated AD from normal aging. Local gray matter loss rates (5.3 ± 2.3% per year in AD v 0.9 ± 0.9% per year in controls) were faster in the left hemisphere (p < 0.029) than the right. Transient barriers to disease progression appeared at limbic/frontal boundaries. This degenerative sequence, observed in vivo as it developed, provides the first quantitative, dynamic visualization of cortical atrophic rates in normal elderly populations and in those with dementia.

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We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 ± 1.9 years) and 14 matched controls (age: 71.4 ± 0.9 years), each scanned twice (2.1 ± 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

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We recently noticed an error in the demographic data in this article. The validity of the findings and the conclusions of the paper is not affected. However, there is an error in the reported sample size and in the means and standard deviations of the subjects’ ages and MMSE scores. We would like to correct this error, which came to light when we were re-analyzing the data for a meta-analysis. The error occurred because an older version of a spreadsheet was incorrectly used when reporting the sample composition. Instead of examining 12 Alzheimer's disease patients and 14 healthy elderly controls, we in fact examined 17 Alzheimer’s disease patients and 14 healthy elderly controls. All maps and morphometric data reported in the paper are correct, except that the sample size was in fact slightly higher than that originally reported, and the maps computed in the paper were based on the larger sample (which included five more subjects in the Alzheimer’s disease group). All of the maps and figures in the paper are correct, and the conclusions of the paper are unchanged. We apologize for this error, which falls under the sole responsibility of the first author. The corrected demographic information appears below.

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Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span.We describe three novel brain mapping techniques, cortical thickness mapping, tensor-based morphometry (TBM), and hippocampal surface modeling, which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI).We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer's disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling, plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.

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This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood- and adult-onset schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages.

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We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

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To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

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Roads and road infrastructure will be faced with multiple challenges over the coming decades – challenges that in many ways bear little resemblance to those previously faced - and as such will require new approaches. The opportunity exists to transform the way road infrastructure is conceived and constructed, as a key part of the process of assisting society to respond to climate change and reduce other environmental pressures. Innovations in road construction, use and management in order to manage these changes can now be seen. Scenario planning is one tool that can take into account emerging challenges, develop or adopt new approaches, and thus help this transformation to occur. The paper explores scenario planning methodologies, global innovations and trends in road construction and maintenance and the findings from stakeholder workshops in Brisbane and Perth. It highlights key opportunities for road agencies to use scenarios to enable planning that, in the face of future uncertainties, facilitates appropriate responses.

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There is widespread agreement that entrepreneurial skills are crucial for young people today, yet there are few studies of high school students engaging in entrepreneurship education that might prepare them for music industry careers. This study has been developed in response to these challenges. It explores a group of high school students (15 – 17 years) who alongside their teacher, have co-designed, developed and driven a new business venture, Youth Music Industries (YMI) since 2010. This venture staged cycles of differently scaled events featuring young artists for a young audience. The project was designed to give students a real business situation for developing their project management skills and a broader understanding of working in the music industry. Informed by concepts of social capital and communities of practice, the study examines the process of learning with and through others. This high-stakes environment increased their sense of presence and participation and made it possible for these young people to distribute expertise and learn from each other in a reciprocal and more democratic way. The ongoing success of this organisation can be attributed to the entrepreneurial competencies students developed. The resulting model and design principles talk to an ongoing challenge that has been identified in music education, and creative industries more generally. These principles offer a way forward for other music and creative industries educators or researchers interested in developing models of, and designs for, nurturing an entrepreneurial mindset.

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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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This unique and comprehensive collection investigates the challenges posed to intellectual property by recent paradigm shifts in biology. It explores the legal ramifications of emerging technologies, such as genomics, synthetic biology, stem cell research, nanotechnology, and biodiscovery. Extensive contributions examine recent controversial court decisions in patent law – such as Bilski v. Kappos, and the litigation over Myriad’s patents in respect of BRCA1 and BRCA2 – while other papers explore sui generis fields, such as access to genetic resources, plant breeders' rights, and traditional knowledge. The collection considers the potential and the risks of the new biology for global challenges – such as access to health-care, the protection of the environment and biodiversity, climate change, and food security. It also considers Big Science projects – such as biobanks, the 1000 Genomes Project, and the Doomsday Vault. The inter-disciplinary research brings together the work of scholars from Australia, Canada, Europe, the UK and the US and involves not only legal analysis of case law and policy developments, but also historical, comparative, sociological, and ethical methodologies. Intellectual Property and Emerging Technologies will appeal to policy-makers, legal practitioners, business managers, inventors, scientists and researchers.

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In her album, Hymns of the 49th Parallel, the chanteuse K.D. Lang pays tribute to a series of great Canadian songwriters—such as Neil Young, Leonard Cohen, Joni Mitchell and Jane Siberry. In a similar spirit of celebration, this review essay pays homage to a number of recent texts and films dealing with Canadian intellectual property. First, it considers Ysolde Gendreau’s collection, An Emerging Intellectual Property Paradigm: Perspectives from Canada. Second, this essay looks at Laura Murray and Samuel Trosow’s manual, Canadian Copyright: A Citizen’s Guide. Finally, this review evaluates Brett Gaylor’s documentary, RiP! A Remix Manifesto. The three works share certain affinities—a spirit of scepticism about the legitimacy and the efficacy of existing networks of law, policy and bureaucracy; a populist interest in the impact of intellectual property on the everyday lives of citizens, creators and consumers; a passion for human rights; and a melioristic desire for sensible law reform of copyright law and related regimes of intellectual property.