482 resultados para Dutch elm disease


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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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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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Aim To document current practice by dietitians in Australia and Canada in the nutrition management of Parkinson's disease. This will help identify priority areas for review and development of practice guidelines and direct future research. Methods Current practice in the phases of the Nutrition Care Plan was captured using an online survey distributed to Dietitians Association of Australia members and Practice-Based Evidence in Nutrition subscribers through their email newsletters. The results of the diagnosis, intervention and monitoring phases are presented here. Results Eighty-four dietitians responded. There was consistency in practice for nutrition issues that are encountered in other populations, such as malnutrition and constipation. There was more variation in practice in the nutrition issues that are more specific to Parkinson's disease, such as nutrition and meal interactions with medication. A lack of awareness of emerging treatments, such as deep brain stimulation surgery, appears to exist in the responding dietitians. Conclusions The variation in practice that was present for the nutrition issues specific to Parkinson's disease may reflect the lack of quality evidence and subsequently evidence-based guidelines in these areas. Work to provide background information about treatment options and to translate current evidence for the nutrition issues that are specific to Parkinson's disease into practice recommendations should be completed.

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Ankylosing spondylitis (AS) is a common inflammatory arthritic condition. Overt inflammatory bowel disease (IBD) occurs in about 10% of AS patients, and in addition 70% of AS cases may have subclinical terminal ileitis. Spondyloarthritis is also common in IBD patients. We therefore tested Crohn's disease susceptibility genes for association with AS, aiming to identify pleiotropic genetic associations with both diseases. Genotyping was carried out using Sequenom and Applied Biosystems TaqMan and OpenArray technologies on 53 markers selected from 30 Crohn's disease associated genomic regions. We tested genotypes in a population of unrelated individual cases (n = 2,773) and controls (n = 2,215) of white European ancestry for association with AS. Statistical analysis was carried out using a Cochran-Armitage test for trend in PLINK. Strong association was detected at chr1q32 near KIF21B (rs11584383, P = 1.66 x 10-10, odds ratio (OR) = 0.74, 95% CI:0.68-0.82). Association with disease was also detected for 2 variants within STAT3 (rs6503695, P = 4.6×10-4. OR = 0.86 (95% CI:0.79-0.93); rs744166, P = 2.6×10-5, OR = 0.84 (95% CI:0.77-0.91)). Association was confirmed for IL23R (rs11465804, P = 1.2×10-5, OR = 0.65 (95% CI:0.54-0.79)), and further associations were detected for IL12B (rs10045431, P = 5.261025, OR = 0.83 (95% CI:0.76-0.91)), CDKAL1 (rs6908425, P = 1.1×10-4, OR = 0.82 (95% CI:0.74-0.91)), LRRK2/MUC19 (rs11175593, P = 9.9×10-5, OR = 1.92 (95% CI: 1.38-2.67)), and chr13q14 (rs3764147, P = 5.9×10-4, OR = 1.19 (95% CI: 1.08-1.31)). Excluding cases with clinical IBD did not significantly affect these findings. This study identifies chr1q32 and STAT3 as ankylosing spondylitis susceptibility loci. It also further confirms association for IL23R and detects suggestive association with another 4 loci. STAT3 is a key signaling molecule within the Th17 lymphocyte differentiation pathway and further enhances the case for a major role of this T-lymphocyte subset in ankylosing spondylitis. Finally these findings suggest common aetiopathogenic pathways for AS and Crohn's disease and further highlight the involvement of common risk variants across multiple diseases.

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Background: Changing perspectives on the natural history of celiac disease (CD), new serology and genetic tests, and amended histological criteria for diagnosis cast doubt on past prevalence estimates for CD. We set out to establish a more accurate prevalence estimate for CD using a novel serogenetic approach.Methods: The human leukocyte antigen (HLA)-DQ genotype was determined in 356 patients with 'biopsy-confirmed' CD, and in two age-stratified, randomly selected community cohorts of 1,390 women and 1,158 men. Sera were screened for CD-specific serology.Results: Only five 'biopsy-confirmed' patients with CD did not possess the susceptibility alleles HLA-DQ2.5, DQ8, or DQ2.2, and four of these were misdiagnoses. HLA-DQ2.5, DQ8, or DQ2.2 was present in 56% of all women and men in the community cohorts. Transglutaminase (TG)-2 IgA and composite TG2/deamidated gliadin peptide (DGP) IgA/IgG were abnormal in 4.6% and 5.6%, respectively, of the community women and 6.9% and 6.9%, respectively, of the community men, but in the screen-positive group, only 71% and 75%, respectively, of women and 65% and 63%, respectively, of men possessed HLA-DQ2.5, DQ8, or DQ2.2. Medical review was possible for 41% of seropositive women and 50% of seropositive men, and led to biopsy-confirmed CD in 10 women (0.7%) and 6 men (0.5%), but based on relative risk for HLA-DQ2.5, DQ8, or DQ2.2 in all TG2 IgA or TG2/DGP IgA/IgG screen-positive subjects, CD affected 1.3% or 1.9%, respectively, of females and 1.3% or 1.2%, respectively, of men. Serogenetic data from these community cohorts indicated that testing screen positives for HLA-DQ, or carrying out HLA-DQ and further serology, could have reduced unnecessary gastroscopies due to false-positive serology by at least 40% and by over 70%, respectively.Conclusions: Screening with TG2 IgA serology and requiring biopsy confirmation caused the community prevalence of CD to be substantially underestimated. Testing for HLA-DQ genes and confirmatory serology could reduce the numbers of unnecessary gastroscopies. © 2013 Anderson et al.; licensee BioMed Central Ltd.

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Familial autosomal dominant calcium pyrophosphate dihydrate (CPPD) chondrocalcinosis has previously been mapped to chromosome 5pl5. We have identified a mutation in the ANKH gene that segregates with the disease in a family with this condition. ANKH encodes a putative transmembrane inorganic pyrophosphate (PPi) transport channel. We postulate that loss of function of ANKH causes elevated extracellular PPi levels, predisposing to CPPD crystal deposition.

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Patients with rheumatoid arthritis (RA) have a significantly higher risk of coronary heart disease, despite being less likely to report symptoms of angina, and are more likely to experience unrecognised myocardial infarction and sudden cardiac death than non-RA controls.1 Furthermore, left ventricular diastolic dysfunction has been described in up to 40% of patients with RA.2...

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New classification criteria for axial spondyloarthritis have been developed with the goal of increasing sensitivity of criteria for early inflammatory spondyloarthritis. However these criteria substantially increase heterogeneity of the resulting disease group, reducing their value in both research and clinical settings. Further research to establish criteria based on better knowledge of the natural history of non-radiographic axial spondyloarthritis, its aetiopathogenesis and response to treatment is required. In the meantime the modified New York criteria for ankylosing spondylitis remain a very useful classification criteria set, defining a relatively homogenous group of cases for clinical use and research studies.