956 resultados para DIFFERENTIATE ALZHEIMERS-DISEASE


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The clinical presentation and neuroimaging findings of children with pseudotumoral hemicerebellitis (PTHC) and Lhermitte-Duclos disease (LDD) may be very similar. The differentiation between these entities, however, is important because their management and prognosis are different. We report on three children with PTHC. For all three children, in the acute situation, the differentiation between PTHC and LDD was challenging. A review of the literature shows that a detailed evaluation of conventional and neuroimaging data may help to differentiate between these two entities. A striated folial pattern, brainstem involvement, and prominent veins surrounding the thickened cerebellar foliae on susceptibility weighted imaging favor LDD, while post-contrast enhancement and an increased choline peak on (1)H-Magnetic resonance spectroscopy suggest PTHC.

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The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3% and specificity of 70%. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.

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The aim of this study was to analyze the effects of dual tasking on obstacle crossing during walking by individuals with Alzheimer's disease (AD) and by healthy older people. Thirty four elderly individuals (16 healthy subjects and 18 individuals with AD) were recruited to participate in this study. Three AD individuals and one control participant were excluded due to exclusion criteria. The participants were instructed to walk barefoot at their own speed along an 8 m long pathway. Each participant performed five trials for each condition (unobstructed walking, unobstructed walking with dual tasking, and obstacle crossing during walking with dual tasking). The trials were completely randomized for each participant. The mid-pathway stride was measured in the unobstructed walking trials and the stride that occurred during the obstacle avoidance was measured in the trials that involved obstacle crossing. The behavior of the healthy elderly subjects and individuals with AD was similar for obstacle crossing during walking with dual tasking. Both groups used the posture first strategy to prioritize stability and showed decreased attention to executive tasking while walking. Additionally, AD had a strong influence on the modifications that are made by the elderly while walking under different walking conditions.

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There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

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The neuropathological changes associated with Huntington's disease (HD) are most marked in the head of the caudate nucleus and, to a lesser extent, in the putamen and globus pallidus, suggesting that at least part of the language impairments found in patients with HD may result from non-thalamic subcortical (NTS) pathology. The present study aimed to test the hypothesis that a signature profile of impaired language functions is found in patients who have sustained damage to the non-thalamic subcortex, either focally induced or resulting from neurodegenerative pathology. The language abilities of a group of patients with Huntington's disease (n=13) were compared with those of an age- and education-matched group of patients with chronic NTS lesions following stroke (n=13) and a non-neurologically impaired control group (n=13). The three groups were compared on language tasks that assessed both primary and more complex language abilities. The primary language battery consisted of The Western Aphasia Battery and The Boston Naming Test, whilst the more complex cognitive-linguistic battery employed selected subtests from The Test of Language Competence-Expanded, The Test of Word Knowledge and The Word Test-Revised. On many of the tests of primary language function from the Western Aphasia Battery, both the HD and NTS participants performed in a similar manner to the control participants. The language performances of the HD participants were significantly more impaired (p<0.05 using modified Bonferroni adjustments) than the control group, however, on various lexico-semantic tasks (e. g. the Boston Naming Test and providing definitions), on both single-word and sentence-level generative tasks (e. g. category fluency and formulating sentences), and on tasks which required interpretation of ambiguous, figurative and inferential meaning. The difficulties that patients with HD experienced with tasks assessing complex language abilities were strikingly similar, both qualitatively and quantitatively, to the language profile produced by NTS participants. The results provide evidence to suggest that a signature language profile is associated with damage to the non-thalamic subcortex resulting from either focal neurological insult or a degenerative disease.

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INTRODUCTION: Exanthem subitum is a classical rash disease of early childhood caused by human herpesvirus 6B (HHV-6B). However, the rash is frequently misdiagnosed as that of either measles or rubella. METHODS: In this study, a nested multiplex polymerase chain reaction (PCR) was used to diagnose HHV-6B primary infection, differentiate it from infections caused by HHV-6A and compare it to antibody avidity tests. The samples were separated into case group and control group according to the results of the indirect immunofluorescence assay (IFA) technique. RESULTS: From the saliva samples analyzed, HHV-6A DNA was detected in 3.2% of the case group and in 2.6% of the control group. Regarding HHV-6B, PCR detected viral DNA in 4.8% of the case group and in 1.3% of the control group. Among the serum samples studied, a frequency of 1.7% was determined for HHV-6A in the case group and 1.2% in the control group. PCR did not detect HHV-6B DNA in serum samples. The sensitivity and specificity of the PCR technique ranged from 0% to 4.8% and 97.5% to 100%, respectively, compared to IFA. CONCLUSIONS: The PCR technique was not suitable for diagnosing primary infection by HHV-6B in children with exanthematic disease and should not substitute the IFA.

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Introduction CD4+CD25+ T lymphocytes have been implicated in the regulation of host inflammatory response against Trypanosoma cruzi, and may be involved in the clinical course of the disease. Methods Peripheral blood mononuclear cells from patients with chronic Chagas disease were cultured in the presence of T. cruzi recombinant antigens and assayed for lymphocytes at distinct time points. Results It was possible to differentiate clinical forms of chronic Chagas disease at days 3 and 5 according to presence of CD4+CD25+ T cells in cell cultures. Conclusions Longer periods of cell culture proved to be potentially valuable for prospective evaluations of CD4+CD25+ T lymphocytes in patients with chronic Chagas disease.

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OBJECTIVE: To differentiate the nature of functional cardiorespiratory limitations during exercise in individuals with chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF) and to determine indicators that may help their classifications. METHODS: The study comprised 40 patients: 23 with COPD and 17 with CHF. All individuals underwent maximal cardiopulmonary exercise testing on a treadmill. RESULTS: The values of peak gas exchange ratio (R peak), peak carbon dioxide production (VCO2 peak), and peak oxygen ventilatory equivalent (V E O2 peak) were higher in the patients with CHF than in those with COPD, and, therefore, those were the variables that characterized the differences between the groups. For group classification, the differentiating functions with the R peak, VCO2 peak (L/min), and V E O2 peak variables were used as follows: group COPD: - 44.886 + 78.832 x R peak + 5.442 x VCO2 peak + 0.336 x V E O2 peak; group CHF: - 69.251 + 89.740 x R peak + 8.461 x VCO2 peak + 0.574 x V E O2 peak. The differentiating function, whose result is greater, correctly classifies the patient's group as 90%. CONCLUSION: The R peak, VCO2 peak, and V E O2 peak values may be used to identify the cause of the functional cardiorespiratory limitations in patients with COPD and CHF.

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Enzyme polymorphism in Rhodnius prolixus and R. pallescens (Hemiptera, Reduviidae), principal vectors of Chagas' disease in Colombia, was analyzed using starch gel electrophoresis. Three geographic locations were sampled in order to determine gene flow between populations and to characterize intra- and interspecific differences. Of 25 enzymes assayed 10 were successfully resolved and then used to score the genetic variation. The enzymes PEPD, GPI, PGM and ICD were useful to differentiate these species and PGD, PGM and MDH distinguished between sylvatic and domiciliary populations of R. prolixus. Both polymorphism and heterozygosity indicated greater genetic variability in sylvatic habitats (H = 0.021) compared to domiciliary habitats (H = 0.006) in both species. Gene flow between sylvatic and domiciliary populations in R. prolixus was found to be minimal. This fact and the genetic distance between them suggest a process of genetic isolation in the domiciliary population.

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Neuroimaging techniques provide valuable tools for diagnosing Alzheimer's disease (AD), monitoring disease progression and evaluating responses to treatment. There is currently a wide array of techniques available including computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and, for recording electrical brain activity, electroencephalography (EEG). The choice of technique depends on the contrast between tissues of interest, spatial resolution, temporal resolution, requirements for functional data and the probable number of scans required. For example, while PET, CT and MRI can be used to differentiate between AD and other dementias, MRI is safer and provides better contrast of soft tissues. Neuroimaging is a technique spanning many disciplines and requires effective communication between doctors requesting a scan of a patient or group of patients and those with technical expertise. Consideration and discussion of the most suitable type of scan and the necessary settings to achieve the best results will help ensure appropriate techniques are chosen and used effectively. Neuroimaging techniques are currently expanding understanding of the structural and functional changes that occur in dementia. Further research may allow identification of early neurological signs ofAD, before clinical symptoms are evident, providing the opportunity to test preventative therapies. CombiningMRI and machine learning techniques may be a powerful approach to improve diagnosis ofAD and to predict clinical outcomes.

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This report gives a comprehensive and up-to-date review of Alzheimer's disease biomarkers. Recent years have seen significant advances in this field. Whilst considerable effort has focused on A�_ and tau related markers, a substantial number of other molecules have been identified, that may offer new opportunities.This Report : Identifies 60 candidate Alzheimer's (AD) biomarkers and their associated studies. Of these, 49 are single species or single parameters, 7 are combinations or panels and 4 involve the measurement of two species or parameters or their ratios. These include proteins (n=34), genes (n=11), image-based parameters (n=7), small molecules (n=3), proteins + genes (n=2) and others (n=3). Of these, 30 (50%) relate to species identified in CSF and 19 (32%) were found in the blood. These candidate may be classified on the basis of their diagnostic utility, namely those which i) may allow AD to be detected when the disease has developed (48 of 75†= 64%), ii) may allow early detection of AD (18 of 75† = 24%) and iii) may allow AD to be predicted before the disease has begun to develop (9 of 75†= 12%). † Note: Of these, 11 were linked to two or more of these capabilities (e.g. allowed both early-stage detection as well as diagnosis after the disease has developed).Biomarkers: AD biomarkers identified in this report show significant diversity, however of the 60 described, 18 (30%) are associated with amyloid beta (A�_) and 9 (15%) relate to Tau. The remainder of the biomarkers (just over half) fall into a number of different groups. Of these, some are associated with other hypotheses on the pathogenesis of AD however the vast majority are individually unique and not obviously linked with other markers. Analysis and discussion presented in this report includes summaries of the studies and clinical trials that have lead to the identification of these markers. Where it has been calculated, diagnostic sensitivity, specificity and the capacity of these markers to differentiate patients with suspected AD from healthy controls and individuals believed to be suffering from other neurodegenerative conditions, have been indicated. These findings are discussed in relation to existing hypotheses on the pathogenesis of the AD and the current drug development pipeline. Many uncertainties remain in relation to the pathogenesis of AD, in diagnosing and treating the disease and many of the studies carried out to identify disease markers are at an early stage and will require confirmation through larger and longer investigations. Nevertheless, significant advances in the identification of AD biomarkers have now been made. Moreover, whilst much of the research on AD biomarkers has focused on amyloid and tau related species, it is evident that a substantial number of other species may provide important opportunities.Purpose of Report: To provide a comprehensive review of important and recently discovered candidate biomarkers of AD, in particular those with potential to reliably detect the disease or with utility in clinical development, drug repurposing, in studies of the pathogenesis and in monitoring drug response and the course of the disease. Other key goals were to identify markers that support current pipeline developments, indicate new potential drug targets or which advance understanding of the pathogenesis of this disease.Drug Repurposing: Studies of the pathogenesis of AD have identified aberrant changes in a number of other disease areas including inflammation, diabetes, oxidative stress, lipid metabolism and others. These findings have prompted studies to evaluate some existing approved drugs to treat AD. This report identifies studies of 9 established drug classes currently being investigated for potential repurposing.Alzheimer’s Disease: In 2005, the global prevalence of dementia was estimated at 25 million, with more than 4 million new cases occurring each year. It is also calculated that the number of people affected will double every 20 years, to 80 million by 2040, if a cure is not found. More than 50% of dementia cases are due to AD. Today, approximately 5 million individuals in the US suffer from AD, representing one in eight people over the age of 65. Direct and indirect costs of AD and other forms of dementia in the US are around $150 billion annually. Worldwide, costs for dementia care are estimated at $315 billion annually. Despite significant research into this debilitating and ultimately fatal disease, advances in the development of diagnostic tests for AD and moreover, effective treatments, remain elusive.Background: Alzheimer's disease is the most common cause of dementia, yet its clinical diagnosis remains uncertain until an eventual post-mortem histopathology examination is carried out. Currently, therapy for patients with Alzheimer disease only treats the symptoms; however, it is anticipated that new disease-modifying drugs will soon become available. The urgency for new and effective treatments for AD is matched by the need for new tests to detect and diagnose the condition. Uncertainties in the diagnosis of AD mean that the disease is often undiagnosed and under treated. Moreover, it is clear that clinical confirmation of AD, using cognitive tests, can only be made after substantial neuronal cell loss has occurred; a process that may have taken place over many years. Poor response to current therapies may therefore, in part, reflect the fact that such treatments are generally commenced only after neuronal damage has occurred. The absence of tests to detect or diagnose presymptomatic AD also means that there is no standard that can be applied to validate experimental findings (e.g. in drug discovery) without performing lengthy studies, and eventual confirmation by autopsy.These limitations are focusing considerable effort on the identification of biomarkers that advance understanding of the pathogenesis of AD and how the disease can be diagnosed in its early stages and treated. It is hoped that developments in these areas will help physicians to detect AD and guide therapy before the first signs of neuronal damage appears. The last 5-10 years have seen substantial research into the pathogenesis of AD and this has lead to the identification of a substantial number of AD biomarkers, which offer important insights into this disease. This report brings together the latest advances in the identification of AD biomarkers and analyses the opportunities they offer in drug R&D and diagnostics.��

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����This survey commissioned by Alzheimer Europe��examined public perception and awareness of Alzheimer’s disease and aimed to identify the views of the general public on the value of diagnosis. The survey of 2,678 people was designed and analysed by the Harvard School of Public Health and Alzheimer Europe. Fieldwork was conducted via telephone (landline and cell phone) with nationally representative random samples of adults age 18 and older in five countries by TNS, an independent research company based in London. Countries surveyed were the USA, Germany, France, Spain and Poland. The survey was supported by a grant to Alzheimer Europe from Bayer AG. Bayer was not involved in the design of the survey or the analysis of the findings.��Full details of the survey results are available on the AE website at: http://www.alzheimer-europe.org/EN/Research��Alzheimer Europe is the umbrella organisation of national Alzheimer associations and currently has 31 member organisations in 27 European countries. The mission statement of the organisation is to change perceptions, practice and policy to ensure equal access of people with dementia to a high level of care services and treatment options.����

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Chagas disease (CD) causes the highest burden of parasitic diseases in the Western Hemisphere and is therefore a priority for drug research and development. Platelet-activating factor (PAF) causes the CD parasite Trypanosoma cruzi to differentiate, which suggests that the parasite may express PAF receptors. Here, we explored the T. cruzi proteome for PAF receptor-like proteins. From a total of 23,000 protein sequences, we identified 29 hypothetical proteins that are predicted to have seven transmembrane domains (TMDs), which is the main characteristic of the G protein-coupled receptors (GPCRs), including the PAF receptor. The TMDs of these sequences were independently aligned with domains from 25 animal PAF receptors and the sequences were analysed for conserved residues. The conservation score mean values for the TMDs of the hypothetical proteins ranged from 31.7-44.1%, which suggests that if the putative T. cruzi PAF receptor is among the sequences identified, the TMDs are not highly conserved. These results suggest that T. cruzi contains several GPCR-like proteins and that one of these GPCRs may be a PAF receptor. Future studies may further validate the PAF receptor as a target for CD chemotherapy.

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Patients with stage-I (very mild and mild) Alzheimer s disease were asked to participatein a Dictator Game, a type of game in which a subject has to decide how to allocate acertain amount of money between himself and another person. The game enables theexperimenter to examine the influence of social norms and social preferences on thedecision-making process. When the results of treatments involving Alzheimer s diseasepatients were compared with those of identical treatments involving patients with mildcognitive impairment or healthy control subjects, with similar ages and socialbackgrounds, no statistically significant difference was found. This finding suggests thatstage-I Alzheimer s disease patients may be as capable of making decisions involvingsocial norms and preferences as other individuals of their age. Whatever brain structuresare affected by the disease, they do not appear to influence, at this early stage, the neuralbasis for cooperation-enhancing social interactions.

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To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.