973 resultados para COGNITIVE DECLINE
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AIMS: Cognitive decline in Alzheimer's disease (AD) patients has been linked to synaptic damage and neuronal loss. Hyperphosphorylation of tau protein destabilizes microtubules leading to the accumulation of autophagy/vesicular material and the generation of dystrophic neurites, thus contributing to axonal/synaptic dysfunction. In this study, we analyzed the effect of a microtubule-stabilizing compound in the progression of the disease in the hippocampus of APP751SL/PS1M146L transgenic model. METHODS: APP/PS1 mice (3 month-old) were treated with a weekly intraperitoneal injection of 2 mg/kg epothilone-D (Epo-D) for 3 months. Vehicle-injected animals were used as controls. Mice were tested on the Morris water maze, Y-maze and object-recognition tasks for memory performance. Abeta, AT8, ubiquitin and synaptic markers levels were analyzed by Western-blots. Hippocampal plaque, synaptic and dystrophic loadings were quantified by image analysis after immunohistochemical stainings. RESULTS: Epo-D treated mice exhibited a significant improvement in the memory tests compared to controls. The rescue of cognitive deficits was associated to a significant reduction in the AD-like hippocampal pathology. Levels of Abeta, APP and ubiquitin were significantly reduced in treated animals. This was paralleled by a decrease in the amyloid burden, and more importantly, in the plaque-associated axonal dystrophy pathology. Finally, synaptic levels were significantly restored in treated animals compared to controls. CONCLUSION: Epo-D treatment promotes synaptic and spatial memory recovery, reduces the accumulation of extracellular Abeta and the associated neuritic pathology in the hippocampus of APP/PS1 model. Therefore, microtubule stabilizing drugs could be considered therapeutical candidates to slow down AD progression. Supported by FIS-PI12/01431 and PI15/00796 (AG),FIS-PI12/01439 and PI15/00957(JV)
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Trabalho de Projeto apresentado à Escola Superior de Educação do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gerontologia Social.
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El propósito de este estudio es medir los efectos que tiene el videojuego League of Legends en los procesos cognitivos de memoria de trabajo visual (MVT) y solución de problemas (SP). Para medir dichos efectos se implementó un diseño pre test-post con un grupo experimental y uno control, compuestos cada uno por siete participantes, en donde se evaluaron los procesos previamente mencionados utilizando los cubos de Corsi para MVT y las matrices del WAIS III para SP. Después de realizar los respectivos entrenamientos se encontraron resultados significativos en los diferentes momentos de aplicación. En el grupo experimental se encontraron diferencias en la variable dependiente SP, mientras que en el grupo control en MVT, pero no en la interacción entre grupos ni diferencias entre grupos, lo que sugiere un efecto de familiarización a la prueba.
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El presente trabajo tuvo como objetivo evaluar la existencia de la relación entre la atrofia cortical difusa objetivada por neuroimagenes cerebrales y desempeños cognitivos determinados mediante la aplicación de pruebas neuropsicológicas que evalúan memoria de trabajo, razonamiento simbólico verbal y memoria anterógrada declarativa. Participaron 114 sujetos reclutados en el Hospital Universitario Mayor Méderi de la ciudad de Bogotá mediante muestreo de conveniencia. Los resultados arrojaron diferencias significativas entre los dos grupos (pacientes con diagnóstico de atrofia cortical difusa y pacientes con neuroimagenes interpretadas como dentro de los límites normales) en todas las pruebas neuropsicológicas aplicadas. Respecto a las variables demográficas se pudo observar que el grado de escolaridad contribuye como factor neuroprotector de un posible deterioro cognitivo. Tales hallazgos son importantes para determinar protocoles tempranos de detección de posible instalación de enfermedades neurodegenerativas primarias.
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Magnetic Resonance Imaging (MRI) is the in vivo technique most commonly employed to characterize changes in brain structures. The conventional MRI-derived morphological indices are able to capture only partial aspects of brain structural complexity. Fractal geometry and its most popular index, the fractal dimension (FD), can characterize self-similar structures including grey matter (GM) and white matter (WM). Previous literature shows the need for a definition of the so-called fractal scaling window, within which each structure manifests self-similarity. This justifies the existence of fractal properties and confirms Mandelbrot’s assertion that "fractals are not a panacea; they are not everywhere". In this work, we propose a new approach to automatically determine the fractal scaling window, computing two new fractal descriptors, i.e., the minimal and maximal fractal scales (mfs and Mfs). Our method was implemented in a software package, validated on phantoms and applied on large datasets of structural MR images. We demonstrated that the FD is a useful marker of morphological complexity changes that occurred during brain development and aging and, using ultra-high magnetic field (7T) examinations, we showed that the cerebral GM has fractal properties also below the spatial scale of 1 mm. We applied our methodology in two neurological diseases. We observed the reduction of the brain structural complexity in SCA2 patients and, using a machine learning approach, proved that the cerebral WM FD is a consistent feature in predicting cognitive decline in patients with small vessel disease and mild cognitive impairment. Finally, we showed that the FD of the WM skeletons derived from diffusion MRI provides complementary information to those obtained from the FD of the WM general structure in T1-weighted images. In conclusion, the fractal descriptors of structural brain complexity are candidate biomarkers to detect subtle morphological changes during development, aging and in neurological diseases.
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Deep learning methods are extremely promising machine learning tools to analyze neuroimaging data. However, their potential use in clinical settings is limited because of the existing challenges of applying these methods to neuroimaging data. In this study, first a data leakage type caused by slice-level data split that is introduced during training and validation of a 2D CNN is surveyed and a quantitative assessment of the model’s performance overestimation is presented. Second, an interpretable, leakage-fee deep learning software written in a python language with a wide range of options has been developed to conduct both classification and regression analysis. The software was applied to the study of mild cognitive impairment (MCI) in patients with small vessel disease (SVD) using multi-parametric MRI data where the cognitive performance of 58 patients measured by five neuropsychological tests is predicted using a multi-input CNN model taking brain image and demographic data. Each of the cognitive test scores was predicted using different MRI-derived features. As MCI due to SVD has been hypothesized to be the effect of white matter damage, DTI-derived features MD and FA produced the best prediction outcome of the TMT-A score which is consistent with the existing literature. In a second study, an interpretable deep learning system aimed at 1) classifying Alzheimer disease and healthy subjects 2) examining the neural correlates of the disease that causes a cognitive decline in AD patients using CNN visualization tools and 3) highlighting the potential of interpretability techniques to capture a biased deep learning model is developed. Structural magnetic resonance imaging (MRI) data of 200 subjects was used by the proposed CNN model which was trained using a transfer learning-based approach producing a balanced accuracy of 71.6%. Brain regions in the frontal and parietal lobe showing the cerebral cortex atrophy were highlighted by the visualization tools.
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Neuroinflammation represents a key hallmark of neurodegenerative diseases and is the result of a complex network of signaling cascades within microglial cells. A positive feedback loop exists between inflammation, microglia activation and protein misfolding processes, that, together with oxidative stress and excitotoxicity, lead to neuronal degeneration. Therefore, targeting this vicious cycle can be beneficial for mitigating neurodegeneration and cognitive decline in central nervous system disorders. At molecular level, GSK-3B and Fyn kinases play a crucial role in microglia activation and their deregulation has been associated to many neurodegenerative diseases. Thus, we envisioned their combined targeting as an effective approach to disrupt this toxic loop. Specifically in this project, a hit compound, based on a 7-azaindole-3-aminothiazole structure, was first identified in a virtual screening campaign, and displayed a weak dual inhibitory activity on GSK-3B and Fyn, unbalanced towards the former. Then, in a commitment to uncover the structural features required for modulating the activity on the two targets, we systematically manipulated this compound by inserting various substitution patterns in different positions. The most potent compounds obtained were advanced to deeper investigations to test their ability of tackling the inflammatory burden also in cellular systems and to unveil their binding modes within the catalytic pocket. The new class of molecules synthesized emerged as a valuable tool to deepen our understanding of the complex network governing the inflammatory events in neurodegenerative disorders.
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Alzheimer’s Disease and other dementias are one of the most challenging illnesses confronting countries with ageing populations. Treatment options for dementia are limited, and the costs are significant. There is a growing need to develop new treatments for dementia, especially for the elderly. There is also growing evidence that centrally acting angiotensin converting enzyme (ACE) inhibitors, which cross the blood-brain barrier, are associated with a reduced rate of cognitive and functional decline in dementia, especially in Alzheimer’s disease (AD). The aim of this research is to investigate the effects of centrally acting ACE inhibitors (CACE-Is) on the rate of cognitive and functional decline in dementia, using a three phased KDD process. KDD, as a scientific way to process and analysis clinical data, is used to find useful insights from a variety of clinical databases. The data used are from three clinic databases: Geriatric Assessment Tool (GAT), the Doxycycline and Rifampin for Alzheimer’s Disease (DARAD), and the Qmci validation databases, which were derived from several different geriatric clinics in Canada. This research involves patients diagnosed with AD, vascular or mixed dementia only. Patients were included if baseline and end-point (at least six months apart) Standardised Mini-Mental State Examination (SMMSE), Quick Mild Cognitive Impairment (Qmci) or Activities Daily Living (ADL) scores were available. Basically, the rates of change are compared between patients taking CACE-Is, and those not currently treated with CACE-Is. The results suggest that there is a statistically significant difference in the rate of decline in cognitive and functional scores between CACE-I and NoCACE-I patients. This research also validates that the Qmci, a new short assessment test, has potential to replace the current popular screening tests for cognition in the clinic and clinical trials.
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The main objective of this study was to examine the relationships among demographic characteristics, depressive symptoms, and cognitive impairment in oldest-old elders from rural areas of the Brazilian State of Rio Grande do Sul. A cross-sectional, descriptive correlational design was used to conduct the study. 137 Brazilian elders age 80 years or over. A target population data form, a county data form, a demographic questionnaire, the Mini-Mental State Examination, and the Depressive Cognition Scale were used to collect the data. A significant difference was found between males and females in regard to cognitive impairment. In addition, educational level and depressive symptoms were correlated with cognitive impairment. Depressive symptoms were a weak but significant predictor of cognitive impairment after controlling for the effect of age, gender, and educational level of the oldest-old elders. The findings need to be interpreted cautiously since the sample scored above the cutoff points for cognitive impairment, and had low scores on depressive symptoms. Despite several limitations, findings from this study can be a foundation for further studies, and well-designed correlational or experimental approaches, are warranted.
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Background: At least for a subset of patients, the clinical diagnosis of mild cognitive impairment (MCI) may represent an intermediate stage between normal aging and dementia. Nevertheless, the patterns of transition of cognitive states between normal cognitive aging and MCI to dementia are not well established. In this study we address the pattern of transitions between cognitive states in patients with MCI and healthy controls, prior to the conversion to dementia. Methods: 139 subjects (78% women, mean age, 68.5 +/- 6.1 years; mean educational level, 11.7 +/- 5.4 years) were consecutively assessed in a memory clinic with a standardized clinical and neuropsychological protocol, and classified as cognitively healthy (normal controls) or with MCI (including subtypes) at baseline. These subjects underwent annual reassessments (mean duration of follow-up: 2.7 +/- 1.1 years), in which cognitive state was ascertained independently of prior diagnoses. The pattern of transitions of the cognitive state was determined by Markov chain analysis. Results: The transitions from one cognitive state to another varied substantially between MCI subtypes. Single-domain MCI (amnestic and non-amnestic) more frequently returned to normal cognitive state upon follow-up (22.5% and 21%, respectively). Among subjects who progressed to Alzheimer`s disease (AD), the most common diagnosis immediately prior conversion was multiple-domain MCI (85%). Conclusion: The clinical diagnosis of MCI and its subtypes yields groups of patients with heterogeneous patterns of transitions between one given cognitive state to another. The presence of more severe and widespread cognitive deficits, as indicated by the group of multiple-domain amnestic MCI may be a better predictor of AD than single-domain amnestic or non-amnestic deficits. These higher-risk individuals could probably be the best candidates for the development of preventive strategies and early treatment for the disease.
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Background: Previous studies have reported an association between executive dysfunction and the ability to perform activities of daily living (ADL)s among older adults. This study aims to examine the association between executive functions and functional status in a cross-section of older adults with varying degrees of cognitive impairment. Methods: 89 individuals (mean age 73.8 years) were recruited at a memory clinic in Sao Paulo, Brazil. Subjects underwent evaluation, and were allocated into three diagnostic groups according to cognitive status: normal controls (NC, n = 32), mild cognitive impairment (MCI, n = 3 1) and mild Alzheimer`s disease (AD, n=26). Executive functions were assessed with the 25-item Executive Interview (EXIT25), and functional status was measured with the Direct Assessment of Functional Status test (DAFS-R). Results: Significantly different total DAFS-R scores were observed across the three diagnostic groups. Patients with AD performed significantly worse in EXIT25 compared with subjects without dementia, and no significant differences were detected between NC and MCI patients. We found a robust negative correlation between the DAFS-R and the EXIT25 scores (r=-0.872, p < 0.001). Linear regression analyses suggested a significant influence of the EXIT-25 and the CAMCOG on the DAFS-R scores. Conclusion: Executive dysfunction and decline in general measures of cognitive functioning are associated with a lower ability to undertake instrumental ADLs. MCI patients showed worse functional status than NC subjects. MCI patients may show subtle changes in functional status that may only be captured by objective measures of ADLs.
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Background The CAMCOG is a brief neuropsychological battery designed to assess global cognitive function and ascertain the impairments that are required for the diagnosis of dementia. To date, the cut-off scores for mild cognitive impairment (MCI) have not been determined. Given the need for an earlier diagnosis of mild dementia, new cut-off values are also necessary, taking into account cultural and educational effects. Methods One hundred and fifty-seven older adults (mean age: 69.6 +/- 7.4 years) with 8 or more years of formal education (mean years of schooling 14.2 +/- 3.8) attending a memory clinic at the Institute of Psychiatry University of Sao Paulo were included. Subjects were divided into three groups according to their cognitive status, established through clinical and neuropsychological assessment: normal controls, n = 62; MCI, n = 65; and mild or moderate dementia, n = 30. ROC curve analyses were performed for dementia vs controls, MCI vs controls and MCI vs dementia. Results The cut-off values were: 92/93 for dementia is controls (AUC = 0.99: sensitivity: 100%, specificity: 95%); 95/96 for MCI vs controls (AUC = 0.83, sensitivity: 64%, specificity: 88%), and 85/86 for MCI vs dementia (AUC = 0.91, sensitivity: 81%, specificity: 88%). The total CAMCOG score was more accurate than its subtests Mini-mental State Examination, Verbal Fluency Test and Clock Drawing Test when used separately. Conclusions The CAMCOG discriminated controls and MCI from demented patients, but was less accurate to discriminate MCI from controls. The best cut-off value to differentiate controls and demented was higher than suggested in the original publication, probably because only cases of mild to moderate dementia were included. This is important given the need for a diagnostic at earlier stages of Alzheimer`s disease. Copyright (C) 2008 John Wiley & Sons, Ltd.
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Purpose: Fifty percent of patients with Multiple Sclerosis (MS) are estimated to have cognitive impairments leading to considerable decline in productivity and quality of life. Cognitive intervention has been considered to complement pharmacological treatments. However, a lack of agreement concerning the efficacy of cognitive interventions in MS still exists. A systematic review and meta-analysis was conducted to assess the effects of cognitive interventions in MS. Methods: To overcome limitations of previous meta-analyses, several databases were searched only for Randomized Clinical Trials (RCTs) with low risk of bias. Results: Five studies (total of 139 participants) met our eligibility criteria. Although good completion and adherence rates were evident, we found no evidence of intervention effects on cognition or mood in post-intervention or follow-up assessments. Conclusions: This is the first meta-analysis assessing the effects of cognitive intervention in MS including only RCTs with comparable conditions. Research regarding efficacy, cost-effectiveness and feasibility is still in its infancy. Caution is advised when interpreting these results due to the small number of RCTs meeting the inclusion criteria. Considering the costs of disease, good completion and adherence rates of this approach, further research is warranted. Recommendations concerning improved research practices in the field are presented as well.
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Background: Coronary artery bypass graft (CABG) is a standard surgical option for patients with diffuse and significant arterial plaque. This procedure, however, is not free of postoperative complications, especially pulmonary and cognitive disorders. Objective: This study aimed at comparing the impact of two different physiotherapy treatment approaches on pulmonary and cognitive function of patients undergoing CABG. Methods: Neuropsychological and pulmonary function tests were applied, prior to and following CABG, to 39 patients randomized into two groups as follows: Group 1 (control) - 20 patients underwent one physiotherapy session daily; and Group 2 (intensive physiotherapy) - 19 patients underwent three physiotherapy sessions daily during the recovery phase at the hospital. Non-paired and paired Student t tests were used to compare continuous variables. Variables without normal distribution were compared between groups by using Mann-Whitney test, and, within the same group at different times, by using Wilcoxon test. The chi-square test assessed differences of categorical variables. Statistical tests with a p value ≤ 0.05 were considered significant. Results: Changes in pulmonary function were not significantly different between the groups. However, while Group 2 patients showed no decline in their neurocognitive function, Group 1 patients showed a decline in their cognitive functions (P ≤ 0.01). Conclusion: Those results highlight the importance of physiotherapy after CABG and support the implementation of multiple sessions per day, providing patients with better psychosocial conditions and less morbidity.
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Background: Cerebral cholinergic transmission plays a key role in cognitive function and anticholinergic drugs are associated with impaired cognitive functions [1]. In the perioperative phase many substances with anticholinergic effects are administered and disturbed cholinergic transmission is a hypothetical cause of postoperative cognitive dysfunction (POCD). Serum anticholinergic activity (SAA; pmol/ml) may be measured as a summary marker of anticholinergic activity in an individual patient's blood. We hypothesised that an increase in SAA from preoperatively to one week postoperatively is associated with POCD in elderly patients. Methods: Thirty-two patients aged >65 yrs undergoing elective major surgery under standardized general anaesthesia (thiopental, sevoflurane, fentanyl) were investigated. Cognitive functions were measured preoperatively and 7 days postoperatively using the extended version of the Consortium to Establish a Registry for Alzheimer's Disease - Neuropsychological Assessment Battery. POCD was defined as a postoperative decline >1 z-score in at least 2 cognitive domains. SAA was measured preoperatively and 7 days postoperatively at the time of cognitive testing. Results: 50% of the investigated patients developed POCD. There were no statistically significant differences between patients with and without POCD regarding age, education, baseline cognitive function, duration of anaesthesia, SAA preoperatively (median (range) 1.0 (0.3 to 5.0) vs 1.5 (0.4 to 5.0), SAA 7 days postoperatively (median (range) 1.3 (0.1 to 7.0) vs 1.4 (0.6 to 5.5) or changes in SAA (median (range) 0.1 (-1.6 to 2.2) vs 0.2 (-1.4 to 2.8). The variability of SAA in individual patients was considerable and marked changes in SAA between the two examinations were observed in some patients. However, there was no significant relationship between changes in SAA and changes in cognitive function. Conclusion: In this preliminary analysis of a small group of patients, changes in SAA in the perioperative phase were highly variable. SAA was not associated with POCD suggesting that POCD is not simply caused by anticholinergic medications administered in the perioperative phase. A further analysis of a larger group of patients is in progress.