855 resultados para BRAIN HEMORRHAGE


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Carotid atherosclerotic disease is a major cause of stroke, but it may remain clinically asymptomatic. The factors that turn the asymptomatic plaque into a symptomatic one are not fully understood, neither are the subtle effects that a high-grade carotid stenosis may have on the brain. The purpose of this study was to evaluate brain microcirculation, diffusion, and cognitive performance in patients with a high-grade stenosis in carotid artery, clinically either symptomatic or asymptomatic, undergoing carotid endarterectomy (CEA). We wanted to find out whether the stenoses are associated with diffusion or perfusion abnormalities of the brain or variation in the cognitive functioning of the patients, and to what extent the potential findings are affected by CEA, and compare the clinically symptomatic and asymptomatic subjects as well as strictly healthy controls. Coagulation and fibrinolytic parameters were compared with the rate microembolic signals (MES) in transcranial Doppler (TCD) and the macroscopic appearance of stenosing plaques in surgery. Patients (n=92) underwent CEA within the study. Blood samples pertaining to coagulation and fibrinolysis were collected before CEA, and the subjects underwent repeated TCD monitoring for MES. A subpopulation (n= 46) underwent MR imaging and repeated neuropsychological examination (preoperative, as well 4 and 100 days after CEA). In MRI, the average apparent diffusion coefficients were higher in the ipsilateral white matter (WM), and altough the interhemispheric difference was abolished by CEA, the levels remained higher than in controls. Symptomatic stenoses were associated with more sluggish perfusion especially in WM, and lower pulsatility of flow in TCD. All patients had poorer cognitive performance than healthy controls. Cognitive functions improved as expected by learning effect despite transient postoperative worsening in a few subjects. Improvement was greater in patients with deepest hypoperfusion, primarily in executive functions. Symptomatic stenoses were associated with higher hematocrit and tissue plasminogen activator antigen levels, as well as higher rate of MES and ulcerated plaques, and better postoperative improvement of vasoreactivity and pulsatility. In light of the findings, carotid stenosis is associated with differences in brain diffusion, perfusion, and cognition. The effect on diffusion in the ipsilateral WM, partially reversible by CEA, may be associated with WM degeneration. Asymptomatic and symptomatic subpopulations differ from each other in terms of hemodynamic adaptation and in their vascular physiological response to removal of stenosis. Although CEA may be associated with a transient cognitive decline, a true improvement of cognitive performance by CEA is possible in patients with the most pronounced perfusion deficits. Mediators of fibrinolysis and unfavourable hemorheology may contribute to the development of a symptomatic disease in patients with a high-grade stenosis.

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The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

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Anatomical brain networks change throughout life and with diseases. Genetic analysis of these networks may help identify processes giving rise to heritable brain disorders, but we do not yet know which network measures are promising for genetic analyses. Many factors affect the downstream results, such as the tractography algorithm used to define structural connectivity. We tested nine different tractography algorithms and four normalization methods to compute brain networks for 853 young healthy adults (twins and their siblings). We fitted genetic structural equation models to all nine network measures, after a normalization step to increase network consistency across tractography algorithms. Probabilistic tractography algorithms with global optimization (such as Probtrackx and Hough) yielded higher heritability statistics than 'greedy' algorithms (such as FACT) which process small neighborhoods at each step. Some global network measures (probtrackx-derived GLOB and ST) showed significant genetic effects, making them attractive targets for genome-wide association studies.

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Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.

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The metabolic syndrome and type 1 diabetes are associated with brain alterations such as cognitive decline brain infarctions, atrophy, and white matter lesions. Despite the importance of these alterations, their pathomechanism is still poorly understood. This study was conducted to investigate brain glucose and metabolites in healthy individuals with an increased cardiovascular risk and in patients with type 1 diabetes in order to discover more information on the nature of the known brain alterations. We studied 43 20- to 45-year-old men. Study I compared two groups of non-diabetic men, one with an accumulation of cardiovascular risk factors and another without. Studies II to IV compared men with type 1 diabetes (duration of diabetes 6.7 ± 5.2 years, no microvascular complications) with non-diabetic men. Brain glucose, N-acetylaspartate (NAA), total creatine (tCr), choline, and myo-inositol (mI) were quantified with proton magnetic resonance spectroscopy in three cerebral regions: frontal cortex, frontal white matter, thalamus, and in cerebellar white matter. Data collection was performed for all participants during fasting glycemia and in a subgroup (Studies III and IV), also during a hyperglycemic clamp that increased plasma glucose concentration by 12 mmol/l. In non-diabetic men, the brain glucose concentration correlated linearly with plasma glucose concentration. The cardiovascular risk group (Study I) had a 13% higher plasma glucose concentration than the control group, but no difference in thalamic glucose content. The risk group thus had lower thalamic glucose content than expected. They also had 17% increased tCr (marker of oxidative metabolism). In the control group, tCr correlated with thalamic glucose content, but in the risk group, tCr correlated instead with fasting plasma glucose and 2-h plasma glucose concentration in the oral glucose tolerance test. Risk factors of the metabolic syndrome, most importantly insulin resistance, may thus influence brain metabolism. During fasting glycemia (Study II), regional variation in the cerebral glucose levels appeared in the non-diabetic subjects but not in those with diabetes. In diabetic patients, excess glucose had accumulated predominantly in the white matter where the metabolite alterations were also the most pronounced. Compared to the controls values, the white matter NAA (marker of neuronal metabolism) was 6% lower and mI (glia cell marker) 20% higher. Hyperglycemia is therefore a potent risk factor for diabetic brain disease and the metabolic brain alterations may appear even before any peripheral microvascular complications are detectable. During acute hyperglycemia (Study III), the increase in cerebral glucose content in the patients with type 1 diabetes was, dependent on brain region, between 1.1 and 2.0 mmol/l. An every-day hyperglycemic episode in a diabetic patient may therefore as much as double brain glucose concentration. While chronic hyperglycemia had led to accumulation of glucose in the white matter, acute hyperglycemia burdened predominantly the gray matter. Acute hyperglycemia also revealed that chronic fluctuation in blood glucose may be associated with alterations in glucose uptake or in metabolism in the thalamus. The cerebellar white matter appeared very differently from the cerebral (Study IV). In the non-diabetic men it contained twice as much glucose as the cerebrum. Diabetes had altered neither its glucose content nor the brain metabolites. The cerebellum seems therefore more resistant to the effects of hyperglycemia than is the cerebrum.

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The purpose of this study was to compare the neuropsychological performance of two frontal dysexecutive phenotypes - disinhibited&' syndrome (DS) and &'apathetic&' syndrome (AS) following a traumatic brain injury in a non-western population, Oman. Methods: The study compared the performance of DS and AS in neuropsychological measures including those tapping into verbal reasoning ability/working memory/attention planning/goal-directed behavior and affective ranges. Results: The present analysis showed that DS and AS participants did not differ on indices measuring working memory/attention and affective ranges. However, the two cohorts differed significantly in measures of planning/goal-directed behaviour. Conclusion: This study lays the groundwork for further scrutiny in delineating the different characteristics of what has been previously labelled as frontal dysexecutive phenotype. This study indicates that DS and AS are marked with specific neuropsychological deficits.

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Acute pain has substantial survival value because of its protective function in the everyday environment. Instead, chronic pain lacks survival and adaptive function, causes great amount of individual suffering, and consumes the resources of the society due to the treatment costs and loss of production. The treatment of chronic pain has remained challenging because of inadequate understanding of mechanisms working at different levels of the nervous system in the development, modulation, and maintenance of chronic pain. Especially in unclear chronic pain conditions the treatment may be suboptimal because it can not be targeted to the underlying mechanisms. Noninvasive neuroimaging techniques have greatly contributed to our understanding of brain activity associated with pain in healthy individuals. Many previous studies, focusing on brain activations to acute experimental pain in healthy individuals, have consistently demonstrated a widely-distributed network of brain regions that participate in the processing of acute pain. The aim of the present thesis was to employ non-invasive brain imaging to better understand the brain mechanisms in patients suffering from chronic pain. In Study I, we used magnetoencephalography (MEG) to measure cortical responses to painful laser stimulation in healthy individuals for optimization of the stimulus parameters for patient studies. In Studies II and III, we monitored with MEG the cortical processing of touch and acute pain in patients with complex regional pain syndrome (CRPS). We found persisting plastic changes in the hand representation area of the primary somatosensory (SI) cortex, suggesting that chronic pain causes cortical reorganization. Responses in the posterior parietal cortex to both tactile and painful laser stimulation were attenuated, which could be associated with neglect-like symptoms of the patients. The primary motor cortex reactivity to acute pain was reduced in patients who had stronger spontaneous pain and weaker grip strength in the painful hand. The tight coupling between spontaneous pain and motor dysfunction supports the idea that motor rehabilitation is important in CRPS. In Studies IV and V we used MEG and functional magnetic resonance imaging (fMRI) to investigate the central processing of touch and acute pain in patients who suffered from recurrent herpes simplex virus infections and from chronic widespread pain in one side of the body. With MEG, we found plastic changes in the SI cortex, suggesting that many different types of chronic pain may be associated with similar cortical reorganization. With fMRI, we found functional and morphological changes in the central pain circuitry, as an indication of central contribution for the pain. These results show that chronic pain is associated with morphological and functional changes in the brain, and that such changes can be measured with functional imaging.

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Introduction Metastatic spread to the brain is common in patients with non–small cell lung cancer (NSCLC), but these patients are generally excluded from prospective clinical trials. The studies, phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations (LUX-Lung 3) and a randomized, open-label, phase III study of BIBW 2992 versus chemotherapy as first-line treatment for patients with stage IIIB or IV adenocarcinoma of the lung harbouring an EGFR activating mutation (LUX-Lung 6) investigated first-line afatinib versus platinum-based chemotherapy in epidermal growth factor receptor gene (EGFR) mutation-positive patients with NSCLC and included patients with brain metastases; prespecified subgroup analyses are assessed in this article. Methods For both LUX-Lung 3 and LUX-Lung 6, prespecified subgroup analyses of progression-free survival (PFS), overall survival, and objective response rate were undertaken in patients with asymptomatic brain metastases at baseline (n = 35 and n = 46, respectively). Post hoc analyses of clinical outcomes was undertaken in the combined data set (n = 81). Results In both studies, there was a trend toward improved PFS with afatinib versus chemotherapy in patients with brain metastases (LUX-Lung 3: 11.1 versus 5.4 months, hazard ratio [HR] = 0.54, p = 0.1378; LUX-Lung 6: 8.2 versus 4.7 months, HR = 0.47, p = 0.1060). The magnitude of PFS improvement with afatinib was similar to that observed in patients without brain metastases. In combined analysis, PFS was significantly improved with afatinib versus with chemotherapy in patients with brain metastases (8.2 versus 5.4 months; HR, 0.50; p = 0.0297). Afatinib significantly improved the objective response rate versus chemotherapy in patients with brain metastases. Safety findings were consistent with previous reports. Conclusions These findings lend support to the clinical activity of afatinib in EGFR mutation–positive patients with NSCLC and asymptomatic brain metastases.

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The experimental model using intracerebral (i.c.) challenge was employed in many studies evaluating the protection against disease induced by Japanese encephalitis virus (JEV). We investigated alterations in peripheral lymphocyte response caused by i.c. infection of mice with JEV. Splenocytes from the i.c.-infected mice showed suppressed proliferative response to concanavalin A (con A) and anti-CD3 antibody stimulation. At the same time, the expression of CD25 (IL-2R) and production of IL-2 was inhibited. Addition of anti-CD28 antibody restored the decreased anti-CD3 antibody-mediated proliferation in the splenocytes. Moreover, the number of con A-stimulated cells secreting IL-4 was significantly reduced in splenocytes from i.c.-infected mice. These studies suggested that the i.c. infection with JEV might involve additional immune modulation effects due to massive virus replication in the brain.

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‘Practice Forum’ provides a forum for social work practitioners to share their practice with others; to describe what they are doing and assess its effectiveness. The practice of case management is applied in a wide range of service delivery models to meet complex client needs. Unfortunately, cost containment and lack of clarity of the role of the case manager has blurred the definition and practice of case management for both the consumer and professional providers. This article examines two cases of a small non-government agency in Melbourne called Alcohol Related Brain Injury Assessment, Accommodation & Support Inc. (ARBIAS) where case management services are delivered to people with alcohol acquired brain damage. The analysis presented here supports the view that continuity of care and intensive relationship building with clients is vital for successful client outcomes and has application to a variety of programs which service chronically disabled clients.

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Aim: So far, most of the cognitive neuroscience studies investigating the development of brain activity in childhood have made comparisons between different age groups and ignored the individual stage of cognitive development. Given the wide variation in the rate of cognitive development, this study argues that chronological age alone cannot explain the developmental changes in brain activity. This study demonstrates how Piaget s theory and information on child s individual stage of development can complement the age-related evaluations of brain oscillatory activity. In addition, the relationship between cognitive development and working memory is investigated. Method: A total of 33 children (17 11-year-olds, 16 14-year-olds) participated in this study. The study consisted of behavioural tests and an EEG experiment. Behavioral tests included two Piagetian tasks (the Volume and Density task, the Pendulum task) and Raven s Standard Progressive Matrices task. During EEG experiment, subjects performed a modified version of the Sternberg s memory search paradigm which consisted of an auditorily presented memory set of 4 words and a probe word following these. The EEG data was analyzed using the event-related desynchronization / synchronization (ERD/ERS) method. The Pendulum task was used to assess the cognitive developmental stage of each subject and to form four groups based on age (11- or 14-year-olds) and cognitive developmental stage (concrete or formal operational stage). Group comparisons between these four groups were performed for the EEG data. Results and conclusions: Both age- and cognitive stage-related differences in brain oscillatory activity were found between the four groups. Importantly, age-related changes similar to those reported by previous studies were found also in this study, but these changes were modified by developmental stage. In addition, the results support a strong link between working memory and cognitive development by demonstrating differences in memory task related brain activity and cognitive developmental stages. Based on these findings it is suggested that in the future, comparisons of development of brain activity should not be based only on age but also on the individual cognitive developmental stage.

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Listening to music involves a widely distributed bilateral network of brain regions that controls many auditory perceptual, cognitive, emotional, and motor functions. Exposure to music can also temporarily improve mood, reduce stress, and enhance cognitive performance as well as promote neural plasticity. However, very little is currently known about the relationship between music perception and auditory and cognitive processes or about the potential therapeutic effects of listening to music after neural damage. This thesis explores the interplay of auditory, cognitive, and emotional factors related to music processing after a middle cerebral artery (MCA) stroke. In the acute recovery phase, 60 MCA stroke patients were randomly assigned to a music listening group, an audio book listening group, or a control group. All patients underwent neuropsychological assessments, magnetoencephalography (MEG) measurements, and magnetic resonance imaging (MRI) scans repeatedly during a six-month post-stroke period. The results revealed that amusia, a deficit of music perception, is a common and persistent deficit after a stroke, especially if the stroke affects the frontal and temporal brain areas in the right hemisphere. Amusia is clearly associated with deficits in both auditory encoding, as indicated by the magnetic mismatch negativity (MMNm) response, and domain-general cognitive processes, such as attention, working memory, and executive functions. Furthermore, both music and audio book listening increased the MMNm, whereas only music listening improved the recovery of verbal memory and focused attention as well as prevented a depressed and confused mood during the first post-stroke months. These findings indicate a close link between musical, auditory, and cognitive processes in the brain. Importantly, they also encourage the use of listening to music as a rehabilitative leisure activity after a stroke and suggest that the auditory environment can induce long-term plastic changes in the recovering brain.

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In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.