972 resultados para focal epilepsy


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Background Against a backdrop of recommendations for increasing access to and uptake of early surgical intervention for children with medically intractable epilepsy, it is important to understand how parents and professionals decide to put children forward for epilepsy surgery and what their decisional support needs are. Aim The aim of this study was to explore how parents and health professionals make decisions regarding putting children forward for pediatric epilepsy surgery. Methods Individual interviews were conducted with nine parents of children who had undergone pediatric epilepsy surgery at a specialist children's hospital and ten healthcare professionals who made up the children's epilepsy surgery service multidisciplinary healthcare team (MDT). Three MDT meetings were also observed. Data were analyzed thematically. Findings Four themes were generated from analysis of interviews with parents: presentation of surgery as a treatment option, decision-making, looking back, and interventions. Three themes were generated from analysis of interviews/observations with health professionals: triangulating information, team working, and patient and family perspectives. Discussion Parents wanted more information and support in deciding to put their child forward for epilepsy surgery. They attempted to balance the potential benefits of surgery against any risks of harm. For health professionals, a multidisciplinary approach was seen as crucial to the decision-making process. Advocating for the family was perceived to be the responsibility of nonmedical professionals. Conclusion Decision-making can be supported by incorporating families into discussions regarding epilepsy surgery as a potential treatment option earlier in the process and by providing families with additional information and access to other parents with similar experiences.

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This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.

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This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

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This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: (1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; (2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and (3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

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The primary objective of this proposal was to determine whether mitochondrial oxidative stress and variation in a particular mtDNA lineage contribute to the risk of developing cortical dysplasia and are potential contributing factors in epileptogenesis in children. The occurrence of epilepsy in children is highly associated with malformations of cortical development (MCD). It appears that MCD might arise from developmental errors due to environmental exposures in combination with inherited variation in response to environmental exposures and mitochondrial function. Therefore, it is postulated that variation in a particular mtDNA lineage of children contributes to the effects of mitochondrial DNA damage on MCD phenotype. Quantitative PCR and dot blot were used to examine mitochondrial oxidative damage and single nucleotide polymorphism (SNP) in the mitochondrial genome in brain tissue from 48 pediatric intractable epilepsy patients from Miami Children’s Hospital and 11 control samples from NICHD Brain and Tissue Bank for Developmental Disorders. Epilepsy patients showed higher mtDNA copy number compared to normal health subjects (controls). Oxidative mtDNA damage was lower in non-neoplastic but higher in neoplastic epilepsy patients compared to controls. There was a trend of lower mtDNA oxidative damage in the non-neoplastic (MCD) patients compared to controls, yet, the reverse was observed in neoplastic (MCD and Non-MCD) epilepsy patients. The presence of mtDNA SNP and haplogroups did not show any statistically significant relationships with epilepsy phenotypes. However, SNPs G9804A and G9952A were found in higher frequencies in epilepsy samples. Logistic regression analysis showed no relationship between mtDNA oxidative stress, mtDNA copy number, mitochondrial haplogroups and SNP variations with epilepsy in pediatric patients. The levels of mtDNA copy number and oxidative mtDNA damage and the SNPs G9952A and T10010C predicted neoplastic epilepsy, however, this was not significant due to a small sample size of pediatric subjects. Findings of this study indicate that an increase in mtDNA content may be compensatory mechanisms for defective mitochondria in intractable epilepsy and brain tumor. Further validation of these findings related to mitochondrial genotypes and mitochondrial dysfunction in pediatric epilepsy and MCD may lay the ground for the development of new therapies and prevention strategies during embryogenesis.

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This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

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This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

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An accurate and simple technique for determining the focal length of a lens is presented. It consists of measuring the period of the fringes produced by a diffraction grating at the near field when it is illuminated with a beam focused by the unknown lens. In paraxial approximation, the period of the fringes varies linearly with the distance. After some calculations, a simple extrapolation of data is performed to obtain the locations of the principal plane and the focal plane of the lens. Thus, the focal length is obtained as the distance between the two mentioned planes. The accuracy of the method is limited by the collimation degree of the incident beam and by the algorithm used to obtain the period of the fringes. We have checked the technique with two commercial lenses, one convergent and one divergent, with nominal focal lengths (+100±1) mm and (−100±1) mm respectively. We have experimentally obtained the focal lengths resulting into the interval given by the manufacturer but with an uncertainty of 0.1%, one order of magnitude lesser than the uncertainty given by the manufacturer.

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The development of atherosclerosis in the aorta is associated with low and oscillatory wall shear stress for normal patients. Moreover, localized differences in wall shear stress heterogeneity have been correlated with the presence of complex plaques in the descending aorta. While it is known that coarctation of the aorta can influence indices of wall shear stress, it is unclear how the degree of narrowing influences resulting patterns. We hypothesized that the degree of coarctation would have a strong influence on focal heterogeneity of wall shear stress. To test this hypothesis, we modeled the fluid dynamics in a patient-specific aorta with varied degrees of coarctation. We first validated a massively parallel computational model against experimental results for the patient geometry and then evaluated local shear stress patterns for a range of degrees of coarctation. Wall shear stress patterns at two cross sectional slices prone to develop atherosclerotic plaques were evaluated. Levels at different focal regions were compared to the conventional measure of average circumferential shear stress to enable localized quantification of coarctation-induced shear stress alteration. We find that the coarctation degree causes highly heterogeneous changes in wall shear stress.

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[EN]The work presented in this paper is related to Depth Recovery from Focus The approach starts calibrating focal length of the camera using the Gaussian lens law for the thin lens camera model Two approaches are presented based on the availability of the internal distance of the lens

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Background and Aims: It is well recognized that mood disorders and epilepsy commonly co-occur. However, the relationship between epilepsy and the clinical features and course of illness in bipolar disorder (BD) is currently unknown. Here we explore the rate of epilepsy within a large sample of individuals with BD and examine bipolar illness characteristics according to the presence or absence of epilepsy. Methods: 1596 participants recruited to the Bipolar Disorder Research Network; a well-defined sample of UK subjects with a diagnosis of BD, completed a self-report questionnaire to assess lifetime history of epilepsy (Ottman et al., 2010). A subset of participants (n = 29) completed a telephone interview assessment to determine expert-confirmed epilepsy status. Lifetime clinical characteristics of illness were compared between BD subjects with and without a history of epilepsy. Results: 127 individuals (8%) screened positively for lifetime history of epilepsy. Bipolar subjects with epilepsy experienced higher rates of: suicide attempt (64.2% vs. 47.4%, p = 0.000367); panic disorder (29.6% vs. 16.1%, p = 0.001); phobias (13.6% vs. 5.7%, 0.004); alcohol abuse (18.6% vs. 10.6%, p = 0.017); and other substance abuse (10.2% vs. 4%, p = 0.009). History of suicide attempt (OR = 1.79, p = 0.013) remained significant within a multivariate model. Similar trends were observed within bipolar subjects with well-defined, expert-confirmed epilepsy (n = 29). Conclusions: Results demonstrate an increased rate of self-reported epilepsy in the BD sample, compared to the general population, and suggest differences in the clinical course of BD according to the presence of epilepsy. Comorbid epilepsy within BD may provide an attractive opportunity for subcategorising for future genetic studies, potentially identifying common underlying mechanisms.

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Der ischämische Schlaganfall ist nicht nur die zweithäufigste Todesursache weltweit, sondern auch eine der Hauptursachen für körperliche Beeinträchtigungen im Erwachsenenalter. Das Ausmaß der durch den Schlaganfall hervorgerufenen Gewebeschädigung ist stark durch das Immunsystem geprägt. Die im Zentralnervensystem (ZNS) ansässigen Mikroglia und die aus dem Blutsystem infiltrierenden Makrophagen sind die Schlüsselzellen der lokalen und systemischen Entzündungsantwort nach dem ischämischen Schlaganfall. Sowohl Mikroglia als auch Makrophagen spielen in der Entwicklung der Gewebeschädigung eine duale Rolle. Zum einen phagozytieren sie Zelltrümmer und unterstützen neuroregenerative Prozesse, zum anderen sind diese Zellen in der Lage den Zustand der Gewebsschädigung zu verschlimmern und einer Regeneration des ZNS entgegenzuwirken. Die Polarisierung der Mikroglia/Makrophagen hin zu verschiedenen Phänotypen ist abhängig von der jeweiligen Phase der Gewebeschädigung. Der destruktive, proinflammatorische Phänotyp (M1) steht dabei dem protektiven, antiinflammatorischen Phänotyp (M2) gegenüber. Die Notwendigkeit einer zielgerichteten Regulierung der polarisierten Mikroglia/Makrophagen zum protektiven M2-Phänotyp wurde bereits mehrfach im Zusammenhang mit der Behandlung von neurodegenerativen Erkrankungen erwähnt. In der vorliegenden Dissertation soll die immunregulierende und neuroprotektive Wirkung der microRibonukleinsäure-124 (miRNA-124) in Bezug auf die Polarisierung von Mikroglia/Makrophagen zu verschiedenen Zeitpunkten nach Verschluss der Arteria cerebri media (ACM) im Gehirn von Mäusen gezeigt werden. Zu diesem Zweck wurde die liposomierte miRNA-124 zu einem frühen Zeitpunkt (Tag 2) und zu einem späten Zeitpunkt (Tag 10) nach Verschluss der ACM verabreicht. Die Behandlung mit der miRNA-124 zu einem frühen Zeitpunkt resultierte dabei in einem signifikanten Anstieg in der Anzahl der M2-positiven Mikroglia/Makrophagen im Vergleich zur Kontrollgruppe. Gleichzeitig nahm die Anzahl der M1-positiven Mikroglia/Makrophagen signifikant ab. Im Wesentlichen resultierte die Behandlung mit der miRNA-124 zu beiden Zeitpunkten in einem geringeren Verhältnis von proinflammatorischen (M1) zu antiinflammatorischen (M2) Mikroglia/Makrophagen. Zu den weiteren Erkenntnissen einer frühzeitigen Behandlung im Rahmen dieser Dissertation gehören: (i) eine signifikante Zunahme des neuronalen Überlebens, das zudem positiv mit der Anzahl der M2-positiven Mikroglia/Makrophagen korreliert, (ii) eine verbesserte funktionelle Erholung, welche in Verbindung mit den veränderten neuroinflammatorischen Ereignissen steht und (iii) ein signifikant verkleinertes Läsionsareal, welches durch reaktive Astrozyten zum gesunden Gewebe hin abgegrenzt wird. Die Ergebnisse dieser Dissertation zeigen, dass die Verabreichung von miRNA-124 eine neue Möglichkeit zur Regulierung der Immunantwort und der Neuroprotektion im Rahmen der Behandlung des ischämischen Schlaganfalls darstellt.

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Barrett's esophagus is the major risk factor for esophageal adenocarcinoma. It has a low but non-neglectable risk, high surveillance costs and no reliable risk stratification markers. We sought to identify early biomarkers, predictive of Barrett's malignant progression, using a meta-analysis approach on gene expression data. This in silico strategy was followed by experimental validation in a cohort of patients with extended follow up from the Instituto Português de Oncologia de Lisboa de Francisco Gentil EPE (Portugal). Bioinformatics and systems biology approaches singled out two candidate predictive markers for Barrett's progression, CYR61 and TAZ. Although previously implicated in other malignancies and in epithelial-to-mesenchymal transition phenotypes, our experimental validation shows for the first time that CYR61 and TAZ have the potential to be predictive biomarkers for cancer progression. Experimental validation by reverse transcriptase quantitative PCR and immunohistochemistry confirmed the up-regulation of both genes in Barrett's samples associated with high-grade dysplasia/adenocarcinoma. In our cohort CYR61 and TAZ up-regulation ranged from one to ten years prior to progression to adenocarcinoma in Barrett's esophagus index samples. Finally, we found that CYR61 and TAZ over-expression is correlated with early focal signs of epithelial to mesenchymal transition. Our results highlight both CYR61 and TAZ genes as potential predictive biomarkers for stratification of the risk for development of adenocarcinoma and suggest a potential mechanistic route for Barrett's esophagus neoplastic progression.