1000 resultados para Joao Cabral
Resumo:
Background Accurate diagnosis of portal vein (PV) stenosis by real-time and color Doppler US (CD-US) after segmental liver transplantation in children can decrease morbidity by avoiding unnecessary biopsy, PV hypertension, thrombosis and loss of the graft. Objective To evaluate CD-US parameters for the prediction of PV stenosis after segmental liver transplantation in children. Materials and methods We retrospectively reviewed 61 CD-US examinations measuring the diameter at the PV anastomosis, velocities at the anastomosis (PV1) and in the segment proximal to the anastomosis (PV2), and the PV1/PV2 velocity ratio. The study group comprised patients with stenosis confirmed by angiography and the control group comprised patients with a good clinical outcome. Results PV stenosis was seen in 12 CD-US examinations. The mean PV diameter was smaller in the study group (2.6 mm versus 5.7 mm) and a PV diameter of < 3.5 mm was highly predictive of stenosis (sensitivity 100%, specificity 91.8%). Conclusion A PV diameter of < 3.5 mm is a highly predictive CD-US parameter for the detection of hemodynamically significant stenosis on angiography.
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The mechanisms underlying the effects of antidepressant treatment in patients with Parkinson`s disease (PD) are unclear. The neural changes after successful therapy investigated by neuroimaging methods can give insights into the mechanisms of action related to a specific treatment choice. To study the mechanisms of neural modulation of repetitive transcranial magnetic Stimulation (rTMS) and fluoxetine, 21 PD depressed patients were randomized into only two active treatment groups for 4 wk: active rTMS over left dorsolateral prefrontal cortex (DLPFC) (5 Hz rTMS; 120% motor threshold) with placebo pill and sham rTMS with fluoxetine 20mg/d. Event-related functional magnetic resonance imaging (fMRI) with emotional stimuli was performed before and after treatment - in two sessions (test and re-test) at each time-point. The two groups of treatment had a significant, similar mood improvement. After rTMS treatment, there were brain activity decreases in left fusiform gyrus, cerebellum and right DLPFC and brain activity increases in left DLPFC and anterior cingulate gyrus compared to baseline. In contrast, after fluoxetine treatment, there were brain activity increases in right premotor and right medial prefrontal cortex. There was a significant interaction effect between groups vs. time in the left medial prefrontal cortex, suggesting that the activity in this area changed differently in the two treatment groups. Our findings show that antidepressant effects of rTMS and fluoxetine in PD are associated with changes in different areas of the depression-related neural network.
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Members of the nuclear factor of activated T cell (NFAT) family of transcription factors were originally described in T lymphocytes but later shown to be expressed in several immune and non-immune cell types. NFAT proteins can modulate cellular transformation intrinsically, and NFAT-deficient (NFAT1-/-) mice are indeed more susceptible to transformation than wild-type counterparts. However, the contribution of an NFAT1-/- microenvironment to tumor progression has not been studied. We have addressed this question by inoculating NFAT1-/- mice with B16F10 melanoma cells intravenously, an established model of tumor homing and growth. Surprisingly, NFAT1-/- animals sustained less tumor growth in the lungs after melanoma inoculation than wild-type counterparts. Even though melanoma cells equally colonize NFAT1-/- and wild-type lungs, tumors do not progress in the absence of NFAT1 expression. A massive mononuclear perivascular infiltrate and reduced expression of TGF-beta in the absence of NFAT1 suggested a role for tumor-infiltrating immune cells and the cytokine milieu. However, these processes are independent of an IL-4-induced regulatory tumor microenvironment, since lack of this cytokine does not alter the phenotype in NFAT1-/- animals. Bone marrow chimera experiments meant to differentiate the contributions of stromal and infiltrating cells to tumor progression demonstrated that NFAT1-induced susceptibility to pulmonary tumor growth depends on NFAT1-expressing parenchyma rather than on bone marrow-derived cells. These results suggest an important role for NFAT1 in radio-resistant tumor-associated parenchyma, which is independent of the anti-tumor immune response and Th1 versus Th2 cytokine milieu established by the cancer cells, but able to promote site-specific tumor growth.
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Our aim was to evaluate the interaction between breast cancer cells and nodal fibroblasts, by means of their gene expression profile. Fibroblast primary cultures were established from negative and positive lymph nodes from breast cancer patients and a similar gene expression pattern was identified, following cell culture. Fibroblasts and breast cancer cells (MDA-MB231, MDA-MB435, and MCF7) were cultured alone or co-cultured separated by a porous membrane (which allows passage of soluble factors) for comparison. Each breast cancer lineage exerted a particular effect on fibroblasts viability and transcriptional profile. However, fibroblasts from positive and negative nodes had a parallel transcriptional behavior when co-cultured with a specific breast cancer cell line. The effects of nodal fibroblasts on breast cancer cells were also investigated. MDA MB-231 cells viability and migration were enhanced by the presence of fibroblasts and accordingly, MDA-MB435 and MCF7 cells viability followed a similar pattern. MDA-MB231 gene expression profile, as evaluated by cDNA microarray, was influenced by the fibroblasts presence, and HNMT, COMT, FN3K, and SOD2 were confirmed downregulated in MDA-MB231 co-cultured cells with fibroblasts from both negative and positive nodes, in a new series of RT-PCR assays. In summary, transcriptional changes induced in breast cancer cells by fibroblasts from positive as well as negative nodes are very much alike in a specific lineage. However, fibroblasts effects are distinct in each one of the breast cancer lineages, suggesting that the inter-relationships between stromal and malignant cells are dependent on the intrinsic subtype of the tumor.
Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI
Resumo:
Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.
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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.
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Among nonmotor symptoms observed in Parkinson`s disease (PD) dysfunction in the visual system, including hallucinations, has a significant impact in their quality of life. To further explore the visual system in PD patients we designed two fMRI experiments comparing 18 healthy volunteers with 16 PD patients without visual complaints in two visual fMRI paradigms: the flickering checkerboard task and a facial perception paradigm. PD patients displayed a decreased activity in the primary visual cortex (Broadmann area 17) bilaterally as compared to healthy volunteers during flickering checkerboard task and increased activity in fusiform gyms (Broadmann area 37) during facial perception paradigm. Our findings confirm the notion that PD patients show significant changes in the visual cortex system even before the visual symptoms are clinically evident. Further studies are necessary to evaluate the contribution of these abnormalities to the development visual symptoms in PD. (C) 2010 Movement Disorder Society
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Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.
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The purpose of this study was to evaluate the mid- and long-term results of percutaneous transhepatic cholangiography (PTC) and biliary drainage in children with isolated bilioenteric anastomotic stenosis (BAS) after pediatric liver transplantation. Sixty-four children underwent PTC from March 1993 to May 2008. Nineteen cholangiograms were normal; 10 showed intrahepatic biliary stenosis and BAS, and 35 showed isolated BAS. Cadaveric grafts were used in 19 and living donor grafts in 16 patients. Four patients received a whole liver, and 31 patients received a left lobe or left lateral segment. Roux-en-Y hepaticojejunostomy was performed in all patients. Indication for PTC was based on clinical, laboratory, and histopathologic findings. In patients with isolated BAS, dilation and biliary catheter placement, with changes every 2 months, were performed. Patients were separated into 4 groups according to number of treatment sessions required. The drainage catheter was removed if cholangiogram showed no significant residual stenosis and normal biliary emptying time after a minimum of 6 months. The relationship between risk factors (recipient`s weight < 10 kg, previous exposure to Cytomegalovirus, donor-recipient sex and weight relations, autoimmune disease as indication for transplantion, previous Kasai`s surgery, use of reduced liver grafts, chronic or acute rejection occurrence) and treatment was evaluated. Before PTC, fever was observed in 46%, biliary dilation in 23%, increased bilirubin in 57%, and increased gamma-glutamyltransferase (GGT) in 100% of patients. In the group with BAS, 24 of 35 (69%) patients had histopathologic findings of cholestasis as did 9 of 19 (47%) patients in the group with normal PTC. Of the 35 patients, 23 (65.7%) needed 1 (group I), 7 needed 2 (group II), 4 needed 3 (group III), and 1 needed 4 treatment sessions (group IV). The best results were observed after 1 treatment session, and the mean duration of catheter placement and replacement was 10 months. The primary patency rate was 61.2%, and the recurrence rate was 34.3% (group I). Seven patients (7 of 35; 20%) had their stricture treated with a second treatment session (group II). The average drainage time in group II was 24 months. During a period > 20 months, 4 patients (4 of 35; 11.4%) required 1 additional treatment session (group III), and 1 patient (1 of 35; 2.9%) had a catheter placed at the end of the study period (group IV). Drainage time in group I was significantly shorter than those in groups II, III, and IV (p < 0.05). There was no statistically significant relation between therapeutic response and the selected risk factors (p > 0.05). The majority of complications, such as catheter displacement and leakage, were classified as minor; however, 2 patients (5.7%) with hemobilia were noted. Complications increased according to the need for reintervention. In conclusion, balloon dilation and percutaneous drainage placement is safe and effective, and it has long-term patency for children with BAS after liver transplantation. Because of prolonged treatment time, reintervention may be necessary, thereby increasing the complication rate. Balloon dilation and percutaneous drainage placement should be considered as the first treatment option because of its minimally invasive nature.
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Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.
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The importance of epithelial-stroma interaction in normal breast development and tumor progression has been recognized. To identify genes that were regulated by these reciprocal interactions, we cocultured a nonmalignant (MCF10A) and a breast cancer derived (MDA-MB231) basal cell lines, with fibroblasts isolated from breast benign-disease adjacent tissues (NAF) or with carcinoma-associated fibroblasts (CAF), in a transwell system. Gene expression profiles of each coculture pair were compared with the correspondent monocultures, using a customized microarray. Contrariwise to large alterations in epithelial cells genomic profiles, fibroblasts were less affected. In MDA-MB231 highly represented genes downregulated by CAF derived factors coded for proteins important for the specificity of vectorial transport between ER and golgi, possibly affecting cell polarity whereas the response of MCF10A comprised an induction of genes coding for stress responsive proteins, representing a prosurvival effect. While NAF downregulated genes encoding proteins associated to glycolipid and fatty acid biosynthesis in MDA-MB231, potentially affecting membrane biogenesis, in MCF10A, genes critical for growth control and adhesion were altered. NAFs responded to coculture with MDA-MB231 by a decrease in the expression of genes induced by TGF beta 1 and associated to motility. However, there was little change in NAFs gene expression profile influenced by MCF10A. CAFs responded to the presence of both epithelial cells inducing genes implicated in cell proliferation. Our data indicate that interactions between breast fibroblasts and basal epithelial cells resulted in alterations in the genomic profiles of both cell types which may help to clarify some aspects of this heterotypic signaling. (C) 2009 UICC
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Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.
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The histopathological counterpart of white matter hyperintensities is a matter of debate. Methodological and ethical limitations have prevented this question to be elucidated. We want to introduce a protocol applying state-of-the-art methods in order to solve fundamental questions regarding the neuroimaging-neuropathological uncertainties comprising the most common white matter hyperintensities [WMHs] seen in aging. By this protocol, the correlation between signal features in in situ, post mortem MRI-derived methods, including DTI and MTR and quantitative and qualitative histopathology can be investigated. We are mainly interested in determining the precise neuroanatomical substrate of incipient WMHs. A major issue in this protocol is the exact co-registration of small lesion in a tridimensional coordinate system that compensates tissue deformations after histological processing. The protocol is based on four principles: post mortem MRI in situ performed in a short post mortem interval, minimal brain deformation during processing, thick serial histological sections and computer-assisted 3D reconstruction of the histological sections. This protocol will greatly facilitate a systematic study of the location, pathogenesis, clinical impact, prognosis and prevention of WMHs. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.
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The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.