900 resultados para Probabilistic cellular automaton


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Background: Soft tissue sarcomas (STSs) are a group of neoplasms, which, despite current therapeutic advances, still confer a poor outcome to half of the patients. As other solid tumors, STSs exhibit high glucose consumption rates, associated with worse prognosis and therapeutic response. As highly glycolytic tumors, we hypothesized that sarcomas should present an increased expression of lactate transporters (MCTs).Methods: Immunohistochemical expression of MCT1, MCT2, MCT4 and CD147 was assessed in a series of 86 STSs and the expression profiles were associated with patients' clinical-pathological parameters.Results: MCT1, MCT4 and CD147 were mainly observed in the plasma membrane of cancer cells (around 60% for MCTs and 40% for CD147), while MCT2 was conspicuously found in the cytoplasm (94.2%). Importantly, we observed MCT1 nuclear expression (32.6%). MCT1 and MCT4, alone or co-expressed with CD147 in the plasma membrane, were associated with poor prognostic variables including high tumor grade, disease progression and shorter overall survival. Conversely, we found MCT1 nuclear expression to be associated with low grade tumors and longer overall survival.Conclusions: The present work represents the first report of MCTs characterization in STSs. We showed the original finding of MCT1 expression in the nucleus. Importantly, opposite biological roles should be behind the dual sub-cellular localization of MCT1, as plasma membrane expression of MCT1 is associated with worse patients' prognosis, while nuclear expression is associated with better prognosis.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.

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Objective - For patients with medication refractory medial temporal lobe epilepsy (MTLE), surgery offers the hope of a cure. However, up to 30% of patients with MTLE continue to experience disabling seizures after surgery. The reasons why some patients do not achieve seizure freedom are poorly understood. A promising theory suggests that epileptogenic networks are broadly distributed in surgically refractory MTLE, involving regions beyond the medial temporal lobe. In this retrospective study, we aimed to investigate the distribution of epileptogenic networks in MTLE using Bayesian distributed EEG source analysis from preoperative ictal onset recordings. This analysis has the advantage of generating maps of source probability, which can be subjected to voxel-based statistical analyses.Methods - We compared 10 patients who achieved post-surgical seizure freedom with 10 patients who continued experiencing seizures after surgery. Voxel-based Wilcoxon tests were employed with correction for multiple comparisons.Results - We observed that ictal EEG source intensities were significantly more likely to occur in lateral temporal and posterior medial temporal regions in patients with continued seizures post-surgery.Conclusions - Our findings support the theory of broader spatial distribution of epileptogenic networks at seizure onset in patients with surgically refractory MTLE.

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Cancer is a multistep process that begins with the transformation of normal epithelial cells and continues with tumor growth, stromal invasion and metastasis. The remodeling of the peritumoral environment is decisive for the onset of tumor invasiveness. This event is dependent on epithelial–stromal interactions, degradation of extracellular matrix components and reorganization of fibrillar components. Our research group has studied in a new proposed rodent model the participation of cellular and molecular components in the prostate microenvironment that contributes to cancer progression. Our group adopted the gerbil Meriones unguiculatus as an alternative experimental model for prostate cancer study. This model has presented significant responses to hormonal treatments and to development of spontaneous and induced neoplasias. The data obtained indicate reorganization of type I collagen fibers and reticular fibers, synthesis of new components such as tenascin and proteoglycans, degradation of basement membrane components and elastic fibers and increased expression of metalloproteinases. Fibroblasts that border the region, apparently participate in the stromal reaction. The roles of each of these events, as well as some signaling molecules, participants of neoplastic progression and factors that promote genetic reprogramming during epithelial–stromal transition are also discussed.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)