844 resultados para neural representations


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Aquest treball vol implementar un projecte de mineria de dades en l'àrea de la petrologia ígnia, especialitat englobada dins la geologia clàssica.

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The analysis of the intergenerational process of disease/health representations constitutes a requisite for the construction of projects and health education interventions. The objective of this work is to describe the meaning attributed to schistosomiasis in the family context. Twenty-one residents of an endemic area were interviewed. The interviews were submitted to content analysis. The results demonstrated different representations of the disease by the children, parents and grandparents. This paper discusses the differences in these representations and its impact in schistosomiasis control programs.

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Genetically engineered bioreporters are an excellent complement to traditional methods of chemical analysis. The application of fluorescence flow cytometry to detection of bioreporter response enables rapid and efficient characterization of bacterial bioreporter population response on a single-cell basis. In the present study, intrapopulation response variability was used to obtain higher analytical sensitivity and precision. We have analyzed flow cytometric data for an arsenic-sensitive bacterial bioreporter using an artificial neural network-based adaptive clustering approach (a single-layer perceptron model). Results for this approach are far superior to other methods that we have applied to this fluorescent bioreporter (e.g., the arsenic detection limit is 0.01 microM, substantially lower than for other detection methods/algorithms). The approach is highly efficient computationally and can be implemented on a real-time basis, thus having potential for future development of high-throughput screening applications.

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Background. The enteric nervous system (ENS) is entirely derived from neural crest and its normal development is regulated by specific molecular pathways. Failure in complete ENS formation results in aganglionic gut conditions such as Hirschsprung's disease (HSCR). Recently, PROKR1 expression has been demonstrated in mouse enteric neural crest derived cells and Prok-1 was shown to work coordinately with GDNF in the development of the ENS. Principal Findings. In the present report, ENS progenitors were isolated and characterized from the ganglionic gut from children diagnosed with and without HSCR, and the expression of prokineticin receptors was examined. Immunocytochemical analysis of neurosphere-forming cells demonstrated that both PROKR1 and PROKR2 were present in human enteric neural crest cells. In addition, we also performed a mutational analysis of PROKR1, PROKR2, PROK1 and PROK2 genes in a cohort of HSCR patients, evaluating them for the first time as susceptibility genes for the disease. Several missense variants were detected, most of them affecting highly conserved amino acid residues of the protein and located in functional domains of both receptors, which suggests a possible deleterious effect in their biological function. Conclusions. Our results suggest that not only PROKR1, but also PROKR2 might mediate a complementary signalling to the RET/GFRα1/GDNF pathway supporting proliferation/survival and differentiation of precursor cells during ENS development. These findings, together with the detection of sequence variants in PROKR1, PROK1 and PROKR2 genes associated to HSCR and, in some cases in combination with RET or GDNF mutations, provide the first evidence to consider them as susceptibility genes for HSCR.

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The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

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Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

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INTRODUCTION Functional imaging studies of addiction following protracted abstinence have not been systematically conducted to look at the associations between severity of use of different drugs and brain dysfunction. Findings from such studies may be relevant to implement specific interventions for treatment. The aim of this study was to examine the association between resting-state regional brain metabolism (measured with 18F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and the severity of use of cocaine, heroin, alcohol, MDMA and cannabis in a sample of polysubstance users with prolonged abstinence from all drugs used. METHODS Our sample consisted of 49 polysubstance users enrolled in residential treatment. We conducted correlation analyses between estimates of use of cocaine, heroin, alcohol, MDMA and cannabis and brain metabolism (BM) (using Statistical Parametric Mapping voxel-based (VB) whole-brain analyses). In all correlation analyses conducted for each of the drugs we controlled for the co-abuse of the other drugs used. RESULTS The analysis showed significant negative correlations between severity of heroin, alcohol, MDMA and cannabis use and BM in the dorsolateral prefrontal cortex (DLPFC) and temporal cortex. Alcohol use was further associated with lower metabolism in frontal premotor cortex and putamen, and stimulants use with parietal cortex. CONCLUSIONS Duration of use of different drugs negatively correlated with overlapping regions in the DLPFC, whereas severity of cocaine, heroin and alcohol use selectively impact parietal, temporal, and frontal-premotor/basal ganglia regions respectively. The knowledge of these associations could be useful in the clinical practice since different brain alterations have been associated with different patterns of execution that may affect the rehabilitation of these patients.

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Background: Activating mutations of the anaplastic lymphoma receptor tyrosine kinase gene (ALK) were identified in both somatic and familial neuroblastoma. The most common somatic mutation, F1174L, is associated with NMYC amplification and displayed an efficient transforming activity in vivo. In addition, both AKL-F1174L and NMYC were shown cooperate in neuroblastoma tumorigenesis in animal models. To analyse the role of ALK mutations in the oncogenesis of neuroblastoma, ALK wt and various ALK mutants were transduced in murine neural crest stem cells (MONC1). Methods: ALK-wt, and F1174L, and R1275Q mutants were stably expressed by retroviral infection using the pMIGR1 vector in the murine neural crest stem cell line MONC-1, previously immortalised with v-myc, and further implanted subcutaneously or orthotopically in nude mice. Results: Both MONC1-ALK-F1174L and -R1275Q cells displayed a rapid tumour forming capacity upon subcutaneous injection in nude mice compared to control MONC1-MIGR or MONC1 cells. Interestingly, the transforming capacity of the F1174L mutant was much more potent compared to that of R1275Q mutant in murine neural crest stem cells, while ALK-wt was not tumorigenic. In addition, mice implanted orthotopically in the left adrenal gland with MONC1-ALK-F1174L cells developed highly aggressive tumours in 100% of mice within three weeks, while MONC1-Migr or MONC1 derived tumours displayed a longer latency and a reduced tumour take. Conclusions: The activating ALK-F1174L mutant is highly tumorigenic in neural crest stem cells. Nevertheless, we cannot exclude a functional implication of the v-myc oncogene used for MONC1 cells immortalisation. Indeed, the control MONC1-Migr and MONC1 cells were also able to derive subcutaneous and orthotopic tumours, although with considerable reduced efficiency. Further investigations using neural crest stem cell lacking exogenous myc expression are currently on way to assess the exclusive role of ALK mutations in NB oncogenesis.