997 resultados para Paolo


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Colorectal cancer is one of the most frequent neoplasms and an important cause of mortality in the developed world. Mendelian syndromes account for about 5% of the total burden of CRC, being Lynch syndrome and familial adenomatous polyposis the most common forms. Lynch syndrome tumors develop mainly as a consequence of defective DNA mismatch repair associated with germline mutations in MLH1, MSH2, MSH6 and PMS2. A significant proportion of variants identified by screening these genes correspond to missense or noncoding changes without a clear pathogenic consequence, and they are designated as "variants of uncertain significance'', being the c.1852_1853delinsGC (p.K618A) variant in the MLH1 gene a clear example. The implication of this variant as a low-penetrance risk variant for CRC was assessed in the present study by performing a case-control study within a large cohort from the COGENT consortium-COST Action BM1206 including 18,723 individuals (8,055 colorectal cancer cases and 10,668 controls) and a case-only genotype-phenotype correlation with several clinical and pathological characteristics restricted to the Epicolon cohort. Our results showed no involvement of this variant as a low-penetrance variant for colorectal cancer genetic susceptibility and no association with any clinical and pathological characteristics including family history for this neoplasm or Lynch syndrome.

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Os aspectos quânticos de teorias de campo formuladas no espaço-tempo não comutativo têm sido amplamente estudados ao longo dos anos. Um dos principais aspectos é o que na literatura ficou conhecido como mixing IR/UV. Trata-se de uma mistura das divergências, que foi vista pela primeira vez no trabalho de Minwalla et al [28], onde num estudo do campo escalar não comutativo com interação quártica vemos já a 1 loop que o tadpole tem uma divergência UV associada a sua parte planar e, junto com ela, temos uma divergência IR associada com um gráfico não planar. Essa mistura torna a teoria não renormalizável. Dado tal problema, houve então uma busca por mecanismos que separassem essas divergências a fim de termos teorias renormalizáveis. Um mecanismo proposto foi a adição de um termo não local na ação U*(1) para que esta seja estável.Neste trabalho, estudamos através da renormalização algébrica a estabilidade deste modelo. Para tal, precisamos localizar o operador não local através de campos auxiliares e seus respectivos ghosts (metodo de Zwanziger) na intenção de retirar os graus de liberdade indesejados que surgem. Usamos o approachda quebra soft de BRST para analisar o termo que quebra BRST, que consiste em reescrevermos tal termo com o auxílio de fontes externas que num determinado limite físico voltam ao termo original.Como resultado, vimos que a teoria com a adição deste termo na ação só é renormalizável se tivermos que introduzir novos termos, sendo alguns deles quárticos. Porém, estes termos mudam a forma do propagador, que não desacopla as divergências. Um outro aspecto que podemos salientar é que, dependendo da escolha de alguns parâmetros, o propagador dá indícios de termos um fótonconfinante, seguindo o critério de Wilson e o critério da perda da positividade do propagador.

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The common 2652 6N del variant in the CASP8 promoter (rs3834129) has been described as a putative low-penetrance risk factor for different cancer types. In particular, some studies suggested that the deleted allele (del) was inversely associated with CRC risk while other analyses failed to confirm this. Hence, to better understand the role of this variant in the risk of developing CRC, we performed a multi-centric case-control study. In the study, the variant 2652 6N del was genotyped in a total of 6,733 CRC cases and 7,576 controls recruited by six different centers located in Spain, Italy, USA, England, Czech Republic and the Netherlands collaborating to the international consortium COGENT (COlorectal cancer GENeTics). Our analysis indicated that rs3834129 was not associated with CRC risk in the full data set. However, the del allele was under-represented in one set of cases with a family history of CRC (per allele model OR = 0.79, 95% CI = 0.69-0.90) suggesting this allele might be a protective factor versus familial CRC. Since this multi-centric case-control study was performed on a very large sample size, it provided robust clarification of the effect of rs3834129 on the risk of developing CRC in Caucasians.

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Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.

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Systemic lupus erythematosus is a chronic autoimmune disease with multifactorial ethiopathogenesis. The complement system is involved in both the early and late stages of disease development and organ damage. To better understand autoantibody mediated complement consumption we examined ex vivo immune complex formation on autoantigen arrays. We recruited patients with SLE (n = 211), with other systemic autoimmune diseases (n = 65) and non-autoimmune control subjects (n = 149). Standard clinical and laboratory data were collected and serum complement levels were determined. The genotype of SNP rs1143679 in the ITGAM gene was also determined. Ex vivo formation of immune complexes, with respect to IgM, IgG, complement C4 and C3 binding, was examined using a functional immunoassay on autoantigen microarray comprising nucleic acids, proteins and lipids. Complement consumption of nucleic acids increased upon binding of IgM and IgG even when serum complement levels were decreased due to consumption in SLE patients. A negative correlation between serum complement levels and ex vivo complement deposition on nucleic acid autoantigens is demonstrated. On the contrary, complement deposition on tested protein and lipid autoantigens showed positive correlation with C4 levels. Genetic analysis revealed that the non-synonymous variant rs1143679 in complement receptor type 3 is associated with an increased production of anti-dsDNA IgG antibodies. Notwithstanding, homozygous carriers of the previously reported susceptible allele (AA) had lower levels of dsDNA specific IgM among SLE patients. Both the non-synonymous variant rs1143679 and the high ratio of nucleic acid specific IgG/IgM were associated with multiple organ involvement. In summary, secondary complement deficiency in SLE does not impair opsonization of nucleic-acid-containing autoantigens but does affect other antigens and potentially other complement dependent processes. Dysfunction of the receptor recognizing complement opsonized immune complexes promotes the development of class-switched autoantibodies targeting nucleic acids.

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European hake (Merluccius merluccius) is an important predator of deeper shelf-upper slope Mediterranean communities. It is a nectobenthic species distributed over a wide depth range (20−1000 m) throughout the Mediterranean Sea and the north east Atlantic region (Fisher et al., 1987). Notwithstanding the ecological and economic importance (Oliver and Massutí, 1995) of hake in the Mediterranean, many aspects of its biology (e.g., recruitment and reproduction), due to multiple spawning (Sarano, 1986) and the current state of exploitation, are poorly understood (Arneri and Morales-Nin, 2000).

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Nesta tese falamos essencialmente sobre a simetria BRST no modelo de Gribov-Zwanziger. Estudamos a quebra suave, a quebra linear e a quebra espontânea, todas da simetria BRST. Na formulação padrão do modelo, quebrada suavemente, construímos o modelo de réplica usado para estimar os valores das massas das glueballs. Utilizando campos auxiliares construímos um modelo quebrado linearmente, e utilizando basicamente o mesmo procedimento, uma formulação mais recente onde a simetria é quebrada espontâneamente.

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After the 1980s it is diffi cult, following stylistic criteria, to draw a map of contemporary academic music. All styles are compossible, and all are practiced. In this context, the geographical entity “South of Italy” does not stand out for a musical identity with special technical-stylistic features. Rather, at a socio-cultural level, the South remains today – in music no less than in all areas where there is a gap between top development and stagnation – a land of emigrants: six out of the seven composers treated (Ivan Fedele, Giuseppe Colardo, Rosario Mirigliano, Giuseppe Soccio, Nicola Cisternino, Biagio Putignano, Paolo Aralla) live in the North of Italy. The positive aspect of this is the affi nity of the South with the transnational and superstructural community of contemporary music, which from European and Western has now become almost global. The composers under consideration belong to the generation of the ‘50s, rooted in the serial and post-serial movements (from which Franco Donatoni, Luciano Berio, Luigi Nono, Salvatore Sciarrino, Giacinto Scelsi, are the principals models, to mention only the Italians), dipped in the general phenomenon of timbrism (particularly spectralism), and acquainted with electronics. They draw from these sources various instruments of compositional technique and aspects of their poetics. In particular these composers, active from the ‘80s, develop new ways of construction of the temporal form of music. They share the goal to establish a new continuity, different from the tonal one but at the same time transcending the serial and post-serial disintegration and fragmentation. The primary means to this end is a new enhancement of the category of fi gure, as a clear and distinct, recognizable aggregate of pitches, intervals, register, durations, timbre, articulation, dynamics, and texture. Each composer elaborates the atonal fi gural material in different ways, emphasizing one aspect or another. For example, Fedele (1953) is a master in the management of form per se, Colardo (1953) in the activation of disturbed harmonic effects, Mirigliano (1950) in the creation of a slight tension from the smallest vibrations of sound, Soccio (1950) in the set up of movement by means of accumulations and discharges of energy, Cisternino (1957) in a Cagean-Scelsian emphasis on sound as such, Putignano (1960) in the suspension of time through the succession and transformation of images, Aralla (1960) in the foundation of form from below, from the concreteness of sound.

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Stabilized micron-sized bubbles, known as contrast agents, are often injected into the body to enhance ultrasound imaging of blood flow. The ability to detect such bubbles in blood depends on the relative magnitude of the acoustic power backscattered from the microbubbles (‘signal’) to the power backscattered from the red blood cells (‘noise’). Erythrocytes are acoustically small (Rayleigh regime), weak scatterers, and therefore the backscatter coefficient (BSC) of blood increases as the fourth power of frequency throughout the diagnostic frequency range. Microbubbles, on the other hand, are either resonant or super-resonant in the range 5-30 MHz. Above resonance, their total scattering cross-section remains constant with increasing frequency. In the present thesis, a theoretical model of the BSC of a suspension of red blood cells is presented and compared to the BSC of Optison® contrast agent microbubbles. It is predicted that, as the frequency increases, the BSC of red blood cell suspensions eventually exceeds the BSC of the strong scattering microbubbles, leading to a dramatic reduction in signal-to-noise ratio (SNR). This decrease in SNR with increasing frequency was also confirmed experimentally by use of an active cavitation detector for different concentrations of Optison® microbubbles in erythrocyte suspensions of different hematocrits. The magnitude of the observed decrease in SNR correlated well with theoretical predictions in most cases, except for very dense suspensions of red blood cells, where it is hypothesized that the close proximity of erythrocytes inhibits the acoustic response of the microbubbles.

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This article describes a nonlinear model of neural processing in the vertebrate retina, comprising model photoreceptors, model push-pull bipolar cells, and model ganglion cells. Previous analyses and simulations have shown that with a choice of parameters that mimics beta cells, the model exhibits X-like linear spatial summation (null response to contrast-reversed gratings) in spite of photoreceptor nonlinearities; on the other hand, a choice of parameters that mimics alpha cells leads to Y-like frequency doubling. This article extends the previous work by showing that the model can replicate qualitatively many of the original findings on X and Y cells with a fixed choice of parameters. The results generally support the hypothesis that X and Y cells can be seen as functional variants of a single neural circuit. The model also suggests that both depolarizing and hyperpolarizing bipolar cells converge onto both ON and OFF ganglion cell types. The push-pull connectivity enables ganglion cells to remain sensitive to deviations about the mean output level of nonlinear photoreceptors. These and other properties of the push-pull model are discussed in the general context of retinal processing of spatiotemporal luminance patterns.

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This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.

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This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.

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This article introduces a quantitative model of early visual system function. The model is formulated to unify analyses of spatial and temporal information processing by the nervous system. Functional constraints of the model suggest mechanisms analogous to photoreceptors, bipolar cells, and retinal ganglion cells, which can be formally represented with first order differential equations. Preliminary numerical simulations and analytical results show that the same formal mechanisms can explain the behavior of both X (linear) and Y (nonlinear) retinal ganglion cell classes by simple changes in the relative width of the receptive field (RF) center and surround mechanisms. Specifically, an increase in the width of the RF center results in a change from X-like to Y-like response, in agreement with anatomical data on the relationship between α- and