17 resultados para INTERACTION NETWORKS

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Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

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

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

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

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

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A significant proportion (up to 62) of oral squamous cell carcinomas (OSCCs) may arise from oral potential malignant lesions (OPMLs), such as leukoplakia. Patient outcomes may thus be improved through detection of lesions at a risk for malignant transformation, by identifying and categorizing genetic changes in sequential, progressive OPMLs. We conducted array comparative genomic hybridization analysis of 25 sequential, progressive OPMLs and same-site OSCCs from five patients. Recurrent DNA copy number gains were identified on 1p in 20/25 cases (80) with minimal, high-level amplification regions on 1p35 and 1p36. Other regions of gains were frequently observed: 11q13.4 (68), 9q34.13 (64), 21q22.3 (60), 6p21 and 6q25 (56) and 10q24, 19q13.2, 22q12, 5q31.2, 7p13, 10q24 and 14q22 (48). DNA losses were observed in 20 of samples and mainly detected on 5q31.2 (35), 16p13.2 (30), 9q33.1 and 9q33.29 (25) and 17q11.2, 3p26.2, 18q21.1, 4q34.1 and 8p23.2 (20). Such copy number alterations (CNAs) were mapped in all grades of dysplasia that progressed, and their corresponding OSCCs, in 70 of patients, indicating that these CNAs may be associated with disease progression. Amplified genes mapping within recurrent CNAs (KHDRBS1, PARP1, RAB1A, HBEGF, PAIP2, BTBD7) were selected for validation, by quantitative real-time PCR, in an independent set of 32 progressive leukoplakia, 32 OSSCs and 21 non-progressive leukoplakia samples. Amplification of BTBD7, KHDRBS1, PARP1 and RAB1A was exclusively detected in progressive leukoplakia and corresponding OSCC. BTBD7, KHDRBS1, PARP1 and RAB1A may be associated with OSCC progression. Proteinprotein interaction networks were created to identify possible pathways associated with OSCC progression.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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

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

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

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In this work two kinds of material were studied: chitosan cross-linked with glutaraldehyde and in a blend with PEO. The resulting products as well as chitosan and PEO raw materials, were analyzed by TG/DTG, DSC and DMTA to determinate the in?uence of cross-linking and PEO addition on thermal properties of the resulting materials. It was observed by thermogravimetry that the water-polymer interaction will be different for the cross-linked material compared to the blend, according to the specific site availability. The in?uence of such modifications (cross-linking and PEO addition), on chitosan thermal stability was also studied. The DSC results showed a good agreement with the TG/DTG results, reinforcing the interpretation given for TG/DTG results. DMTA results indicate that glass transition temperature is around 50 degrees C for the polymer under study. (c) 2005 Elsevier Ltd. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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How many dimensions (trait-axes) are required to predict whether two species interact? This unanswered question originated with the idea of ecological niches, and yet bears relevance today for understanding what determines network structure. Here, we analyse a set of 200 ecological networks, including food webs, antagonistic and mutualistic networks, and find that the number of dimensions needed to completely explain all interactions is small (< 10), with model selection favouring less than five. Using 18 high-quality webs including several species traits, we identify which traits contribute the most to explaining network structure. We show that accounting for a few traits dramatically improves our understanding of the structure of ecological networks. Matching traits for resources and consumers, for example, fruit size and bill gape, are the most successful combinations. These results link ecologically important species attributes to large-scale community structure. © 2013 Blackwell Publishing Ltd/CNRS.