150 research outputs found

    Ambulance location through optimization and simulation : the case of Milano urban area

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    In this paper, the problem of locating ambulance posts over an urban area is considered. A three steps approach is presented to deal with this problem, that combines different skills. First, the real life data on the considered system behavior are analyzed. Then, integer linear programming models are considered with the aim of finding new post locations. As such models represent a simplification and an abstraction with respect to the real life situation, the behavior of the proposed solutions is tested with a simulation framework, tailored on the considered problem features. The whole approach is tested over the Milano city area case, with the aim of pointing out the criticality of the system and providing suggestions for the emergency service management. Computational results are presented and discussed

    Multimodal imaging and diagnosis of myopic choroidal neovascularization in Caucasians

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    To investigate myopic choroidal neovascularization (mCNV) by fluorescein angiography (FA), spectral-domain optical coherence tomography (SD-OCT), near-infrared (NIR) reflectance, and autofluorescence (AF)

    Non-local kinetic and macroscopic models for self-organised animal aggregations

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    The last two decades have seen a surge in kinetic and macroscopic models derived to investigate the multi-scale aspects of self-organised biological aggregations. Because the individual-level details incorporated into the kinetic models (e.g., individual speeds and turning rates) make them somewhat difficult to investigate, one is interested in transforming these models into simpler macroscopic models, by using various scaling techniques that are imposed by the biological assumptions of the models. However, not many studies investigate how the dynamics of the initial models are preserved via these scalings. Here, we consider two scaling approaches (parabolic and grazing collision limits) that can be used to reduce a class of non-local 1D and 2D models for biological aggregations to simpler models existent in the literature. Then, we investigate how some of the spatio-temporal patterns exhibited by the original kinetic models are preserved via these scalings. To this end, we focus on the parabolic scaling for non-local 1D models and apply asymptotic preserving numerical methods, which allow us to analyse changes in the patterns as the scaling coefficient ϵ is varied from ϵ=1 (for 1D transport models) to ϵ=0 (for 1D parabolic models). We show that some patterns (describing stationary aggregations) are preserved in the limit ϵ→0, while other patterns (describing moving aggregations) are lost. To understand the loss of these patterns, we construct bifurcation diagrams

    Breast cancer "tailored follow-up" in Italian oncology units: a web-based survey

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    urpose: Breast cancer follow-up procedures after primary treatment are still a controversial issue. Aim of this study was to investigate, through a web-based survey, surveillance methodologies selected by Italian oncologists in everyday clinical practice. Methods: Referents of Italian medical oncology units were invited to participate to the study via e-mail through the SurveyMonkey website. Participants were asked how, in their institution, exams of disease staging and follow-up are planned in asymptomatic women and if surveillance continues beyond the 5th year. Results: Between February and May 2013, 125 out of 233 (53.6%) invited referents of Italian medical oncology units agreed to participate in the survey. Ninety-seven (77.6%) referents state that modalities of breast cancer follow-up are planned according to the risk of disease progression at diagnosis and only 12 (9.6%) oncology units apply the minimal follow-up procedures according to international guidelines. Minimal follow-up is never applied in high risk asymptomatic women. Ninety-eight (78.4%) oncology units continue follow-up in all patients beyond 5 years. Conclusions: Our survey shows that 90.4% of participating Italian oncology units declare they do not apply the minimal breast cancer follow-up procedures after primary treatment in asymptomatic women, as suggested by national and international guidelines. Interestingly, about 80.0% of interviewed referents performs the so called "tailored follow-up", high intensity for high risk, low intensity for low risk patients. There is an urgent need of randomized clinical trials able to determine the effectiveness of risk-based follow-up modalities, their ideal frequency and persistence in time

    Differential Cerebral Cortex Transcriptomes of Baboon Neonates Consuming Moderate and High Docosahexaenoic Acid Formulas

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    BACKGROUND: Docosahexaenoic acid (DHA, 22:6n-3) and arachidonic acid (ARA, 20:4n-6) are the major long chain polyunsaturated fatty acids (LCPUFA) of the central nervous system (CNS). These nutrients are present in most infant formulas at modest levels, intended to support visual and neural development. There are no investigations in primates of the biological consequences of dietary DHA at levels above those present in formulas but within normal breastmilk levels. METHODS AND FINDINGS: Twelve baboons were divided into three formula groups: Control, with no DHA-ARA; “L”, LCPUFA, with 0.33%DHA-0.67%ARA; “L3”, LCPUFA, with 1.00%DHA-0.67%ARA. All the samples are from the precentral gyrus of cerebral cortex brain regions. At 12 weeks of age, changes in gene expression were detected in 1,108 of 54,000 probe sets (2.05%), with most showing <2-fold change. Gene ontology analysis assigns them to diverse biological functions, notably lipid metabolism and transport, G-protein and signal transduction, development, visual perception, cytoskeleton, peptidases, stress response, transcription regulation, and 400 transcripts having no defined function. PLA2G6, a phospholipase recently associated with infantile neuroaxonal dystrophy, was downregulated in both LCPUFA groups. ELOVL5, a PUFA elongase, was the only LCPUFA biosynthetic enzyme that was differentially expressed. Mitochondrial fatty acid carrier, CPT2, was among several genes associated with mitochondrial fatty acid oxidation to be downregulated by high DHA, while the mitochondrial proton carrier, UCP2, was upregulated. TIMM8A, also known as deafness/dystonia peptide 1, was among several differentially expressed neural development genes. LUM and TIMP3, associated with corneal structure and age-related macular degeneration, respectively, were among visual perception genes influenced by LCPUFA. TIA1, a silencer of COX2 gene translation, is upregulated by high DHA. Ingenuity pathway analysis identified a highly significant nervous system network, with epidermal growth factor receptor (EGFR) as the outstanding interaction partner. CONCLUSIONS: These data indicate that LCPUFA concentrations within the normal range of human breastmilk induce global changes in gene expression across a wide array of processes, in addition to changes in visual and neural function normally associated with formula LCPUFA

    Analysis of protein-coding genetic variation in 60,706 humans

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    Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes

    Modeling and simulating animal grouping Individual-based models

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    This paper contains a review of recent results about two interacting particle models describing aggregation of social individuals; a cellular automaton model and a system of of It\uf4 type stochastic differential equations are described

    Cellular automata and many-particle systems modeling aggregation behavior among populations

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    A cellular automaton model is presented in order to describe mutual interactions among the individuals of a population due to social decisions. The scheme is used for getting qualitative results, comparable to field experiments carried out on a population of ants which present an aggregative behavior. We also present a second description of a biological spatially structured population of NN individuals by a system of stochastic differential equations of It\^o type. A ''law of large numbers'' to a continuum dynamics described by an integro-differential equation is given
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