965 resultados para Recognition algorithms
Resumo:
Dendritic cells (DCs) are essential antigen-presenting cells for the induction of immunity against pathogens. However, HIV-1 spread is strongly enhanced in clusters of DCs and CD4(+) T cells. Uninfected DCs capture HIV-1 and mediate viral transfer to bystander CD4(+) T cells through a process termed trans-infection. Initial studies identified the C-type lectin DC-SIGN as the HIV-1 binding factor on DCs, which interacts with the viral envelope glycoproteins. Upon DC maturation, however, DC-SIGN is down-regulated, while HIV-1 capture and trans-infection is strongly enhanced via a glycoprotein-independent capture pathway that recognizes sialyllactose-containing membrane gangliosides. Here we show that the sialic acid-binding Ig-like lectin 1 (Siglec-1, CD169), which is highly expressed on mature DCs, specifically binds HIV-1 and vesicles carrying sialyllactose. Furthermore, Siglec-1 is essential for trans-infection by mature DCs. These findings identify Siglec-1 as a key factor for HIV-1 spread via infectious DC/T-cell synapses, highlighting a novel mechanism that mediates HIV-1 dissemination in activated tissues.
3D seismic facies characterization and geological patterns recognition (Australian North West Shelf)
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EXECUTIVE SUMMARY This PhD research, funded by the Swiss Sciences Foundation, is principally devoted to enhance the recognition, the visualisation and the characterization of geobodies through innovative 3D seismic approaches. A series of case studies from the Australian North West Shelf ensures the development of reproducible integrated 3D workflows and gives new insight into local and regional stratigraphic as well as structural issues. This project was initiated in year 2000 at the Geology and Palaeontology Institute of the University of Lausanne (Switzerland). Several collaborations ensured the improvement of technical approaches as well as the assessment of geological models. - Investigations into the Timor Sea structural style were carried out at the Tectonics Special Research Centre of the University of Western Australia and in collaboration with Woodside Energy in Perth. - Seismic analysis and attributes classification approach were initiated with Schlumberger Oilfield Australia in Perth; assessments and enhancements of the integrated seismic approaches benefited from collaborations with scientists from Schlumberger Stavanger Research (Norway). Adapting and refining from "linear" exploration techniques, a conceptual "helical" 3D seismic approach has been developed. In order to investigate specific geological issues this approach, integrating seismic attributes and visualisation tools, has been refined and adjusted leading to the development of two specific workflows: - A stratigraphic workflow focused on the recognition of geobodies and the characterization of depositional systems. Additionally, it can support the modelling of the subsidence and incidentally the constraint of the hydrocarbon maturity of a given area. - A structural workflow used to quickly and accurately define major and secondary fault systems. The integration of the 3D structural interpretation results ensures the analysis of the fault networks kinematics which can affect hydrocarbon trapping mechanisms. The application of these integrated workflows brings new insight into two complex settings on the Australian North West Shelf and ensures the definition of astonishing stratigraphic and structural outcomes. The stratigraphic workflow ensures the 3D characterization of the Late Palaeozoic glacial depositional system on the Mermaid Nose (Dampier Subbasin, Northern Carnarvon Basin) that presents similarities with the glacial facies along the Neotethys margin up to Oman (chapter 3.1). A subsidence model reveals the Phanerozoic geodynamic evolution of this area (chapter 3.2) and emphasizes two distinct mode of regional extension for the Palaeozoic (Neotethys opening) and Mesozoic (abyssal plains opening). The structural workflow is used for the definition of the structural evolution of the Laminaria High area (Bonaparte Basin). Following a regional structural characterization of the Timor Sea (chapter 4.1), a thorough analysis of the Mesozoic fault architecture reveals a local rotation of the stress field and the development of reverse structures (flower structures) in extensional setting, that form potential hydrocarbon traps (chapter 4.2). The definition of the complex Neogene structural architecture associated with the fault kinematic analysis and a plate flexure model (chapter 4.3) suggest that the Miocene to Pleistocene reactivation phases recorded at the Laminaria High most probably result from the oblique normal reactivation of the underlying Mesozoic fault planes. This episode is associated with the deformation of the subducting Australian plate. Based on these results three papers were published in international journals and two additional publications will be submitted. Additionally this research led to several communications in international conferences. Although the different workflows presented in this research have been primarily developed and used for the analysis of specific stratigraphic and structural geobodies on the Australian North West Shelf, similar integrated 3D seismic approaches will have applications to hydrocarbon exploration and production phases; for instance increasing the recognition of potential source rocks, secondary migration pathways, additional traps or reservoir breaching mechanisms. The new elements brought by this research further highlight that 3D seismic data contains a tremendous amount of hidden geological information waiting to be revealed and that will undoubtedly bring new insight into depositional systems, structural evolution and geohistory of the areas reputed being explored and constrained and other yet to be constrained. The further development of 3D texture attributes highlighting specific features of the seismic signal, the integration of quantitative analysis for stratigraphic and structural processes, the automation of the interpretation workflow as well as the formal definition of "seismo-morphologic" characteristics of a wide range of geobodies from various environments would represent challenging examples of continuation of this present research. The 21st century will most probably represent a transition period between fossil and other alternative energies. The next generation of seismic interpreters prospecting for hydrocarbon will undoubtedly face new challenges mostly due to the shortage of obvious and easy targets. They will probably have to keep on integrating techniques and geological processes in order to further capitalise the seismic data for new potentials definition. Imagination and creativity will most certainly be among the most important quality required from such geoscientists.
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The arenaviruses are an important family of emerging viruses that includes several causative agents of severe hemorrhagic fevers in humans that represent serious public health problems. A crucial step of the arenavirus life cycle is maturation of the envelope glycoprotein precursor (GPC) by the cellular subtilisin kexin isozyme 1 (SKI-1)/site 1 protease (S1P). Comparison of the currently known sequences of arenavirus GPCs revealed the presence of a highly conserved aromatic residue at position P7 relative to the SKI-1/S1P cleavage side in Old World and clade C New World arenaviruses but not in New World viruses of clades A and B or cellular substrates of SKI-1/S1P. Using a combination of molecular modeling and structure-function analysis, we found that residueY285 of SKI-1/S1P, distal from the catalytic triad, is implicated in the molecular recognition of the aromatic "signature residue" at P7 in the GPC of Old World Lassa virus. Using a quantitative biochemical approach, we show that Y285 of SKI-1/S1P is crucial for the efficient processing of peptides derived from Old World and clade C New World arenavirus GPCs but not of those from clade A and B New World arenavirus GPCs. The data suggest that during coevolution with their mammalian hosts, GPCs of Old World and clade C New World viruses expanded the molecular contacts with SKI-1/S1P beyond the classical four-amino-acid recognition sequences and currently occupy an extended binding pocket.
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PRECON S.A is a manufacturing company dedicated to produce prefabricatedconcrete parts to several industries as rail transportation andagricultural industries.Recently, PRECON signed a contract with RENFE,the Spanish Nnational Rail Transportation Company to manufacturepre-stressed concrete sleepers for siding of the new railways of the highspeed train AVE. The scheduling problem associated with the manufacturingprocess of the sleepers is very complex since it involves severalconstraints and objectives. The constraints are related with productioncapacity, the quantity of available moulds, satisfying demand and otheroperational constraints. The two main objectives are related withmaximizing the usage of the manufacturing resources and minimizing themoulds movements. We developed a deterministic crowding genetic algorithmfor this multiobjective problem. The algorithm has proved to be a powerfuland flexible tool to solve the large-scale instance of this complex realscheduling problem.
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While the influence of HLA-AB and -DRB1 matching on the outcome of bone marrow transplantation (BMT) with unrelated donors is clear, the evaluation of HLA-C has been hampered by its poor serological definition. Because the low resolution of standard HLA-C typing could explain the significant number of positive cytotoxic T lymphocyte precursor frequency (CTLpf) tests found among HLA-AB-subtype, DRB1/B3/B5-subtype matched patient/donor pairs, we have identified by sequencing the incompatibilities recognized by CD8+ CTL clones obtained from such positive CTLpf tests. In most cases the target molecules were HLA-C antigens that had escaped detection by serology (e.g. Cw*1601, 1502 or 0702). Direct recognition of HLA-C by a CTL clone was demonstrated by lysis of the HLA class I-negative 721.221 cell line transfected with Cw*1601 cDNA. Because of the functional importance of Cw polymorphism, a PCR-SSO oligotyping procedure was set up allowing the resolution of 29 Cw alleles. Oligotyping of a panel of 382 individuals (including 101 patients and their 272 potential unrelated donors, 5 related donors and 4 platelet donors) allowed to determine HLA-C and HLA A-B-Cw-DRB1 allelic frequencies, as well as a number of A-Cw, B-Cw, and DRB1-Cw associations. Two new HLA-Cw alleles (Cw*02023 and Cw*0707) were identified by DNA sequencing of PCR-amplified exon 2-intron 2-exon 3 amplicons. Furthermore, we determined the degree of HLA-C compatibility in 287 matched pairs that could be formed from 73 patients and their 184 potential unrelated donors compatible for HLA-AB by serology and for HLA-DRB1/ B3/B5 by oligotyping. Cw mismatches were identified in 42.1% of these pairs, and AB-subtype oligotyping showed that 30% of these Cw-incompatible pairs were also mismatched for A or B-locus subtype. The degree of HLA-C incompatibility was strongly influenced by the linkage with B alleles and by the ABDR haplotypes. Cw alleles linked with B*4403, B*5101, B18, and B62 haplotypes were frequently mismatched. Apparently high resolution DNA typing for HLA-AB does not result in full matching at locus C. Since HLA-C polymorphism is recognized by alloreactive CTLs, such incompatibilities might be as relevant as AB-subtype mismatches in clinical transplantation.
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We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.
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Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random-ization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in orderto obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.
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Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques
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The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.
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Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.
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In unicolonial populations of ants, individuals can mix freely within large networks of nests that contain many queens. It has been proposed that the absence of aggression in unicolonial populations stems from a loss of nest mate recognition, but few studies have tested this hypothesis. We investigated patterns of aggression and nest mate recognition in the unicolonial wood ant, Formica paralugubris. Little aggression occurred, even between workers from nests separated by up to 5 km. However, when aggression took place, it was directed toward non-nest mates rather than nest mates. Trophallaxis (exchange of liquid food) occurred very frequently, and surprisingly, workers performed significantly more trophallaxis with non-nest mates than with nest mates (bias 2.4:1). Hence, workers are able to discriminate nest mates from non-nest mates. Higher rates of trophallaxis between non-nest mates may serve to homogenize the colony odor or may be an appeasement mechanism. Trophallaxis rate and aggression level were not correlated with geographical distance and did not differ within and between two populations separated by several kilometers. Hence, these populations do not represent differentiated supercolonies with clear-cut behavioral boundaries. Overall, the data demonstrate that unicoloniality can evolve despite well-developed nest mate recognition. Reduced levels of aggression might have been favored by the low rate of interactions with foreign workers, high cost of erroneously rejecting nest mates, and low cost of accepting foreign workers.
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ABSTRACT: BACKGROUND: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have shown that a patient's antibody reaction in a confirmatory line immunoassay (INNO-LIATM HIV I/II Score, Innogenetics) provides information on the duration of infection. Here, we sought to further investigate the diagnostic specificity of various Inno-Lia algorithms and to identify factors affecting it. METHODS: Plasma samples of 714 selected patients of the Swiss HIV Cohort Study infected for longer than 12 months and representing all viral clades and stages of chronic HIV-1 infection were tested blindly by Inno-Lia and classified as either incident (up to 12 m) or older infection by 24 different algorithms. Of the total, 524 patients received HAART, 308 had HIV-1 RNA below 50 copies/mL, and 620 were infected by a HIV-1 non-B clade. Using logistic regression analysis we evaluated factors that might affect the specificity of these algorithms. RESULTS: HIV-1 RNA <50 copies/mL was associated with significantly lower reactivity to all five HIV-1 antigens of the Inno-Lia and impaired specificity of most algorithms. Among 412 patients either untreated or with HIV-1 RNA ≥50 copies/mL despite HAART, the median specificity of the algorithms was 96.5% (range 92.0-100%). The only factor that significantly promoted false-incident results in this group was age, with false-incident results increasing by a few percent per additional year. HIV-1 clade, HIV-1 RNA, CD4 percentage, sex, disease stage, and testing modalities exhibited no significance. Results were similar among 190 untreated patients. CONCLUSIONS: The specificity of most Inno-Lia algorithms was high and not affected by HIV-1 variability, advanced disease and other factors promoting false-recent results in other STARHS. Specificity should be good in any group of untreated HIV-1 patients.
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Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.
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1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.