147 resultados para Efficient dominating set


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Homologous recombination is important for the repair of double-strand breaks during meiosis. Eukaryotic cells require two homologs of Escherichia coli RecA protein, Rad51 and Dmc1, for meiotic recombination. To date, it is not clear, at the biochemical level, why two homologs of RecA are necessary during meiosis. To gain insight into this, we purified Schizosaccharomyces pombe Rad51 and Dmc1 to homogeneity. Purified Rad51 and Dmc1 form homo-oligomers, bind single-stranded DNA preferentially, and exhibit DNA-stimulated ATPase activity. Both Rad51 and Dmc1 promote the renaturation of complementary single-stranded DNA. Importantly, Rad51 and Dmc1 proteins catalyze ATP-dependent strand exchange reactions with homologous duplex DNA. Electron microscopy reveals that both S. pombe Rad51 and Dmc1 form nucleoprotein filaments. Rad51 formed helical nucleoprotein filaments on single-stranded DNA, whereas Dmc1 was found in two forms, as helical filaments and also as stacked rings. These results demonstrate that Rad51 and Dmc1 are both efficient recombinases in lower eukaryotes and reveal closer functional and structural similarities between the meiotic recombinase Dmc1 and Rad51. The DNA strand exchange activity of both Rad51 and Dmc1 is most likely critical for proper meiotic DNA double-strand break repair in lower eukaryotes.

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Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

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In recent years there has been growing interest in the question of how the particular topology of polymeric chains affects their overall dimensions and physical behavior. The majority of relevant studies are based on numerical simulation methods or analytical treatment; however, both these approaches depend on various assumptions and simplifications. Experimental verification is clearly needed but was hampered by practical difficulties in obtaining preparative amounts of knotted or catenated polymers with predefined topology and precisely set chain length. We introduce here an efficient method of production of various single-stranded DNA knots and catenanes that have the same global chain length. We also characterize electrophoretic migration of the produced single-stranded DNA knots and catenanes with increasing complexity.

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Medicine counterfeiting is a crime that has increased in recent years and now involves the whole world. Health and economic repercussions have led pharmaceutical industries and agencies to develop many measures to protect genuine medicines and differentiate them from counterfeits. Detecting counterfeit is chemically relatively simple for the specialists, but much more information can be gained from the analyses in a forensic intelligence perspective. Analytical data can feed criminal investigation and law enforcement by detecting and understanding the criminal phenomenon. Profiling seizures using chemical and packaging data constitutes a strong way to detect organised production and industrialised forms of criminality, and is the focus of this paper. Thirty-three seizures of a commonly counterfeited type of capsule have been studied. The results of the packaging and chemical analyses were gathered within an organised database. Strong linkage was found between the seizures at the different production steps, indicating the presence of a main counterfeit network dominating the market. The interpretation of the links with circumstantial data provided information about the production and the distribution of counterfeits coming from this network. This forensic intelligence perspective has the potential to be generalised to other types of products. This may be the only reliable approach to help the understanding of the organised crime phenomenon behind counterfeiting and to enable efficient strategic and operational decision making in an attempt to dismantle counterfeit network.

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The recent availability of the chicken genome sequence poses the question of whether there are human protein-coding genes conserved in chicken that are currently not included in the human gene catalog. Here, we show, using comparative gene finding followed by experimental verification of exon pairs by RT-PCR, that the addition to the multi-exonic subset of this catalog could be as little as 0.2%, suggesting that we may be closing in on the human gene set. Our protocol, however, has two shortcomings: (i) the bioinformatic screening of the predicted genes, applied to filter out false positives, cannot handle intronless genes; and (ii) the experimental verification could fail to identify expression at a specific developmental time. This highlights the importance of developing methods that could provide a reliable estimate of the number of these two types of genes.

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Two cationic octanuclear metalla-cubes [Ru(8)(η(6)-C(6)H(5)Me)(8)(tpp-H2)(2)(dhbq)(4)](8+) and [Ru(8)(η(6)-p-iPrC(6)H(4)Me)(8)(tpp-H2)(2)(dhbq)(4)](8+) were prepared and evaluated as dual photosensitizers and chemotherapeutics in cancer cells. In the dark, the complexes presented high cytotoxicity towards only melanoma and ovarian cancer cells. However, the complexes exhibited good phototoxicities toward all cancer cells (1μM concentration, LD(50)=2-7J/cm(2)), thus suggesting a dual synergistic effect with good properties of both the arene ruthenium chemotherapeutics and the porphyrin photosensitizers.

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BACKGROUND: New evidence shows that high density lipoproteins (HDL) have protective effects beyond their role in reverse cholesterol transport. Reconstituted HDL (rHDL) offer an attractive means of clinically exploiting these novel effects including cardioprotection against ischemia reperfusion injury (IRI). However, basic rHDL composition is limited to apolipoprotein AI (apoAI) and phospholipids; addition of bioactive compound may enhance its beneficial effects. OBJECTIVE: The aim of this study was to investigate the role of rHDL in post-ischemic model, and to analyze the potential impact of sphingosine-1-phosphate (S1P) in rHDL formulations. METHODS AND RESULTS: The impact of HDL on IRI was investigated using complementary in vivo, ex vivo and in vitro IRI models. Acute post-ischemic treatment with native HDL significantly reduced infarct size and cell death in the ex vivo, isolated heart (Langendorff) model and the in vivo model (-48%, p<0.01). Treatment with rHDL of basic formulation (apoAI + phospholipids) had a non-significant impact on cell death in vitro and on the infarct size ex vivo and in vivo. In contrast, rHDL containing S1P had a highly significant, protective influence ex vivo, and in vivo (-50%, p<0.01). This impact was comparable with the effects observed with native HDL. Pro-survival signaling proteins, Akt, STAT3 and ERK1/2 were similarly activated by HDL and rHDL containing S1P both in vitro (isolated cardiomyocytes) and in vivo. CONCLUSION: HDL afford protection against IRI in a clinically relevant model (post-ischemia). rHDL is significantly protective if supplemented with S1P. The protective impact of HDL appears to target directly the cardiomyocyte.

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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

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BACKGROUND: Expression of heterologous genes in mammalian cells or organisms for therapeutic or experimental purposes often requires tight control of transgene expression. Specifically, the following criteria should be met: no background gene activity in the off-state, high gene expression in the on-state, regulated expression over an extended period, and multiple switching between on- and off-states. METHODS: Here, we describe a genetic switch system for controlled transgene transcription using chimeric repressor and activator proteins functioning in a novel regulatory network. In the off-state, the target transgene is actively silenced by a chimeric protein consisting of multimerized eukaryotic transcriptional repression domains fused to the DNA-binding tetracycline repressor. In the on-state, the inducer drug doxycycline affects both the derepression of the target gene promoter and activation by the GAL4-VP16 transactivator, which in turn is under the control of an autoregulatory feedback loop. RESULTS: The hallmark of this new system is the efficient transgene silencing in the off-state, as demonstrated by the tightly controlled expression of the highly cytotoxic diphtheria toxin A gene. Addition of the inducer drug allows robust activation of transgene expression. In stably transfected cells, this control is still observed after months of repeated cycling between the repressed and activated states of the target genes. CONCLUSIONS: This system permits tight long-term regulation when stably introduced into cell lines. The underlying principles of this network system should have general applications in biotechnology and gene therapy.

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BACKGROUND: Granulocyte-macrophage colony-stimulating factor (GM-CSF) therapy is effective in treating some Crohn's disease (CD) patients and protects mice from colitis induced by dextran sulfate sodium (DSS) administration. However, its mechanisms of action remain elusive. We hypothesized that GM-CSF affects intestinal mucosal repair. METHODS: DSS colitic mice were treated with daily pegylated GM-CSF or saline and clinical, histological, and inflammatory parameters were kinetically evaluated. Further, the role of bone marrow-derived cells in the impact of GM-CSF therapy on DSS colitis was addressed using cell transfers. RESULTS: GM-CSF therapy reduced clinical signs of colitis and the release of inflammatory mediators. GM-CSF therapy improved mucosal repair, with faster ulcer reepithelialization, accelerated hyperproliferative response of epithelial cells in ulcer-adjacent crypts, and lower colonoscopic ulceration scores in GM-CSF-administered mice relative to untreated mice. We observed that GM-CSF-induced promotion of mucosal repair is timely associated with a reduction in neutrophil numbers and increased accumulation of CD11b(+) monocytic cells in colon tissues. Importantly, transfer of splenic GM-CSF-induced CD11b(+) myeloid cells into DSS-exposed mice improved colitis, and lethally irradiated GM-CSF receptor-deficient mice reconstituted with wildtype bone marrow cells were protected from DSS-induced colitis upon GM-CSF therapy. Lastly, GM-CSF-induced CD11b(+) myeloid cells were shown to promote in vitro wound repair. CONCLUSIONS: Our study shows that GM-CSF-dependent stimulation of bone marrow-derived cells during DSS-induced colitis accelerates colonic tissue repair. These data provide a putative mechanism for the observed beneficial effects of GM-CSF therapy in Crohn's disease.

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This paper presents an ITK implementation for exportingthe contours of the automated segmentation results toDICOM-RT Structure Set format. The âeurooeradiotherapystructure setâeuro (RTSTRUCT) object of the DICOM standard isused for the transfer of patient structures and relateddata, between the devices found within and outside theradiotherapy department. It mainly contains theinformation of regions of interest (ROIs) and points ofinterest (E.g. dose reference points). In many cases,rather than manually drawing these ROIs on the CT images,one can indeed benefit from the automated segmentationalgorithms already implemented in ITK. But at present, itis not possible to export the ROIs obtained from ITK toRTSTRUCT format. In order to bridge this gap, we havedeveloped a framework for exporting contour data toRTSTRUCT. We provide here the complete implementation ofRTSTRUCT exporter and present the details of the pipelineused. Results on a 3-D CT image of the Head and Neck(H&N) region are presented.

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The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

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Caspase cleaved amyloid precursor protein (APPcc) and SET are increased and mislocalized in the neuronal cytoplasm in Alzheimer Disease (AD) brains. Translocated SET to the cytoplasm can induce tau hyperphosphorylation. To elucidate the putative relationships between mislocalized APPcc and SET, we studied their level and distribution in the hippocampus of 5 controls, 3 Down syndrome and 10 Alzheimer patients. In Down syndrome and Alzheimer patients, APPcc and SET levels were increased in CA1 and the frequency of both localizations in the neuronal cytoplasm was high in CA1, and low in CA4. As the increase of APPcc is already present at early stages of AD, we overexpressed APPcc in CA1 and the dentate gyrus neurons of adult mice with a lentiviral construct. APPcc overexpression in CA1 and not in the dentate gyrus induced endogenous SET translocation and tau hyperphosphorylation. These data suggest that increase in APPcc in CA1 neurons could be an early event leading to the translocation of SET and the progression of AD through tau hyperphosphorylation.

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In this paper we propose a highly accurate approximation procedure for ruin probabilities in the classical collective risk model, which is based on a quadrature/rational approximation procedure proposed in [2]. For a certain class of claim size distributions (which contains the completely monotone distributions) we give a theoretical justification for the method. We also show that under weaker assumptions on the claim size distribution, the method may still perform reasonably well in some cases. This in particular provides an efficient alternative to a related method proposed in [3]. A number of numerical illustrations for the performance of this procedure is provided for both completely monotone and other types of random variables.

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Renal colic (RC) is a common problem in primary care practice. It is estimated that 5-12% of the general population will suffer once RC during his lifetime. The primary care physicians play a central role in the management of urolithiasis. This article summarizes the current recommendations in terms of renal colic emergency management: biological assessment, imaging, pain relief and specific treatment. The vast majority of patients only needs efficient antalgic treatment and an outpatient monitoring. A minimal assessment must however be undertaken to detect complicated RC that will require urgent treatment in urology department. The analysis of the stone after the crisis is crucial to set up a preventive treatment.