986 resultados para Jasper Jones


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En aquest projecte es pretén utilitzar mètodes coneguts com ara Viola&Jones (detecció) i EigenFaces (reconeixement) per a detectar i reconèixer cares dintre d’imatges de vídeo. Per a aconseguir aquesta tasca cal partir d’un conjunt de dades d’entrenament per a cada un dels mètodes (base de dades formada per imatges i anotacions manuals). A partir d’aquí, l’aplicació, ha de ser capaç de detectar cares en noves imatges i reconèixer-les (identificar de quina cara es tracta)

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Members of the leucine-rich repeat protein family are involved in diverse functions including protein phosphatase 2-inhibition, cell cycle regulation, gene regulation and signalling pathways. A novel Schistosoma mansoni gene, called SmLANP, presenting homology to various genes coding for proteins that belong to the super family of leucine-rich repeat proteins, was characterized here. SmLANP was 1184bp in length as determined from cDNA and genomic sequences and encoded a 296 amino acid open reading frame that spanning from 6 to 894bp. The predicted amino acid sequence had a calculated molecular weight of 32kDa. Analysis of the predicted sequence indicated the presence of 3 leucine-rich domains (LRR) located in the N-terminal region and an aspartic acid rich region in the C-terminal end. SmLANP transcript is expressed in all stages of the S. mansoni life cycle analyzed, exhibiting the highest expression level in males. The SmLANP protein was expressed in a GST expression system and antibodies raised in mice against the recombinant protein. By immunolocalization assay, using adult worms, it was shown that the protein is mainly present in the cell nucleus through the whole body and strongly expressed along the tegument cell body nuclei of adult worms. As members of this family are usually involved in protein-protein interaction, a yeast two hybrid assay was conducted to identify putative binding partners for SmLANP. Thirty-six possible partners were identified, and a protein ATP synthase subunit alpha was confirmed by pull down assays, as a binding partner of the SmLANP protein.

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The family Nematotaeniidae, tapeworms commonly found in the small intestines of amphibians and reptiles, includes 27 recognised species distributed among four genera: Bitegmen Jones, Cylindrotaenia Jewell, Distoichometra Dickey and Nematotaenia Lühe. The taxonomy of these cestodes is poorly defined, due in part to the difficulties of observing many anatomical traits. This study presents and describes a new genus and species of nematotaeniid parasite found in cane toads (Rhinella marina) from eastern Brazilian Amazonia. The cestodes were collected during the necropsy of 20 hosts captured in the urban area of Belém, Pará. The specimens were fixed and processed for light microscopy, scanning electron microscopy (SEM) and three-dimensional (3D) reconstruction. Samples were also collected for molecular analyses. The specimens presented a cylindrical body, two testes and paruterine organs. However, they could not be allocated to any of the four existing nematotaeniid genera due to the presence of two each of dorsal compact medullary testes, cirri, cirrus pouches, genital pores, ovaries and vitelline glands per mature segment. Lanfrediella amphicirrus gen. nov. sp. nov. is the first nematotaeniid studied using Historesin analysis, SEM and 3D reconstruction, and it is the second taxon for which molecular data have been deposited in GenBank.

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A dimensional analysis of the classical equations related to the dynamics of vector-borne infections is presented. It is provided a formal notation to complete the expressions for the Ross' Threshold Theorem, the Macdonald's basic reproduction "rate" and sporozoite "rate", Garret-Jones' vectorial capacity and Dietz-Molineaux-Thomas' force of infection. The analysis was intended to provide a formal notation that complete the classical equations proposed by these authors.

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In this study the effect of eight DNA topoisomerase inhibitors on the growth Trypanosoma rangeli epimastigotes in cell culture was investigated. Among the eight compounds tested, idarubicin was the only compound that displayed promising trypanocidal activity with a half-maximal growth inhibition (GI50) value in the sub-micromolar range. Fluorescence-activated cell sorting analysis showed a reduction in DNA content in T. rangeli epimastigotes when treated with idarubicin. In contrast to T. rangeli, against Trypanosoma cruzi epimastigotes idarubicin was much less effective exhibiting a GI50 value in the mid-micromolar range. This result indicates that idarubicin displays differential toxic effects in T. rangeli and T. cruzi. Compared with African trypanosomes, it seems that American trypanosomes are generally less susceptible to DNA topoisomerase inhibitors.

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INTRODUCTION CD226 genetic variants have been associated with a number of autoimmune diseases and recently with systemic sclerosis (SSc). The aim of this study was to test the influence of CD226 loci in SSc susceptibility, clinical phenotypes and autoantibody status in a large multicenter European population. METHODS A total of seven European populations of Caucasian ancestry were included, comprising 2,131 patients with SSc and 3,966 healthy controls. Three CD226 single nucleotide polymorphisms (SNPs), rs763361, rs3479968 and rs727088, were genotyped using Taqman 5'allelic discrimination assays. RESULTS Pooled analyses showed no evidence of association of the three SNPs, neither with the global disease nor with the analyzed subphenotypes. However, haplotype block analysis revealed a significant association for the TCG haplotype (SNP order: rs763361, rs34794968, rs727088) with lung fibrosis positive patients (PBonf = 3.18E-02 OR 1.27 (1.05 to 1.54)). CONCLUSION Our data suggest that the tested genetic variants do not individually influence SSc susceptibility but a CD226 three-variant haplotype is related with genetic predisposition to SSc-related pulmonary fibrosis.

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INTRODUCTION The aim of the present study was to investigate the possible role of CD40 and CD40 ligand (CD40LG) genes in the susceptibility and phenotype expression of systemic sclerosis (SSc). METHODS In total, 2,670 SSc patients and 3,245 healthy individuals from four European populations (Spain, Germany, The Netherlands, and Italy) were included in the study. Five single-nucleotide polymorphisms (SNPs) of CD40 (rs1883832, rs4810485, rs1535045) and CD40LG (rs3092952, rs3092920) were genotyped by using a predesigned TaqMan allele-discrimination assay technology. Meta-analysis was assessed to determine whether an association exists between the genetic variants and SSc or its main clinical subtypes. RESULTS No evidence of association between CD40 and CD40LG genes variants and susceptibility to SSc was observed. Similarly, no significant statistical differences were observed when SSc patients were stratified by the clinical subtypes, the serologic features, and pulmonary fibrosis. CONCLUSIONS Our results do not suggest an important role of CD40 and CD40LG gene polymorphisms in the susceptibility to or clinical expression of SSc.

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Several viruses have been associated with acute gastroenteritis (AGE), and group A rotavirus (RVA) and nor-ovirus (NoV) are the most prevalent. This study aimed to assess their prevalence among children hospitalised for diarrhoea during a three-year surveillance study. From May 2008-April 2011, overall positivity rates of 21.6% (628/2904) and 35.4% (171/483) were observed for RVA and NoV, respectively. The seasonality observed indicated distinct patterns when both viruses were compared. This finding may explain why hospitalisation for AGE remains constant throughout the year. Continuous AGE monitoring is needed to better assess the patterns of infection.

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Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC), a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP) malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

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Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

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Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

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Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

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Ryanodine receptor 1 (RYR1) mutations are a common cause of congenital myopathies associated with both dominant and recessive inheritance. Histopathological findings frequently feature central cores or multi-minicores, more rarely, type 1 predominance/uniformity, fiber-type disproportion, increased internal nucleation, and fatty and connective tissue. We describe 71 families, 35 associated with dominant RYR1 mutations and 36 with recessive inheritance. Five of the dominant mutations and 35 of the 55 recessive mutations have not been previously reported. Dominant mutations, typically missense, were frequently located in recognized mutational hotspot regions, while recessive mutations were distributed throughout the entire coding sequence. Recessive mutations included nonsense and splice mutations expected to result in reduced RyR1 protein. There was wide clinical variability. As a group, dominant mutations were associated with milder phenotypes; patients with recessive inheritance had earlier onset, more weakness, and functional limitations. Extraocular and bulbar muscle involvement was almost exclusively observed in the recessive group. In conclusion, our study reports a large number of novel RYR1 mutations and indicates that recessive variants are at least as frequent as the dominant ones. Assigning pathogenicity to novel mutations is often difficult, and interpretation of genetic results in the context of clinical, histological, and muscle magnetic resonance imaging findings is essential.

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ABSTRACT The interorganizational cooperation, through joint efforts with various actors, allows the high-tech companies to complement resources, especially in R&D projects. Collaborative projects have been identified in many studies as an important strategy to produce complex products and services in uncertain and competitive environments. Thus, this research aims at deepening the understanding of how the development dynamics of a collaborative R&D project in an industry of high technology occur. In order to achieve the proposed objective, the R&D project of the first microcontroller in the Brazilian semiconductor industry was defined as the object of analysis. The empirical choice is justified by the uniqueness of the case, besides bringing a diversity of actors and a level of complementarity of resources that were significant to the success of the project. Given the motivation to know who the actors were and what the main forms of interorganizational coordination were used in this project, interviews were carried out and a questionnaire was also made, besides other documents related to the project. The results presented show a network of nine actors and their roles in the interorganizational collaboration process, as well as the forms of social and temporal overlapping, used in the coordination of collective efforts. Focusing on the mechanisms of temporal and social integration highlighted throughout the study, the inclusion of R&D projects in the typology for interorganizational projects is proposed in this paper, which was also proposed by Jones and Lichtenstein (2008).

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Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.