961 resultados para MAPPING MOLECULAR NETWORKS
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The analysis of genetic data for human immunodeficiency virus type 1 (HIV-1) and human T-cell lymphotropic virus type 1 (HTLV-1) is essential to improve treatment and public health strategies as well as to select strains for vaccine programs. However, the analysis of large quantities of genetic data requires collaborative efforts in bioinformatics, computer biology, molecular biology, evolution, and medical science. The objective of this study was to review and improve the molecular epidemiology of HIV-1 and HTLV-1 viruses isolated in Brazil using bioinformatic tools available in the Laboratório Avançado de Sáude Pública (Lasp) bioinformatics unit. The analysis of HIV-1 isolates confirmed a heterogeneous distribution of the viral genotypes circulating in the country. The Brazilian HIV-1 epidemic is characterized by the presence of multiple subtypes (B, F1, C) and B/F1 recombinant virus while, on the other hand, most of the HTLV-1 sequences were classified as Transcontinental subgroup of the Cosmopolitan subtype. Despite the high variation among HIV-1 subtypes, protein glycosylation and phosphorylation domains were conserved in the pol, gag, and env genes of the Brazilian HIV-1 strains suggesting constraints in the HIV-1 evolution process. As expected, the functional protein sites were highly conservative in the HTLV-1 env gene sequences. Furthermore, the presence of these functional sites in HIV-1 and HTLV-1 strains could help in the development of vaccines that pre-empt the viral escape process.
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This study was carried out to evaluate the molecular pattern of all available Brazilian human T-cell lymphotropic virus type 1 Env (n = 15) and Pol (n = 43) nucleotide sequences via epitope prediction, physico-chemical analysis, and protein potential sites identification, giving support to the Brazilian AIDS vaccine program. In 12 previously described peptides of the Env sequences we found 12 epitopes, while in 4 peptides of the Pol sequences we found 4 epitopes. The total variation on the amino acid composition was 9 and 17% for human leukocyte antigen (HLA) class I and class II Env epitopes, respectively. After analyzing the Pol sequences, results revealed a total amino acid variation of 0.75% for HLA-I and HLA-II epitopes. In 5 of the 12 Env epitopes the physico-chemical analysis demonstrated that the mutations magnified the antigenicity profile. The potential protein domain analysis of Env sequences showed the loss of a CK-2 phosphorylation site caused by D197N mutation in one epitope, and a N-glycosylation site caused by S246Y and V247I mutations in another epitope. Besides, the analysis of selection pressure have found 8 positive selected sites (w = 9.59) using the codon-based substitution models and maximum-likelihood methods. These studies underscore the importance of this Env region for the virus fitness, for the host immune response and, therefore, for the development of vaccine candidates.
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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.
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Malondialdehyde (MDA) is a small, ubiquitous, and potentially toxic aldehyde that is produced in vivo by lipid oxidation and that is able to affect gene expression. Tocopherol deficiency in the vitamin E2 mutant vte2-1 of Arabidopsis thaliana leads to massive lipid oxidation and MDA accumulation shortly after germination. MDA accumulation correlates with a strong visual phenotype (growth reduction, cotyledon bleaching) and aberrant GST1 (glutathione S-transferase 1) expression. We suppressed MDA accumulation in the vte2-1 background by genetically removing tri-unsaturated fatty acids. The resulting quadruple mutant, fad3-2 fad7-2 fad8 vte2-1, did not display the visual phenotype or the aberrant GST1 expression observed in vte2-1. Moreover, cotyledon bleaching in vte2-1 was chemically phenocopied by treatment of wild-type plants with MDA. These data suggest that products of tri-unsaturated fatty acid oxidation underlie the vte2-1 seedling phenotype, including cellular toxicity and gene regulation properties. Generation of the quadruple mutant facilitated the development of an in situ fluorescence assay based on the formation of adducts of MDA with 2-thiobarbituric acid at 37 degrees C. Specificity was verified by measuring pentafluorophenylhydrazine derivatives of MDA and by liquid chromatography analysis of MDA-2-thiobarbituric acid adducts. Potentially applicable to other organisms, this method allowed the localization of MDA pools throughout the body of Arabidopsis and revealed an undiscovered pool of the compound unlikely to be derived from trienoic fatty acids in the vicinity of the root tip quiescent center.
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Labile or mutation-sensitised proteins may spontaneously convert into aggregation-prone conformations that may be toxic and infectious. This hazardous behavior, which can be described as a form of "molecular criminality", can be actively counteracted in the cell by a network of molecular chaperone and proteases. Similar to law enforcement agents, molecular chaperones and proteases can specifically identify, apprehend, unfold and thus neutralize "criminal" protein conformers, allowing them to subsequently refold into harmless functional proteins. Irreversibly damaged polypeptides that have lost the ability to natively refold are preferentially degraded by highly controlled ATP-consuming proteases. Damaged proteins that escape proteasomal degradation can also be "incarcerated" into dense amyloids, "evicted" from the cell, or internally "exiled" to the lysosome to be hydrolysed and recycled. Thus, remarkable parallels exist between molecular and human forms of criminality, as well as in the cellular and social responses to various forms of crime. Yet, differences also exist: whereas programmed death is the preferred solution chosen by aged and aggregation-stressed cells, collective suicide is seldom chosen by lawless societies. Significantly, there is no cellular equivalent for the role of familial care and of education in general, which is so crucial to the proper shaping of functional persons in the society. Unlike in the cell, humanism introduces a bias against radical solutions such as capital punishment, favouring crime prevention, reeducation and social reinsertion of criminals.
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Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.
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Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.
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A neural network was used to map three PID operating regions for a two-input two-output steam generator system. The network was used in stand alone feedforward operation to control the whole operating range of the process, after being trained from the PID controllers corresponding to each control region. The network inputs are the plant error signals, their integral, their derivative and a 4-error delay train.
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In this working paper we discuss current attempts to engage communities in planning policy formulation in the UK. In particular we focus on the preparation of Community Strategies (CS) in England to inform local public policy and the wider proposals recently published by the UK government to move towards enhanced community engagement in planning (DTLR, 2001). We discuss how such strategies could be operationalised with a conceptual framework developed following ideas derived from ANT (cf. Murdoch, 1997, 1998; Selman, 2000; Parker & Wragg, 1999; Callon, 1986, 1998) and the ‘capitals’ literature (Lin, 2002; Fine, 2001; Selman, 2000; Putnam, 1993). We see this as an expression of neo-pragmatic planning theory, (Hoch, 1996; Stein & Harper, 2000) to develop a form of ‘pre-plan mapping’.
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BACKGROUND: Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. OBJECTIVES: The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. METHODS: Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. RESULTS: All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). CONCLUSIONS: This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by other organizations, and we conjecture that patterns observed in this study could be found in other DHSNs. Future research should analyze network growth over time and examine the characteristics and survival rates of superusers.
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The isolate AF199 of Lettuce mosaic virus (LMV, genus Potyvirus) causes local lesions followed by systemic wilting and plant death in the lettuce cultivars Ithaca and Vanguard 75. Analysis of the phenotype of virus chimeras revealed that a region within the PI protein coding region (nucleotides 112-386 in the viral genome) and/or another one within the CI protein coding region (nucleoticles 5496-5855) are sufficient together to cause the lethal wilting in Ithaca, but not in Vanguard 75. This indicates that the determinants of this particular symptom are different in these two lettuce cultivars. The wilting phenotype was not directly correlated with differences in the deduced amino acid sequence of these two regions. Furthermore, transient expression of the LMV-AF 199 proteins, separately or in combination, did not induce local necrosis or any other visible reaction in the plants. Together, these results Suggest that the systemic wilting reaction might be Clue to RNA rather than protein sequences. (c) 2004 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Asian soybean rust (ASR) is caused by the fungal pathogen Phakopsora pachyrhizi Sydow & Sydow. It was first identified in Brazil in 2001 and quickly infected soybean areas in several countries in South America. Primary efforts to combat this disease must involve the development of resistant cultivars. Four distinct genes that confer resistance against ASR have been reported: Rpp1, Rpp2, Rpp3, and Rpp4. However, no cultivar carrying any of those resistance loci has been released. The main objective of this study was to genetically map Rpp2 and Rpp4 resistance genes. Two F(2:3) populations, derived from the crosses between the resistant lines PI 230970 (Rpp2), PI 459025 (Rpp4) and the susceptible cultivar BRS 184, were used in this study. The mapping populations and parental lines were inoculated with a field isolate of P. pachyrhizi and evaluated for lesion type as resistant (RB lesions) or susceptible (TAN lesions). The mapping populations were screened with SSR markers, using the bulk segregant analysis (BSA) to expedite the identification of linked markers. Both resistance genes showed an expected segregation ratio for a dominant trait. This study allowed mapping Rpp2 and Rpp4 loci on the linkage groups J and G, respectively. The associated markers will be of great value on marker assisted selection for this trait.