917 resultados para vector error correction model


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Dendritic cells (DCs) are the most potent professional antigen-presenting cells (APCs), which play a vital role in primary immune responses. Introducing genes into DCs will allow constitutive expression of the encoded proteins and thus prolong the presentation of the antigens derived therefrom. In addition, multiple and unidentified epitopes encoded by the entire tumor-associated antigen (TAA) gene may enhance T cell activation. This study demonstrated that an HIV-1-based lentiviral vector conferred efficient gene transfer to DCs. The transgene, murine tyrosinase-related protein 2 (mTRP-2), encodes a clinically relevant melanoma-associated antigen (MAA), which has been found to be a tumor rejection antigen for B16 melanoma. The transfer and proper processing of mTRP-2 in DCs, in terms of RNA transcription activity and protein expression, were verified by RT-PCR and specific antibody, respectively. Administration of mTRP-2 gene-modified DCs (DC-HR'CmT2) to C57BL/6 mice evoked strong protection against tumor challenge, for which the presence of CD4(+) and CD8(+) cells during both the priming and challenge phase was essential. In a therapy model, our results showed that four of seven mice with preestablished tumor remained tumor free for 80 days after therapeutic vaccination. Given the results shown in this study, mTRP-2 gene transfer to DCs provides a potential therapeutic strategy for the management of melanoma, especially in the early stage of the disease.

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The paper presents a theory for modeling flow in anisotropic, viscous rock. This theory has originally been developed for the simulation of large deformation processes including the folding and kinking of multi-layered visco-elastic rock (Muhlhaus et al. [1,2]). The orientation of slip planes in the context of crystallographic slip is determined by the normal vector - the director - of these surfaces. The model is applied to simulate anisotropic mantle convection. We compare the evolution of flow patterns, Nusselt number and director orientations for isotropic and anisotropic rheologies. In the simulations we utilize two different finite element methodologies: The Lagrangian Integration Point Method Moresi et al [8] and an Eulerian formulation, which we implemented into the finite element based pde solver Fastflo (www.cmis.csiro.au/Fastflo/). The reason for utilizing two different finite element codes was firstly to study the influence of an anisotropic power law rheology which currently is not implemented into the Lagrangian Integration point scheme [8] and secondly to study the numerical performance of Eulerian (Fastflo)- and Lagrangian integration schemes [8]. It turned out that whereas in the Lagrangian method the Nusselt number vs time plot reached only a quasi steady state where the Nusselt number oscillates around a steady state value the Eulerian scheme reaches exact steady states and produces a high degree of alignment (director orientation locally orthogonal to velocity vector almost everywhere in the computational domain). In the simulations emergent anisotropy was strongest in terms of modulus contrast in the up and down-welling plumes. Mechanisms for anisotropic material behavior in the mantle dynamics context are discussed by Christensen [3]. The dominant mineral phases in the mantle generally do not exhibit strong elastic anisotropy but they still may be oriented by the convective flow. Thus viscous anisotropy (the main focus of this paper) may or may not correlate with elastic or seismic anisotropy.

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Protein engineering is a powerful tool, which correlates protein structure with specific functions, both in applied biotechnology and in basic research. Here, we present a practical teaching course for engineering the green fluorescent protein (GFP) from Aequorea victoria by a random mutagenesis strategy using error-prone polymerase chain reaction. Screening of bacterial colonies transformed with random mutant libraries identified GFP variants with increased fluorescence yields. Mapping the three-dimensional structure of these mutants demonstrated how alterations in structural features such as the environment around the fluorophore and properties of the protein surface can influence functional properties such as the intensity of fluorescence and protein solubility.

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Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

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Background Metastatic renal cell carcinoma (mRCC) is one of the most treatment-resistant malignancies. Despite all new therapeutic advances, almost all patients develop resistance to treatment and cure is rarely seen. In the present study, we evaluated the antitumor effect of a bicistronic retrovirus vector encoding both endostatin (ES) and interleukin (IL)-2 using an orthotopic metastatic RCC mouse model. Methods Balb/C-bearing Renca cells were treated with NIH/3T3-LendIRES-IL-2-SN cells. In the survival studies, mice were monitored daily until they died. At the end of the in vivo experiment, serum levels of IL-2 and ES were measured, the lung was weighed, and the number of metastatic nodules, nodule area, tumor vessels and proliferation of tumor-infiltrating Renca cells were determined. Results Inoculation of NIH/3T3-LendIRES-IL-2-SN cells resulted in an increase in ES and IL-2 levels in the treated group (p < 0.05). There was a significant decrease in lung wet weight, lung nodule area and tumor vessels in the treated group compared to the control group (p < 0.001). The proliferation of Renca cells in the bicistronic-treated group was significantly reduced compared to the control group (p < 0.05). Kaplan-Meier survival curves showed that the probability of survival was significantly higher for mice submitted to bicistronic therapy (log-rank test, p = 0.0016). Bicistronic therapy caused an increase in the infiltration of CD4, CD4 interferon (IFN)gamma-producing, CD8, CD8 IFN gamma-producing and natural killer (CD49b) cells. Conclusions Retroviral bicistronic gene transfer led to the secretion of functional ES and IL-2 that was sufficiently active to: (i) inhibit tumor angiogenesis and tumor cell proliferation and (ii) increase the infiltration of immune cells (C) Copyright. 2011 John Wiley & Sons, Ltd.

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Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

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There seems to be controversy on the anorectal sphincter presentation and anatomical division, as well as on its functional representation. Evaluation of the anorectal sphincter musculature has been achieved through several methods, including anorectal manometry and computerized tomography, but to date there is no experimental model allowing a detailed manometric study of this muscle complex. In this work, we have developed such a model, which should enable the manometric and radiographic study of the anatomical features and functional mechanisms of sphincteric injuries, as well as the assessment of drug effects on the anorectal musculature upon incontinence and constipation. Twenty-two piglets (aged 25-30 days, weighing 5-7 kg) were studied by anorectal manometry (rectoanal inhibitory reflex and vector volume) and computerized tomography (anorectal angle and anal canal length). The data obtained for the rectoanal inhibitory reflex, represented here as the average and standard deviation, were the following: relaxation duration = 14.75 +/- 3.62 s, sphincter basal pressure = 41.58 +/- 8.20 mmHg, relaxation index = 87.26 +/- 11.52%, speed of relaxation = 5.90 +/- 2.10 mm/s, and speed of relaxation recovery = 4.03 +/- 1.78 mm/s. As for the vector volume, results were as follows: vector volume = 2692.32 +/- 1298.12 mmHg(2) cm, sphincter length = 11.82 +/- 2.74 mm, high pressure zone length = 5.09 +/- 1.34 mm, maximum pressure = 61.50 +/- 20.58 mmHg, and asymmetry index = 43.50 +/- 10.03%. Radiographic evaluation led to the following results: anal canal length = 9.61 +/- 2.14 mm and anorectal angle = 137.91 +/- 7.75 degrees. The experimental model designed here allows both anorectal manometry and computerized tomography to be carried out in the same way it is performed in human beings, as long as animal sedation is strictly controlled.

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Objective: To analyse the effect of integrated orthodontic treatment, orthognathic surgery and orofacial myofunctional therapy on masseter muscle thickness in patients with class III dentofacial deformity three years after orthognathic surgery. Design: A longitudinal study was conducted on 13 patients with class III dentofacial deformities, denoted here as group P1 (before surgery) and group P3 (same patients 3 years to 3 years and 8 months after surgery). Fifteen individuals with no changes in facial morphology or dental occlusion were assigned to the control group (CG). Masseter muscle ultrasonography was performed in the resting and biting situations in the three groups. Data were analysed statistically by a mixed-effects linear model considering a level of significance of P < 0.05. Results: Significantly higher values (P < 0.01) of masseter muscle thickness (cm) were detected in group P3 (right rest: 0.82 +/- 0.16, left rest: 0.87 +/- 0.21, right bite: 1 +/- 0.22, left bite: 1.04 +/- 0.28) compared to group P1 (right rest: 0.63 +/- 0.19, left rest: 0.64 +/- 0.15, right bite: 0.87 +/- 0.16, left bite: 0.88 +/- 0.14). Between P3 and CG (right rest: 1.02 +/- 0.19, left rest: 1 +/- 0.19, right bite: 1.18 +/- 0.22, left bite: 1.16 +/- 0.22) there was a significant difference on the right side of the muscle (P < 0.05) in both situations and on the left side at rest. Conclusion: The proposed treatment resulted in improved masseter muscle thickness in patients with class III dentofacial deformity. (C) 2011 Elsevier Ltd. All rights reserved.

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Bioelectrical impedance vector analysis (BIVA) is a new method that is used for the routine monitoring of the variation in body fluids and nutritional status with assumptions regarding body composition values. The aim of the present study was to determine bivariate tolerance intervals of the whole-body impedance vector and to describe phase angle (PA) values for healthy term newborns aged 7-28 d. This descriptive cross-sectional study was conducted on healthy term neonates born at a low-risk public maternity. General and anthropometric neonatal data and bioelectrical impedance data (800 mu A-50 kHz) were obtained. Bivariate vector analysis was conducted with the resistance-reactance (RXc) graph method. The BIVA software was used to construct the graphs. The study was conducted on 109 neonates (52.3% females) who were born at term, adequate for gestational age, exclusively breast-fed and aged 13 (SD 3.6) d. We constructed one standard, reference, RXc-score graph and RXc-tolerance ellipses (50, 75 and 95 %) that can be used with any analyser. Mean PA was 3.14 (SD 0.43)degrees (3.12 (SD 0.39)degrees for males and 3.17 (SD 0.48)degrees for females). Considering the overlapping of ellipses of males and females with the general distribution, a graph for newborns aged 7-28 d with the same reference tolerance ellipse was defined for boys and girls. The results differ from those reported in the literature probably, in part, due to the ethnic differences in body composition. BIVA and PA permit an assessment without the need to know body weight and the prediction error of conventional impedance formulas.

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Introduction. Capybaras (Hydrochoerus hydrochaeris) are considered amplifying hosts of Rickettsia sp. These rodents are usually parasitized by the tick vector, Amblyomma cajennense, the main vector of rickettsioses in humans and animals in South America. Capybaras can be used as sentinels in detection of circulation of rickettsiae. Objective. Antibodies to rickettsiae of spotted fever group were detected in capybaras in a rural area of Cordoba Province, northern Colombia. Materials and methods. Sera were analyzed from 36 capybaras in a rural area of Monteria (village of San Jeronimo) in Cordoba. For the detection of IgG antibodies, indirect immunofluorescence was performed. The antigens were derived from R. rickettsia strain Taiacu isolated in Brazil. Capybara sera were diluted 1:64 for IFA analysis. Ticks were collected from each capybara (also known as chiguiro) and identified to species. Results. The seroprevalence of spotted fever group Rickettsia was 22% (8 capybaras). Four sera had a titer of 1:64, 3 had a titer of 1:128 and one serum had a titer of 1:512. All ticks removed from the capybaras (n=933) were taxonomically identified as Amblyomma cajennense. Conclusion. Colombia has areas endemic for rickettsioses, as indicated by confirmed annual outbreaks. The current study reports the first evidence of natural rickettsial infection of the spotted fever group in capybaras from Colombia. The findings suggest that capybaras can be used as sentinels for the circulation of rickettsiae and can identify endemic areas for the transmission of rickettsial diseases.

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The magnitude of the basic reproduction ratio R(0) of an epidemic can be estimated in several ways, namely, from the final size of the epidemic, from the average age at first infection, or from the initial growth phase of the outbreak. In this paper, we discuss this last method for estimating R(0) for vector-borne infections. Implicit in these models is the assumption that there is an exponential phase of the outbreaks, which implies that in all cases R(0) > 1. We demonstrate that an outbreak is possible, even in cases where R(0) is less than one, provided that the vector-to-human component of R(0) is greater than one and that a certain number of infected vectors are introduced into the affected population. This theory is applied to two real epidemiological dengue situations in the southeastern part of Brazil, one where R(0) is less than one, and other one where R(0) is greater than one. In both cases, the model mirrors the real situations with reasonable accuracy.

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Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.

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We constructed a BAC library of the model legume Lotus japonicus with a 6-to 7-fold genome coverage. We used vector PCLD04541, which allows direct plant transformation by BACs. The average insert size is 94 kb. Clones were stable in Escherichia coli and Agrobacterium tumefaciens.

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In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example. (C) 2002 Elsevier Science (USA).

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In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.