Gene transfer and expression of a non-viral polycation-based vector in CD4(+) cells

CD4-selective targeting of an antibody-polycation-DNA complex was investigated The complex was synthesized with the anti-CD4 monoclonal antibody B-F5, polylysine(268) (pLL) and either the pGL3 control vector containing the luciferase reporter gene or the pGeneGrip vector containing the green fluorescent protein (GFP) gene. B-F5-pLL-DNA complexes inhibited the binding of I-125-B-F5 to CD4(+) Jurkat cells, while complexes synthesised either without B-F5 or using a non-specific mouse IgG1 antibody had little or no effect Expression of the luciferase reporter gene was achieved in Jurkat cells using the B-F5-pLL-pGL3 complex and was enhanced in the presence of PMA. Negligible luciferase activity was defected with the non-specific antibody complex in Jurkat cells or with the B-F5-pLL-pGL3 complex in the CD4(-) K-562 cells. Using complexes synthesised with the pGeneGrip vector, the transfection efficiency in Jurkat and K-562 cells was examined using confocal microscopy. More than 95% of Jurkat cells expressed GFP and the level of this expression was markedly enhanced by PMA. Negligible GFP expression was seen in K-562 cells or when B-F5 was replaced by a nonspecific antibody. Using flow cytometry, fluorescein-labelled complex showed specific targeting to CD4(+) cells in a mixed cell population from human peripheral blood. These studies demonstrate the selective transfection of CD4(+) T-lymphoid cells using a polycation-based gene delivery system. The complex may provide a means of delivering anti-HIV gene therapies to CD4(+) cells in vivo.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

Structured modeling of recombinant protein production in batch and fed-batch culture of baculovirus-infected insect cells

The infection of insect cells with baculovirus was described in a mathematical model as a part of the structured dynamic model describing whole animal cell metabolism. The model presented here is capable of simulating cell population dynamics, the concentrations of extracellular and intracellular viral components, and the heterologous product titers. The model describes the whole processes of viral infection and the effect of the infection on the host cell metabolism. Dynamic simulation of the model in batch and fed-batch mode gave good agreement between model predictions and experimental data. Optimum conditions for insect cell culture and viral infection in batch and fed-batch culture were studied using the model.

Lentiviral vector-mediated tyro sinase-related protein 2 gene transfer to dendritic cells for the therapy of melanoma

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.

Three-dimensional electrical impedance, tomography: A topology optimization approach

Electrical impedance tomography is a technique to estimate the impedance distribution within a domain, based on measurements on its boundary. In other words, given the mathematical model of the domain, its geometry and boundary conditions, a nonlinear inverse problem of estimating the electric impedance distribution can be solved. Several impedance estimation algorithms have been proposed to solve this problem. In this paper, we present a three-dimensional algorithm, based on the topology optimization method, as an alternative. A sequence of linear programming problems, allowing for constraints, is solved utilizing this method. In each iteration, the finite element method provides the electric potential field within the model of the domain. An electrode model is also proposed (thus, increasing the accuracy of the finite element results). The algorithm is tested using numerically simulated data and also experimental data, and absolute resistivity values are obtained. These results, corresponding to phantoms with two different conductive materials, exhibit relatively well-defined boundaries between them, and show that this is a practical and potentially useful technique to be applied to monitor lung aeration, including the possibility of imaging a pneumothorax.

Endostatin- and interleukin-2-expressing retroviral bicistronic vector for gene therapy of metastatic renal cell carcinoma

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.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Transfer of an autonomously replicating vector between vegetatively incompatible biotypes of Colletotrichum gloeosporioides

Previous research has indicated that biotypes A and B of Colletotrichum gloeosporioides that infect Stylosanthes spp. in Australia are asexual and vegetatively incompatible. Selectable marker genes conferring resistance either to hygromycin or phleomycin were introduced into isolates of these biotypes. Vectors conferring resistance to hygromycin and carrying telomeric sequences from Fusarium oxysporum replicated autonomously in C. gloeosporioides and gave frequencies of transformation 100-times higher than vectors that integrated into the genome. Monoconidial colonies resistant to both antibiotics were recovered when hygromycin-resistant biotype-A transformants carrying an autonomously replicating vector were paired in culture with a phleomycin-resistant biotype-B transformant carrying integrative vector sequences. Molecular analysis of double antibiotic-resistant progeny indicated that they contained the autonomous vector in a biotype-B genetic background, Results indicate that transfer of the autonomous vector had occurred from biotype A to biotype B, demonstrating the potential for transfer of genetic information between these biotypes.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.