Optimization of the piggyBac Transposon Using mRNA and Insulators: Toward a More Reliable Gene Delivery System.

Integrating and expressing stably a transgene into the cellular genome remain major challenges for gene-based therapies and for bioproduction purposes. While transposon vectors mediate efficient transgene integration, expression may be limited by epigenetic silencing, and persistent transposase expression may mediate multiple transposition cycles. Here, we evaluated the delivery of the piggyBac transposase messenger RNA combined with genetically insulated transposons to isolate the transgene from neighboring regulatory elements and stabilize expression. A comparison of piggyBac transposase expression from messenger RNA and DNA vectors was carried out in terms of expression levels, transposition efficiency, transgene expression and genotoxic effects, in order to calibrate and secure the transposition-based delivery system. Messenger RNA reduced the persistence of the transposase to a narrow window, thus decreasing side effects such as superfluous genomic DNA cleavage. Both the CTF/NF1 and the D4Z4 insulators were found to mediate more efficient expression from a few transposition events. We conclude that the use of engineered piggyBac transposase mRNA and insulated transposons offer promising ways of improving the quality of the integration process and sustaining the expression of transposon vectors.

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

Combination of enteral and parenteral nutrition in intensive care patients: A new concept of optimization

Undernutrition is a widespread problem in intensive care unit and is associated with a worse clinical outcome. A state of negative energy balance increases stress catabolism and is associated with increased morbidity and mortality in ICU patients. Undernutrition-related increased morbidity is correlated with an increase in the length of hospital stay and health care costs. Enteral nutrition is the recommended feeding route in critically ill patients, but it is often insufficient to cover the nutritional needs. The initiation of supplemental parenteral nutrition, when enteral nutrition is insufficient, could optimize the nutritional therapy by preventing the onset of early energy deficiency, and thus, could allow to reduce morbidity, length of stay and costs, shorten recovery period and, finally, improve quality of life. (C) 2009 Elsevier Masson SAS. All rights reserved.

Potential evidence of parasite avoidance in an avian malarial vector

Epidemiological studies of malaria or other vector-transmitted diseases often consider vectors as passive actors in the complex life cycle of the parasites, assuming that vector populations are homogeneous and vertebrate hosts are equally susceptible to being infected during their lifetime. However, some studies based on both human and rodent malaria systems found that mosquito vectors preferentially selected infected vertebrate hosts. This subject has been scarcely investigated in avian malaria models and even less in wild animals using natural host-parasite associations. We investigated whether the malaria infection status of wild great tits, Parus major, played a role in host selection by the mosquito vector Culex pipiens. Pairs of infected and uninfected birds were tested in a dual-choice olfactometer to assess their attractiveness to the mosquitoes. Plasmodium-infected birds attracted significantly fewer mosquitoes than the uninfected ones, which suggest that avian malaria parasites alter hosts' odours involved in vector orientation. Reaction time of the mosquitoes, that is, the time taken to select a host, and activation of mosquitoes, defined as the proportion of individuals flying towards one of the hosts, were not affected by the bird's infection status. The importance of these behavioural responses for the vector is discussed in light of recent advances in related or similar model systems.

Construction and Quantitative Evaluation of a Dual Specific Promoter System for Monitoring the Expression Status of Stra8 and c-kit Genes.

Applications of genetic constructs with multiple promoters, which are fused with reporter genes and simultaneous monitoring of various events in cells, have gained special attention in recent years. Lentiviral vectors, with their distinctive characteristics, have been considered to monitor the developmental changes of cells in vitro. In this study, we constructed a novel lentiviral vector (FUM-M), containing two germ cell-specific promoters (Stra8 and c-kit), fused with ZsGreen and DsRed2 reporter genes, and evaluated its efficiency in different cells following treatments with retinoic acid and DMSO. Several cell lines (P19, GC-1 spg and HEK293T) were transduced with this vector, and functional capabilities of the promoters were verified by flow cytometry and quantitative RT-PCR. Our results indicate that FUM-M shows dynamic behavior in the presence and absence of extrinsic factors. A correlation was also observed between the function of promoters, present in the lentiviral construct and the endogenous level of the Stra8 and c-kit mRNAs in the cells. In conclusion, we recommend this strategy, which needs further optimization of the constructs, as a beneficial and practical way to screen chemical inducers involved in cellular differentiation toward germ-like cells.

Lentiviral Vector Tropism In Degenerating Retinas

Introduction: In normal mice, lentiviral vector (LV) shows a great efficiency to infect the RPE cells, but transduces retinal neurons more efficiently during development. Here, we investigated the tropism of LV in the degenerating retina of mice, knowing that the retina structure changes during degeneration. We postulated that the viral transduction would be increased by the alteration of the interphotoreceptor matrix (IPM). We tested two different LV-pseudotypes using the VSVG and the Mokola envelopes. Methods: Subretinal injections were performed in wild-type (C57/Bl6) and rhodopsin knockout (Rho-/-) mice. We injected LV-VSVG-EFS-GFPII into 3.3-4.9 month old mice and LV-VSVG-Rho-GFP into 1-1.4 month old mice to target the photoreceptors (PR). LV-MOK-CMV-GFP was injected into 2.4-3.3 months old mice. We sacrificed the animals one week post injection, used immunohistochemistry to identify the transduced cells, and investigated the OLM integrity. Results: Using LV-VSVG-EFS-GFPII into 3.3-4.9 months mice, we observed significant retinal and RPE transduction in Rho-/- mice. However, the retinas showed transduction mainly at the injection's site. We mostly observed GFP+ cells having a Müller cell morphology. Using LV-MOK-CMV-GFP into 2.4-3.3 months mice, we evidenced the same pattern of viral infection, but with more Müller cells targeted by the virus. Using LV-VSVG-Rho-GFP into 1-1.4 month old mice, we don't note any difference between Rho-/- and wild-type mice for transduced cells. The IPM stained with ZO1 appears irregular into the 4.9 months old Rho-/- mice; for the youngest mice (Rho-/- and C57/Bl6), there is no modification of the IPM. Conclusion: The degeneration improves retinal cells transduction due to the alteration of the IPM in old Rho-/- mice. Müller cells seem (by morphological evidences) to be the principal cells expressing the transgene. The LV with Mokola envelope can transduce Müller cells in a degenerating retina with an intact IPM. In 1 month old mice, the degeneration doesn't enhance the transduction in rod PR probably because the IPM is not yet altered. The possibility to target photoreceptors at a later stage of the degeneration is under investigation.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

Low-dose multidetector computed tomography of the cervical spine: optimization of iterative reconstruction strength levels.

BACKGROUND: Iterative reconstruction (IR) techniques reduce image noise in multidetector computed tomography (MDCT) imaging. They can therefore be used to reduce radiation dose while maintaining diagnostic image quality nearly constant. However, CT manufacturers offer several strength levels of IR to choose from. PURPOSE: To determine the optimal strength level of IR in low-dose MDCT of the cervical spine. MATERIAL AND METHODS: Thirty consecutive patients investigated by low-dose cervical spine MDCT were prospectively studied. Raw data were reconstructed using filtered back-projection and sinogram-affirmed IR (SAFIRE, strength levels 1 to 5) techniques. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured at C3-C4 and C6-C7 levels. Two radiologists independently and blindly evaluated various anatomical structures (both dense and soft tissues) using a 4-point scale. They also rated the overall diagnostic image quality using a 10-point scale. RESULTS: As IR strength levels increased, image noise decreased linearly, while SNR and CNR both increased linearly at C3-C4 and C6-C7 levels (P < 0.001). For the intervertebral discs, the content of neural foramina and dural sac, and for the ligaments, subjective image quality scores increased linearly with increasing IR strength level (P ≤ 0.03). Conversely, for the soft tissues and trabecular bone, the scores decreased linearly with increasing IR strength level (P < 0.001). Finally, the overall diagnostic image quality scores increased linearly with increasing IR strength level (P < 0.001). CONCLUSION: The optimal strength level of IR in low-dose cervical spine MDCT depends on the anatomical structure to be analyzed. For the intervertebral discs and the content of neural foramina, high strength levels of IR are recommended.

Fitness, inclusive fitness, and optimization

Individual-as-maximizing agent analogies result in a simple understanding of the functioning of the biological world. Identifying the conditions under which individuals can be regarded as fitness maximizing agents is thus of considerable interest to biologists. Here, we compare different concepts of fitness maximization, and discuss within a single framework the relationship between Hamilton's (J Theor Biol 7: 1-16, 1964) model of social interactions, Grafen's (J Evol Biol 20: 1243-1254, 2007a) formal Darwinism project, and the idea of evolutionary stable strategies. We distinguish cases where phenotypic effects are additive separable or not, the latter not being covered by Grafen's analysis. In both cases it is possible to define a maximand, in the form of an objective function phi(z), whose argument is the phenotype of an individual and whose derivative is proportional to Hamilton's inclusive fitness effect. However, this maximand can be identified with the expression for fecundity or fitness only in the case of additive separable phenotypic effects, making individual-as-maximizing agent analogies unattractive (although formally correct) under general situations of social interactions. We also feel that there is an inconsistency in Grafen's characterization of the solution of his maximization program by use of inclusive fitness arguments. His results are in conflict with those on evolutionary stable strategies obtained by applying inclusive fitness theory, and can be repaired only by changing the definition of the problem.

Development of a T Cell Receptor Targeting an HLA-A*0201 Restricted Epitope from the Cancer-Testis Antigen SSX2 for Adoptive Immunotherapy of Cancer.

The clinical success of adoptive immunotherapy of cancer relies on the selection of target antigens that are highly expressed in tumor cells but absent in essential normal tissues. A group of genes that encode the cancer/testis or cancer germline antigens have been proposed as ideal targets for immunotherapy due to their high expression in multiple cancer types and their restricted expression in immunoprivileged normal tissues. In the present work we report the isolation and characterization of human T cell receptors (TCRs) with specificity for synovial sarcoma X breakpoint 2 (SSX2), a cancer/testis antigen expressed in melanoma, prostate cancer, lymphoma, multiple myeloma and pancreatic cancer, among other tumors. We isolated seven HLA-A2 restricted T cell receptors from natural T cell clones derived from tumor-infiltrated lymph nodes of two SSX2-seropositive melanoma patients, and selected four TCRs for cloning into retroviral vectors. Peripheral blood lymphocytes (PBL) transduced with three of four SSX2 TCRs showed SSX241-49 (KASEKIFYV) peptide specific reactivity, tumor cell recognition and tetramer binding. One of these, TCR-5, exhibited tetramer binding in both CD4 and CD8 cells and was selected for further studies. Antigen-specific and HLA-A*0201-restricted interferon-γ release, cell lysis and lymphocyte proliferation was observed following culture of TCR engineered human PBL with relevant tumor cell lines. Codon optimization was found to increase TCR-5 expression in transduced T cells, and this construct has been selected for development of clinical grade viral vector producing cells. The tumor-specific pattern of expression of SSX2, along with the potent and selective activity of TCR-5, makes this TCR an attractive candidate for potential TCR gene therapy to treat multiple cancer histologies.

Impact of Pre-Existing Immunity on the Selection of Rare Adenovirus Vector Candidates: Implications for HIV Vaccine Development

Background: Adenovirus serotype 5 (Ad5) phase IIb vaccine trial (STEP) was prematurely stopped due to a lack of efficacy and two-fold higher incidence of HIV infection among Ad5 seropositive vaccine recipients. We have recently demonstrated that Ad5 immune complexes (Ad5 ICs)-mediated activation of the dendritic cell (DC)-T cell axis was associated with the enhancement of HIV infection in vitro. Although the direct role of Ad5 neutralizing antibodies (NAbs) in the increase of HIV susceptibility during the STEP trial is still under debate, vector-specific NAbs remain a major hurdle for vector-based gene therapies or vaccine strategies. To surmount this obstacle, vectors based on ''rare'' Ad serotypes including Ad6, Ad26, Ad36 and Ad41 were engineered.Methods: The present study aimed to determine whether Ad ICmediated DC maturation could be circumvented using these Advector candidates.Results: We found that all Ad vectors tested forming ICs with plasma containing serotype-specific NAbs had the capacity to 1) mature human DCs as monitored by the up-regulation of costimulatory molecules and the release of pro-inflammatory cytokines (TNF-a), via the stabilization of Ad capsid at endosomal but not lysosomal pH rendering Ad DNA/TLR9 interactions possible and 2) potentiate Ad-specific CD4 and CD8 T cell responses.Conclusion: In conclusion, despite a conserved DC maturation potential, the low prevalence of serotype-specific NAbs renders rare Ad vectors attractive for vaccine strategies.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.