Reduced phospholipase A2 activity is not accompanied by reduced arachidonic acid release

Arachidonic acid release in cells highly over expressing cytosolic phospholipase A2 has been attributed to mitogen-activated protein kinase phosphorylation of cytosolic phospholipase A2 on serine-505. To investigate the role of cytosolic phospholipase A2 in cellular physiology, we attempted to inhibit cytosolic phospholipase A2 in the intact cell employing an antisense RNA strategy. Swiss 3T3 cells were stably transfected with an antisense cytosolic phospholipase A2 expression vector. A clone of cells with reduced immunodetectable cytosolic phospholipase A2, compared to a vector transfected cell line, was identified by Western blotting and a corresponding decrease in phospholipase A2 activity was confirmed by enzymatic assay in cell free extracts. However, arachidonic acid release from intact cells in response to agonists was not different between antisense and control cell lines. Thus, arachidonic acid release in intact cells with decreased cytosolic phospholipase A2 activity is likely to be modulated by rate limiting factors that are extrinsic to cytosolic phospholipase A2.

Finite element modelling of the formation of pre-load damage in cement mantles of orthopaedic joint replacements

Finite element modeling of the formation of pre-loaded damage in cement mantles of orthopaedic joint replacements was presented. The existence of cracking suggested a high level of residual stress. The direction of maximum principal stress vectors corresponded well with the observed crack orientation. Results suggested that cracking depends upon a combination of residual stress, porosity and temperature rise during polymerization.

Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets

Motivation: To date, Gene Set Analysis (GSA) approaches primarily focus on identifying differentially expressed gene sets (pathways). Methods for identifying differentially coexpressed pathways also exist but are mostly based on aggregated pairwise correlations, or other pairwise measures of coexpression. Instead, we propose Gene Sets Net Correlations Analysis (GSNCA), a multivariate differential coexpression test that accounts for the complete correlation structure between genes.

Results: In GSNCA, weight factors are assigned to genes in proportion to the genes' cross-correlations (intergene correlations). The problem of finding the weight vectors is formulated as an eigenvector problem with a unique solution. GSNCA tests the null hypothesis that for a gene set there is no difference in the weight vectors of the genes between two conditions. In simulation studies and the analyses of experimental data, we demonstrate that GSNCA, indeed, captures changes in the structure of genes' cross-correlations rather than differences in the averaged pairwise correlations. Thus, GSNCA infers differences in coexpression networks, however, bypassing method-dependent steps of network inference. As an additional result from GSNCA, we define hub genes as genes with the largest weights and show that these genes correspond frequently to major and specific pathway regulators, as well as to genes that are most affected by the biological difference between two conditions. In summary, GSNCA is a new approach for the analysis of differentially coexpressed pathways that also evaluates the importance of the genes in the pathways, thus providing unique information that may result in the generation of novel biological hypotheses.

The influence of the magnetic field on running penumbral waves in the solar chromosphere

We use images of high spatial and temporal resolution, obtained using both ground- and space-based instrumentation, to investigate the role magnetic field inclination angles play in the propagation characteristics of running penumbral waves in the solar chromosphere. Analysis of a near-circular sunspot, close to the center of the solar disk, reveals a smooth rise in oscillatory period as a function of distance from the umbral barycenter. However, in one directional quadrant, corresponding to the north direction, a pronounced kink in the period-distance diagram is found. Utilizing a combination of the inversion of magnetic Stokes vectors and force-free field extrapolations, we attribute this behavior to the cut-off frequency imposed by the magnetic field geometry in this location. A rapid, localized inclination of the magnetic field lines in the north direction results in a faster increase in the dominant periodicity due to an accelerated reduction in the cut-off frequency. For the first time, we reveal how the spatial distribution of dominant wave periods, obtained with one of the highest resolution solar instruments currently available, directly reflects the magnetic geometry of the underlying sunspot, thus opening up a wealth of possibilities in future magnetohydrodynamic seismology studies. In addition, the intrinsic relationships we find between the underlying magnetic field geometries connecting the photosphere to the chromosphere, and the characteristics of running penumbral waves observed in the upper chromosphere, directly supports the interpretation that running penumbral wave phenomena are the chromospheric signature of upwardly propagating magneto-acoustic waves generated in the photosphere.

Putrescine Reduces Antibiotic-Induced Oxidative Stress as a Mechanism of Modulation of Antibiotic Resistance in Burkholderia cenocepacia

Communication of antibiotic resistance among bacteria via small molecules is implicated in transient reduction of bacterial susceptibility to antibiotics, which could lead to therapeutic failures aggravating the problem of antibiotic resistance. Released putrescine from the extremely antibiotic resistant bacterium Burkholderia cenocepacia protects less resistant cells from different species against the antimicrobial peptide polymyxin B (PmB). Exposure of B. cenocepacia to sub-lethal concentrations of PmB and other bactericidal antibiotics induce reactive oxygen species (ROS) production and expression of the oxidative stress response regulator OxyR. We evaluated whether putrescine alleviates antibiotic-induced oxidative stress. The accumulation of intracellular ROS such as superoxide ion and hydrogen peroxide was assessed fluorometrically with dichlorofluorescein diacetate, while the expression of OxyR and putrescine synthesis enzymes was determined in luciferase assays using chromosomal promoter-lux reporter system fusions. We evaluated wild type and isogenic deletion mutant strains with defects in putrescine biosynthesis after exposure to sub-lethal concentrations of PmB and other bactericidal antibiotics. Exogenous putrescine protected against oxidative stress induced by PmB and other antibiotics, whereas reduced putrescine synthesis resulted in increased ROS generation, and a parallel increased sensitivity to PmB. Of the 3 B. cenocepacia putrescine synthesizing enzymes, PmB induced only BCAL2641, an ornithine decarboxylase. This study exposes BCAL2641 as a critical component of the putrescine-mediated communication of antibiotic resistance, and as a plausible target for designing inhibitors that would block the communication of such resistance among different bacteria, ultimately reducing the window of therapeutic failure in treating bacterial infections.

On transition rates in surface hopping

Trajectory surface hopping (TSH) is one of the most widely used quantum-classical algorithms for nonadiabatic molecular dynamics. Despite its empirical effectiveness and popularity, a rigorous derivation of TSH as the classical limit of a combined quantum electron-nuclear dynamics is still missing. In this work, we aim to elucidate the theoretical basis for the widely used hopping rules. Naturally, we concentrate thereby on the formal aspects of the TSH. Using a Gaussian wave packet limit, we derive the transition rates governing the hopping process at a simple avoided level crossing. In this derivation, which gives insight into the physics underlying the hopping process, some essential features of the standard TSH algorithm are retrieved, namely (i) non-zero electronic transition rate ("hopping probability") at avoided crossings; (ii) rescaling of the nuclear velocities to conserve total energy; (iii) electronic transition rates linear in the nonadiabatic coupling vectors. The well-known Landau-Zener model is then used for illustration. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4770280]

Development of a method to quantify the DNA content in DNA- cationic peptide nanoparticles

Gene therapy has the potential to provide safe and targeted therapies for a variety of diseases. A range of intracellular gene delivery vehicles have been proposed for this purpose. Non-viral vectors are a particularly attractive option and among them cationic peptides have emerged as promising candidates. For the pharmaceutical formulation and application to clinical studies it is necessary to quantify the amount of pDNA condensed with the delivery system. There is a severe deficiency in this area, thus far no methods have been reported specifically for pDNA condensed with cationic peptide to form nanoparticles. The current study seeks to address this and describes the evaluation of a range of disruption agents to extract DNA from nanoparticles formed by condensation with cationic fusogenic peptides RALA and KALA. Only proteinase K exhibited efficient and reproducible results and compatibility with the PicoGreen reagent based quantification assay. Thus we report for the first time a simple and reliable method that can quantify the pDNA content in pDNA cationic peptide nanoparticles.

Synergistic effects on gene delivery - co-formulation of small disulfide-linked dendritic polycations with Lipofectamine 2000 (TM)

This paper describes the application of gene delivery vectors based on connecting together two well-defined low-generation poly(L-lysine) (PLL) dendrons using a disulfide-containing linker unit. We report that the transfection ability of these vectors in their own right is relatively low, because the low-generation number limits the endosomal buffering capacity. Importantly, however, we demonstrate that when applied in combination with Lipofectamine 2000 (TM), a vector from the cationic lipid family, these small cationic additives significantly enhance the levels of gene delivery (up to four-fold). Notably, the cationic additives have no effect on the levels of transfection observed with a cationic polymer, such as DEAE dextran. We therefore argue that the synergistic effects observed with Lipofectamine 2000 (TM) arise as a result of combining the delivery advantages of two different classes of vector within a single formulation, with our dendritic additives providing a degree of pH buffering within the endosome. As such, the data we present indicate that small dendritic structures, although previously largely overlooked for gene delivery owing to their inability to transfect in their own right, may actually be useful well-defined additives to well-established vector systems in order to enhance the gene delivery payload.

Measurements of immune responses for establishing correlates of vaccine protection against HIV

Well-defined correlates of protective immunity are an essential component of rational vaccine development. Despite years of basic science and three HIV vaccine efficacy trials, correlates of immunological protection from HIV infection remain undefined. In December 2010, a meeting of scientists engaged in basic and translational work toward developing HIV-1 vaccines was convened. The goal of this meeting was to discuss current opportunities and optimal approaches for defining correlates of protection, both for ongoing and future HIV-1 vaccine candidates; specific efforts were made to engage young scientists. We discuss here the highlights from the meeting regarding the progress made and the way forward for a protective HIV-1 vaccine.

Towards Organic Electronic Materials for Electrically Stimulated Gene Delivery

The cell-specific delivery of polynucleic acids (e.g., DNA, RNA), gene therapy, has the potential to treat various diseases. In this chapter we discuss the use of organic electronic materials as non-viral gene delivery vectors and the great potential for electrochemically triggered gene delivery. We highlight some examples in this chapter based on fullerenes (bucky balls and carbon nanotubes), graphenes and electroactive polymers, particularly those that include experiments in vivo.

Biocompatibility of Calcium Phosphate Bone Cement with Optimised Mechanical Properties

The broad aim of this work was to investigate and optimise the properties of calcium phosphate bone cements (CPCs) for use in vertebroplasty to achieve effective primary fixation of spinal fractures. The incorporation of collagen, both bovine and from a marine sponge (Chondrosia reniformis), into a CPC was investigated. The biological properties of the CPC and collagen-CPC composites were assessed in vitro through the use of human bone marrow stromal cells. Cytotoxicity, proliferation and osteoblastic differentiation were evaluated using lactate dehydrogenase, PicoGreen and alkaline phosphatase activity assays respectively. The addition of both types of collagen resulted in an increase in cytotoxicity, albeit not to a clinically relevant level. Cellular proliferation after 1, 7 and 14 days was unchanged. The osteogenic potential of the CPC was reduced through the addition of bovine collagen but remained unchanged in the case of the marine collagen. These findings, coupled with previous work showing that incorporation of marine collagen in this way can improve the physical properties of CPCs, suggest that such a composite may offer an alternative to CPCs in applications where low setting times and higher mechanical stability are important.

Space-Constrained Massive MIMO: Hitting the Wall of Favorable Propagation

The recent development of the massive multiple-input multiple-output (MIMO) paradigm, has been extensively based on the pursuit of favorable propagation: in the asymptotic limit, the channel vectors become nearly orthogonal and interuser interference tends to zero [1]. In this context, previous studies
have considered fixed inter-antenna distance, which implies an increasing array aperture as the number of elements increases. Here, we focus on a practical, space-constrained topology, where an increase in the number of antenna elements in a fixed total space imposes an inversely proportional decrease in the inter-antenna distance. Our analysis shows that, contrary to existing studies, inter-user interference does not vanish in the massive MIMO regime, thereby creating a saturation effect on the achievable rate.

Deriving meteorological variables across Africa for the study and control of vector-borne disease:a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) onboard the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study anti control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Development of an app to support learning in A-level maths

This project involved producing an app for smart devices to enable modernised learning for A-level maths students. Research in a stakeholder school showed that 94% of pupils surveyed within the upper-secondary level owned a smartphone and most owned a tablet also, emphasising the opportunity for using apps to support learning. The app was developed using iBuildApp, an online app-creation programme which requires no programming. Past exam questions and solutions, notes and video tutorials were included and the topic was vectors, identified by teachers as problematic. Pupils generally found the app easy to use and wanted further development. The videos were popular despite this not ranking highly as a preferred method of revision previously. Teachers were happy for pupils to use the app to supplement their learning, both in the classroom and outside.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.