Using surveys of Affymetrix GeneChips to study antisense expression.

We have used large surveys of Affymetrix GeneChip data in the public domain to conduct a study of antisense expression across diverse conditions. We derive correlations between groups of probes which map uniquely to the same exon in the antisense direction. When there are no probes assigned to an exon in the sense direction we find that many of the antisense groups fail to detect a coherent block of transcription. We find that only a minority of these groups contain coherent blocks of antisense expression suggesting transcription. We also derive correlations between groups of probes which map uniquely to the same exon in both sense and antisense direction. In some of these cases the locations of sense probes overlap with the antisense probes, and the sense and antisense probe intensities are correlated with each other. This configuration suggests the existence of a Natural Antisense Transcript (NAT) pair. We find the majority of such NAT pairs detected by GeneChips are formed by a transcript of an established gene and either an EST or an mRNA. In order to determine the exact antisense regulatory mechanism indicated by the correlation of sense probes with antisense probes, a further investigation is necessary for every particular case of interest. However, the analysis of microarray data has proved to be a good method to reconfirm known NATs, discover new ones, as well as to notice possible problems in the annotation of antisense transcripts

Identifying the impact of G-quadruplexes on Affymetrix 3' arrays using cloud computing.

A tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips. In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3' arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google. We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3' arrays

Exploring carbon nanotubes / BaTiO3 / Fe3O4 Nanocomposites as microwave absorbers

This is the final version of the article. Available from EM Academy via the link in this record.Open access journalWe report the modelling and characterization of microwave absorbing materials specially designed for 26–37 GHz frequency range (Ka-band). Composite materials based on carbon nanotubes/BaTiO3/Fe3O4 in a phosphate ceramic matrix were produced, and their electromagnetic response was investigated. Both theoretical and experimental results demonstrate that this material can absorb up to 100% of the power of an incident plane wave at a normal incidence angle. The physics underlying such absorption level is discussed in terms of refractive index of the material.This work was supported in part by FP7-PEOPLE-2013-IRSES-610875 NAmiceMC, FP7 Twinning Grant Inconet EaP 004. P. Kuzhir is thankful for support by Tomsk State University Competitiveness Improvement Program. Lab-STICC is UMR CNRS 6285

Comparison between Suitable Priors for Additive Bayesian Networks

Additive Bayesian networks are types of graphical models that extend the usual Bayesian generalized linear model to multiple dependent variables through the factorisation of the joint probability distribution of the underlying variables. When fitting an ABN model, the choice of the prior of the parameters is of crucial importance. If an inadequate prior - like a too weakly informative one - is used, data separation and data sparsity lead to issues in the model selection process. In this work a simulation study between two weakly and a strongly informative priors is presented. As weakly informative prior we use a zero mean Gaussian prior with a large variance, currently implemented in the R-package abn. The second prior belongs to the Student's t-distribution, specifically designed for logistic regressions and, finally, the strongly informative prior is again Gaussian with mean equal to true parameter value and a small variance. We compare the impact of these priors on the accuracy of the learned additive Bayesian network in function of different parameters. We create a simulation study to illustrate Lindley's paradox based on the prior choice. We then conclude by highlighting the good performance of the informative Student's t-prior and the limited impact of the Lindley's paradox. Finally, suggestions for further developments are provided.Comment: 8 pages, 4 figure

Exploring the adoption of precision agricultural technologies: a cross regional study of EU farmers

Precision agricultural technologies (PATs) allow more detailed management of in-field variability. Policy and advisory communities have championed PATs as a route to preserving natural capital whilst increasing productivity from agricultural land. A range of PATs are currently available for the agricultural producer but uptake varies by the type of technology and region. Whereas most studies on uptake have focused on US or Australia we empirically examine uptake of machine guidance (MG) and variable rate nitrogen technologies (VRNT) within European farming systems. Using primary information from 971 arable crop growers across five countries: Belgium, Germany, Greece, the Netherlands and the UK, a multilevel random intercept regression estimated a) the differences between adoption and non-adoption and b) the differences between VRNT and MG adoption. We find, aside from size and income differences, which reflect the economic cost barrier to adoption, an attitudinal difference, in terms of optimism towards the technology's economic return leading to more probability of uptake. Moreover innovative and information seeking behaviour also proved significant when upgrading from machine guidance to variable rate technologies. Subsidy and taxation were considered positive drivers of uptake within the community. However, results suggest that more indirect interventions, such as informational support to counteract industry bias, and demonstration to prove the viability of economic return may be effective at meeting land manager and policy expectations towards PATs

Heterostructures produced from nanosheet-based inks.

The new paradigm of heterostructures based on two-dimensional (2D) atomic crystals has already led to the observation of exciting physical phenomena and creation of novel devices. The possibility of combining layers of different 2D materials in one stack allows unprecedented control over the electronic and optical properties of the resulting material. Still, the current method of mechanical transfer of individual 2D crystals, though allowing exceptional control over the quality of such structures and interfaces, is not scalable. Here we show that such heterostructures can be assembled from chemically exfoliated 2D crystals, allowing for low-cost and scalable methods to be used in device fabrication.This work was supported by The Royal Society, U.S. Army, European Science Foundation (ESF) under the EUROCORES Programme EuroGRAPHENE (GOSPEL), European Research Council, and EC under the Graphene Flagship (contract no. CNECT-ICT-604391). Y.-J.K.’s work was supported by the Global Research Laboratory (GRL) Program (2011-0021972) of the Ministry of Education, Science and Technology, Korea. F.W. acknowledges support from the Royal Academy of Engineering; A.F. is a FRS-FNRS Research Fellow

Influence of the Alkali-promoted phase transformation in monazite for selective recovery of rare-oxides using deep eutectic solvents

This is the final version. Available on open access from Elsevier via the DOI in this recordThe physico-chemical changes occurring during the high-temperature phase transformation of monazite in the presence of Na2CO3 at 1000 °C for 2 h duration at monazite: Na2CO3 ratios between 1.0 and 5.0, were investigated. The formation of sodium lanthanide phosphates was prevalent above a monazite:alkali ratio of 2, however, below this ratio, the dephosphorization of monazite as Na3PO4 and solid solutions occur offering unique selectivity for rare-earth oxide separation from the mineral matrix. Cyclic voltammetry of pure CeO2, La2O3, Nd2O3, and PrO2/Pr2O3 was carried out in the deep eutectic solvent Ethaline (1:2 mixture of choline chloride and ethylene glycol) proving the electrochemical activity of these oxides. Electrodissolution of pure oxides and water-leached monazite after high-temperature reaction with a ratio of 1:1 was carried out in a 0.1 mol/L glucose solution in Ethaline showing a preferential solubility of 23.85% for pure Nd2O3. In contrast, pure oxides of CeO2, La2O3 and PrO2/Pr2O3 were found to be insoluble. We also observed that electrodissolution of the water leached monazite was not possible because of the inert behaviour of solid solutions. Avoiding cerium oxidation during the high-temperature process will lead to a method for further selectivity for rare-earth oxide processing using staged electro-chemical winning of oxides.Natural Environment Research Council (NERC)Ministry of Science, Innovation and University of Spai

Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth

Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations