Stabilization of multi-stranded nucleic acid structures using 3'-S-phosphorothiolate linkages

3 '-S-Phosphorothiolate linkages incorporated into an oligodeoxynucleotide have been shown to stabilise duplex formation with a complementary RNA strand, but destabilise a duplex formed with a complementary DNA strand. The four-stranded i-motif structure is also stabilised this modification.

The Genomic Threading Database: a comprehensive resource for structural annotations of the genomes from key organisms

Currently, the Genomic Threading Database (GTD) contains structural assignments for the proteins encoded within the genomes of nine eukaryotes and 101 prokaryotes. Structural annotations are carried out using a modified version of GenTHREADER, a reliable fold recognition method. The Gen THREADER annotation jobs are distributed across multiple clusters of processors using grid technology and the predictions are deposited in a relational database accessible via a web interface at http://bioinf.cs.ucl.ac.uk/GTD. Using this system, up to 84% of proteins encoded within a genome can be confidently assigned to known folds with 72% of the residues aligned. On average in the GTD, 64% of proteins encoded within a genome are confidently assigned to known folds and 58% of the residues are aligned to structures.

The Genomic Threading Database

The Genomic Threading Database currently contains structural annotations for the genomes of over 100 recently sequenced organisms. Annotations are carried out by using our modified GenTHREADER software and through implementing grid technology.

Improvement of the GenTHREADER method for genomic fold recognition

Motivation: In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins. Results: The improvements made to GenTHREADER increase the number of remote homologues that can be detected with a low error rate, implying higher reliability of score, whilst also increasing the quality of the models produced. We find that up to five times as many true positives can be detected with low error rate per query. Total MaxSub score is doubled at low false positive rates using the improved method.

Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water

We present a novel kinetic multi-layer model for gas-particle interactions in aerosols and clouds (KMGAP) that treats explicitly all steps of mass transport and chemical reaction of semi-volatile species partitioning between gas phase, particle surface and particle bulk. KMGAP is based on the PRA model framework (P¨oschl-Rudich- Ammann, 2007), and it includes gas phase diffusion, reversible adsorption, surface reactions, bulk diffusion and reaction, as well as condensation, evaporation and heat transfer. The size change of atmospheric particles and the temporal evolution and spatial profile of the concentration of individual chemical species can be modeled along with gas uptake and accommodation coefficients. Depending on the complexity of the investigated system and the computational constraints, unlimited numbers of semi-volatile species, chemical reactions, and physical processes can be treated, and the model shall help to bridge gaps in the understanding and quantification of multiphase chemistry and microphysics in atmospheric aerosols and clouds. In this study we demonstrate how KM-GAP can be used to analyze, interpret and design experimental investigations of changes in particle size and chemical composition in response to condensation, evaporation, and chemical reaction. For the condensational growth of water droplets, our kinetic model results provide a direct link between laboratory observations and molecular dynamic simulations, confirming that the accommodation coefficient of water at 270K is close to unity (Winkler et al., 2006). Literature data on the evaporation of dioctyl phthalate as a function of particle size and time can be reproduced, and the model results suggest that changes in the experimental conditions like aerosol particle concentration and chamber geometry may influence the evaporation kinetics and can be optimized for efficient probing of specific physical effects and parameters. With regard to oxidative aging of organic aerosol particles, we illustrate how the formation and evaporation of volatile reaction products like nonanal can cause a decrease in the size of oleic acid particles exposed to ozone.

In vitro evaluation of single- and multi-strain probiotics: inter-species inhibition between probiotic strains, and inhibition of pathogens

Many studies comparing the effects of single- and multi-strain probiotics on pathogen inhibition compare treatments with different concentrations. They also do not examine the possibility of inhibition between probiotic strains with a mixture. We tested the ability of 14 single-species probiotics to inhibit each other using a cross-streak assay, and agar spot test. We then tested the ability of 15 single-species probiotics and 5 probiotic mixtures to inhibit C. difficile, E. coli and S. Typhimurium, using the agar spot test. Testing was done with mixtures created in two ways: one group contained component species incubated together, the other group of mixtures was made using component species which had been incubated separately, equalised to equal optical density, and then mixed in equal volumes. Inhibition was observed for all combinations of probiotics, suggesting that when used as such there may be inhibition between probiotics, potentially reducing efficacy of the mixture. Significant inter-species variation was seen against each pathogen. When single species were tested against mixtures, the multi-species preparations displayed significantly (p<0.05 or less) greater inhibition of pathogens in 12 out of 24 cases. Despite evidence that probiotic species will inhibit each other when incubated together in vitro, in many cases a probiotic mixture was more effective at inhibiting pathogens than its component species when tested at approximately equal concentrations of biomass. This suggests that using a probiotic mixture might be more effective at reducing gastrointestinal infections, and that creating a mixture using species with different effects against different pathogens may have a broader spectrum of action that a single provided by a single strain.

Sources of multi-decadal variability in Arctic sea ice extent

The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability.

Aligning business and IT from multi-level learning perspectives

Business and IT alignment is increasingly acknowledged as a key for organisational performance. However, alignment research lack to mechanisms that enable for on-going process with multi-level effects. Multi-level learning allows on-going effectiveness through development of the organisation and improved quality of business and IT strategies. In particular, exploration and exploitation enable effective process of alignment across dynamic multi-level of learning. Hence, this paper proposes a conceptual framework that links multi-level learning and business-IT strategy through the concept of exploration and exploitation, which considers short-term and long-term alignment together to address the challenges of strategic alignment faced in sustaining organisational performance.