Identifying oil species in oil mixtures

Detection of adulteration of non-processed vegetable oil with lesser value seed oils (classic example is hazelnut in virgin olive oil) has been in the centre of scientific attention for many years and several chemical methods were proposed. The recent EC Regulation 1169/2011, however, introduces necessity for different analytical method in a more complicated matrix. From the end of 2014, food businesses required to declare the composition of the refined oil mixture in the food product label. This creates a gap since there is no analytical method currently available to perform such analysis. In the first phase the work focused on 100% oil blends of various oil species of palm oil (and derivatives), sunflower and rapeseed oil before expanding to foodstuffs. Chromatographic methods remain highly relevant although suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques based on machine learning algorithms, however, when applied in FTIR, Raman spectroscopic data have a strong potential in tackling the problem.

Coherence and discontinuity in the scaling of species' distribution patterns

The spatial distribution of a species can be characterized at many different spatial scales, from fine-scale measures of local population density to coarse-scale geographical-range structure. Previous studies have shown a degree of correlation in species' distribution patterns across narrow ranges of scales, making it possible to predict fine-scale properties from coarser-scale distributions. To test the limits of such extrapolation, we have compiled distributional information on 16 species of British plants, at scales ranging across six orders of magnitude in linear resolution (1 in to 100 km). As expected, the correlation between patterns at different spatial scales tends to degrade as the scales become more widely separated. There is, however, an abrupt breakdown in cross-scale correlations across intermediate (ca. 0.5 km) scales, suggesting that local and regional patterns are influenced by essentially non-overlapping sets of processes. The scaling discontinuity may also reflect characteristic scales of human land use in Britain, suggesting a novel method for analysing the 'footprint' of humanity on a landscape.

Phenotypic characterization of an international Pseudomonas aeruginosa reference panel: strains of cystic fibrosis (CF) origin show less in vivo virulence than non-CF strains

Pseudomonas aeruginosa causes chronic lung infections in people with cystic fibrosis (CF) and acute opportunistic infections in people without CF. Forty two P. aeruginosa strains from a range of clinical and environmental sources were collated into a single reference strain panel to harmonise research on this diverse opportunistic pathogen. To facilitate further harmonized and comparable research on P. aeruginosa, we characterised the panel strains for growth rates, motility, virulence in the Galleria mellonella infection model, pyocyanin and alginate production, mucoid phenotype, lipopolysaccharide (LPS) pattern, biofilm formation, urease activity, antimicrobial and phage susceptibilities. Phenotypic diversity across the P. aeruginosa panel was apparent for all phenotypes examined agreeing with the marked variability seen in this species. However, except for growth rate, the phenotypic diversity among strains from CF versus non-CF sources was comparable. CF strains were less virulent in the G. mellonella model than non-CF strains (p=0.037). Transmissible CF strains generally lacked O antigen, produced less pyocyanin, and had low virulence in G. mellonella. Further, in the three sets of sequential CF strains, virulence, O-antigen expression and pyocyanin production were higher in the earlier isolate compared to the isolate obtained later in infection. Overall, full phenotypic characterization of the defined panel of P. aeruginosa strains increases our understanding of the virulence and pathogenesis of P. aeruginosa and may provide a valuable resource for the testing of novel therapies against this problematic pathogen.

Plasmid DNA damage following exposure to atmospheric pressure non-thermal plasma: kinetics and influence of oxygen admixture

The nature and kinetics of plasmid DNA damage after DNA exposure to a kHz-driven atmospheric pressure nonthermal plasma jet has been investigated. Both single-strand break (SSB) and double-strand break (DSB) processes are reported here. While SSB had a higher rate constant, DSB is recognized to be more significant in living systems, often resulting in loss of viability. In a helium-operated plasma jet, adding oxygen to the feed gas resulted in higher rates of DNA DSB, which increased linearly with increasing oxygen content, up to an optimum level of 0.75% oxygen, after which the DSB rate decreased slightly, indicating an essential role for reactive oxygen species in the rapid degradation of DNA.

The reliability of R50 as a measure of vulnerability of food webs to sequential species deletions

Recent studies predict elevated and accelerating rates of species extinctions over the 21st century, due to climate change and habitat loss. Considering that such primary species loss may initiate cascades of secondary extinctions and push systems towards critical tipping points, we urgently need to increase our understanding of if certain sequences of species extinctions can be expected to be more devastating than others Most theoretical studies addressing this question have used a topological (non-dynamical) approach to analyse the probability that food webs will collapse, below a fixed threshold value in species richness, when subjected to different sequences of species loss. Typically, these studies have neither considered the possibility of dynamical responses of species, nor that conclusions may depend on the value of the collapse threshold. Here we analyse how sensitive conclusions on the importance of different species are to the threshold value of food web collapse. Using dynamical simulations, where we expose model food webs to a range of extinction sequences, we evaluate the reliability of the most frequently used index, R<inf>50</inf>, as a measure of food web robustness. In general, we find that R<inf>50</inf> is a reliable measure and that identification of destructive deletion sequences is fairly robust, within a moderate range of collapse thresholds. At the same time, however, focusing on R<inf>50</inf> only hides a lot of interesting information on the disassembly process and can, in some cases, lead to incorrect conclusions on the relative importance of species in food webs.

An invasive-native mammalian species replacement process captured by camera trap survey random encounter models

Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.