Natural genetic variation in caesium (Cs) accumulation by Arabidopsis thaliana

Ingestion of caesium (Cs) radioisotopes poses a health risk to humans. Crop varieties that accumulate less Cs in their edible tissues may provide a useful countermeasure. This study was performed to determine whether quantitative genetics on a model plant (Arabidopsis thaliana) might inform such 'safe'-crop strategies. Arabidopsis accessions and recombinant inbred lines (RILs), from Landsberg erecta (Ler) x Cape Verdi Island (Cvi), Ler x Columbia (Col), and Niederzenz (Nd) x Col mapping populations, were grown on agar supplemented with subtoxic levels of Cs. Shoot Cs concentration varied up to three-fold, and shoot f. wt varied up to 25-fold within populations. The heritability of growth and Cs accumulation traits ranged from 0.06 to 0.28. Four quantitative trait loci (QTL) accounted for > 80 of the genetic contribution to the total phenotypic variation in shoot Cs concentration in the Ler x Col population. QTL identified in this study, in particular, QTL co-localizing to the top and bottom regions of Chromosomes I and V in two different mapping populations, are amenable to positional cloning and, through collinearity, may inform selection or breeding strategies for the development of 'safe' crops.

O6-carboxymethylguanine DNA adduct formation and lipid peroxidation upon in vitro gastrointestinal digestion of haem-rich meat

Scope Epidemiological and clinical studies have demonstrated that the consumption of red haem-rich meat may contribute to the risk of colorectal cancer. Two hypotheses have been put forward to explain this causal relationship, i.e. N-nitroso compound (NOC) formation and lipid peroxidation (LPO). Methods and Results In this study, the NOC-derived DNA adduct O6-carboxymethylguanine (O6-CMG) and the LPO product malondialdehyde (MDA) were measured in individual in vitro gastrointestinal digestions of meat types varying in haem content (beef, pork, chicken). While MDA formation peaked during the in vitro small intestinal digestion, alkylation and concomitant DNA adduct formation was observed in seven (out of 15) individual colonic digestions using separate faecal inocula. From those, two haem-rich meat digestions demonstrated a significantly higher O6-CMG formation (p < 0.05). MDA concentrations proved to be positively correlated (p < 0.0004) with haem content of digested meat. The addition of myoglobin, a haem-containing protein, to the digestive simulation showed a dose–response association with O6-CMG (p = 0.004) and MDA (p = 0.008) formation. Conclusion The results suggest the haem-iron involvement for both the LPO and NOC pathway during meat digestion. Moreover, results unambiguously demonstrate that DNA adduct formation is very prone to inter-individual variation, suggesting a person-dependent susceptibility to colorectal cancer development following haem-rich meat consumption.

A refined parametric model for short term load forecasting

Abstract We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays.

Weighted alpha-rate dominating sets in social networks

We are looking into variants of a domination set problem in social networks. While randomised algorithms for solving the minimum weighted domination set problem and the minimum alpha and alpha-rate domination problem on simple graphs are already present in the literature, we propose here a randomised algorithm for the minimum weighted alpha-rate domination set problem which is, to the best of our knowledge, the first such algorithm. A theoretical approximation bound based on a simple randomised rounding technique is given. The algorithm is implemented in Python and applied to a UK Twitter mentions networks using a measure of individuals’ influence (klout) as weights. We argue that the weights of vertices could be interpreted as the costs of getting those individuals on board for a campaign or a behaviour change intervention. The minimum weighted alpha-rate dominating set problem can therefore be seen as finding a set that minimises the total cost and each individual in a network has at least alpha percentage of its neighbours in the chosen set. We also test our algorithm on generated graphs with several thousand vertices and edges. Our results on this real-life Twitter networks and generated graphs show that the implementation is reasonably efficient and thus can be used for real-life applications when creating social network based interventions, designing social media campaigns and potentially improving users’ social media experience.

Increases in plasma sheet temperature with solar wind driving during substorm growth phases

During the substorm growth phase, magnetic reconnection extracts ~10^15 J from the solar wind through magnetic reconnection at the magnetopause, which is then stored in the magnetotail lobes. Plasma sheet pressure then increases to balance magnetic flux density increases in the lobes. We examine plasma sheet pressure, density and temperature during substorm growth phases using nine years of Cluster data (>316,000 data points). We show that plasma sheet pressure and temperature are higher during growth phases with higher solar wind driving whereas the density is approximately constant. We also show a weak correlation between plasma sheet temperature before onset and the minimum SuperMAG SML auroral index in the subsequent substorm. We discuss how energization of the plasma sheet before onset may result from thermodynamically adiabatic processes; how hotter plasma sheets may result in magnetotail instabilities and how this relates to the onset and size of the subsequent substorm expansion phase.

The perceived impact of the National Health Service on personalised nutrition service delivery among the UK public

Personalised nutrition (PN) has the potential to reduce disease risk and optimise health and performance. Although previous research has shown good acceptance of the concept of PN in the UK, preferences regarding the delivery of a PN service (e.g. online v. face-to-face) are not fully understood. It is anticipated that the presence of a free at point of delivery healthcare system, the National Health Service (NHS), in the UK may have an impact on end-user preferences for deliverances. To determine this, supplementary analysis of qualitative data obtained from focus group discussions on PN service delivery, collected as part of the Food4Me project in the UK and Ireland, was undertaken. Irish data provided comparative analysis of a healthcare system that is not provided free of charge at the point of delivery to the entire population. Analyses were conducted using the 'framework approach' described by Rabiee (Focus-group interview and data analysis. Proc Nutr Soc 63, 655-660). There was a preference for services to be led by the government and delivered face-to-face, which was perceived to increase trust and transparency, and add value. Both countries associated paying for nutritional advice with increased commitment and motivation to follow guidelines. Contrary to Ireland, however, and despite the perceived benefit of paying, UK discussants still expected PN services to be delivered free of charge by the NHS. Consideration of this unique challenge of free healthcare that is embedded in the NHS culture will be crucial when introducing PN to the UK.

Factors influencing European consumer uptake of personalised nutrition: results of a qualitative analysis

The aim of this research was to explore consumer perceptions of personalised nutrition and to compare these across three different levels of ‘‘medicalization’’: lifestyle assessment (no blood sampling); phenotypic assessment (blood sampling); genomic assessment (blood and buccal sampling). The protocol was developed from two pilot focus groups conducted in the UK. Two focus groups (one comprising only ‘‘older’’ individuals between 30 and 60 years old, the other of adults 18–65 yrs of age) were run in the UK, Spain, the Netherlands, Poland, Portugal, Ireland, Greece and Germany (N = 16). The analysis (guided using grounded theory) suggested that personalised nutrition was perceived in terms of benefit to health and fitness and that convenience was an important driver of uptake. Negative attitudes were associated with internet delivery but not with personalised nutrition per se. Barriers to uptake were linked to broader technological issues associated with data protection, trust in regulator and service providers. Services that required a fee were expected to be of better quality and more secure. An efficacious, transparent and trustworthy regulatory framework for personalised nutrition is required to alleviate consumer concern. In addition, developing trust in service providers is important if such services to be successful.

Sticking to the script? The co-production of Neighbourhood Planning in England

Efforts to engage with communities in spatial planning have been criticised as being tokenistic, vehicles for co-option or designed to promote neo-liberal agendas. The introduction of neighbourhood planning (NP) in England under the Localism Act (2011) is claimed by proponents to be a step change in the way that local communities are involved in planning their own areas. However, little empirical evidence has yet emerged to substantiate such claims, or provide details about the practices and experiences of NP. The paper highlights that there are numerous parties involved in the co-production of Neighbourhood Development Plans and there are numerous instances where ideas, policies and priorities that emerge from within neighbourhoods are being ‘rescripted’ to ensure conformity to a bounded form of collaboration.

Towards predictive understanding of regional climate change

Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.

Self-assembled arginine-capped peptide bolaamphiphile nanosheets for cell culture and controlled wettability surfaces

The spontaneous assembly of a peptide bolaamphiphile in water, namely, RFL4FR (R, arginine; F, phenylalanine; L, leucine) is investigated, along with its novel properties in surface modification and usage as substrates for cell culture. RFL4FR self-assembles into nanosheets through lateral association of the peptide backbone. The L4 sequence is located within the core of the nanosheets, whereas the R moieties are exposed to the water at the surface of the nanosheets. Kinetic assays indicate that the self-assembly is driven by a remarkable two-step process, where a nucleation phase is followed by fast growth of nanosheets with an autocatalysis process. The internal structure of the nanosheets is formed from ultrathin bolaamphiphile monolayers with a crystalline orthorhombic symmetry with cross-β organization. We show that human corneal stromal fibroblast (hCSF) cells can grow on polystyrene films coated with films dried from RFL4FR solutions. For the first time, this type of amphiphilic peptide is used as a substrate to modulate the wettability of solid surfaces for cell culture applications.

Activation of the G-protein coupled receptor 30 (GPR30) has different effects on anxiety in male and female mice

The GPR30, a former orphan GPCR, is a putative membrane estrogen receptor that can activate rapid signaling pathways such as extracellular regulated kinase (ERK) in a variety of cells and may contribute to estrogen's effects in the central nervous system. The distribution of GPR30 in the limbic system predicts a role for this receptor in the regulation of learning and memory and anxiety by estrogens. Though acute G-1 treatment is reported to be anxiogenic in ovariectomised female mice and in gonadally intact male mice, the effect of GPR30 activation is unknown in gonadectomised male mice. In this study, we show that an acute administration of G-1 to gonadectomised male mice, but not female mice, was anxiolytic on an elevated plus maze task, without affecting locomotor activity. In addition, though G-1 treatment did not regulate ERK, it was associated with increased estrogen receptor (ER)alpha phosphorylation in the ventral, but not dorsal, hippocampus of males. In the female, G-1 increased the ERK activation solely in the dorsal hippocampus, independent of state anxiety. This is the first study to report an anxiolytic effect of GPR30 activation in male mice, in a rapid time frame that is commensurate with non-genomic signaling by estrogen.

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.