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.

Subsurface urban heat island and its effects on horizontal ground-source heat pump potential under climate change

Recent urban air temperature increase is attributable to the climate change and heat island effects due to urbanization. This combined effects of urbanization and global warming can penetrate into the underground and elevate the subsurface temperature. In the present study, over-100 years measurements of subsurface temperature at a remote rural site were analysed, and an increasing rate of 0.17⁰C per decade at soil depth of 30cm due to climate change was identified in the UK, but the subsurface warming in an urban site showed a much higher rate of 0.85⁰C per decade at a 30cm depth and 1.18⁰C per decade at 100cm. The subsurface urban heat island (SUHI) intensity obtained at the paired urban-rural stations in London showed an unique 'U-shape', i.e. lowest in summer and highest during winter. The maximum SUHII is 3.5⁰C at 6:00 AM in December, and the minimum UHII is 0.2⁰C at 18:00PM in July. Finally, the effects of SUHI on the energy efficiency of the horizontal ground source heat pump (GSHP) were determined. Provided the same heat pump used, the installation at an urban site will maintain an overall higher COP compared with that at a rural site in all seasons, but the highest COP improvement can be achieved in winter.

Investigating the influence of extracellular matrix and glycolytic metabolism on muscle stem cell migration on their native fibre environment

The composition of the extracellular matrix (ECM) of skeletal muscle fibres is a unique environment that supports the regenerative capacity of satellite cells; the resident stem cell population. The impact of environment has great bearing on key properties permitting satellite cells to carry out tissue repair. In this study, we have investigated the influence of the ECM and glycolytic metabolism on satellite cell emergence and migration- two early processes required for muscle repair. Our results show that both influence the rate at which satellite cells emerge from the sub-basal lamina position and their rate of migration. These studies highlight the necessity of performing analysis of satellite behaviour on their native substrate and will inform on the production of artificial scaffolds intended for medical uses.

Washington's growth and opportunity act or Beijing's 'Overarching Brilliance': will African governments choose neither?

Growing criticism of Chinese engagement in Africa centres on the risk to African development posed by China's aggressive export policies and the threat to the Washington Consensus and African governance posed by China's 'non-interference' approach to engagement. This article challenges both these assumptions. The growth of Chinese trade has a wide range of impacts, depending on the sector in question, and the current terms of trade Washington extends to Africa under the auspices of the AGOA do not result in uniformly beneficial effects. With regard to African governance, it is argued that the 'Washington Consensus' has been based on competing and often muddled perceptions of US national interest. This fact tempers the regret felt at Washington's loss of influence over the good governance agenda. Evidence is provided to show that China can work within properly regulated countries and industries, if the African governments in question can provide fair, efficient and transparent environments in which to operate.

Foodomics for personalized nutrition: how far are we?

To effectively prevent the onset and reduce mortality from noncommunicable diseases, we must consider every individual as metabolically unique to allow for a personalized management to take place. Diet and gut microbiota are major components of the exposome that interact together with a genetic make-up in a complex interplay to result in an individual’s metabolic phenotype. In this context, foodomics approaches (such as nutrigenetics, nutrimetabolomics, nutritranscriptomics, nutriproteomics and metagenomics) are essential tools to assess an individual’s optimal metabolic space. These have recently been applied to large human cohorts to identify specific gene-metabolite, diet-metabolite and gene–diet interactions. As the gut microbiota is a key player in metabolic homeostasis, we suggest following a holistic investigation of metagenome–hyperbolome–diet interactions, the findings of which will provide the basis for developing personalized nutrition and personalized functional foods. However, examining these three-way interactions will only be possible when the challenge of large datasets integration will be overcome.

How will the stratosphere affect climate change?

Changes in stratospheric chemistry and circulation associated with ozone recovery may affect the patterns of future climate change.

Evaluating the climate and air quality impacts of short-lived pollutants

This paper presents a summary of the work done within the European Union's Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). ECLIPSE had a unique systematic concept for designing a realistic and effective mitigation scenario for short-lived climate pollutants (SLCPs; methane, aerosols and ozone, and their precursor species) and quantifying its climate and air quality impacts, and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a new emission inventory based on current legislation (CLE) for the recent past and until 2050. Substantial progress compared to previous work was made by including previously unaccounted types of sources such as flaring of gas associated with oil production, and wick lamps. These emission data were used for present-day reference simulations with four advanced Earth system models (ESMs) and six chemistry transport models (CTMs). The model simulations were compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than in previous studies. Problems likely related to the emissions were identified for northern Russia and India, in particular. To estimate the climate impacts of SLCPs, ECLIPSE followed two paths of research: the first path calculated radiative forcing (RF) values for a large matrix of SLCP species emissions, for different seasons and regions independently. Based on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20) was calculated for each SLCP emission type. This climate metric was then used in an integrated assessment model to identify all emission mitigation measures with a beneficial air quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario. Compared to CLE, the MIT scenario would reduce global methane (CH4) and black carbon (BC) emissions by about 50 and 80 %, respectively. For CH4, measures on shale gas production, waste management and coal mines were most important. For non-CH4 SLCPs, elimination of high-emitting vehicles and wick lamps, as well as reducing emissions from gas flaring, coal and biomass stoves, agricultural waste, solvents and diesel engines were most important. These measures lead to large reductions in calculated surface concentrations of ozone and particulate matter. We estimate that in the EU, the loss of statistical life expectancy due to air pollution was 7.5 months in 2010, which will be reduced to 5.2 months by 2030 in the CLE scenario. The MIT scenario would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate metrics cannot fully quantify the climate response. Therefore, a second research path was taken. Transient climate ensemble simulations with the four ESMs were run for the CLE and MIT scenarios, to determine the climate impacts of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.70 ± 0.14 K between the years 2006 and 2050. For the decade 2041–2050, the warming was reduced by 0.22 ± 0.07 K in the MIT scenario, and this result was in almost exact agreement with the response calculated based on the emission metrics (reduced warming of 0.22 ± 0.09 K). The metrics calculations suggest that non-CH4 SLCPs contribute ~ 22 % to this response and CH4 78 %. This could not be fully confirmed by the transient simulations, which attributed about 90 % of the temperature response to CH4 reductions. Attribution of the observed temperature response to non-CH4 SLCP emission reductions and BC specifically is hampered in the transient simulations by small forcing and co-emitted species of the emission basket chosen. Nevertheless, an important conclusion is that our mitigation basket as a whole would lead to clear benefits for both air quality and climate. The climate response from BC reductions in our study is smaller than reported previously, possibly because our study is one of the first to use fully coupled climate models, where unforced variability and sea ice responses cause relatively strong temperature fluctuations that may counteract (and, thus, mask) the impacts of small emission reductions. The temperature responses to the mitigation were generally stronger over the continents than over the oceans, and with a warming reduction of 0.44 K (0.39–0.49) K the largest over the Arctic. Our calculations suggest particularly beneficial climate responses in southern Europe, where surface warming was reduced by about 0.3 K and precipitation rates were increased by about 15 (6–21) mm yr−1 (more than 4 % of total precipitation) from spring to autumn. Thus, the mitigation could help to alleviate expected future drought and water shortages in the Mediterranean area. We also report other important results of the ECLIPSE project.

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Dynamical properties of S-gap shifts and other shift spaces

We study the dynamical properties of certain shift spaces. To help study these properties we introduce two new classes of shifts, namely boundedly supermultiplicative (BSM) shifts and balanced shifts. It turns out that any almost specified shift is both BSM and balanced, and any balanced shift is BSM. However, as we will demonstrate, there are examples of shifts which are BSM but not balanced. We also study the measure theoretic properties of balanced shifts. We show that a shift space admits a Gibbs state if and only if it is balanced. Restricting ourselves to S-gap shifts, we relate certain dynamical properties of an S-gap shift to combinatorial properties from expansions in non-integer bases. This identification allows us to use the machinery from expansions in non-integer bases to give straightforward constructions of S -gap shifts with certain desirable properties. We show that for any q∈(0,1) there is an S-gap shift which has the specification property and entropy q . We also use this identification to address the question, for a given q∈(0,1), how many S-gap shifts exist with entropy q? For certain exceptional values of q there is a unique S-gap shift with this entropy.

Analysis Scheme in the Ensemble Kalman Filter

This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter . I t i s shown that the obser vations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the obser vations and generate an ensemble of obser vations that then is used in updating the ensemble of model states. T raditionally , this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low . This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach

Plenary Lecture 2: Milk and dairy produce and CVD: new perspectives on dairy and cardiovascular health

Cardiovascular diseases (CVD) are the leading cause of mortality and morbidity worldwide. One of the key dietary recommendations for CVD prevention is reduction of saturated fat intake. Yet despite milk and dairy foods contributing on average 27 % of saturated fat intake in the UK diet, evidence from prospective cohort studies does not support a detrimental effect of milk and dairy foods on risk of CVD. This paper provides a brief overview of the role of milk and dairy products in the diets of UK adults, and will summarise the evidence in relation to the effects of milk and dairy consumption on CVD risk factors and mortality. The majority of prospective studies and meta-analyses examining the relationship between milk and dairy product consumption and risk of CVD show that milk and dairy products, excluding butter, are not associated with detrimental effects on CVD mortality or risk biomarkers, that include serum LDL cholesterol. In addition, there is increasing evidence that milk and dairy products are associated with lower blood pressure and arterial stiffness. These apparent benefits of milk and dairy foods have been attributed to their unique nutritional composition, and suggest that the elimination of milk and dairy may not be the optimum strategy for CVD risk reduction.

Projected changes in medicanes in the HadGEM3 N512 high-resolution global climate model

Medicanes or “Mediterranean hurricanes” represent a rare and physically unique type of Mediterranean mesoscale cyclone. There are similarities with tropical cyclones with regard to their development (based on the thermodynamical disequilibrium between the warm sea and the overlying troposphere) and their kinematic and thermodynamical properties (medicanes are intense vortices with a warm core and even a cloud-free eye). Although medicanes are smaller and their wind speeds are lower than in tropical cyclones, the severity of their winds can cause substantial damage to islands and coastal areas. Concern about how human-induced climate change will affect extreme events is increasing. This includes the future impacts on medicanes due to the warming of the Mediterranean waters and the projected changes in regional atmospheric circulation. However, most global climate models do not have high enough spatial resolution to adequately represent small features such as medicanes. In this study, a cyclone tracking algorithm is applied to high resolution global climate model data with a horizontal grid resolution of approximately 25 km over the Mediterranean region. After a validation of the climatology of general Mediterranean mesoscale cyclones, changes in medicanes are determined using climate model experiments with present and future forcing. The magnitude of the changes in the winds, frequency and location of medicanes is assessed. While no significant changes in the total number of Mediterranean mesoscale cyclones are found, medicanes tend to decrease in number but increase in intensity. The model simulation suggests that medicanes tend to form more frequently in the Gulf of Lion–Genoa and South of Sicily.