Supranutritional selenium induces alterations in molecular targets related to energy metabolism in skeletal muscle and visceral adipose tissue of pigs

While selenium (Se) is an essential micronutrient for humans, epidemiological studies have raised concern that supranutritional Se intake may increase the risk to develop Type 2 diabetes mellitus (T2DM). We aimed to determine the impact of Se at a dose and source frequently ingested by humans on markers of insulin sensitivity and signalling. Male pigs were fed either a Se-adequate (0.17 mg Se/kg) or a Se-supranutritional (0.50 mg Se/kg; high-Se) diet. After 16 weeks of intervention, fasting plasma insulin and cholesterol levels were non-significantly increased in the high-Se pigs, whereas fasting glucose concentrations did not differ between the two groups. In skeletal muscle of high-Se pigs, glutathione peroxidase activity was increased, gene expression of forkhead box O1 transcription factor and peroxisomal proliferator-activated receptor- coactivator 1 were increased and gene expression of the glycolytic enzyme pyruvate kinase was decreased. In visceral adipose tissue of high-Se pigs, mRNA levels of sterol regulatory element-binding transcription factor 1 were increased, and the phosphorylation of Akt, AMP-activated kinase and mitogen-activated protein kinases was affected. In conclusion, dietary Se oversupply may affect expression and activity of proteins involved in energy metabolism in major insulin target tissues, though this is probably not sufficient to induce diabetes.

The concept of exchangeability in ensemble forecasting

A set of random variables is exchangeable if its joint distribution function is invariant under permutation of the arguments. The concept of exchangeability is discussed, with a view towards potential application in evaluating ensemble forecasts. It is argued that the paradigm of ensembles being an independent draw from an underlying distribution function is probably too narrow; allowing ensemble members to be merely exchangeable might be a more versatile model. The question is discussed whether established methods of ensemble evaluation need alteration under this model, with reliability being given particular attention. It turns out that the standard methodology of rank histograms can still be applied. As a first application of the exchangeability concept, it is shown that the method of minimum spanning trees to evaluate the reliability of high dimensional ensembles is mathematically sound.

Comment on ``Conditional Exceedance Probabilities''

In a recent paper, Mason et al. propose a reliability test of ensemble forecasts for a continuous, scalar verification. As noted in the paper, the test relies on a very specific interpretation of ensembles, namely, that the ensemble members represent quantiles of some underlying distribution. This quantile interpretation is not the only interpretation of ensembles, another popular one being the Monte Carlo interpretation. Mason et al. suggest estimating the quantiles in this situation; however, this approach is fundamentally flawed. Errors in the quantile estimates are not independent of the exceedance events, and consequently the conditional exceedance probabilities (CEP) curves are not constant, which is a fundamental assumption of the test. The test would reject reliable forecasts with probability much higher than the test size.

Predicting outliers in ensemble forecasts

An ensemble forecast is a collection of runs of a numerical dynamical model, initialized with perturbed initial conditions. In modern weather prediction for example, ensembles are used to retrieve probabilistic information about future weather conditions. In this contribution, we are concerned with ensemble forecasts of a scalar quantity (say, the temperature at a specific location). We consider the event that the verification is smaller than the smallest, or larger than the largest ensemble member. We call these events outliers. If a K-member ensemble accurately reflected the variability of the verification, outliers should occur with a base rate of 2/(K + 1). In operational forecast ensembles though, this frequency is often found to be higher. We study the predictability of outliers and find that, exploiting information available from the ensemble, forecast probabilities for outlier events can be calculated which are more skilful than the unconditional base rate. We prove this analytically for statistically consistent forecast ensembles. Further, the analytical results are compared to the predictability of outliers in an operational forecast ensemble by means of model output statistics. We find the analytical and empirical results to agree both qualitatively and quantitatively.

Rank histograms of stratified Monte-Carlo ensembles

The application of forecast ensembles to probabilistic weather prediction has spurred considerable interest in their evaluation. Such ensembles are commonly interpreted as Monte Carlo ensembles meaning that the ensemble members are perceived as random draws from a distribution. Under this interpretation, a reasonable property to ask for is statistical consistency, which demands that the ensemble members and the verification behave like draws from the same distribution. A widely used technique to assess statistical consistency of a historical dataset is the rank histogram, which uses as a criterion the number of times that the verification falls between pairs of members of the ordered ensemble. Ensemble evaluation is rendered more specific by stratification, which means that ensembles that satisfy a certain condition (e.g., a certain meteorological regime) are evaluated separately. Fundamental relationships between Monte Carlo ensembles, their rank histograms, and random sampling from the probability simplex according to the Dirichlet distribution are pointed out. Furthermore, the possible benefits and complications of ensemble stratification are discussed. The main conclusion is that a stratified Monte Carlo ensemble might appear inconsistent with the verification even though the original (unstratified) ensemble is consistent. The apparent inconsistency is merely a result of stratification. Stratified rank histograms are thus not necessarily flat. This result is demonstrated by perfect ensemble simulations and supplemented by mathematical arguments. Possible methods to avoid or remove artifacts that stratification induces in the rank histogram are suggested.

Real-time multi-model decadal climate predictions

We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.

Decadal climate prediction: an update from the trenches

This paper provides an update on research in the relatively new and fast-moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about six to nine years. Recent multi-model results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialized multi-model ensemble decadal hindcasts than in single model results, with multi-model initialized predictions for near term climate showing somewhat less global warming than uninitialized simulations. Some decadal hindcasts have shown statistically reliable predictions of surface temperature over various land and ocean regions for lead times of up to 6-9 years, but this needs to be investigated in a wider set of models. As in the early days of El Niño-Southern Oscillation (ENSO) prediction, improvements to models will reduce the need for bias adjustment, and increase the reliability, and thus usefulness, of decadal climate predictions in the future.

Arctic ozone depletion in 2002–2003 measured by ASUR and comparison with POAM observations

We present ozone loss estimated from airborne measurements taken during January–February and March in the Arctic winter 2002/2003. The first half of the winter was characterized by unusually cold temperatures and the second half by a major stratospheric sudden warming around 15–18 January 2003. The potential vorticity maps show a vortex split in the lower stratosphere during the major warming (MW) in late January and during the minor warming in mid-February due to wave 1 amplification. However, the warming can be termed as a vortex displacement event as there was no vortex split during the MW period at 10 hPa. Very low temperatures, large areas of polar stratospheric clouds (PSCs), and high chlorine activation triggered significant ozone loss in the early winter, as the vortex moved to the midlatitude regions. The ozone depletion derived from the ASUR measurements sampled inside the vortex, in conjunction with the Mimosa-Chim model tracer, shows a maximum of 1.3 ± 0.2 ppmv at 450–500 K by late March. The partial column loss derived from the ASUR ozone profiles reaches up to 61 ± 4 DU in 400–550 K in the same period. The evolution of ozone and ozone loss assessed from the ASUR measurements is in very good agreement with POAM observations. The reduction in ozone estimated from the POAM measurements shows a similar maximum of 1.3 ± 0.2 ppmv at 400–500 K or 63 ± 4 DU in 400–550 K in late March. Our study reveals that the Arctic winter 2002/2003 was unique as it had three minor warmings and a MW, yet showed large loss in ozone. No such feature was observed in any other Arctic winter in the 1989–2010 period. In addition, an unusually large ozone loss in December, around 0.5 ± 0.2 ppmv at 450–500 K or 12 ± 1 DU in 400–550 K, was estimated for the first time in the Arctic. A careful and detailed diagnosis with all available published results for this winter exhibits an average ozone loss of 1.5 ± 0.3 ppmv at 450–500 K or 65 ± 5 DU in 400–550 K by the end of March, which exactly matches the ozone depletion derived from the ASUR, POAM and model data. The early ozone loss together with considerable loss afterwards put the warm Arctic winter 2002/2003 amongst the moderately cold winters in terms of the significance of the ozone loss.

Crooks' fluctuation theorem for a process on a two dimensional fluid field

We investigate the behavior of a two-dimensional inviscid and incompressible flow when pushed out of dynamical equilibrium. We use the two-dimensional vorticity equation with spectral truncation on a rectangular domain. For a sufficiently large number of degrees of freedom, the equilibrium statistics of the flow can be described through a canonical ensemble with two conserved quantities, energy and enstrophy. To perturb the system out of equilibrium, we change the shape of the domain according to a protocol, which changes the kinetic energy but leaves the enstrophy constant. We interpret this as doing work to the system. Evolving along a forward and its corresponding backward process, we find numerical evidence that the distributions of the work performed satisfy the Crooks relation. We confirm our results by proving the Crooks relation for this system rigorously.

A digital ecosystems model of assessment feedback on student learning

The term ecosystem has been used to describe complex interactions between living organisms and the physical world. The principles underlying ecosystems can also be applied to complex human interactions in the digital world. As internet technologies make an increasing contribution to teaching and learning practice in higher education, the principles of digital ecosystems may help us understand how to maximise technology to benefit active, self-regulated learning especially among groups of learners. Here, feedback on student learning is presented within a conceptual digital ecosystems model of learning. Additionally, we have developed a Web 2.0-based system, called ASSET, which incorporates multimedia and social networking features to deliver assessment feedback within the functionality of the digital ecosystems model. Both the digital ecosystems model and the ASSET system are described and their implications for enhancing feedback on student learning are discussed.

Complex dynamics in simple systems with periodic parameter oscillations

We study systems with periodically oscillating parameters that can give way to complex periodic or nonperiodic orbits. Performing the long time limit, we can define ergodic averages such as Lyapunov exponents, where a negative maximal Lyapunov exponent corresponds to a stable periodic orbit. By this, extremely complicated periodic orbits composed of contracting and expanding phases appear in a natural way. Employing the technique of ϵ-uncertain points, we find that values of the control parameters supporting such periodic motion are densely embedded in a set of values for which the motion is chaotic. When a tiny amount of noise is coupled to the system, dynamics with positive and with negative nontrivial Lyapunov exponents are indistinguishable. We discuss two physical systems, an oscillatory flow inside a duct and a dripping faucet with variable water supply, where such a mechanism seems to be responsible for a complicated alternation of laminar and turbulent phases.

Adult palatum as a novel source of neural crest-related stem cells

Somatic neural and neural crest stem cells are promising sources for cellular therapy of several neurodegenerative diseases. However, because of practical considerations such as inadequate accessibility of the source material, the application of neural crest stem cells is strictly limited. The secondary palate is a highly regenerative and heavily innervated tissue, which develops embryonically under direct contribution of neural crest cells. Here, we describe for the first time the presence of nestin-positive neural crest-related stem cells within Meissner corpuscles and Merkel cell-neurite complexes located in the hard palate of adult Wistar rats. After isolation, palatal neural crest-related stem cells (pNC-SCs) were cultivated in the presence of epidermal growth factor and fibroblast growth factor under serum-free conditions, resulting in large amounts of neurospheres. We used immunocytochemical techniques and reverse transcriptase-polymerase chain reaction to assess the expression profile of pNC-SCs. In addition to the expression of neural crest stem cell markers such as Nestin, Sox2, and p75, we detected the expression of Klf4, Oct4, and c-Myc. pNC-SCs differentiated efficiently into neuronal and glial cells. Finally, we investigated the potential expression of stemness markers within the human palate. We identified expression of stem cell markers nestin and CD133 and the transcription factors needed for reprogramming of somatic cells into pluripotent cells: Sox2, Oct4, Klf4, and c-Myc. These data show that cells isolated from palatal rugae form neurospheres, are highly plastic, and express neural crest stem cell markers. In addition, pNC-SCs may have the ability to differentiate into functional neurons and glial cells, serving as a starting point for therapeutic studies.