A newly developed in vitro model of the human epithelial airway barrier to study the toxic potential of nanoparticles

The potential health effects of inhaled engineered nanoparticles are almost unknown. To avoid and replace toxicity studies with animals, a triple cell co-culture system composed of epithelial cells, macrophages and dendritic cells was established, which simulates the most important barrier functions of the epithelial airway. Using this model, the toxic potential of titanium dioxide was assessed by measuring the production of reactive oxygen species and the release of tumour necrosis factor alpha. The intracellular localisation of titanium dioxide nanoparticles was analyzed by energy filtering transmission electron microscopy. Titanium dioxide nanoparticles were detected as single particles without membranes and in membrane-bound agglomerates. Cells incubated with titanium dioxide particles showed an elevated production of reactive oxygen species but no increase of the release of tumour necrosis factor alpha. Our in vitro model of the epithelial airway barrier offers a valuable tool to study the interaction of particles with lung cells at a nanostructural level and to investigate the toxic potential of nanoparticles.

Loss of astrocyte polarity marks blood-brain barrier impairment during experimental autoimmune encephalomyelitis

In multiple sclerosis (MS), and its animal model experimental autoimmune encephalomyelitis (EAE), dysfunction of the blood-brain barrier (BBB) leads to edema formation within the central nervous system. The molecular mechanisms of edema formation in EAE/MS are poorly understood. We hypothesized that edema formation is due to imbalanced water transport across the BBB caused by a disturbed crosstalk between BBB endothelium and astrocytes. Here, we demonstrate at the light microscopic and ultrastructural level, the loss of polarized localization of the water channel protein aquaporin-4 (AQP4) in astrocytic endfeet surrounding microvessels during EAE. AQP4 was found to be redistributed over the entire astrocytic cell surface and lost its arrangement in orthogonal arrays of intramembranous particles as seen in the freeze-fracture replica. In addition, immunostaining for the astrocytic extracellular matrix receptor beta-dystroglycan disappeared from astroglial membranes in the vicinity of inflammatory cuffs, whereas immunostaining for the dystroglycan ligands agrin and laminin in the perivascular basement membrane remained unchanged. Our data suggest that during EAE, loss of beta-dystroglycan-mediated astrocyte foot process anchoring to the basement membrane leads to loss of polarized AQP4 localization in astrocytic endfeet, and thus to edema formation in EAE.

Cutting edge: Natalizumab blocks adhesion but not initial contact of human T cells to the blood-brain barrier in vivo in an animal model of multiple sclerosis

The humanized anti-alpha(4) integrin Ab Natalizumab is an effective treatment for relapsing-remitting multiple sclerosis. Natalizumab is thought to exert its therapeutic efficacy by blocking the alpha(4) integrin-mediated binding of circulating immune cells to the blood-brain barrier (BBB). As alpha(4) integrins control other immunological processes, natalizumab may, however, execute its beneficial effects elsewhere. By means of intravital microscopy we demonstrate that natalizumab specifically inhibits the firm adhesion but not the rolling or capture of human T cells on the inflamed BBB in mice with acute experimental autoimmune encephalomyelitis (EAE). The efficiency of natalizumab to block T cell adhesion to the inflamed BBB was found to be more effective in EAE than in acute systemic TNF-alpha-induced inflammation. Our data demonstrate that alpha(4) integrin-mediated adhesion of human T cells to the inflamed BBB during EAE is efficiently blocked by natalizumab and thus provide the first direct in vivo proof of concept of this therapy in multiple sclerosis.

Impact of volcanic stratospheric aerosols on diurnal temperature range in Europe over the past 200 years: Observations versus model simulations

We analyze the impact of stratospheric volcanic aerosols on the diurnal temperature range (DTR) over Europe using long-term subdaily station records. We compare the results with a 28-member ensemble of European Centre/Hamburg version 5.4 (ECHAM5.4) general circulation model simulations. Eight stratospheric volcanic eruptions during the instrumental period are investigated. Seasonal all- and clear-sky DTR anomalies are compared with contemporary (approximately 20 year) reference periods. Clear sky is used to eliminate cloud effects and better estimate the signal from the direct radiative forcing of the volcanic aerosols. We do not find a consistent effect of stratospheric aerosols on all-sky DTR. For clear skies, we find average DTR anomalies of −0.08°C (−0.13°C) in the observations (in the model), with the largest effect in the second winter after the eruption. Although the clear-sky DTR anomalies from different stations, volcanic eruptions, and seasons show heterogeneous signals in terms of order of magnitude and sign, the significantly negative DTR anomalies (e.g., after the Tambora eruption) are qualitatively consistent with other studies. Referencing with clear-sky DTR anomalies to the radiative forcing from stratospheric volcanic eruptions, we find the resulting sensitivity to be of the same order of magnitude as previously published estimates for tropospheric aerosols during the so-called “global dimming” period (i.e., 1950s to 1980s). Analyzing cloud cover changes after volcanic eruptions reveals an increase in clear-sky days in both data sets. Quantifying the impact of stratospheric volcanic eruptions on clear-sky DTR over Europe provides valuable information for the study of the radiative effect of stratospheric aerosols and for geo-engineering purposes.

Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation

The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.

Evaluation of control and surveillance strategies for classical swine fever using a simulation model

Classical swine fever (CSF) outbreaks can cause enormous losses in naïve pig populations. How to best minimize the economic damage and number of culled animals caused by CSF is therefore an important research area. The baseline CSF control strategy in the European Union and Switzerland consists of culling all animals in infected herds, movement restrictions for animals, material and people within a given distance to the infected herd and epidemiological tracing of transmission contacts. Additional disease control measures such as pre-emptive culling or vaccination have been recommended based on the results from several simulation models; however, these models were parameterized for areas with high animal densities. The objective of this study was to explore whether pre-emptive culling and emergency vaccination should also be recommended in low- to moderate-density areas such as Switzerland. Additionally, we studied the influence of initial outbreak conditions on outbreak severity to improve the efficiency of disease prevention and surveillance. A spatial, stochastic, individual-animal-based simulation model using all registered Swiss pig premises in 2009 (n=9770) was implemented to quantify these relationships. The model simulates within-herd and between-herd transmission (direct and indirect contacts and local area spread). By varying the four parameters (a) control measures, (b) index herd type (breeding, fattening, weaning or mixed herd), (c) detection delay for secondary cases during an outbreak and (d) contact tracing probability, 112 distinct scenarios were simulated. To assess the impact of scenarios on outbreak severity, daily transmission rates were compared between scenarios. Compared with the baseline strategy (stamping out and movement restrictions) vaccination and pre-emptive culling neither reduced outbreak size nor duration. Outbreaks starting in a herd with weaning piglets or fattening pigs caused higher losses regarding to the number of culled premises and were longer lasting than those starting in the two other index herd types. Similarly, larger transmission rates were estimated for these index herd type outbreaks. A longer detection delay resulted in more culled premises and longer duration and better transmission tracing increased the number of short outbreaks. Based on the simulation results, baseline control strategies seem sufficient to control CSF in low-medium animal-dense areas. Early detection of outbreaks is crucial and risk-based surveillance should be focused on weaning piglet and fattening pig premises.

Paleoclimate data-model comparison and the role of climate forcings over the past 1500 years

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

Understanding the performance of the FLake model over two African Great Lakes

The ability of the one-dimensional lake model FLake to represent the mixolimnion temperatures for tropical conditions was tested for three locations in East Africa: Lake Kivu and Lake Tanganyika's northern and southern basins. Meteorological observations from surrounding automatic weather stations were corrected and used to drive FLake, whereas a comprehensive set of water temperature profiles served to evaluate the model at each site. Careful forcing data correction and model configuration made it possible to reproduce the observed mixed layer seasonality at Lake Kivu and Lake Tanganyika (northern and southern basins), with correct representation of both the mixed layer depth and water temperatures. At Lake Kivu, mixolimnion temperatures predicted by FLake were found to be sensitive both to minimal variations in the external parameters and to small changes in the meteorological driving data, in particular wind velocity. In each case, small modifications may lead to a regime switch, from the correctly represented seasonal mixed layer deepening to either completely mixed or permanently stratified conditions from similar to 10 m downwards. In contrast, model temperatures were found to be robust close to the surface, with acceptable predictions of near-surface water temperatures even when the seasonal mixing regime is not reproduced. FLake can thus be a suitable tool to parameterise tropical lake water surface temperatures within atmospheric prediction models. Finally, FLake was used to attribute the seasonal mixing cycle at Lake Kivu to variations in the near-surface meteorological conditions. It was found that the annual mixing down to 60m during the main dry season is primarily due to enhanced lake evaporation and secondarily to the decreased incoming long wave radiation, both causing a significant heat loss from the lake surface and associated mixolimnion cooling.

Effect of surface restoring on subsurface variability in a climate model during 1949–2005

Initializing the ocean for decadal predictability studies is a challenge, as it requires reconstructing the little observed subsurface trajectory of ocean variability. In this study we explore to what extent surface nudging using well-observed sea surface temperature (SST) can reconstruct the deeper ocean variations for the 1949–2005 period. An ensemble made with a nudged version of the IPSLCM5A model and compared to ocean reanalyses and reconstructed datasets. The SST is restored to observations using a physically-based relaxation coefficient, in contrast to earlier studies, which use a much larger value. The assessment is restricted to the regions where the ocean reanalyses agree, i.e. in the upper 500 m of the ocean, although this can be latitude and basin dependent. Significant reconstruction of the subsurface is achieved in specific regions, namely region of subduction in the subtropical Atlantic, below the thermocline in the equatorial Pacific and, in some cases, in the North Atlantic deep convection regions. Beyond the mean correlations, ocean integrals are used to explore the time evolution of the correlation over 20-year windows. Classical fixed depth heat content diagnostics do not exhibit any significant reconstruction between the different existing bservation-based references and can therefore not be used to assess global average time-varying correlations in the nudged simulations. Using the physically based average temperature above an isotherm (14°C) alleviates this issue in the tropics and subtropics and shows significant reconstruction of these quantities in the nudged simulations for several decades. This skill is attributed to the wind stress reconstruction in the tropics, as already demonstrated in a perfect model study using the same model. Thus, we also show here the robustness of this result in an historical and observational context.

Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain

Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a set-up of the Weather Research and Forecasting Model (WRF) model that minimises system- atic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable set-up: the horizontal resolution, the planetary boundary layer (PBL) parameterisation scheme and the way the WRF is nested to the driving data set. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model set-ups, but sharing the same driving data set. The results show that the lack of representation of the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis nudging, spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model performance is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

CD4 T cells are required for both development and maintenance of disease in a new mouse model of reversible colitis

Current therapies to treat inflammatory bowel diseases have limited efficacy, significant side effects, and often wane over time. Little is known about the cellular and molecular mechanisms operative in the process of mucosal healing from colitis. To study such events, we developed a new model of reversible colitis in which adoptive transfer of CD4(+)CD45RB(hi) T cells into Helicobacter typhlonius-colonized lymphopenic mice resulted in a rapid onset of colonic inflammation that was reversible through depletion of colitogenic T cells. Remission was associated with an improved clinical and histopathological score, reduced immune cell infiltration to the intestinal mucosa, altered intestinal gene expression profiles, regeneration of the colonic mucus layer, and the restoration of epithelial barrier integrity. Notably, colitogenic T cells were not only critical for induction of colitis but also for maintenance of disease. Depletion of colitogenic T cells resulted in a rapid drop in tumor necrosis factor α (TNFα) levels associated with reduced infiltration of inflammatory immune cells to sites of inflammation. Although neutralization of TNFα prevented the onset of colitis, anti-TNFα treatment of mice with established disease failed to resolve colonic inflammation. Collectively, this new model of reversible colitis provides an important research tool to study the dynamics of mucosal healing in chronic intestinal remitting-relapsing disorders.Mucosal Immunology advance online publication 16 September 2015; doi:10.1038/mi.2015.93.

Standard model cross-over on the lattice

With the physical Higgs mass the standard model symmetry restoration phase transition is a smooth cross-over. We study the thermodynamics of the cross-over using numerical lattice Monte Carlo simulations of an effective SU(2)×U(1) gauge+Higgs theory, significantly improving on previously published results. We measure the Higgs field expectation value, thermodynamic quantities like pressure, energy density, speed of sound and heat capacity, and screening masses associated with the Higgs and Z fields. While the cross-over is smooth, it is very well defined with a width of only ∼5  GeV. We measure the cross-over temperature from the maximum of the susceptibility of the Higgs condensate, with the result Tc=159.5±1.5  GeV. Outside of the narrow cross-over region the perturbative results agree well with nonperturbative ones.

From quantum to classical dynamics: The relativistic O ( N ) model in the framework of the real-time functional renormalization group

We investigate the transition from unitary to dissipative dynamics in the relativistic O(N) vector model with the λ(φ2)2 interaction using the nonperturbative functional renormalization group in the real-time formalism. In thermal equilibrium, the theory is characterized by two scales, the interaction range for coherent scattering of particles and the mean free path determined by the rate of incoherent collisions with excitations in the thermal medium. Their competition determines the renormalization group flow and the effective dynamics of the model. Here we quantify the dynamic properties of the model in terms of the scale-dependent dynamic critical exponent z in the limit of large temperatures and in 2≤d≤4 spatial dimensions. We contrast our results to the behavior expected at vanishing temperature and address the question of the appropriate dynamic universality class for the given microscopic theory.