Posttranslational modifications of cardiac ryanodine receptors: Ca2+ signaling and EC-coupling

In cardiac muscle, a number of posttranslational protein modifications can alter the function of the Ca(2+) release channel of the sarcoplasmic reticulum (SR), also known as the ryanodine receptor (RyR). During every heartbeat RyRs are activated by the Ca(2+)-induced Ca(2+) release mechanism and contribute a large fraction of the Ca(2+) required for contraction. Some of the posttranslational modifications of the RyR are known to affect its gating and Ca(2+) sensitivity. Presently, research in a number of laboratories is focused on RyR phosphorylation, both by PKA and CaMKII, or on RyR modifications caused by reactive oxygen and nitrogen species (ROS/RNS). Both classes of posttranslational modifications are thought to play important roles in the physiological regulation of channel activity, but are also known to provoke abnormal alterations during various diseases. Only recently it was realized that several types of posttranslational modifications are tightly connected and form synergistic (or antagonistic) feed-back loops resulting in additive and potentially detrimental downstream effects. This review summarizes recent findings on such posttranslational modifications, attempts to bridge molecular with cellular findings, and opens a perspective for future work trying to understand the ramifications of crosstalk in these multiple signaling pathways. Clarifying these complex interactions will be important in the development of novel therapeutic approaches, since this may form the foundation for the implementation of multi-pronged treatment regimes in the future. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.

Gas transport in firn: multiple-tracer characterisation and model intercomparison for NEEM, Northern Greenland

Air was sampled from the porous firn layer at the NEEM site in Northern Greenland. We use an ensemble of ten reference tracers of known atmospheric history to characterise the transport properties of the site. By analysing uncertainties in both data and the reference gas atmospheric histories, we can objectively assign weights to each of the gases used for the depth-diffusivity reconstruction. We define an objective root mean square criterion that is minimised in the model tuning procedure. Each tracer constrains the firn profile differently through its unique atmospheric history and free air diffusivity, making our multiple-tracer characterisation method a clear improvement over the commonly used single-tracer tuning. Six firn air transport models are tuned to the NEEM site; all models successfully reproduce the data within a 1σ Gaussian distribution. A comparison between two replicate boreholes drilled 64 m apart shows differences in measured mixing ratio profiles that exceed the experimental error. We find evidence that diffusivity does not vanish completely in the lock-in zone, as is commonly assumed. The ice age- gas age difference (1 age) at the firn-ice transition is calculated to be 182+3−9 yr. We further present the first intercomparison study of firn air models, where we introduce diagnostic scenarios designed to probe specific aspects of the model physics. Our results show that there are major differences in the way the models handle advective transport. Furthermore, diffusive fractionation of isotopes in the firn is poorly constrained by the models, which has consequences for attempts to reconstruct the isotopic composition of trace gases back in time using firn air and ice core records.

In-situ, satellite measurement and model evidence on the dominant regional contribution to fine particulate matter levels in the Paris Megacity

A detailed characterization of air quality in the megacity of Paris (France) during two 1-month intensive campaigns and from additional 1-year observations revealed that about 70% of the urban background fine particulate matter (PM) is transported on average into the megacity from upwind regions. This dominant influence of regional sources was confirmed by in situ measurements during short intensive and longer-term campaigns, aerosol optical depth (AOD) measurements from ENVISAT, and modeling results from PMCAMx and CHIMERE chemistry transport models. While advection of sulfate is well documented for other megacities, there was surprisingly high contribution from long-range transport for both nitrate and organic aerosol. The origin of organic PM was investigated by comprehensive analysis of aerosol mass spectrometer (AMS), radiocarbon and tracer measurements during two intensive campaigns. Primary fossil fuel combustion emissions constituted less than 20%in winter and 40%in summer of carbonaceous fine PM, unexpectedly small for a megacity. Cooking activities and, during winter, residential wood burning are the major primary organic PM sources. This analysis suggests that the major part of secondary organic aerosol is of modern origin, i.e., from biogenic precursors and from wood burning. Black carbon concentrations are on the lower end of values encountered in megacities worldwide, but still represent an issue for air quality. These comparatively low air pollution levels are due to a combination of low emissions per inhabitant, flat terrain, and a meteorology that is in general not conducive to local pollution build-up. This revised picture of a megacity only being partially responsible for its own average and peak PM levels has important implications for air pollution regulation policies.

Pollen-based quantitative reconstructions of Holocene regional vegetation cover (plant-functional types and land-cover types) in Europe suitable for climate modelling

We present quantitative reconstructions of regional vegetation cover in north-western Europe, western Europe north of the Alps, and eastern Europe for five time windows in the Holocene around 6k, 3k, 0.5k, 0.2k, and 0.05k calendar years before present (bp)] at a 1 degrees x1 degrees spatial scale with the objective of producing vegetation descriptions suitable for climate modelling. The REVEALS model was applied on 636 pollen records from lakes and bogs to reconstruct the past cover of 25 plant taxa grouped into 10 plant-functional types and three land-cover types evergreen trees, summer-green (deciduous) trees, and open land]. The model corrects for some of the biases in pollen percentages by using pollen productivity estimates and fall speeds of pollen, and by applying simple but robust models of pollen dispersal and deposition. The emerging patterns of tree migration and deforestation between 6k bp and modern time in the REVEALS estimates agree with our general understanding of the vegetation history of Europe based on pollen percentages. However, the degree of anthropogenic deforestation (i.e. cover of cultivated and grazing land) at 3k, 0.5k, and 0.2k bp is significantly higher than deduced from pollen percentages. This is also the case at 6k in some parts of Europe, in particular Britain and Ireland. Furthermore, the relationship between summer-green and evergreen trees, and between individual tree taxa, differs significantly when expressed as pollen percentages or as REVEALS estimates of tree cover. For instance, when Pinus is dominant over Picea as pollen percentages, Picea is dominant over Pinus as REVEALS estimates. These differences play a major role in the reconstruction of European landscapes and for the study of land cover-climate interactions, biodiversity and human resources.

Type A aortic dissection model to improve endovascular research and technologies.

OBJECTIVE Type A aortic dissection is a life-threatening disease requiring immediate surgical treatment. With emerging catheter-based technologies, endovascular stent-graft implantation to treat aneurysms and dissections has become a standardized procedure. However, endovascular treatment of the ascending aorta remains challenging. Thus we designed an ascending aortic dissection model to allow simulation of endovascular treatment. METHODS Five formalin-fixed human aortas were prepared. The ascending aorta was opened semicircularly in the middle portion and the medial layer was separated from the intima. The intimal tube was readapted using running monofilament sutures. The preparations were assessed by 128-slice computed tomography. A bare-metal stent was implanted for thoracic endovascular aortic repair in 4 of the aortic dissection models. RESULTS Separation of the intimal and medial layer of the aorta was considered to be sufficient because computed tomography showed a clear image of the dissection membrane in each aorta. The dissection was located 3.9 ± 1.4 cm proximally from the aortic annulus, with a length of 4.6 ± 0.9 cm. Before stent implantation, the mean distance from the intimal flap to the aortic wall was measured as 0.63 ± 0.163 cm in the ascending aorta. After stent implantation, this distance decreased to 0.26 ± 0.12 cm. CONCLUSION This model of aortic dissection of the ascending human aorta was reproducible with a comparable pathological and morphological appearance. The technique and model can be used to evaluate new stent-graft technologies to treat type A dissection and facilitate training for surgeons.

An overview of the objectives of and the approaches to propensity score analyses

The assessment of treatment effects from observational studies may be biased with patients not randomly allocated to the experimental or control group. One way to overcome this conceptual shortcoming in the design of such studies is the use of propensity scores to adjust for differences of the characteristics between patients treated with experimental and control interventions. The propensity score is defined as the probability that a patient received the experimental intervention conditional on pre-treatment characteristics at baseline. Here, we review how propensity scores are estimated and how they can help in adjusting the treatment effect for baseline imbalances. We further discuss how to evaluate adequate overlap of baseline characteristics between patient groups, provide guidelines for variable selection and model building in modelling the propensity score, and review different methods of propensity score adjustments. We conclude that propensity analyses may help in evaluating the comparability of patients in observational studies, and may account for more potential confounding factors than conventional covariate adjustment approaches. However, bias due to unmeasured confounding cannot be corrected for.

Risk attribution of Campylobacter infection by age group using exposure modelling

Knowledge on the relative importance of alternative sources of human campylobacteriosis is important in order to implement effective disease prevention measures. The objective of this study was to assess the relative importance of three key exposure pathways (travelling abroad, poultry meat, pet contact) for different patient age groups in Switzerland. With a stochastic exposure model data on Campylobacter incidence for the years 2002-2007 were linked with data for the three exposure pathways and the results of a case-control study. Mean values for the population attributable fractions (PAF) over all age groups and years were 27% (95% CI 17-39) for poultry consumption, 27% (95% CI 22-32) for travelling abroad, 8% (95% CI 6-9) for pet contact and 39% (95% CI 25-50) for other risk factors. This model provided robust results when using data available for Switzerland, but the uncertainties remained high. The output of the model could be improved if more accurate input data are available to estimate the infection rate per exposure. In particular, the relatively high proportion of cases attributed to 'other risk factors' requires further attention.

Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

Shifted Coupling of EEG Driving Frequencies and fMRI Resting State Networks in Schizophrenia Spectrum Disorders

INTRODUCTION: The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state networks (RSNs). Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates) and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN) and left-working-memory network (LWMN). METHODS: Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11) and matched healthy controls (n = 11) using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps. RESULTS: The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls. CONCLUSIONS: By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling. SIGNIFICANCE: The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations), arise.

Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis

The responses of carbon dioxide (CO2) and other climate variables to an emission pulse of CO2 into the atmosphere are often used to compute the Global Warming Potential (GWP) and Global Temperature change Potential (GTP), to characterize the response timescales of Earth System models, and to build reduced-form models. In this carbon cycle-climate model intercomparison project, which spans the full model hierarchy, we quantify responses to emission pulses of different magnitudes injected under different conditions. The CO2 response shows the known rapid decline in the first few decades followed by a millennium-scale tail. For a 100 Gt-C emission pulse added to a constant CO2 concentration of 389 ppm, 25 ± 9% is still found in the atmosphere after 1000 yr; the ocean has absorbed 59 ± 12% and the land the remainder (16 ± 14%). The response in global mean surface air temperature is an increase by 0.20 ± 0.12 °C within the first twenty years; thereafter and until year 1000, temperature decreases only slightly, whereas ocean heat content and sea level continue to rise. Our best estimate for the Absolute Global Warming Potential, given by the time-integrated response in CO2 at year 100 multiplied by its radiative efficiency, is 92.5 × 10−15 yr W m−2 per kg-CO2. This value very likely (5 to 95% confidence) lies within the range of (68 to 117) × 10−15 yr W m−2 per kg-CO2. Estimates for time-integrated response in CO2 published in the IPCC First, Second, and Fourth Assessment and our multi-model best estimate all agree within 15% during the first 100 yr. The integrated CO2 response, normalized by the pulse size, is lower for pre-industrial conditions, compared to present day, and lower for smaller pulses than larger pulses. In contrast, the response in temperature, sea level and ocean heat content is less sensitive to these choices. Although, choices in pulse size, background concentration, and model lead to uncertainties, the most important and subjective choice to determine AGWP of CO2 and GWP is the time horizon.