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Institute
- Institut für Physik und Astronomie (244)
- Institut für Geowissenschaften (237)
- Institut für Biochemie und Biologie (219)
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- Institut für Ernährungswissenschaft (47)
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The investigation of luminal factors influencing zinc availability and accessibility in the intestine is of great interest when analyzing parameters regulating intestinal zinc resorption. Of note, intestinal mucins were suggested to play a beneficial role in the luminal availability of zinc. Their exact zinc binding properties, however, remain unknown and the impact of these glycoproteins on human intestinal zinc resorption has not been investigated in detail. Thus, the aim of this study is to elucidate the impact of intestinal mucins on luminal uptake of zinc into enterocytes and its transfer into the blood. In the present study, in vitro zinc binding properties of mucins were analyzed using commercially available porcine mucins and secreted mucins of the goblet cell line HT-29-MTX. The molecular zinc binding capacity and average zinc binding affinity of these glycoproteins demonstrates that mucins contain multiple zinc-binding sites with biologically relevant affinity within one mucin molecule. Zinc uptake into the enterocyte cell line Caco-2 was impaired by zinc-depleted mucins. Yet this does not represent their form in the intestinal lumen in vivo under zinc adequate conditions. In fact, zinc-uptake studies into enterocytes in the presence of mucins with differing degree of zinc saturation revealed zinc buffering by these glycoproteins, indicating that mucin-bound zinc is still available for the cells. Finally, the impact of mucins on zinc resorption using three-dimensional cultures was studied comparing the zinc transfer of a Caco-2/HT-29-MTX co-culture and conventional Caco-2 monoculture. Here, the mucin secreting co-cultures yielded higher fractional zinc resorption and elevated zinc transport rates, suggesting that intestinal mucins facilitate the zinc uptake into enterocytes and act as a zinc delivery system for the intestinal epithelium.
Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering similar to 10% of the permafrost region. Lake area loss (-1.45%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59%), but in tundra regions (0.63%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (< 10(-5)%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.
Allometric trophic network (ATN) models offer high flexibility and scalability while minimizing the number of parameters and have been successfully applied to investigate complex food web dynamics and their influence on food web diversity and stability. However, the realism of ATN model energetics has never been assessed in detail, despite their critical influence on dynamic biomass and production patterns. Here, we compare the energetics of the currently established original ATN model, considering only biomass-dependent basal respiration, to an extended ATN model version, considering both basal and assimilation-dependent activity respiration. The latter is crucial in particular for unicellular and invertebrate organisms which dominate the metabolism of pelagic and soil food webs. Based on metabolic scaling laws, we show that the extended ATN version reflects the energy transfer through a chain of four trophic levels of unicellular and invertebrate organisms more realistically than the original ATN version. Depending on the strength of top-down control, the original ATN model yields trophic transfer efficiencies up to 71% at either the third or the fourth trophic level, which considerably exceeds any realistic values. In contrast, the extended ATN version yields realistic trophic transfer efficiencies 30% at all trophic levels, in accordance with both physiological considerations and empirical evidence from pelagic systems. Our results imply that accounting for activity respiration is essential for consistently implementing the metabolic theory of ecology in ATN models and for improving their quantitative predictions, which makes them more powerful tools for investigating the dynamics of complex natural communities.
High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR <= GPP < SIF < VIs/VOD. SIF as an indicator of photosynthesis is maximised around the time of highest annual temperatures. The modelled GPP peaks at a similar time to APAR. The time lag of the annual peak between APAR and instantaneous SIF fluxes indicates that the SIF data do contain information on light-use efficiency of tundra vegetation, but further detailed studies are necessary to verify this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. A particularly late peak of the normalised difference vegetation index (NDVI) in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness or growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models.
We present an optically addressed non-pixelated spatial light modulator. The system is based on reversible photoalignment of a LC cell using a red light sensitive novel azobenzene photoalignment layer. It is an electrode-free device that manipulates the liquid crystal orientation and consequently the polarization via light without artifacts caused by electrodes. The capability to miniaturize the spatial light modulator allows the integration into a microscope objective. This includes a miniaturized 200 channel optical addressing system based on a VCSEL array and hybrid refractive-diffractive beam shapers. As an application example, the utilization as a microscope objective integrated analog phase contrast modulator is shown. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Applications with different characteristics in the cloud may have different resources preferences. However, traditional resource allocation and scheduling strategies rarely take into account the characteristics of applications. Considering that an I/O-intensive application is a typical type of application and that frequent I/O accesses, especially small files randomly accessing the disk, may lead to an inefficient use of resources and reduce the quality of service (QoS) of applications, a weight allocation strategy is proposed based on the available resources that a physical server can provide as well as the characteristics of the applications. Using the weight obtained, a resource allocation and scheduling strategy is presented based on the specific application characteristics in the data center. Extensive experiments show that the strategy is correct and can guarantee a high concurrency of I/O per second (IOPS) in a cloud data center with high QoS. Additionally, the strategy can efficiently improve the utilization of the disk and resources of the data center without affecting the service quality of applications.
Background Previous studies found evidence that dispositional optimism is related to lower pain sensitivity. Recent findings suggest that temporarily increasing optimism by means of imagining a positive future may also have pain-alleviating effects. Objectives The present experiment was designed to investigate conditioned pain modulation (CPM) as a potential underlying mechanism of this pain-alleviating effect of induced optimism. Methods For this purpose, 45 healthy participants were randomized into an optimistic or neutral imagery condition. Additionally, participants completed questionnaires on dispositional optimism, pain catastrophizing and pain expectations. CPM was assessed by delivering a series of five heat pain stimuli on the nondominant hand before and during immersion of the dominant hand in water of 5 degrees C for 70 s. Results A clear CPM effect was found, that is heat pain reports were lower during simultaneous cold water stimulation. Although the optimism manipulation successfully increased optimism, it did not affect pain ratings or CPM. Post hoc analyses indicated that dispositional optimism was not associated with the magnitude of CPM, but pain catastrophizing and pain expectations did significantly correlate with the CPM effect. Conclusion Pain-specific but not general cognitions appear to influence endogenous pain modulation. Significance Conditioned pain modulation is not the underlying mechanism of the pain-alleviating effects of induced optimism. However, pain-specific cognitions including pain catastrophizing and pain expectations affect endogenous pain modulation which should be taken into account in treatment and CPM research.
Environmental drivers interactively affect individual tree growth across temperate European forests
(2018)
Forecasting the growth of tree species to future environmental changes requires abetter understanding of its determinants. Tree growth is known to respond to global‐change drivers such as climate change or atmospheric deposition, as well as to localland‐use drivers such as forest management. Yet, large geographical scale studiesexamining interactive growth responses to multiple global‐change drivers are relativelyscarce and rarely consider management effects. Here, we assessed the interactiveeffects of three global‐change drivers (temperature, precipitation and nitrogen deposi-tion) on individual tree growth of three study species (Quercus robur/petraea, Fagus syl-vatica and Fraxinus excelsior). We sampled trees along spatial environmental gradientsacross Europe and accounted for the effects of management for Quercus. We collectedincrement cores from 267 trees distributed over 151 plots in 19 forest regions andcharacterized their neighbouring environment to take into account potentially confounding factors such as tree size, competition, soil conditions and elevation. Wedemonstrate that growth responds interactively to global‐change drivers, with species ‐specific sensitivities to the combined factors. Simultaneously high levels of precipita-tion and deposition benefited Fraxinus, but negatively affected Quercus’ growth, high-lighting species‐specific interactive tree growth responses to combined drivers. ForFagus, a stronger growth response to higher temperatures was found when precipita-tion was also higher, illustrating the potential negative effects of drought stress underwarming for this species. Furthermore, we show that past forest management canmodulate the effects of changing temperatures on Quercus’ growth; individuals in plotswith a coppicing history showed stronger growth responses to higher temperatures.Overall, our findings highlight how tree growth can be interactively determined by glo-bal‐change drivers, and how these growth responses might be modulated by past for-est management. By showing future growth changes for scenarios of environmentalchange, we stress the importance of considering multiple drivers, including past man-agement and their interactions, when predicting tree growth.
The Gutenberg-Richter relation for earthquake magnitudes is the most famous empirical law in seismology. It states that the frequency of earthquake magnitudes follows an exponential distribution; this has been found to be a robust feature of seismicity above the completeness magnitude, and it is independent of whether global, regional, or local seismicity is analyzed. However, the exponent b of the distribution varies significantly in space and time, which is important for process understanding and seismic hazard assessment; this is particularly true because of the fact that the Gutenberg-Richter b-value acts as a proxy for the stress state and quantifies the ratio of large-to-small earthquakes. In our work, we focus on the automatic detection of statistically significant temporal changes of the b-value in seismicity data. In our approach, we use Bayes factors for model selection and estimate multiple change-points of the frequency-magnitude distribution in time. The method is first applied to synthetic data, showing its capability to detect change-points as function of the size of the sample and the b-value contrast. Finally, we apply this approach to examples of observational data sets for which b-value changes have previously been stated. Our analysis of foreshock and after-shock sequences related to mainshocks, as well as earthquake swarms, shows that only a portion of the b-value changes is statistically significant.
Tundra be dammed
(2018)
Increasing air temperatures are changing the arctic tundra biome. Permafrost is thawing, snow duration is decreasing, shrub vegetation is proliferating, and boreal wildlife is encroaching. Here we present evidence of the recent range expansion of North American beaver (Castor canadensis) into the Arctic, and consider how this ecosystem engineer might reshape the landscape, biodiversity, and ecosystem processes. We developed a remote sensing approach that maps formation and disappearance of ponds associated with beaver activity. Since 1999, 56 new beaver pond complexes were identified, indicating that beavers are colonizing a predominantly tundra region (18,293km(2)) of northwest Alaska. It is unclear how improved tundra stream habitat, population rebound following overtrapping for furs, or other factors are contributing to beaver range expansion. We discuss rates and likely routes of tundra beaver colonization, as well as effects on permafrost, stream ice regimes, and freshwater and riparian habitat. Beaver ponds and associated hydrologic changes are thawing permafrost. Pond formation increases winter water temperatures in the pond and downstream, likely creating new and more varied aquatic habitat, but specific biological implications are unknown. Beavers create dynamic wetlands and are agents of disturbance that may enhance ecosystem responses to warming in the Arctic.