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Abstract Type 2 diabetes (T2D) is associated with a systemic increase in the pro-inflammatory cytokine IL-1β. While transient exposure to low IL-1β concentrations improves insulin secretion and β-cell proliferation in pancreatic islets, prolonged exposure leads to impaired insulin secretion and collective β-cell death. IL-1 is secreted locally by islet-resident macrophages and β-cells; however, it is unknown if and how the two opposing modes may emerge at single islet level. We investigated the duality of IL-1β with a quantitative in silico model of the IL-1 regulatory network in pancreatic islets. We find that the network can produce either transient or persistent IL-1 responses when induced by pro-inflammatory and metabolic cues. This suggests that the duality of IL-1 may be regulated at the single islet level. We use two core feedbacks in the IL-1 regulation to explain both modes: First, a fast positive feedback in which IL-1 induces its own production through the IL-1R/IKK/NF-κB pathway. Second, a slow negative feedback where NF-κB upregulates inhibitors acting at different levels along the IL-1R/IKK/NF-κB pathway—IL-1 receptor antagonist and A20, among others. A transient response ensues when the two feedbacks are balanced. When the positive feedback dominates over the negative, islets transit into the persistent inflammation mode. Consistent with several observations, where the size of islets was implicated in its inflammatory state, we find that large islets and islets with high density of IL-1β amplifying cells are more prone to transit into persistent IL-1β mode. Our results are likely not limited to IL-1β but are general for the combined effect of multiple pro-inflammatory cytokines and chemokines. Generalizing complex regulations in terms of two feedback mechanisms of opposing nature and acting on different time scales provides a number of testable predictions. Taking islet architecture and cellular heterogeneity into consideration, further dynamic monitoring and experimental validation in actual islet samples will be crucial to verify the model predictions and enhance its utility in clinical applications.

Abstract It has been widely reported that isoprene emissions from the Arctic ecosystem have a strong temperature response. Here we identify sedges (Carex spp. and Eriophorum spp.) as key contributors to this high sensitivity using plant chamber experiments. We observe that sedges exhibit a markedly stronger temperature response compared to that of other isoprene emitters and predictions by the widely accepted isoprene emission model, the Model of Emissions of Gases and Aerosols from Nature (MEGAN). MEGAN is able to reproduce eddy-covariance flux observations at three high-latitude sites by integrating our findings. Furthermore, the omission of the strong temperature responses of Arctic isoprene emitters causes a 20% underestimation of isoprene emissions for the high-latitude regions of the Northern Hemisphere during 2000-2009 in the Community Land Model with the MEGAN scheme. We also find that the existing model had underestimated the long-term trend of isoprene emissions from 1960 to 2009 by 55% for the high-latitude regions.

Abstract Oxidative stress from ozone (O3) causes plants to alter their emission of biogenic volatile organic compounds (BVOC) and their photosynthetic rate. Stress reactions from O3 on birch trees can result in prohibited plant growth and lead to increased BVOC emission rates as well as changes in their compound blend to emit more monoterpenes (MT) and sesquiterpenes (SQT). BVOCs take part in atmospheric reactions such as enhancing the production of secondary organic aerosols (SOA). As the compound blend and emission rate change with O3 stress, this can influence the atmospheric conditions by affecting the production of SOA. Studying the stress responses of plants provides important information on how these reactions might change, which is vital to making better predictions of the future climate. In this study, measurements were taken to find out how the leaves of mature mountain birch trees (Betula pubescens ssp. czerepanovii) respond to different levels of elevated O3 exposure in situ depending on leaf age. We found that leaves from both early and late summers responded with induced SQT emission after exposure to 120 ppb O3. Early leaves were, however, more sensitive to increased O3 concentrations, with enhanced emission of green leaf volatiles (GLV) and tendencies of both induced leaf senescence as well as poor recovery in the photosynthetic rate between exposures. Late leaves had more stable photosynthetic rates throughout the experiment and responded less to exposure at different O3 levels.

Permafrost thaw allows biological activity in previously frozen ground, leading to a potential release of climate-relevant gases. Here the authors show that thawing permafrost emits volatile organic compounds but that their release to the atmosphere is limited by microbial consumption in the overlaying soil.

In Europe, willow (Salix spp.) trees have been used commercially since the 1980s at a large scale to produce renewable energy. While reducing fossil fuel needs, growing short rotation coppices (SRCs), such as poplar or willow, may have a high impact on local air quality as these species are known to produce high amounts of isoprene, which can lead to the production of tropospheric ozone (O3). Here, we present a long-term leaf-scale study of biogenic volatile organic compound (BVOC) emissions from a Swedish managed willow site with the aim of providing information on the seasonal variability in BVOC emissions during two growing seasons, 2015–2016. Total BVOC emissions during these two seasons were dominated by isoprene (>96% by mass) and the monoterpene (MT) ocimene. The average standardized (STD, temperature of 30 °C and photosynthetically active radiation of 1000 µmol m−2 s−1) emission rate for isoprene was 45.2 (±42.9, standard deviation (SD)) μg gdw−1 h−1. Isoprene varied through the season, mainly depending on the prevailing temperature and light, where the measured emissions peaked in July 2015 and August 2016. The average STD emission for MTs was 0.301 (±0.201) μg gdw−1 h−1 and the MT emissions decreased from spring to autumn. The average STD emission for sesquiterpenes (SQTs) was 0.103 (±0.249) μg gdw−1 h−1, where caryophyllene was the most abundant SQT. The measured emissions of SQTs peaked in August both in 2015 and 2016. Non-terpenoid compounds were grouped as other VOCs (0.751 ± 0.159 μg gdw−1 h−1), containing alkanes, aldehydes, ketones, and other compounds. Emissions from all the BVOC groups decreased towards the end of the growing season. The more sun-adapted leaves in the upper part of the plantation canopy emitted higher rates of isoprene, MTs, and SQTs compared with more shade-adapted leaves in the lower canopy. On the other hand, emissions of other VOCs were lower from the upper part of the canopy compared with the lower part. Light response curves showed that ocimene and α-farnesene increased with light but only for the sun-adapted leaves, since the shade-adapted leaves did not emit ocimene and α-farnesene. An infestation with Melampsora spp. likely induced high emissions of, e.g., hexanal and nonanal in August 2015. The results from this study imply that upscaling BVOC emissions with model approaches should account for seasonality and also include the canopy position of leaves as a parameter to allow for better estimates for the regional and global budgets of ecosystem emissions.

Biogenic Volatile Organic Compounds (BVOCs) are trace gases other than CO2 and CH4 produced and emitted by the biosphere, where the amounts released depend on climatic factors such as temperature and solar irradiation. However, interpretation of leaf-level measurements is currently hampered by factors such as large within-genotypic variability, measurement height and time in the season. A campaign was performed between June and August in 2013 in Taastrup, Denmark to study these uncertainties. BVOC emissions were measured from leaves and needles at heights of 2 m, 5.5 m and 12.5 m in the canopy and for seven trees; four Norway spruces (Picea abies) of which two trees had a budburst approximately a week before the other two, two English oaks (Quercus robur) and one European beech (Fagus sylvatica). Differences in chemical composition and emission strength between June and August were observed between the different trees. English oak's main compound isoprene increased from 62–74 % of the total emission in June to approximately 97 % in August, which is linked to leaf development over the summer season. The total emission from all measured spruce trees decreased from July to August, but without a loss in the diversity of emitted compounds. The trees showed indications of drought stress as there was a period without precipitation lasting 21 days during the study. There were no differences in emission patterns within all of the measured Norway spruces. For measurement height, there was only a significant difference in emission pattern for European beech as the top of the canopy emitted 7–9 times more in relation to lower canopy levels. Our results suggest there was little within-genotype variability and the wide spacing between trees had an influence on the individual emission patterns. These results are important in order to understand the significance of within-genotypic variation, canopy height and seasonal development in relation to the emission patterns of the selected species. Furthermore, it will provide helpful insights for modelers who wish to improve their emission estimates.

Willow (Salix spp.) trees are commonly used in short rotation coppices (SRC) to produce renewable energy. However, these plants are also known to emit high concentrations of biogenic volatile organic compounds (BVOCs), which have a large influence on air quality. Many different clones of commercially used Salix varieties exist today, but only a few studies have focused on BVOC emissions from these newer varieties. In this study, four varieties commercially propagated for biofuel production have been studied on a leaf-scale in the southern part of Sweden. The trees had either their first or second growing season, and measurements on BVOC emissions were done during the growing season in 2017 from the end of May to the beginning of September. Isoprene was the dominant emitted compound for all varieties but the average emission amongst varieties varied from 4.00 to 12.66 µg gdw−1 h−1. Average monoterpene (MT) (0.78–1.87 µg gdw−1 h−1) and sesquiterpene (SQT) emission rates (0.22–0.57 µg gdw−1 h−1) differed as well among the varieties. Besides isoprene, other compounds like ocimene, linalool and caryophyllene also showed a response to light but not for all varieties. Younger plants had several times higher emissions of non-isoprenoids (other VOCs) than the corresponding 1-year-old trees. The conclusions from this study show that the choice of variety can have a large impact on the regional BVOC emission budget. Genetics, together with stand age, should be taken into account when modelling BVOC emissions on a regional scale, for example, for air quality assessments.

Satellite derived normalized difference vegetation index (NDVI) is a common data source for monitoring regional and global ecosystem properties. In dry lands it has contributed to estimation of inter-annual and seasonal vegetation dynamics and phenology. However, due to the spectral properties of NDVI it can be affected by clouds which can introduce missing data in the time series. Remotely sensed soil moisture has in contrast to NDVI the benefit of being unaffected by clouds due to the measurements being made in the microwave domain. There is therefore a potential in combining the remotely sensed NDVI with remotely sensed soil moisture to enhance the quality and estimate the missing data. We present a step towards the usage of remotely sensed soil moisture for estimation of savannah NDVI. This was done by evaluating the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture and three of its individual products with respect to their relative performance. The individual products are from the advance scatterometer (ASCAT), Soil Moisture and Ocean Salinity (SMOS), and the Land Parameter Retrieval Model-Advanced Microwave Scanning Radiometer-Earth Observing System (LPRM-AMSR-E). Each dataset was used to simulate NDVI, which was subsequently compared to remotely sensed NDVI from MODIS. Differences in their ability to estimate NDVI indicated that, on average, CCI soil moisture differs from its individual products by showing a higher average correlation with measured NDVI. Overall NDVI modelled from CCI soil moisture gave an average correlation of 0.81 to remotely sensed NDVI which indicates its potential to be used to estimate seasonal variations in savannah NDVI. Our result shows promise for further development in using CCI soil moisture to estimate NDVI. The modelled NDVI can potentially be used together with other remotely sensed vegetation datasets to enhance the phenological information that can be acquired, thereby, improving the estimates of savannah vegetation phenology.

A large portion of atmospheric aerosol particles consists of secondary material produced by oxidation reactions. The relative importance of secondary organic aerosol (SOA) can increase with improved emission regulations. A relatively simple way to study potential particle formation in the atmosphere is by using oxidation flow reactors (OFRs) which simulate atmospheric ageing. Here we report on the first ambient OFR ageing experiment in Europe, coupled with scanning mobility particle sizer (SMPS), aerosol mass spectrometer (AMS) and proton transfer reaction (PTR)-MS measurements. We found that the simulated ageing did not produce any measurable increases in particle mass or number concentrations during the two months of the campaign due to low concentrations of precursors. Losses in the reactor increased with hydroxyl radical (OH) exposure and with increasing difference between ambient and reactor temperatures, indicating fragmentation and evaporation of semivolatile material.

Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.

The short-term limit value for PM10 having become effective in January 2005 was exceeded in many regions within the EU in 2005 and 2006. Therefore, strategies, particularly with respect to traffic control, are discussed, which could cause reduced PM10 concentrations leading to a more effective compliance with the short-term PM10 limit value. These strategies are often justified on PM10 differences between a roadside and an adjacent urban background station. As PM10 is a complex mixture of species originating from different sources, the working hypothesis has been posted that the meteorological exchange conditions strongly affect the PM10 concentration. Therefore, the role of the meteorological exchange conditions with respect to different PM10 patterns, like cycles and PM10 episodes, was investigated on the basis of mean daily PM10 values from air pollution monitoring stations in Baden-Württemberg (SW Germany) in the period January 2001 to February 2006. To characterise the meteorological exchange conditions in a spatial resolution, different meteorological variables were used. Partly, they are directly measured at the air pollution monitoring stations or, as for the height of the mixing-layer (MLH) and the stagnation index (SI), they were derived from results of the local model (LM) of the German Weather Service. For periods without precipitation, the results show a statistically significant relationship between PM10 and MLH as well as SI. PM10 increased with decreasing MLH and increasing SI. During periods with precipitation, these relationships were very weak and had no statistical significance. The analysis of the influence of precipitation performed on a daily basis revealed a distinct reduction of PM10 on the first day with precipitation after a period without precipitation. On following days without precipitation, PM10 increased again. Characteristic of the PM10 episodes analysed were remarkably reduced meteorological exchange conditions described by MLH, near-surface wind speed and precipitation. As a case study, two extreme PM10 episodes in January/February 2006 were investigated in detail. As expected, the station-specific variability of the mean daily PM10 values correlated well with daily values of MLH and SI reflecting the pattern of the regional meteorological exchange conditions. Altogether, all results of this investigation point out the main significance of the meteorological exchange conditions on the PM10 level, which is particularly dominant during PM10 episodes.

Within the framework of an interdisciplinary project on the impact of climate and forest management on beech dominated deciduous forests, forest meteorological measurements are carried out within and above different beech stands (Fagus sylvatica L.) on opposite slopes of a narrow valley located in the Swabian Jura mountain range (south-west Germany). Referring to test plots on both slopes, the following cycles of radiation components are discussed: (1) Monthly mean values of transmission and extinction of global solar irradiance, photosynthetically active radiation as well as UV-A and UV-B radiation through the canopy, (2) diurnal courses of surface albedo α, net short-wave radiation K*, net long-wave radiation L* and net all-wave radiation Q* for a cloudless day in March (leafless period) and a cloudless day in July (fully-leaved period) above and below the canopy of different beech stands, and (3) monthly mean values of α, K*, L* and Q* for the same stand conditions as for (2). The results point out the combined impact on the investigated radiation components emanating from seasonally variable canopy density (quantified by the plant area index), exposure and sun elevation.

Obwohl der Begriff Intelligenz mittlerweile in den verschiedensten Bereichen verwandt wird, um die Entstehung komplexer Kausalitäten zu erklären, wird Intelligenz hier primär als die Fähigkeit neuronaler Systeme verstanden, Probleme in kognitiven Entscheidungsprozessen zu lösen. Kognition und intelligentes Verhalten sind daher primäre Objekt, aber nicht Subjekt der zufallsgetriebenen biologischen Evolution. – Aktuelle Arbeiten aus der Neurobiologie und vergleichenden Genomforschung haben jetzt gezeigt, wie, ausgehend von einfachen neuronalen Systemen, in allen Großgruppen des Tierreichs Formen entstanden sind, die in der Lage sind, vergleichbar komplexe Probleme in kognitiven Prozessen zu lösen. Diese Kognition beruht zwar auf den gleichen zellulären Grundelementen (Neuronen), wird aber in zum Teil ganz unterschiedlich gestalteten zentralnervösen Strukturen (Gehirne) realisiert. Durch den Vergleich der Nervensysteme von Tieren, die zu höheren intelligenten Sinnesleistungen fähig sind, werden jetzt erste gemeinsame Eigenschaften und Prinzipien offenkundig, welche Voraussetzung für die Entstehung höherer intelligenter Systeme sind (z. B. die Verschaltungsdichte, aber nicht Zahl neuronaler Elemente). Sie sind wahrscheinlich auch Constraints in der Entwicklung künstlicher intelligenter Systeme.

Wet printing traditionally has been conducted with the use of naturally occurring gums as the thickening agent. These natural gums are long chain polysaccharides and must be chemically and physically modified to make them suitable as textile print thickeners. As an alternative to natural gums the textile print market bas begun to investigate the use of synthetic thickeners with wet colors. These synthetic thickeners are long chain polymers derived from substituted vinyl compounds. Over the last three years synthetics have been introduced in wet printing applications, including the upholstery, carpet and apparel markets. The advantages and disadvantages of the synthetic system are reviewed, particularly as the system relates to apparel printing. In addition, proper methods of handling synthetics on a commercial basis are discussed, and projections are made concerning the future of synthetic thickeners. [ABSTRACT FROM AUTHOR]