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Pancreatic ductal adenocarcinoma (PDAC) is classified into two key subtypes, classical and basal, with basal PDAC predicting worse survival. Using in vitro drug assays, genetic manipulation experiments, and in vivo drug studies in human patient-derived xenografts (PDXs) of PDAC, we found that basal PDACs were uniquely sensitive to transcriptional inhibition by targeting cyclin-dependent kinase 7 (CDK7) and CDK9, and this sensitivity was recapitulated in the basal subtype of breast cancer. We showed in cell lines, PDXs, and publicly available patient datasets that basal PDAC was characterized by inactivation of the integrated stress response (ISR), which leads to a higher rate of global mRNA translation. Moreover, we identified the histone deacetylase sirtuin 6 (SIRT6) as a critical regulator of a constitutively active ISR. Using expression analysis, polysome sequencing, immunofluorescence, and cycloheximide chase experiments, we found that SIRT6 regulated protein stability by binding activating transcription factor 4 (ATF4) in nuclear speckles and protecting it from proteasomal degradation. In human PDAC cell lines and organoids as well as in murine PDAC genetically engineered mouse models where SIRT6 was deleted or down-regulated, we demonstrated that SIRT6 loss both defined the basal PDAC subtype and led to reduced ATF4 protein stability and a nonfunctional ISR, causing a marked vulnerability to CDK7 and CDK9 inhibitors. Thus, we have uncovered an important mechanism regulating a stress-induced transcriptional program that may be exploited with targeted therapies in particularly aggressive PDAC.

The EMT-transcription factor ZEB1 is heterogeneously expressed in tumor cells and in cancer-associated fibroblasts (CAFs) in colorectal cancer (CRC). While ZEB1 in tumor cells regulates metastasis and therapy resistance, its role in CAFs is largely unknown. Combining fibroblast-specificZeb1deletion with immunocompetent mouse models of CRC, we observe that inflammation-driven tumorigenesis is accelerated, whereas invasion and metastasis in sporadic cancers is reduced upon fibroblast-specific loss ofZeb1. Single-cell transcriptomics, histological andin vitrocharacterization reveal a crucial role in CAF polarization, promoting myofibroblastic features whilst restricting inflammatory activation.Zeb1deficiency impairs collagen deposition and CAF barrier function but increases cytokine production, jointly promoting lymphocyte recruitment and immune checkpoint activation. Strikingly, theZeb1-deficient CAF repertoire sensitizes to immune checkpoint inhibition, pointing to a therapeutic opportunity of targeting ZEB1 in CAFs and its usage as a prognostic biomarker. Collectively, we demonstrate that ZEB1-dependent plasticity of CAFs suppresses anti-tumor immunity and promotes metastasis.

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to −6% (SSP126) and from +1% to −24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated. Climate change affects agricultural productivity. New systematic global agricultural yield projections of the major crops were conducted using ensembles of the latest generation of crop and climate models. Substantial shifts in global crop productivity due to climate change will occur within the next 20 years—several decades sooner than previous projections—highlighting the need for targeted food system adaptation and risk management in the coming decades.

The DNA damage response (DDR) and epithelial-to-mesenchymal transition (EMT) are two crucial cellular programs in cancer biology. While the DDR orchestrates cell cycle progression, DNA repair and cell death, EMT promotes invasiveness, cellular plasticity and intratumor heterogeneity. Therapeutic targeting of EMT transcription factors, such as ZEB1, remains challenging, but tumor-promoting DDR alterations elicit specific vulnerabilities. Using multi-omics, inhibitors and high-content microscopy, we discover a chemoresistant ZEB1 high expressing sub-population (ZEB1hi) with co-rewired cell cycle progression and proficient DDR across tumor entities. ZEB1 stimulates accelerated S-phase entry via CDK6, inflicting endogenous DNA replication stress. However, DDR buildups involving constitutive MRE11-dependent fork resection allow homeostatic cycling and enrichment of ZEB1hi cells during TGFβ-induced EMT and chemotherapy. Thus, ZEB1 promotes G1/S transition to launch a progressive DDR benefitting stress tolerance, which concurrently manifests a targetable vulnerability in chemoresistant ZEB1hi cells. Our study thus highlights the translationally relevant intercept of the DDR and EMT.&nbsp

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

The use of nitrogen (N) fertilizers and cultivation of N-fixing crops has grown exponentially over the last century, with severe environmental consequences. Most of the anthropogenic reactive nitrogen will ultimately be returned by denitrification to the atmosphere as inert N2, but the magnitude of denitrification and the ratio of N2O to (N2O + N2) emitted ( R N 2 O ) is unknown for the vast majority of terrestrial ecosystems. This paper provides estimates of terrestrial denitrification and R N 2 O by reviewing existing literature and compiling a N budget for the global land surface. We estimate that terrestrial denitrification has doubled from 80 Tg-N year−1 in pre-industrial times to 160 Tg-N year−1 in 2005 with a mean R N 2 O of approximately 0.08. We conclude that upscaling of R N 2 O can provide spatial estimates of terrestrial denitrification when data from acetylene inhibition methods are excluded. Recent advances in methodologies to measure N2 emissions and R N 2 O under field conditions could open the way for more effective management of terrestrial N flows.

Irrigated cotton in Australia is mainly grown on heavy textured soils which are prone to waterlogging, resulting in significant losses of nitrogen (N) via denitrification and surface run-off. This study investigated fertiliser nitrogen use efficiency (fNUE) over three seasons on five commercial cotton farms using the 15N tracer technique. Fertiliser NUE was consistently low across all fertilised treatments, with on average 47% of the applied fertiliser lost and only 17% of the N taken up by the crop derived from fertiliser. There was no significant effect of different N fertiliser products and rates on cotton lint yield. High lint yields (0.9–3.6 Mg ha−1) could be achieved even without the application of N fertiliser, demonstrating mineralisation of soil organic N, residual fertiliser, or N returned with crop residues, as key source of N in these cropping systems. Using the nitrification inhibitor DMPP and overhead instead of furrow irrigation showed potential to reduce N fertiliser losses. The results demonstrate that under current on-farm management fNUE is low on irrigated cotton farms in Australia and highlight the need to account for soil N stocks and mineralisation rates when assessing optimized fertiliser rates. There is substantial scope to improve fNUE and reduce N losses without any impact on lint yield, by adjusting N fertiliser application rates, in particular in combination with the use of the nitrification inhibitor DMPP. Using overhead instead of furrow irrigation is a promising approach to improve not only water use efficiency, but also fNUE in irrigated cotton systems.

Pancreatic Ductal Adenocarcinoma (PDA) can be characterized by two distinct transcriptional subtypes: Classical and Basal-like. The basal PDA subtype is more aggressive and has the worst overall survival. Previous work has shown that Sirtuin 6 histone deacetylase (SIRT6) acts as a tumor suppressor and cooperates with oncogenic KRAS in GEMM models of PDA. Our study identifies SIRT6 as a biomarker for basal PDA and investigates the underlying sensitivity of basal PDA to inhibition of transcriptional cyclin dependent kinases (CDKs). Through analysis of data from hundreds of human PDA tumors, we identified that low SIRT6 expression correlates with basal PDA while the converse is true for classical PDA. Using many in vitro drug assays, genetic manipulation experiments, and in vivo drug studies in human patient-derived xenografts of PDA, we also discovered that basal PDA is uniquely sensitive to the covalent CDK7/12/13 inhibitor THZ1 as well as other inhibitors of transcriptional CDKs. Importantly, removal of SIRT6 can sensitize SIRT6 high/classical PDA to THZ1. Further investigation identified that SIRT6 low/basal PDA has an inactivated Integrated Stress Response (ISR), which is primarily driven by ATF4. To determine how loss of SIRT6 leads to an inability to activate the ISR, we have integrated use of human PDA cell lines, and organoids as well as murine PDA GEMMs where SIRT6 has been deleted or downregulated. We uncovered that SIRT6 regulates the ISR through control of ATF4 translation, specifically through a 3’ UTR open reading frame (uORF) dependent mechanism. To determine whether ISR activation could protect basal PDA cells from transcriptional CDK inhibition, we manipulated expression of ISR pathway components. We found that activation of the ISR in SIRT6 low/basal PDA reduces sensitivity to THZ1, while inactivation of the ISR sensitizes SIRT6 high/classical PDA to this inhibitor. Interestingly, both basal and classical PDA exhibit increased phosphorylation of eIF2a upon inhibition of transcriptional CDKs, which typically indicates activation of the ISR in response to stress. However, this activation of the ISR remains incomplete since ATF4 translation is not upregulated in basal PDA in the absence of SIRT6. Therefore, we discovered that loss of SIRT6 sensitizes basal PDA to inhibition of transcriptional CDKs through an inability to launch a functional ISR response. Furthermore, we have uncovered an important biomarker which controls a stress-induced transcriptional program that may be exploited with targeted therapies in a particularly aggressive PDA subtype. Citation Format: Jessica Gianopulos, Nithya Kartha, Zachary Schrank, Stephanie Dobersch, Sarah Cavender, Bryan Kynnap, Adrianne Wallace-Povirk, Cynthia Wladyka, Juan Santana, Jaeseung C. Kim, Angela Yu, Caroline Bridgwater, Kathrin Fuchs, Sarah Dysinger, Aaron Lampano, Faiyaz Notta, David Price, Andrew Hsieh, Sunil Hingorani, Sita Kugel. Sirtuin 6 histone deacetylase is required for the integrated stress response and resistance to inhibition of transcriptional cyclin dependent kinases in Pancreatic Ductal Adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B075.

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET). ISSN:0168-1923 ISSN:1873-2240

Potential climate-related impacts on future crop yield are a major societal concern first surveyed in a harmonized multi-model effort in 2014. We report here on new 21st-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean, and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5 to -6% (SSP126) and +1 to -24% (SSP585) — explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9 shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts — when the change signal emerges from the noise — consistently occurs earlier in the new projections for several main producing regions before 2040. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Grasslands comprised of grass-legume mixtures could become a substitute for nitrogen fertiliser through biological nitrogen fixation (BNF) which in turn can reduce nitrous oxide emissions directly from soils without negative impacts on productivity. Models can test how legumes can be used to meet environmental and production goals, but many models used to simulate greenhouse gas (GHG) emissions from grasslands have either a poor representation of grass-legume mixtures and BNF, or poor validation of these features. Our objective is to examine how such systems are currently represented in two process-based biogeochemical models, APSIM and DayCent, when compared against an experimental dataset with different grass-legume mixtures at three nitrogen (N) fertiliser rates. Here, we propose a novel approach for coupling DayCent, a single species model to APSIM, a multi-species model, to increase the capability of DayCent when representing a range of grass-legume fractions. While dependent on specific assumptions, both models can capture the key aspects of the grass-legume growth, including biomass production and BNF and to correctly simulate the interactions between changing legume and grass fractions, particularly mixtures with a high clover fraction. Our work suggests that single species models should not be used for grass-legume mixtures beyond about 30% legume content, unless using a similar approach to that adopted here.

Agricultural nitrogen (N) inputs have grown massively over the last century, driving increases in crop yields, but also resulting in increased greenhouse-gas emissions and nutrient overloading of ecosystems. Of particular note is the increase in emissions of N2O, a greenhouse gas with 300 times the warming potential of CO2. While the total global yearly N2O emissions can be easily deduced from atmospheric measurements, much less is known about the contribution of different cropping systems, and how increasing food demand will affect these emissions in the future. This knowledge is important for developing well-targeted mitigation strategies that reduce N2O emissions while increasing crop production. In order to help resolve this issue, we have simulated global croplands, one of the main beneficiaries of increased N inputs, using a process-based model that captures both crop growth and nitrogen and carbon cycling through the soil. This allows us to quantify total N2O emissions by crop type, identify hotspots and explore how a changing climate and increasing food demand are likely to impact future emissions. The idea is that this will aid in the search for agricultural management strategies that ensure food security while reducing the climate impact.

Osteosarcoma is an often‐fatal mesenchyme‐derived malignancy in children and young adults. Overexpression of EMT‐transcription factors (EMT‐TFs) has been associated with poor clinical outcome. Here, we demonstrated that the EMT‐TF ZEB1 is able to block osteoblastic differentiation in normal bone development as well as in osteosarcoma cells. Consequently, overexpression of ZEB1 in osteosarcoma characterizes poorly differentiated, highly metastatic subgroups and its depletion induces differentiation of osteosarcoma cells. Overexpression of ZEB1 in osteosarcoma is frequently associated with silencing of the imprinted DLK‐DIO3 locus, which encodes for microRNAs targeting ZEB1. Epigenetic reactivation of this locus in osteosarcoma cells reduces ZEB1 expression, induces differentiation, and sensitizes to standard treatment, thus indicating therapeutic options for ZEB1‐driven osteosarcomas. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE-JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE-JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N-Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN-MIP project funded by the French National Research Agency (ANR-13-JFAC-0001) and from ADEME (no. 12-60-C0023). Open access funding enabled and organized by Projekt DEAL Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE‐JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE‐JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N‐Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN‐MIP project funded by the French National Research Agency (ANR‐13‐JFAC‐0001) and from ADEME (no. 12‐60‐C0023). Open access funding enabled and organized by Projekt DEAL Publisher Copyright: ©2020. The Authors. Open access funding enabled and organized by Projekt DEAL

A five-year greenhouse gas (GHG) exchange study of the three major gas species (CO2, CH4 and N2O) from an intensively managed permanent grassland in Switzerland is presented. Measurements comprise two years (2010/2011) of manual static chamber measurements of CH4 and N2O, five years of continuous eddy covariance (EC) measurements (CO2/H2O – 2010–2014) and three years (2012–2014) of EC measurement of CH4 and N2O. Intensive grassland management included both regular and sporadic management activities. Regular management practices encompassed mowing (3–5 cuts per year) with subsequent organic fertilizer amendments and occasional grazing whereas sporadic management activities comprised grazing or similar activities. The primary objective of our measurements was to compare pre-ploughing to post-ploughing GHG exchange and to identify potential memory effects of such a substantial disturbance on GHG exchange and carbon (C) and nitrogen (N) budgets. In order to include measurements carried with different observation techniques, we tested two different measurement techniques jointly in 2013, namely the manual static chamber approach and the eddy covariance technique, to quantify the GHG exchange from the observed grassland site. Our results showed that there were no memory effects on N2O and CH4 emissions after ploughing, whereas the CO2 uptake of the site considerably increased when compared to post-restoration years. In detail, we observed large losses of CO2 and N2O during the year of restoration. In contrast, the grassland acted as a carbon sink under usual management, i.e. the time periods (2010–2011 and 2013–2014). Enhanced emissions/emission peaks of N2O (defined as exceeding background emissions < 0.21 ± 0.55 nmol m−2s−1 (SE = 0.02) for at least two sequential days and the seven-day moving average exceeding background emissions) were observed for almost seven continuous months after restoration as well following organic fertilizer applications during all. Net ecosystem exchange of CO2 (NEECO2) showed a common pattern of increased uptake of CO2 in spring and reduced uptake in late fall. NEECO2 dropped to zero and became positive after each harvest event. Methane (CH4) exchange in contrast to N2O showed minor net uptake of methane seen by the static chambers and small net release of methane seen by the eddy covariance method. Overall, CH4 exchange was of negligible importance for both, the GHG budget as well as for the carbon budget of the site. Our results stress the inclusion of grassland restoration events when providing cumulative sums of C sequestration and/or global warming potentials (GWPs). Consequently, this study further highlights the need for continuous long-term GHG exchange observations as well as the implementation of our findings into biogeochemical process models to track potential GHG mitigation objectives as well as to predict future GHG emission scenarios reliably.

Summary Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate.We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf‐ and ecosystem‐level observations.SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem‐level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root‐mean‐square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites.SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors., See also the Commentary on this article by Anderegg & Venturas, 226: 1535–1538.

Denitrification is a key but poorly quantified component of the N cycle. Because it is difficult to measure the gaseous (NOx, N2O, N2) and soluble (NO3) components of denitrification with sufficient intensity, models of varying scope and complexity have been developed and applied to estimate how vegetation cover, land management and environmental factors such as soil type and weather interact to control these variables. In this paper we assess the strengths and limitations of different modeling approaches, highlight major uncertainties, and suggest how different observational methods and process-based understanding can be combined to better quantify N cycling. Representation of how biogeochemical (e.g. org. C., pH) and physical (e.g. soil structure) factors influence denitrification rates and product ratios combined with ensemble approaches may increase accuracy without requiring additional site level model inputs.

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC‐based T estimates show higher correlation to sap flow‐based T than EC‐based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high‐quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data‐based estimates of ecosystem T permitting a data‐driven perspective on the role of plants’ water use for global water and carbon cycling in a changing climate. We acknowledge insightful discussions with Dario Papale and apologize for having a cappuccino after lunch. We further acknowledge Ulrich Weber for preparing the cappuccino. M.G. acknowledges funding by Swiss National Science Foundation project ICOS‐CH Phase 2 20FI20_173691. L.Š. was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and by SustES‐Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). G.W. acknowledges support by the Austrian National Science Fund (FWF, project I03859) and the Province of South Tyrol (“Cycling of carbon and water in mountain ecosystems under changing climate and land use”). R.P. was supported by grants CGL2014‐55883‐JIN, RTI2018‐095297‐J‐I00 (Spain), and by a Humboldt Research Fellowship for Experienced Researchers (Germany). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: Ameri‐Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. Open access funding enabled and organized by Projekt DEAL.

Across landscape and field scales, nitrogen (N) transformation rates are enhanced in hot spots (HS) and transient hot moments (HM), leading to losses of environmentally reactive N. Nitrous oxide (N2O) emission trends follow these spatial and temporal patterns. Consequently, landscape features can accelerate N2O emissions, and significant fractions of total annual emissions occur in these N2O emissions HS and HM. In agroecosystems, naturally occurring and management-induced HS and HM can be exacerbated or ameliorated through mitigation management practices. Although mitigation practices have been recommended for reduction of N2O emissions, these have not explicitly targeted HS and HM. Here we review, and synthesize, N2O mitigation practices with an emphasis on how they can be aligned to reduce the occurrence of HS and HM of N2O emission.

Replacing fertilizer nitrogen with biological nitrogen fixation (BNF) through legumes has been suggested as a strategy for nitrous oxide (N 2 O) mitigation from intensively managed grasslands. While current literature provides evidence for an N 2 O emission reduction effect due to reduced fertilizer input, little is known about the effect of increased legume proportions potentially offsetting these reductions, i.e. by increased N 2 O emissions from plant residues and root exudates. In order to assess the overall effect of this mitigation strategy on permanent grassland, we performed an in-situ experiment to quantify net N 2 O fluxes and biomass yields in two differently managed grass-clover mixtures. We measured N 2 O fluxes in an unfertilized parcel with high clover proportions vs. a fertilized control parcel with low clover proportions using the eddy–covariance (EC) technique over two years. Furthermore, we related the measured N 2 O fluxes to management and environmental drivers. To assess the effect of the mitigation strategy, we measured biomass yields and quantified biologically fixed nitrogen using the 15 N natural abundance method. The mitigation management effectively reduced N 2 O emissions by 54 % and 39 % in 2015 and 2016, respectively. These reductions in N 2 O emissions can be attributed to the absence of fertilization on the clover parcel. Differences in clover proportions during periods with no recent management showed no measurable effect on N 2 O emissions, indicating that decomposition of plant residues and rhizodeposition did not compensate the effect of fertilizer reduction on N 2 O emissions. Annual biomass yields were similar under mitigation management, resulting in a reduction of N 2 O emission intensities from 0.42 g N 2 O-N kg −1 DM (control) to 0.28 g N 2 O-N kg −1 DM (clover parcel) over the two years observation period. We conclude that N 2 O emissions from fertilized grasslands can be effectively reduced without losses in yield by increasing the clover proportion and reducing fertilization.

Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grassland systems caused by changes in management practices. To support agricultural policies, it is however important to contrast the responses of alternative models, which can differ greatly in their treatment of key processes and in their response to management. We applied eight biogeochemical models at five grassland sites (in France, New Zealand, Switzerland, United Kingdom and United States) to compare the sensitivity of modelled C and N fluxes to changes in the density of grazing animals (from 100% to 50% of the original livestock densities), also in combination with decreasing N fertilization levels (reduced to zero from the initial levels). Simulated multi-model median values indicated that input reduction would lead to an increase in the C sink strength (negative net ecosystem C exchange) in intensive grazing systems: −64 ± 74 g C m−2 yr−1 (animal density reduction) and −81 ± 74 g C m−2 yr−1 (N and animal density reduction), against the baseline of −30.5 ± 69.5 g C m−2 yr−1 (LSU [livestock units] ≥ 0.76 ha−1 yr−1). Simulations also indicated a strong effect of N fertilizer reduction on N fluxes, e.g. N2O-N emissions decreased from 0.34 ± 0.22 (baseline) to 0.1 ± 0.05 g N m−2 yr−1 (no N fertilization). Simulated decline in grazing intensity had only limited impact on the N balance. The simulated pattern of enteric methane emissions was dominated by high model-to-model variability. The reduction in simulated offtake (animal intake + cut biomass) led to a doubling in net primary production per animal (increased by 11.6 ± 8.1 t C LSU−1 yr−1 across sites). The highest N2O-N intensities (N2O-N/offtake) were simulated at mown and extensively grazed arid sites. We show the possibility of using grassland models to determine sound mitigation practices while quantifying the uncertainties associated with the simulated outputs.

Macrophages are key regulators of innate and adaptive immune responses. Exposure to microenvironmental stimuli determines their polarization into proinflammatory M1 and anti-inflammatory M2 macrophages. M1 exhibit high expression of proinflammatory TNF-α and IL-1β, and M2 promote tissue repair, but likewise support tumor growth and cause immune suppression by expressing IL-10. Thus, the M1/M2 balance critically determines tissue homeostasis. By using carboxyl- (PS-COOH) and amino-functionalized (PS-NH2) polystyrene nanoparticles, the effects of surface decoration on the polarization of human macrophages were investigated. The nanoparticles did not compromise macrophage viability nor did they affect the expression of the M1 markers CD86, NOS2, TNF-α, and IL-1β. By contrast, in M2, both nanoparticles impaired expression of scavenger receptor CD163 and CD200R, and the release of IL-10. PS-NH2 also inhibited phagocytosis of Escherichia coli by both, M1 and M2. PS-COOH did not impair phagocytosis by M2, but increased protein mass in M1 and M2, TGF-β1 release by M1, and ATP levels in M2. Thus, nanoparticles skew the M2 macrophage polarization without affecting M1 markers. Given the critical role of the M1 and M2 polarization for the immunological balance in patients with cancer or chronic inflammation, functionalized nanoparticles might serve as tools for reprogramming the M1/M2 polarization.

PurposeThe question arises whether entrepreneurship education will be able to facilitate the entrepreneurial attitude in the near future. Unfortunately, the decisive role of compulsory schooling has long been neglected in this context. Until recently it was considered sufficient to provide education in entrepreneurship in universities (especially in the area of Business Administration) or in the form of special courses for people who consider starting their own business. Picking up the discussion at this point, the purpose of this paper is to analyse to what extent compulsory school education in Germany and Sweden facilitates a more entrepreneurial way of thinking among pupils.Design/methodology/approachFirst, the paper briefly summarises the relevant research literature and specify important components of entrepreneurship education. Second, it discusses what exactly is to be understood by entrepreneurial qualities and present a holistic approach based on a model by Dahlgren. Third, it describes the unique data and presents some empirical results. The empirical analysis concentrates on Germany. Yet, for reasons of comparison, it additionally analyses the situation in Sweden. Finally, the paper summarises the results and discusses the policy implications.FindingsThe results presented clearly suggest that German schools do not succeed very well in presenting self‐employment as an attractive alternative to dependent work. Swedish pupils generally show a higher preference for self‐employment than their German counterparts. Furthermore, the results suggest that German schools diminish rather than encourage pupils' ambitions to become self‐employed as the pupils become older.Originality/valueTo the authors' knowledge this is the first empirical study which compares the effect of different school systems on entrepreneurial attitude simultaneously (i.e. with the same questionnaire and at the same point of time).

Amyloid β (Aβ) fibrils are strongly involved in the pathogenesis of Alzheimer's diseases. The Aβ oligomers represent a non-fibrillar intermediate state of fibril formation.Here we explored the potential of Aβ peptide oligomers as a novel class of biological nanoparticles for macrophage targeting. This study shows that Aβ(1-40) peptide oligomers have a near-spheroid shape and due to a β-sheet assembly possess a compact, quasi-crystalline architecture. Additionally, FRET analysis revealed that Aβ(1-40) are structurally dynamic. Hence, they represent highly structured and biocompatible nanoparticles, which can be readily degraded by natural enzymes. Macrophages play a major role in immunity and tissue repair. However, recent evidence implicates them in progression of atherosclerosis, fibrosis, tumor initiation and development. In this context, specific labeling and imaging of macrophages are of special interest for diagnostic and therapeutic applications. We found that oligomeric Aβ(1-40) is preferentially t...

The Tibetan Plateau plays a significant role in atmospheric circulation and the Asian monsoon system. Turbulent surface fluxes and the evolution of boundary-layer clouds to deep and moist convection provide a feedback system that modifies the plateau's surface energy balance on scales that are currently unresolved in mesoscale models. This work analyses the land surface's role and specifically the influence of soil moisture on the triggering of convection at a cross section of the Nam Co Lake basin, 150 km north of Lhasa using a cloud-resolving atmospheric model with a fully coupled surface. The modelled turbulent fluxes and development of convection compare reasonably well with the observed weather. The simulations span Bowen ratios of 0.5 to 2.5. It is found that convective development is the strongest at intermediate soil moisture. Dry cases with soils close to the permanent wilting point are moisture limited in convective development, while convection in wet soil moisture cases is limited by cloud cover reducing incoming solar radiation and sensible heat fluxes, which has a strong impact on the surface energy balance. This study also shows that local development of convection is an important mechanism for the upward transport of water vapour, which originates from the lake basin that can then be transported to dryer regions of the plateau. Both processes demonstrate the importance of soil moisture and surface–atmosphere interactions on the energy and hydrological cycles of the Tibetan Plateau.

Amyloid oligomers are nonfibrillar polypeptide aggregates linked to diseases, such as Alzheimer's and Parkinson's. Here we show that these aggregates possess a compact, quasi-crystalline architecture that presents significant nanoscale regularity. The amyloid oligomers are dynamic assemblies and are able to release their individual subunits. The small oligomeric size and spheroid shape confer diffusible characteristics, electrophoretic mobility, and the ability to enter hydrated gel matrices or cells. We finally showed that the amyloid oligomers can be labeled with both fluorescence agents and iron oxide nanoparticles and can target macrophage cells. Oligomer amyloids may provide a new biological nanomaterial for improved targeting, drug release, and medical imaging.

A biocompatible device for the voltage dependent uptake and release of the neural transmitter L-glutamate in neutral pH solutions is demonstrated. The device consists of a gold electrode coated with molecularly imprinted, overoxidised polypyrrole (oPPy). It is shown here that oPPy can behave as an anion exchanger in neutral pH. The voltage dependent uptake and release of glutamate from the oPPy as well as the enantioselectivity of the polymer layer for L-glutamate over D-glutamate are investigated in neutral pH solutions using electrochemical quartz crystal microbalance techniques. The biocompatibility of the oPPy layer is demonstrated using retinae from young rats. The retinae were isolated and the dissociated cells were kept in culture for up to 1-week. The cells were exposed to the oPPy layers for 3 days, and there is no significant difference in the survival rate between the cells cultured on the oPPy layers and the control samples. Additionally the cell-polymer interface from cells grown directly on the oPPy layers is investigated using electron microscopy.

In this paper results are presented on the development of a device demonstrating the uptake and release of L-glutamate in solutions with neutral pH. A device which selectively regulates the concentration of biomolecules, such as the primary neural transmitter L-glutamate, could be useful for many biological and medical applications. In the literature it has been demonstrated that polypyrrole (PPy) is a promising material for the recognition basis of molecularly selective devices [1, 2]. In this study we investigated the feasibility of the PPy based “glutamate switch” for the voltage dependent uptake and release of L-glutamate for physiological applications

In recent years, three main arguments have been advanced in Germany to substantiate the need to promote entrepreneurship: The foremost motivation to promote entrepreneurship is the difficult employment situation (EUROPEAN COMMISSION 2004a). Many companies respond to the growing competitive pressures either by reducing their workforce or by relocating the business to other parts of the world. Thus, in Germany we need new, innovative enterprises that are able to withstand the competitive pressures and create new jobs. Secondly, it is estimated that every third entrepreneur will retire within the next ten years (EUROPEAN COMMISSION 2002a). At the same time, the number of business transfers within the family is decreasing. If the retiring entrepreneurs fail to find appropriate successors, an estimated 70,900 German enterprises and 680,000 jobs are at risk every year (FREUND 2004). Thus, we need young people with entrepreneurial abilities willing to take over these enterprises. Thirdly, the transition from the industrial to the modern knowledge and information society entails significant changes regarding the structure of the labour market: A business environment which is increasingly marked by flat hierarchies poses new challenges to the workforce requiring them to co-operate across department boundaries and take independent decisions (BOSTON CONSULTING GROUP 2002). Thus, the German business sector needs employees that display a high degree of entrepreneurial spirit in their workplace and are willing to face these new challenges.