Showing papers by "University of East Anglia published in 2022"
University of Exeter1, Max Planck Institute for Biogeochemistry2, Tyndall Centre3, Atlantic Oceanographic and Meteorological Laboratory4, Bjerknes Centre for Climate Research5, University of Maryland, College Park6, CICERO Center for International Climate Research7, Leibniz Institute for Baltic Sea Research8, University of Reading9, Leibniz Institute of Marine Sciences10, Goddard Space Flight Center11, Flanders Marine Institute12, Food and Agriculture Organization13, Alfred Wegener Institute for Polar and Marine Research14, National Oceanic and Atmospheric Administration15, University of East Anglia16, Japan Meteorological Agency17, ETH Zurich18, National Institute for Environmental Studies19, Karlsruhe Institute of Technology20, Laboratoire des Sciences du Climat et de l'Environnement21, Tula Foundation22, Hertie Institute for Clinical Brain Research23, Nanjing University of Information Science and Technology24, Wageningen University and Research Centre25, Tsinghua University26, University of Western Sydney27, Cooperative Institute for Research in Environmental Sciences28, University of Florida29, Center for Neuroscience and Regenerative Medicine30, Woods Hole Research Center31, Michigan State University32, Tianjin University33, Auburn University34, Jilin Medical University35, Max Planck Institute for Meteorology36, Imperial College London37, Centre National de Recherches Météorologiques38, University of Groningen39, Tohoku University40, Ludwig Maximilian University of Munich41, Bank for International Settlements42, Institut Pierre-Simon Laplace43, Environment Canada44, North West Agriculture and Forestry University45, Northwest A&F University46, Pacific Marine Environmental Laboratory47, Stanford University48, Utrecht University49
TL;DR: Friedlingstein et al. as mentioned in this paper presented and synthesized datasets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including fossil CO2 emissions, land use and land-use change data and bookkeeping models.
Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize datasets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the first time, an approach is shown to reconcile the difference in our ELUC estimate with the one from national greenhouse gas inventories, supporting the assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with fossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of 10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for 2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1, and SLAND was 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The global atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOS relative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).
343 citations
University of Exeter1, Max Planck Institute for Biogeochemistry2, Tyndall Centre3, Leibniz Institute for Baltic Sea Research4, Atlantic Oceanographic and Meteorological Laboratory5, University of Maryland, College Park6, CICERO Center for International Climate Research7, University of Reading8, Leibniz Institute of Marine Sciences9, Goddard Space Flight Center10, Flanders Marine Institute11, Food and Agriculture Organization12, Alfred Wegener Institute for Polar and Marine Research13, Geophysical Institute14, University of Victoria15, National Oceanic and Atmospheric Administration16, Karlsruhe Institute of Technology17, Laboratoire des Sciences du Climat et de l'Environnement18, Japan Meteorological Agency19, Indiana University20, ETH Zurich21, National Institute for Environmental Studies22, University of East Anglia23, European Commission24, Tula Foundation25, Bjerknes Centre for Climate Research26, Hertie Institute for Clinical Brain Research27, Nanjing University of Information Science and Technology28, Ludwig Maximilian University of Munich29, Auburn University30, Wageningen University and Research Centre31, University of Western Sydney32, Cooperative Institute for Research in Environmental Sciences33, Tsinghua University34, University of Florida35, Center for Neuroscience and Regenerative Medicine36, Woods Hole Research Center37, University of Alaska Fairbanks38, Princeton University39, Michigan State University40, University of Washington41, Appalachian State University42, Sun Yat-sen University43, Imperial College London44, University of Groningen45, University of Tennessee46, Washington University in St. Louis47, Jilin Medical University48, Tohoku University49, Rutgers University50, Centre for Research on Ecology and Forestry Applications51, Institut Pierre-Simon Laplace52, North West Agriculture and Forestry University53, Northwest A&F University54, Pacific Marine Environmental Laboratory55, Xi'an Jiaotong University56, Stanford University57, National Center for Atmospheric Research58, University of Edinburgh59, Max Planck Institute for Meteorology60, Utrecht University61, Oak Ridge National Laboratory62
TL;DR: Friedlingstein et al. as mentioned in this paper presented and synthesized data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties, including fossil CO2 emissions, land use and land-use change data and bookkeeping models.
Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).
98 citations
University of Wuppertal1, Kafrelsheikh University2, King Abdulaziz University3, University of Thessaly4, COMSATS Institute of Information Technology5, University of Hong Kong6, Cairo University7, China Agricultural University8, University of Agriculture, Faisalabad9, Egyptian Petroleum Research Institute10, Hanyang University11, University of East Anglia12, University of Auckland13, Sejong University14
TL;DR: In this paper, a comprehensive review of rice biochar (RBC) and rice compost (RC) applications with respect to preparation and characterization is presented, with a focus on the potential for the sustainable use of RBC and RC in the management of contaminated soils and water as well as the construction industry.
Abstract: Rice is second only to maize among the world's most important cereal crops, with a global harvested area of approximately 158 million hectares and an annual production of more than 700 million tonnes as paddy rice. At this scale, rice production generates vast amounts of waste in the form of straw, husk, and bran. Because of high cellulose, lignin, and silica contents, rice biowaste (RB) can be used to produce rice biochar (RBC) and rice compost (RC). Furthermore, RB can be used as sorbents, soil conditioners, bricks/concrete blocks, flat steel products, and biofuels, all of which make significant contributions to meeting United Nations Sustainable Development Goals (UNSDGs). Although previous reviews have explored individual applications of rice feedstocks, inadequate attention has been paid to multifunctional values and potential multi-utilities. Here, we offer a comprehensive review of RBC and RC with respect to: (1) preparation and characterization; (2) applications as soil conditioners and organic fertilizers and their effects on soil-carbon sequestration; (3) remediation of toxic element–contaminated soils and water; (4) removal of colors, dyes, endocrine-disrupting chemicals, personal-care products, and residual pesticides from water; and (5) applications in the construction industry. Specifically, we describe the opportunities for the sustainable use of RBC and RC in the management of contaminated soils and water as well as the construction industry. Overall, this review is expected to lengthen the list of possible multifunctional applications of RBC and RC.
56 citations
TL;DR: In this article, the authors investigate country-level trade resilience during the 1st wave of the pandemic, by employing Fuzzy-set Qualitative Comparative Analysis (fsQCA).
49 citations
TL;DR: In this paper, a convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel.
Abstract: Structural health monitoring for lightweight complex composite structures is being investigated in this paper with a data-driven deep learning approach to facilitate automated learning of the map of transformed signal features to damage classes. Towards this, a series of acoustic emission (AE) based laboratory experiments have been carried out on a composite sample using a piezoelectric AE sensor network. The registered time-domain AE signals from the assigned sensor networks on the composite panel are processed with the continuous wavelet transform to extract time-frequency scalograms. A convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel. The proposed deep-learning approach has shown an effective damage monitoring potential with high training, validation and test accuracy for unseen datasets as well as for entirely new neighboring damage datasets. Further, the proposed network is trained, validated and tested only for the peak-signal data extracted from the raw AE data. The application of peak-signal scalogram data has shown a significant improvement in damage-source classification performance with high training, validation and test accuracy.
31 citations
TL;DR: The determination of chlorinated paraffins (CPs) has posed an intractable challenge in analytical chemistry for over three decades as discussed by the authors, and recent advances in instrumentation (mass spectrometric detectors and nuclear magnetic resonance), combined with interlaboratory studies, have allowed a better insight into the nature of the conundrums.
26 citations
TL;DR: In this article, a compact model was developed to predict the PV temperature Tpv, coefficient f which relates TpV with the in-plane solar irradiance IT, and power output Pm with relative error 1.9% for PV operating near its nominal value.
24 citations
TL;DR: In this paper, the authors focus on how utilities have changed their business model to adapt to the emergence of sustainable energy innovations in the energy system and which value creation drivers they draw on.
18 citations
TL;DR: In this paper , the authors examined the influence of BEVs generated by the gut commensal bacterium, Bacteroides thetaiotaomicron, on host immune cells.
Abstract: The gastrointestinal (GI) tract harbours a complex microbial community, which contributes to its homeostasis. A disrupted microbiome can cause GI-related diseases, including inflammatory bowel disease (IBD), therefore identifying host-microbe interactions is crucial for better understanding gut health. Bacterial extracellular vesicles (BEVs), released into the gut lumen, can cross the mucus layer and access underlying immune cells. To study BEV-host interactions, we examined the influence of BEVs generated by the gut commensal bacterium, Bacteroides thetaiotaomicron, on host immune cells. Single-cell RNA sequencing data and host-microbe protein-protein interaction networks were used to predict the effect of BEVs on dendritic cells, macrophages and monocytes focusing on the Toll-like receptor (TLR) pathway. We identified biological processes affected in each immune cell type and cell-type specific processes including myeloid cell differentiation. TLR pathway analysis highlighted that BEV targets differ among cells and between the same cells in healthy versus disease (ulcerative colitis) conditions. The in silico findings were validated in BEV-monocyte co-cultures demonstrating the requirement for TLR4 and Toll-interleukin-1 receptor domain-containing adaptor protein (TIRAP) in BEV-elicited NF-kB activation. This study demonstrates that both cell-type and health status influence BEV-host communication. The results and the pipeline could facilitate BEV-based therapies for the treatment of IBD.
17 citations
TL;DR: This paper found that the majority of students actively engaged with this integrated approach and that it effectively promoted students' behavioural, affective, and cognitive engagement with feedback on their writing and encouraged thoughtful revisions.
16 citations
TL;DR: In this article, a stable and efficient photo-driven electrochemical desalination technique without any external bias is proposed, where two salt streams are sandwiched between the photoanode and cathode, and salt ions in desalted stream are continuously extracted by the redox reaction of I-/I3- electrolyte at their respective electrode chambers.
TL;DR: In this paper, the authors make two contributions to the COVID-related green recovery literature, which is dominated by optimistic and speculative opportunity narratives, and suggest that green recovery analyses should focus not only on the opportunities (permissive conditions) created by the crisis, but also on the actions and strategic considerations (productive conditions) and pre-existing contexts (critical antecedents) that shape the exploitation of these opportunities.
Abstract: This article makes two contributions to the COVID-related green recovery literature, which is dominated by optimistic and speculative opportunity narratives. Mobilising insights from political science theories, our conceptual contribution is to suggest that green recovery analyses should focus not only on the opportunities (‘permissive conditions’) created by the COVID-crisis, but also on the actions and strategic considerations (‘productive conditions’) and pre-existing contexts (‘critical antecedents’) that shape the exploitation of these opportunities. Our empirical contribution is to analyse actual green recovery spending plans of three leading countries (France, Germany, and the UK), focusing on the size, sectoral allocation, and implementation choices, which differ markedly. France spends the most, both in absolute and GDP-relative terms, followed by Germany. UK spending is 43% less than France. The UK and France mostly support existing sectors (buildings, railways), while Germany focuses 57.8% of its funding on new technologies (electric vehicles, hydrogen). We explain country differences by analysing different mixes of strategic considerations, including climate mitigation, jobs, GDP growth, productivity, exports, global competitiveness, regional support, social fairness, party politics, and electoral ambitions. We relate these different motivations to pre-existing context conditions such as varying socio-economic effects of the COVID-crisis, pre-existing concerns (e.g., high unemployment, social and regional inequalities), the economic importance of particular sectors, and pre-existing climate policy plans. We conclude that the green recovery plans are powerfully shaped by pre-existing contexts, plans and developments, which constrain the use of the crisis-induced opportunities.
TL;DR: In this article , it was shown that 3D structured optical vortices which possess the phase factor $exp(il\phi)$ have a contribution to the optical helicity density which is completely independent of polarization.
Abstract: Recently arXiv:2004.02970 showed that the extraordinary transverse spin momentum density of spatially confined optical fields is largely independent of polarization. Here it is shown that 3D structured optical vortices which possess the phase factor $exp(il\phi)$ have a contribution to the optical helicity density which is completely independent of polarization. In stark contrast to what is known in classical optics with plane waves and paraxial light, the physical consequence is that unpolarized light can exhibit optical activity and chiral light-matter interactions.
TL;DR: In this article, the authors investigated the possibility of using unmodified biochar derived from rice husk (RB) and aspen wood (WB) at 400°C and 700°C to enhance the precipitation of calcium/arsenic compounds for the removal of As(III) from solution.
Nagoya City University1, National Cancer Center2, Luxembourg Institute of Health3, University Hospital Waterford4, University of East Anglia5, University of Toronto6, University of Chile7, Maastricht University8, Brigham and Women's Hospital9, University of Calgary10, University of British Columbia11, Katholieke Universiteit Leuven12
TL;DR: In this paper , the authors examined international incidence trends of lung, colorectal, prostate, and breast cancers, as well as all cancers combined excluding non-melanoma skin cancer (NMSC) in adults aged 50 and older, over a fifteen-year period using data from 113 high quality population-based cancer registries included in the Cancer in Five Continents (CI5) series and NORDCAN.
TL;DR: In this paper , a systematic review and meta-analysis sought to estimate the point prevalence of current PTSD-DS, and the extent to which method of assessment, demographic and trauma variables moderate this estimate, across different methods of prevalence estimation.
Abstract: The dissociative subtype of post-traumatic stress disorder (PTSD-DS) was introduced in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), and is characterised by symptoms of either depersonalisation or derealisation, in addition to a diagnosis of post-traumatic stress disorder (PTSD). This systematic review and meta-analysis sought to estimate the point prevalence of current PTSD-DS, and the extent to which method of assessment, demographic and trauma variables moderate this estimate, across different methods of prevalence estimation. Studies included were identified by searching MEDLINE (EBSCO), PsycInfo, CINAHL, Academic Search Complete and PTSDpubs, yielding 49 studies that met the inclusion criteria (N = 8214 participants). A random-effects meta-analysis estimated the prevalence of PTSD-DS as 38.1% (95% CI 31.5-45.0%) across all samples, 45.5% (95% CI 37.7-53.4%) across all diagnosis-based and clinical cut-off samples, 22.8% (95% CI 14.8-32.0%) across all latent class analysis (LCA) and latent profile analysis (LPA) samples and 48.1% (95% CI 35.0-61.3%) across samples which strictly used the DSM-5 PTSD criteria; all as a proportion of those already with a diagnosis of PTSD. All results were characterised by high levels of heterogeneity, limiting generalisability. Moderator analyses mostly failed to identify sources of heterogeneity. PTSD-DS was more prevalent in children compared to adults, and in diagnosis-based and clinical cut-off samples compared to LCA and LPA samples. Risk of bias was not significantly related to prevalence estimates. The implications of these results are discussed further.
TL;DR: In this paper , the authors compared the characteristics of PEUGIC and detected upper gastrointestinal cancers (PEUGIC) using random effects meta-analysis, and found that PEUGI patients were typically smaller at diagnosis and associated with less advanced disease staging compared with detected cancers.
TL;DR: In this paper , the authors show that the GRC has the potential to be paternally inherited in the zebra finch (Taeniopygia guttata castanotis).
Abstract: Songbirds have one special accessory chromosome, the so-called germline-restricted chromosome (GRC), which is only present in germline cells and absent from all somatic tissues. Earlier work on the zebra finch (Taeniopygia guttata castanotis) showed that the GRC is inherited only through the female line-like the mitochondria-and is eliminated from the sperm during spermatogenesis. Here, we show that the GRC has the potential to be paternally inherited. Confocal microscopy using GRC-specific fluorescent in situ hybridization probes indicated that a considerable fraction of sperm heads (1 to 19%) in zebra finch ejaculates still contained the GRC. In line with these cytogenetic data, sequencing of ejaculates revealed that individual males from two families differed strongly and consistently in the number of GRCs in their ejaculates. Examining a captive-bred male hybrid of the two zebra finch subspecies (T. g. guttata and T. g. castanotis) revealed that the mitochondria originated from a castanotis mother, whereas the GRC came from a guttata father. Moreover, analyzing GRC haplotypes across nine castanotis matrilines, estimated to have diverged for up to 250,000 y, showed surprisingly little variability among GRCs. This suggests that a single GRC haplotype has spread relatively recently across all examined matrilines. A few diagnostic GRC mutations that arose since this inferred spreading suggest that the GRC has continued to jump across matriline boundaries. Our findings raise the possibility that certain GRC haplotypes could selfishly spread through the population via occasional paternal transmission, thereby outcompeting other GRC haplotypes that were limited to strict maternal inheritance, even if this was partly detrimental to organismal fitness.
TL;DR: In this paper , the authors highlight enantioselective optical gradient forces present in 3D structured optical vortex tweezing systems, where one chiral force originates from the circular polarization of the light, while the other is independent of the input polarization and is not present in 2D structured light nor propagating plane waves.
TL;DR: In this paper , three-dimensional imaging of waves from a moving vessel and simultaneous imaging of floe sizes are reported, with the potential to enhance the marginal ice zone database substantially.
Abstract: Abstract The marginal ice zone is the dynamic interface between the open ocean and consolidated inner pack ice. Surface gravity waves regulate marginal ice zone extent and properties, and, hence, atmosphere-ocean fluxes and ice advance/retreat. Over the past decade, seminal experimental campaigns have generated much needed measurements of wave evolution in the marginal ice zone, which, notwithstanding the prominent knowledge gaps that remain, are underpinning major advances in understanding the region’s role in the climate system. Here, we report three-dimensional imaging of waves from a moving vessel and simultaneous imaging of floe sizes, with the potential to enhance the marginal ice zone database substantially. The images give the direction–frequency wave spectrum, which we combine with concurrent measurements of wind speeds and reanalysis products to reveal the complex multi-component wind-plus-swell nature of a cyclone-driven wave field, and quantify evolution of large-amplitude waves in sea ice.
TL;DR: In this paper , the authors used two guide RNAs to effectively 'drop out' a miRNA and compared the results to morpholino knockdown (KD) of the same miRNAs.
TL;DR: This article found that ERN2 was required for microbiota-induced goblet cell maturation and mucus barrier assembly in the colon, which occurred only after colonization of the alimentary tract with normal gut microflora, which induced Ern2 expression.
Abstract: Epithelial cells lining mucosal surfaces of the gastrointestinal and respiratory tracts uniquely express ERN2/IRE1β, a paralogue of the most evolutionarily conserved endoplasmic reticulum stress sensor, ERN1/IRE1α. How ERN2 functions at the host-environment interface and why a second paralogue evolved remain incompletely understood. Using conventionally raised and germ-free Ern2-/- mice, we found that ERN2 was required for microbiota-induced goblet cell maturation and mucus barrier assembly in the colon. This occurred only after colonization of the alimentary tract with normal gut microflora, which induced Ern2 expression. ERN2 acted by splicing Xbp1 mRNA to expand ER function and prevent ER stress in goblet cells. Although ERN1 can also splice Xbp1 mRNA, it did not act redundantly to ERN2 in this context. By regulating assembly of the colon mucus layer, ERN2 further shaped the composition of the gut microbiota. Mice lacking Ern2 had a dysbiotic microbial community that failed to induce goblet cell development and increased susceptibility to colitis when transferred into germ-free WT mice. These results show that ERN2 evolved at mucosal surfaces to mediate crosstalk between gut microbes and the colonic epithelium required for normal homeostasis and host defense.
TL;DR: In this article, a review discusses published occurrences of 134Cs and 137Cs in twenty four species of Tricholoma mushrooms sourced from the Northern Hemisphere over the last five decades, but also includes some recent data from Italy and Poland.
TL;DR: In this article , the authors analyzed 11883 mtDNA sequences from 18 taxonomic sub-groups and identified their frequency and location within mtDNA and found that quadruplex-forming sequences (PQS) were overrepresented in the 3'UTRs, D-loops, replication origins, and stem loops, indicating regulatory roles for quadruplexes in mtDNA.
TL;DR: In this paper , the authors measured the spatial extent of significant wave height attenuation in sea ice from variations in ICESat-2 surface heights and found that sea-ice-concentration-derived MIZ width estimates are far narrower than those from the new technique presented here.
Abstract: Abstract. The Antarctic marginal ice zone (MIZ) is a highly dynamic region where sea ice interacts with ocean surface waves generated in ice-free areas of the Southern Ocean. Improved large-scale (satellite-based) estimates of MIZ extent and variability are crucial for understanding atmosphere–ice–ocean interactions and biological processes and detection of change therein. Legacy methods for defining the MIZ are typically based on sea ice concentration thresholds and do not directly relate to the fundamental physical processes driving MIZ variability. To address this, new techniques have been developed to measure the spatial extent of significant wave height attenuation in sea ice from variations in Ice, Cloud and land Elevation Satellite-2 (ICESat-2) surface heights. The poleward wave penetration limit (boundary) is defined as the location where significant wave height attenuation equals the estimated error in significant wave height. Extensive automated and manual acceptance/rejection criteria are employed to ensure confidence in along-track wave penetration width estimates due to significant cloud contamination of ICESat-2 data or where wave attenuation is not observed. Analysis of 304 ICESat-2 tracks retrieved from four months of 2019 (February, May, September and December) reveals that sea-ice-concentration-derived MIZ width estimates are far narrower (by a factor of ∼ 7 on average) than those from the new technique presented here. These results suggest that indirect methods of MIZ estimation based on sea ice concentration are insufficient for representing physical processes that define the MIZ. Improved large-scale measurements of wave attenuation in the MIZ will play an important role in increasing our understanding of this complex sea ice zone.
TL;DR: In this paper, the authors investigated the challenges for the road freight transition are principally political and socio-technical, and opportunities are identified to further explore these through future research, and revealed a range of themes and relevant issues which underline the complexity of this transition.
Abstract: Road freight represents approximately 8.5% of UK carbon emissions and therefore must be abated if the UK government’s objective to reach net zero carbon emissions by 2050 is to be achieved. While several technology options exist, it is commonly viewed as a hard-to-abate sector and progress to decarbonisation remains slow. Whereas techno-economic aspects of the low carbon transition of road freight are well studied, socio-technical and political aspects are much less so. This is in contrast with substantial socio-technical literature focused on the transition of passenger vehicles. Symptomatic of this, there is little direct engagement in research with freight industry operators and participants. This study seeks to address these gaps by considering the views of these key actors through qualitative social science research. Fifteen semi-structured interviews were undertaken with key stakeholders within the road freight industry. These revealed a range of themes and relevant issues which underline the complexity of this transition. Further analysis of the data revealed six overarching viewpoints that reflect the primary concerns of the expert interviewees. These viewpoints suggest that the challenges for the road freight transition are principally political and socio-technical, and opportunities are identified to further explore these through future research.
TL;DR: In this paper, the authors present a proficiency testing scheme for polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecanes (HBCDDs).
TL;DR: In this article , the authors identify the BET protein family, and Brd4 in particular, as novel regulators of basal and D1R-dependent transcription in rat striatal neurons, and delineate complex bi-directional effects of bromodomain inhibitors on neuronal transcription.
TL;DR: In this article, a single nucleotide polymorphism (SNP) genotyping panel was developed from whole-genome resequencing data that enables targeted species identification in Tanzania.