92 research outputs found

    First principles calculation of structural and magnetic properties for Fe monolayers and bilayers on W(110)

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    Structure optimizations were performed for 1 and 2 monolayers (ML) of Fe on a 5 ML W(110) substrate employing the all-electron full-potential linearized augmented plane-wave (FP-LAPW) method. The magnetic moments were also obtained for the converged and optimized structures. We find significant contractions (\sim 10 %) for both the Fe-W and the neighboring Fe-Fe interlayer spacings compared to the corresponding bulk W-W and Fe-Fe interlayer spacings. Compared to the Fe bcc bulk moment of 2.2 μB\mu_B, the magnetic moment for the surface layer of Fe is enhanced (i) by 15% to 2.54 μB\mu_B for 1 ML Fe/5 ML W(110), and (ii) by 29% to 2.84 μB\mu_B for 2 ML Fe/5 ML W(110). The inner Fe layer for 2 ML Fe/5 ML W(110) has a bulk-like moment of 2.3 μB\mu_B. These results agree well with previous experimental data

    Registration of \u27Manska\u27 Pubescent Intermediate Wheatgrass

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    \u27MANSKA\u27 pubescent intermediate wheatgrass [Thinopyrum intermedium subsp. barbulatum (Schur) Barkw. & Dewey] (Reg. no. CV-21, PI 562527) was tested as Mandan 12781 and released 16 April 1992 by the USDA-ARS in cooperation with the USDA-SCS; the Agricultural Research Division, Institute of Agriculture and Natural Resources, University of Nebraska; and the North Agricultural Experiment Station

    Electron correlation effects and magnetic ordering at the Gd(0001) surface

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    Effects of electron correlation on the electronic structure and magnetic properties of the Gd(0001) surface are investigated using of the full-potential linearized augmented plane wave implementation of correlated band theory ("LDA+U"). The use of LDA+U instead of LDA (local density approximation) total energy calculations produces the correct ferromagnetic ground state for both bulk Gd and the Gd surface. Surface strain relaxation leads to an 90 % enhancement of the interlayer surface-to-bulk effective exchange coupling. Application of a Landau-Ginzburg type theory yields a 30 % enhancement of the Curie temperature at the surface, in very good agreement with the experiment.Comment: revised version: minor typos correcte

    Half the story: Thermal effects on within-host infectious disease progression in a warming climate

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    Immune defense is temperature dependent in cold-blooded vertebrates (CBVs) and thus directly impacted by global warming. We examined whether immunity and within-host infectious disease progression are altered in CBVs under realistic climate warming in a seasonal mid-latitude setting. Going further, we also examined how large thermal effects are in relation to the effects of other environmental variation in such a setting (critical to our ability to project infectious disease dynamics from thermal relationships alone). We employed the three-spined stickleback and three ecologically relevant parasite infections as a “wild” model. To generate a realistic climatic warming scenario we used naturalistic outdoors mesocosms with precise temperature control. We also conducted laboratory experiments to estimate thermal effects on immunity and within-host infectious disease progression under controlled conditions. As experimental readouts we measured disease progression for the parasites and expression in 14 immune-associated genes (providing insight into immunophenotypic responses). Our mesocosm experiment demonstrated significant perturbation due to modest warming (+2°C), altering the magnitude and phenology of disease. Our laboratory experiments demonstrated substantial thermal effects. Prevailing thermal effects were more important than lagged thermal effects and disease progression increased or decreased in severity with increasing temperature in an infection-specific way. Combining laboratory-determined thermal effects with our mesocosm data, we used inverse modeling to partition seasonal variation in Saprolegnia disease progression into a thermal effect and a latent immunocompetence effect (driven by nonthermal environmental variation and correlating with immune gene expression). The immunocompetence effect was large, accounting for at least as much variation in Saprolegnia disease as the thermal effect. This suggests that managers of CBV populations in variable environments may not be able to reliably project infectious disease risk from thermal data alone. Nevertheless, such projections would be improved by primarily considering prevailing thermal effects in the case of within-host disease and by incorporating validated measures of immunocompetence

    The role of the EP receptors for prostaglandin E2 in skin and skin cancer

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    One of the most common features of exposure of skin to ultraviolet (UV) light is the induction of inflammation, a contributor to tumorigenesis, which is characterized by the synthesis of cytokines, growth factors and arachidonic acid metabolites, including the prostaglandins (PGs). Studies on the role of the PGs in non-melanoma skin cancer (NMSC) have shown that the cyclooxygenase-2 (COX-2) isoform of the cyclooxygenases is responsible for the majority of the pathological effects of PGE2. In mouse skin models, COX-2 deficiency significantly protects against chemical carcinogen- or UV-induced NMSC while overexpression confers endogenous tumor promoting activity. Current studies are focused on identifying which of the G protein-coupled EP receptors mediate the tumor promotion/progression activities of PGE2 and the signaling pathways involved. As reviewed here, the EP1, EP2, and EP4 receptors, but not the EP3 receptor, contribute to NMSC development, albeit through different signaling pathways and with somewhat different outcomes. The signaling pathways activated by the specific EP receptors are context specific and likely depend on the level of PGE2 synthesis, the differential levels of expression of the different EP receptors, as well as the levels of expression of other interacting receptors. Understanding the role and mechanisms of action of the EP receptors potentially offers new targets for the prevention or therapy of NMSCs

    A time-resolved proteomic and prognostic map of COVID-19

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    COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

    A proteomic survival predictor for COVID-19 patients in intensive care

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    Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

    A time-resolved proteomic and prognostic map of COVID-19

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    COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

    An Overview of the Ethics of Eating and Drinking

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    Eating and drinking are ethical acts. When we make decisions about what to eat and what not to, we are making decisions that impact our own health, the well-being of those who work in the food system, animal welfare, and the environment. Food ethics is the interdisciplinary study of how what we eat – including the way it is produced, distributed, marketed, prepared, and ultimately consumed – impacts human, animal, and planetary health and well-being. Food ethics also analyses the justice or fairness of these impacts. Food ethics raises many difficult questions that do not always have clear or easy answers, such as how do we produce enough food to feed everyone well and equitably; how do we ensure that everyone has access to high-quality, nutritious food that is culturally appropriate; how do we do this in a way that treats workers fairly and respectfully, is considerate of animal welfare, and is environmentally sustainable; and how do we shift power across the food system in favor of the public good over multinational food companies. This chapter will explore these questions and more, hopefully encouraging thoughtful discussions and potential solutions for the future
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