SHORT-RUN DEMAND RELATIONSHIPS IN THE U.S. FATS AND OILS COMPLEX

Fats and oils play a prominent role in U.S. dietary patterns. Recent concerns over the negative health consequences associated with fats and oils have led many to suspect structural change in demand conditions. We consider short run (monthly) demand relationships for edible fats and oils. In that monthly quantities of fats and oils are likely to be relatively fixed, we utilize an inverse AIDS specification. Our analysis consists of two components. In the first, we utilize a smooth transition function to model a switching inverse almost ideal demand system (IAIDS) that assesses short-run demand conditions for edible fats and oils in the U.S. Our results suggest that short-run demand conditions for fats and oils experienced a rather rapid structural shift in the early 1990s. Although this shift generally made price flexibilities more elastic, differences in flexibilities across regimes are modest in most cases. Our results suggest that decreases in marginal valuations for most fats and oils in response to consumption increases are rather small. Scale flexibilities are relatively close to -1, suggesting near homothetic preferences for fats and oils. An important distinction occurs for lard and tallow, which exhibit a very elastic scale response. This suggests that scale increases in the consumption of edible fats and oils will significantly decrease consumers' marginal valuation of these animal fats. A second segment of our analysis considers dynamic extensions to the IAIDS model that recognize habit effects. Although nested hypothesis testing supports the dynamic specification over the static IAIDS model, price and scale flexibilities are quite similar to the static case.Demand and Price Analysis,

Simulating Root Growth as a Function of Soil Strength and Yield With a Field-Scale Crop Model Coupled With a 3D Architectural Root Model

Accurate prediction of root growth and related resource uptake is crucial to accurately simulate crop growth especially under unfavorable environmental conditions. We coupled a 1D field-scale crop-soil model running in the SIMPLACE modeling framework with the 3D architectural root model CRootbox on a daily time step and implemented a stress function to simulate root elongation as a function of soil bulk density and matric potential. The model was tested with field data collected during two growing seasons of spring barley and winter wheat on Haplic Luvisol. In that experiment, mechanical strip-wise subsoil loosening (30–60 cm) (DL treatment) was tested, and effects on root and shoot growth at the melioration strip as well as in a control treatment were evaluated. At most soil depths, strip-wise deep loosening significantly enhanced observed root length densities (RLDs) of both crops as compared to the control. However, the enhanced root growth had a beneficial effect on crop productivity only in the very dry season in 2018 for spring barley where the observed grain yield at the strip was 18% higher as compared to the control. To understand the underlying processes that led to these yield effects, we simulated spring barley and winter wheat root and shoot growth using the described field data and the model. For comparison, we simulated the scenarios with the simpler 1D conceptual root model. The coupled model showed the ability to simulate the main effects of strip-wise subsoil loosening on root and shoot growth. It was able to simulate the adaptive plasticity of roots to local soil conditions (more and thinner roots in case of dry and loose soil). Additional scenario runs with varying weather conditions were simulated to evaluate the impact of deep loosening on yield under different conditions. The scenarios revealed that higher spring barley yields in DL than in the control occurred in about 50% of the growing seasons. This effect was more pronounced for spring barley than for winter wheat. Different virtual root phenotypes were tested to assess the potential of the coupled model to simulate the effect of varying root traits under different conditions.Peer Reviewe

Root system markup language: toward an unified root architecture description language

The number of image analysis tools supporting the extraction of architectural features of root systems has increased over the last years. These tools offer a handy set of complementary facilities, yet it is widely accepted that none of these software tool is able to extract in an efficient way growing array of static and dynamic features for different types of images and species. We describe the Root System Markup Language (RSML) that has been designed to overcome two major challenges: (i) to enable portability of root architecture data between different software tools in an easy and interoperable manner allowing seamless collaborative work, and (ii) to provide a standard format upon which to base central repositories which will soon arise following the expanding worldwide root phenotyping effort. RSML follows the XML standard to store 2D or 3D image metadata, plant and root properties and geometries, continuous functions along individual root paths and a suite of annotations at the image, plant or root scales, at one or several time points. Plant ontologies are used to describe botanical entities that are relevant at the scale of root system architecture. An xml-schema describes the features and constraints of RSML and open-source packages have been developed in several languages (R, Excel, Java, Python, C#) to enable researchers to integrate RSML files into popular research workflow

Within-host evolution of SARS-CoV-2 in an immunosuppressed COVID-19 patient as a source of immune escape variants.

The origin of SARS-CoV-2 variants of concern remains unclear. Here, we test whether intra-host virus evolution during persistent infections could be a contributing factor by characterizing the long-term SARS-CoV-2 infection dynamics in an immunosuppressed kidney transplant recipient. Applying RT-qPCR and next-generation sequencing (NGS) of sequential respiratory specimens, we identify several mutations in the viral genome late in infection. We demonstrate that a late viral isolate exhibiting genome mutations similar to those found in variants of concern first identified in UK, South Africa, and Brazil, can escape neutralization by COVID-19 antisera. Moreover, infection of susceptible mice with this patient's escape variant elicits protective immunity against re-infection with either the parental virus and the escape variant, as well as high neutralization titers against the alpha and beta SARS-CoV-2 variants, B.1.1.7 and B.1.351, demonstrating a considerable immune control against such variants of concern. Upon lowering immunosuppressive treatment, the patient generated spike-specific neutralizing antibodies and resolved the infection. Our results suggest that immunocompromised patients could be a source for the emergence of potentially harmful SARS-CoV-2 variants

KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models. I. review and model concept

The relatively poor simulation of the below-ground processes is a severe drawback for many ecosystem models, especially when predicting responses to climate change and management. For a meaningful estimation of ecosystem production and the cycling of water, energy, nutrients and carbon, the integration of soil processes and the exchanges at the surface is crucial. It is increasingly recognized that soil biota play an important role in soil organic carbon and nutrient cycling, shaping soil structure and hydrological properties through their activity, and in water and nutrient uptake by plants through mycorrhizal processes. In this article, we review the main soil biological actors (microbiota, fauna and roots) and their effects on soil functioning. We review to what extent they have been included in soil models and propose which of them could be included in ecosystem models. We show that the model representation of the soil food web, the impact of soil ecosystem engineers on soil structure and the related effects on hydrology and soil organic matter (SOM) stabilization are key issues in improving ecosystem-scale soil representation in models. Finally, we describe a new core model concept (KEYLINK) that integrates insights from SOM models, structural models and food web models to simulate the living soil at an ecosystem scale

Mechanistic framework to link root growth models with weather and soil physical properties, including example applications to soybean growth in Brazil

Background and aimsRoot elongation is generally limited by a combination of mechanical impedance and water stress in most arable soils. However, dynamic changes of soil penetration resistance with soil water content are rarely included in models for predicting root growth. Better modelling frameworks are needed to understand root growth interactions between plant genotype, soil management, and climate. Aim of paper is to describe a new model of root elongation in relation to soil physical characteristics like penetration resistance, matric potential, and hypoxia.MethodsA new diagrammatic framework is proposed to illustrate the interaction between root elongation, soil management, and climatic conditions. The new model was written in Matlab®, using the root architecture model RootBox and a model that solves the 1D Richards equations for water flux in soil. Inputs: root architectural parameters for Soybean; soil hydraulic properties; root water uptake function in relation to matric flux potential; root elongation rate as a function of soil physical characteristics. Simulation scenarios: (a) compact soil layer at 16 to 20 cm; (b) test against a field experiment in Brazil during contrasting drought and normal rainfall seasons.Results(a) Soil compaction substantially slowed root growth into and below the compact layer. (b) Simulated root length density was very similar to field measurements, which was influenced greatly by drought. The main factor slowing root elongation in the simulations was evaluated using a stress reduction function.ConclusionThe proposed framework offers a way to explore the interaction between soil physical properties, weather and root growth. It may be applied to most root elongation models, and offers the potential to evaluate likely factors limiting root growth in different soils and tillage regimes

Proceedings of the 4th bwHPC Symposium

The bwHPC Symposium 2017 took place on October 4th, 2017, Alte Aula, Tübingen. It focused on the presentation of scientific computing projects as well as on the progress and the success stories of the bwHPC realization concept. The event offered a unique opportunity to engage in an active dialogue between scientific users, operators of bwHPC sites, and the bwHPC support team

Protist-Type Lysozymes of the Nematode Caenorhabditis elegans Contribute to Resistance against Pathogenic Bacillus thuringiensis

Pathogens represent a universal threat to other living organisms. Most organisms express antimicrobial proteins and peptides, such as lysozymes, as a protection against these challenges. The nematode Caenorhabditis elegans harbours 15 phylogenetically diverse lysozyme genes, belonging to two distinct types, the protist- or Entamoeba-type (lys genes) and the invertebrate-type (ilys genes) lysozymes. In the present study we characterized the role of several protist-type lysozyme genes in defence against a nematocidal strain of the Gram-positive bacterium Bacillus thuringiensis. Based on microarray and subsequent qRT-PCR gene expression analysis, we identified protist-type lysozyme genes as one of the differentially transcribed gene classes after infection. A functional genetic analysis was performed for three of these genes, each belonging to a distinct evolutionary lineage within the protist-type lysozymes (lys-2, lys-5, and lys-7). Their knock-out led to decreased pathogen resistance in all three cases, while an increase in resistance was observed when two out of three tested genes were overexpressed in transgenic lines (lys-5, lys-7, but not lys-2). We conclude that the lysozyme genes lys-5, lys-7, and possibly lys-2 contribute to resistance against B. thuringiensis, thus highlighting the particular role of lysozymes in the nematode's defence against pathogens

Improving Cry8Ka toxin activity towards the cotton boll weevil (Anthonomus grandis)

<p>Abstract</p> <p>Background</p> <p>The cotton boll weevil (<it>Anthonomus grandis</it>) is a serious insect-pest in the Americas, particularly in Brazil. The use of chemical or biological insect control is not effective against the cotton boll weevil because of its endophytic life style. Therefore, the use of biotechnological tools to produce insect-resistant transgenic plants represents an important strategy to reduce the damage to cotton plants caused by the boll weevil. The present study focuses on the identification of novel molecules that show improved toxicity against the cotton boll weevil. <it>In vitro </it>directed molecular evolution through DNA shuffling and phage display screening was applied to enhance the insecticidal activity of variants of the Cry8Ka1 protein of <it>Bacillus thuringiensis</it>.</p> <p>Results</p> <p>Bioassays carried out with <it>A. grandis </it>larvae revealed that the LC₅₀of the screened mutant Cry8Ka5 toxin was 3.15-fold higher than the wild-type Cry8Ka1 toxin. Homology modelling of Cry8Ka1 and the Cry8Ka5 mutant suggested that both proteins retained the typical three-domain Cry family structure. The mutated residues were located mostly in loops and appeared unlikely to interfere with molecular stability.</p> <p>Conclusions</p> <p>The improved toxicity of the Cry8Ka5 mutant obtained in this study will allow the generation of a transgenic cotton event with improved potential to control <it>A. grandis</it>.</p

Measurement of b jet shapes in proton-proton collisions at root s=5.02 TeV

We present the first study of charged-hadron production associated with jets originating from b quarks in proton-proton collisions at a center-of-mass energy of 5.02 TeV. The data sample used in this study was collected with the CMS detector at the CERN LHC and corresponds to an integrated luminosity of 27.4 pb(-1). To characterize the jet substructure, the differential jet shapes, defined as the normalized transverse momentum distribution of charged hadrons as a function of angular distance from the jet axis, are measured for b jets. In addition to the jet shapes, the per-jet yields of charged particles associated with b jets are also quantified, again as a function of the angular distance with respect to the jet axis. Extracted jet shape and particle yield distributions for b jets are compared with results for inclusive jets, as well as with the predictions from the pythia and herwig++ event generators.Peer reviewe