Einfluss von Bewirtschaftungsmaßnahmen auf die Struktur und Funktion der Bodenmikroflora

Im ökologischen Landbau gilt es unter umweltschonender Bewirtschaftung trotzdem hohe Erträge zu erzielen. Bisher wurde dies durch konventionelle Pflügung realisiert, diese Maßnahme zerstört aber die Bodenstruktur und damit den Lebensraum wichtiger Organismengruppen. Daher ist es wünschenswert die im konventionellen Landbau schon übliche reduzierte Bodenbearbeitung auch im ökologischen Landbau zu etablieren. Im Rahmen dieses Projektes wurde daher untersucht wie sich die reduzierte Bodenbearbeitung auf das Mikrobiom auswirkt. Da Pflügen insbesondere die Bodenstruktur zerstört, lag der besondere Fokus auf dem bakteriellen Potential strukturbildende Substanzen wie Exo-(EPS) und Lipopolysaccharide (LPS) zu produzieren. Dazu wurden vier Standorte mit unterschiedlicher Bodentextur untersucht. Das Potential zur Bildung von EPS/LPS war generell im Pflughorizont am größten. Als Indikatorgene wurden wza für die EPS-Synthese und lptG und lptF für den LPS Transport identifiziert. Während die Abundanz der Gene nicht durch die Bodenbearbeitung beeinflusst wurde, hat sich die Zusammensetzung der Schlüsselorganismen je nach Standort, Tiefe und Bodenbearbeitung unterschieden. Da die strukturbildenden Eigenschaften der Polysaccharide bei jedem Organismus anders sind, können kleine Unterschiede in der mikrobiellen Zusammensetzung zu großen Unterschieden in der Aggregatstabilität führen. So hat sich gezeigt, dass trotz vergleichbarer relativer Genabundanzen schluffiger Boden am sensibelsten auf die Bodenbearbeitung reagiert, mit höheren Werten unter reduzierter Bodenbearbeitung. Die sowieso schon schlechte Aggregierung in sandigen Böden, konnte nicht verbessert werden. Alternativ könnte man hier aber durch reduzierte Bodenbearbeitung die Entwicklung von BBK unterstützen, die wie sich gezeigt hat ein großes Potential für die Speicherung von Nährstoffen haben, als auch die Bildung von EPS/LPS. Interessanterweise haben die Netzwerkanalysen ergeben, dass insbesondere Bakterien, die das Pflanzenwachstum unterstützen wie Micromonapsora und Actinobacteria durch die Bodenbearbeitung beeinflusst werden. Sie akkumulieren im Oberboden bei reduzierter Bearbeitung und unter dem Pflughorizont bei den Pflugvarianten und folgen somit der Wurzelpenetrationstiefe

Engaging the Youngest Readers with Shared Reading Experiences

This article explores Shared Reading as an instructional approach that mimics home reading experiences in a group setting for young children. The article includes information about how to use enlarged text as the teacher provides experiences with books that first focus on the meaning and enjoyment of the story and then shifts to how print works and conventions that enhance the meaning of the story. The importance of being able to see the print in enlarged text that allows the teacher to extend the read aloud experience to include viewing print in big books and charts establishing the beginnings of visual attention to letters, words, and punctuation is examined

TIde: a software for the systematic scanning of drug targets in kinetic network models

<p>Abstract</p> <p>Background</p> <p>During the stages of the development of a potent drug candidate compounds can fail for several reasons. One of them, the efficacy of a candidate, can be estimated <it>in silico </it>if an appropriate ordinary differential equation model of the affected pathway is available. With such a model at hand it is also possible to detect reactions having a large effect on a certain variable such as a substance concentration.</p> <p>Results</p> <p>We show an algorithm that systematically tests the influence of activators and inhibitors of different type and strength acting at different positions in the network. The effect on a quantity to be selected (e.g. a steady state flux or concentration) is calculated. Moreover, combinations of two inhibitors or one inhibitor and one activator targeting different network positions are analysed. Furthermore, we present TIde (Target Identification), an open source, platform independent tool to investigate ordinary differential equation models in the common systems biology markup language format. It automatically assigns the respectively altered kinetics to the inhibited or activated reactions, performs the necessary calculations, and provides a graphical output of the analysis results. For illustration, TIde is used to detect optimal inhibitor positions in simple branched networks, a signalling pathway, and a well studied model of glycolysis in <it>Trypanosoma brucei</it>.</p> <p>Conclusion</p> <p>Using TIde, we show in the branched models under which conditions inhibitions in a certain pathway can affect a molecule concentrations in a different. In the signalling pathway we illuminate which inhibitions have an effect on the signalling characteristics of the last active kinase. Finally, we compare our set of best targets in the glycolysis model with a similar analysis showing the applicability of our tool.</p

BERT WEAVER: Using WEight AVERaging to enable lifelong learning for transformer-based models in biomedical semantic search engines

Recent developments in transfer learning have boosted the advancements in natural language processing tasks. The performance is, however, dependent on high-quality, manually annotated training data. Especially in the biomedical domain, it has been shown that one training corpus is not enough to learn generic models that are able to efficiently predict on new data. Therefore, in order to be used in real world applications state-of-the-art models need the ability of lifelong learning to improve performance as soon as new data are available - without the need of re-training the whole model from scratch. We present WEAVER, a simple, yet efficient post-processing method that infuses old knowledge into the new model, thereby reducing catastrophic forgetting. We show that applying WEAVER in a sequential manner results in similar word embedding distributions as doing a combined training on all data at once, while being computationally more efficient. Because there is no need of data sharing, the presented method is also easily applicable to federated learning settings and can for example be beneficial for the mining of electronic health records from different clinics

Factors That Influence Nitrous Oxide Emissions from Agricultural Soils as Well as Their Representation in Simulation Models: A Review

Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model

Site-Specific Conditions Change the Response of Bacterial Producers of Soil Structure-Stabilizing Agents Such as Exopolysaccarides and Lipopolysaccarides to Tillage Intensity

Agro-ecosystems experience huge losses of land every year due to soil erosion induced by poor agricultural practices such as intensive tillage. Erosion can be minimized by the presence of stable soil aggregates, the formation of which can be promoted by bacteria. Some of these microorganisms have the ability to produce exopolysaccharides and lipopolysaccharides that "glue" soil particles together. However, little is known about the influence of tillage intensity on the bacterial potential to produce these polysaccharides, even though more stable soil aggregates are usually observed under less intense tillage. As the effects of tillage intensity on soil aggregate stability may vary between sites, we hypothesized that the response of polysaccharide-producing bacteria to tillage intensity is also determined by site-specific conditions. To investigate this, we performed a high-throughput shotgun sequencing of DNA extracted from conventionally and reduced tilled soils from three tillage system field trials characterized by different soil parameters. While we confirmed that the impact of tillage intensity on soil aggregates is site-specific, we could connect improved aggregate stability with increased absolute abundance of genes involved in the production of exopolysaccharides and lipopolysaccharides. The potential to produce polysaccharides was generally promoted under reduced tillage due to the increased microbial biomass. We also found that the response of most potential producers of polysaccharides to tillage was site-specific, e.g., Oxalobacteraceae had higher potential to produce polysaccharides under reduced tillage at one site, and showed the opposite response at another site. However, the response of some potential producers of polysaccharides to tillage did not depend on site characteristics, but rather on their taxonomic affiliation, i.e., all members of Actinobacteria that responded to tillage intensity had higher potential for exopolysaccharide and lipopolysaccharide production specifically under reduced tillage. This could be especially crucial for aggregate stability, as polysaccharides produced by different taxa have different "gluing" efficiency. Overall, our data indicate that tillage intensity could affect aggregate stability by both influencing the absolute abundance of genes involved in the production of exopolysaccharides and lipopolysaccharides, as well as by inducing shifts in the community of potential polysaccharide producers. The effects of tillage intensity depend mostly on site-specific conditions

Reservoir Memory Machines as Neural Computers

Differentiable neural computers extend artificial neural networks with an explicit memory without interference, thus enabling the model to perform classic computation tasks such as graph traversal. However, such models are difficult to train, requiring long training times and large datasets. In this work, we achieve some of the computational capabilities of differentiable neural computers with a model that can be trained very efficiently, namely an echo state network with an explicit memory without interference. This extension enables echo state networks to recognize all regular languages, including those that contractive echo state networks provably can not recognize. Further, we demonstrate experimentally that our model performs comparably to its fully-trained deep version on several typical benchmark tasks for differentiable neural computers.Comment: In print at the special issue 'New Frontiers in Extremely Efficient Reservoir Computing' of IEEE TNNL

Marine bacterial inhibitors from the sponge-derived fungus Aspergillus sp

Chromatographic separation of a crude extract obtained from the fungus Aspergillus sp., isolated from the Mediterranean sponge Tethya aurantium, yielded a new tryptophan derived alkaloid, 34(1-hydroxy-3-(2methylbut-3-en-2-y1)-2-oxoindolin-3-yl)methyl)-1-methyl-3,4-dihydrobenzo[e][1,41diazepine-2, 5-dione (1), and a new meroterpenoid, austalide R (2), together with three known compounds (3-5). The structures of the new compounds were unambiguously elucidated on the basis of extensive one and twodimensional NMR (1H, 13C, COSY, HMBC, and ROESY) and mass spectral analysis. Interestingly, the compounds exhibited antibacterial activity when tested against a panel of marine bacteria, with 1 selectively inhibiting Vibrio species and 2 showing a broad spectrum of activity. In contrast, no significant activity was observed against terrestrial bacterial strains and the murine cancer cell line L5178Y. (C) 2014 Elsevier Ltd. All rights reserved.Chemistry, OrganicSCI(E)[email protected]