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Institution

University of Hohenheim

EducationStuttgart, Germany
About: University of Hohenheim is a education organization based out in Stuttgart, Germany. It is known for research contribution in the topics: Population & Soil water. The organization has 8585 authors who have published 16406 publications receiving 567377 citations.


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Journal ArticleDOI
TL;DR: Data is reported on for amino acid composition, fatty acid profile, vitamin K, iodine, kainic acid, inorganic arsenic, as well as for various heavy metals in samples from Denmark, Iceland, and Maine.
Abstract: The red seaweed dulse (Palmaria palmata) is one of the more popular seaweed species for human consumption in the Western world. With a documented historical use up to present days in Ireland, Brittany (France), Iceland, Maine (USA), and Nova Scotia (Canada), it has remained a snack, a food supplement, and an ingredient in various dishes. The trend towards more healthy and basic foodstuffs, together with an increasing interest among chefs for the seaweed cuisine, has posed the need for more quantitative knowledge about the chemical composition of dulse of relevance for human consumption. Here, we report on data for amino acid composition, fatty acid profile, vitamin K, iodine, kainic acid, inorganic arsenic, as well as for various heavy metals in samples from Denmark, Iceland, and Maine.

147 citations

Journal ArticleDOI
TL;DR: Results are indicative of a specific interplay of a distinct pheromone component with an appropriate binding protein and its related receptor subtype, which may be considered as basis for the remarkable sensitivity and specificity of the phersomone detection system.
Abstract: Male moths respond to conspecific female-released pheromones with remarkable sensitivity and specificity, due to highly specialized chemosensory neurons in their antennae. In Antheraea silkmoths, three types of sensory neurons have been described, each responsive to one of three pheromone components. Since also three different pheromone binding proteins (PBPs) have been identified, the antenna of Antheraea seems to provide a unique model system for detailed analyzes of the interplay between the various elements underlying pheromone reception. Efforts to identify pheromone receptors of Antheraea polyphemus have led to the identification of a candidate pheromone receptor (ApolOR1). This receptor was found predominantly expressed in male antennae, specifically in neurons located beneath pheromone-sensitive sensilla trichodea. The ApolOR1-expressing cells were found to be surrounded by supporting cells co-expressing all three ApolPBPs. The response spectrum of ApolOR1 was assessed by means of calcium imaging using HEK293-cells stably expressing the receptor. It was found that at nanomolar concentrations ApolOR1-cells responded to all three pheromones when the compounds were solubilized by DMSO and also when DMSO was substituted by one of the three PBPs. However, at picomolar concentrations, cells responded only in the presence of the subtype ApolPBP2 and the pheromone (E,Z)-6,11-hexadecadienal. These results are indicative of a specific interplay of a distinct pheromone component with an appropriate binding protein and its related receptor subtype, which may be considered as basis for the remarkable sensitivity and specificity of the pheromone detection system.

147 citations

Journal ArticleDOI
Abstract: High-quality data from appropriate archives are needed for the continuing improvement of radiocarbon cali- bration curves. We discuss here the basic assumptions behind 14C dating that necessitate calibration and the relative strengths and weaknesses of archives from which calibration data are obtained. We also highlight the procedures, problems, and uncer- tainties involved in determining atmospheric and surface ocean 14C/12C in these archives, including a discussion of the vari- ous methods used to derive an independent absolute timescale and uncertainty. The types of data required for the current IntCal database and calibration curve model are tabulated with examples.

146 citations

Journal ArticleDOI
Ashis Saha1, Yungil Kim1, Ariel D. H. Gewirtz2, Brian Jo2  +256 moreInstitutions (49)
TL;DR: These networks are built that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues, and provide an improved understanding of the complex relationships of the human transcriptome across tissues.
Abstract: Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.

146 citations

Journal ArticleDOI
01 Feb 2020
TL;DR: Different genomic approaches that can be used to investigate and predict species responses to GCC are discussed and can serve as guidance for researchers looking for the appropriate experimental setup for their particular system.
Abstract: Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

146 citations


Authors

Showing all 8665 results

NameH-indexPapersCitations
Robert J. Lefkowitz214860147995
Patrick O. Brown183755200985
Mark Stitt13245660800
Wolf B. Frommer10534530918
Muhammad Imran94305351728
Muhammad Farooq92134137533
Yakov Kuzyakov8766737050
Werner Goebel8536726106
Ismail Cakmak8424925991
Reinhold Carle8441824858
Michael Wink8393832658
Albrecht E. Melchinger8339823140
Tilman Grune8247930327
Volker Römheld7923120763
Klaus Becker7932027494
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202344
2022161
20211,045
2020954
2019868
2018802