Association of Caldendrin splice isoforms with secretory vesicles in neurohypophyseal axons and the pituitary

AbstractCaldendrin is a neuronal calcium-binding protein, which is highly enriched in the postsynaptic density fraction and exhibits a prominent somato-dendritic distribution in brain. Two additional splice variants derive from the caldendrin gene, which have unrelated N-termini and were previously only detected in the retina. We now show that these isoforms are present in neurohypophyseal axons and on secretory granules of endocrine cells. In light of the described interaction of the Caldendrin C-terminus with Q-type Cav2.1 calcium channels these data suggest that this interaction takes place in neurohypophyseal axons and pituitary cells indicating functions of the short splice variants in triggering Ca2+ transients to a vesicular target interaction

Finding needles in haystacks:Linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

Fungal Genomes and Insights into the Evolution of the Kingdom

The kingdom Fungi comprises species that inhabit nearly all ecosystems. Fungi exist as both free-living and symbiotic unicellular and multicellular organisms with diverse morphologies. The genomes of fungi encode genes that enable them to thrive in diverse environments, invade plant and animal cells, and participate in nutrient cycling in terrestrial and aquatic ecosystems. The continuously expanding databases of fungal genome sequences have been generated by individual and large-scale efforts such as Génolevures, Broad Institute's Fungal Genome Initiative, and the 1000 Fungal Genomes Project (http://1000.fungalgenomes.org). These efforts have produced a catalog of fungal genes and genomic organization. The genomic datasets can be utilized to better understand how fungi have adapted to their lifestyles and ecological niches. Large datasets of fungal genomic and transcriptomic data have enabled the use of novel methodologies and improved the study of fungal evolution from a molecular sequence perspective. Combined with microscopes, petri dishes, and woodland forays, genome sequencing supports bioinformatics and comparative genomics approaches as important tools in the study of the biology and evolution of fungi

Finding needles in haystacks : linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

Notes for genera: basal clades of Fungi (including Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota)

Compared to the higher fungi (Dikarya), taxonomic and evolutionary studies on the basal clades of fungi are fewer in number. Thus, the generic boundaries and higher ranks in the basal clades of fungi are poorly known. Recent DNA based taxonomic studies have provided reliable and accurate information. It is therefore necessary to compile all available information since basal clades genera lack updated checklists or outlines. Recently, Tedersoo et al. (MycoKeys 13:1--20, 2016) accepted Aphelidiomycota and Rozellomycota in Fungal clade. Thus, we regard both these phyla as members in Kingdom Fungi. We accept 16 phyla in basal clades viz. Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. Thus, 611 genera in 153 families, 43 orders and 18 classes are provided with details of classification, synonyms, life modes, distribution, recent literature and genomic data. Moreover, Catenariaceae Couch is proposed to be conserved, Cladochytriales Mozl.-Standr. is emended and the family Nephridiophagaceae is introduced

Verfahren der digitalen Photogrammetrie bei der Auswertung historischer Luftbilder zur Erfassung von Altlastverdachtsflächen

In dieser Arbeit werden Verfahren und Methoden entwickelt und angewendet, mit deren Hilfe historische Luftbilder für die Erfassung von Altlastverdachtsflächen photogrammetrisch ausgewertet werden können. Diese werden an exemplarisch ausgewähltem Bildmaterial getestet und hinsichtlich der geometrischen Verwendbarkeit der Ergebnisse bewertet. Dabei wird vornehmlich den folgenden Fragen nachgegangen: Mit welchen Hilfsmitteln und Methoden kann ungeeignet erscheinendes Bildmaterial stereoskopisch ausgewertet werden, wie genau sind die Kartierungen im 3D-Stereomodell mit historischem Bildmaterial und in wie weit lassen sich Geländeveränderungen mit Hilfe von Höhenmodellen aus historischen Luftbildern analysieren? Ein Schwerpunkt der Betrachtungen wird auf Kriegsluftbilder gelegt, die aufgrund der Aufnahmetechnik, widriger Aufnahmesituationen und Überlieferungseinflüsse ein Problem für die Verarbeitung mit Verfahren der digitalen Photogrammetrie darstellen

Geospatial data analysis and economic evaluation of companies for sustainable business development

Sustainable business development is connected with environmental impact, natural resources and people. This makes the location a crucial factor for the operation of a business. Therefore, a combination of both geo-spatial data analysis and traditional economic evaluation of companies are advantageous. The consideration of geolocation is beneficial with calculations for process optimizations and cost efficiency as well as ecological and social compliance. Since integrating geospatial methods into economics is a rather new interdisciplinary approach, it seems necessary to establish innovative teaching concepts for the education of experts in this field. Creating and testing such new teaching concepts based on playful learning is the idea behind the ERASMUS+ project SPATIONOMY ("Spatial exploration of economic data — methods of interdisciplinary analytics"). An interdisciplinary team of teachers educates an interdisciplinary assembled group of international students. Hence, the fields of economics/business informatics and geography/geomatics are represented by participants and staff. Based on initial lessons about basic knowledge in the connected subjects, the central elements of the teaching concept are case studies and a simulation game, each with interdisciplinary challenges. The principal aim of the project — to educate students to become specialists in spatial economics — could be achieved. This paper aims to present, evaluate and discuss the methodological approach as well as the results from the application of the simulation game. The results show that the gamification of education is worthy. Simulation game-based learning appears to be more playful and experiential compared to traditional teaching approaches. Further research in this area should focus on the students' engagement evaluation and attitude towards sustainable behaviour in their own business

Combined small- and large-scale geo-spatial analysis of the Ruhr area for an environmental justice assessment

This paper investigates spatial relationships regarding the accessibility of urban green space, the overall yearly vitality of the surrounding vegetation, and additional indicators such as air and noise pollution, in urban areas. The analysis uses socio-economic data sets derived from a sophisticated disaggregation approach. It results from applying a new tool that processes data from coarse and small-scale data sets to smaller spatial units in order to derive more fine-grained insights into the characteristics of the smallest suburb. The consequent data sets are then augmented by comprehensive raster-based accessibility network analysis and the incorporation of measured data on air and noise pollution. Gaining an overview over the whole area on the one hand, and looking at smaller city districts in detail on the other, unveils whether there is an imbalance regarding all combined indicators. After correlating two socio-economic indicators, a spatial comparison of the preliminary results determines whether this approach reveals neighborhoods wherein residents of a lower socio-economic status are exposed to multiple threats at once. As a result, the paper presents a workflow to obtain a broader and, at the same time, more small-scale overview of polycentric agglomeration. Simultaneously, it provides a large-scale insight into single sites, right down to the city block level. Consequently, this study provides a sophisticated approach that helps to assess the quality, quantity and characteristics of the specific spatial distribution of environmental justice in small- to large-scale urban areas at a glance. The results help to identify regions of inequalities and disadvantages. They allow for querying additional values assigned to large-scale spatial units. These versatile variables provide a means to reveal other noticeable indicators. Furthermore, this entails the opportunity to evaluate the distinct living conditions of locally affected demographic groups, and improve them with tailored approaches. Finally, the results can enhance the perception of these living conditions, and be used to promote the capacity for organizing the lives of the respective residents more sustainably, helping the neighborhood to grow accordingly

Geo-spatial analysis of population density and annual income to identify large-scale socio-demographic disparities

This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of these variables to identify locations of imbalance or disparities assisted by bivariate choropleth maps. The aim is to gain a deeper insight into spatial components of socioeconomic nexuses, such as the relationships between the two variables, especially for high-resolution spatial units. The used methodology is able to assist political decision-making, target group advertising in the field of geo-marketing and for the site searches of new shop locations, as well as further socioeconomic research and urban planning. The developed methodology was tested in a national case study in Germany and is easily transferrable to other countries with comparable datasets. The analysis was carried out utilising data about population density and average annual income linked to spatially referenced polygons of postal codes. These were disaggregated initially via a readapted three-class dasymetric mapping approach and allocated to large-scale city block polygons. Univariate and bivariate choropleth maps generated from the resulting datasets were then used to identify and compare spatial economic disparities for a study area in North Rhine-Westphalia (NRW), Germany. Subsequently, based on these variables, a multivariate clustering approach was conducted for a demonstration area in Dortmund. In the result, it was obvious that the spatially disaggregated data allow more detailed insight into spatial patterns of socioeconomic attributes than the coarser data related to postal code polygons