ALBERT

Description: The marine environment encompasses a huge biological diversity and can be considered as an underexplored location for prospecting bioactive molecules. In this review, the current state of art about antimicrobial molecules from marine bacteria has been summarized considering the main phylum and sources evolved in a marine environment. Considering the last two decades, we have found as most studied group of bacteria producers of substances with antimicrobial activity is the Firmicutes phylum, in particular strains of the Bacillus genus. The reason for that can be attributed to the difficult cultivation of typical Actinobacteria from a marine sediment, whose members are the major producers of antimicrobial substances in land environments. However, a reversed trend has been observed in recent years with an increasing number of reports settling on Actinobacteria. Great diversity of chemical structures have been identified, such as fijimicyns and lynamicyns from Actinomycetes and macrolactins produced by Bacillus.

Description: Introduction: The marine environment is a very promising resource for natural product research, with many of these reaching the market as new drugs, especially in the field of cancer therapy as well as the drug discovery pipeline for new antimicrobials. Exploitation for bioactive marine compounds with unique structures and novel bioactivity such as the isoquinoline alkaloid; trabectedin, the polyether macrolide; halichondrin B, and the peptide; dolastatin 10, requires the use of analytical techniques, which can generate unbiased, quantitative, and qualitative data to benefit the biodiscovery process. Metabolomics has shown to bridge this understanding and facilitate the development of new potential drugs from marine sources and particularly their microbial symbionts. Areas covered: In this review, articles on applied secondary metabolomics ranging from 1990–2018 as well as to the last quarter of 2019 were probed to investigate the impact of metabolomics on drug discovery for new antibiotics and cancer treatment. Expert opinion: The current literature review highlighted the effectiveness of metabolomics in the study of targeting biologically active secondary metabolites from marine sources for optimized discovery of potential new natural products to be made accessible to a R&D pipeline.

Description: Warming air temperatures, shifting hydrological regimes and accelerating permafrost thaw in the catchments of the Arctic rivers is affecting their biogeochemistry. Arctic river monitoring is necessary to observe changes in the mobilization of dissolved organic matter (DOM) from permafrost. The Lena River is the second largest Arctic river and 71% of its catchment is continuous permafrost. Biogeochemical parameters, including temperature, electrical conductivity (EC), stable water isotopes, dissolved organic carbon (DOC) and absorption by colored dissolved organic matter (aCDOM) have been measured as part of a new high-frequency sampling program in the central Lena River Delta. The results show strong seasonal variations of all biogeochemical parameters that generally follow seasonal patterns of the hydrograph. Optical indices of DOM indicate a trend of decreasing aromaticity and molecular weight from spring to winter. High-frequency sampling improved our estimated annual fluvial flux of annual dissolved organic carbon flux (6.79 Tg C). EC and stable isotope data were used to distinguish three different source water types which explain most of the seasonal variation in the biogeochemistry of the Lena River. These water types match signatures of (1) melt water, (2) rain water, and (3) subsurface water. Melt water and rain water accounted for 84% of the discharge flux and 86% of the DOC flux. The optical properties of melt water DOM were characteristic of fresh organic matter. In contrast, the optical properties of DOM in subsurface water revealed lower aromaticity and lower molecular weights, which indicate a shift toward an older organic matter source mobilized from deeper soil horizons or permafrost deposits. The first year of this new sampling program sets a new baseline for flux calculations of dissolved matter and has enabled the identification and characterization of water types that drive the seasonality of the Lena River water properties.

Description: Traceability and reliable results are the two pillars of analytical methods; certified reference materials (CRMs) meet this requirement. ISO 17034:2016 credentials provide brief information on general requirements for the competence of Reference Material Producers (RMPs). The different types of CRMs have been produced in recent years for chemical analysis in food, water, soil, and sediment matrices in recent years. This review provides a detailed overview of the development of CRMs in the field of marine environment, as matrix CRMs play an important role in the field of environmental monitoring. COMAR database, EVISA database: materials, LGC standards, and JRC catalogs are very helpful online resources to find various types of CRMs according to the application requirements. Highlights - The classification of certified reference materials (CRMs) in the field of marine environment is presented; - General information about the production and characteristics of CRMs is discussed; - Examples of use of existing marine CRMs are described in detail; - Importance of CRMs for QA/QC and CRMs development for chemical analysis is presented; - The parameters that characterize the CRMs: representativeness, homogeneity, stability, and certified value are provided.

Description: The Trans-European Suture Zone (TESZ) is the transition zone from the Precambrian East European Craton in the north and east to the younger Phanerozoic mobile belts to the south and west. It is the most prominent lithospheric tectonic feature of Europe. The term Trans-European Suture Zone was only adapted around year 2000 during the Pan-European EUROPROBE program of the European Science Foundation. Until then, parts of the zone were termed Teisseyre-Tornquist Zone, Sorgenfrei-Tornquist Zone, Trans-European Fault, and Tornquist Fan.

Description: The warming of our planet is changing the Arctic dramatically. The area covered by sea-ice is shrinking and the ice that is left is younger and thinner. We took part in an expedition to the Arctic, to study how these changes affect organisms living in and under the ice. Following this expedition, we found that storms can more easily break the thinner ice. Storms form cracks in the sea ice, allowing sunlight to pass into the water below, which makes algal growth possible. Algae are microscopic “plants” that grow in water or sea ice. Storms also brought thick heavy snow, which pushed the ice surface below the water. This flooded the snow and created slush. We discovered that this slush is another good habitat for algae. If Arctic sea ice continues to thin, and storms become more common, we expect that these algal habitats will become more important in the future.

Description: Freshwater sponges can be considered a promising new source of bioactive compounds for the pharmaceutical industry; however, the research on their chemical composition is still in the incipient stage. We evaluated the most endemic Amazonian freshwater sponge species from the Drulia and Metania genera by untargeted metabolomic approaches, based on UHPCL-HRMS, in order to identify chemical markers and explore the diversity of specialized metabolites. The use of untargeted approaches allowed us to observe subsets of metabolites that enabled the characterization of, not only each genus, but also, of each species. Freshwater sponge species presented themselves as rich sources of fatty acids and sterols, which were putatively identified. These metabolites were suggested as chemical markers for further targeted metabolomic studies.

Description: Deep artificial neural networks have become the go-to method for many machine learning tasks. In the field of computer vision, deep convolutional neural networks achieve state-of-the-art performance for tasks such as classification, object detection, or instance segmentation. As deep neural networks become more and more complex, their inner workings become more and more opaque, rendering them a “black box” whose decision making process is no longer comprehensible. In recent years, various methods have been presented that attempt to peek inside the black box and to visualize the inner workings of deep neural networks, with a focus on deep convolutional neural networks for computer vision. These methods can serve as a toolbox to facilitate the design and inspection of neural networks for computer vision and the interpretation of the decision making process of the network. Here, we present the new tool Interactive Feature Localization in Deep neural networks (IFeaLiD) which provides a novel visualization approach to convolutional neural network layers. The tool interprets neural network layers as multivariate feature maps and visualizes the similarity between the feature vectors of individual pixels of an input image in a heat map display. The similarity display can reveal how the input image is perceived by different layers of the network and how the perception of one particular image region compares to the perception of the remaining image. IFeaLiD runs interactively in a web browser and can process even high resolution feature maps in real time by using GPU acceleration with WebGL 2. We present examples from four computer vision datasets with feature maps from different layers of a pre-trained ResNet101. IFeaLiD is open source and available online at https://ifealid.cebitec.uni-bielefeld.de.