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- ItemInvestigating the Mutagenicity of a Cold Argon-Plasma Jet in an HET-MN Model(San Francisco, California, US : PLOS, 2016) Kluge, Susanne; Bekeschus, Sander; Bender, Claudia; Benkhai, Hicham; Sckell, Axel; Below, Harald; Stope, Matthias B.; Kramer, Axel; Yousfi, MohammedObjective: So-called cold physical plasmas for biomedical applications generate reactive oxygen and nitrogen species and the latter can trigger DNA damage at high concentrations. Therefore, the mutagenic risks of a certified atmospheric pressure argon plasma jet (kINPen MED) and its predecessor model (kINPen 09) were assessed. Methods: Inner egg membranes of fertilized chicken eggs received a single treatment with either the kINPen 09 (1.5, 2.0, or 2.5 min) or the kINPen MED (3, 4, 5, or 10 min). After three days of incubation, blood smears (panoptic May-Grünwald-Giemsa stain) were performed, and 1000 erythrocytes per egg were evaluated for the presence of polychromatic and normochromic nuclear staining as well as nuclear aberrations and binucleated cells (hen’s egg test for micronuclei induction, HET-MN). At the same time, the embryo mortality was documented. For each experiment, positive controls (cyclophosphamide and methotrexate) and negative controls (NaCl-solution, argon gas) were included. Additionally, the antioxidant potential of the blood plasma was assessed by ascorbic acid oxidation assay after treatment. Results: For both plasma sources, there was no evidence of genotoxicity, although at the longest plasma exposure time of 10 min the mortality of the embryos exceeded 40%. The antioxidant potential in the egg’s blood plasma was not significantly reduced immediately (p = 0.32) or 1 h (p = 0.19) post exposure to cold plasma. Conclusion: The longest plasma treatment time with the kINPen MED was 5–10 fold above the recommended limit for treatment of chronic wounds in clinics. We did not find mutagenic effects for any plasma treatment time using the either kINPen 09 or kINPen MED. The data provided with the current study seem to confirm the lack of a genotoxic potential suggesting that a veterinary or clinical application of these argon plasma jets does not pose mutagenic risks.
- ItemMonoclonal Antibodies 13A4 and AC133 Do Not Recognize the Canine Ortholog of Mouse and Human Stem Cell Antigen Prominin-1 (CD133)(San Francisco, California, US : PLOS, 2016) Thamm, Kristina; Graupner, Sylvi; Werner, Carsten; Huttner, Wieland B.; Corbeil, Denis; Nabi, Ivan RThe pentaspan membrane glycoprotein prominin-1 (CD133) is widely used in medicine as a cell surface marker of stem and cancer stem cells. It has opened new avenues in stem cell-based regenerative therapy and oncology. This molecule is largely used with human samples or the mouse model, and consequently most biological tools including antibodies are directed against human and murine prominin-1. Although the general structure of prominin-1 including its membrane topology is conserved throughout the animal kingdom, its primary sequence is poorly conserved. Thus, it is unclear if anti-human and -mouse prominin-1 antibodies cross-react with their orthologs in other species, especially dog. Answering this issue is imperative in light of the growing number of studies using canine prominin-1 as an antigenic marker. Here, we address this issue by cloning the canine prominin-1 and use its overexpression as a green fluorescent protein fusion protein in Madin-Darby canine kidney cells to determine its immunoreactivity with antibodies against human or mouse prominin-1. We used immunocytochemistry, flow cytometry and immunoblotting techniques and surprisingly found no cross-species immunoreactivity. These results raise some caution in data interpretation when anti-prominin-1 antibodies are used in interspecies studies.
- ItemProximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?(San Francisco, California, US : PLOS, 2016) Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, JensBackground: Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Methodology/Principal Findings: Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Conclusions/Significance: Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.