Oceanic biogeochemical characteristic maps identified with holistic use of satellite, model and data

This is the final published version.Ocean province level plankton community exhibit heterogeneity across Arctic, Nordic, Atlantic Gyre and Southern Ocean provinces. GreenSeas research is an international FP7 consortium that includes Arctic, Atlantic and Southern Ocean based research teams who are analysing the planktonic ecosystem. We are looking at how the planktonic ecosystem responds to environmental and climate change. Using Earth Observation monitoring data we report new results on identifying generic plankton characteristics observable at a province level, and also touch on spatial and temporal trends that are evident using a holistic analysis framework. Using advanced statistical methods this framework compares and combines Earth Observation information together with an in-situ Oceanic plankton Analytical Database and up to 40 year ocean general circulation biogeochemical model (OGCBM) time series of the equivalent plankton and sea-state measures of this system. Specifically, we outline the use of the GreenSeas Analytical Database, which is a harmonised set of Oceanic in-situ plankton and sea-state measures covering different cruises and time periods. The Analytical Database information ranges from plankton community, primary production, nutrient cycling to physical sea state temperature and salinity measures. The combined analysis utilises current, 10 year+ Earth Observations of ocean colour and sea surface temperature metrics and interprets these together with biogeochemical model outputs from PELAGOS, ERSEM & NORWECOM model runs to help identify planktonic based biomes. Generic planktonic characteristic maps that are equivalently observable in both the Earth Observations and numerical models are reported on. Both ocean surface and sub-surface signals are analysed together with relevant Analytical Database biome extracts. We present the current results of this inter-comparison & discuss challenges of identifying the province level plankton dominance with the satellite, model and data. In particular we discuss the strategic importance of systematically analysing the knowledge present in the existing key long term Oceanic observation platforms through such holistic analysis frameworks. These maps help to enhance and improve current biogeochemical models, our understanding of the plankton community structure and predictions used for future assessment of climate change

Complete Sequencing of the blaNDM-1-Positive IncA/C Plasmid from Escherichia coli ST38 Isolate Suggests a Possible Origin from Plant Pathogens

The complete sequence of the plasmid pNDM-1_Dok01 carrying New Delhi metallo-β-lactamase (NDM-1) was determined by whole genome shotgun sequencing using Escherichia coli strain NDM-1_Dok01 (multilocus sequence typing type: ST38) and the transconjugant E. coli DH10B. The plasmid is an IncA/C incompatibility type composed of 225 predicted coding sequences in 195.5 kb and partially shares a sequence with blaCMY-2-positive IncA/C plasmids such as E. coli AR060302 pAR060302 (166.5 kb) and Salmonella enterica serovar Newport pSN254 (176.4 kb). The blaNDM-1 gene in pNDM-1_Dok01 is terminally flanked by two IS903 elements that are distinct from those of the other characterized NDM-1 plasmids, suggesting that the blaNDM-1 gene has been broadly transposed, together with various mobile elements, as a cassette gene. The chaperonin groES and groEL genes were identified in the blaNDM-1-related composite transposon, and phylogenetic analysis and guanine-cytosine content (GC) percentage showed similarities to the homologs of plant pathogens such as Pseudoxanthomonas and Xanthomonas spp., implying that plant pathogens are the potential source of the blaNDM-1 gene. The complete sequence of pNDM-1_Dok01 suggests that the blaNDM-1 gene was acquired by a novel composite transposon on an extensively disseminated IncA/C plasmid and transferred to the E. coli ST38 isolate

Genetic Overexpression of NR2B Subunit Enhances Social Recognition Memory for Different Strains and Species

The ability to learn and remember conspecifics is essential for the establishment and maintenance of social groups. Many animals, including humans, primates and rodents, depend on stable social relationships for survival. Social learning and social recognition have become emerging areas of interest for neuroscientists but are still not well understood. It has been established that several hormones play a role in the modulation of social recognition including estrogen, oxytocin and arginine vasopression. Relatively few studies have investigated how social recognition might be improved or enhanced. In this study, we investigate the role of the NMDA receptor in social recognition memory, specifically the consequences of altering the ratio of the NR2B∶NR2A subunits in the forebrain regions in social behavior. We produced transgenic mice in which the NR2B subunit of the NMDA receptor was overexpressed postnatally in the excitatory neurons of the forebrain areas including the cortex, amygdala and hippocampus. We investigated the ability of both our transgenic animals and their wild-type littermate to learn and remember juvenile conspecifics using both 1-hr and 24-hr memory tests. Our experiments show that the wild-type animals and NR2B transgenic mice preformed similarly in the 1-hr test. However, transgenic mice showed better performances in 24-hr tests of recognizing animals of a different strain or animals of a different species. We conclude that NR2B overexpression in the forebrain enhances social recognition memory for different strains and animal species

2-Hydroxylethyl methacrylate (HEMA), a tooth restoration component, exerts its genotoxic effects in human gingival fibroblasts trough methacrylic acid, an immediate product of its degradation

HEMA (2-hydroxyethyl methacrylate), a methacrylate commonly used in dentistry, was reported to induce genotoxic effects, but their mechanism is not fully understood. HEMA may be degraded by the oral cavity esterases or through mechanical stress following the chewing process. Methacrylic acid (MAA) is the primary product of HEMA degradation. In the present work we compared cytotoxic and genotoxic effects induced by HEMA and MAA in human gingival fibroblasts (HGFs). A 6-h exposure to HEMA or MAA induced a weak decrease in the viability of HGFs. Neither HEMA nor MAA induced strand breaks in the isolated plasmid DNA, but both compounds evoked DNA damage in HGFs, as evaluated by the alkaline comet assay. Oxidative modifications to the DNA bases were monitored by the DNA repair enzymes Endo III and Fpg. DNA damage induced by HEMA and MAA was not persistent and was removed during a 120 min repair incubation. Results from the neutral comet assay indicated that both compounds induced DNA double strand breaks (DSBs) and they were confirmed by the γ-H2AX assay. Both compounds induced apoptosis and perturbed the cell cycle. Therefore, methacrylic acid, a product of HEMA degradation, may be involved in its cytotoxic and genotoxic action

Magnon-assisted tunnelling in van der Waals heterostructures based on CrBr3

Van der Waals heterostructures, which are composed of layered two-dimensional materials, offer a platform to investigate a diverse range of physical phenomena and could be of use in a variety of applications. Heterostructures containing two-dimensional ferromagnets, such as chromium triiodide (CrI3), have recently been reported, which could allow two-dimensional spintronic devices to be developed. Here we study tunnelling through thin ferromagnetic chromium tribromide (CrBr3) barriers that are sandwiched between graphene electrodes. In devices with non-magnetic barriers, conservation of momentum can be relaxed by phonon-assisted tunnelling or by tunnelling through localized states. In contrast, in the devices with ferromagnetic barriers, the major tunnelling mechanisms are the emission of magnons at low temperatures and the scattering of electrons on localized magnetic excitations at temperatures above the Curie temperature. Magnetoresistance in the graphene electrodes further suggests induced spin–orbit coupling and proximity exchange via the ferromagnetic barrier. Tunnelling with magnon emission offers the possibility of spin injection

Optimization of orifice geometry for crossflow mixing in a cylindrical duct

Mixing of gaseous jets in a crossflow has significant applications in combustion science and engineering, one example of which is the mixing zone of a rich-burn/quick-mix/lean-burn gas turbine combustor. A major design question is the jet orifice shape and jet orifice number that optimizes the mixing performance. To delineate the optimal orifice features for a given axial distance and momentum-flux ratio, a statistical design of experiments test matrix was established around three variables: the number of orifices, the orifice aspect ratio, and the orifice angle (in circumferential plane). A jet-to-mainstream momentum-flux ratio of 40 and a mass-flow ratio of 2.5 were selected as representative of a practical design. To yield an interpolating equation that predicts the mixing performance of orifice geometry combinations within the range of the test matrix parameters, a regression analysis was conducted on the data. The results reveal that 1) mixture uniformity is a nonlinear function of the number of orifices, the orifice aspect ratio, and the orifice angle and that 2) optimum mixing occurs when the mean jet trajectories are in the range of 0.30<ζ/R<0.5 (where ζ = R-r) at x/R = 1. At the optimum number of orifices, the difference between shallow-angled slots with large aspect ratios and round holes is minimal and either geometry produces optimal mixing performance

Optimization of orifice geometry for crossflow mixing in a cylindrical duct

Mixing of gaseous jets in a crossflow has significant applications in combustion science and engineering, one example of which is the mixing zone of a rich-burn/quick-mix/lean-burn gas turbine combustor. A major design question is the jet orifice shape and jet orifice number that optimizes the mixing performance. To delineate the optimal orifice features for a given axial distance and momentum-flux ratio, a statistical design of experiments test matrix was established around three variables: the number of orifices, the orifice aspect ratio, and the orifice angle (in circumferential plane). A jet-to-mainstream momentum-flux ratio of 40 and a mass-flow ratio of 2.5 were selected as representative of a practical design. To yield an interpolating equation that predicts the mixing performance of orifice geometry combinations within the range of the test matrix parameters, a regression analysis was conducted on the data. The results reveal that 1) mixture uniformity is a nonlinear function of the number of orifices, the orifice aspect ratio, and the orifice angle and that 2) optimum mixing occurs when the mean jet trajectories are in the range of 0.30<ζ/R<0.5 (where ζ = R-r) at x/R = 1. At the optimum number of orifices, the difference between shallow-angled slots with large aspect ratios and round holes is minimal and either geometry produces optimal mixing performance