Environmental surveying and surveillance

© Springer International Publishing AG 2018. In this section, we discuss the quantitative and qualitative data that could be collected using GNSS satellites, and in so doing, attempt to answer the question “what can GNSS satellites deliver that are of use to environmental monitoring?” The observed parameters necessary for environmental monitoring vary, depending upon the indicators being assessed. Some are physical variables such as changes in soil patterns, vegetation, rainfall, water levels, temperature, deforestation, solar and UV radiation. Others are chemical variables, e.g., pH, salinity, nutrients, metals, pesticides, while others are biological variables, e.g., species types, ecosystem health, and indicator species

Genome-Wide Association Study of l

BACKGROUND: Dimethylarginines (DMA) interfere with nitric oxide (NO) formation by inhibiting NO synthase (asymmetric dimethylarginine, ADMA) and L-arginine uptake into the cell (ADMA and symmetric dimethylarginine, SDMA). In prospective clinical studies ADMA has been characterized as a cardiovascular risk marker whereas SDMA is a novel marker for renal function and associated with all-cause mortality after ischemic stroke. The aim of the current study was to characterise the environmental and genetic contributions to inter-individual variability of these biomarkers. METHODS AND RESULTS: This study comprised a genome-wide association analysis of 3 well-characterized population-based cohorts (FHS (n=2992), GHS (n=4354) and MONICA/KORA F3 (n=581)) and identified replicated loci (DDAH1, MED23, Arg1 and AGXT2) associated with the inter-individual variability in ADMA, L-arginine and SDMA. Experimental in-silico and in-vitro studies confirmed functional significance of the identified AGXT2 variants. Clinical outcome analysis in 384 patients of the Leeds stroke study demonstrated an association between increased plasma levels of SDMA, AGXT2 variants and various cardiometabolic risk factors. AGXT2 variants were not associated with post-stroke survival in the Leeds study, nor were they associated with incident stroke in the CHARGE consortium. CONCLUSION: These GWAS support the importance of DDAH1 and MED23/Arg1 in regulating ADMA and L-arginine metabolism, respectively, and identify a novel regulatory renal pathway for SDMA by AGXT2. AGXT2 variants might explain part of the pathogenic link between SDMA, renal function, and outcome. An association between AGXT2 variants and stroke is unclear and warrants further investigation