Phagocyte-derived catecholamines enhance acute inflammatory injury

It is becoming increasingly clear that the autonomic nervous system and the immune system demonstrate cross-talk during inflammation by means of sympathetic and parasympathetic pathways. We investigated whether phagocytes are capable of de novo production of catecholamines, suggesting an autocrine/paracrine self-regulatory mechanism by catecholamines during inflammation, as has been described for lymphocytes. Here we show that exposure of phagocytes to lipopolysaccharide led to a release of catecholamines and an induction of catecholamine-generating and degrading enzymes, indicating the presence of the complete intracellular machinery for the generation, release and inactivation of catecholamines. To assess the importance of these findings in vivo, we chose two models of acute lung injury. Blockade of alpha2-adrenoreceptors or catecholamine-generating enzymes greatly suppressed lung inflammation, whereas the opposite was the case either for an alpha2-adrenoreceptor agonist or for inhibition of catecholamine-degrading enzymes. We were able to exclude T cells or sympathetic nerve endings as sources of the injury-modulating catecholamines. Our studies identify phagocytes as a new source of catecholamines, which enhance the inflammatory response.     

The human footprint in the carbon cycle of temperate and boreal forests

Temperate and boreal forests in the Northern Hemisphere cover an area of about 2 x 10(7) square kilometres and act as a substantial carbon sink (0.6-0.7 petagrams of carbon per year). Although forest expansion following agricultural abandonment is certainly responsible for an important fraction of this carbon sink activity, the additional effects on the carbon balance of established forests of increased atmospheric carbon dioxide, increasing temperatures, changes in management practices and nitrogen deposition are difficult to disentangle, despite an extensive network of measurement stations. The relevance of this measurement effort has also been questioned, because spot measurements fail to take into account the role of disturbances, either natural (fire, pests, windstorms) or anthropogenic (forest harvesting). Here we show that the temporal dynamics following stand-replacing disturbances do indeed account for a very large fraction of the overall variability in forest carbon sequestration. After the confounding effects of disturbance have been factored out, however, forest net carbon sequestration is found to be overwhelmingly driven by nitrogen deposition, largely the result of anthropogenic activities. The effect is always positive over the range of nitrogen deposition covered by currently available data sets, casting doubts on the risk of widespread ecosystem nitrogen saturation under natural conditions. The results demonstrate that mankind is ultimately controlling the carbon balance of temperate and boreal forests, either directly (through forest management) or indirectly (through nitrogen deposition).     

A new chromosome 17q21.31 microdeletion syndrome associated with a common inversion polymorphism

Submicroscopic genomic copy number changes have been identified only recently as an important cause of mental retardation. We describe the detection of three interstitial, overlapping 17q21.31 microdeletions in a cohort of 1,200 mentally retarded individuals associated with a clearly recognizable clinical phenotype of mental retardation, hypotonia and a characteristic face. The deletions encompass the MAPT and CRHR1 genes and are associated with a common inversion polymorphism.     

Probabilistic Forecasts of Wind Power Generation by Stochastic Differential Equation Models

The increasing penetration of wind power has resulted in larger shares of volatile sources of supply in power systems worldwide. In order to operate such systems efficiently, methods for reliable probabilistic forecasts of future wind power production are essential. It is well known that the conditional density of wind power production is highly dependent on the level of predicted wind power and prediction horizon. This paper describes a new approach for wind power forecasting based on logistic‐type stochastic differential equations (SDEs). The SDE formulation allows us to calculate both state‐dependent conditional uncertainties as well as correlation structures. Model estimation is performed by maximizing the likelihood of a multidimensional random vector while accounting for the correlation structure defined by the SDE formulation. We use non‐parametric modelling to explore conditional correlation structures, and skewness of the predictive distributions as a function of explanatory variables. Copyright © 2015 John Wiley & Sons, Ltd.     

Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population

Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.     

The value of data

Data citation and the derivation of semantic constructs directly from datasets have now both found their place in scientific communication. The social challenge facing us is to maintain the value of traditional narrative publications and their relationship to the datasets they report upon while at the same time developing appropriate metrics for citation of data and data constructs.