Modeling denitrification in aquatic sediments

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Biogeochemistry 93 (2009): 159-178, doi:10.1007/s10533-008-9270-z.Sediment denitrification is a major pathway of fixed nitrogen loss from aquatic systems. Due to technical difficulties in measuring this process and its spatial and temporal variability, estimates of local, regional and global denitrification have to rely on a combination of measurements and models. Here we review approaches to describing denitrification in aquatic sediments, ranging from mechanistic diagenetic models to empirical parameterizations of nitrogen fluxes across the sediment-water interface. We also present a compilation of denitrification measurements and ancillary data for different aquatic systems, ranging from freshwater to marine. Based on this data compilation we reevaluate published parameterizations of denitrification. We recommend that future models of denitrification use (1) a combination of mechanistic diagenetic models and measurements where bottom waters are temporally hypoxic or anoxic, and (2) the much simpler correlations between denitrification and sediment oxygen consumption for oxic bottom waters. For our data set, inclusion of bottom water oxygen and nitrate concentrations in a multivariate regression did not improve the statistical fit.Financial support for AEG to work on the manuscript came from NSF NSF-DEB-0423565. KF, DB and DDT acknowledge support from NOAA CHRP grant NA07NOS4780191

Genetic and environmental effects on body mass index from infancy to the onset of adulthood: an individual-based pooled analysis of 45 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) study

Background: Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking. Objectives: We analyzed the genetic and environmental contributions to BMI variation from infancy to early adulthood and the ways they differ by sex and geographic regions representing high (North America and Australia), moderate (Europe), and low levels (East Asia) of obesogenic environments. Design: Data were available for 87,782 complete twin pairs from 0.5 to 19.5 y of age from 45 cohorts. Analyses were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and environmental components through genetic structural equation modeling. Results: The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive genetic factors was lowest at 4 y of age in boys (a2 = 0.42) and girls (a2 = 0.41) and then generally increased to 0.75 in both sexes at 19 y of age. This was because of a stronger influence of environmental factors shared by co-twins in midchildhood. After 15 y of age, the effect of shared environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained roughly similar across different regions. Conclusions: Environmental factors shared by co-twins affect BMI in childhood, but little evidence for their contribution was found in late adolescence. Our results suggest that genetic factors play a major role in the variation of BMI in adolescence among populations of different ethnicities exposed to different environmental factors related to obesity

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Seasonal and inter-annual variations of nitrogen diagenesis in the sediments of a recently impounded basin

The Méry-sur-Oise (France) storage reservoir is an artificial basin of 9 m average depth, fed by water from the river Oise with a mean residence time of about 4 days. Sediments are accumulating at a rate of about 0.7 cm/month. In the sediments, two fractions of organic nitrogen with different rates of bacterial degradation could be distinguished, one associated with fresh phytoplankton, the other made of detrital and more refractory compounds. The fluxes of oxygen, nitrate and ammonium across the sediment-water interface were measured with a bell-jar system at different seasons during a 3 year period following flooding of the basin. The measurements show clear seasonal variations in relation with the variations of temperature and input of fresh phytoplanktonic material to the sediment. In addition, a long term trend of increasing ammonium was observed. Measurements were also carried out after dredging of all accumulated sediments of the basin. They showed a considerable reduction of the flux of nitrate to the sediments and a significant reduction of the flux of ammonium to the water column. These results are interpreted in the light of a non stationary model of N diagenesis in accumulating sediments. This model is able to predict at least the general trends of benthic N cycling of basins during the early stage of their ecological succession.info:eu-repo/semantics/publishe

Lipidomic profiling identifies signatures of metabolic risk

BACKGROUND:Metabolic syndrome (MetS), the clustering of metabolic risk factors, is associated with cardiovascular disease risk. We sought to determine if dysregulation of the lipidome may contribute to metabolic risk factors. METHODS:We measured 154 circulating lipid species in 658 participants from the Framingham Heart Study (FHS) using liquid chromatography-tandem mass spectrometry and tested for associations with obesity, dysglycemia, and dyslipidemia. Independent external validation was sought in three independent cohorts. Follow-up data from the FHS were used to test for lipid metabolites associated with longitudinal changes in metabolic risk factors. RESULTS:Thirty-nine lipids were associated with obesity and eight with dysglycemia in the FHS. Of 32 lipids that were available for replication for obesity and six for dyslipidemia, 28 (88%) replicated for obesity and five (83%) for dysglycemia. Four lipids were associated with longitudinal changes in body mass index and four were associated with changes in fasting blood glucose in the FHS. CONCLUSIONS:We identified and replicated several novel lipid biomarkers of key metabolic traits. The lipid moieties identified in this study are involved in biological pathways of metabolic risk and can be explored for prognostic and therapeutic utility