Greenhouse gas emissions from a constructed wetland in southern Sweden

This paper investigates the greenhouse gas emissions from a Swedish wetland, constructed to decrease nutrient content in sewage treatment water. To evaluate the effect of the construction in terms of greenhouse gas emissions we carried out ecosystem-atmosphere flux measurements of CO₂, CH₄ and N₂O using a closed chamber technique. To evaluate the importance of vascular plant species composition to gas emissions we distributed the measurement plots over the three dominating plant species at the field site, i.e., Typha latifolia, Phragmites australis and Juncus effusus. The fluxes of CO₂ (total respiration), CH₄ and N₂O from vegetated plots ranged from 1.39 to 77.5 (g m⁻² day⁻¹), −377 to 1387 and −13.9 to 31.5 (mg m⁻² day⁻¹) for CO₂, CH₄ and N₂O, respectively. Presence of vascular plants lead as expected to significantly higher total respiration rates compared with un-vegetated control plots. Furthermore, we found that the emission rates of N₂O and CH₄ was affected by presence of vascular plants and tended to be species-specific. We assessed the integrated greenhouse warming effect of the emissions using a Global Warming Potential over a 100-year horizon (GWP₁₀₀) and it corresponded to 431 kg CO₂ equivalents m⁻² day⁻¹. Assuming a 7-month season with conditions similar to the study period this is equal to 90 tonnes of CO₂ equivalents annually. N₂O emissions were responsible for one third of the estimated total greenhouse forcing. Furthermore, we estimated that the emission from the forested bog that was the precursor land to Magle constructed wetland amounted to 18.6 tonnes of CO₂ equivalents annually. Hence, the constructed wetland has increased annual greenhouse gas emissions by 71.4 tonnes of CO₂ equivalents for the whole area. Our findings indicate that management processes in relation to wetland construction projects must consider the primary function of the wetland in decreasing eutrophication, in relation to other positive aspects on for instance plant and animal life and recreation as well as possible negative climatic aspects of increased emissions of CH₄ and N₂O.     

DNA double-strand break repair pathways, chromosomal rearrangements and cancer

Chromosomal rearrangements, which can lead to oncogene activation and tumour suppressor loss, are a hallmark of cancer cells. Such outcomes can result from both the repair and misrepair of DNA ends, which arise from a variety of lesions including DNA double strand breaks (DSBs), collapsed replication forks and dysfunctional telomeres. Here we review the mechanisms by which non-homologous end joining (NHEJ) and homologous recombination (HR) repair pathways can both promote chromosomal rearrangements and also suppress them in response to such lesions, in accordance with their increasingly recognised tumour suppressor function. Further, we consider how chromosomal rearrangements, together with a modular approach towards understanding their etiology, may be exploited for cancer therapy.     

Rseg--an R package to optimize segmentation of SNP array data

The use of high-density SNP arrays for investigating copy number alterations in clinical tumor samples, with intra tumor heterogeneity and varying degrees of normal cell contamination, imposes several problems for commonly used segmentation algorithms. This calls for flexibility when setting thresholds for calling gains and losses. In addition, sample normalization can induce artifacts in the copy-number ratios for the non-changed genomic elements in the tumor samples. RESULTS: We present an open source R package, Rseg, which allows the user to define sample-specific thresholds to call gains and losses. It also allows the user to correct for normalization artifacts. AVAILABILITY: The R package, Rseg, is available at: http://www.cs.au.dk/~plamy/Rseg/ and runs on Linux and MS-Windows.     

Studies of metabolic phenotypic correlates of 15 obesity associated gene variants

Aims

Genome-wide association studies have identified novel BMI/obesity associated susceptibility loci. The purpose of this study is to determine associations with overweight, obesity, morbid obesity and/or general adiposity in a Danish population. Moreover, we want to investigate if these loci associate with type 2 diabetes and to elucidate potential underlying metabolic mechanisms.

Methods

15 gene variants in 14 loci including TMEM18 (rs7561317), SH2B1 (rs7498665), KCTD15 (rs29941), NEGR1 (rs2568958), ETV5 (rs7647305), BDNF (rs4923461, rs925946), SEC16B (rs10913469), FAIM2 (rs7138803), GNPDA2 (rs10938397), MTCH2 (rs10838738), BAT2 (rs2260000), NPC1 (rs1805081), MAF (rs1424233), and PTER (rs10508503) were genotyped in 18,014 middle-aged Danes.

Results

Five of the 15 gene variants associated with overweight, obesity and/or morbid obesity. Per allele ORs ranged from 1.15–1.20 for overweight, 1.10–1.25 for obesity, and 1.41–1.46 for morbid obesity. Five of the 15 variants moreover associated with increased measures of adiposity. BDNF rs4923461 displayed a borderline BMI-dependent protective effect on type 2 diabetes (0.87 (0.78–0.96, p = 0.008)), whereas SH2B1 rs7498665 associated with nominally BMI-independent increased risk of type 2 diabetes (1.16 (1.07–1.27, p = 7.8×10⁻⁴)).

Conclusions

Associations with overweight and/or obesity and measures of obesity were confirmed for seven out of the 15 gene variants. The obesity risk allele of BDNF rs4923461 protected against type 2 diabetes, which could suggest neuronal and peripheral distinctive ways of actions for the protein. SH2B1 rs7498665 associated with type 2 diabetes independently of BMI.     

Comparison of accuracy of diabetes risk score and components of the metabolic syndrome in assessing risk of incident type 2 diabetes in Inter99 cohort

Background

Given the increasing worldwide incidence of diabetes, methods to assess diabetes risk which would identify those at highest risk are needed. We compared two risk-stratification approaches for incident type 2 diabetes mellitus (T2DM); factors of metabolic syndrome (MetS) and a previously developed diabetes risk score, PreDx® Diabetes Risk Score (DRS). DRS assesses 5 yr risk of incident T2DM based on the measurement of 7 biomarkers in fasting blood.

Methodology/Principal Findings

DRS was evaluated in baseline serum samples from 4,128 non-diabetic subjects in the Inter99 cohort (Danes aged 30–60) for whom diabetes outcomes at 5 years were known. Subjects were classified as having MetS based on the presence of at least 3 MetS risk factors in baseline clinical data. The sensitivity and false positive rate for predicting diabetes using MetS was compared to DRS. When the sensitivity was fixed to match MetS, DRS had a significantly lower false positive rate. Similarly, when the false positive rate was fixed to match MetS, DRS had a significantly higher specificity. In further analyses, subjects were classified by presence of 0–2, 3 or 4–5 risk factors with matching proportions of subjects distributed among three DRS groups. Comparison between the two risk stratification schemes, MetS risk factors and DRS, were evaluated using Net Reclassification Improvement (NRI). Comparing risk stratification by DRS to MetS factors in the total population, the NRI was 0.146 (p = 0.008) demonstrating DRS provides significantly improved stratification. Additionally, the relative risk of T2DM differed by 15 fold between the low and high DRS risk groups, but only 8-fold between the low and high risk MetS groups.

Conclusions/Significance

DRS provides a more accurate assessment of risk for diabetes than MetS. This improved performance may allow clinicians to focus preventive strategies on those most in need of urgent intervention.