Spatially explicit estimates of N2O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management

With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2O emissions at the country scale by aggregating all crops, under the assumption that N2O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2O emissions are relatively greater at higher N application rates. Here we apply a super-linear emissions response model to crop-specific, spatially-explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2O emissions from croplands. We estimate 0.66 Tg of N2O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2O emissions range from 20-40% lower throughout Sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak non-linear response of N2O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2O emissions. Since aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2O emissions estimates

External Control of the GAL Network in S. cerevisiae: A View from Control Theory

While there is a vast literature on the control systems that cells utilize to regulate their own state, there is little published work on the formal application of control theory to the external regulation of cellular functions. This paper chooses the GAL network in S. cerevisiae as a well understood benchmark example to demonstrate how control theory can be employed to regulate intracellular mRNA levels via extracellular galactose. Based on a mathematical model reduced from the GAL network, we have demonstrated that a galactose dose necessary to drive and maintain the desired GAL genes' mRNA levels can be calculated in an analytic form. And thus, a proportional feedback control can be designed to precisely regulate the level of mRNA. The benefits of the proposed feedback control are extensively investigated in terms of stability and parameter sensitivity. This paper demonstrates that feedback control can both significantly accelerate the process to precisely regulate mRNA levels and enhance the robustness of the overall cellular control system

Stochastic analysis of the GAL genetic switch in Saccharomyces cerevisiae: Modeling and experiments reveal hierarchy in glucose repression

<p>Abstract</p> <p>Background</p> <p>Transcriptional regulation involves protein-DNA and protein-protein interactions. Protein-DNA interactions involve reactants that are present in low concentrations, leading to stochastic behavior. In addition, multiple regulatory mechanisms are typically involved in transcriptional regulation. In the <it>GAL </it>regulatory system of <it>Saccharomyces cerevisiae</it>, the inhibition of glucose is accomplished through two regulatory mechanisms: one through the transcriptional repressor Mig1p, and the other through regulating the amount of transcriptional activator Gal4p. However, the impact of stochasticity in gene expression and hierarchy in regulatory mechanisms on the phenotypic level is not clearly understood.</p> <p>Results</p> <p>We address the question of quantifying the effect of stochasticity inherent in these regulatory mechanisms on the performance of various genes under the regulation of Mig1p and Gal4p using a dynamic stochastic model. The stochastic analysis reveals the importance of both the mechanisms of regulation for tight expression of genes in the <it>GAL </it>network. The mechanism involving Gal4p is the dominant mechanism, yielding low variability in the expression of <it>GAL </it>genes. The mechanism involving Mig1p is necessary to maintain the switch-like response of certain <it>GAL </it>genes. The number of binding sites for Mig1p and Gal4p further influences the expression of the genes, with extra binding sites lowering the variability of expression. Our experiments involving growth on various substrates show that the trends predicted in mean expression and its variability are transmitted to the phenotypic level.</p> <p>Conclusion</p> <p>The mechanisms involved in the transcriptional regulation and their variability set up a hierarchy in the phenotypic response to growth on various substrates. Structural motifs, such as the number of binding sites and the mechanism of regulation, determine the level of stochasticity and eventually, the phenotypic response.</p

L'utilisation par la viticulture française d'un exercice de prospective pour l'élaboration d'une stratégie d'adaptation au changement climatique

Foresight studies are regularly conducted at sectoral or geographical scales, in order to help policy makers and economic actors to define their strategy of adaptation to climate change (CC)

Interoperable and scalable data analysis with microservices: applications in metabolomics.

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator. We developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the Virtual Research Environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. Supplementary data are available at Bioinformatics online

Workforce preparation: the Biohealth computing model for Master and PhD students

The article addresses the strategic role of workforce preparation in the process of adoption of Systems Medicine as a driver of biomedical research in the new health paradigm. It reports on relevant initiatives, like CASyM, fostering Systems Medicine at EU level. The chapter focuses on the BioHealth Computing Program as a reference for multidisciplinary training of future systems-oriented researchers describing the productive interactions with the Synergy-COPD project

Non-invasive ventilation in obesity hypoventilation syndrome without severe obstructive sleep apnoea

Background Non-invasive ventilation (NIV) is an effective form of treatment in patients with obesity hypoventilation syndrome (OHS) who have concomitant severe obstructive sleep apnoea (OSA). However, there is a paucity of evidence on the efficacy of NIV in patients with OHS without severe OSA. We performed a multicentre randomised clinical trial to determine the comparative efficacy of NIV versus lifestyle modification (control group) using daytime arterial carbon dioxide tension (PaCO2) as the main outcome measure. Methods Between May 2009 and December 2014 we sequentially screened patients with OHS without severe OSA. Participants were randomised to NIV versus lifestyle modification and were followed for 2 months. Arterial blood gas parameters, clinical symptoms, health-related quality of life assessments, polysomnography, spirometry, 6-min walk distance test, blood pressure measurements and healthcare resource utilisation were evaluated. Statistical analysis was performed using intention-to-treat analysis. Results A total of 365 patients were screened of whom 58 were excluded. Severe OSA was present in 221 and the remaining 86 patients without severe OSA were randomised. NIV led to a significantly larger improvement in PaCO2 of -6 (95% CI -7.7 to -4.2) mm Hg versus -2.8 (95% CI -4.3 to -1.3) mm Hg, (p<0.001) and serum bicarbonate of -3.4 (95% CI -4.5 to -2.3) versus -1 (95% CI -1.7 to -0.2 95% CI) mmol/L (p<0.001). PaCO2 change adjusted for NIV compliance did not further improve the inter-group statistical significance. Sleepiness, some health-related quality of life assessments and polysomnographic parameters improved significantly more with NIV than with lifestyle modification. Additionally, there was a tendency towards lower healthcare resource utilisation in the NIV group. Conclusions NIV is more effective than lifestyle modification in improving daytime PaCO2, sleepiness and polysomnographic parameters. Long-term prospective studies are necessary to determine whether NIV reduces healthcare resource utilisation, cardiovascular events and mortality