Liquidité ou solvabilité ? Les émissions de covered bonds dans le secteur bancaire européen entre 2007 et 2012

15 pagesCe papier présente une étude d'évènement évaluant l'impact des émissions de covered bonds sur les primes des CDS des banques européennes. Les covered bonds sont garanties par des actifs isolés mais conservés dans le bilan de l'émetteur. Nous montrons que les émissions de covered bonds ne semblent pas avoir une influence sur les primes de CDS

Development Of Innovating Na Leak Detector On Pipes

International audienceWithin the ASTRID reactor project, CEA, EDF and AREVA NP, have launched a RetD program focused on the low leak rates detection of sodium on pipes. This program is focused on the development of innovating detectors, multilayer-type and Optic Fiber, involving tests in the FUTUNa sodium loop. This loop is designed to produce very accurate sodium leak rates within a range around 1cm$^3$/min, the tests being performed at different temperature (up to 550DC) on large-diameter pipe mock-ups (D 800 mm) at ambient atmosphere. This paper presents the first series of tests carried out with various materials of the first and second layer of the detector. The results are compared and discussed as well as the observations made after removing the mock-ups. The most interesting result of the overall tests is a detection time less than 2 hours for the two types of detectors

Modelling the emergent dynamics and major metabolites of the human colonic microbiota

Funded by Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS) Acknowledgements We would like to thank Thanasis Vogogias, David Nutter and Alec Mann for their assistance in developing the software for this model. We also acknowledge the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS) for their financial support. Furthermore,many thanks go to the two anonymous reviewers whose hard work has greatly improved this paper.Peer reviewedPublisher PD

MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. It automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat

Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology

Objective: Individuals with obesity and type 2 diabetes differ from lean and healthy individuals in their abundance of certain gut microbial species and microbial gene richness. Abundance of Akkermansia muciniphila, a mucin-degrading bacterium, has been inversely associated with bodyfat mass and glucose intolerance in mice, but more evidence is needed in humans. The impact of diet and weight loss on this bacterial species is unknown. Our objective was to evaluate the association between fecal A. muciniphila abundance, fecal microbiome gene richness, diet, host characteristics, and their changes after calorie restriction (CR). Design: The intervention consisted of a 6-week CR period followed by a 6-week weight stabilization (WS) diet in overweight and obese adults (N=49, including 41 women). Fecal A. muciniphila abundance, fecal microbial gene richness, diet and bioclinical parameters were measured at baseline and after CR and WS. Results: At baseline A. muciniphila was inversely related to fasting glucose, waist-to-hip ratio, and subcutaneous adipocyte diameter. Subjects with higher gene richness and A. muciniphila abundance exhibited the healthiest metabolic status, particularly in fasting plasma glucose, plasma triglycerides and body fat distribution. Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. A. muciniphila was associated with microbial species known to be related to health. Conclusion: A. muciniphila is associated with a healthier metabolic status and better clinicaloutcomes after CR in overweight/obese adults, however the interaction between gut microbiota ecology and A. muciniphila has to be taken into account

Microbial-host co-metabolites are prodromal markers predicting phenotypic heterogeneity in behavior, obesity, and impaired glucose tolerance

The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1 H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50) and show that microbial-host co-metabolites are prodromal (i.e., early) markers predicting future divergence in metabolic (obesity and glucose homeostasis) and behavioral (anxiety and activity) outcomes with 94%– 100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO), a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT), and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity

Quantifying diet-induced metabolic changes of the human gut microbiome

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome-scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community and Systems-level Interactive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in in vitro. Focusing on metabolic interactions between the diet, gut microbiota and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals, and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention

Mineral and organic fertilization alters the microbiome of a soil nematode Dorylaimus stagnalis and its resistome

Although the effects of fertilization on the abundance and diversity of soil nematodes have been widely studied, the impact of fertilization on soil nematode microbiomes remains largely unknown. Here, we investigated how different fertilizers: no fertilizer, mineral fertilizer, clean slurry (pig manure with a reduced antibiotic burden) and dirty slurry (pig manure with antibiotics) affect the microbiome of a dominant soil nematode and its associated antibiotic resistance genes (ARGs). The results of 16S rRNA gene high throughput sequencing showed that the microbiome of the soil nematode Dorylaimus stagnalis is diverse (Shannon index: 9.95) and dominated by Proteobacteria (40.3%). Application of mineral fertilizers significantly reduced the diversity of the nematode microbiome (by 28.2%; P < 0.05) but increased the abundance of Proteobacteria (by 70.1%; P = 0.001). Microbial community analysis, using a null hypothesis model, indicated that microbiomes associated with the nematode are not neutrally assembled. Organic fertilizers also altered the diversity of the nematode microbiome, but had no impact on its composition as illustrated by principal coordinates analysis (PCoA). Interestingly, although no change of total ARGs was observed in the nematode microbiome and no significant relationship existed between nematode microbiome and resistome, the abundance of 48 out of a total of 75 ARGs was enriched in the organic fertilizer treatments. Thus, the data suggests that ARGs in the nematode microbiome still had a risk of horizontal gene transfer under fertilization and nematodes might be a potential refuge for ARGs