Circulating and tissue microRNAs as a potential diagnostic biomarker in patients with thrombotic events

Venous and arterial thrombosis are conditions that have a considerable burden if left untreated. The hypoxia-induced by the occluded vessel can disrupt the circulation of any organ, the cornerstone of treating thrombosis is rapid diagnosis and appropriate treatment. Diagnosis of thrombosis may be made by using laboratory tests or imaging techniques in individuals who have clinical manifestations of a thrombotic event. The use of serum micro ribonucleic acids (RNAs) has recently been applied to the diagnosis of thrombosis. These small RNA molecules are emerging as new diagnostic markers but have had very limited applications in vascular disease. Most of the articles provided various microRNAs with different levels of accuracy. However, there remains a lack of an appropriate panel of the most specific microRNA in the literature. The purpose of the present review was to summarize the existing data on the use of microRNAs as a diagnostic biomarker for venous thrombosis.     

Pyramidal Neurons Derived from Human Pluripotent Stem Cells Integrate Efficiently into Mouse Brain Circuits In Vivo

Download : Download video (68MB)     

Immune gene variability influences roe deer natal dispersal

Dispersal is a key life‐history trait governing the response of individuals, populations and species to changing environmental conditions. In the context of global change, it is therefore essential to better understand the respective role of condition‐, phenotype‐ and genetic‐dependent drivers of dispersal behaviour. Although the importance of immune function and pathogen infestation in determining patterns of dispersal is increasingly recognised, no study to our knowledge has yet investigated the influence of immune gene variability on dispersal behaviour. Here, we filled this knowledge gap by assessing whether individual heterozygosity at five immune gene loci (one from the Major histocompatibility complex and four from encoding Toll‐like receptors) influences roe deer natal dispersal. We found that dispersal propensity was affected by immune gene diversity, suggesting potential pathogen‐mediated selection through over‐dominance. However, the direction of this effect differed between high and low quality individuals, suggesting that dispersal propensity is driven by two different mechanisms. In support of the condition‐dependent dispersal hypothesis, dispersal propensity increased with increasing body mass and, among high quality individuals only (standardized body mass > 18 kg), with increasing immune gene diversity. However, among poor quality individuals, we observed the opposite pattern such that dispersal propensity was higher for individuals with lower immune gene diversity. We suggest that these poor quality individuals expressed an emergency dispersal tactic in an attempt to escape a heavily infested environment associated with poor fitness prospects. Our results have potentially important consequences in terms of population genetics and demography, as well as host–pathogen evolution.     

Linking demographic responses and life history tactics from longitudinal data in mammals

In stochastic environments, a change in a demographic parameter can influence the population growth rate directly or via a resulting impact on age structure. Stochastic elasticity of the long‐run stochastic growth rate λ_s to a demographic parameter offers a suitable way to measure the overall demographic response because it includes both the direct effect of changing the demographic parameter and its indirect effect through changes in the age structure. From 25 mammalian populations with contrasting life histories, we investigated how pace of life and population growth rate influence the demographic responses (measured as the relative contributions of the direct and indirect components of stochastic elasticity on λ_s). We found that in short‐lived species, the change in population structure resulting from an increase in yearling survival leads to an additional increase in λ_s, whereas in long‐lived species, the same change in population structure leads to a decrease. Short‐lived species thus display a boom‐bust life history strategy contrary to long‐lived species, for which the long lifespan dampens the demographic consequences of changing age structure. Irrespective of the species’ life history strategy, the change in population age structure resulting from an increase in adult survival leads to an additional increase in λ_s due to an increase of the proportion of mature individuals in the population. On the contrary, a change in population age structure resulting from an increase of reproductive performance leads to a decrease in λ_s that is due to the increase of the proportion of immature individuals in the population. Our comparative analysis of stochastic elasticity patterns in mammals shows the existence of different demographic responses to changes in age structure between short‐ and long‐lived species, which improves our understanding of population dynamics in variable environments in relation to the species‐specific pace of life.     

Genomic and physiological analysis reveals versatile metabolic capacity of deep-sea <Emphasis Type="Italic">Photobacterium phosphoreum</Emphasis> ANT-2200

Bacteria of the genus Photobacterium thrive worldwide in oceans and show substantial eco-physiological diversity including free-living, symbiotic and piezophilic life styles. Genomic characteristics underlying this variability across species are poorly understood. Here we carried out genomic and physiological analysis of Photobacterium phosphoreum strain ANT-2200, the first deep-sea luminous bacterium of which the genome has been sequenced. Using optical mapping we updated the genomic data and reassembled it into two chromosomes and a large plasmid. Genomic analysis revealed a versatile energy metabolic potential and physiological analysis confirmed its growth capacity by deriving energy from fermentation of glucose or maltose, by respiration with formate as electron donor and trimethlyamine N-oxide (TMAO), nitrate or fumarate as electron acceptors, or by chemo-organo-heterotrophic growth in rich media. Despite that it was isolated at a site with saturated dissolved oxygen, the ANT-2200 strain possesses four gene clusters coding for typical anaerobic enzymes, the TMAO reductases. Elevated hydrostatic pressure enhances the TMAO reductase activity, mainly due to the increase of isoenzyme TorA1. The high copy number of the TMAO reductase isoenzymes and pressure-enhanced activity might imply a strategy developed by bacteria to adapt to deep-sea habitats where the instant TMAO availability may increase with depth.     

Protein side chain conformation predictions with an MMGBSA energy function

The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an “MMGBSA” energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803–819. © 2016 Wiley Periodicals, Inc.     

Contribution of Flooded Soils to Sediment and Nutrient Fluxes in a Hydropower Reservoir (Sarrans,Central France)

Ecosystems - When a water reservoir is created, the pre-existing soils and vegetation are flooded. Here, we took advantage of the complete emptying of the Sarrans Reservoir, which was flooded...     

Importance of a pilot study for non-invasive genetic sampling: genotyping errors and population size estimation in red deer

Population size information is critical for managing endangered or harvested populations. Population size can now be estimated from non-invasive genetic sampling. However, pitfalls remain such as genotyping errors (allele dropout and false alleles at microsatellite loci). To evaluate the feasibility of non-invasive sampling (e.g., for population size estimation), a pilot study is required. Here, we present a pilot study consisting of (i) a genetic step to test loci amplification and to estimate allele frequencies and genotyping error rates when using faecal DNA, and (ii) a simulation step to quantify and minimise the effects of errors on estimates of population size. The pilot study was conducted on a population of red deer in a fenced natural area of 5440 ha, in France. Twelve microsatellite loci were tested for amplification and genotyping errors. The genotyping error rates for microsatellite loci were 0–0.83 (mean=0.2) for allele dropout rates and 0–0.14 (mean=0.02) for false allele rates, comparable to rates encountered in other non-invasive studies. Simulation results suggest we must conduct 6 PCR amplifications per sample (per locus) to achieve approximately 97% correct genotypes. The 3% error rate appears to have little influence on the accuracy and precision of population size estimation. This paper illustrates the importance of conducting a pilot study (including genotyping and simulations) when using non-invasive sampling to study threatened or managed populations.