Risk factors for heart failure in patients with type 2 diabetes mellitus and stage 4 chronic kidney disease treated with bardoxolone methyl

Background: A phase 3 randomized clinical trial was designed to test whether bardoxolone methyl, a nuclear factor erythroid-2–related factor 2 (Nrf2) activator, slows progression to end-stage renal disease in patients with stage 4 chronic kidney disease and type 2 diabetes mellitus. The trial was terminated because of an increase in heart failure in the bardoxolone methyl group; many of the events were clinically associated with fluid retention.<p></p> Methods and Results: We randomized 2,185 patients with type 2 diabetes mellitus (T2DM) and stage 4 chronic kidney disease (CKD) (estimated glomerular filtration rate 15 to <30 mL min−1 1.73 m−2) to once-daily bardoxolone methyl (20 mg) or placebo. We used classification and regression tree analysis to identify baseline factors predictive of heart failure or fluid overload events. Elevated baseline B-type natriuretic peptide and previous hospitalization for heart failure were identified as predictors of heart failure events; bardoxolone methyl increased the risk of heart failure by 60% in patients with these risk factors. For patients without these baseline characteristics, the risk for heart failure events among bardoxolone methyl– and placebo-treated patients was similar (2%). The same risk factors were also identified as predictors of fluid overload and appeared to be related to other serious adverse events.<p></p> Conclusions: Bardoxolone methyl contributed to events related to heart failure and/or fluid overload in a subpopulation of susceptible patients with an increased risk for heart failure at baseline. Careful selection of participants and vigilant monitoring of the study drug will be required in any future trials of bardoxolone methyl to mitigate the risk of heart failure and other serious adverse events.<p></p&gt

Metagenomic Analysis of the Bioremediation of Diesel-Contaminated Canadian High Arctic Soils

As human activity in the Arctic increases, so does the risk of hydrocarbon pollution events. On site bioremediation of contaminated soil is the only feasible clean up solution in these remote areas, but degradation rates vary widely between bioremediation treatments. Most previous studies have focused on the feasibility of on site clean-up and very little attention has been given to the microbial and functional communities involved and their ecology. Here, we ask the question: which microorganisms and functional genes are abundant and active during hydrocarbon degradation at cold temperature? To answer this question, we sequenced the soil metagenome of an ongoing bioremediation project in Alert, Canada through a time course. We also used reverse-transcriptase real-time PCR (RT-qPCR) to quantify the expression of several hydrocarbon-degrading genes. Pseudomonas species appeared as the most abundant organisms in Alert soils right after contamination with diesel and excavation (t = 0) and one month after the start of the bioremediation treatment (t = 1m), when degradation rates were at their highest, but decreased after one year (t = 1y), when residual soil hydrocarbons were almost depleted. This trend was also reflected in hydrocarbon degrading genes, which were mainly affiliated with Gammaproteobacteria at t = 0 and t = 1m and with Alphaproteobacteria and Actinobacteria at t = 1y. RT-qPCR assays confirmed that Pseudomonas and Rhodococcus species actively expressed hydrocarbon degradation genes in Arctic biopile soils. Taken together, these results indicated that biopile treatment leads to major shifts in soil microbial communities, favoring aerobic bacteria that can degrade hydrocarbons

Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits

Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks

Complete Genome Sequences of Cluster A Mycobacteriophages BobSwaget, Fred313, KADY, Lokk, MyraDee, Stagni, and StepMih

Seven mycobacteriophages from distinct geographical locations were isolated, using Mycobacterium smegmatis mc2155 as the host, and then purified and sequenced. All of the genomes are related to cluster A mycobacteriophages, BobSwaget and Lokk in subcluster A2; Fred313, KADY, Stagni, and StepMih in subcluster A3; and MyraDee in subcluster A18, the first phage to be assigned to that subcluster

Decoding human fetal liver haematopoiesis.

Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs.We acknowledge funding from the Wellcome Human Cell Atlas Strategic Science Support (WT211276/Z/18/Z); M.H. is funded by Wellcome (WT107931/Z/15/Z), The Lister Institute for Preventive Medicine and NIHR and Newcastle-Biomedical Research Centre; S.A.T. is funded by Wellcome (WT206194), ERC Consolidator and EU MRG-Grammar awards and; S.B. is funded by Wellcome (WT110104/Z/15/Z) and St. Baldrick’s Foundation; E.L. is funded by a Wellcome Sir Henry Dale and Royal Society Fellowships, European Haematology Association, Wellcome and MRC to the Wellcome-MRC Cambridge Stem Cell Institute and BBSRC

Chronic Consumption of Farmed Salmon Containing Persistent Organic Pollutants Causes Insulin Resistance and Obesity in Mice

Background: Dietary interventions are critical in the prevention of metabolic diseases. Yet, the effects of fatty fish consumption on type 2 diabetes remain unclear. The aim of this study was to investigate whether a diet containing farmed salmon prevents or contributes to insulin resistance in mice. Methodology/Principal Findings: Adult male C57BL/6J mice were fed control diet (C), a very high-fat diet without or with farmed Atlantic salmon fillet (VHF and VHF/S, respectively), and Western diet without or with farmed Atlantic salmon fillet (WD and WD/S, respectively). Other mice were fed VHF containing farmed salmon fillet with reduced concentrations of persistent organic pollutants (VHF/S-POPs). We assessed body weight gain, fat mass, insulin sensitivity, glucose tolerance, ex vivo muscle glucose uptake, performed histology and immunohistochemistry analysis, and investigated gene and protein expression. In comparison with animals fed VHF and WD, consumption of both VHF/S and WD/S exaggerated insulin resistance, visceral obesity, and glucose intolerance. In addition, the ability of insulin to stimulate Akt phosphorylation and muscle glucose uptake was impaired in mice fed farmed salmon. Relative to VHF/S-fed mice, animals fed VHF/S-POPs had less body burdens of POPs, accumulated less visceral fat, and had reduced mRNA levels of TNFa as well as macrophage infiltration in adipose tissue. VHF/S-POPs-fed mice further exhibited better insulin sensitivity and glucose tolerance than mice fed VHF/S. Conclusions/Significance: Our data indicate that intake of farmed salmon fillet contributes to several metabolic disorders linked to type 2 diabetes and obesity, and suggest a role of POPs in these deleterious effects. Overall, these findings may participate to improve nutritional strategies for the prevention and therapy of insulin resistance

Mitogenomic phylogenetic analyses of the Delphinidae with an emphasis on the Globicephalinae

BACKGROUND: Previous DNA-based phylogenetic studies of the Delphinidae family suggest it has undergone rapid diversification, as characterised by unresolved and poorly supported taxonomic relationships (polytomies) for some of the species within this group. Using an increased amount of sequence data we test between alternative hypotheses of soft polytomies caused by rapid speciation, slow evolutionary rate and/or insufficient sequence data, and hard polytomies caused by simultaneous speciation within this family. Combining the mitogenome sequences of five new and 12 previously published species within the Delphinidae, we used Bayesian and maximum-likelihood methods to estimate the phylogeny from partitioned and unpartitioned mitogenome sequences. Further ad hoc tests were then conducted to estimate the support for alternative topologies. RESULTS: We found high support for all the relationships within our reconstructed phylogenies, and topologies were consistent between the Bayesian and maximum-likelihood trees inferred from partitioned and unpartitioned data. Resolved relationships included the placement of the killer whale (Orcinus orca) as sister taxon to the rest of the Globicephalinae subfamily, placement of the Risso's dolphin (Grampus griseus) within the Globicephalinae subfamily, removal of the white-beaked dolphin (Lagenorhynchus albirostris) from the Delphininae subfamily and the placement of the rough-toothed dolphin (Steno bredanensis) as sister taxon to the rest of the Delphininae subfamily rather than within the Globicephalinae subfamily. The additional testing of alternative topologies allowed us to reject all other putative relationships, with the exception that we were unable to reject the hypothesis that the relationship between L. albirostris and the Globicephalinae and Delphininae subfamilies was polytomic. CONCLUSION: Despite their rapid diversification, the increased sequence data yielded by mitogenomes enables the resolution of a strongly supported, bifurcating phylogeny, and a chronology of the divergences within the Delphinidae family. This highlights the benefits and potential application of large mitogenome datasets to resolve long-standing phylogenetic uncertainties

The Genome of Mycobacterium Africanum West African 2 Reveals a Lineage-Specific Locus and Genome Erosion Common to the M. tuberculosis Complex

Mycobacterium africanum, a close relative of M. tuberculosis, is studied for the following reasons: M. africanum is commonly isolated from West African patients with tuberculosis yet has not spread beyond this region, it is more common in HIV infected patients, and it is less likely to lead to tuberculosis after one is exposed to an infectious case. Understanding this organism's unique biology gets a boost from the decoding of its genome, reported in this issue. For example, genome analysis reveals that M. africanum contains a region shared with “ancient” lineages in the M. tuberculosis complex and other mycobacterial species, which was lost independently from both M. tuberculosis and M. bovis. This region encodes a protein involved in transmembrane transport. Furthermore, M. africanum has lost genes, including a known virulence gene and genes for vitamin synthesis, in addition to an intact copy of a gene that may increase its susceptibility to antibiotics that are insufficiently active against M. tuberculosis. Finally, the genome sequence and analysis reported here will aid in the development of new diagnostics and vaccines against tuberculosis, which need to take into account the differences between M. africanum and other species in order to be effective worldwide

Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families.

BACKGROUND: Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS: Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS: Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS: Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity