Pulmonary Predictors of Incident Diabetes in Smokers.

BACKGROUND: Diabetes mellitus and its complications are a large and increasing burden for health care worldwide. Reduced pulmonary function has been observed in diabetes (both type 1 and type 2), and this reduction is thought to occur prior to diagnosis. Other measures of pulmonary health are associated with diabetes, including lower exercise tolerance, greater dyspnea, lower quality of life (as measured by the St. George's Respiratory Questionaire [SGRQ]) and susceptibility to lung infection and these measures may also predate diabetes diagnosis. METHODS: We examined 7080 participants in the COPD Genetic Epidemiology (COPDGene) study who did not report diabetes at their baseline visit and who provided health status updates during 4.2 years of longitudinal follow-up (LFU). We used Cox proportional hazards modeling, censoring participants at final LFU contact, reported mortality or report of incident diabetes to model predictors of diabetes. These models were constructed using known risk factors as well as proposed markers related to pulmonary health, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FEV1/FVC, respiratory exacerbations (RE), 6-minute walk distance (6MWD), pulmonary associated quality of life (as measured by the SGRQ), corticosteroid use, chronic bronchitis and dyspnea. RESULTS: Over 21,519 person years of follow-up, 392 of 7080 participants reported incident diabetes which was associated with expected predictors; increased body mass index (BMI), high blood pressure, high cholesterol and current smoking status. Age, gender and accumulated smoking exposure were not associated with incident diabetes. Additionally, preserved ratio with impaired spirometry (PRISm) pattern pulmonary function, reduced 6MWD and any report of serious pulmonary events were associated with incident diabetes. CONCLUSIONS: This cluster of pulmonary indicators may aid clinicians in identifying and treating patients with pre- or undiagnosed diabetes

A Catastrophic Failure to Build a Massive Galaxy around a Supermassive Black Hole at z=3.84

We present observations of the stellar and molecular gas mass of SDSS J163909+282447.1, a luminous quasar at z = 3.84 with an extreme mass for a supermassive black hole (SMBH; M-BH 2.5 x 10(10) M-circle dot). The local SMBH mass-galaxy mass relation predicts a massive host galaxy with M-stellar greater than or similar to 10(12) M-circle dot for this quasar. Based on sensitive near-infrared imaging with adaptive optics (AO) using Subaru, the stellar light from the host is undetected, thus resulting in an upper limit on the mass, M-stellar < 6.3 x 10(10) M-circle dot, a factor of greater than or similar to 16 less than expected. The CO(4 - 3) observations at 0 ''.2 resolution using the Atacama Large Millimeter/submillimeter Array indicate a molecular gas mass from CO of M-H2 similar to 4.5 x 10(9) M-circle dot and a dynamical mass within a radius of 0.45 +/- 0.2 kpc of M-dyn = 4(-4)(+10) x 10(10) M-circle dot. With the SMBH accounting for similar to 60% of the dynamical mass and considering the amount of molecular gas, we find an upper limit on the stellar mass to be M-stellar less than or similar to 1.5 x 10 10 M-circle dot, a value consistent with the limit from Subaru AO imaging. Based on these results, this SMBH has one of the largest host stellar mass deficits known given its SMBH mass; hence, it is unclear how to grow a SMBH/host galaxy to such a state since there is not enough molecular gas available to form a substantial amount of stellar mass to make up for the difference. Any physical model is likely to require an earlier phase of super-Eddington accretion onto the SMBH

A multi-tier adaptive grid algorithm for the evolutionary multi-objective optimisation of complex problems

The multi-tier Covariance Matrix Adaptation Pareto Archived Evolution Strategy (m-CMA-PAES) is an evolutionary multi-objective optimisation (EMO) algorithm for real-valued optimisation problems. It combines a non-elitist adaptive grid based selection scheme with the efficient strategy parameter adaptation of the elitist Covariance Matrix Adaptation Evolution Strategy (CMA-ES). In the original CMA-PAES, a solution is selected as a parent for the next population using an elitist adaptive grid archiving (AGA) scheme derived from the Pareto Archived Evolution Strategy (PAES). In contrast, a multi-tiered AGA scheme to populate the archive using an adaptive grid for each level of non-dominated solutions in the considered candidate population is proposed. The new selection scheme improves the performance of the CMA-PAES as shown using benchmark functions from the ZDT, CEC09, and DTLZ test suite in a comparison against the (μ+λ) μ λ Multi-Objective Covariance Matrix Adaptation Evolution Strategy (MO-CMA-ES). In comparison with MO-CMA-ES, the experimental results show that the proposed algorithm offers up to a 69 % performance increase according to the Inverse Generational Distance (IGD) metric

Different genes interact with particulate matter and tobacco smoke exposure in affecting lung function decline in the general population

BACKGROUND: Oxidative stress related genes modify the effects of ambient air pollution or tobacco smoking on lung function decline. The impact of interactions might be substantial, but previous studies mostly focused on main effects of single genes. OBJECTIVES: We studied the interaction of both exposures with a broad set of oxidative-stress related candidate genes and pathways on lung function decline and contrasted interactions between exposures. METHODS: For 12679 single nucleotide polymorphisms (SNPs), change in forced expiratory volume in one second (FEV(1)), FEV(1) over forced vital capacity (FEV(1)/FVC), and mean forced expiratory flow between 25 and 75% of the FVC (FEF(25-75)) was regressed on interval exposure to particulate matter >10 microm in diameter (PM10) or packyears smoked (a), additive SNP effects (b), and interaction terms between (a) and (b) in 669 adults with GWAS data. Interaction p-values for 152 genes and 14 pathways were calculated by the adaptive rank truncation product (ARTP) method, and compared between exposures. Interaction effect sizes were contrasted for the strongest SNPs of nominally significant genes (p(interaction)>0.05). Replication was attempted for SNPs with MAF<10% in 3320 SAPALDIA participants without GWAS. RESULTS: On the SNP-level, rs2035268 in gene SNCA accelerated FEV(1)/FVC decline by 3.8% (p(interaction) = 2.5x10(-6)), and rs12190800 in PARK2 attenuated FEV1 decline by 95.1 ml p(interaction) = 9.7x10(-8)) over 11 years, while interacting with PM10. Genes and pathways nominally interacting with PM10 and packyears exposure differed substantially. Gene CRISP2 presented a significant interaction with PM10 (p(interaction) = 3.0x10(-4)) on FEV(1)/FVC decline. Pathway interactions were weak. Replications for the strongest SNPs in PARK2 and CRISP2 were not successful. CONCLUSIONS: Consistent with a stratified response to increasing oxidative stress, different genes and pathways potentially mediate PM10 and tobac smoke effects on lung function decline. Ignoring environmental exposures would miss these patterns, but achieving sufficient sample size and comparability across study samples is challengin

Observational and Physical Classification of Supernovae

This chapter describes the current classification scheme of supernovae (SNe). This scheme has evolved over many decades and now includes numerous SN Types and sub-types. Many of these are universally recognized, while there are controversies regarding the definitions, membership and even the names of some sub-classes; we will try to review here the commonly-used nomenclature, noting the main variants when possible. SN Types are defined according to observational properties; mostly visible-light spectra near maximum light, as well as according to their photometric properties. However, a long-term goal of SN classification is to associate observationally-defined classes with specific physical explosive phenomena. We show here that this aspiration is now finally coming to fruition, and we establish the SN classification scheme upon direct observational evidence connecting SN groups with specific progenitor stars. Observationally, the broad class of Type II SNe contains objects showing strong spectroscopic signatures of hydrogen, while objects lacking such signatures are of Type I, which is further divided to numerous subclasses. Recently a class of super-luminous SNe (SLSNe, typically 10 times more luminous than standard events) has been identified, and it is discussed. We end this chapter by briefly describing a proposed alternative classification scheme that is inspired by the stellar classification system. This system presents our emerging physical understanding of SN explosions, while clearly separating robust observational properties from physical inferences that can be debated. This new system is quantitative, and naturally deals with events distributed along a continuum, rather than being strictly divided into discrete classes. Thus, it may be more suitable to the coming era where SN numbers will quickly expand from a few thousands to millions of events.Comment: Extended final draft of a chapter in the "SN Handbook". Comments most welcom

Empirical Bayes analysis of single nucleotide polymorphisms

<p>Abstract</p> <p>Background</p> <p>An important goal of whole-genome studies concerned with single nucleotide polymorphisms (SNPs) is the identification of SNPs associated with a covariate of interest such as the case-control status or the type of cancer. Since these studies often comprise the genotypes of hundreds of thousands of SNPs, methods are required that can cope with the corresponding multiple testing problem. For the analysis of gene expression data, approaches such as the empirical Bayes analysis of microarrays have been developed particularly for the detection of genes associated with the response. However, the empirical Bayes analysis of microarrays has only been suggested for binary responses when considering expression values, i.e. continuous predictors.</p> <p>Results</p> <p>In this paper, we propose a modification of this empirical Bayes analysis that can be used to analyze high-dimensional categorical SNP data. This approach along with a generalized version of the original empirical Bayes method are available in the R package siggenes version 1.10.0 and later that can be downloaded from <url>http://www.bioconductor.org</url>.</p> <p>Conclusion</p> <p>As applications to two subsets of the HapMap data show, the empirical Bayes analysis of microarrays cannot only be used to analyze continuous gene expression data, but also be applied to categorical SNP data, where the response is not restricted to be binary. In association studies in which typically several ten to a few hundred SNPs are considered, our approach can furthermore be employed to test interactions of SNPs. Moreover, the posterior probabilities resulting from the empirical Bayes analysis of (prespecified) interactions/genotypes can also be used to quantify the importance of these interactions.</p

The Majority of MicroRNAs Detectable in Serum and Saliva Is Concentrated in Exosomes

There is an increasing interest in using microRNAs (miRNA) as biomarkers in autoimmune diseases. They are easily accessible in many body fluids but it is controversial if they are circulating freely or are encapsulated in microvesicles, particularly exosomes. We investigated if the majority of miRNas in serum and saliva are free-circulating or concentrated in exosomes. Exosomes were isolated by ultracentrifugation from fresh and frozen human serum and saliva. The amount of selected miRNAs extracted from the exosomal pellet and the exosome-depleted serum and saliva was compared by quantitative RT-PCR. Some miRNAs tested are ubiquitously expressed, others were previously reported as biomarkers. We included miRNAs previously reported to be free circulating and some thought to be exosome specific. The purity of exosome fraction was confirmed by electronmicroscopy and western blot. The concentration of miRNAs was consistently higher in the exosome pellet compared to the exosome-depleted supernatant. We obtained the same results using an equal volume or equal amount of total RNA as input of the RT-qPCR. The concentration of miRNA in whole, unfractionated serum, was between the exosomal pellet and the exosome-depleted supernatant. Selected miRNAs, which were detectable in exosomes, were undetectable in whole serum and the exosome-depleted supernantant. Exosome isolation improves the sensitivity of miRNA amplification from human biologic fluids. Exosomal miRNA should be the starting point for early biomarker studies to reduce the probability of false negative results involving low abundance miRNAs that may be missed by using unfractionated serum or saliva

RNase L Mediated Protection from Virus Induced Demyelination

IFN-α/β plays a critical role in limiting viral spread, restricting viral tropism and protecting mice from neurotropic coronavirus infection. However, the IFN-α/β dependent mechanisms underlying innate anti-viral functions within the CNS are poorly understood. The role of RNase L in viral encephalomyelitis was explored based on its functions in inhibiting translation, inducing apoptosis, and propagating the IFN-α/β pathway through RNA degradation intermediates. Infection of RNase L deficient (RL−/−) mice with a sub-lethal, demyelinating mouse hepatitis virus variant revealed that the majority of mice succumbed to infection by day 12 p.i. However, RNase L deficiency did not affect overall control of infectious virus, or diminish IFN-α/β expression in the CNS. Furthermore, increased morbidity and mortality could not be attributed to altered proinflammatory signals or composition of cells infiltrating the CNS. The unique phenotype of infected RL−/− mice was rather manifested in earlier onset and increased severity of demyelination and axonal damage in brain stem and spinal cord without evidence for enhanced neuronal infection. Increased tissue damage coincided with sustained brain stem infection, foci of microglia infection in grey matter, and increased apoptotic cells. These data demonstrate a novel protective role for RNase L in viral induced CNS encephalomyelitis, which is not reflected in overall viral control or propagation of IFN-α/β mediated signals. Protective function is rather associated with cell type specific and regional restriction of viral replication in grey matter and ameliorated neurodegeneration and demyelination