50 research outputs found

    The Carnegie Supernova Project: First Near-Infrared Hubble Diagram to z~0.7

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    The Carnegie Supernova Project (CSP) is designed to measure the luminosity distance for Type Ia supernovae (SNe Ia) as a function of redshift, and to set observational constraints on the dark energy contribution to the total energy content of the Universe. The CSP differs from other projects to date in its goal of providing an I-band {rest-frame} Hubble diagram. Here we present the first results from near-infrared (NIR) observations obtained using the Magellan Baade telescope for SNe Ia with 0.1 < z < 0.7. We combine these results with those from the low-redshift CSP at z <0.1 (Folatelli et al. 2009). We present light curves and an I-band Hubble diagram for this first sample of 35 SNe Ia and we compare these data to 21 new SNe Ia at low redshift. These data support the conclusion that the expansion of the Universe is accelerating. When combined with independent results from baryon acoustic oscillations (Eisenstein et al. 2005), these data yield Omega_m = 0.27 +/- 0.0 (statistical), and Omega_DE = 0.76 +/- 0.13 (statistical) +/- 0.09 (systematic), for the matter and dark energy densities, respectively. If we parameterize the data in terms of an equation of state, w, assume a flat geometry, and combine with baryon acoustic oscillations, we find that w = -1.05 +/- 0.13 (statistical) +/- 0.09 (systematic). The largest source of systematic uncertainty on w arises from uncertainties in the photometric calibration, signaling the importance of securing more accurate photometric calibrations for future supernova cosmology programs. Finally, we conclude that either the dust affecting the luminosities of SNe Ia has a different extinction law (R_V = 1.8) than that in the Milky Way (where R_V = 3.1), or that there is an additional intrinsic color term with luminosity for SNe Ia independent of the decline rate.Comment: 44 pages, 23 figures, 9 tables; Accepted for publication in the Astrophysical Journa

    First-Year Spectroscopy for the SDSS-II Supernova Survey

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    This paper presents spectroscopy of supernovae discovered in the first season of the Sloan Digital Sky Survey-II Supernova Survey. This program searches for and measures multi-band light curves of supernovae in the redshift range z = 0.05 - 0.4, complementing existing surveys at lower and higher redshifts. Our goal is to better characterize the supernova population, with a particular focus on SNe Ia, improving their utility as cosmological distance indicators and as probes of dark energy. Our supernova spectroscopy program features rapid-response observations using telescopes of a range of apertures, and provides confirmation of the supernova and host-galaxy types as well as precise redshifts. We describe here the target identification and prioritization, data reduction, redshift measurement, and classification of 129 SNe Ia, 16 spectroscopically probable SNe Ia, 7 SNe Ib/c, and 11 SNe II from the first season. We also describe our efforts to measure and remove the substantial host galaxy contamination existing in the majority of our SN spectra.Comment: Accepted for publication in The Astronomical Journal(47pages, 9 figures

    Lupus risk variants in the PXK locus alter B-cell receptor internalization

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    Genome wide association studies have identified variants in PXK that confer risk for humoral autoimmune diseases, including systemic lupus erythematosus (SLE or lupus), rheumatoid arthritis and more recently systemic sclerosis. While PXK is involved in trafficking of epidermal growth factor Receptor (EGFR) in COS-7 cells, mechanisms linking PXK to lupus pathophysiology have remained undefined. In an effort to uncover the mechanism at this locus that increases lupus-risk, we undertook a fine-mapping analysis in a large multi-ancestral study of lupus patients and controls. We define a large (257kb) common haplotype marking a single causal variant that confers lupus risk detected only in European ancestral populations and spans the promoter through the 3' UTR of PXK. The strongest association was found at rs6445972 with P &lt; 4.62 × 10-10, OR 0.81 (0.75 - 0.86). Using stepwise logistic regression analysis, we demonstrate that one signal drives the genetic association in the region. Bayesian analysis confirms our results, identifying a 95% credible set consisting of 172 variants spanning 202 kb. Functionally, we found that PXK operates on the B-cell antigen receptor (BCR); we confirmed that PXK influenced the rate of BCR internalization. Furthermore, we demonstrate that individuals carrying the risk haplotype exhibited a decreased rate of BCR internalization, a process known to impact B cell survival and cell fate. Taken together, these data define a new candidate mechanism for the genetic association of variants around PXK with lupus risk and highlight the regulation of intracellular trafficking as a genetically regulated pathway mediating human autoimmunity

    Host galaxy identification for supernova surveys

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    Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey

    The Relationship of Maternal Prepregnancy Body Mass Index and Pregnancy Weight Gain to Neurocognitive Function at Age 10 Years among Children Born Extremely Preterm

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    OBJECTIVE: To assess the association between maternal prepregnancy body mass index and adequacy of pregnancy weight gain in relation to neurocognitive function in school-aged children born extremely preterm. STUDY DESIGN: Study participants were 535 ten-year-old children enrolled previously in the prospective multicenter Extremely Low Gestational Age Newborns cohort study who were products of singleton pregnancies. Soon after delivery, mothers provided information about prepregnancy weight. Prepregnancy body mass index and adequacy of weight gain were characterized based on this information. Children underwent a neurocognitive evaluation at 10 years of age. RESULTS: Maternal prepregnancy obesity was associated with increased odds of a lower score for Differential Ability Scales-II Verbal IQ, for Developmental Neuropsychological Assessment-II measures of processing speed and visual fine motor control, and for Wechsler Individual Achievement Test-III Spelling. Children born to mothers who gained an excessive amount of weight were at increased odds of a low score on the Oral and Written Language Scales Oral Expression assessment. Conversely, children whose mother did not gain an adequate amount of weight were at increased odds of a lower score on the Oral and Written Language Scales Oral Expression and Wechsler Individual Achievement Test-III Word Reading assessments. CONCLUSION: In this cohort of infants born extremely preterm, maternal obesity was associated with poorer performance on some assessments of neurocognitive function. Our findings are consistent with the observational and experimental literature and suggest that opportunities may exist to mitigate risk through education and behavioral intervention before pregnancy

    An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

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    Contains fulltext : 158967.pdf (publisher's version ) (Open Access)Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine

    A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder

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    Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead
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