| 1. |
- Elsik, Christine G., et al.
(författare)
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The Genome Sequence of Taurine Cattle : A Window to Ruminant Biology and Evolution
- 2009
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 324:5926, s. 522-528
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Tidskriftsartikel (refereegranskat)abstract
- To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
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| 2. |
- Kessler, Richard, et al.
(författare)
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First-Year Sloan Digital Sky Survey-II Supernova Results : Hubble Diagram and Cosmological Parameters
- 2009
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Ingår i: Astrophysical Journal Supplement Series. - : American Astronomical Society. - 0067-0049 .- 1538-4365. ; 185:1, s. 32-84
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Tidskriftsartikel (refereegranskat)abstract
- We present measurements of the Hubble diagram for 103 Type Ia supernovae (SNe) with redshifts 0.04 < z < 0.42, discovered during the first season (Fall 2005) of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. These data fill in the redshift "desert" between low- and high-redshift SN Ia surveys. Within the framework of the MLCS2K2 light-curve fitting method, we use the SDSS-II SN sample to infer the mean reddening parameter for host galaxies, RV = 2.18 ± 0.14stat ± 0.48syst, and find that the intrinsic distribution of host-galaxy extinction is well fitted by an exponential function, P(AV ) = exp(-AV /τV), with τV = 0.334 ± 0.088 mag. We combine the SDSS-II measurements with new distance estimates for published SN data from the ESSENCE survey, the Supernova Legacy Survey (SNLS), the Hubble Space Telescope (HST), and a compilation of Nearby SN Ia measurements. A new feature in our analysis is the use of detailed Monte Carlo simulations of all surveys to account for selection biases, including those from spectroscopic targeting. Combining the SN Hubble diagram with measurements of baryon acoustic oscillations from the SDSS Luminous Red Galaxy sample and with cosmic microwave background temperature anisotropy measurements from the Wilkinson Microwave Anisotropy Probe, we estimate the cosmological parameters w and ΩM, assuming a spatially flat cosmological model (FwCDM) with constant dark energy equation of state parameter, w. We also consider constraints upon ΩM and ΩΛ for a cosmological constant model (ΛCDM) with w = -1 and non-zero spatial curvature. For the FwCDM model and the combined sample of 288 SNe Ia, we find w = -0.76 ± 0.07(stat) ± 0.11(syst), ΩM = 0.307 ± 0.019(stat) ± 0.023(syst) using MLCS2K2 and w = -0.96 ± 0.06(stat) ± 0.12(syst), ΩM = 0.265 ± 0.016(stat) ± 0.025(syst) using the SALT-II fitter. We trace the discrepancy between these results to a difference in the rest-frame UV model combined with a different luminosity correction from color variations; these differences mostly affect the distance estimates for the SNLS and HST SNe. We present detailed discussions of systematic errors for both light-curve methods and find that they both show data-model discrepancies in rest-frame U band. For the SALT-II approach, we also see strong evidence for redshift-dependence of the color-luminosity parameter (β). Restricting the analysis to the 136 SNe Ia in the Nearby+SDSS-II samples, we find much better agreement between the two analysis methods but with larger uncertainties: w = -0.92 ± 0.13(stat)+0.10 -0.33(syst) for MLCS2K2 and w = -0.92 ± 0.11(stat)+0.07 -0.15 (syst) for SALT-II.
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| 3. |
- Davis, Faith G, et al.
(författare)
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Issues of diagnostic review in brain tumor studies : from the brain tumor epidemiology consortium
- 2008
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 17:3, s. 484-489
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Tidskriftsartikel (refereegranskat)abstract
- Epidemiologists routinely conduct centralized single pathology reviews to minimize interobserver diagnostic variability, but this practice does not facilitate the combination of studies across geographic regions and institutions where diagnostic practices differ. A meeting of neuropathologists and epidemiologists focused on brain tumor classification issues in the context of protocol needs for consortial studies (http://epi.grants.cancer.gov/btec/). It resulted in recommendations relevant to brain tumors and possibly other rare disease studies. Two categories of brain tumors have enough general agreement over time, across regions, and between individual pathologists that one can consider using existing diagnostic data without further review: glioblastomas and meningiomas (as long as uniform guidelines such as those provided by the WHO are used). Prospective studies of these tumors benefit from collection of pathology reports, at a minimum recording the pathology department and classification system used in the diagnosis. Other brain tumors, such as oligodendroglioma, are less distinct and require careful histopathologic review for consistent classification across study centers. Epidemiologic study protocols must consider the study specific aims, diagnostic changes that have taken place over time, and other issues unique to the type(s) of tumor being studied. As diagnostic changes are being made rapidly, there are no readily available answers on disease classification issues. It is essential that epidemiologists and neuropathologists collaborate to develop appropriate study designs and protocols for specific hypothesis and populations.
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