ALBERT

Description: Author(s): M. Chung, M. G. Collura, G. Flanagan, B. Freemire, P. M. Hanlet, M. R. Jana, R. P. Johnson, D. M. Kaplan, M. Leonova, A. Moretti, M. Popovic, T. Schwarz, A. Tollestrup, Y. Torun, and K. Yonehara A major technological challenge in building a muon cooling channel is operating rf cavities in multitesla external magnetic fields. We report the first proof-of-principle experiment of a high pressure gas-filled rf cavity for use with intense ionizing beams and strong external magnetic fields. rf po... [Phys. Rev. Lett. 111, 184802] Published Tue Oct 29, 2013

Description: Detection of the epoch of reionization H i signal requires a precise understanding of the intervening galaxies and AGN, both for instrumental calibration and foreground removal. We present a catalogue of 7394 extragalactic sources at 182 MHz detected in the RA = 0 field of the Murchison Widefield Array Epoch of Reionization observation programme. Motivated by unprecedented requirements for precision and reliability we develop new methods for source finding and selection. We apply machine learning methods to self-consistently classify the relative reliability of 9490 source candidates. A subset of 7466 are selected based on reliability class and signal-to-noise ratio criteria. These are statistically cross-matched to four other radio surveys using both position and flux density information. We find 7369 sources to have confident matches, including 90 partially resolved sources that split into a total of 192 sub-components. An additional 25 unmatched sources are included as new radio detections. The catalogue sources have a median spectral index of –0.85. Spectral flattening is seen towards lower frequencies with a median of –0.71 predicted at 182 MHz. The astrometric error is 7 arcsec compared to a 2.3 arcmin beam FWHM. The resulting catalogue covers ~1400 deg 2 and is complete to approximately 80 mJy within half beam power. This provides the most reliable discrete source sky model available to date in the MWA EoR0 field for precision foreground subtraction.

Description: We estimated local ancestry on the autosomes and X chromosome in a large US-based study of 12,793 Hispanic/Latino individuals using the RFMix method, and we compared different reference panels and approaches to local ancestry estimation on the X chromosome by means of Mendelian inconsistency rates as a proxy for accuracy. We developed a novel and straightforward approach to performing ancestry-specific PCA after finding artifactual behavior in the results from an existing approach. Using the ancestry-specific PCA, we found significant population structure within African, European, and Amerindian ancestries in the Hispanic/Latino individuals in our study. In the African ancestral component of the admixed individuals, individuals whose grandparents were from Central America clustered separately from individuals whose grandparents were from the Caribbean, and also from reference Yoruba and Mandenka West African individuals. In the European component, individuals whose grandparents were from Puerto Rico diverged partially from other background groups. In the Amerindian ancestral component, individuals clustered into multiple different groups depending on the grandparental country of origin. Therefore, local ancestry estimation provides further insight into the complex genetic structure of US Hispanic/Latino populations, which must be properly accounted for in genotype-phenotype association studies. It also provides a basis for admixture mapping and ancestry-specific allele frequency estimation, which are useful in the identification of risk factors for disease.

Description: We analyse a 154 MHz image made from a 12 h observation with the Murchison Widefield Array (MWA) to determine the noise contribution and behaviour of the source counts down to 30 mJy. The MWA image has a bandwidth of 30.72 MHz, a field-of-view within the half-power contour of the primary beam of 570 deg 2 , a resolution of 2.3 arcmin and contains 13 458 sources above 5. The rms noise in the centre of the image is 4–5 mJy beam –1 . The MWA counts are in excellent agreement with counts from other instruments and are the most precise ever derived in the flux density range 30–200 mJy due to the sky area covered. Using the deepest available source count data, we find that the MWA image is affected by sidelobe confusion noise at the 3.5 mJy beam –1 level, due to incompletely peeled and out-of-image sources, and classical confusion becomes apparent at 1.7 mJy beam –1 . This work highlights that (i) further improvements in ionospheric calibration and deconvolution imaging techniques would be required to probe to the classical confusion limit and (ii) the shape of low-frequency source counts, including any flattening towards lower flux densities, must be determined from deeper 150 MHz surveys as it cannot be directly inferred from higher frequency data.

Description: Langmuir DOI: 10.1021/la301661x

Description: Abstract Liu et al. (2018) used a virtual species approach to test the effects of outliers on species distribution models. In their simulations, they applied a threshold value over the simulated suitabilities to generate the species distributions, suggesting that using a probabilistic simulation approach would have been more complex and yield the same results. Here, we argue that using a probabilistic approach is not necessarily more complex and may significantly change results. Although the threshold approach may be justified under limited circumstances, the probabilistic approach has multiple advantages. First, it is in line with ecological theory, which largely assumes non‐threshold responses. Second, it is more general, as it includes the threshold as a limiting case. Third, it allows a better separation of the relevant intervening factors that influence model performance. Therefore, we argue that the probabilistic simulation approach should be used as a general standard in virtual species studies.

Description: Langmuir DOI: 10.1021/la2043153

Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kaplan, Matt -- England -- Nature. 2008 Feb 14;451(7180):760-2. doi: 10.1038/451760a.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/18272991" target="_blank"〉PubMed〈/a〉

Description: Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in 〉100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P 〈 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3039276/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3039276/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Teslovich, Tanya M -- Musunuru, Kiran -- Smith, Albert V -- Edmondson, Andrew C -- Stylianou, Ioannis M -- Koseki, Masahiro -- Pirruccello, James P -- Ripatti, Samuli -- Chasman, Daniel I -- Willer, Cristen J -- Johansen, Christopher T -- Fouchier, Sigrid W -- Isaacs, Aaron -- Peloso, Gina M -- Barbalic, Maja -- Ricketts, Sally L -- Bis, Joshua C -- Aulchenko, Yurii S -- Thorleifsson, Gudmar -- Feitosa, Mary F -- Chambers, John -- Orho-Melander, Marju -- Melander, Olle -- Johnson, Toby -- Li, Xiaohui -- Guo, Xiuqing -- Li, Mingyao -- Shin Cho, Yoon -- Jin Go, Min -- Jin Kim, Young -- Lee, Jong-Young -- Park, Taesung -- Kim, Kyunga -- Sim, Xueling -- Twee-Hee Ong, Rick -- Croteau-Chonka, Damien C -- Lange, Leslie A -- Smith, Joshua D -- Song, Kijoung -- Hua Zhao, Jing -- Yuan, Xin -- Luan, Jian'an -- Lamina, Claudia -- Ziegler, Andreas -- Zhang, Weihua -- Zee, Robert Y L -- Wright, Alan F -- Witteman, Jacqueline C M -- Wilson, James F -- Willemsen, Gonneke -- Wichmann, H-Erich -- Whitfield, John B -- Waterworth, Dawn M -- Wareham, Nicholas J -- Waeber, Gerard -- Vollenweider, Peter -- Voight, Benjamin F -- Vitart, Veronique -- Uitterlinden, Andre G -- Uda, Manuela -- Tuomilehto, Jaakko -- Thompson, John R -- Tanaka, Toshiko -- Surakka, Ida -- Stringham, Heather M -- Spector, Tim D -- Soranzo, Nicole -- Smit, Johannes H -- Sinisalo, Juha -- Silander, Kaisa -- Sijbrands, Eric J G -- Scuteri, Angelo -- Scott, James -- Schlessinger, David -- Sanna, Serena -- Salomaa, Veikko -- Saharinen, Juha -- Sabatti, Chiara -- Ruokonen, Aimo -- Rudan, Igor -- Rose, Lynda M -- Roberts, Robert -- Rieder, Mark -- Psaty, Bruce M -- Pramstaller, Peter P -- Pichler, Irene -- Perola, Markus -- Penninx, Brenda W J H -- Pedersen, Nancy L -- Pattaro, Cristian -- Parker, Alex N -- Pare, Guillaume -- Oostra, Ben A -- O'Donnell, Christopher J -- Nieminen, Markku S -- Nickerson, Deborah A -- Montgomery, Grant W -- Meitinger, Thomas -- McPherson, Ruth -- McCarthy, Mark I -- McArdle, Wendy -- Masson, David -- Martin, Nicholas G -- Marroni, Fabio -- Mangino, Massimo -- Magnusson, Patrik K E -- Lucas, Gavin -- Luben, Robert -- Loos, Ruth J F -- Lokki, Marja-Liisa -- Lettre, Guillaume -- Langenberg, Claudia -- Launer, Lenore J -- Lakatta, Edward G -- Laaksonen, Reijo -- Kyvik, Kirsten O -- Kronenberg, Florian -- Konig, Inke R -- Khaw, Kay-Tee -- Kaprio, Jaakko -- Kaplan, Lee M -- Johansson, Asa -- Jarvelin, Marjo-Riitta -- Janssens, A Cecile J W -- Ingelsson, Erik -- Igl, Wilmar -- Kees Hovingh, G -- Hottenga, Jouke-Jan -- Hofman, Albert -- Hicks, Andrew A -- Hengstenberg, Christian -- Heid, Iris M -- Hayward, Caroline -- Havulinna, Aki S -- Hastie, Nicholas D -- Harris, Tamara B -- Haritunians, Talin -- Hall, Alistair S -- Gyllensten, Ulf -- Guiducci, Candace -- Groop, Leif C -- Gonzalez, Elena -- Gieger, Christian -- Freimer, Nelson B -- Ferrucci, Luigi -- Erdmann, Jeanette -- Elliott, Paul -- Ejebe, Kenechi G -- Doring, Angela -- Dominiczak, Anna F -- Demissie, Serkalem -- Deloukas, Panagiotis -- de Geus, Eco J C -- de Faire, Ulf -- Crawford, Gabriel -- Collins, Francis S -- Chen, Yii-der I -- Caulfield, Mark J -- Campbell, Harry -- Burtt, Noel P -- Bonnycastle, Lori L -- Boomsma, Dorret I -- Boekholdt, S Matthijs -- Bergman, Richard N -- Barroso, Ines -- Bandinelli, Stefania -- Ballantyne, Christie M -- Assimes, Themistocles L -- Quertermous, Thomas -- Altshuler, David -- Seielstad, Mark -- Wong, Tien Y -- Tai, E-Shyong -- Feranil, Alan B -- Kuzawa, Christopher W -- Adair, Linda S -- Taylor, Herman A Jr -- Borecki, Ingrid B -- Gabriel, Stacey B -- Wilson, James G -- Holm, Hilma -- Thorsteinsdottir, Unnur -- Gudnason, Vilmundur -- Krauss, Ronald M -- Mohlke, Karen L -- Ordovas, Jose M -- Munroe, Patricia B -- Kooner, Jaspal S -- Tall, Alan R -- Hegele, Robert A -- Kastelein, John J P -- Schadt, Eric E -- Rotter, Jerome I -- Boerwinkle, Eric -- Strachan, David P -- Mooser, Vincent -- Stefansson, Kari -- Reilly, Muredach P -- Samani, Nilesh J -- Schunkert, Heribert -- Cupples, L Adrienne -- Sandhu, Manjinder S -- Ridker, Paul M -- Rader, Daniel J -- van Duijn, Cornelia M -- Peltonen, Leena -- Abecasis, Goncalo R -- Boehnke, Michael -- Kathiresan, Sekar -- 068545/Z/02/Wellcome Trust/United Kingdom -- 076113/B/04/Z/Wellcome Trust/United Kingdom -- 077016/Z/05/Z/Wellcome Trust/United Kingdom -- 079895/Wellcome Trust/United Kingdom -- 1Z01 HG000024/HG/NHGRI NIH HHS/ -- 5R01DK06833603/DK/NIDDK NIH HHS/ -- 5R01DK07568102/DK/NIDDK NIH HHS/ -- 5R01HL087679-02/HL/NHLBI NIH HHS/ -- 5R01HL08770003/HL/NHLBI NIH HHS/ -- 5R01HL08821502/HL/NHLBI NIH HHS/ -- CA 047988/CA/NCI NIH HHS/ -- CZB/4/710/Chief Scientist Office/United Kingdom -- DK062370/DK/NIDDK NIH HHS/ -- DK063491/DK/NIDDK NIH HHS/ -- DK072193/DK/NIDDK NIH HHS/ -- DK078150/DK/NIDDK NIH HHS/ -- DK56350/DK/NIDDK NIH HHS/ -- ES10126/ES/NIEHS NIH HHS/ -- G0000934/Medical Research Council/United Kingdom -- G0401527/Medical Research Council/United Kingdom -- G0601966/Medical Research Council/United Kingdom -- G0700931/Medical Research Council/United Kingdom -- G0701863/Medical Research Council/United Kingdom -- G0801056/Medical Research Council/United Kingdom -- G0801566/Medical Research Council/United Kingdom -- G9521010/Medical Research Council/United Kingdom -- G9521010D/Medical Research Council/United Kingdom -- HHSN268200625226C/PHS HHS/ -- HL 04381/HL/NHLBI NIH HHS/ -- HL 080467/HL/NHLBI NIH HHS/ -- HL-54776/HL/NHLBI NIH HHS/ -- HL085144/HL/NHLBI NIH HHS/ -- K99 HL098364/HL/NHLBI NIH HHS/ -- K99 HL098364-01/HL/NHLBI NIH HHS/ -- K99HL094535/HL/NHLBI NIH HHS/ -- M01-RR00425/RR/NCRR NIH HHS/ -- MC_QA137934/Medical Research Council/United Kingdom -- MC_U106179471/Medical Research Council/United Kingdom -- MC_U106188470/Medical Research Council/United Kingdom -- MC_U127561128/Medical Research Council/United Kingdom -- N01 HC-15103/HC/NHLBI NIH HHS/ -- N01 HC-55222/HC/NHLBI NIH HHS/ -- N01-AG-12100/AG/NIA NIH HHS/ -- N01-HC-25195/HC/NHLBI NIH HHS/ -- N01-HC-35129/HC/NHLBI NIH HHS/ -- N01-HC-45133/HC/NHLBI NIH HHS/ -- N01-HC-55015/HC/NHLBI NIH HHS/ -- N01-HC-55016/HC/NHLBI NIH HHS/ -- N01-HC-55018/HC/NHLBI NIH HHS/ -- N01-HC-55019/HC/NHLBI NIH HHS/ -- N01-HC-55020/HC/NHLBI NIH HHS/ -- N01-HC-55021/HC/NHLBI NIH HHS/ -- N01-HC-55022/HC/NHLBI NIH HHS/ -- N01-HC-75150/HC/NHLBI NIH HHS/ -- N01-HC-85079/HC/NHLBI NIH HHS/ -- N01-HC-85080/HC/NHLBI NIH HHS/ -- N01-HC-85081/HC/NHLBI NIH HHS/ -- N01-HC-85082/HC/NHLBI NIH HHS/ -- N01-HC-85083/HC/NHLBI NIH HHS/ -- N01-HC-85084/HC/NHLBI NIH HHS/ -- N01-HC-85085/HC/NHLBI NIH HHS/ -- N01-HC-85086/HC/NHLBI NIH HHS/ -- N01-HG-65403/HG/NHGRI NIH HHS/ -- N02-HL-6-4278/HL/NHLBI NIH HHS/ -- PG/02/128/British Heart Foundation/United Kingdom -- PG/08/094/British Heart Foundation/United Kingdom -- PG/08/094/26019/British Heart Foundation/United Kingdom -- R01 DK072193/DK/NIDDK NIH HHS/ -- R01 DK078150/DK/NIDDK NIH HHS/ -- R01 HL087647/HL/NHLBI NIH HHS/ -- R01 HL087676/HL/NHLBI NIH HHS/ -- R01 HL089650/HL/NHLBI NIH HHS/ -- R01HL086694/HL/NHLBI NIH HHS/ -- R01HL087641/HL/NHLBI NIH HHS/ -- R01HL087652/HL/NHLBI NIH HHS/ -- R01HL59367/HL/NHLBI NIH HHS/ -- R24 HD050924/HD/NICHD NIH HHS/ -- RC1 HL099634/HL/NHLBI NIH HHS/ -- RC1 HL099634-02/HL/NHLBI NIH HHS/ -- RC1 HL099793/HL/NHLBI NIH HHS/ -- RC2 HL101864,/HL/NHLBI NIH HHS/ -- RC2 HL102419/HL/NHLBI NIH HHS/ -- RG/07/005/23633/British Heart Foundation/United Kingdom -- RR20649/RR/NCRR NIH HHS/ -- SP/08/005/25115/British Heart Foundation/United Kingdom -- T32 GM007092/GM/NIGMS NIH HHS/ -- T32 HG00040/HG/NHGRI NIH HHS/ -- T32HL007208/HL/NHLBI NIH HHS/ -- TW05596/TW/FIC NIH HHS/ -- U01 DK062370/DK/NIDDK NIH HHS/ -- U01 DK062418/DK/NIDDK NIH HHS/ -- U01 HL069757/HL/NHLBI NIH HHS/ -- U01 HL080295/HL/NHLBI NIH HHS/ -- U01HG004402/HG/NHGRI NIH HHS/ -- U54 RR020278/RR/NCRR NIH HHS/ -- UL1RR025005/RR/NCRR NIH HHS/ -- Intramural NIH HHS/ -- England -- Nature. 2010 Aug 5;466(7307):707-13. doi: 10.1038/nature09270.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20686565" target="_blank"〉PubMed〈/a〉

Description: Understanding the timings of interhemispheric climate changes during the Holocene, along with their causes, remains a major problem of climate science. Here, we present a high-resolution 10Be chronology of glacier fluctuations in New Zealand's Southern Alps over the past 7000 years, including at least five events during the last millennium. The extents of glacier advances decreased from the middle to the late Holocene, in contrast with the Northern Hemisphere pattern. Several glacier advances occurred in New Zealand during classic northern warm periods. These findings point to the importance of regional driving and/or amplifying mechanisms. We suggest that atmospheric circulation changes in the southwest Pacific were one important factor in forcing high-frequency Holocene glacier fluctuations in New Zealand.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Schaefer, Joerg M -- Denton, George H -- Kaplan, Michael -- Putnam, Aaron -- Finkel, Robert C -- Barrell, David J A -- Andersen, Bjorn G -- Schwartz, Roseanne -- Mackintosh, Andrew -- Chinn, Trevor -- Schluchter, Christian -- New York, N.Y. -- Science. 2009 May 1;324(5927):622-5. doi: 10.1126/science.1169312.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Geochemistry, Lamont-Doherty Earth Observatory (LDEO), Palisades, NY 10964, USA. schaefer@ldeo.columbia.edu〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/19407198" target="_blank"〉PubMed〈/a〉