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1. Mapping the intracluster medium temperature in the era of NIKA2 and MUSTANG-2

Author

Ruppin F., Adam R., Ade P., Ajeddig H., André P., Artis E., Aussel H., Beelen A., Benoît A., Berta S., Bing L., Bourrion O., Brodwin M., Calvo M., Catalano A., Decker B., De Petris M., Désert F.-X., Doyle S., Driessen E. F. C., Eisenhardt P. R. M., Gomez A., Gonzalez A. H., Goupy J., Kéruzoré F., Kramer C., Ladjelate B., Lagache G., Leclercq S., Lestrade J.-F., Macías-Pérez J.-F., Maury A., Mauskopf P., Mayet F., McDonald M., Monfardini A., Moravec E., Muñoz-Echeverría M., Perotto L., Pisano G., Ponthieu N., Revéret V., Rigby A. J., Ritacco A., Romero C., Roussel H., Schuster K., Shu S., Sievers A., Stanford S.A., Stern D., Tucker C., and Zylka R.

Subjects
Physics, QC1-999
Abstract

We present preliminary results from an on-going program that aims at mapping the intracluster medium (ICM) temperature of high redshift galaxy clusters from the MaDCoWS sample using a joint analysis of shallow X-ray data obtained by Chandra and high angular resolution Sunyaev-Zel’dovich (SZ) observations realized with the NIKA2 and MUSTANG-2 cameras. We also present preliminary results from an on-going Open Time program within the NIKA2 collaboration that aims at mapping the ICM temperature of a galaxy cluster at z = 0.45 from the resolved detection of the relativistic corrections to the SZ spectrum. These studies demonstrate how high angular resolution SZ observations will play a major role in the coming decade to push the investigation of ICM dynamics and non-gravitational processes to high redshift before the next generation X-ray observatories come into play.

Published
2022
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2. Mapping the gas thermodynamic properties of the massive cluster merger MOO J1142+1527 at z = 1.2

Author

Ruppin F., Adam R., Ade P., André P., Andrianasolo A., Arnaud M., Aussel H., Bartalucci I., Bautz M.W., Beelen A., Benoît A., Bideaud A., Bourrion O., Brodwin M., Calvo M., Catalano A., Comis B., Decker B., De Petris M., Désert F.-X., Doyle S., Driessen E. F. C., Eisenhardt P. R. M., Gomez A., Gonzalez A. H., Goupy J., Kéruzoré F., Kramer C., Ladjelate B., Lagache G., Leclercq S., Lestrade J.-F., Macías-Pérez J.F., Mauskopf P., Mayet F., McDonald M., Monfardini A., Moravec E., Perotto L., Pisano G., Pointecouteau E., Ponthieu N., Pratt G. W., Revéret V., Ritacco A., Romero C., Roussel H., Schuster K., Shu S., Sievers A., Stanford S. A., Stern D., Tucker C., and Zylka R.

Subjects
Physics, QC1-999
Abstract

We present the results of the analysis of the very massive cluster MOO J1142+1527 at a redshift z = 1.2 based on high angular resolution NIKA2 Sunyaev-Zel’dovich (SZ) and Chandra X-ray data. This multi-wavelength analysis enables us to estimate the shape of the temperature profile with unprecedented precision at this redshift and to obtain a map of the gas entropy distribution averaged along the line of sight. The comparison between the cluster morphological properties observed in the NIKA2 and Chandra maps together with the analysis of the entropy map allows us to conclude that MOOJ1142+1527 is an on-going merger hosting a cool-core at the position of the X-ray peak. This work demonstrates how the addition of spatially-resolved SZ observations to low signal-to-noise X-ray data can bring valuable insights on the intracluster medium thermodynamic properties at z > 1.

Published
2020
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3. Immune checkpoint inhibitors for POLE or POLD1 proofreading-deficient metastatic colorectal cancer

Author

Ambrosini, M., Rousseau, B., Manca, P., Artz, O., Marabelle, A., André, T., Maddalena, G., Mazzoli, G., Intini, R., Cohen, R., Cercek, A., Segal, N.H., Saltz, L., Varghese, A.M., Yaeger, R., Nusrat, M., Goldberg, Z., Ku, G.Y., El Dika, I., Margalit, O., Grinshpun, A., Kasi, P.M., Schilsky, R., Lutfi, A., Shacham-Shmueli, E., Khan Afghan, M., Weiss, L., Westphalen, C.B., Conca, V., Decker, B., Randon, G., Elez, E., Fakih, M., Schrock, A.B., Cremolini, C., Jayachandran, P., Overman, M.J., Lonardi, S., and Pietrantonio, F.

Published
2024
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4. Unveiling the merger dynamics of the most massive MaDCoWS cluster at $z = 1.2$ from a multi-wavelength mapping of its intracluster medium properties

Author

Ruppin, F., McDonald, M., Brodwin, M., Adam, R., Ade, P., André, P., Andrianasolo, A., Arnaud, M., Aussel, H., Bartalucci, I., Bautz, M. W., Beelen, A., Benoît, A., Bideaud, A., Bourrion, O., Calvo, M., Catalano, A., Comis, B., Decker, B., De Petris, M., Désert, F. -X., Doyle, S., Driessen, E. F. C., Eisenhardt, P. R. M., Gomez, A., Gonzalez, A. H., Goupy, J., Kéruzoré, F., Kramer, C., Ladjelate, B., Lagache, G., Leclercq, S., Lestrade, J. -F., Macías-Pérez, J. F., Mauskopf, P., Mayet, F., Monfardini, A., Moravec, E., Perotto, L., Pisano, G., Pointecouteau, E., Ponthieu, N., Pratt, G. W., Revéret, V., Ritacco, A., Romero, C., Roussel, H., Schuster, K., Shu, S., Sievers, A., Stanford, S. A., Stern, D., Tucker, C., and Zylka, R.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The characterization of the Intra-Cluster Medium (ICM) properties of high-redshift galaxy clusters is fundamental to our understanding of large-scale structure formation processes. We present the results of a multi-wavelength analysis of the very massive cluster MOO J1142$+$1527 at a redshift $z = 1.2$ discovered as part of the Massive and Distant Clusters of WISE Survey (MaDCoWS). This analysis is based on high angular resolution $Chandra$ X-ray and NIKA2 Sunyaev-Zel'dovich (SZ) data. Although the X-ray data have only about 1700 counts, we are able to determine the ICM thermodynamic radial profiles, namely temperature, entropy, and hydrostatic mass. These have been obtained with unprecedented precision at this redshift and up to $0.7R_{500}$, thanks to the combination of high-resolution X-ray and SZ data. The comparison between the galaxy distribution mapped in infrared by $Spitzer$ and the morphological properties of the ICM derived from the combined analysis of the $Chandra$ and NIKA2 data leads us to the conclusion that the cluster is an on-going merger. We measure the hydrostatic mass profile of the cluster in four angular sectors centered on the large-scale X-ray centroid. This allows us to estimate a systematic uncertainty on the cluster total mass that characterizes both the impact of the observed deviations from spherical symmetry and of the core dynamics on the mass profile. We further combine the X-ray and SZ data at the pixel level to obtain maps of the temperature and entropy distributions averaged along the line of sight. We find a relatively low entropy core at the position of the X-ray peak and high temperature regions located on its south and west sides. The increase in ICM temperature at the location of the SZ peak is expected given the merger dynamics. (abridged)

Published
2019
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5. The Massive and Distant Clusters of WISE Survey. I. Survey Overview and a Catalog of >2000 Galaxy Clusters at z ≃ 1

Author

Gonzalez, AH, Gettings, DP, Brodwin, M, Eisenhardt, PRM, Stanford, SA, Wylezalek, D, Decker, B, Marrone, DP, Moravec, E, O'Donnell, C, Stalder, B, Stern, D, Abdulla, Z, Brown, G, Carlstrom, J, Chambers, KC, Hayden, B, Lin, YT, Magnier, E, Masci, FJ, Mantz, AB, McDonald, M, Mo, W, Perlmutter, S, Wright, EL, and Zeimann, GR

Subjects
Space Sciences, Physical Sciences, Life Below Water, galaxies: clusters: general, galaxies: distances and redshifts, galaxies: evolution, surveys, astro-ph.CO, astro-ph.GA, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Physical Chemistry (incl. Structural), Astronomy & Astrophysics, Astronomical sciences
Abstract

© 2019. The American Astronomical Society. All rights reserved. We present the Massive and Distant Clusters of WISE Survey (MaDCoWS), a search for galaxy clusters at 0.7 ≲ z ≲ 1.5 based upon data from the Wide-field Infrared Survey Explorer (WISE) mission. MaDCoWS is the first cluster survey capable of discovering massive clusters at these redshifts over the full extragalactic sky. The search is divided into two regions - the region of the extragalactic sky covered by Pan-STARRS (δ > -30°) and the remainder of the southern extragalactic sky at δ < -30° for which shallower optical data from the SuperCOSMOS Sky Survey is available. In this paper, we describe the search algorithm, characterize the sample, and present the first MaDCoWS data release - catalogs of the 2433 highest amplitude detections in the WISE-Pan-STARRS region and the 250 highest amplitude detections in the WISE-SuperCOSMOS region. A total of 1723 of the detections from the WISE-Pan-STARRS sample have also been observed with the Spitzer Space Telescope, providing photometric redshifts and richnesses, and an additional 64 detections within the WISE-SuperCOSMOS region also have photometric redshifts and richnesses. Spectroscopic redshifts for 38 MaDCoWS clusters with IRAC photometry demonstrate that the photometric redshifts have an uncertainty of σ z /(1 + z) ≃ 0.036. Combining the richness measurements with Sunyaev-Zel'dovich observations of MaDCoWS clusters, we also present a preliminary mass-richness relation that can be used to infer the approximate mass distribution of the full sample. The estimated median mass for the WISE-Pan-STARRS catalog is , with the Sunyaev-Zel'dovich data confirming that we detect clusters with masses up to M 500 ∼ 5 ×10 14 M (M 200 ∼ 10 15 M ).

Published
2019

6. The High-Redshift Clusters Occupied by Bent Radio AGN (COBRA) Survey: The \spitzer Catalog

Author

Paterno-Mahler, R., Blanton, E. L., Brodwin, M., Ashby, M. L. N., Golden-Marx, E., Decker, B., Wing, J. D., and Anand, G.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present 190 galaxy cluster candidates (most at high redshift) based on galaxy overdensity measurements in the \spitzer/IRAC imaging of the fields surrounding 646 bent, double-lobed radio sources drawn from the Clusters Occupied by Bent Radio AGN (COBRA) Survey. The COBRA sources were chosen as objects in the VLA FIRST survey that lack optical counterparts in the Sloan Digital Sky Survey (SDSS) to a limit of $m_r=22$, making them likely to lie at high redshift. This is confirmed by our observations: the redshift distribution of COBRA sources with estimated redshifts peaks near $z=1$, and extends out to $z\approx3$. Cluster candidates were identified by comparing our target fields to a background field and searching for statistically significant ($\ge2\sigma$) excesses in the galaxy number counts surrounding the radio sources; 190 fields satisfy the $\ge2\sigma$ limit. We find that 530 fields (82.0\%) have a net positive excess of galaxies surrounding the radio source. Many of the fields with positive excesses but below the $2\sigma$ cutoff are likely to be galaxy groups. Forty-one COBRA sources are quasars with known spectroscopic redshifts, which may be tracers of some of the most distant clusters known., Comment: 18 pages, 8 figures, 3 tables, ApJ accepted

Published
2016
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8. The Massive and Distant Clusters of WISE Survey. III. Sunyaev-Zel'dovich Masses of Galaxy Clusters at $z \sim 1$

Author

Brodwin, M., Greer, C. H., Leitch, E. M., Stanford, S. A., Gonzalez, A. H., Gettings, D. P., Abdulla, Z., Carlstrom, J. E., Decker, B., Eisenhardt, P. R., Lin, H. W., Mantz, A. B., Marrone, D. P., McDonald, M., Stalder, B., Stern, D., and Wylezalek, D.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

We present CARMA 30 GHz Sunyaev-Zel'dovich (SZ) observations of five high-redshift ($z \gtrsim 1$), infrared-selected galaxy clusters discovered as part of the all-sky Massive and Distant Clusters of WISE Survey (MaDCoWS). The SZ decrements measured toward these clusters demonstrate that the MaDCoWS selection is discovering evolved, massive galaxy clusters with hot intracluster gas. Using the SZ scaling relation calibrated with South Pole Telescope clusters at similar masses and redshifts, we find these MaDCoWS clusters have masses in the range $M_{200} \approx 2-6 \times 10^{14}$ $M_\odot$. Three of these are among the most massive clusters found to date at $z\gtrsim 1$, demonstrating that MaDCoWS is sensitive to the most massive clusters to at least $z = 1.3$. The added depth of the AllWISE data release will allow all-sky infrared cluster detection to $z \approx 1.5$ and beyond., Comment: 8 pages, 4 figures, 3 tables; Accepted to ApJ after minor revisions; results unchanged

Published
2014
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10. HPR171 WTP Threshold: A Review of International Approaches and Inspiration for Cultivation of Current Situation in the Czech Republic

Author

Klimes, J., primary, Mlcoch, T., additional, Pasztor, B., additional, Tuzil, J., additional, Bulejova, L., additional, Decker, B., additional, Dostal, F., additional, Kminek, A., additional, Kolek, M., additional, Kostern, M., additional, Kubesova, D., additional, Mazalova, M., additional, Michalek, G., additional, Novotna, K., additional, Spousta, T., additional, Stuchlik, O., additional, Spoustova Tauchmanova, M., additional, Uherek, Š, additional, Volfova, G., additional, Vydrova, J., additional, and Zivansky, M., additional

Published
2023
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15. Dysregulation of the homeobox transcription factor gene HOXB13: role in prostate cancer

Author

Decker B and Ostrander EA

Subjects
Therapeutics. Pharmacology, RM1-950
Abstract

Brennan Decker1,2, Elaine A Ostrander1 1Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA; 2Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK Abstract: Prostate cancer (PC) is the most common noncutaneous cancer in men, and epidemiological studies suggest that about 40% of PC risk is heritable. Linkage analyses in hereditary PC families have identified multiple putative loci. However, until recently, identification of specific risk alleles has proven elusive. Cooney et al used linkage mapping and segregation analysis to identify a putative risk locus on chromosome 17q21-22. In search of causative variant(s) in genes from the candidate region, a novel, potentially deleterious G84E substitution in homeobox transcription factor gene HOXB13 was observed in multiple hereditary PC families. In follow-up testing, the G84E allele was enriched in cases, especially those with an early diagnosis or positive family history of disease. This finding was replicated by others, confirming HOXB13 as a PC risk gene. The HOXB13 protein plays diverse biological roles in embryonic development and terminally differentiated tissue. In tumor cell lines, HOXB13 participates in a number of biological functions, including coactivation and localization of the androgen receptor and FOXA1. However, no consensus role has emerged and many questions remain. All HOXB13 variants with a proposed role in PC risk are predicted to damage the protein and lie in domains that are highly conserved across species. The G84E variant has the strongest epidemiological support and lies in a highly conserved MEIS protein-binding domain, which binds cofactors required for activation. On the basis of epidemiological and biological data, the G84E variant likely modulates the interaction between the HOXB13 protein and the androgen receptor, as well as affecting FOXA1-mediated transcriptional programming. However, further studies of the mutated protein are required to clarify the mechanisms by which this translates into PC risk. Keywords: prostate cancer risk, HOXB13

Published
2014

20. Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women

Author

Dorling, L., Carvalho, S., Allen, J., Gonzalez-Neira, A., Luccarini, C., Wahlstrom, C., Pooley, K.A., Parsons, M.T., Fortuno, C., Wang, Q., Bolla, M.K., Dennis, J., Keeman, R., Alonso, M.R., Alvarez, N., Herraez, B., Fernandez, V., Nunez-Torres, R., Osorio, A., Valcich, J., Li, M., Torngren, T., Harrington, P.A., Baynes, C., Conroy, D.M., Decker, B., Fachal, L., Mavaddat, N., Ahearn, T., Aittomaki, K., Antonenkova, N.N., Arnold, N., Arveux, P., Ausems, M.G.E.M., Auvinen, P., Becher, H., Beckmann, M.W., Behrens, S., Bermisheva, M., Bialkowska, K., Blomqvist, C., Bogdanova, N.V., Bogdanova-Markov, N., Bojesen, S.E., Bonanni, B., Borresen-Dale, A.L., Brauch, H., Bremer, M., Briceno, I., Bruning, T., Burwinkel, B., Cameron, D.A., Camp, N.J., Campbell, A., Carracedo, A., Castelao, J.E., Cessna, M.H., Chanock, S.J., Christiansen, H., Collee, J.M., Cordina-Duverger, E., Cornelissen, S., Czene, K., Dork, T., Ekici, A.B., Engel, C., Eriksson, M., Fasching, P.A., Figueroa, J., Flyger, H., Forsti, A., Gabrielson, M., Gago-Dominguez, M., Georgoulias, V., Gil, F., Giles, G.G., Glendon, G., Garcia, E.B.G., Alnaes, G.I.G., Guenel, P., Hadjisavvas, A., Haeberle, L., Hahnen, E., Hall, P., Hamann, U., Harkness, E.F., Hartikainen, J.M., Hartman, M., He, W., Heemskerk-Gerritsen, B.A.M., Hillemanns, P., Hogervorst, F.B.L., Hollestelle, A., Ho, W.K., Hooning, M.J., Howell, A., Humphreys, K., Idris, F., Jakubowska, A., Jung, A., Kapoor, P.M., Kerin, M.J., Khusnutdinova, E., Kim, S.W., Ko, Y.D., Kosma, V.M., Kristensen, V.N., Kyriacou, K., Lakeman, I.M.M., Lee, J.W., Lee, M.H., Li, J.M., Lindblom, A., W.Y. lo, Loizidou, M.A., Lophatananon, A., Lubinski, J., MacInnis, R.J., Madsen, M.J., Mannermaa, A., Manoochehri, M., Manoukian, S., Margolin, S., Martinez, M.E., Maurer, T., Mavroudis, D., McLean, C., Meindl, A., Mensenkamp, A.R., Michailidou, K., Miller, N., Taib, N.A.M., Muir, K., Mulligan, A.M., Nevanlinna, H., Newman, W.G., Nordestgaard, B.G., Ng, P.S., Oosterwijk, J.C., Park, S.K., Park-Simon, T.W., Perez, J.I.A., Peterlongo, P., Porteous, D.J., Prajzendanc, K., Prokofyeva, D., Radice, P., Rashid, M.U., Rhenius, V., Rookus, M.A., Rudiger, T., Saloustros, E., Sawyer, E.J., Schmutzler, R.K., Schneeweiss, A., Schurmann, P., Shah, M., Sohn, C., Southey, M.C., Surowy, H., Suvanto, M., Thanasitthichai, S., Tomlinson, I., Torres, D., Truong, T., Tzardi, M., Valova, Y., Asperen, C.J. van, Dam, R.M. van, Ouweland, A.M.W. van den, Kolk, L.E. van der, Veen, E.M. van, Wendt, C., Williams, J.A., Yang, X.H.R., Yoon, S.Y., Zamora, M.P., Evans, D.G., Hoya, M. de la, Simard, J., Antoniou, A.C., Borg, A., Andrulis, I.L., Chang-Claude, J., Garcia-Closas, M., Chenevix-Trench, G., Milne, R.L., Pharoah, P.D.P., Schmidt, M.K., Spurdle, A.B., Vreeswijk, M.P.G., Benitez, J., Dunning, A.M., Kvist, A., Teo, S.H., Devilee, P., Easton, D.F., Breast Canc Assoc Consortium, Erasmus MC other, Medical Oncology, Clinical Genetics, Keeman, Renske [0000-0002-5452-9933], Decker, Brennan [0000-0003-4516-7421], Eriksson, Mikael [0000-0001-8135-4270], Martinez, Maria Elena [0000-0002-6728-1834], Surowy, Harald [0000-0002-3595-9188], Pharoah, Paul DP [0000-0001-8494-732X], Apollo - University of Cambridge Repository, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Targeted Gynaecologic Oncology (TARGON), RS: GROW - R4 - Reproductive and Perinatal Medicine, MUMC+: DA KG Polikliniek (9), and Klinische Genetica

Subjects
Adult, Risk, Oncology, medicine.medical_specialty, Adolescent, PALB2, Genetic counseling, Genes, BRCA2, Mutation, Missense, Genes, BRCA1, Estrogen receptor, Breast Neoplasms, 030204 cardiovascular system & hematology, OVARIAN-CANCER, Article, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, SDG 3 - Good Health and Well-being, Internal medicine, Odds Ratio, medicine, Humans, Genetic Predisposition to Disease, 030212 general & internal medicine, skin and connective tissue diseases, CHEK2, Aged, Genetic testing, Genetic association, Aged, 80 and over, Women's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17], medicine.diagnostic_test, MUTATIONS, business.industry, Age Factors, Genetic Variation, Sequence Analysis, DNA, General Medicine, Odds ratio, Middle Aged, BRCA1, medicine.disease, 3. Good health, Logistic Models, Female, business
Abstract

BACKGROUNDGenetic testing for breast cancer susceptibility is widely used, but for many genes,evidence of an association with breast cancer is weak, underlying risk estimatesare imprecise, and reliable subtype-specific risk estimates are lacking.METHODSWe used a panel of 34 putative susceptibility genes to perform sequencing onsamples from 60,466 women with breast cancer and 53,461 controls. In separateanalyses for protein-truncating variants and rare missense variants in these genes,we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluatedmissense-variant associations according to domain and classification of pathogenicity.RESULTSProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2)were associated with a risk of breast cancer overall with a P value of less than0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D,and TP53) were associated with a risk of breast cancer overall with a P value ofless than 0.05 and a Bayesian false-discovery probability of less than 0.05. Forprotein-truncating variants in 19 of the remaining 25 genes, the upper limit ofthe 95% confidence interval of the odds ratio for breast cancer overall was lessthan 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios werehigher for estrogen receptor (ER)–positive disease than for ER-negative disease;for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, andRAD51D, odds ratios were higher for ER-negative disease than for ER-positivedisease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 wereassociated with a risk of breast cancer overall with a P value of less than 0.001.For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a riskof breast cancer overall, with the risk being similar to that of protein-truncatingvariants.CONCLUSIONSThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimatesof the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.)

Published
2021
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24. Expanding the use of targeted therapy for Urothelial Bladder Cancer (UBC): Non-FGFR3 Receptor Tyrosine Kinase (RTK) Gene Rearrangements (ReAr) and Fusions (Fus)

Author

Necchi, A., primary, Pavlick, D., additional, Bratslavsky, G., additional, Jacob, J., additional, Kravtsov, O., additional, Spiess, P., additional, Grivas, P., additional, Parini, V., additional, Decker, B., additional, Lin, D., additional, Danziger, N., additional, Levy, M., additional, and Ross, J., additional

Published
2022
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26. Scrimmage! Teaching quantitative literacy through a multidimensional simulation

Author

Melissa L. Intindola, Decker B. Hains, Douglas A. Lepisto, and Bret J. Wagner

Subjects
Strategy and Management, media_common.quotation_subject, 05 social sciences, 050301 education, Literacy, Education, 0502 economics and business, ComputingMilieux_COMPUTERSANDEDUCATION, Mathematics education, Psychology, 0503 education, Value (mathematics), 050203 business & management, media_common, Accreditation
Abstract

Researchers and employers both herald the importance of quantitative literacy among undergraduates in business schools. Despite this, the ability to effectively train students in quantitative literacy is difficult due to its multi-disciplinary nature, everchanging accreditation recommendations, and administrative restrictions faced by today's business schools. In this paper, we explore the use of the ScrimmageSIMTM simulation in a Midwestern U.S. business school across two semesters one year apart. We demonstrate qualitatively via student comments and quantitatively via course evaluations the value of this simulation in increasing the quantitative literacy of undergraduate business students.

Published
2019
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29. 694P Methylthioadenosine phosphorylase (MTAP) deletion is more common in sarcomatoid (srcRCC) than in clear cell renal cell carcinoma (ccRCC)

Author

Necchi, A., primary, Grivas, P., additional, Spiess, P.E., additional, Jacob, J., additional, Sokol, E., additional, Ramkissoon, S., additional, Severson, E., additional, Huang, R.S.P., additional, Lin, D.I., additional, Mata, D.A., additional, Decker, B., additional, Mcgregor, K., additional, Danziger, N.A., additional, Ross, J.S., additional, and Bratslavsky, G., additional

Published
2021
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31. 598P A phase Ib study of enzalutamide (Enza) plus CC-115 in men with metastatic castration-resistant prostate cancer (mCRPC)

Author

Zhao, J.L., primary, Antonarakis, E.S., additional, Cheng, H., additional, George, D.J., additional, Aggarwal, R.R., additional, Abida, W., additional, Decker, B., additional, Smart-Curley, T., additional, Schonhoft, J., additional, Anderson, A., additional, Haywood, S., additional, Riedel, E., additional, Carver, B., additional, Wyatt, A., additional, Feng, F., additional, Knudsen, K., additional, and Rathkopf, D.E., additional

Published
2021
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35. Methylthioadenosine Phosphorylase (MTAP) deletion is more common in Sarcomatoid (srcRCC) than in clear cell Renal Cell Carcinoma (ccRCC)

Author

Necchi, A., primary, Grivas, P., additional, Spiess, P., additional, Jacob, J., additional, Schrock, A., additional, Madison, R., additional, Pavlick, D., additional, Sokol, E., additional, Danziger, N., additional, Ramkissoon, S., additional, Severson, E., additional, Huang, R., additional, Lin, D., additional, Mata, D., additional, Decker, B., additional, Gjoerup, O., additional, Mcgregor, K., additional, Venstrom, J., additional, Alexander, B., additional, Ross, J., additional, and Bratslavsky, G., additional

Published
2021
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38. Breast cancer risk genes - Association analysis in more than 113,000 women.

Author

Cornelissen S., Michailidou K., Miller N., Taib N.A.M., Muir K., Mulligan A.M., Nevanlinna H., Newman W.G., Nordestgaard B.G., Ng P.-S., Oosterwijk J.C., Park S.K., Park-Simon T.-W., Perez J.I.A., Peterlongo P., Porteous D.J., Prajzendanc K., Prokofyeva D., Radice P., Rashid M.U., Rhenius V., Rookus M.A., Rudiger T., Saloustros E., Sawyer E.J., Schmutzler R.K., Schneeweiss A., Schurmann P., Shah M., Sohn C., Southey M.C., Surowy H., Suvanto M., Thanasitthichai S., Tomlinson I., Torres D., Truong T., Tzardi M., Valova Y., van Asperen C.J., van Dam R.M., van den Ouweland A.M.W., van der Kolk L.E., van Veen E.M., Wendt C., Williams J.A., Yang X.R., Yoon S.-Y., Zamora M.P., Evans D.G., de la Hoya M., Simard J., Antoniou A.C., Borg A., Andrulis I.L., Chang-Claude J., Garcia-Closas M., Chenevix-Trench G., Milne R.L., Pharoah P.D.P., Schmidt M.K., Spurdle A.B., Vreeswijk M.P.G., Benitez J., Dunning A.M., Kvist A., Teo S.H., Devilee P., Easton D.F., Dorling L., Carvalho S., Allen J., Gonzalez-Neira A., Luccarini C., Wahlstrom C., Pooley K.A., Parsons M.T., Fortuno C., Wang Q., Bolla M.K., Dennis J., Keeman R., Alonso M.R., Alvarez N., Herraez B., Fernandez V., Nunez-Torres R., Osorio A., Valcich J., Li M., Torngren T., Harrington P.A., Baynes C., Conroy D.M., Decker B., Fachal L., Mavaddat N., Ahearn T., Aittomaki K., Antonenkova N.N., Arnold N., Arveux P., Ausems M.G.E.M., Auvinen P., Becher H., Beckmann M.W., Behrens S., Bermisheva M., Bialkowska K., Blomqvist C., Bogdanova N.V., Bogdanova-Markov N., Bojesen S.E., Bonanni B., Borresen-Dale A.-L., Brauch H., Bremer M., Briceno I., Bruning T., Burwinkel B., Cameron D.A., Camp N.J., Campbell A., Carracedo A., Castelao J.E., Cessna M.H., Chanock S.J., Christiansen H., Collee J.M., Cordina-Duverger E., Czene K., Dork T., Ekici A.B., Engel C., Eriksson M., Fasching P.A., Figueroa J., Flyger H., Forsti A., Gabrielson M., Gago-Dominguez M., Georgoulias V., Gil F., Giles G.G., Glendon G., Gomez Garcia E.B., Grenaker Alnaes G.I., Guenel P., Hadjisavvas A., Haeberle L., Hahnen E., Hall P., Hamann U., Harkness E.F., Hartikainen J.M., Hartman M., He W., Heemskerk-Gerritsen B.A.M., Hillemanns P., Hogervorst F.B.L., Hollestelle A., Ho W.K., Hooning M.J., Howell A., Humphreys K., Idris F., Jakubowska A., Jung A., Kapoor P.M., Kerin M.J., Khusnutdinova E., Kim S.-W., Ko Y.-D., Kosma V.-M., Kristensen V.N., Kyriacou K., Lakeman I.M.M., Lee J.W., Lee M.H., Li J., Lindblom A., Lo W.-Y., Loizidou M.A., Lophatananon A., Lubinski J., MacInnis R.J., Madsen M.J., Mannermaa A., Manoochehri M., Manoukian S., Margolin S., Martinez M.E., Maurer T., Mavroudis D., McLean C., Meindl A., Mensenkamp A.R., Cornelissen S., Michailidou K., Miller N., Taib N.A.M., Muir K., Mulligan A.M., Nevanlinna H., Newman W.G., Nordestgaard B.G., Ng P.-S., Oosterwijk J.C., Park S.K., Park-Simon T.-W., Perez J.I.A., Peterlongo P., Porteous D.J., Prajzendanc K., Prokofyeva D., Radice P., Rashid M.U., Rhenius V., Rookus M.A., Rudiger T., Saloustros E., Sawyer E.J., Schmutzler R.K., Schneeweiss A., Schurmann P., Shah M., Sohn C., Southey M.C., Surowy H., Suvanto M., Thanasitthichai S., Tomlinson I., Torres D., Truong T., Tzardi M., Valova Y., van Asperen C.J., van Dam R.M., van den Ouweland A.M.W., van der Kolk L.E., van Veen E.M., Wendt C., Williams J.A., Yang X.R., Yoon S.-Y., Zamora M.P., Evans D.G., de la Hoya M., Simard J., Antoniou A.C., Borg A., Andrulis I.L., Chang-Claude J., Garcia-Closas M., Chenevix-Trench G., Milne R.L., Pharoah P.D.P., Schmidt M.K., Spurdle A.B., Vreeswijk M.P.G., Benitez J., Dunning A.M., Kvist A., Teo S.H., Devilee P., Easton D.F., Dorling L., Carvalho S., Allen J., Gonzalez-Neira A., Luccarini C., Wahlstrom C., Pooley K.A., Parsons M.T., Fortuno C., Wang Q., Bolla M.K., Dennis J., Keeman R., Alonso M.R., Alvarez N., Herraez B., Fernandez V., Nunez-Torres R., Osorio A., Valcich J., Li M., Torngren T., Harrington P.A., Baynes C., Conroy D.M., Decker B., Fachal L., Mavaddat N., Ahearn T., Aittomaki K., Antonenkova N.N., Arnold N., Arveux P., Ausems M.G.E.M., Auvinen P., Becher H., Beckmann M.W., Behrens S., Bermisheva M., Bialkowska K., Blomqvist C., Bogdanova N.V., Bogdanova-Markov N., Bojesen S.E., Bonanni B., Borresen-Dale A.-L., Brauch H., Bremer M., Briceno I., Bruning T., Burwinkel B., Cameron D.A., Camp N.J., Campbell A., Carracedo A., Castelao J.E., Cessna M.H., Chanock S.J., Christiansen H., Collee J.M., Cordina-Duverger E., Czene K., Dork T., Ekici A.B., Engel C., Eriksson M., Fasching P.A., Figueroa J., Flyger H., Forsti A., Gabrielson M., Gago-Dominguez M., Georgoulias V., Gil F., Giles G.G., Glendon G., Gomez Garcia E.B., Grenaker Alnaes G.I., Guenel P., Hadjisavvas A., Haeberle L., Hahnen E., Hall P., Hamann U., Harkness E.F., Hartikainen J.M., Hartman M., He W., Heemskerk-Gerritsen B.A.M., Hillemanns P., Hogervorst F.B.L., Hollestelle A., Ho W.K., Hooning M.J., Howell A., Humphreys K., Idris F., Jakubowska A., Jung A., Kapoor P.M., Kerin M.J., Khusnutdinova E., Kim S.-W., Ko Y.-D., Kosma V.-M., Kristensen V.N., Kyriacou K., Lakeman I.M.M., Lee J.W., Lee M.H., Li J., Lindblom A., Lo W.-Y., Loizidou M.A., Lophatananon A., Lubinski J., MacInnis R.J., Madsen M.J., Mannermaa A., Manoochehri M., Manoukian S., Margolin S., Martinez M.E., Maurer T., Mavroudis D., McLean C., Meindl A., and Mensenkamp A.R.

Abstract

BACKGROUND Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODS We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTS Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONS The results of this study define

Published
2021

39. Mapping the intracluster medium temperature in the era of NIKA2 and MUSTANG-2

Author

Ruppin, F., Adam, R., Ade, P., Ajeddig, H., André, P., Artis, E., Aussel, H., Beelen, A., Benoît, A., Berta, S., Bing, L., Bourrion, O., Brodwin, M., Calvo, M., Catalano, A., Decker, B., De Petris, M., Désert, F. -X., Doyle, S., Driessen, E. F. C., Eisenhardt, P. R. M., Gomez, A., Gonzalez, A. H., Goupy, J., Kéruzoré, F., Kramer, C., Ladjelate, B., Lagache, G., Leclercq, S., Lestrade, J. -F., Macías-Pérez, J. -F., Maury, A., Mauskopf, P., Mayet, F., McDonald, M., Monfardini, A., Moravec, E., Muñoz-Echeverría, M., Perotto, L., Pisano, G., Ponthieu, N., Revéret, V., Rigby, A. J., Ritacco, A., Romero, C., Roussel, H., Schuster, K., Shu, S., Sievers, A., Stanford, S. A., Stern, D., Tucker, C., Zylka, R., Ruppin, F., Adam, R., Ade, P., Ajeddig, H., André, P., Artis, E., Aussel, H., Beelen, A., Benoît, A., Berta, S., Bing, L., Bourrion, O., Brodwin, M., Calvo, M., Catalano, A., Decker, B., De Petris, M., Désert, F. -X., Doyle, S., Driessen, E. F. C., Eisenhardt, P. R. M., Gomez, A., Gonzalez, A. H., Goupy, J., Kéruzoré, F., Kramer, C., Ladjelate, B., Lagache, G., Leclercq, S., Lestrade, J. -F., Macías-Pérez, J. -F., Maury, A., Mauskopf, P., Mayet, F., McDonald, M., Monfardini, A., Moravec, E., Muñoz-Echeverría, M., Perotto, L., Pisano, G., Ponthieu, N., Revéret, V., Rigby, A. J., Ritacco, A., Romero, C., Roussel, H., Schuster, K., Shu, S., Sievers, A., Stanford, S. A., Stern, D., Tucker, C., and Zylka, R.

Abstract

We present preliminary results from an on-going program that aims at mapping the intracluster medium (ICM) temperature of high redshift galaxy clusters from the MaDCoWS sample using a joint analysis of shallow X-ray data obtained by $Chandra$ and high angular resolution Sunyaev-Zel'dovich (SZ) observations realized with the NIKA2 and MUSTANG-2 cameras. We also present preliminary results from an on-going Open Time program within the NIKA2 collaboration that aims at mapping the ICM temperature of a galaxy cluster at $z=0.45$ from the resolved detection of the relativistic corrections to the SZ spectrum. These studies demonstrate how high angular resolution SZ observations will play a major role in the coming decade to push the investigation of ICM dynamics and non-gravitational processes to high redshift before the next generation X-ray observatories come into play., Comment: To appear in the Proceedings of the International Conference entitled "mm Universe @ NIKA2", Rome (Italy), June 2021, EPJ Web of conferences

Published
2021
Full Text
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43. Unveiling the Merger Dynamics of the Most Massive MaDCoWS Cluster at z = 1.2 from a Multiwavelength Mapping of Its Intracluster Medium Properties

Author

Ruppin, F., primary, McDonald, M., additional, Brodwin, M., additional, Adam, R., additional, Ade, P., additional, André, P., additional, Andrianasolo, A., additional, Arnaud, M., additional, Aussel, H., additional, Bartalucci, I., additional, Bautz, M. W., additional, Beelen, A., additional, Benoît, A., additional, Bideaud, A., additional, Bourrion, O., additional, Calvo, M., additional, Catalano, A., additional, Comis, B., additional, Decker, B., additional, Petris, M. De, additional, Désert, F.-X., additional, Doyle, S., additional, Driessen, E. F. C., additional, Eisenhardt, P. R. M., additional, Gomez, A., additional, Gonzalez, A. H., additional, Goupy, J., additional, Kéruzoré, F., additional, Kramer, C., additional, Ladjelate, B., additional, Lagache, G., additional, Leclercq, S., additional, Lestrade, J.-F., additional, Macías-Pérez, J. F., additional, Mauskopf, P., additional, Mayet, F., additional, Monfardini, A., additional, Moravec, E., additional, Perotto, L., additional, Pisano, G., additional, Pointecouteau, E., additional, Ponthieu, N., additional, Pratt, G. W., additional, Revéret, V., additional, Ritacco, A., additional, Romero, C., additional, Roussel, H., additional, Schuster, K., additional, Shu, S., additional, Sievers, A., additional, Stanford, S. A., additional, Stern, D., additional, Tucker, C., additional, and Zylka, R., additional

Published
2020
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46. Performance of 170 grid connected PV plants in northern Germany - analysis of yields and optimization potentials

Author

Decker, B. and Jahn, U.

Subjects
Lower Saxony, Germany -- Energy use, Solar heating -- Analysis, Solar collectors -- Analysis, Earth sciences, Petroleum, energy and mining industries
Abstract

Within the German 1000 roof PV programme, about 2000 grid connected PV plants (1-5 [kW.sub.p]) with a total peak power of 5 [MW.sub.p] were installed on the roofs of single and two family houses. In the Federal State of Lower Saxony, ISFH has been responsible for the technical inspections and the global monitoring of 172 PV plants up until now. The annual final yields range between 430 kWh/([[kW.sub.p].sup.*]a) and 875 kWh/([[kW.sub.p].sup.*]a) with a mean value of 680 kWh/([[kW.sub.p].sup.*]a). Using the annual in-plane irradiation, we determine annual performance ratios in the range 47.5%-81% (mean 66.5%). A procedure to receive standardized performance ratios is introduced using actual peak powers of the PV modules and inverter-specific efficiencies. Typical curves of monthly values of the performance ratio are recorded. PV plants with low final yields are analyzed with respect to operational failures, partly shadowing effects, and poorness in maximum power point adaptation of some inverters. Optimization potentials are also discussed.

Published
1997

47. Cancer risks associated with germline PALB2 pathogenic variants: An international study of 524 families.

Author

Hake C., Redman J., Kleibl Z., Kleiblova P., Konstantopoulou I., Kvist A., Laduca H., Lee A.S.G., Lesueur F., Maher E.R., Mannermaa A., Manoukian S., McFarland R., McKinnon W., Meindl A., Metcalfe K., Taib N.A.M., Moilanen J., Nathanson K.L., Neuhausen S., Ng P.S., Nguyen-Dumont T., Nielsen S.M., Obermair F., Offit K., Olopade O.I., Ottini L., Penkert J., Pylkas K., Radice P., Ramus S.J., Rudaitis V., Side L., Silva-Smith R., Silvestri V., Skytte A.-B., Slavin T., Soukupova J., Tondini C., Trainer A.H., Unzeitig G., Usha L., Van Overeem Hansen T., Whitworth J., Wood M., Yip C.H., Yoon S.-Y., Yussuf A., Zogopoulos G., Goldgar D., Hopper J.L., Chenevix-Trench G., Pharoah P., George S.H.L., Balmana J., Houdayer C., James P., El-Haffaf Z., Ehrencrona H., Janatova M., Peterlongo P., Nevanlinna H., Schmutzler R., Teo S.-H., Robson M., Pal T., Couch F., Weitzel J.N., Elliott A., Southey M., Winqvist R., Easton D.F., Foulkes W.D., Antoniou A.C., Tischkowitz M., Yang X., Leslie G., Doroszuk A., Schneider S., Allen J., Decker B., Dunning A.M., Scarth J., Plaskocinska I., Luccarini C., Shah M., Pooley K., Dorling L., Leei A., Adank M.A., Adlard J., Aittomaki K., Andrulis I.L., Ang P., Barwell J., Bernstein J.L., Bobolis K., Borg A., Blomqvist C., Claes K.B.M., Concannon P., Cuggia A., Culver J.O., Damiola F., De Pauw A., Diez O., Dolinsky J.S., Domchek S.M., Engel C., Evans D.G., Fostira F., Garber J., Golmard L., Goode E.L., Gruber S.B., Hahnen E., Heikkinen T., Hurley J.E., Janavicius R., Hake C., Redman J., Kleibl Z., Kleiblova P., Konstantopoulou I., Kvist A., Laduca H., Lee A.S.G., Lesueur F., Maher E.R., Mannermaa A., Manoukian S., McFarland R., McKinnon W., Meindl A., Metcalfe K., Taib N.A.M., Moilanen J., Nathanson K.L., Neuhausen S., Ng P.S., Nguyen-Dumont T., Nielsen S.M., Obermair F., Offit K., Olopade O.I., Ottini L., Penkert J., Pylkas K., Radice P., Ramus S.J., Rudaitis V., Side L., Silva-Smith R., Silvestri V., Skytte A.-B., Slavin T., Soukupova J., Tondini C., Trainer A.H., Unzeitig G., Usha L., Van Overeem Hansen T., Whitworth J., Wood M., Yip C.H., Yoon S.-Y., Yussuf A., Zogopoulos G., Goldgar D., Hopper J.L., Chenevix-Trench G., Pharoah P., George S.H.L., Balmana J., Houdayer C., James P., El-Haffaf Z., Ehrencrona H., Janatova M., Peterlongo P., Nevanlinna H., Schmutzler R., Teo S.-H., Robson M., Pal T., Couch F., Weitzel J.N., Elliott A., Southey M., Winqvist R., Easton D.F., Foulkes W.D., Antoniou A.C., Tischkowitz M., Yang X., Leslie G., Doroszuk A., Schneider S., Allen J., Decker B., Dunning A.M., Scarth J., Plaskocinska I., Luccarini C., Shah M., Pooley K., Dorling L., Leei A., Adank M.A., Adlard J., Aittomaki K., Andrulis I.L., Ang P., Barwell J., Bernstein J.L., Bobolis K., Borg A., Blomqvist C., Claes K.B.M., Concannon P., Cuggia A., Culver J.O., Damiola F., De Pauw A., Diez O., Dolinsky J.S., Domchek S.M., Engel C., Evans D.G., Fostira F., Garber J., Golmard L., Goode E.L., Gruber S.B., Hahnen E., Heikkinen T., Hurley J.E., and Janavicius R.

Abstract

PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 x 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 x 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 x 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 3 1022). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 x 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer ri

Published
2020

48. Cancer Risks Associated With Germline PALB2 Pathogenic Variants: An International Study of 524 Families

Author

Yang, X, Leslie, G, Doroszuk, A, Schneider, S, Allen, J, Decker, B, Dunning, AM, Redman, J, Scarth, J, Plaskocinska, I, Luccarini, C, Shah, M, Pooley, K, Dorling, L, Lee, A, Adank, MA, Adlard, J, Aittomaki, K, Andrulis, IL, Ang, P, Barwell, J, Bernstein, JL, Bobolis, K, Borg, A, Blomqvist, C, Claes, KBM, Concannon, P, Cuggia, A, Culver, JO, Damiola, F, de Pauw, A, Diez, O, Dolinsky, JS, Domchek, SM, Engel, C, Evans, DG, Fostira, F, Garber, J, Golmard, L, Goode, EL, Gruber, SB, Hahnen, E, Hake, C, Heikkinen, T, Hurley, JE, Janavicius, R, Kleibl, Z, Kleiblova, P, Konstantopoulou, I, Kvist, A, Laduca, H, Lee, ASG, Lesueur, F, Maher, ER, Mannermaa, A, Manoukian, S, McFarland, R, McKinnon, W, Meindl, A, Metcalfe, K, Taib, NAM, Moilanen, J, Nathanson, KL, Neuhausen, S, Ng, PS, Nguyen-Dumont, T, Nielsen, SM, Obermair, F, Offit, K, Olopade, O, Ottini, L, Penkert, J, Pylkas, K, Radice, P, Ramus, SJ, Rudaitis, V, Side, L, Silva-Smith, R, Silvestri, V, Skytte, A-B, Slavin, T, Soukupova, J, Tondini, C, Trainer, AH, Unzeitig, G, Usha, L, Hansen, TVO, Whitworth, J, Wood, M, Yip, CH, Yoon, S-Y, Yussuf, A, Zogopoulos, G, Goldgar, D, Hopper, JL, Chenevix-Trench, G, Pharoah, P, George, SHL, Balmana, J, Houdayer, C, James, P, El-Haffaf, Z, Ehrencrona, H, Janatova, M, Peterlongo, P, Nevanlinna, H, Schmutzler, R, Teo, S-H, Robson, M, Pal, T, Couch, F, Weitzel, JN, Elliott, A, Southey, M, Winqvist, R, Easton, DF, Foulkes, WD, Antoniou, AC, Tischkowitz, M, Yang, X, Leslie, G, Doroszuk, A, Schneider, S, Allen, J, Decker, B, Dunning, AM, Redman, J, Scarth, J, Plaskocinska, I, Luccarini, C, Shah, M, Pooley, K, Dorling, L, Lee, A, Adank, MA, Adlard, J, Aittomaki, K, Andrulis, IL, Ang, P, Barwell, J, Bernstein, JL, Bobolis, K, Borg, A, Blomqvist, C, Claes, KBM, Concannon, P, Cuggia, A, Culver, JO, Damiola, F, de Pauw, A, Diez, O, Dolinsky, JS, Domchek, SM, Engel, C, Evans, DG, Fostira, F, Garber, J, Golmard, L, Goode, EL, Gruber, SB, Hahnen, E, Hake, C, Heikkinen, T, Hurley, JE, Janavicius, R, Kleibl, Z, Kleiblova, P, Konstantopoulou, I, Kvist, A, Laduca, H, Lee, ASG, Lesueur, F, Maher, ER, Mannermaa, A, Manoukian, S, McFarland, R, McKinnon, W, Meindl, A, Metcalfe, K, Taib, NAM, Moilanen, J, Nathanson, KL, Neuhausen, S, Ng, PS, Nguyen-Dumont, T, Nielsen, SM, Obermair, F, Offit, K, Olopade, O, Ottini, L, Penkert, J, Pylkas, K, Radice, P, Ramus, SJ, Rudaitis, V, Side, L, Silva-Smith, R, Silvestri, V, Skytte, A-B, Slavin, T, Soukupova, J, Tondini, C, Trainer, AH, Unzeitig, G, Usha, L, Hansen, TVO, Whitworth, J, Wood, M, Yip, CH, Yoon, S-Y, Yussuf, A, Zogopoulos, G, Goldgar, D, Hopper, JL, Chenevix-Trench, G, Pharoah, P, George, SHL, Balmana, J, Houdayer, C, James, P, El-Haffaf, Z, Ehrencrona, H, Janatova, M, Peterlongo, P, Nevanlinna, H, Schmutzler, R, Teo, S-H, Robson, M, Pal, T, Couch, F, Weitzel, JN, Elliott, A, Southey, M, Winqvist, R, Easton, DF, Foulkes, WD, Antoniou, AC, and Tischkowitz, M

Abstract

PURPOSE: To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS: We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS: We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 × 10-2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 × 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION: These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cance

Published
2020

49. Unveiling the merger dynamics of the most massive madcows cluster at z = 1.2 from a multiwavelength mapping of its intracluster medium properties

Author

Ruppin, F., McDonald, M., Brodwin, Mark, Adam, R., Ade, P., André, P., Andrianasolo, A., Arnaud, Monique, Aussel, H., Bartalucci, I., Bautz, M.W., Beelen, A., Benoît, A, Bideaud, A., Bourrion, O., Calvo, M., Catalano, Assunta, Comis, B., Decker, B., Petris, M.D., Désert, F.X., Doyle, S., Driessen, E.F.C., Eisenhardt, P.R.M., Gomez, A, Gonzalez, Anthony H., Kéruzoré, F., Kramer, C., Ladjelate, B., Lagache, Guilaine, Leclercq, S., Lestrade, J.F., Macías-Pérez, J. F., Mauskopf, P., Mayet, F., Monfardini, A, Moravec, David, Perotto, L., Pisano, G., Pointecouteau, E., Ponthieu, N., Pratt, G.W., Revéret, V., Ritacco, A., Romero, C., Roussel, H., Schuster, K., Shu, S., Sievers, A., Stanford, S.A., Stern, D., Tucker, C., Zylka, R., Ruppin, F., McDonald, M., Brodwin, Mark, Adam, R., Ade, P., André, P., Andrianasolo, A., Arnaud, Monique, Aussel, H., Bartalucci, I., Bautz, M.W., Beelen, A., Benoît, A, Bideaud, A., Bourrion, O., Calvo, M., Catalano, Assunta, Comis, B., Decker, B., Petris, M.D., Désert, F.X., Doyle, S., Driessen, E.F.C., Eisenhardt, P.R.M., Gomez, A, Gonzalez, Anthony H., Kéruzoré, F., Kramer, C., Ladjelate, B., Lagache, Guilaine, Leclercq, S., Lestrade, J.F., Macías-Pérez, J. F., Mauskopf, P., Mayet, F., Monfardini, A, Moravec, David, Perotto, L., Pisano, G., Pointecouteau, E., Ponthieu, N., Pratt, G.W., Revéret, V., Ritacco, A., Romero, C., Roussel, H., Schuster, K., Shu, S., Sievers, A., Stanford, S.A., Stern, D., Tucker, C., and Zylka, R.

Abstract

The characterization of the Intracluster Medium (ICM) properties of high-redshift galaxy clusters is fundamental to our understanding of large-scale structure formation processes. We present the results of a multiwavelength analysis of the very massive cluster MOO J1142+1527 at a redshift z = 1.2 discovered as part of the Massive and Distant Clusters of WISE Survey. This analysis is based on high angular resolution Chandra X-ray and NIKA2 Sunyaev-Zel'dovich (SZ) data. The cluster thermodynamic radial profiles have been obtained with unprecedented precision at this redshift and up to 0.7R , thanks to the combination of high-resolution X-ray and SZ data. The comparison between the galaxy distribution mapped in infrared by Spitzer and the morphological properties of the ICM derived from the combined analysis of the Chandra and NIKA2 data leads us to the conclusion that the cluster is an ongoing merger. We have estimated a systematic uncertainty on the cluster total mass that characterizes both the impact of the observed deviations from spherical symmetry and of the core dynamics on the mass profile. We further combine the X-ray and SZ data at the pixel level to obtain maps of the temperature and entropy distributions. We find a relatively low-entropy core at the position of the X-ray peak and high-temperature regions located on its south and west sides. This work demonstrates that the addition of spatially resolved SZ observations to low signal-to-noise X-ray data brings a high information gain on the characterization of the evolution of ICM thermodynamic properties at z > 1.

Published
2020

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