Flavor Physics in an SO(10) Grand Unified Model

In supersymmetric grand-unified models, the lepton mixing matrix can possibly affect flavor-changing transitions in the quark sector. We present a detailed analysis of a model proposed by Chang, Masiero and Murayama, in which the near-maximal atmospheric neutrino mixing angle governs large new b -> s transitions. Relating the supersymmetric low-energy parameters to seven new parameters of this SO(10) GUT model, we perform a correlated study of several flavor-changing neutral current (FCNC) processes. We find the current bound on B(tau -> mu gamma) more constraining than B(B -> X_s gamma). The LEP limit on the lightest Higgs boson mass implies an important lower bound on tan beta, which in turn limits the size of the new FCNC transitions. Remarkably, the combined analysis does not rule out large effects in B_s-B_s-bar mixing and we can easily accomodate the large CP phase in the B_s-B_s-bar system which has recently been inferred from a global analysis of CDF and DO data. The model predicts a particle spectrum which is different from the popular Constrained Minimal Supersymmetric Standard Model (CMSSM). B(tau -> mu gamma) enforces heavy masses, typically above 1 TeV, for the sfermions of the degenerate first two generations. However, the ratio of the third-generation and first-generation sfermion masses is smaller than in the CMSSM and a (dominantly right-handed) stop with mass below 500 GeV is possible.Comment: 44 pages, 5 figures. Footnote and references added, minor changes, Fig. 2 corrected; journal versio

On the Correlations between Flavour Observables in Minimal U(2)^3 Models

The stringent correlations between flavour observables in models with CMFV are consistent with the present data except for the correlation Delta M_{s,d}-epsilon_K. Motivated by the recent work of Barbieri et al, we compare the CMFV correlations with the ones present in a special class of models with an approximate global U(2)^3 flavour symmetry, constrained by a minimal set of spurions governing the breakdown of this symmetry and the assumption that only SM operators are relevant in flavour physics. This analog of CMFV to be called MU(2)^3 allows to avoid the Delta M_{s,d}-epsilon_K tension in question because of reduced flavour symmetry and implied non-MFV contributions to Delta M_{s,d}. While the patterns of flavour violation in K meson system is the same as in CMFV models, the CP-violation in B_{s,d} meson systems can deviate from the one in the SM and CMFV models. We point out a stringent triple S_{psi K_S}-S_{psi phi}-|V_ub| correlation in this class of models that could in the future provide a transparent distinction between different MU(2)^3 models and in the context of these models determine |V_ub| by means of precise measurements of S_{psi K_S} and S_{psi phi} with only small hadronic uncertainties. For fixed S_{psi K_S} the correlation between B(B^+ -> tau^+nu_tau) and S_{psi phi} follows. We also find that MU(2)^3 models could in principle accommodate a negative value of S_{psi phi}, provided |V_ub| is found to be in the ballpark of exclusive determinations and the particular MU(2)^3 model provides a 25% enhancement of epsilon_K. A supersymmetric U(2)^3 model worked out in the Barbieri-School appears to satisfy these requirements. However if B(B^+ -> tau^+nu_tau)>1.0 10^{-4} will be confirmed by future experiments only positive S_{psi phi} is allowed in this framework. We summarize briefly the pattern of flavour violation in rare K and B_{s,d} decays in MU(2)^3 models.Comment: 28 pages, 6 figures; v2: Few references and discussion on CP violation in B_s-> mu^+ mu^- added; v3: Several clarifying comments added, conclusions unchanged, version accepted for publication in JHE

The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version

Beliefs and perceptions about the causes of breast cancer: a case-control study

Background: Attributions of causality are common for many diseases, including breast cancer. The risk of developing breast cancer can be reduced by modifications to lifestyle and behaviours to minimise exposure to specific risk factors, such as obesity. However, these modifications will only occur if women believe that certain behaviours/lifestyle factors have an impact on the development of breast cancer. Method: The Breast Cancer, Environment and Employment Study is a case-control study of breast cancer conducted in Western Australia between 2009 and 2011. As part of the study 1109 women with breast cancer and 1633 women without the disease completed a Risk Perception questionnaire in which they were asked in an open-ended question for specific cause/s to the development of breast cancer in themselves or in others. The study identified specific causal beliefs, and assessed differences in the beliefs between women with and without breast cancer. Results: The most common attributions in women without breast cancer were to familial or inherited factors (77.6%), followed by lifestyle factors, such as poor diet and smoking (47.1%), and environmental factors, such as food additives (45.4%). The most common attributions in women with breast cancer were to mental or emotional factors (46.3%), especially stress, followed by lifestyle factors (38.6%) and physiological factors (37.5%), particularly relating to hormonal history.Conclusions: While the majority of participants in this study provided one or more causal attributions for breast cancer, many of the reported risk factors do not correspond to those generally accepted by the scientific community. These misperceptions could be having a significant impact on the success of prevention and early detection programs that seek to minimise the pain and suffering caused by this disease. In particular, women who have no family history of the disease may not work to minimise their exposure to the modifiable risk factors

Population genomics of marine zooplankton

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Bucklin, Ann et al. "Population Genomics of Marine Zooplankton." Population Genomics: Marine Organisms. Ed. Om P. Rajora and Marjorie Oleksiak. Springer, 2018. doi:10.1007/13836_2017_9.The exceptionally large population size and cosmopolitan biogeographic distribution that distinguish many – but not all – marine zooplankton species generate similarly exceptional patterns of population genetic and genomic diversity and structure. The phylogenetic diversity of zooplankton has slowed the application of population genomic approaches, due to lack of genomic resources for closelyrelated species and diversity of genomic architecture, including highly-replicated genomes of many crustaceans. Use of numerous genomic markers, especially single nucleotide polymorphisms (SNPs), is transforming our ability to analyze population genetics and connectivity of marine zooplankton, and providing new understanding and different answers than earlier analyses, which typically used mitochondrial DNA and microsatellite markers. Population genomic approaches have confirmed that, despite high dispersal potential, many zooplankton species exhibit genetic structuring among geographic populations, especially at large ocean-basin scales, and have revealed patterns and pathways of population connectivity that do not always track ocean circulation. Genomic and transcriptomic resources are critically needed to allow further examination of micro-evolution and local adaptation, including identification of genes that show evidence of selection. These new tools will also enable further examination of the significance of small-scale genetic heterogeneity of marine zooplankton, to discriminate genetic “noise” in large and patchy populations from local adaptation to environmental conditions and change.Support was provided by the US National Science Foundation to AB and RJO (PLR-1044982) and to RJO (MCB-1613856); support to IS and MC was provided by Nord University (Norway)

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis