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Institution

University of Glasgow

EducationGlasgow, United Kingdom
About: University of Glasgow is a education organization based out in Glasgow, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 40355 authors who have published 98254 publications receiving 3815419 citations. The organization is also known as: Glasgow University & Glasgow Uni.


Papers
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Journal ArticleDOI
TL;DR: It is shown that typical road surfaces may be considered as realizations of homogeneous and isotropic two-dimensional Gaussian random processes, and a single direct spectral density function provides a road surface description which is sufficient for multi-track vehicle response analysis.

586 citations

Journal ArticleDOI
Roel Aaij1, Bernardo Adeva2, Marco Adinolfi3, Ziad Ajaltouni4  +818 moreInstitutions (68)
TL;DR: In this article, a test of lepton universality is performed by measuring the ratio of the branching fractions of the B$0$ → K$*0}$ e$+}$ π$−}$ decays, and the ratio is measured in two regions of the dilepton invariant mass squared.
Abstract: A test of lepton universality, performed by measuring the ratio of the branching fractions of the B$^{0}$ → K$^{*0}$ μ$^{+}$ μ$^{−}$ and B$^{0}$ → K$^{*0}$ e$^{+}$ e$^{−}$ decays, $ {R}_{K^{*0}} $ , is presented. The K$^{*0}$ meson is reconstructed in the final state K$^{+}$ π$^{−}$, which is required to have an invariant mass within 100 MeV/c$^{2}$ of the known K$^{*}$(892)$^{0}$ mass. The analysis is performed using proton-proton collision data, corresponding to an integrated luminosity of about 3 fb$^{−1}$, collected by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV. The ratio is measured in two regions of the dilepton invariant mass squared, q$^{2}$, to be $ {R}_{K^{*0}}=\left\{\begin{array}{l}{0.66_{-}^{+}}_{0.07}^{0.11}\left(\mathrm{stat}\right)\pm 0.03\left(\mathrm{syst}\right)\kern1em \mathrm{f}\mathrm{o}\mathrm{r}\kern1em 0.045<{q}^2<1.1\kern0.5em {\mathrm{GeV}}^2/{c}^4,\hfill \\ {}{0.69_{-}^{+}}_{0.07}^{0.11}\left(\mathrm{stat}\right)\pm 0.05\left(\mathrm{syst}\right)\kern1em \mathrm{f}\mathrm{o}\mathrm{r}\kern1em 1.1<{q}^2<6.0\kern0.5em {\mathrm{GeV}}^2/{c}^4.\hfill \end{array}\right. $

586 citations

Journal ArticleDOI
TL;DR: It is proposed that the processes by which a cell enters into, maintains viability in, and exits from quiescence are best viewed as an environmentally triggered cycle: the cell quiescent cycle.
Abstract: The cells of organisms as diverse as bacteria and humans can enter stable, nonproliferating quiescent states. Quiescent cells of eukaryotic and prokaryotic microorganisms can survive for long periods without nutrients. This alternative state of cells is still poorly understood, yet much benefit is to be gained by understanding it both scientifically and with reference to human health. Here, we review our knowledge of one “model” quiescent cell population, in cultures of yeast grown to stationary phase in rich media. We outline the importance of understanding quiescence, summarize the properties of quiescent yeast cells, and clarify some definitions of the state. We propose that the processes by which a cell enters into, maintains viability in, and exits from quiescence are best viewed as an environmentally triggered cycle: the cell quiescence cycle. We synthesize what is known about the mechanisms by which yeast cells enter into quiescence, including the possible roles of the protein kinase A, TOR, protein kinase C, and Snf1p pathways. We also discuss selected mechanisms by which quiescent cells maintain viability, including metabolism, protein modification, and redox homeostasis. Finally, we outline what is known about the process by which cells exit from quiescence when nutrients again become available.

584 citations

Journal ArticleDOI
Thomas W. Winkler1, Anne E. Justice2, Mariaelisa Graff2, Llilda Barata3  +435 moreInstitutions (106)
TL;DR: In this paper, the authors performed meta-analyses of 114 studies with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium.
Abstract: Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

584 citations

Journal ArticleDOI
TL;DR: The singular value decomposition and its interpretation as a linear biplot have proved to be a powerful tool for analysing many forms of multivariate data as discussed by the authors, including compositional data consisting of positive vectors.
Abstract: Summary. The singular value decomposition and its interpretation as a linear biplot have proved to be a powerful tool for analysing many forms of multivariate data. Here we adapt biplot methodology to the specific case of compositional data consisting of positive vectors each of which is constrained to have unit sum. These relative variation biplots have properties relating to the special features of compositional data: the study of ratios, subcompositions and models of compositional relationships. The methodology is applied to a data set consisting of six-part colour compositions in 22 abstract paintings, showing how the singular value decomposition can achieve an accurate biplot of the colour ratios and how possible models interrelating the colours can be diagnosed.

584 citations


Authors

Showing all 40860 results

NameH-indexPapersCitations
George Davey Smith2242540248373
John J.V. McMurray1781389184502
David A. Weitz1781038114182
Robin M. Murray1711539116362
Ian J. Deary1661795114161
G. A. Cowan1592353172594
Hannes Jung1592069125069
Gavin Davies1592036149835
Naveed Sattar1551326116368
Rajesh Kumar1494439140830
Debbie A Lawlor1471114101123
Kevin Murphy146728120475
David L. Clements145597112129
Alan J. Silman14170892864
Dario Bisello1402005107859
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023201
2022765
20215,834
20205,606
20195,187
20184,619