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Institution

University of Oxford

EducationOxford, Oxfordshire, United Kingdom
About: University of Oxford is a education organization based out in Oxford, Oxfordshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 99713 authors who have published 258108 publications receiving 12972806 citations. The organization is also known as: Oxford University & Oxon..


Papers
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Journal ArticleDOI
TL;DR: Six donors who make a strong CTL response to an immunodominant HLA-B27-restricted epitope and two donors who progressed to AIDS, CTL escape to fixation by the same mutation was observed, but only after 9–12 years of epitope stability.
Abstract: The precise role played by HIV-specific cytotoxic T lymphocytes (CTL) in HIV infection remains controversial Despite strong CTL responses being generated during the asymptomatic phase, the virus persists and AIDS ultimately develops It has been argued that the virus is so variable, and the virus turnover so great that escape from CTL recognition would occur continually, but so far there is limited evidence for CTL escape The opposing argument is that evidence for CTL escape is present but hard to find because multiple anti-HIV immune responses are acting simultaneously during the asymptomatic phase of infection We describe six donors who make a strong CTL response to an immunodominant HLA-B27-restricted epitope In the two donors who progressed to AIDS, CTL escape to fixation by the same mutation was observed, but only after 9-12 years of epitope stability CTL escape may play an important role in the pathogenesis of HIV infection

1,192 citations

Book ChapterDOI
06 Jul 2015
TL;DR: This paper describes a zero-shot learning approach that can be implemented in just one line of code, yet it is able to outperform state of the art approaches on standard datasets.
Abstract: Zero-shot learning consists in learning how to recognise new concepts by just having a description of them. Many sophisticated approaches have been proposed to address the challenges this problem comprises. In this paper we describe a zero-shot learning approach that can be implemented in just one line of code, yet it is able to outperform state of the art approaches on standard datasets. The approach is based on a more general framework which models the relationships between features, attributes, and classes as a two linear layers network, where the weights of the top layer are not learned but are given by the environment. We further provide a learning bound on the generalisation error of this kind of approaches, by casting them as domain adaptation methods. In experiments carried out on three standard real datasets, we found that our approach is able to perform significantly better than the state of art on all of them, obtaining a ratio of improvement up to 17%.

1,192 citations

Journal ArticleDOI
TL;DR: In this paper, the authors studied the unitary time evolution of the entropy of entanglement of a one-dimensional system between the degrees of freedom in an interval of length and its complement, starting from a pure state which is not an eigenstate of the Hamiltonian.
Abstract: We study the unitary time evolution of the entropy of entanglement of a one-dimensional system between the degrees of freedom in an interval of length and its complement, starting from a pure state which is not an eigenstate of the Hamiltonian. We use path integral methods of quantum field theory as well as explicit computations for the transverse Ising spin chain. In both cases, there is a maximum speed v of propagation of signals. In general the entanglement entropy increases linearly with time t up to , after which it saturates at a value proportional to , the coefficient depending on the initial state. This behaviour may be understood as a consequence of causality.

1,191 citations

Journal ArticleDOI
04 May 2020-Science
TL;DR: It is shown how SARS-CoV-2 S glycans differ from typical host glycan processing, which may have implications in viral pathobiology and vaccine design, and enables mapping of the glycan-processing states across the trimeric viral spike.
Abstract: The emergence of the betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), represents a considerable threat to global human health. Vaccine development is focused on the principal target of the humoral immune response, the spike (S) glycoprotein, which mediates cell entry and membrane fusion. The SARS-CoV-2 S gene encodes 22 N-linked glycan sequons per protomer, which likely play a role in protein folding and immune evasion. Here, using a site-specific mass spectrometric approach, we reveal the glycan structures on a recombinant SARS-CoV-2 S immunogen. This analysis enables mapping of the glycan-processing states across the trimeric viral spike. We show how SARS-CoV-2 S glycans differ from typical host glycan processing, which may have implications in viral pathobiology and vaccine design.

1,190 citations

Journal ArticleDOI
TL;DR: A genome-wide association scan in individuals with Crohn's disease by the Wellcome Trust Case Control Consortium detected strong association at four novel loci, and 37 SNPs from these and other loci were tested for association in an independent case-control sample.
Abstract: A genome-wide association scan in individuals with Crohn's disease by the Wellcome Trust Case Control Consortium detected strong association at four novel loci. We tested 37 SNPs from these and other loci for association in an independent case-control sample. We obtained replication for the autophagy-inducing IRGM gene on chromosome 5q33.1 (replication P = 6.6 x 10(-4), combined P = 2.1 x 10(-10)) and for nine other loci, including NKX2-3, PTPN2 and gene deserts on chromosomes 1q and 5p13.

1,189 citations


Authors

Showing all 101421 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Albert Hofman2672530321405
Douglas G. Altman2531001680344
Salim Yusuf2311439252912
George Davey Smith2242540248373
Yi Chen2174342293080
David J. Hunter2131836207050
Nicholas J. Wareham2121657204896
Christopher J L Murray209754310329
Cyrus Cooper2041869206782
Mark J. Daly204763304452
David Miller2032573204840
Mark I. McCarthy2001028187898
Raymond J. Dolan196919138540
Frank E. Speizer193636135891
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023654
20222,554
202117,608
202017,299
201915,037
201813,726