Institution
University of Cambridge
Education•Cambridge, United Kingdom•
About: University of Cambridge is a education organization based out in Cambridge, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 118293 authors who have published 282289 publications receiving 14497093 citations. The organization is also known as: Cambridge University & Cambridge.
Topics: Population, Galaxy, Context (language use), Gene, Transplantation
Papers published on a yearly basis
Papers
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Harvard University1, McGill University2, University of Washington3, Erasmus University Rotterdam4, UCL Institute of Child Health5, University of Helsinki6, University of Cambridge7, Indiana University – Purdue University Indianapolis8, National Institutes of Health9, Wellcome Trust Sanger Institute10, Imperial College London11, Wake Forest University12, Churchill Hospital13, Wellcome Trust Centre for Human Genetics14, University of Oxford15, Tufts University16, Cedars-Sinai Medical Center17, Agency for Science, Technology and Research18, University of Miami19, Health Canada20, Public Health Agency of Canada21, University College London22, University of Aberdeen23, Broad Institute24, University of Pittsburgh25, Boston University26, King's College London27, University of Oulu28, Finnish Institute of Occupational Health29
TL;DR: In this article, a genome-wide association study of 25-hydroxyvitamin D concentrations in 33,996 individuals of European descent from 15 cohorts was conducted to identify common genetic variants affecting vitamin D concentrations and risk of insufficiency.
1,381 citations
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28 Jun 2011TL;DR: PILCO reduces model bias, one of the key problems of model-based reinforcement learning, in a principled way by learning a probabilistic dynamics model and explicitly incorporating model uncertainty into long-term planning.
Abstract: In this paper, we introduce PILCO, a practical, data-efficient model-based policy search method. PILCO reduces model bias, one of the key problems of model-based reinforcement learning, in a principled way. By learning a probabilistic dynamics model and explicitly incorporating model uncertainty into long-term planning, PILCO can cope with very little data and facilitates learning from scratch in only a few trials. Policy evaluation is performed in closed form using state-of-the-art approximate inference. Furthermore, policy gradients are computed analytically for policy improvement. We report unprecedented learning efficiency on challenging and high-dimensional control tasks.
1,379 citations
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TL;DR: Direct evidence for CAF heterogeneity in PDA tumor biology is provided, providing direct evidence for disease etiology and therapeutic development in mouse and human PDA tissue.
Abstract: Pancreatic stellate cells (PSCs) differentiate into cancer-associated fibroblasts (CAFs) that produce desmoplastic stroma, thereby modulating disease progression and therapeutic response in pancreatic ductal adenocarcinoma (PDA). However, it is unknown whether CAFs uniformly carry out these tasks or if subtypes of CAFs with distinct phenotypes in PDA exist. We identified a CAF subpopulation with elevated expression of α-smooth muscle actin (αSMA) located immediately adjacent to neoplastic cells in mouse and human PDA tissue. We recapitulated this finding in co-cultures of murine PSCs and PDA organoids, and demonstrated that organoid-activated CAFs produced desmoplastic stroma. The co-cultures showed cooperative interactions and revealed another distinct subpopulation of CAFs, located more distantly from neoplastic cells, which lacked elevated αSMA expression and instead secreted IL6 and additional inflammatory mediators. These findings were corroborated in mouse and human PDA tissue, providing direct evidence for CAF heterogeneity in PDA tumor biology with implications for disease etiology and therapeutic development.
1,379 citations
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TL;DR: In this article, the authors argue that the Lorentz model has reached the limit of its usefulness and must be abandoned before we can make further progress in the field of physics.
Abstract: The Lorentz model of the electron as a small sphere charged with electricity, possessing mass on account of the energy of the electric field around it, has proved very valuable in accounting for the motion and radiation of electrons in a certain domain of problems, in which the electromagnetic field does not vary too rapidly and the accelerations of the electrons are not too great. Beyond this domain it will not go unless supplemented by further assumptions about the forces that hold the charge on an electron together. No natural way of introducing such further assumptions has been discovered, and it seems that the Lorentz model has reached the limit of its usefulness and must be abandoned before we can make further progress. One of the most attractive ideas in the Lorentz model of the electron, the idea that all mass is of electromagnetic; origin, appears at the present time to be wrong, for two separate reasons. First, the discovery of the neutron has provided us with a form of mass which it is very hard to believe could be of electromagnetic nature. Secondly, we have the theory of the positron— a theory in agreement with experiment so far as is known—in which positive and negative values for the mass of an electron play symmetrical roles. This cannot be fitted in with the electromagnetic idea of mass, which insists on all mass being positive, even in abstract theory.
1,378 citations
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TL;DR: There is convincing evidence of a modest association between DUP and outcome, which supports the case for clinical trials that examine the effect of reducing DUP.
Abstract: Context Duration of untreated psychosis (DUP) is the time from manifestation of the first psychotic symptom to initiation of adequate treatment. It has been postulated that a longer DUP leads to a poorer prognosis. If so, outcome might be improved through earlier detection and treatment. Objectives To establish whether DUP is associated with prognosis and to determine whether any association is explained by confounding with premorbid adjustment. Data Sources The CINAHL (Cumulative Index to Nursing and Allied Health), EMBASE, MEDLINE, and PsychLIT databases were searched from their inception dates to May 2004. Study Selection Eligible studies reported the relationship between DUP and outcome in prospective cohorts recruited during their first episode of psychosis. Twenty-six eligible studies involving 4490 participants were identified from 11 458 abstracts, each screened by 2 reviewers. Data Extraction Data were extracted independently and were checked by double entry. Sensitivity analyses were conducted excluding studies that had follow-up rates of less than 80%, included affective psychoses, or did not use a standardized assessment of DUP. Data Synthesis Independent meta-analyses were conducted of correlational data and of data derived from comparisons of long and short DUP groups. Most data were correlational, and these showed a significant association between DUP and several outcomes at 6 and 12 months (including total symptoms, depression/anxiety, negative symptoms, overall functioning, positive symptoms, and social functioning). Long vs short DUP data showed an association between longer DUP and worse outcome at 6 months in terms of total symptoms, overall functioning, positive symptoms, and quality of life. Patients with a long DUP were significantly less likely to achieve remission. The observed association between DUP and outcome was not explained by premorbid adjustment. Conclusions There is convincing evidence of a modest association between DUP and outcome, which supports the case for clinical trials that examine the effect of reducing DUP.
1,377 citations
Authors
Showing all 119522 results
Name | H-index | Papers | Citations |
---|---|---|---|
Albert Hofman | 267 | 2530 | 321405 |
Zhong Lin Wang | 245 | 2529 | 259003 |
Solomon H. Snyder | 232 | 1222 | 200444 |
Trevor W. Robbins | 231 | 1137 | 164437 |
George Davey Smith | 224 | 2540 | 248373 |
Nicholas J. Wareham | 212 | 1657 | 204896 |
Cyrus Cooper | 204 | 1869 | 206782 |
Eric B. Rimm | 196 | 988 | 147119 |
Martin White | 196 | 2038 | 232387 |
Simon D. M. White | 189 | 795 | 231645 |
Michael Rutter | 188 | 676 | 151592 |
George Efstathiou | 187 | 637 | 156228 |
Mark Hallett | 186 | 1170 | 123741 |
David H. Weinberg | 183 | 700 | 171424 |
Paul G. Richardson | 183 | 1533 | 155912 |