Institution
Paris Descartes University
Government•Paris, France•
About: Paris Descartes University is a government organization based out in Paris, France. It is known for research contribution in the topics: Population & Immune system. The organization has 20987 authors who have published 37456 publications receiving 1206222 citations. The organization is also known as: Université Paris V-Descartes & Université de Paris V.
Topics: Population, Immune system, Cancer, Transplantation, Pregnancy
Papers published on a yearly basis
Papers
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University of Bristol1, University Hospitals Bristol NHS Foundation Trust2, Monash University3, Cochrane Collaboration4, French Institute of Health and Medical Research5, Paris Descartes University6, St George's, University of London7, University of York8, Queen Mary University of London9, Clinical Trial Service Unit10, Harvard University11, University of Oxford12, Odense University Hospital13, University of Southern Denmark14, University of Alberta15, University of Toronto16, University of Manchester17, Johns Hopkins University18, McGill University19, University College London20
TL;DR: The Cochrane risk-of-bias tool has been updated to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.
Abstract: Assessment of risk of bias is regarded as an essential component of a systematic review on the effects of an intervention. The most commonly used tool for randomised trials is the Cochrane risk-of-bias tool. We updated the tool to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.
9,228 citations
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University of Bristol1, Harvard University2, University Hospitals Bristol NHS Foundation Trust3, Research Triangle Park4, University of Toronto5, University of Oxford6, University of Ottawa7, Paris Descartes University8, University of London9, University of York10, University of Birmingham11, University of Southern Denmark12, University of Liverpool13, University of East Anglia14, Loyola University Chicago15, University of Aberdeen16, Kaiser Permanente17, Baruch College18, McMaster University19, Cochrane Collaboration20, McGill University21, Ottawa Hospital Research Institute22, University of Louisville23, University of Melbourne24
TL;DR: Risk of Bias In Non-randomised Studies - of Interventions is developed, a new tool for evaluating risk of bias in estimates of the comparative effectiveness of interventions from studies that did not use randomisation to allocate units or clusters of individuals to comparison groups.
Abstract: Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.
8,028 citations
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Wellcome Trust Sanger Institute1, Cambridge University Hospitals NHS Foundation Trust2, Wellcome Trust3, University of British Columbia4, University of Cambridge5, Oslo University Hospital6, The Breast Cancer Research Foundation7, University of Oslo8, University of Münster9, Université libre de Bruxelles10, German Cancer Research Center11, University of Iceland12, Erasmus University Rotterdam13, Paris Descartes University14, French Institute of Health and Medical Research15, University of Paris16, Broad Institute17, University of Bergen18, University of Oviedo19, University of Queensland20, University of Glasgow21, Harvard University22, United States Department of Veterans Affairs23, Netherlands Cancer Institute24, University of Kiel25, Radboud University Nijmegen26, King's College London27, Curie Institute28, University of New South Wales29, Bankstown Lidcombe Hospital30, University of Barcelona31
TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Abstract: All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.
7,904 citations
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Medical University of Vienna1, Boston University2, Arthritis Research UK3, Johns Hopkins University4, University of California, San Francisco5, Humboldt University of Berlin6, University of Toronto7, National Jewish Health8, Brigham and Women's Hospital9, Paris Descartes University10, University of Leeds11, Catholic University of the Sacred Heart12, Erasmus University Rotterdam13, University of Colorado Denver14, Leiden University15, University of California, San Diego16, University of Massachusetts Medical School17, University of Michigan18, University of Washington19, McGill University Health Centre20, University of Pittsburgh21, Ministry of Health (New Zealand)22, New York University23, University of Manchester24, University of Amsterdam25, University of Kansas26, Women's College Hospital27
TL;DR: This new classification system redefines the current paradigm of RA by focusing on features at earlier stages of disease that are associated with persistent and/or erosive disease, rather than defining the disease by its late-stage features.
Abstract: Objective The 1987 American College of Rheumatology (ACR; formerly the American Rheumatism Association) classifi cation criteria for rheumatoid arthritis (RA) have been criticised for their lack of sensitivity in early disease. This work was undertaken to develop new classifi cation criteria for RA. Methods A joint working group from the ACR and the European League Against Rheumatism developed, in three phases, a new approach to classifying RA. The work focused on identifying, among patients newly presenting with undifferentiated infl ammatory synovitis, factors that best discriminated between those who were and those who were not at high risk for persistent and/ or erosive disease—this being the appropriate current paradigm underlying the disease construct ‘RA’. Results In the new criteria set, classifi cation as ‘defi nite RA’ is based on the confi rmed presence of synovitis in at least one joint, absence of an alternative diagnosis better explaining the synovitis, and achievement of a total score of 6 or greater (of a possible 10) from the individual scores in four domains: number and site of involved joints (range 0–5), serological abnormality (range 0–3), elevated acute-phase response (range 0–1) and symptom duration (two levels; range 0–1). Conclusion This new classifi cation system redefi nes the current paradigm of RA by focusing on features at earlier stages of disease that are associated with persistent and/or erosive disease, rather than defi ning the disease by its late-stage features. This will refocus attention on the important need for earlier diagnosis and institution of effective disease-suppressing therapy to prevent or minimise the occurrence of the undesirable sequelae that currently comprise the paradigm underlying the disease construct ‘RA’.
7,120 citations
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TL;DR: A molecular mechanism for regulation of the mammalian autophagy-initiating kinase Ulk1, a homologue of yeast ATG1, is demonstrated and a signalling mechanism for UlK1 regulation and autophagic induction in response to nutrient signalling is revealed.
Abstract: Autophagy is a process by which components of the cell are degraded to maintain essential activity and viability in response to nutrient limitation. Extensive genetic studies have shown that the yeast ATG1 kinase has an essential role in autophagy induction. Furthermore, autophagy is promoted by AMP activated protein kinase (AMPK), which is a key energy sensor and regulates cellular metabolism to maintain energy homeostasis. Conversely, autophagy is inhibited by the mammalian target of rapamycin (mTOR), a central cell-growth regulator that integrates growth factor and nutrient signals. Here we demonstrate a molecular mechanism for regulation of the mammalian autophagy-initiating kinase Ulk1, a homologue of yeast ATG1. Under glucose starvation, AMPK promotes autophagy by directly activating Ulk1 through phosphorylation of Ser 317 and Ser 777. Under nutrient sufficiency, high mTOR activity prevents Ulk1 activation by phosphorylating Ulk1 Ser 757 and disrupting the interaction between Ulk1 and AMPK. This coordinated phosphorylation is important for Ulk1 in autophagy induction. Our study has revealed a signalling mechanism for Ulk1 regulation and autophagy induction in response to nutrient signalling.
5,314 citations
Authors
Showing all 21023 results
Name | H-index | Papers | Citations |
---|---|---|---|
Serge Hercberg | 106 | 942 | 56791 |
Paul Dieppe | 105 | 618 | 53529 |
Laurent Abel | 105 | 473 | 37932 |
Jean-Claude Baron | 105 | 522 | 36770 |
Berthold Koletzko | 104 | 976 | 45661 |
Capucine Picard | 103 | 414 | 35779 |
Philippe Ravaud | 101 | 618 | 41409 |
Arnold Munnich | 100 | 729 | 38565 |
David P. Salmon | 99 | 419 | 43935 |
Alan R. Saltiel | 99 | 336 | 49325 |
Stéphane Blanche | 99 | 466 | 34235 |
Michael Doherty | 98 | 525 | 37253 |
Christophe Tzourio | 98 | 475 | 53680 |
Alain Tedgui | 98 | 325 | 34281 |
Archana Singh-Manoux | 97 | 435 | 28730 |