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 & Transplantation. 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, Transplantation, Immune system, Cancer, Pregnancy
Papers published on a yearly basis
Papers
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TL;DR: An essential role for type I IFN is defined, produced via cooperation between multiple host sensors and acting directly on nonhematopoietic cells, in the control of CHIKV.
Abstract: Chikungunya virus (CHIKV) is the causative agent of an outbreak that began in La Reunion in 2005 and remains a major public health concern in India, Southeast Asia, and southern Europe. CHIKV is transmitted to humans by mosquitoes and the associated disease is characterized by fever, myalgia, arthralgia, and rash. As viral load in infected patients declines before the appearance of neutralizing antibodies, we studied the role of type I interferon (IFN) in CHIKV pathogenesis. Based on human studies and mouse experimentation, we show that CHIKV does not directly stimulate type I IFN production in immune cells. Instead, infected nonhematopoietic cells sense viral RNA in a Cardif-dependent manner and participate in the control of infection through their production of type I IFNs. Although the Cardif signaling pathway contributes to the immune response, we also find evidence for a MyD88-dependent sensor that is critical for preventing viral dissemination. Moreover, we demonstrate that IFN-alpha/beta receptor (IFNAR) expression is required in the periphery but not on immune cells, as IFNAR(-/-)-->WT bone marrow chimeras are capable of clearing the infection, whereas WT-->IFNAR(-/-) chimeras succumb. This study defines an essential role for type I IFN, produced via cooperation between multiple host sensors and acting directly on nonhematopoietic cells, in the control of CHIKV.
286 citations
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TL;DR: Data integration and biomolecular network reconstruction is a powerful approach to uncover molecular mechanisms in colorectal cancer and shows the utility of this approach for the investigation of malignant tumors and other diseases.
286 citations
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TL;DR: A simulation study using data models and analysis of real microarray data shows that for small samples the root mean square differences of the estimated and true metrics are considerable, and even for large samples, there is only weak correlation between the true and estimated metrics.
Abstract: Motivation: The receiver operator characteristic (ROC) curves are commonly used in biomedical applications to judge the performance of a discriminant across varying decision thresholds. The estimated ROC curve depends on the true positive rate (TPR) and false positive rate (FPR), with the key metric being the area under the curve (AUC). With small samples these rates need to be estimated from the training data, so a natural question arises: How well do the estimates of the AUC, TPR and FPR compare with the true metrics?
Results: Through a simulation study using data models and analysis of real microarray data, we show that (i) for small samples the root mean square differences of the estimated and true metrics are considerable; (ii) even for large samples, there is only weak correlation between the true and estimated metrics; and (iii) generally, there is weak regression of the true metric on the estimated metric. For classification rules, we consider linear discriminant analysis, linear support vector machine (SVM) and radial basis function SVM. For error estimation, we consider resubstitution, three kinds of cross-validation and bootstrap. Using resampling, we show the unreliability of some published ROC results.
Availability: Companion web site at http://compbio.tgen.org/paper_supp/ROC/roc.html
Contact: edward@mail.ece.tamu.edu
286 citations
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Erasmus University Rotterdam1, University of Southampton2, University Hospital Southampton NHS Foundation Trust3, University of Porto4, Paris Descartes University5, Sorbonne6, University of Southern California7, University of Crete8, Maastricht University9, National and Kapodistrian University of Athens10, University Medical Center Groningen11, Université de Sherbrooke12, Norwegian Institute of Public Health13, University of Bologna14, Nofer Institute of Occupational Medicine15, University of California, Davis16, Harvard University17, University of Illinois at Chicago18, University of Valencia19, National Institutes of Health20, University of Turku21, University of Bristol22, Helmholtz Centre for Environmental Research - UFZ23, Jagiellonian University Medical College24, Åbo Akademi University25, Harokopio University26, Public Health Research Institute27, University of Copenhagen28, University of Southern Denmark29, La Trobe University30, University of Helsinki31, University of Turin32, Radboud University Nijmegen33, University of Trieste34, University of Bergen35, Ludwig Maximilian University of Munich36, Slovak Medical University37, Utrecht University38, Pompeu Fabra University39
TL;DR: In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights, however, the optimal gestations weight gain ranges had limited predictive value for the outcomes assessed.
Abstract: Importance Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all prepregnancy weight ranges. Objectives To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories. Design, Setting, and Participants Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015. Exposures Gestational weight gain. Main Outcomes and Measures The main outcome termedany adverse outcomewas defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth. Results Of the 196 670 women (median age, 30.0 years [quartile 1 and 3, 27.0 and 33.0 years] and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI Conclusions and Relevance In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights. The estimates of optimal gestational weight gain may inform prenatal counseling; however, the optimal gestational weight gain ranges had limited predictive value for the outcomes assessed.
286 citations
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National Institutes of Health1, University of L'Aquila2, University of Genoa3, Universidad Católica de Valencia San Vicente Mártir4, Paris Descartes University5, Science Applications International Corporation6, United States Department of Health and Human Services7, Paris Diderot University8, French Institute of Health and Medical Research9, McGill University10, Washington State University Spokane11, University of Paris-Sud12, Institut Gustave Roussy13, Fondation Jean Dausset Centre d'Etude du Polymorphisme Humain14
TL;DR: The findings suggest that POT1 is a major susceptibility gene for familial melanoma in several populations, and that this variant perturbs telomere maintenance.
Abstract: Although CDKN2A is the most frequent high-risk melanoma susceptibility gene, the underlying genetic factors for most melanoma-prone families remain unknown. Using whole-exome sequencing, we identified a rare variant that arose as a founder mutation in the telomere shelterin gene POT1 (chromosome 7, g.124493086C>T; p.Ser270Asn) in five unrelated melanoma-prone families from Romagna, Italy. Carriers of this variant had increased telomere lengths and numbers of fragile telomeres, suggesting that this variant perturbs telomere maintenance. Two additional rare POT1 variants were identified in all cases sequenced in two separate Italian families, one variant per family, yielding a frequency for POT1 variants comparable to that for CDKN2A mutations in this population. These variants were not found in public databases or in 2,038 genotyped Italian controls. We also identified two rare recurrent POT1 variants in US and French familial melanoma cases. Our findings suggest that POT1 is a major susceptibility gene for familial melanoma in several populations.
286 citations
Authors
Showing all 21023 results
Name | H-index | Papers | Citations |
---|---|---|---|
Guido Kroemer | 236 | 1404 | 246571 |
Cyrus Cooper | 204 | 1869 | 206782 |
Jean-Laurent Casanova | 144 | 842 | 76173 |
Alain Fischer | 143 | 770 | 81680 |
Maxime Dougados | 134 | 1054 | 69979 |
Carlos López-Otín | 126 | 494 | 83933 |
Giuseppe Viale | 123 | 740 | 72799 |
Thierry Poynard | 119 | 668 | 64548 |
Lorenzo Galluzzi | 118 | 477 | 71436 |
Shahrokh F. Shariat | 118 | 1637 | 58900 |
Richard E. Tremblay | 116 | 685 | 45844 |
Olivier Hermine | 111 | 1026 | 43779 |
Yehezkel Ben-Ari | 110 | 459 | 44293 |
Loïc Guillevin | 108 | 800 | 51085 |
Gérard Socié | 107 | 920 | 44186 |