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1. Impacts of electric carsharing on a power sector with variable renewables

Author

Guéret, Adeline, Schill, Wolf-Peter, and Gaete-Morales, Carlos

Subjects
Economics - General Economics
Abstract

Electrifying the car fleet is a major strategy for mitigating emissions in the transport sector. As electrification cannot solve all negative externalities associated with cars, reducing the size of the car fleet would be beneficial. Electric carsharing could allow to reconcile current car usage habits with a smaller fleet, but this may reduce the potential of electric cars to align their grid interactions with variable renewable electricity generation. We investigate how electric carsharing may impact the power sector, combining three methods: sequence clustering of car travel diaries, generation of synthetic electric vehicle time series, and power sector modelling. We show that switching to electric carsharing only moderately increases power sector costs, less than 110 euros per substituted car in our main setting. This effect is largest with bidirectional charging. We conclude that the power sector interactions of shared electric car fleets could still be aligned with variable renewable electricity generation., Comment: Additional sensitivity analyses; added references; corrected typos

Published
2024
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2. Veni, Vidi, Vici: Solving the Myriad of Challenges before Knowledge Graph Learning

Author

Sardina, Jeffrey, Costabello, Luca, and Guéret, Christophe

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Knowledge Graphs (KGs) have become increasingly common for representing large-scale linked data. However, their immense size has required graph learning systems to assist humans in analysis, interpretation, and pattern detection. While there have been promising results for researcher- and clinician- empowerment through a variety of KG learning systems, we identify four key deficiencies in state-of-the-art graph learning that simultaneously limit KG learning performance and diminish the ability of humans to interface optimally with these learning systems. These deficiencies are: 1) lack of expert knowledge integration, 2) instability to node degree extremity in the KG, 3) lack of consideration for uncertainty and relevance while learning, and 4) lack of explainability. Furthermore, we characterise state-of-the-art attempts to solve each of these problems and note that each attempt has largely been isolated from attempts to solve the other problems. Through a formalisation of these problems and a review of the literature that addresses them, we adopt the position that not only are deficiencies in these four key areas holding back human-KG empowerment, but that the divide-and-conquer approach to solving these problems as individual units rather than a whole is a significant barrier to the interface between humans and KG learning systems. We propose that it is only through integrated, holistic solutions to the limitations of KG learning systems that human and KG learning co-empowerment will be efficiently affected. We finally present our "Veni, Vidi, Vici" framework that sets a roadmap for effectively and efficiently shifting to a holistic co-empowerment model in both the KG learning and the broader machine learning domain., Comment: This article was accepted for publication at IEEE ICSC 2024, and is being made available as an author preprint. As soon as it is published by IEEE, this registry will be updated in accordance with the IEEE copyright agreement

Published
2024

3. Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals

Author

Warren, Greta, Keane, Mark T., Gueret, Christophe, and Delaney, Eoin

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Counterfactual explanations are an increasingly popular form of post hoc explanation due to their (i) applicability across problem domains, (ii) proposed legal compliance (e.g., with GDPR), and (iii) reliance on the contrastive nature of human explanation. Although counterfactual explanations are normally used to explain individual predictive-instances, we explore a novel use case in which groups of similar instances are explained in a collective fashion using ``group counterfactuals'' (e.g., to highlight a repeating pattern of illness in a group of patients). These group counterfactuals meet a human preference for coherent, broad explanations covering multiple events/instances. A novel, group-counterfactual algorithm is proposed to generate high-coverage explanations that are faithful to the to-be-explained model. This explanation strategy is also evaluated in a large, controlled user study (N=207), using objective (i.e., accuracy) and subjective (i.e., confidence, explanation satisfaction, and trust) psychological measures. The results show that group counterfactuals elicit modest but definite improvements in people's understanding of an AI system. The implications of these findings for counterfactual methods and for XAI are discussed.

Published
2023

5. Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows

Author

Ryan, Cathal, Guéret, Christophe, Berry, Donagh, Corcoran, Medb, Keane, Mark T., and Mac Namee, Brian

Subjects
Computer Science - Machine Learning
Abstract

Mastitis is a billion dollar health problem for the modern dairy industry, with implications for antibiotic resistance. The use of AI techniques to identify the early onset of this disease, thus has significant implications for the sustainability of this agricultural sector. Current approaches to treating mastitis involve antibiotics and this practice is coming under ever increasing scrutiny. Using machine learning models to identify cows at risk of developing mastitis and applying targeted treatment regimes to only those animals promotes a more sustainable approach. Incorrect predictions from such models, however, can lead to monetary losses, unnecessary use of antibiotics, and even the premature death of animals, so it is important to generate compelling explanations for predictions to build trust with users and to better support their decision making. In this paper we demonstrate a system developed to predict mastitis infections in cows and provide explanations of these predictions using counterfactuals. We demonstrate the system and describe the engagement with farmers undertaken to build it.

Published
2021

6. Variant calling and genotyping accuracy of ddRAD-seq: Comparison with 20X WGS in layers.

Author

Mathilde Doublet, Fabien Degalez, Sandrine Lagarrigue, Laetitia Lagoutte, Elise Gueret, Sophie Allais, and Frédéric Lecerf

Subjects
Medicine, Science
Abstract

Whole Genome Sequencing (WGS) remains a costly or unsuitable method for routine genotyping of laying hens. Until now, breeding companies have been using or developing SNP chips. Nevertheless, alternatives methods based on sequencing have been developed. Among these, reduced representation sequencing approaches can offer sequencing quality and cost-effectiveness by reducing the genomic regions covered by sequencing. The aim of this study was to evaluate the ability of double digested Restriction site Associated DNA sequencing (ddRAD-seq) to identify and genotype SNPs in laying hens, by comparison with a presumed reliable WGS approach. Firstly, the sensitivity and precision of variant calling and the genotyping reliability of ddRADseq were determined. Next, the SNP Call Rate (CRSNP) and mean depth of sequencing per SNP (DPSNP) were compared between both methods. Finally, the effect of multiple combinations of thresholds for these parameters on genotyping reliability and amount of remaining SNPs in ddRAD-seq was studied. In raw form, the ddRAD-seq identified 349,497 SNPs evenly distributed on the genome with a CRSNP of 0.55, a DPSNP of 11X and a mean genotyping reliability rate per SNP of 80%. Considering genomic regions covered by expected enzymatic fragments (EFs), the sensitivity of the ddRAD-seq was estimated at 32.4% and its precision at 96.4%. The low CRSNP and DPSNP values were explained by the detection of SNPs outside the EFs theoretically generated by the ddRAD-seq protocol. Indeed, SNPs outside the EFs had significantly lower CRSNP (0.25) and DPSNP (1X) values than SNPs within the EFs (0.7 and 17X, resp.). The study demonstrated the relationship between CRSNP, DPSNP, genotyping reliability and the number of SNPs retained, to provide a decision-support tool for defining filtration thresholds. Severe quality control over ddRAD-seq data allowed to retain a minimum of 40% of the SNPs with a CcR of 98%. Then, ddRAD-seq was defined as a suitable method for variant calling and genotyping in layers.

Published
2024
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7. Can We Detect Mastitis earlier than Farmers?

Author

Ryan, Cathal, Guéret, Christophe, Berry, Donagh, and Mac Namee, Brian

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning
Abstract

The aim of this study was to build a modelling framework that would allow us to be able to detect mastitis infections before they would normally be found by farmers through the introduction of machine learning techniques. In the making of this we created two different modelling framework's, one that works on the premise of detecting Sub Clinical mastitis infections at one Somatic Cell Count recording in advance called SMA and the other tries to detect both Sub Clinical mastitis infections aswell as Clinical mastitis infections at any time the cow is milked called AMA. We also introduce the idea of two different feature sets for our study, these represent different characteristics that should be taken into account when detecting infections, these were the idea of a cow differing to a farm mean and also trends in the lactation. We reported that the results for SMA are better than those created by AMA for Sub Clinical infections yet it has the significant disadvantage of only being able to classify Sub Clinical infections due to how we recorded Sub Clinical infections as being any time a Somatic Cell Count measurement went above a certain threshold where as CM could appear at any stage of lactation. Thus in some cases the lower accuracy values for AMA might in fact be more beneficial to farmers.

Published
2020

8. Background Knowledge Injection for Interpretable Sequence Classification

Author

Gsponer, Severin, Costabello, Luca, Van, Chan Le, Pai, Sumit, Gueret, Christophe, Ifrim, Georgiana, and Lecue, Freddy

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols. Although accuracy is paramount, in certain scenarios interpretability is a must. Unfortunately, such trade-off is often hard to achieve since we lack human-independent interpretability metrics. We introduce a novel sequence learning algorithm, that combines (i) linear classifiers - which are known to strike a good balance between predictive power and interpretability, and (ii) background knowledge embeddings. We extend the classic subsequence feature space with groups of symbols which are generated by background knowledge injected via word or graph embeddings, and use this new feature space to learn a linear classifier. We also present a new measure to evaluate the interpretability of a set of symbolic features based on the symbol embeddings. Experiments on human activity recognition from wearables and amino acid sequence classification show that our classification approach preserves predictive power, while delivering more interpretable models., Comment: New Frontiers in Mining Complex Patterns 2019 @ ECML 2019, 12 pages

Published
2020

9. Diabetes and male sex are key risk factor correlates of the extent of coronary artery calcification: A Euro-CCAD study

Author

Nicoll, Rachel, Zhao, Ying, Wiklund, Urban, Diederichsen, Axel, Mickley, Hans, Ovrehus, Kristian, Zamorano, Jose, Gueret, Pascal, Schmermund, Axel, Maffei, Erica, Cademartiri, Filippo, Budoff, Matt, and Henein, Michael

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease - Coronary Heart Disease, Diabetes, Cardiovascular, Heart Disease, Prevention, Adult, Age Factors, Aged, Cohort Studies, Computed Tomography Angiography, Coronary Artery Disease, Cross-Sectional Studies, Diabetic Angiopathies, Europe, Female, Hospitals, Special, Humans, Male, Middle Aged, Prevalence, Registries, Retrospective Studies, Risk Factors, Severity of Illness Index, Sex Factors, United States, Vascular Calcification, Coronary calcification extent, Risk factors, Gender, Hypertension, Endocrinology & Metabolism, Clinical sciences
Abstract

Background and aimsAlthough much has been written about the conventional cardiovascular risk factor correlates of the extent of coronary artery calcification (CAC), few studies have been carried out on symptomatic patients. This paper assesses the potential ability of risk factors to associate with an increasing CAC score.MethodsFrom the European Calcific Coronary Artery Disease (Euro-CCAD) cohort, we retrospectively investigated 6309 symptomatic patients, 62% male, from Denmark, France, Germany, Italy, Spain and the USA. All had conventional cardiovascular risk factor assessment and CT scanning for CAC scoring.ResultsAmong all patients, male sex (OR = 4.85, p

Published
2017

10. Tinzaparin, an alternative to subcutaneous unfractionated heparin, in patients with severe and end-stage renal impairment: a retrospective observational single-center study

Author

Gouin-Thibault, Isabelle, Mansour, Alexandre, Caribotti, Charlène, Pierre-Jean, Morgane, Bouzille, Guillaume, Ballerie, Alice, Maucorps, Laure, Gueret, Pierre, Nédelec-Gac, Fabienne, Pontis, Adeline, Mahé, Guillaume, Vannier, Stéphane, Behar, Nathalie, Cardiet, Isabelle, Mismetti, Patrick, Frouget, Thierry, and Delavenne, Xavier

Abstract

Tinzaparin could be easier to manage than unfractionated heparin in patients with severe renal impairment. However, clinical and pharmacologic data regarding its use in such patients are lacking.

Published
2024
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11. Hemodialysis access flow measurement: Comparison of ultrasound dilution and ultrafiltration method on NIKKISO DBB-EXA™ dialysis machine

Author

Kosmadakis, Georgios, Enache, Ioana, Gueret, Claudine, Haskour, Abraham, Necoara, Aura, Deville, Clémence, Baudenon, Julien, and Rance, Nicole

Abstract

Background: The methods of estimating vascular access (VA) flow rates are usually based on the indicator dilution theory by measuring recirculation during dialysis sessions.Methods: This is an observational study comparing the VA flow rates measured by NIKKISO DBB-EXA™ and Transonic®. Sixty-five patients (38 M/27 F, mean age 72 ± 10 years) participated in the study. We measured the VA flow rates during dialysis twice with each method and repeated the procedure 7 days later.Results: In 130 double measurements for each method on the same day, mean flow with Transonic® was 1413±715 ml/min and with DBB-EXA™ 1297 ± 664 ml/min. In Bland-Altman analysis, the mean difference between the two methods was 159 ± 211 ml/min (limits of agreement: −274 and 572 ml/min). Eighty-one out of the 130 DBB-EXA™ measurements were within 25% of the Transonic® measurements (62% accuracy). Regarding reproducibility of each method on different days, mean difference in the Bland-Altman analysis was 29 ± 620 ml/min (limits of agreement: −1186 and 1244 ml/min) for the Transonic® measurements and 132 ± 625 ml/min (limits of agreement: −1092 and 1356 ml/min) for the DBB-EXA™ measurements. The measurements on two different days were within 25% of each other for 52 of the 65 patients (80%) with the Transonic® method, and for 35 of the 65 patients (54%) with the DBB-EXA™ method.Conclusions: In conclusion, the DBB-EXA™ method underestimates VA flow rates compared to the Transonic® technique, resulting in a limited accuracy of 62%. There was poor reproducibility for both methods in different day measurements with better performance of the Transonic® technique. The DBB-EXA™ method could be used as a simple tool for a rough estimate of VA flow rates but cannot replace the Transonic® reference method.

Published
2024
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12. Release Early, Release Often: Predicting Change in Versioned Knowledge Organization Systems on the Web

Author

Meroño-Peñuela, Albert, Guéret, Christophe, and Schlobach, Stefan

Subjects
Computer Science - Artificial Intelligence, I.2.4, I.2.6
Abstract

The Semantic Web is built on top of Knowledge Organization Systems (KOS) (vocabularies, ontologies, concept schemes) that provide a structured, interoperable and distributed access to Linked Data on the Web. The maintenance of these KOS over time has produced a number of KOS version chains: subsequent unique version identifiers to unique states of a KOS. However, the release of new KOS versions pose challenges to both KOS publishers and users. For publishers, updating a KOS is a knowledge intensive task that requires a lot of manual effort, often implying deep deliberation on the set of changes to introduce. For users that link their datasets to these KOS, a new version compromises the validity of their links, often creating ramifications. In this paper we describe a method to automatically detect which parts of a Web KOS are likely to change in a next version, using supervised learning on past versions in the KOS version chain. We use a set of ontology change features to model and predict change in arbitrary Web KOS. We apply our method on 139 varied datasets systematically retrieved from the Semantic Web, obtaining robust results at correctly predicting change. To illustrate the accuracy, genericity and domain independence of the method, we study the relationship between its effectiveness and several characterizations of the evaluated datasets, finding that predictors like the number of versions in a chain and their release frequency have a fundamental impact in predictability of change in Web KOS. Consequently, we argue for adopting a release early, release often philosophy in Web KOS development cycles., Comment: 16 pages, 6 figures, ISWC 2015 conference pre-print The paper has been withdrawn due to significant overlap with a subsequent paper submitted to a conference for review

Published
2015

13. Knowledge Maps and Information Retrieval (KMIR)

Author

Mutschke, Peter, Scharnhorst, Andrea, Guéret, Christophe, Mayr, Philipp, Hansen, Preben, and Slavic, Aida

Subjects
Computer Science - Information Retrieval, Computer Science - Digital Libraries, Computer Science - Human-Computer Interaction
Abstract

Information systems usually show as a particular point of failure the vagueness between user search terms and the knowledge orders of the information space in question. Some kind of guided searching therefore becomes more and more important in order to precisely discover information without knowing the right search terms. Knowledge maps of digital library collections are promising navigation tools through knowledge spaces but still far away from being applicable for searching digital libraries. However, there is no continuous knowledge exchange between the "map makers" on the one hand and the Information Retrieval (IR) specialists on the other hand. Thus, there is also a lack of models that properly combine insights of the two strands. The proposed workshop aims at bringing together these two communities: experts in IR reflecting on visual enhanced search interfaces and experts in knowledge mapping reflecting on visualizations of the content of a collection that might also present a context for a search term in a visual manner. The intention of the workshop is to raise awareness of the potential of interactive knowledge maps for information seeking purposes and to create a common ground for experiments aiming at the incorporation of knowledge maps into IR models at the level of the user interface., Comment: 6 pages, accepted workshop proposal for Digital Libraries 2014

Published
2014

14. Automated 3D bio-imaging analysis of nuclear organization by NucleusJ 2.0

Author

Tristan Dubos, Axel Poulet, Céline Gonthier-Gueret, Guillaume Mougeot, Emmanuel Vanrobays, Yanru Li, Sylvie Tutois, Emilie Pery, Frédéric Chausse, Aline V. Probst, Christophe Tatout, and Sophie Desset

Subjects
three-dimensional microscopy imaging, image analysis, plant nucleus, nuclear organization, 3d dna fish, Genetics, QH426-470, Cytology, QH573-671
Abstract

NucleusJ 1.0, an ImageJ plugin, is a useful tool to analyze nuclear morphology and chromatin organization in plant and animal cells. NucleusJ 2.0 is a new release of NucleusJ, in which image processing is achieved more quickly using a command-lineuser interface. Starting with large collection of 3D nuclei, segmentation can be performed by the previously developed Otsu-modified method or by a new 3D gift-wrapping method, taking better account of nuclear indentations and unstained nucleoli. These two complementary methods are compared for their accuracy by using three types of datasets available to the community at https://www.brookes.ac.uk/indepth/images/. Finally, NucleusJ 2.0 was evaluated using original plant genetic material by assessing its efficiency on nuclei stained with DNA dyes or after 3D-DNA Fluorescence in situ hybridization. With these improvements, NucleusJ 2.0 permits the generation of large user-curated datasets that will be useful for software benchmarking or to train convolution neural networks.

Published
2020
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15. The NADPH oxidase NOX2 is a marker of adverse prognosis involved in chemoresistance of acute myeloid leukemias

Author

Rosa Paolillo, Mathias Boulanger, Pierre Gâtel, Ludovic Gabellier, Marion De Toledo, Denis Tempé, Rawan Hallal, Dana Akl, Jérôme Moreaux, Hayeon Baik, Elise Gueret, Christian Recher, Jean-Emmanuel Sarry, Guillaume Cartron, Marc Piechaczyk, and Guillaume Bossis

Subjects
Diseases of the blood and blood-forming organs, RC633-647.5
Abstract

Resistance to chemotherapeutic drugs is a major cause of treatment failure in acute myeloid leukemias (AML). To better characterize the mechanisms of chemoresistance, we first identified genes whose expression is dysregulated in AML cells resistant to daunorubicin or cytarabine, the main drugs used for induction therapy. The genes found to be activated are mostly linked to immune signaling and inflammation. Among them, we identified a strong upregulation of the NOX2 NAPDH oxidase subunit genes (CYBB, CYBA, NCF1, NCF2, NCF4 and RAC2). The ensuing increase in NADPH oxidase expression and production of reactive oxygen species, which is particularly strong in daunorubicin-resistant cells, participates in the acquisition and/or maintenance of resistance to daunorubicin. Gp91phox (CYBB-encoded Nox2 catalytic subunit), was found to be more expressed and active in leukemic cells from patients with the French-American-British (FAB) M4/M5 subtypes of AML than in those from patients with the FAB M0-M2 ones. Moreover, its expression was increased at the surface of patients’ chemotherapy-resistant AML cells. Finally, using a gene expression based score we demonstrated that high expression of NOX2 subunit genes is a marker of adverse prognosis in AML patients. The prognostic NOX score we defined is independent of the cytogenetic-based risk classification, FAB subtype, FLT3/NPM1 mutational status and age.

Published
2022
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16. Design of a high power solid target for 211At

Author

Brunet Guillaume, Michel Matthieu, De France Gilles, Desmezières Vincent, Jacquot Bertrand, Hocini Clément, Ferey Sébastien, Gueret Jérôme, Rossard Laurent, Morisset Martial, Fremont Georges, Lecerf Sabrina, André Thierry, Michel Clément, Gangnant Patrice, Foy Jean-Claude, Levallois Romuald, Barthe-Dejean Cécile, and Collard Matthieu

Subjects
Physics, QC1-999
Abstract

The new SPIRAL2 LINAC at GANIL delivers light beams (p, d, alpha,…) with very large intensities. In order to exploit these beams in an optimal way, high power target stations are requested. In this contribution, we present such an irradiation station designed to optimize the production of 211At, an alpha emitter of interest for targeted alpha therapy. In order to dissipate at least 10 kW of beam power, a rotating, water-cooled system comprising twelve individual targets has been developed together with a fast and safe extraction mechanism.

Published
2023
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17. The Entity Registry System: Implementing 5-Star Linked Data Without the Web

Author

Charlaganov, Marat, Cudré-Mauroux, Philippe, Dinu, Cristian, Guéret, Christophe, Grund, Martin, and Macicas, Teodor

Subjects
Computer Science - Databases, Computer Science - Computers and Society
Abstract

Linked Data applications often assume that connectivity to data repositories and entity resolution services are always available. This may not be a valid assumption in many cases. Indeed, there are about 4.5 billion people in the world who have no or limited Web access. Many data-driven applications may have a critical impact on the life of those people, but are inaccessible to those populations due to the architecture of today's data registries. In this paper, we propose and evaluate a new open-source system that can be used as a general-purpose entity registry suitable for deployment in poorly-connected or ad-hoc environments., Comment: 16 pages, authors are listed in alphabetical order

Published
2013

18. Genericity versus expressivity - an exercise in semantic interoperable research information systems for Web Science

Author

Guéret, Christophe, Chambers, Tamy, Reijnhoudt, Linda, van der Most, Frank, and Scharnhorst, Andrea

Subjects
Computer Science - Digital Libraries
Abstract

The web does not only enable new forms of science, it also creates new possibilities to study science and new digital scholarship. This paper brings together multiple perspectives: from individual researchers seeking the best options to display their activities and market their skills on the academic job market; to academic institutions, national funding agencies, and countries needing to monitor the science system and account for public money spending. We also address the research interests aimed at better understanding the self-organising and complex nature of the science system through researcher tracing, the identification of the emergence of new fields, and knowledge discovery using large-data mining and non-linear dynamics. In particular this paper draws attention to the need for standardisation and data interoperability in the area of research information as an indispensable pre-condition for any science modelling. We discuss which levels of complexity are needed to provide a globally, interoperable, and expressive data infrastructure for research information. With possible dynamic science model applications in mind, we introduce the need for a "middle-range" level of complexity for data representation and propose a conceptual model for research data based on a core international ontology with national and local extensions., Comment: Long version of a paper submitted to the WebScience 2013

Published
2013

21. Concurrent BMP Signaling Maintenance and TGF-β Signaling Inhibition Is a Hallmark of Natural Resistance to Muscle Atrophy in the Hibernating Bear

Author

Laura Cussonneau, Christian Boyer, Charlotte Brun, Christiane Deval, Emmanuelle Loizon, Emmanuelle Meugnier, Elise Gueret, Emeric Dubois, Daniel Taillandier, Cécile Polge, Daniel Béchet, Guillemette Gauquelin-Koch, Alina L. Evans, Jon M. Arnemo, Jon E. Swenson, Stéphane Blanc, Chantal Simon, Etienne Lefai, Fabrice Bertile, and Lydie Combaret

Subjects
brown bear hibernation, mouse unloading, muscle atrophy, physical inactivity, RNA sequencing, TGF-β/BMP signaling, Cytology, QH573-671
Abstract

Muscle atrophy arises from a multiplicity of physio-pathological situations and has very detrimental consequences for the whole body. Although knowledge of muscle atrophy mechanisms keeps growing, there is still no proven treatment to date. This study aimed at identifying new drivers for muscle atrophy resistance. We selected an innovative approach that compares muscle transcriptome between an original model of natural resistance to muscle atrophy, the hibernating brown bear, and a classical model of induced atrophy, the unloaded mouse. Using RNA sequencing, we identified 4415 differentially expressed genes, including 1746 up- and 2369 down-regulated genes, in bear muscles between the active versus hibernating period. We focused on the Transforming Growth Factor (TGF)-β and the Bone Morphogenetic Protein (BMP) pathways, respectively, involved in muscle mass loss and maintenance. TGF-β- and BMP-related genes were overall down- and up-regulated in the non-atrophied muscles of the hibernating bear, respectively, and the opposite occurred for the atrophied muscles of the unloaded mouse. This was further substantiated at the protein level. Our data suggest TGF-β/BMP balance is crucial for muscle mass maintenance during long-term physical inactivity in the hibernating bear. Thus, concurrent activation of the BMP pathway may potentiate TGF-β inhibiting therapies already targeted to prevent muscle atrophy.

Published
2021
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23. Applicability and accuracy of pretest probability calculations implemented in the NICE clinical guideline for decision making about imaging in patients with chest pain of recent onset

Author

Roehle, Robert, Wieske, Viktoria, Schuetz, Georg M., Gueret, Pascal, Andreini, Daniele, Meijboom, Willem Bob, Pontone, Gianluca, Garcia, Mario, Alkadhi, Hatem, Honoris, Lily, Hausleiter, Jörg, Bettencourt, Nuno, Zimmermann, Elke, Leschka, Sebastian, Gerber, Bernhard, Rochitte, Carlos, Schoepf, U. Joseph, Shabestari, Abbas Arjmand, Nørgaard, Bjarne, Sato, Akira, Knuuti, Juhani, Meijs, Matthijs F. L., Brodoefel, Harald, Jenkins, Shona M. M., Øvrehus, Kristian Altern, Diederichsen, Axel Cosmus Pyndt, Hamdan, Ashraf, Halvorsen, Bjørn Arild, Mendoza Rodriguez, Vladimir, Wan, Yung Liang, Rixe, Johannes, Sheikh, Mehraj, Langer, Christoph, Ghostine, Said, Martuscelli, Eugenio, Niinuma, Hiroyuki, Scholte, Arthur, Nikolaou, Konstantin, Ulimoen, Geir, Zhang, Zhaoqi, Mickley, Hans, Nieman, Koen, Kaufmann, Philipp A., Buechel, Ronny Ralf, Herzog, Bernhard A., Clouse, Melvin, Halon, David A., Leipsic, Jonathan, Bush, David, Jakamy, Reda, Sun, Kai, Yang, Lin, Johnson, Thorsten, Laissy, Jean-Pierre, Marcus, Roy, Muraglia, Simone, Tardif, Jean-Claude, Chow, Benjamin, Paul, Narinder, Maintz, David, Hoe, John, de Roos, Albert, Haase, Robert, Laule, Michael, Schlattmann, Peter, and Dewey, Marc

Published
2018
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24. Acute kidney injury after aneurysmal subarachnoid hemorrhage: is chloride really responsible?

Author

Gildas Gueret, Pierre Lefebvre, Pascale Le Maguet, and Renaud Fabre

Subjects
Chloride, Acute kidney injury, Subarachnoid hemorrhage, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Sadan et al. find an association between acute kidney injury and high chloride containing a hypertonic solution. Recent large prospective non-randomized studies bring conflicting results on the relationship between chloride and acute kidney injury. We discuss Sadan et al.’s results according to the recent literature.

Published
2020
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25. Optimizing Chitin Depolymerization by Lysozyme to Long-Chain Oligosaccharides

Author

Arnaud Masselin, Antoine Rousseau, Stéphanie Pradeau, Laure Fort, Rodolphe Gueret, Laurine Buon, Sylvie Armand, Sylvain Cottaz, Luc Choisnard, and Sébastien Fort

Subjects
chitin oligosaccharides, chemo-enzymatic synthesis, lysozyme, response surface methodology, Biology (General), QH301-705.5
Abstract

Chitin oligosaccharides (COs) hold high promise as organic fertilizers in the ongoing agro-ecological transition. Short- and long-chain COs can contribute to the establishment of symbiotic associations between plants and microorganisms, facilitating the uptake of soil nutrients by host plants. Long-chain COs trigger plant innate immunity. A fine investigation of these different signaling pathways requires improving the access to high-purity COs. Here, we used the response surface methodology to optimize the production of COs by enzymatic hydrolysis of water-soluble chitin (WSC) with hen egg-white lysozyme. The influence of WSC concentration, its acetylation degree, and the reaction time course were modelled using a Box–Behnken design. Under optimized conditions, water-soluble COs up to the nonasaccharide were formed in 51% yield and purified to homogeneity. This straightforward approach opens new avenues to determine the complex roles of COs in plants.

Published
2021
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28. 2015 ESC GUIDELINES FOR THE DIAGNOSIS AND MANAGEMENT OF PERICARDIAL DISEASES

Author

Yehuda Adler, Philippe Charron, Massimo Imazio, Luigi Badano, Gonzalo Barón-Esquivias, Jan Bogaert, Antonio Brucato, Pascal Gueret, Karin Klingel, Christos Lionis, Bernhard Maisch, Bongani Mayosi, Alain Pavie, Arsen D. Ristić, Manel Sabaté Tenas, Petar Seferovic, Karl Swedberg, Witold Tomkowski, E. O. Taratuchin, and G. P. Arutjunov

Subjects
guidelines, aetiology, constrictive pericarditis, diagnosis, myopericarditis, pericardial effusion, pericardiocentesis, pericarditis, pericardium, prognosis, tamponade, therapy, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

The Task Force for the Management of Infective Endocarditis of the European Society of Cardiology (ESC)Endorsed by: European Association for Cardio-Thoracic Surgery (EACTS)

Published
2016
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29. Correction to: Applicability and accuracy of pretest probability calculations implemented in the NICE clinical guideline for decision making about imaging in patients with chest pain of recent onset

Author

Roehle, Robert, Wieske, Viktoria, Schuetz, Georg M., Gueret, Pascal, Andreini, Daniele, Meijboom, Willem Bob, Pontone, Gianluca, Garcia, Mario, Alkadhi, Hatem, Honoris, Lily, Hausleiter, Jörg, Bettencourt, Nuno, Zimmermann, Elke, Leschka, Sebastian, Gerber, Bernhard, Rochitte, Carlos, Schoepf, U. Joseph, Shabestari, Abbas Arjmand, Nørgaard, Bjarne, Sato, Akira, Knuuti, Juhani, Meijs, Matthijs F. L., Brodoefel, Harald, Jenkins, Shona M. M., Øvrehus, Kristian Altern, Diederichsen, Axel Cosmus Pyndt, Hamdan, Ashraf, Halvorsen, Bjørn Arild, Rodriguez, Vladimir Mendoza, Wan, Yung Liang, Rixe, Johannes, Sheikh, Mehraj, Langer, Christoph, Ghostine, Said, Martuscelli, Eugenio, Niinuma, Hiroyuki, Scholte, Arthur, Nikolaou, Konstantin, Ulimoen, Geir, Zhang, Zhaoqi, Mickley, Hans, Nieman, Koen, Kaufmann, Philipp A., Buechel, Ronny Ralf, Herzog, Bernhard A., Clouse, Melvin, Halon, David A., Leipsic, Jonathan, Bush, David, Jakamy, Reda, Sun, Kai, Yang, Lin, Johnson, Thorsten, Laissy, Jean-Pierre, Marcus, Roy, Muraglia, Simone, Tardif, Jean-Claude, Chow, Benjamin, Paul, Narinder, Maintz, David, Hoe, John, de Roos, Albert, Haase, Robert, Laule, Michael, Schlattmann, Peter, and Dewey, Marc

Published
2018
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30. Correction to: Potentially modifiable factors contributing to outcome from acute respiratory distress syndrome: the LUNG SAFE study

Author

Laffey, John G., Bellani, Giacomo, Pham, Tài, Fan, Eddy, Madotto, Fabiana, Bajwa, Ednan K., Brochard, Laurent, Clarkson, Kevin, Esteban, Andres, Gattinoni, Luciano, van Haren, Frank, Heunks, Leo M., Kurahashi, Kiyoyasu, Laake, Jon Henrik, Larsson, Anders, McAuley, Daniel F., McNamee, Lia, Nin, Nicolas, Qiu, Haibo, Ranieri, Marco, Rubenfeld, Gordon D., Thompson, B. Taylor, Wrigge, Hermann, Slutsky, Arthur S., Pesenti, Antonio, Francois, Guy M., Rabboni, Francesca, Conti, Sara, Theresa, Uhc Mother, Sula, Hektor, Nunci, Lordian, Cani, Alma, Zazu, Alan, Dellera, Christian, Insaurralde, Carolina S., Alejandro, Risso V., Daldin, Julio, Vinzio, Mauricio, Fernandez, Ruben O., Cardonnet, Luis P., Bettini, Lisandro R., Bisso, Mariano Carboni, Osman, Emilio M., Setten, Mariano G., Lovazzano, Pablo, Alvarez, Javier, Villar, Veronica, Pozo, Norberto C., Grubissich, Nicolas, Plotnikow, Gustavo A., Vasquez, Daniela N., Ilutovich, Santiago, Tiribelli, Norberto, Chena, Ariel, Pellegrini, Carlos A., Saenz, María G., Estenssoro, Elisa, Brizuela, Matias, Gianinetto, Hernan, Gomez, Pablo E., Cerrato, Valeria I., Bezzi, Marco G., Borello, Silvina A., Loiacono, Flavia A., Fernandez, Adriana M., Knowles, Serena, Reynolds, Claire, Inskip, Deborah M., Miller, Jennene J., Kong, Jing, Whitehead, Christina, Bihari, Shailesh, Seven, Aylin, Krstevski, Amanda, Rodgers, Helen J., Millar, Rebecca T., Mckenna, Toni E., Bailey, Irene M., Hanlon, Gabrielle C., Aneman, Anders, Lynch, Joan M., Azad, Raman, Neal, John, Woods, Paul W., Roberts, Brigit L., Kol, Mark R., Wong, Helen S., Riss, Katharina C., Staudinger, Thomas, Wittebole, Xavier, Berghe, Caroline, Bulpa, Pierre A., Dive, Alain M., Verstraete, Rik, Lebbinck, Herve, Depuydt, Pieter, Vermassen, Joris, Meersseman, Philippe, Ceunen, Helga, Rosa, Jonas I., Beraldo, Daniel O., Piras, Claudio, Rampinelli, Adenilton M., Nassar, Jr., Antonio P., Mataloun, Sergio, Moock, Marcelo, Thompson, Marlus M., Gonçalves, Claudio H., Antônio, Ana Carolina P., Ascoli, Aline, Biondi, Rodrigo S., Fontenele, Danielle C., Nobrega, Danielle, Sales, Vanessa M., Shindhe, Suresh, Aiman, Maizatul, Ismail, B. Pg Hj, Beloncle, Francois, Davies, Kyle G., Cirone, Rob, Manoharan, Venika, Ismail, Mehvish, Goligher, Ewan C., Jassal, Mandeep, Nishikawa, Erin, Javeed, Areej, Curley, Gerard, Rittayamai, Nuttapol, Parotto, Matteo, Ferguson, Niall D., Mehta, Sangeeta, Knoll, Jenny, Pronovost, Antoine, Canestrini, Sergio, Bruhn, Alejandro R., Garcia, Patricio H., Aliaga, Felipe A., Farías, Pamela A., Yumha, Jacob S., Ortiz, Claudia A., Salas, Javier E., Saez, Alejandro A., Vega, Luis D., Labarca, Eduardo F., Martinez, Felipe T., Carreño, Nicolás G., Lora, Pilar, Liu, Haitao, Liu, Ling, Tang, Rui, Luo, Xiaoming, An, Youzhong, Zhao, Huiying, Gao, Yan, Zhai, Zhe, Ye, Zheng L., Wang, Wei, Li, Wenwen, Li, Qingdong, Zheng, Ruiqiang, Yu, Wenkui, Shen, Juanhong, Li, Xinyu, Yu, Tao, Lu, Weihua, Wu, Ya Q., Huang, Xiao B., He, Zhenyang, Lu, Yuanhua, Han, Hui, Zhang, Fan, Sun, Renhua, Wang, Hua X., Qin, Shu H., Zhu, Bao H., Zhao, Jun, Liu, Jian, Li, Bin, Liu, Jing L., Zhou, Fa C., Li, Qiong J., Zhang, Xing Y., Li-Xin, Zhou, Xin-Hua, Qiang, Jiang, Liangyan, Gao, Yuan N., Zhao, Xian Y., Li, Yuan Y., Li, Xiao L., Wang, Chunting, Yao, Qingchun, Yu, Rongguo, Chen, Kai, Shao, Huanzhang, Qin, Bingyu, Huang, Qing Q., Zhu, Wei H., Hang, Ai Y., Hua, Ma X., Li, Yimin, Xu, Yonghao, Di, Yu D., Ling, Long L., Qin, Tie H., Wang, Shou H., Qin, Junping, Han, Yi, Zhou, Suming, Vargas, Monica P., Silesky Jimenez, Juan I., González Rojas, Manuel A., Solis-Quesada, Jaime E., Ramirez-Alfaro, Christian M., Máca, Jan, Sklienka, Peter, Gjedsted, Jakob, Christiansen, Aage, Nielsen, Jonas, Villamagua, Boris G., Llano, Miguel, Burtin, Philippe, Buzancais, Gautier, Beuret, Pascal, Pelletier, Nicolas, Mortaza, Satar, Mercat, Alain, Chelly, Jonathan, Jochmans, Sébastien, Terzi, Nicolas, Daubin, Cédric, Carteaux, Guillaume, de Prost, Nicolas, Chiche, Jean-Daniel, Daviaud, Fabrice, Fartoukh, Muriel, Barberet, Guillaume, Biehler, Jerome, Dellamonica, Jean, Doyen, Denis, Arnal, Jean-Michel, Briquet, Anais, Hraiech, Sami, Papazian, Laurent, Follin, Arnaud, Roux, Damien, Messika, Jonathan, Kalaitzis, Evangelos, Dangers, Laurence, Combes, Alain, Au, Siu-Ming, Béduneau, Gaetan, Carpentier, Dorothée, Zogheib, Elie H., Dupont, Herve, Ricome, Sylvie, Santoli, Francesco L., Besset, Sebastien L., Michel, Philippe, Gelée, Bruno, Danin, Pierre-Eric, Goubaux, Bernard, Crova, Philippe J., Phan, Nga T., Berkelmans, Frantz, Badie, Julio C., Tapponnier, Romain, Gally, Josette, Khebbeb, Samy, Herbrecht, Jean-Etienne, Schneider, Francis, Declercq, Pierre-Louis M., Rigaud, Jean-Philippe, Duranteau, Jacques, Harrois, Anatole, Chabanne, Russell, Marin, Julien, Bigot, Charlene, Thibault, Sandrine, Ghazi, Mohammed, Boukhazna, Messabi, Zein, Salem Ould, Richecoeur, Jack R., Combaux, Daniele M., Grelon, Fabien, Le Moal, Charlene, Sauvadet, Elise P., Robine, Adrien, Lemiale, Virginie, Reuter, Danielle, Dres, Martin, Demoule, Alexandre, Goldgran-Toledano, Dany, Baboi, Loredana, Guérin, Claude, Lohner, Ralph, Kraßler, Jens, Schäfer, Susanne, Zacharowski, Kai D., Meybohm, Patrick, Reske, Andreas W., Simon, Philipp, Hopf, Hans-Bernd F., Schuetz, Michael, Baltus, Thomas, Papanikolaou, Metaxia N., Papavasilopoulou, Theonymfi G., Zacharas, Giannis A., Ourailogloy, Vasilis, Mouloudi, Eleni K., Massa, Eleni V., Nagy, Eva O., Stamou, Electra E., Kiourtzieva, Ellada V., Oikonomou, Marina A., Avila, Luis E., Cortez, Cesar A., Citalán, Johanna E., Jog, Sameer A., Sable, Safal D., Shah, Bhagyesh, Gurjar, Mohan, Baronia, Arvind K., Memon, Mohammedfaruk, Muthuchellappan, Radhakrishnan, Ramesh, Venkatapura J., Shenoy, Anitha, Unnikrishnan, Ramesh, Dixit, Subhal B., Rhayakar, Rachana V., Ramakrishnan, Nagarajan, Bhardwaj, Vallish K., Mahto, Heera L., Sagar, Sudha V., Palaniswamy, Vijayanand, Ganesan, Deeban, Hashemian, Seyed Mohammadreza, Jamaati, Hamidreza, Heidari, Farshad, Meaney, Edel A., Nichol, Alistair, Knapman, Karl M., O’Croinin, Donall, Dunne, Eimhin S., Breen, Dorothy M., Clarkson, Kevin P., Jaafar, Rola F., Dwyer, Rory, Amir, Fahd, Ajetunmobi, Olaitan O., O’Muircheartaigh, Aogan C., Black, Colin S., Treanor, Nuala, Collins, Daniel V., Altaf, Wahid, Zani, Gianluca, Fusari, Maurizio, Spadaro, Savino, Volta, Carlo A., Graziani, Romano, Brunettini, Barbara, Palmese, Salvatore, Formenti, Paolo, Umbrello, Michele, Lombardo, Andrea, Pecci, Elisabetta, Botteri, Marco, Savioli, Monica, Protti, Alessandro, Mattei, Alessia, Schiavoni, Lorenzo, Tinnirello, Andrea, Todeschini, Manuel, Giarratano, Antonino, Cortegiani, Andrea, Sher, Sara, Rossi, Anna, Antonelli, Massimo M., Montini, Luca M., Casalena, Paolo, Scafetti, Sergio, Panarello, Giovanna, Occhipinti, Giovanna, Patroniti, Nicolò, Pozzi, Matteo, Biscione, Roberto R., Poli, Michela M., Raimondi, Ferdinando, Albiero, Daniela, Crapelli, Giulia, Beck, Eduardo, Pota, Vincenzo, Schiavone, Vincenzo, Molin, Alexandre, Tarantino, Fabio, Monti, Giacomo, Frati, Elena, Mirabella, Lucia, Cinnella, Gilda, Fossali, Tommaso, Colombo, Riccardo, Pattarino, Pierpaolo Terragni Ilaria, Mojoli, Francesco, Braschi, Antonio, Borotto, Erika E., Cracchiolo, Andrea N., Palma, Daniela M., Raponi, Francesco, Foti, Giuseppe, Vascotto, Ettore R., Coppadoro, Andrea, Brazzi, Luca, Floris, Leda, Iotti, Giorgio A., Venti, Aaron, Yamaguchi, Osamu, Takagi, Shunsuke, Maeyama, Hiroki N., Watanabe, Eizo, Yamaji, Yoshihiro, Shimizu, Kazuyoshi, Shiozaki, Kyoko, Futami, Satoru, Ryosuke, Sekine, Saito, Koji, Kameyama, Yoshinobu, Ueno, Keiko, Izawa, Masayo, Okuda, Nao, Suzuki, Hiroyuki, Harasawa, Tomofumi, Nasu, Michitaka, Takada, Tadaaki, Ito, Fumihito, Nunomiya, Shin, Koyama, Kansuke, Abe, Toshikazu, Andoh, Kohkichi, Kusumoto, Kohei, Hirata, Akira, Takaba, Akihiro, Kimura, Hiroyasu, Matsumoto, Shuhei, Higashijima, Ushio, Honda, Hiroyuki, Aoki, Nobumasa, Imai, Hiroshi, Ogino, Yasuaki, Mizuguchi, Ichiko, Ichikado, Kazuya, Nitta, Kenichi, Mochizuki, Katsunori, Hashida, Tomoaki, Tanaka, Hiroyuki, Nakamura, Tomoyuki, Niimi, Daisuke, Ueda, Takeshi, Kashiwa, Yozo, Uchiyama, Akinori, Sabelnikovs, Olegs, Oss, Peteris, Haddad, Youssef, Liew, Kong Y., Ñamendys-Silva, Silvio A., Jarquin-Badiola, Yves D., Sanchez-Hurtado, Luis A., Gomez-Flores, Saira S., Marin, Maria C., Villagomez, Asisclo J., Lemus, Jordana S., Fierro, Jonathan M., Cervantes, Mavy Ramirez, Mejia, Francisco Javier Flores, Dector, Dulce, Dector, Dulce M., Gonzalez, Daniel R., Estrella, Claudia R., Sanchez-Medina, Jorge R., Ramirez-Gutierrez, Alvaro, George, Fernando G., Aguirre, Janet S., Buensuseso, Juan A., Poblano, Manuel, Dendane, Tarek, Zeggwagh, Amine Ali, Balkhi, Hicham, Elkhayari, Mina, Samkaoui, Nacer, Ezzouine, Hanane, Benslama, Abdellatif, Amor, Mourad, Maazouzi, Wajdi, Cimic, Nedim, Beck, Oliver, Bruns, Monique M., Schouten, Jeroen A., Rinia, Myra, Raaijmakers, Monique, Van Wezel, Hellen M., Heines, Serge J., Strauch, Ulrich, Buise, Marc P., Simonis, Fabienne D., Schultz, Marcus J., Goodson, Jennifer C., Browne, Troy S., Navarra, Leanlove, Hunt, Anna, Hutchison, Robyn A., Bailey, Mathew B., Newby, Lynette, Mcarthur, Colin, Kalkoff, Michael, Mcleod, Alex, Casement, Jonathan, Hacking, Danielle J., Andersen, Finn H., Dolva, Merete S., Barratt-Due, Andreas, Noremark, Kim Andre L., Søreide, Eldar, Sjøbø, Brit Å., Guttormsen, Anne B., Leon Yoshido, Hector H., Aguilar, Ronald Zumaran, Montes Oscanoa, Fredy A., Alisasis, Alain U., Robles, Joanne B., Pasanting-Lim, Rossini Abbie B., Tan, Beatriz C., Andruszkiewicz, Pawel, Jakubowska, Karina, Coxo, Cristina M., Alvarez, António M., Oliveira, Bruno S., Montanha, Gustavo M., Barros, Nelson C., Pereira, Carlos S., Messias, António M., Monteiro, Jorge M., Araujo, Ana M., Catorze, Nuno T., Marum, Susan M., Bouw, Maria J., Gomes, Rui M., Brito, Vania A., Castro, Silvia, Estilita, Joana M., Barros, Filipa M., Serra, Isabel M., Martinho, Aurelia M., Tomescu, Dana R., Marcu, Alexandra, Bedreag, Ovidiu H., Papurica, Marius, Corneci, Dan E., Negoita, Silvius Ioan, Grigoriev, Evgeny, Gritsan, Alexey I., Gazenkampf, Andrey A., Almekhlafi, Ghaleb, Albarrak, Mohamad M., Mustafa, Ghanem M., Maghrabi, Khalid A., Salahuddin, Nawal, Aisa, Tharwat M., Al Jabbary, Ahmed S., Tabhan, Edgardo, Arabi, Yaseen M., Arabi, Yaseen M., Trinidad, Olivia A., Al Dorzi, Hasan M., Tabhan, Edgardo E., Bolon, Stefan, Smith, Oliver, Mancebo, Jordi, Aguirre-Bermeo, Hernan, Lopez-Delgado, Juan C., Esteve, Francisco, Rialp, Gemma, Forteza, Catalina, De Haro, Candelaria, Artigas, Antonio, Albaiceta, Guillermo M., De Cima-Iglesias, Sara, Seoane-Quiroga, Leticia, Ceniceros-Barros, Alexandra, Ruiz-Aguilar, Antonio L., Claraco-Vega, Luis M., Soler, Juan Alfonso, del Carmen Lorente, Maria, Hermosa, Cecilia, Gordo, Federico, Prieto-González, Miryam, López-Messa, Juan B., Perez, Manuel P., Perez, Cesar P., Allue, Raquel Montoiro, Roche-Campo, Ferran, Ibañez-Santacruz, Marcos, Temprano, Susana, Pintado, Maria C., De Pablo, Raul, Gómez, Pilar Ricart Aroa, Ruiz, Silvia Rodriguez, Moles, Silvia Iglesias, Jurado, Mª Teresa, Arizmendi, Alfons, Piacentini, Enrique A., Franco, Nieves, Honrubia, Teresa, Cheng, Meisy Perez, Losada, Elena Perez, Blanco, Javier, Yuste, Luis J., Carbayo-Gorriz, Cecilia, Cazorla-Barranquero, Francisca G., Alonso, Javier G., Alda, Rosa S., Algaba, Ángela, Navarro, Gonzalo, Cereijo, Enrique, Diaz-Rodriguez, Esther, Marcos, Diego Pastor, Montero, Laura Alvarez, Para, Luis Herrera, Sanchez, Roberto Jimenez, Navalpotro, Miguel Angel Blasco, Abad, Ricardo Diaz, González, Raquel Montiel, Toribio, Dácil Parrilla, Castro, Alejandro G., Artiga, Maria Jose D., Penuelas, Oscar, Roser, Tomas P., Olga, Moreno F., Curto, Elena Gallego, Sánchez, Rocío Manzano, Imma, Vallverdu P., Elisabet, Garcia M., Claverias, Laura, Magret, Monica, Pellicer, Ana M., Rodriguez, Lucia L., Sánchez-Ballesteros, Jesús, González-Salamanca, Ángela, Jimenez, Antonio G., Huerta, Francisco P., Sotillo Diaz, Juan Carlos J., Lopez, Esther Bermejo, Llinares Moya, David D., Tallet Alfonso, Alec A., Luis, Palazon Sanchez Eugenio, Cesar, Palazon Sanchez, Rafael, Sánchez I., Virgilio, Corcoles G., Recio, Noelia N., Adamsson, Richard O., Rylander, Christian C., Holzgraefe, Bernhard, Broman, Lars M., Wessbergh, Joanna, Persson, Linnea, Schiöler, Fredrik, Kedelv, Hans, Tibblin, Anna Oscarsson, Appelberg, Henrik, Hedlund, Lars, Helleberg, Johan, Eriksson, Karin E., Glietsch, Rita, Larsson, Niklas, Nygren, Ingela, Nunes, Silvia L., Morin, Anna-Karin, Kander, Thomas, Adolfsson, Anne, Piquilloud, Lise, Zender, Hervé O., Leemann-Refondini, Corinne, Elatrous, Souheil, Bouchoucha, Slaheddine, Chouchene, Imed, Ouanes, Islem, Souissi, Asma Ben, Kamoun, Salma, Demirkiran, Oktay, Aker, Mustafa, Erbabacan, Emre, Ceylan, Ilkay, Girgin, Nermin Kelebek, Ozcelik, Menekse, Ünal, Necmettin, Meco, Basak Ceyda, Akyol, Onat O., Derman, Suleyman S., Kennedy, Barry, Parhar, Ken, Srinivasa, Latha, McAuley, Danny, Hopkins, Phil, Mellis, Clare, Kakar, Vivek, Hadfield, Dan, Vercueil, Andre, Bhowmick, Kaushik, Humphreys, Sally K., Ferguson, Andrew, Mckee, Raymond, Raj, Ashok S., Fawkes, Danielle A., Watt, Philip, Twohey, Linda, JhaMatthew Thomas, Rajeev R., Morton, Alex, Kadaba, Varsha, Smith, Mark J., Hormis, Anil P., Kannan, Santhana G., Namih, Miriam, Reschreiter, Henrik, Camsooksai, Julie, Kumar, Alek, Rugonfalvi, Szabolcs, Nutt, Christopher, Oneill, Orla, Seasman, Colette, Dempsey, Ged, Scott, Christopher J., Ellis, Helen E., Mckechnie, Stuart, Hutton, Paula J., Di Tomasso, Nora N., Vitale, Michela N., Griffin, Ruth O., Dean, Michael N., Cranshaw, Julius H., Willett, Emma L., Ioannou, Nicholas, Service, Gstt Severe Respiratory Failure, Gillis, Sarah, Csabi, Peter, Macfadyen, Rosaleen, Dawson, Heidi, Preez, Pieter D., Williams, Alexandra J., Boyd, Owen, De Gordoa, Laura Ortiz-Ruiz, Bramall, Jon, Symmonds, Sophie, Chau, Simon K., Wenham, Tim, Szakmany, Tamas, Toth-Tarsoly, Piroska, Mccalman, Katie H., Alexander, Peter, Stephenson, Lorraine, Collyer, Thomas, Chapman, Rhiannon, Cooper, Raphael, Allan, Russell M., Sim, Malcolm, Wrathall, David W., Irvine, Donald A., Zantua, Kim S., Adams, John C., Burtenshaw, Andrew J., Sellors, Gareth P., Welters, Ingeborg D., Williams, Karen E., Hessell, Robert J., Oldroyd, Matthew G., Battle, Ceri E., Pillai, Suresh, Kajtor, Istvan, Sivashanmugavel, Mageswaran, Okane, Sinead C., Donnelly, Adrian, Frigyik, Aniko D., Careless, Jon P., May, Martin M., Stewart, Richard, John Trinder, T., Hagan, Samantha J., Wise, Matt P., Cole, Jade M., MacFie, Caroline C., Dowling, Anna T., Hurtado, Javier, Hurtado, Javier, Nuñez, Edgardo, Pittini, Gustavo, Rodriguez, Ruben, Imperio, María C., Santos, Cristina, França, Ana G., Ebeid, Alejandro, Deicas, Alberto, Serra, Carolina, Uppalapati, Aditya, Kamel, Ghassan, Banner-Goodspeed, Valerie M., Beitler, Jeremy R., Mukkera, Satyanarayana Reddy, Kulkarni, Shreedhar, Lee, Jarone, Mesar, Tomaz, Shinn Iii, John O., Gomaa, Dina, Tainter, Christopher, Lee, Jarone, Mesar, Tomaz, Lee, Jarone, Yeatts, Dale J., Warren, Jessica, Lanspa, Michael J., Miller, Russel R., Grissom, Colin K., Brown, Samuel M., Bauer, Philippe R., Gosselin, Ryan J., Kitch, Barrett T., Cohen, Jason E., Beegle, Scott H., Gueret, Renaud M., Tulaimat, Aiman, Choudry, Shazia, Stigler, William, Batra, Hitesh, Huff, Nidhi G., Lamb, Keith D., Oetting, Trevor W., Mohr, Nicholas M., Judy, Claine, Saito, Shigeki, Kheir, Fayez M., Kheir, Fayez, Schlichting, Adam B., Delsing, Angela, Crouch, Daniel R., Elmasri, Mary, Crouch, Daniel R., Ismail, Dina, Dreyer, Kyle R., Blakeman, Thomas C., Dreyer, Kyle R., Gomaa, Dina, Baron, Rebecca M., Grijalba, Carolina Quintana, Hou, Peter C., Seethala, Raghu, Aisiku, Imo, Henderson, Galen, Frendl, Gyorgy, Hou, Sen-Kuang, Owens, Robert L., Schomer, Ashley, Bumbasirevic, Vesna, Jovanovic, Bojan, Surbatovic, Maja, Veljovic, Milic, McAuley, Danny, Rios, Fernando, Sottiaux, T., Depuydt, P., Lora, Fredy S., Azevedo, Luciano Cesar, Bugedo, Guillermo, Gonzalez, Marcos, Silesky, Juan, Cerny, Vladimir, Nielsen, Jonas, Jibaja, Manuel, Matamis, Dimitrios, Ranero, Jorge Luis, Amin, Pravin, Hashemian, S. M., Villagomez, Asisclo, Zeggwagh, Amine Ali, Palo, Jose Emmanuel, do Vale Fernandes, Antero, Sandesc, Dorel, Arabi, Yaasen, Bumbasierevic, Vesna, Lorente, Jose A., Piquilloud, Lise, Abroug, Fekri, Hurtado, Javier, Démpaire, Gabriel, The LUNG SAFE Investigators, and the ESICM Trials Group

Published
2017
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31. Correction to: The Intensive Care Global Study on Severe Acute Respiratory Infection (IC-GLOSSARI): a multicenter, multinational, 14-day inception cohort study

Author

Sakr, Yasser, Ferrer, Ricard, Reinhart, Konrad, Beale, Richard, Rhodes, Andrew, Moreno, Rui, Timsit, Jean Francois, Brochard, Laurent, Thompson, B. Taylor, Rezende, Ederlon, Chiche, Jean Daniel, Auer, J., Schatzl, G., Mach, K., Gruber, H., Schreurs, E., Vander Laenen, M., Ceunen, H., Wauters, J., Francois, G., Deschamps, P., Castanares, D., Debels, D., Pierrakos, C., Vincent, J. L., Taccone, F., Vymazal, T., Gornik, I., Vujiaklija Brajkovic, A., Medici, R., Nielsen, J., Bendtsen, A., Siegel, H., Suonsyrjä, T., Hraech, S., Daviaux, F., Guillot, M., Castelain, V., Losser, R-R., Novy, E., Bouadma, L., Misset, B., Philippart, F., Mallat, J., Zogheib, E., Miclo, M., Teboul, J-L., Anguel, N., Darmon, M., Pham, T., Barberet, G., Plantefeve, G., Floccard, B., Kheladze, Z., Bloos, F., Faltlhauser, A., Helmes, T., Zacharowski, K., Meybohm, P., Schwarzkopf, K., Christ, M., Baumgaertel, M., John, S., Nentwich, J., Deja, M., Goldmann, A., Gottschalk, A., Honig, F., Siepe, B., Goebel, U., Lehmke, J., Behrens, S., Fiedler, K., Sagoschen, I., Riessen, R., Haap, M., Simon, Ph., Kaisers, U., Behrens, S., Niesen, M., Jaschinski, U., Hoersch, S., Jung, A., Allgaeuer, S., Haake, H., Lange, A., Papanikolaou, M., Balla, M., Giannakou, M., Soultati, I., Nikos, G., Koulouras, V., Kyriazopoulos, G., Gkika, D., Vlachogianni, G., Psaroulis, K., Mouloudi, E., Massa, E., Nichol, A., Meany, E., Motherway, C., Bellani, G., Pota, V., Schiavone, V., Girardis, M., Busani, S., Petrucci, N., Di Pasquale, R., Mazzini, P., Molin, A., Pellerano, G., Volta, C., Spadaro, S., Guarracino, F., Savioli, M., Pellis, T., Chinellato, N., Gatta, A., Cecchini, F., Raineri, S. M., Cortegiani, A., Kekstas, G., Karosas, V., Anguseva, T., Mitrev, Z., Beck, O., Cimic, N., Janssen, G., Bormans, L., Kuiper, M., Koopmans, K., Den Boer, S., de Groot, M., Dennesen, P., van den Bosch, J., Kluge, G., Mikaszewska-Sokolewicz, M., Lazowski, T., Chruscikowski, M., Machon, J., Adamik, B., Kübler, A., Wieczorek, A., Afonso, S., Matos, R., Catorze, N., Araujo, A., Costa, Z., Pais-de-Lacerda, A., Martins, I., Cardiga, R., Fernandes, L., Serra, I., Martinho, A., Tomescu, D., Popescu, M., Scarlatescu, E., Stoica, R., Macri, A., Filipescu, D., Rupnik, E., Tomic, V., Sifrer, F., Sole Violan, J., Ferrer Agüero, J. M., Izura, J., Monedero, P., de Cabo, C. Muños, Aguilar, G., Belda, F. J., Blanquer, J., Nives Carbonell, E., Lopez-Delgado, J-C., Aragon, C., Joya, C., Ortiz-Leyba, C., Fernandez Gonzalez, C. J., de la Torre-Prados, M-V., Puerto-Morlan, A., Araujo Aguilar, P., Tomás Marsilla, J. I., Vera Aratcoz, P., Olmo, A., Ferrer Roca, R., Catalan, R. M., Garcia Olivares, P., Albis, A., Alvarez, M., Corcoles Gonzalez, V., Gutierrez Rubio, J. M., Montoiro Allue, R., Rubio Mateo-Sidron, J., Hobrok, M., Cecconi, M., Di Tomasso, N., Raj, A., Szakmany, T., Srinivasa, L., Mathew, S., Ferguson, A., Blahut-Zugaj, M., Watters, M., Henderson, S., Sim, M., Csabi, P., O’Neill, O., Nutt, C., Humphreys, S., Bhowmick, K., Donnelly, A., O’Kane, S., Garfield, M., Jha, R., Unni, N., Gordon, A., Rubulotta, F., Ravi, K., Lunch, G., Franco, F., Higgs, D., Strandvik, G., Jonas, A., Hopkins, Ph., Hurst, T., Bellini, A., Balogun, O., Srinivasan, R., Ostermann, M., Alexander, P., McCalman, K., Bedford, J., Fulop, M., Brescia, G., Strachan, J., Meyer, J., Stotz, M., Brett, S., Zand, F., Nikandish, R., Hashemian, S., Jamaati, H., Alsheikhly, A. S., Almekhlafi, G., Albarrak, M., Maghrabi, A., Salahuddin, N., Aisa, T., Atalan, H. K., Sungur, M., Hegazi, M., Bauer, P., Mukkera, S., Fried, J., Barger, M., Gueret, R., Gonzalez, C., Lovesio, C., Dellera, Ch., Barrios, D., Leite Mendes, C., Gottardo, P., Caser, E., Santos, C., Carvalho, A., Teixeira, C., Samaniego, W., Whittle, S., Molano, D., Rojas, A., Guerra, K., Villamagua, B., Salgado-Yepez, E., Morocho, D., Remache-Vargas, N., Ñamendys-Silva, S., Rodriguez, D., Dominguez, G., Barraza, G., Bermudez-Aceves, E., Sanchez-Hurtado, L. A., Baltazar-Torres, J. A., Quispe Sierra, R., Chavez, C., von Osten, I., Van Haren, C., Smalley, N., Kol, M., Wong, H., Smith, R., Yu, L., Wu, X., Chao, L., Zhai, Q., Wu, D., Zhang, X., Jing, X., Bigornia, R., Ikeda-Maquiling, Y., Robles, J., Palo, J. E., Nguyen, T., Dao, C., Dixit, S., Gurjar, M., Reddy, P., Pravin, A., Simran, S., Ramakrishnan, N., Shetty, R., Udwadia, F., Faraz, M., Indraratna, K., Rajasinhe, J., and IC-GLOSSARI Investigators and ESICM Trials Group

Published
2017
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32. The prognostic significance of atrial fibrillation in heart failure with preserved ejection function: insights from KaRen, a prospective and multicenter study

Author

Bosseau, Christian, Donal, Erwan, Lund, Lars H., Oger, Emmanuel, Hage, Camilla, Mulak, Geneviève, Daubert, Jean-Claude, Linde, Cecilia, Donal, Erwan, Lund, Lars H., Leclercq, Christophe, de Groote, Pascal, Ennezat, Pierre-Vladimir, Lafitte, Stéphane, Réant, Patricia, Bauer, Fabrice, Derumeaux, Geneviève, Bergerot, Cyrille, de Place, Christian, Juillière, Yves, Selton-Suty, Christine, Logeart, Damien, Gueret, Pascal, Lim, Pascal, Trochu, Jean-Noël, Pirou, Nicolas, Habib, Gilbert, Tournoux, François, Haugen-Löfman, Ida, Edner, Magnus, Emtell, Hans, and On behalf of the KaRen investigators

Published
2017
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36. The Accuracy of Portable Monitoring in Diagnosing Significant Sleep Disordered Breathing in Hospitalized Patients.

Author

Swamy Nagubadi, Rohit Mehta, Mamoun Abdoh, Mohammedumer Nagori, Stephen Littleton, Renaud Gueret, and Aiman Tulaimat

Subjects
Medicine, Science
Abstract

Polysomnograms are not always feasible when sleep disordered breathing (SDB) is suspected in hospitalized patients. Portable monitoring is a practical alternative; however, it has not been recommended in patients with comorbidities.We evaluated the accuracy of portable monitoring in hospitalized patients suspected of having SDB.Prospective observational study.Large, public, urban, teaching hospital in the United States.Hospitalized patients suspected of having SDB.Patients underwent portable monitoring combined with actigraphy during the hospitalization and then polysomnography after discharge. We determined the accuracy of portable monitoring in predicting moderate to severe SDB and the agreement between the apnea hypopnea index measured by portable monitor (AHIPM) and by polysomnogram (AHIPSG).Seventy-one symptomatic patients completed both tests. The median time between the two tests was 97 days (IQR 25-75: 24-109). Forty-five percent were hospitalized for cardiovascular disease. Mean age was 52±10 years, 41% were women, and the majority had symptoms of SDB. Based on AHIPSG, SDB was moderate in 9 patients and severe in 39. The area under the receiver operator characteristics curve for AHIPM was 0.8, and increased to 0.86 in patients without central sleep apnea; it was 0.88 in the 31 patients with hypercapnia. For predicting moderate to severe SDB, an AHIPM of 14 had a sensitivity of 90%, and an AHIPM of 36 had a specificity of 87%. The mean±SD difference between AHIPM and AHIPSG was 2±29 event/hr.In hospitalized, symptomatic patients, portable monitoring is reasonably accurate in detecting moderate to severe SDB.

Published
2016
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37. Déchirure isolée de la jonction myotendineuse du muscle infra-épineux traité par injections de plasma riche en plaquettes. À propos d’un cas

Author

M.L. Mencière, P. Gueret, V. Rotari, T. Aihonnou, and F. Perla

Subjects
030222 orthopedics, 03 medical and health sciences, 0302 clinical medicine, Rehabilitation, Orthopedics and Sports Medicine, Surgery, 030229 sport sciences
Abstract

Resume La dechirure isolee de la jonction myotendineuse (JMT) de l’infra-epineux est une lesion rare evoluant de maniere defavorable vers la degenerescence graisseuse, qu’elle soit operee ou non. Ce cas clinique presente un boxeur professionnel ayant beneficie de deux injections de plasma riche en plaquettes (PRP) au sein d’une lesion ancienne et invalidante de la JMT, tout en poursuivant son entrainement. L’evolution a 3 mois a ete tres favorable. Le patient ne ressentait plus aucune gene dans sa pratique sportive de haut niveau et les images IRM retrouvaient une cicatrisation myotendineuse parfaite. Il s’agit d’un nouveau cas rapporte ou les injections de PRP semblent avoir joue un role primordial dans la cicatrisation tissulaire alors que le niveau de preuves des etudes publiees reste faible voire insuffisant. Cette alternative associant injection de PRP et poursuite du travail musculaire ouvre une nouvelle voie pour la prise en charge de ce type de lesion.

Published
2020
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40. Coke Formation During Hydrocarbons Pyrolysis. Part Two: Methane Thermal Cracking Formation de coke pendant la pyrolyse des hydrocarbures. Deuxième partie : pyrolyse du méthane

Author

Billaud F., Broutin P., Busson C., and Gueret C.

Subjects
Chemical technology, TP1-1185, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract

Part one of this article dealt with coking in a steam cracking furnace. In this process, coke deposition is a very complex phenomenon due to the number of parameters involved. Nevertheless, for this process, coke deposition is a secondary reaction which does not affect steam cracking yields. It is completely different for methane thermal cracking. Coke is one of the main products of this reaction. Part two of this article deals with coke deposition on the walls of the reactors used for methane thermal cracking. After a brief description of the different set-ups used to study coke deposition, the main parameters involved are listed. The importance of temperature, conversion, type of diluent, and hydrocarbon partial pressure will be enhanced. To conclude, two approaches to the mechanism are proposed to explain coke formation during methane thermal cracking. La première partie de cet article faisait le point sur les réactions indésirables de cokage dans les réacteurs de vapocraquage : dans le cadre de ce procédé, la formation de coke est un phénomène complexe du fait du nombre important de paramètres mis en jeu. Toutefois, pour ce procédé, la réaction de formation du coke à la paroi des réacteurs est une réaction secondaire qui n'affecte pas les rendements de vapocraquage. Ceci est complètement différent dans le cas de la pyrolyse thermique du méthane, procédé pour lequel le coke est un produit principal et indésirable de la réaction. La seconde partie de cet article est consacrée plus particulièrement à la formation du coke, lors de la pyrolyse du méthane et présente les principaux résultats expérimentaux décrits dans la littérature. Parmi les différents montages expérimentaux utilisés pour mesurer le dépôt de coke, il est mentionné, à partir des travaux de la littérature, les 2 techniques suivantes : - la technique de la paroi chaude, - la technique du fil chaud. Pour la première technique, les montages expérimentaux utilisés font l'objet des figures 1 à 3. Le montage type consiste en un long tube de quartz ou d'alumine chauffé dans un four à moufles. La quantité de coke déposée à la paroi du tube peut être mesurée, soit par pesée, soit par combustion à l'air. La seconde technique fait l'objet de la figure 4. Pour ce type de montage, la quantité de coke déposée sur le fil est déterminée par pesée. Dans la suite de l'article sont présentés les différents facteurs et leur importance sur la formation du coke. On insiste en particulier sur l'effet de la température (fig. 5), de la conversion (fig. 6), de la pression partielle (fig. 7), de la nature du diluant (fig. 8), de la surface en contact avec le mélange réactionnel (fig. 9). Finalement, deux mécanismes pour expliquer la formation du coke lors de la pyrolyse du méthane sont également proposés.

Published
2006
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41. Coke Formation During Hydrocarbons Pyrolysis. Part One: Steam Cracking Formation de coke pendant la pyrolise des hydrocarbures. Première partie : vapocraquage

Author

Weill J., Broutin P., Billaud F., and Gueret C.

Subjects
Chemical technology, TP1-1185, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract

Thermal cracking is always accompanied by coke formation, which becomes deposited on the wall and limits heat transfers in the reactor while increasing pressure drops and possibly even plugging up the reactor. This review article covers undesirable coking operations in steam craking reactors. These coking reactions may take place in the gas phase and/or on the surface of the reactor, with coke being produced during pyrolysis by a complex mechanism that breaks down into a catalytic sequence and a noncatalytic sequence. After a brief description of different experimental set-ups used to measure the coke deposition, on the basis of research described in the literature, the different factors and their importance for coke formation are listed. In particular, we describe the effects of surface properties of stainless-steel and quartz reactors as well as the influence of the cracked feedstock, of temperature, of dilution, of residence time and of the conversion on coke deposition. Some findings about the morphology of coke are described and linked to formation mechanisms. To illustrate this review, some particularly interesting research is referred to concerning models developed to assess coke formation during propane steam cracking. Le craquage thermique est toujours accompagné de la formation de coke qui, en se déposant à la paroi, limite les transferts de chaleur au réacteur, augmente les pertes de charges et même peut boucher celui-ci. Cet article fait le point sur les réactions indésirables de cokage dans les réacteurs de vapocraquage. Ces réactions de cokage peuvent avoir lieu en phase gazeuse et/ou sur la surface du réacteur, le coke étant produit pendant la pyrolyse par un mécanisme complexe qui se décompose en une séquence catalytique et une séquence non catalytique. Après une brève présentation des différents montages expérimentaux utilisés pour mesurer le dépôt de coke, il est mentionné, à partir de travaux de la littérature, les différents facteurs et leur importance sur la formation du coke. On présentera en particulier les effets de propriétés de surface de réacteurs en inox et en quartz, ainsi que l'influence de la charge craquée, de la température, de la dilution, du temps de séjour et de la conversion sur les dépôts de coke. Quelques résultats sur la morphologie du coke seront présentés et reliés aux mécanismes de formation du coke. Pour illustrer ce travail, on reprendra quelques études particulièrement intéressantes sur des modèles d'évaluation de la formation de coke développés pour le vapocraquage de propane.

Published
2006
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42. Weaning from mechanical ventilation in intensive care units across 50 countries (WEAN SAFE): a multicentre, prospective, observational cohort study

Author

Pham, Tài, Heunks, Leo, Bellani, Giacomo, Madotto, Fabiana, Aragao, Irene, Beduneau, Gaëtan, Goligher, Ewan C, Grasselli, Giacomo, Laake, Jon Henrik, Mancebo, Jordi, Peñuelas, Oscar, Piquilloud, Lise, Pesenti, Antonio, Wunsch, Hannah, van Haren, Frank, Brochard, Laurent, Laffey, John G, Abrough, Fekri, Acharya, Subhash P, Amin, Pravin, Arabi, Yaseen, Aragao, Irene, Bauer, Philippe, Beduneau, Gaëtan, Beitler, Jeremy, Berkius, Johan, Bugedo, Guillermo, Camporota, Luigi, Cerny, Vladimir, Cho, Young-Jae, Clarkson, Kevin, Estenssoro, Elisa, Goligher, Ewan, Grasselli, Giacomo, Gritsan, Alexey, Hashemian, Seyed Mohammadreza, Hermans, Greet, Heunks, Leo M, Jovanovic, Bojan, Kurahashi, Kiyoyasu, Laake, Jon Henrik, Matamis, Dimitrios, Moerer, Onnen, Molnar, Zsolt, Ozyilmaz, Ezgi, Panka, Bernardo, Papali, Alfred, Peñuelas, Óscar, Perbet, Sébastien, Piquilloud, Lise, Qiu, Haibo, Razek, Assem Abdel, Rittayamai, Nuttapol, Roldan, Rollin, Serpa Neto, Ary, Szuldrzynski, Konstanty, Talmor, Daniel, Tomescu, Dana, Van Haren, Frank, Villagomez, Asisclo, Zeggwagh, Amine Ali, Abe, Toshikazu, Aboshady, Abdelrhman, Acampo-de Jong, Melanie, Acharya, Subhash, Adderley, Jane, Adiguzel, Nalan, Agrawal, Vijay Kumar, Aguilar, Gerardo, Aguirre, Gaston, Aguirre-Bermeo, Hernan, Ahlström, Björn, Akbas, Türkay, Akker, Mustafa, Al Sadeh, Ghamdan, Alamri, Sultan, Algaba, Angela, Ali, Muneeb, Aliberti, Anna, Allegue, Jose Manuel, Alvarez, Diana, Amador, Joaquin, Andersen, Finn H, Ansari, Sharique, Apichatbutr, Yutthana, Apostolopoulou, Olympia, Arabi, Yaseen, Arellano, Daniel, Arica, Mestanza, Arikan, Huseyin, Arinaga, Koichi, Arnal, Jean-Michel, Asano, Kengo, Asín-Corrochano, Marta, Avalos Cabrera, Jesus Milagrito, Avila Fuentes, Silvia, Aydemir, Semih, Aygencel, Gulbin, Azevedo, Luciano, Bacakoglu, Feza, Badie, Julio, Baedorf Kassis, Elias, Bai, Gabriela, Balaraj, Govindan, Ballico, Bruno, Banner-Goodspeed, Valerie, Banwarie, Preveen, Barbieri, Rosella, Baronia, Arvind, Barrett, Jonathan, Barrot, Loïc, Barrueco-Francioni, Jesus Emilio, Barry, Jeffrey, Bauer, Philippe, Bawangade, Harshal, Beavis, Sarah, Beck, Eduardo, Beehre, Nina, Belenguer Muncharaz, Alberto, Bellani, Giacomo, Belliato, Mirko, Bellissima, Agrippino, Beltramelli, Rodrigo, Ben Souissi, Asma, Benitez-Cano, Adela, Benlamin, Mohamed, Benslama, Abdellatif, Bento, Luis, Benvenuti, Daniela, Berkius, Johan, Bernabe, Laura, Bersten, Andrew, Berta, Giacomo, Bertini, Pietro, Bertram-Ralph, Elliot, Besbes, Mohamed, Bettini, Lisandro Roberto, Beuret, Pascal, Bewley, Jeremy, Bezzi, Marco, Bhakhtiani, Lakshay, Bhandary, Rakesh, Bhowmick, Kaushik, Bihari, Shailesh, Bissett, Bernie, Blythe, David, Bocher, Simon, Boedjawan, Narain, Bojanowski, Christine M, Boni, Elisa, Boraso, Sabrina, Borelli, Massimo, Borello, Silvina, Borislavova, Margarita, Bosma, Karen J, Bottiroli, Maurizio, Boyd, Owen, Bozbay, Suha, Briva, Arturo, Brochard, Laurent, Bruel, Cédric, Bruni, Andrea, Buehner, Ulrike, Bugedo, Guillermo, Bulpa, Pierre, Burt, Karen, Buscot, Mathieu, Buttera, Stefania, Cabrera, Jorge, Caccese, Roberta, Caironi, Pietro, Canchos Gutierrez, Ivan, Canedo, Nancy, Cani, Alma, Cappellini, Iacopo, Carazo, Jesus, Cardonnet, Luis Pablo, Carpio, David, Carriedo, Demetrio, Carrillo, Ramón, Carvalho, João, Caser, Eliana, Castelli, Antonio, Castillo Quintero, Manuel, Castro, Heloisa, Catorze, Nuno, Cengiz, Melike, Cereijo, Enrique, Ceunen, Helga, Chaintoutis, Christos, Chang, Youjin, Chaparro, Gustavogcha, Chapman, Carmel, Chau, Simon, Chavez, Cecilia Eugenia, Chelazzi, Cosimo, Chelly, Jonathan, Chemouni, Frank, Chen, Kai, Chena, Ariel, Chiarandini, Paolo, Chilton, Phil, Chiumello, Davide, Cho, Young-Jae, Chou-Lie, Yvette, Chudeau, Nicolas, Cinel, Ismail, Cinnella, Gilda, Clark, Michele, Clark, Thomas, Clarkson, Kevin, Clementi, Stefano, Coaguila, Luis, Codecido, Alexis Jaspe, Collins, Amy, Colombo, Riccardo, Conde, Juan, Consales, Guglielmo, Cook, Tim, Coppadoro, Andrea, Cornejo, Rodrigo, Cortegiani, Andrea, Coxo, Cristina, Cracchiolo, Andrea Neville, Crespo Ramirez, Mónica, Crova, Philippe, Cruz, José, Cubattoli, Lucia, Çukurova, Zafer, Curto, Francesco, Czempik, Piotr, D'Andrea, Rocco, da Silva Ramos, Fernando, Dangers, Laurence, Danguy des Déserts, Marc, Danin, Pierre-Eric, Dantas, Fabianne, Daubin, Cédric, Dawei, Wu, de Haro, Candelaria, de Jesus Montelongo, Felipe, De Mendoza, Diego, de Pablo, Raúl, De Pascale, Gennaro, De Rosa, Silvia, Decavèle, Maxens, Declercq, Pierre-Louis, Deicas, Alberto, del Carmen Campos Moreno, María, Dellamonica, Jean, Delmas, Benjamin, Demirkiran, Oktay, Demirkiran, Hilmi, Dendane, Tarek, di Mussi, Rossella, Diakaki, Chrysi, Diaz, Anatilde, Diaz, Willy, Dikmen, Yalim, Dimoula, Aikaterini, Doble, Patricia, Doha, Nagwa, Domingos, Guilherme, Dres, Martin, Dries, David, Duggal, Abhijit, Duke, Graeme, Dunts, Pavel, Dybwik, Knut, Dykyy, Maksym, Eckert, Philippe, Efe, Serdar, Elatrous, Souheil, Elay, Gülseren, Elmaryul, Abubaker S, Elsaadany, Mohamed, Elsayed, Hany, Elsayed, Samar, Emery, Malo, Ena, Sébastien, Eng, Kevin, Englert, Joshua A, Erdogan, Elif, Ergin Ozcan, Perihan, Eroglu, Ege, Escobar, Miguel, Esen, Figen, Esen Tekeli, Arzu, Esquivel, Alejandro, Esquivel Gallegos, Helbert, Ezzouine, Hanane, Facchini, Alberto, Faheem, Mohammad, Fanelli, Vito, Farina, Maria Fernanda, Fartoukh, Muriel, Fehrle, Lutz, Feng, Feng, Feng, Yufeng, Fernandez, Irene, Fernandez, Borja, Fernandez-Rodriguez, Maria Lorena, Ferrando, Carlos, Ferreira da Silva, Maria João, Ferreruela, Mireia, Ferrier, Janet, Flamm Zamorano, Matias Jesús, Flood, Laura, Floris, Leda, Fluckiger, Martin, Forteza, Catalina, Fortunato, Antonella, Frans, Eric, Frattari, Antonella, Fredes, Sebastian, Frenzel, Tim, Fumagalli, Roberto, Furche, Mariano Andres, Fusari, Maurizio, Fysh, Edward, Galeas-Lopez, Juan Luis, Galerneau, Louis-Marie, Garcia, Analía, Garcia, María Fernanda, Garcia, Elisabet, Garcia Olivares, Pablo, Garlicki, Jaroslaw, Garnero, Aude, Garofalo, Eugenio, Gautam, Prabha, Gazenkampf, Andrey, Gelinotte, Stéphanie, Gelormini, Domenico, Ghrenassia, Etienne, Giacomucci, Angelo, Giannoni, Robert, Gigante, Andrea, Glober, Nancy, Gnesin, Paolo, Gollo, Yari, Gomaa, Dina, Gomero Paredes, Rosita, Gomes, Rui, Gomez, Raúl Alejandro, Gomez, Oscar, Gomez, Aroa, Gondim, Louise, Gonzalez, Manuel, Gonzalez, Isabel, Gonzalez-Castro, Alejandro, Gordillo Romero, Orlando, Gordo, Federico, Gouin, Philippe, Graf Santos, Jerónimo, Grainne, Rooney, Grando, Matilde, Granov Grabovica, Sanja, Grasselli, Giacomo, Grasso, Salvatore, Grasso, Rinaldo, Grimmer, Lisa, Grissom, Colin, Gritsan, Alexey, Gu, Qing, Guan, Xiang-Dong, Guarracino, Fabio, Guasch, Neus, Guatteri, Luca, Gueret, Renaud, Guérin, Claude, Guerot, Emmanuel, Guitard, Pierre-Gildas, Gül, Fethi, Gumus, Ayca, Gurjar, Mohan, Gutierrez, Patricia, Hachimi, Abdelhamid, Hadzibegovic, Adi, Hagan, Samantha, Hammel, Clare, Han Song, Joo, Hanlon, Gabrielle, Hashemian, Seyed Mohammadreza, Heines, Serge, Henriksson, Johanna, Herbrecht, Jean-Etienne, Heredia Orbegoso, Gabriel Omar, Hermans, Greet, Hermon, Andrew, Hernandez, Rosana, Hernandez, Carmen, Herrera, Luis, Herrera-Gutierrez, Manuel, Heunks, Leo, Hidalgo, Juan, Hill, Dianne, Holmquist, Dagmar, Homez, Marcela, Hongtao, Xia, Hormis, Anil, Horner, Daniel, Hornos, M Carmen, Hou, Meihong, House, Stacy, Housni, Brahim, Hugill, Keith, Humphreys, Sally, Humbert, Louis, Hunter, Stephanie, Hwa Young, Lee, Iezzi, Nicolas, Ilutovich, Santiago, Inal, Volkan, Innes, Richard, Ioannides, Panagiotis, Iotti, Giorgio Antonio, Ippolito, Mariachiara, Irie, Hiromasa, Iriyama, Hiroki, Itagaki, Taiga, Izura, Javier, Izza, Santiago, Jabeen, Rakhshanda, Jamaati, Hamidreza, Jamadarkhana, Sunil, Jamoussi, Amira, Jankowski, Milosz, Jaramillo, Luis Alberto, Jeon, Kyeongman, Jeong Lee, Seok, Jeswani, Deepak, Jha, Simant, Jiang, Liangyan, Jing, Chen, Jochmans, Sébastien, Johnstad, Bror Anders, Jongmin, Lee, Joret, Aurélie, Jovanovic, Bojan, Junhasavasdikul, Detajin, Jurado, Maria Teresa, Kam, Elisa, Kamohara, Hidenobu, Kane, Caroline, Kara, Iskender, Karakurt, Sait, Karnjanarachata, Cherdkiat, Kataoka, Jun, Katayama, Shinshu, Kaushik, Shuchi, Kelebek Girgin, Nermin, Kerr, Kathryn, Kerslake, Ian, Khairnar, Prakash, Khalid, Abidi, Khan, Akram, Khanna, Ashish K, Khorasanee, Reza, Kienhorst, Dieneke, Kirakli, Cenk, Knafelj, Rihard, Kol, Mark Kol, Kongpolprom, Napplika, Kopitko, Csaba, Korkmaz Ekren, Pervin, Kubisz-Pudelko, Agnieszka, Kulcsar, Zoltan, Kumasawa, Junji, Kurahashi, Kiyoyasu, Kuriyama, Akira, Kutchak, Fernanda, Laake, Jon Henrik, Labarca, Eduardo, Labat, Françoise, Laborda, César, Laca Barrera, Manuel Alberto, Lagache, Laurie, Landaverde Lopez, Antonio, Lanspa, Michael, Lascari, Valeria, Le Meur, Matthieu, Lee, Su Hwan, Lee, Young Ju, Lee, Jinwoo, Lee, Won-Yeon, Lee, Jarone, Legernaes, Terje, Leiner, Tamaas, Lemiale, Virginie, Leonor, Tiago, Lepper, Philipp M, Li, Dahuan, Li, Hongbin, Li, Oleg, Lima, Ana Raquel, Lind, Dan, Litton, Edward, Liu, Ning, Liu, Ling, Liu, Jialin, Llitjos, Jean-François, Llorente, Beatriz, Lopez, Rodolfo, Lopez, Claudia Elizabeth, Lopez Nava, Claudia, Lovazzano, Pablo, Lu, Min, Lucchese, Francesca, Lugano, Manuela, Lugo Goytia, Gustavo, Luo, Hua, Lynch, Ceri, Macheda, Sebastiano, Madrigal Robles, Victor Hugo, Maggiore, Salvatore Maurizio, Magret Iglesias, Mònica, Malaga, Peter, Mallapura Maheswarappa, Harish, Malpartida, Guillermo, Malyarchikov, Andrey, Mansson, Helena, Manzano, Anaid, Marey, Ismael, Marin, Nathalie, Marin, Maria del Carmen, Markman, Eliana, Martin, Felix, Martin, Alex, Martin Dal Gesso, Cristina, Martinez, Felipe, Martínez-Fidalgo, Conchita, Martin-Loeches, Ignacio, Mas, Arantxa, Masaaki, Sakuraya, Maseda, Emilio, Massa, Eleni, Mattsson, Anna, Maugeri, Jessica, McCredie, Victoria, McCullough, James, McGuinness, Shay, McKown, Andrew, Medve, László, Mei, Chengqing, Mellado Artigas, Ricard, Mendes, Vitor, Mervat, Mohamed Khalaf Ebraheim, Michaux, Isabelle, Mikhaeil, Michael, Milagros, Olga, Milet, Igor, Millan, Maria Teresa, Minwei, Zhang, Mirabella, Lucia, Mishra, Sanghamitra, Mistraletti, Giovanni, Mochizuki, Katsunori, Moerer, Onnen, Moghal, Arif, Mojoli, Francesco, Molin, Alexandre, Molnar, Zsolt, Montiel, Raquel, Montini, Luca, Monza, Gianmario, Mora Aznar, Maria, Morakul, Sunthiti, Morales, Maria, Moreno Torres, Daniel, Morocho Tutillo, Diego Rolando, Motherway, Catherine, Mouhssine, Doumiri, Mouloudi, Eleni, Muñoz, Tapia, Munoz de Cabo, Carlos, Mustafa, Mohamed, Muthuchellappan, Radhakrishnan, Muthukrishnan, Muraleekrishnan, Muttini, Stefano, Nagata, Isao, Nahar, Dick, Nakanishi, Misuzu, Nakayama, Izumi, Namendys-Silva, Silvio Antonio, Nanchal, Rahul, Nandakumar, Sivakumar, Nasi, Alessandra, Nasir, Kamal, Navalesi, Paolo, Naz Aslam, Tayyba, Nga Phan, Thuy, Nichol, Alistair, Niiyama, Shuhei, Nikolakopoulou, Sofia, Nikolic, Elena, Nitta, Kenichi, Noc, Marko, Nonas, Stephanie, Nseir, Saad, Nur Soyturk, Ayse, Obata, Yukako, Oeckler, Richard, Oguchi, Moe, Ohshimo, Shinichiro, Oikonomou, Marina, Ojados, Agueda, Oliveira, Maria Teresa, Oliveira Filho, Wilson, Oliveri, Carlo, Olmos, Aitor, Omura, Kazuya, Orlandi, Maria Cristina, Orsenigo, Francesca, Ortiz-Ruiz De Gordoa, Laura, Ota, Kei, Ovalle Olmos, Rainier, Öveges, Nándo, Oziemski, Peter, Ozkan Kuscu, Ozlem, Pachas Alvarado, Fernando, Pagella, Gonzalo, Palaniswamy, Vijayanand, Palazon Sanchez, Eugenio Luis, Palmese, Salvatore, Pan, Guojun, Pan, Wensen, Panka, Bernardo, Papanikolaou, Metaxia, Papavasilopoulou, Theonymfi, Parekh, Ameet, Parke, Rachael, Parrilla, Francisco J, Parrilla, Dácil, Pasha, Taha, Pasin, Laura, Patão, Luis, Patel, Mayur, Patel, Grisma, Pati, Basanta Kumar, Patil, Jayaprakash, Pattnaik, Saroj, Paul, Daniel, Pavesi, Maurizio, Pavlotsky, Vanesa Alejandra, Paz, Graciela, Paz, Enrique, Pecci, Elisabetta, Pellegrini, Carlos, Peña Padilla, Andrea Gabriela, Perchiazzi, Gaetano, Pereira, Tiago, Pereira, Vera, Perez, Manuel, Perez Calvo, Cesar, Perez Cheng, Meisy, Perez Maita, Ronald, Pérez-Araos, Rodrigo, Perez-Teran, Purificación, Perez-Torres, David, Perkins, Gavin, Persona, Paolo, Petnak, Tananchai, Petrova, Marina, Pham, Tai, Philippart, François, Picetti, Edoardo, Pierucci, Elisabetta, Piervincenzi, Edoardo, Pinciroli, Riccardo, Pintado, Maria-Consuelo, Piquilloud, Lise, Piraino, Thomas, Piras, Stephanie, Piras, Claudio, Pirompanich, Pattarin, Pisani, Luigi, Platas, Enrique, Plotnikow, Gustavo, Porras, Willy, Porta, Virginia, Portilla, Mariana, Portugal, José, Povoa, Pedro, Prat, Gwenael, Pratto, Romina, Preda, Gabriel, Prieto, Isidro, Prol-Silva, Estefania, Pugh, Richard, Qi, Yupeng, Qian, Chuanyun, Qin, Tiehe, Qiu, Haibo, Qu, Hongping, Quintana, Teobaldo, Quispe Sierra, Rosari, Quispe Soto, Rocio, Rabbani, Raihan, Rabee, Mohamed, Rabie, Ahmed, Rahe Pereira, Maria Augusta, Rai, Ashish, Raj Ashok, Sundar, Rajab, Mostafa, Ramdhani, Navin, Ramey, Elizabeth, Ranieri, Marco, Rathod, Darshana, Ray, Banambar, Redwanul Huq, Shihan Mahmud, Regli, Adrian, Reina, Rosa, Resano Sarmiento, Natalia, Reynaud, Faustine, Rialp, Gemma, Ricart, Pilar, Rice, Todd, Richardson, Angus, Rieder, Marcelo, Rinket, Martin, Rios, Fernando, Rios, Fernando, Risso Vazquez, Alejandro, Rittayamai, Nuttapol, Riva, Ivano, Rivette, Monaly, Roca, Oriol, Roche-Campo, Ferran, Rodriguez, Covadonga, Rodriguez, Gabriel, Rodriguez Gonzalez, Daniel, Rodriguez Tucto, Xandra Yanina, Rogers, Angela, Romano, María Elena, Rørtveit, Linda, Rose, Alastair, Roux, Damien, Rouze, Anahita, Rubatto Birri, Paolo Nahuel, Ruilan, Wang, Ruiz Robledo, Aldana, Ruiz-Aguilar, Antonio Luis, Sadahiro, Tomohito, Saez, Ignacio, Sagardia, Judith, Saha, Rajnish, Saha, Rohit, Saiphoklang, Narongkorn, Saito, Shigeki, Salem, Maie, Sales, Gabriele, Salgado, Patricia, Samavedam, Srinivas, Sami Mebazaa, Mhamed, Samuelsson, Line, San Juan Roman, Nandyelly, Sanchez, Patricia, Sanchez-Ballesteros, Jesus, Sandoval, Yazcitk, Sani, Emanuele, Santos, Martin, Santos, Carla, Sanui, Masamitsu, Saravanabavan, Lakshmikanthcharan, Sari, Sema, Sarkany, Agnes, Sauneuf, Bertrand, Savioli, Monica, Sazak, Hilal, Scano, Riccardo, Schneider, Francis, Schortgen, Frédérique, Schultz, Marcus J, Schwarz, Gabriele Leonie, Seçkin Yücesoy, Faruk, Seely, Andrew, Seiler, Frederik, Seker Tekdos, Yasemin, Seok Chan, Kim, Serano, Luca, Serednicki, Wojciech, Serpa Neto, Ary, Setten, Mariano, Shah, Asim, Shah, Bhagyesh, Shang, You, Shanmugasundaram, Pradeep, Shapovalov, Konstantin, Shebl, Eman, Shiga, Takuya, Shime, Nobuaki, Shin, Phil, Short, Jack, Shuhua, Chen, Siddiqui, Sughrat, Silesky Jimenez, Juan Ignacio, Silva, Daniel, Silva Sales, Betania, Simons, Koen, Sjøbø, Brit Ågot, Slessor, David, Smiechowicz, Jakub, Smischney, Nathan, Smith, Paul, Smith, Tim, Smith, Mark, Snape, Sarah, Snyman, Lindi, Soetens, Filiep, Sook Hong, Kyung, Sosa Medellin, Miguel Ángel, Soto, Giovanna, Souloy, Xavier, Sousa, Elsa, Sovatzis, Stefania, Sozutek, Didem, Spadaro, Savino, Spagnoli, Marco, Spångfors, Martin, Spittle, Nick, Spivey, Mike, Stapleton, Andrew, Stefanovic, Branislava, Stephenson, Lorraine, Stevenson, Elizabeth, Strand, Kristian, Strano, Maria Teresa, Straus, Slavenka, Sun, Chenliang, Sun, Rongqing, Sundaram, Venkat, SunPark, Tai, Surlemont, Elisabeth, Sutherasan, Yuda, Szabo, Zsuzsanna, Szuldrzynski, Konstanty, Tainter, Christopher, Takaba, Akihiro, Tallott, Mandy, Tamasato, Tamasato, Tang, Zhanhong, Tangsujaritvijit, Viratch, Taniguchi, Leandro, Taniguchi, Daisuke, Tarantino, Fabio, Teerapuncharoen, Krittika, Temprano, Susana, Terragni, Pierpaolo, Terzi, Nicolas, Thakur, Anand, Theerawit, Pongdhep, Thille, Arnaud W, Thomas, Matt, Thungtitigul, Poungrat, Thyrault, Martial, Tilouch, Nejla, Timenetsky, Karina, Tirapu, Juna, Todeschini, Manuel, Tomas, Roser, Tomaszewski, Christian, Tonetti, Tommaso, Tonnelier, Alexandre, Trinder, John, Trongtrakul, Konlawij, Truwit, Jonathon, Tsuei, Betty, Tulaimat, Aiman, Turan, Sema, Turkoglu, Melda, Tyagi, Sanjeev, Ubeda, Alejandro, Vagginelli, Federica, Valenti, María Florencia, Vallverdu, Imma, Van Axel, Alisha, van den Hul, Ingrid, van der Hoeven, Hans, Van Der Meer, Nardo, Van Haren, Frank, Vanhoof, Marc, Vargas-Ordoñez, Mónica, Vaschetto, Rosanna, Vascotto, Ettore, Vatsik, Maria, Vaz, Ana, Vazquez-Sanchez, Antonia, Ventura, Sara, Vermeijden, Jan Wytze, Vidal, Anxela, Vieira, Jocyelle, Vilela Costa Pinto, Bruno, Villagomez, Asisclo, Villagra, Ana, Villegas Succar, Cristina, Vinorum, Ole Georg, Vitale, Giovanni, Vj, Ramesh, Vochin, Ana, Voiriot, Guillaume, Volta, Carlo Alberto, von Seth, Magnus, Wajdi, Maazouzi, Walsh, Don, Wang, Shouhong, Wardi, Gabriel, Ween-Velken, Nils Christian, Wei, Bi-Lin, Weller, Dolf, Welsh, Deborah, Welters, Ingeborg, Wert, Michael, Whiteley, Simon, Wilby, Elizabeth, Williams, Erin, Williams, Karen, Wilson, Antoinette, Wojtas, Jadwiga, Won Huh, Jin, Wrathall, David, Wright, Christopher, Wu, Jian-Feng, Xi, Guo, Xing, Zheng-Jiang, Xu, Hongyang, Yamamoto, Kotaro, Yan, Jie, Yáñez, Julio, Yang, Xiaobo, Yates, Elliot, Yazicioglu Mocin, Ozlem, Ye, Zhenglong, Yildirim, Fatma, Yoshida, Norifumi, Yoshido, Hector Higo Leon, Young Lee, Bo, Yu, Rongguo, Yu, Gong, Yu, Tao, Yuan, Boyun, Yuangtrakul, Nadwipa, Yumoto, Tetsuya, Yun, Xie, Zakalik, Graciela, Zaki, Ahmad, Zalba-Etayo, Begoña, Zambon, Massimo, Zang, Bin, Zani, Gianluca, Zarka, Jonathan, Zerbi, Simone Maria, Zerman, Avsar, Zetterquist, Harald, Zhang, Jiuzhi, Zhang, Hongwen, Zhang, Wei, Zhang, Guoxiu, Zhang, Weixin, Zhao, Hongsheng, Zheng, Jia, Zhu, Bin, and Zumaran, Ronald

Abstract

Current management practices and outcomes in weaning from invasive mechanical ventilation are poorly understood. We aimed to describe the epidemiology, management, timings, risk for failure, and outcomes of weaning in patients requiring at least 2 days of invasive mechanical ventilation.

Published
2023
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43. Epicardial adipose tissue thickness correlates with the presence and severity of angiographic coronary artery disease in stable patients with chest pain.

Author

Fabien A Picard, Pascal Gueret, Jean-Pierre Laissy, Stéphane Champagne, Florence Leclercq, Didier Carrié, Jean-Michel Juliard, Patrick Henry, Ralph Niarra, Gilles Chatellier, and Philippe Gabriel Steg

Subjects
Medicine, Science
Abstract

ObjectiveEpicardial adipose tissue (EAT) is suggested to correlate with metabolic risk factors and to promote plaque development in the coronary arteries. We sought to determine whether EAT thickness was associated or not with the presence and extent of angiographic coronary artery disease (CAD).MethodsWe measured epicardial fat thickness by computed tomography and assessed the presence and extent of CAD by coronary angiography in participants from the prospective EVASCAN study. The association of EAT thickness with cardiovascular risk factors, coronary artery calcification scoring and angiographic CAD was assessed using multivariate regression analysis.ResultsOf 970 patients (age 60.9 years, 71% male), 75% (n = 731) had CAD. Patients with angiographic CAD had thicker EAT on the left ventricle lateral wall when compared with patients without CAD (2.74±2.4 mm vs. 2.08±2.1 mm; p = 0.0001). The adjusted odds ratio (OR) for a patient with a LVLW EAT value ≥2.8 mm to have CAD was OR = 1.46 [1.03-2.08], p = 0.0326 after adjusting for risk factors. EAT also correlated with the number of diseased vessels (p = 0.0001 for trend). By receiver operating characteristic curve analysis, an EAT value ≥2.8 mm best predicted the presence of>50% diameter coronary artery stenosis, with a sensitivity and specificity of 46.1% and 66.5% respectively (AUC:0.58). Coronary artery calcium scoring had an AUC of 0.76.ConclusionAlthough left ventricle lateral wall EAT thickness correlated with the presence and extent of angiographic CAD, it has a low performance for the diagnosis of CAD.

Published
2014
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45. HIV Infection and Long-Term Residual Cardiovascular Risk After Acute Coronary Syndrome

Author

Franck Boccara, Murielle Mary‐Krause, Valérie Potard, Emmanuel Teiger, Sylvie Lang, Nadjib Hammoudi, Marion Chauvet, Stéphane Ederhy, Laurie Dufour‐Soulat, Yann Ancedy, Pascal Nhan, Saroumadi Adavane, Ph. Gabriel Steg, Christian Funck‐Brentano, Dominique Costagliola, Ariel Cohen, S. Weber, K. Wahbi, P. Beaufils, P. Henri, G. Sideris, D. Thomas, G. Montalescot, F. Beygui, C. Meuleman, S. Janower, F. Raoux, G. Dufaitre, N. Benyounes, P. L. Michel, B. Petillon, N. Hammoudi, P. Gueret, J. L. Dubois‐Rande, E. Teiger, P. Lim, M. Slama, P. Colin, C. Saudubray, O. Dubourg, O. Milleron, B. Gallet, F. Duclos, S. Godard, L. Fuchs, V. Dormagen, P. Lewy, S. Cattan, O. Nallet, G. Grollier, J. Shayne, J. E. Wolf, Y. Cottin, J. Machecourt, H. Bouvaist, G. Finet, B. De Breyne, J. N. Trochu, M. Baudouy, E. Ferrari, M. Benhamou, J. Allal, D. Coisne, H. Le Breton, M. Bedossa, J. Puel, M. Elbaz, L. Larifla, S. Matheron, R. Landman, G. Fremont, G. Spiridon, P. Blanche, J. P. Morini, D. Sicard, V. Zeller, D. Batisse, P. Clevenbergh, G. Cessot, E. Dohin, M. A. Valantin, S. Khelifa, P. M. Girard, F. Lallemand, B. Lefebvre, J. P. Laporte, J. L. Meynard, H. Bideault, O. Picard, M. C. Meyohas, P. Campa, J. Tredup, L. Fonquernie, G. Raguin, J. M. Molina, A. Furco, S. Gharakanian, J. P. Vincensini, J. B. Guiard‐Schmid, G. Pialoux, B. Cardon, A. S. Lascaux, F. Chaix, P. Lesprit, R. Fior, F. Boue, C. Dupont, C. Bellier, A. Blanc, T. Lambert, T. Touahri, G. Force, P. de Truchis, M. A. Compagnucci‐Seguenot, I. Cahitte, L. Roudière, M. E. Techer, P. Thelpin, D. Troisvallets, A. Lepretre, M. Echard, Y. Le Mercier, D. Houlbert, S. Dargere, C. Bazin, R. Verdon, B. De Goer, M. Duong, P. Chavanet, E. Gozlan, P. Leclercq, F. Brunel‐Dal Mas, J. Durant, P. Heudier, C. Brunet‐François, G. Le Moal, J. M. Chapplin, C. Arvieux, G. Chaumentin, B. Guerin, E. Bonnet, Y. Poinsignon, F. Boulard, I. De Lacroix, M. T. Goerger‐Sow, M. Kirstetter, M. Volstein, F. Laylavoix, X. Copin, C. Ceppi, Service de Cardiologie [CHU Saint-Antoine], CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre de Recherche Saint-Antoine (CR Saint-Antoine), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-CHU Saint-Antoine [AP-HP], Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Henri Mondor, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Centre d'Investigation Clinique Henri Mondor (CIC Henri Mondor), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut de cardiologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Laboratoire de Recherche Vasculaire Translationnelle (LVTS (UMR_S_1148 / U1148)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Université Sorbonne Paris Nord, CIC Paris Est, Service de pharmacologie médicale [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre de Recherche Saint-Antoine (CRSA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases [IHU ICAN], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Centre d'investigation clinique Paris Est (CIC Paris-Est), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Service de Pharmacologie médicale [CHU Pitié-Salpêtrière]

Subjects
Male, Heart disease, [SDV]Life Sciences [q-bio], Human immunodeficiency virus (HIV), Aftercare, heart failure, HIV Infections, heart disease, 030204 cardiovascular system & hematology, medicine.disease_cause, Coronary artery disease, 0302 clinical medicine, prevention, Recurrence, Risk Factors, Cardiovascular Disease, Secondary Prevention, Medicine, 030212 general & internal medicine, Longitudinal Studies, Prospective Studies, Original Research, Middle Aged, Prognosis, 3. Good health, Editorial, myocardial infarction, Anti-Retroviral Agents, Cardiovascular Diseases, Cardiology, Female, France, Cardiology and Cardiovascular Medicine, coronary artery disease, Adult, Acute coronary syndrome, medicine.medical_specialty, 03 medical and health sciences, Percutaneous Coronary Intervention, Internal medicine, Humans, Acute Coronary Syndrome, business.industry, dyslipidemia, Coronary Care Units, Editorials, HIV, medicine.disease, HIV infection, Cerebrovascular Disorders, Heart Disease Risk Factors, Case-Control Studies, ST Elevation Myocardial Infarction, business, Dyslipidemia
Abstract

Background It is unclear whether HIV infection affects the long‐term prognosis after an acute coronary syndrome (ACS). The objective of the current study was to compare rates of major adverse cardiac and cerebrovascular events after a first ACS between people living with HIV (PLHIV) and HIV‐uninfected (HIV−) patients, and to identify determinants of cardiovascular prognosis. Methods and Results Consecutive PLHIV and matched HIV− patients with a first episode of ACS were enrolled in 23 coronary intensive care units in France. Patients were matched for age, sex, and ACS type. The primary end point was major adverse cardiac and cerebrovascular events (cardiac death, recurrent ACS, recurrent coronary revascularization, and stroke) at 36‐month follow‐up. A total of 103 PLHIV and 195 HIV− patients (mean age, 49 years [SD, 9 years]; 94.0% men) were included. After a mean of 36.6 months (SD, 6.1 months) of follow‐up, the risk of major adverse cardiac and cerebrovascular events was not statistically significant between PLHIV and HIV− patients (17.8% and 15.1%, P =0.22; multivariable hazard ratio [HR], 1.60; 95% CI, 0.67–3.82 [ P =0.29]). Recurrence of ACS was more frequent among PLHIV (multivariable HR, 6.31; 95% CI, 1.32–30.21 [ P =0.02]). Stratified multivariable Cox models showed that HIV infection was the only independent predictor for ACS recurrence. PLHIV were less likely to stop smoking (47% versus 75%; P =0.01) and had smaller total cholesterol decreases (–22.3 versus –35.0 mg/dL; P =0.04). Conclusions Although the overall risk of major adverse cardiac and cerebrovascular events was not statistically significant between PLHIV and HIV− individuals, PLHIV had a higher rate of recurrent ACS. Registration URL: https://www.clini​caltr​ials.gov ; Unique identifier: NCT00139958.

Published
2020
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46. ' Le Vallier Ouest 'à Mainvilliers (Eure-et-Loir, 28) : indices d’un habitat du Néolithique ancien (Villeneuve-Saint-Germain) entre Loire et Seine

Author

Frédéric Dupont, François Fouriaux, Nicolas Garmond, Colas Gueret, Roland Irribarria, and Apolline Louis

Subjects
buildings, ceramics, domestic occupation, Eure-et-Loir, France, lithic stigmatas, Archaeology, CC1-960
Abstract

Despite the delicate context owing to the nature of the substrate and to more recent structures, the excavation site of the Vallier Ouest (Mainvilliers, Eure-et-Loir, France) revealed indications of the presence of a settlement dated from the ancient Neolithic. These indications are, firstly, the material remains (pottery and lithic) attributable evenly to the end of Villeneuve-Saint-Germain and the other few hollow structures indicating the location of buildings or areas of activity. If the lithic corpus is original in its origin and the proportion of blades, these elements as a whole and traceological study tell of an occupation of a domestic nature that cannot be completely understood because of the poor preservation of the site. This site however still offers new keys to the understanding the Neolithic expansion between the Loire and Seine.

Published
2010

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