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3. Oncogenic context shapes the fitness landscape of tumor suppression

Author

Lily M. Blair, Joseph M. Juan, Lafia Sebastian, Vy B. Tran, Wensheng Nie, Gregory D. Wall, Mehmet Gerceker, Ian K. Lai, Edwin A. Apilado, Gabriel Grenot, David Amar, Giorgia Foggetti, Mariana Do Carmo, Zeynep Ugur, Debbie Deng, Alex Chenchik, Maria Paz Zafra, Lukas E. Dow, Katerina Politi, Jonathan J. MacQuitty, Dmitri A. Petrov, Monte M. Winslow, Michael J. Rosen, and Ian P. Winters

Subjects
Science
Abstract

Abstract Tumors acquire alterations in oncogenes and tumor suppressor genes in an adaptive walk through the fitness landscape of tumorigenesis. However, the interactions between oncogenes and tumor suppressor genes that shape this landscape remain poorly resolved and cannot be revealed by human cancer genomics alone. Here, we use a multiplexed, autochthonous mouse platform to model and quantify the initiation and growth of more than one hundred genotypes of lung tumors across four oncogenic contexts: KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R. We show that the fitness landscape is rugged—the effect of tumor suppressor inactivation often switches between beneficial and deleterious depending on the oncogenic context—and shows no evidence of diminishing-returns epistasis within variants of the same oncogene. These findings argue against a simple linear signaling relationship amongst these three oncogenes and imply a critical role for off-axis signaling in determining the fitness effects of inactivating tumor suppressors.

Published
2023
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4. Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy

Author

Victoria N. Parikh, Alexander G. Ioannidis, David Jimenez-Morales, John E. Gorzynski, Hannah N. De Jong, Xiran Liu, Jonasel Roque, Victoria P. Cepeda-Espinoza, Kazutoyo Osoegawa, Chris Hughes, Shirley C. Sutton, Nathan Youlton, Ruchi Joshi, David Amar, Yosuke Tanigawa, Douglas Russo, Justin Wong, Jessie T. Lauzon, Jacob Edelson, Daniel Mas Montserrat, Yongchan Kwon, Simone Rubinacci, Olivier Delaneau, Lorenzo Cappello, Jaehee Kim, Massa J. Shoura, Archana N. Raja, Nathaniel Watson, Nathan Hammond, Elizabeth Spiteri, Kalyan C. Mallempati, Gonzalo Montero-Martín, Jeffrey Christle, Jennifer Kim, Anna Kirillova, Kinya Seo, Yong Huang, Chunli Zhao, Sonia Moreno-Grau, Steven G. Hershman, Karen P. Dalton, Jimmy Zhen, Jack Kamm, Karan D. Bhatt, Alina Isakova, Maurizio Morri, Thanmayi Ranganath, Catherine A. Blish, Angela J. Rogers, Kari Nadeau, Samuel Yang, Andra Blomkalns, Ruth O’Hara, Norma F. Neff, Christopher DeBoever, Sándor Szalma, Matthew T. Wheeler, Christian M. Gates, Kyle Farh, Gary P. Schroth, Phil Febbo, Francis deSouza, Omar E. Cornejo, Marcelo Fernandez-Vina, Amy Kistler, Julia A. Palacios, Benjamin A. Pinsky, Carlos D. Bustamante, Manuel A. Rivas, and Euan A. Ashley

Subjects
Science
Abstract

There is a genetic component to the risk of severe COVID-19, but the genetic effects are difficult to separate from social constructs that covary with genetic ancestry. To address this, the authors identify determinants of COVID-19 severity using admixture mapping, viral phylodynamics, and host immune and metagenomic sequencing.

Published
2022
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5. Time trajectories in the transcriptomic response to exercise - a meta-analysis

Author

David Amar, Malene E. Lindholm, Jessica Norrbom, Matthew T. Wheeler, Manuel A. Rivas, and Euan A. Ashley

Subjects
Science
Abstract

Regular exercise promotes overall health and prevents non-communicable diseases, but the adaptation mechanisms are unclear. Here, the authors perform a meta-analysis to reveal time-specific patterns of the acute and long-term exercise response in human skeletal muscle, and identify sex- and age-specific changes.

Published
2021
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6. Graphical analysis for phenome-wide causal discovery in genotyped population-scale biobanks

Author

David Amar, Nasa Sinnott-Armstrong, Euan A. Ashley, and Manuel A. Rivas

Subjects
Science
Abstract

Mendelian randomization is a popular method to detect causal relationships between traits, but can be confounded by instances of horizontal pleiotropy. Here, the authors present a Mendelian randomization workflow which includes causal discovery analysis and filtering of genetic instruments based on their conditional independencies.

Published
2021
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7. FOCS: a novel method for analyzing enhancer and gene activity patterns infers an extensive enhancer–promoter map

Author

Tom Aharon Hait, David Amar, Ron Shamir, and Ran Elkon

Subjects
Enhancers, Promoters, Gene regulation, ENCODE, Roadmap, FANTOM5, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Recent sequencing technologies enable joint quantification of promoters and their enhancer regions, allowing inference of enhancer–promoter links. We show that current enhancer–promoter inference methods produce a high rate of false positive links. We introduce FOCS, a new inference method, and by benchmarking against ChIA-PET, HiChIP, and eQTL data show that it results in lower false discovery rates and at the same time higher inference power. By applying FOCS to 2630 samples taken from ENCODE, Roadmap Epigenomics, FANTOM5, and a new compendium of GRO-seq samples, we provide extensive enhancer–promotor maps (http://acgt.cs.tau.ac.il/focs). We illustrate the usability of our maps for deriving biological hypotheses.

Published
2018
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8. Biological Insights Into Muscular Strength: Genetic Findings in the UK Biobank

Author

Emmi Tikkanen, Stefan Gustafsson, David Amar, Anna Shcherbina, Daryl Waggott, Euan A. Ashley, and Erik Ingelsson

Subjects
Medicine, Science
Abstract

Abstract We performed a large genome-wide association study to discover genetic variation associated with muscular strength, and to evaluate shared genetic aetiology with and causal effects of muscular strength on several health indicators. In our discovery analysis of 223,315 individuals, we identified 101 loci associated with grip strength (P

Published
2018
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9. Personalized prediction of adverse heart and kidney events using baseline and longitudinal data from SPRINT and ACCORD.

Author

Gal Dinstag, David Amar, Erik Ingelsson, Euan Ashley, and Ron Shamir

Subjects
Medicine, Science
Abstract

BackgroundThe 2017 guidelines of the American College of Cardiology and the American Heart Association propose substantial changes to hypertension management. The guidelines lower the blood pressure threshold defining hypertension and promote more aggressive treatments. Thus, more individuals are now classified as hypertensive and as a result, medication usage may become more extensive. An inevitable byproduct of greater medication use is higher incidence of adverse effects. Here, we examined these issues by developing models that predict both cardiovascular events and other adverse events based on the treatment chosen and other patient's data.Methods and resultsWe used data from the SPRINT trial to produce patient-specific predictions of the risks for adverse cardiovascular or kidney outcomes. Unlike prior models, we used both the baseline characteristics collected upon recruitment and the longitudinal data during the follow-up. Importantly, our cardiovascular predictor outperformed extant models on SPRINT participants, achieving AUC = 0.765, and was validated with good performance in an independent cohort of the ACCORD trial.ConclusionsOur study illustrates the importance of including longitudinal data for assessing personalized risk and provides means for recommending personalized treatment decisions.

Published
2019
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10. MorphDB: Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants

Author

Arthur Zwaenepoel, Tim Diels, David Amar, Thomas Van Parys, Ron Shamir, Yves Van de Peer, and Oren Tzfadia

Subjects
comparative co-expression networks, candidate gene prioritization, functional annotation, MORPH, defense response, Plant culture, SB1-1110
Abstract

Recent times have seen an enormous growth of “omics” data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named “MORPH bulk” (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest.

Published
2018
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11. A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

Author

Shiran Abadi, Winston X Yan, David Amar, and Itay Mayrose

Subjects
Biology (General), QH301-705.5
Abstract

The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.

Published
2017
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12. Extracting replicable associations across multiple studies: Empirical Bayes algorithms for controlling the false discovery rate.

Author

David Amar, Ron Shamir, and Daniel Yekutieli

Subjects
Biology (General), QH301-705.5
Abstract

In almost every field in genomics, large-scale biomedical datasets are used to report associations. Extracting associations that recur across multiple studies while controlling the false discovery rate is a fundamental challenge. Here, we propose a new method to allow joint analysis of multiple studies. Given a set of p-values obtained from each study, the goal is to identify associations that recur in at least k > 1 studies while controlling the false discovery rate. We propose several new algorithms that differ in how the study dependencies are modeled, and compare them and extant methods under various simulated scenarios. The top algorithm, SCREEN (Scalable Cluster-based REplicability ENhancement), is our new algorithm that works in three stages: (1) clustering an estimated correlation network of the studies, (2) learning replicability (e.g., of genes) within clusters, and (3) merging the results across the clusters. When we applied SCREEN to two real datasets it greatly outperformed the results obtained via standard meta-analysis. First, on a collection of 29 case-control gene expression cancer studies, we detected a large set of consistently up-regulated genes related to proliferation and cell cycle regulation. These genes are both consistently up-regulated across many cancer studies, and are well connected in known gene networks. Second, on a recent pan-cancer study that examined the expression profiles of patients with and without mutations in the HLA complex, we detected a large active module of up-regulated genes that are both related to immune responses and are well connected in known gene networks. This module covers thrice more genes as compared to the original study at a similar false discovery rate, demonstrating the high power of SCREEN. An implementation of SCREEN is available in the supplement.

Published
2017
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13. RichMind: A Tool for Improved Inference from Large-Scale Neuroimaging Results.

Author

Adi Maron-Katz, David Amar, Eti Ben Simon, Talma Hendler, and Ron Shamir

Subjects
Medicine, Science
Abstract

As the use of large-scale data-driven analysis becomes increasingly common, the need for robust methods for interpreting a large number of results increases. To date, neuroimaging attempts to interpret large-scale activity or connectivity results often turn to existing neural mapping based on previous literature. In case of a large number of results, manual selection or percent of overlap with existing maps is frequently used to facilitate interpretation, often without a clear statistical justification. Such methodology holds the risk of reporting false positive results and overlooking additional results. Here, we propose using enrichment analysis for improving the interpretation of large-scale neuroimaging results. We focus on two possible cases: position group analysis, where the identified results are a set of neural positions; and connection group analysis, where the identified results are a set of neural position-pairs (i.e. neural connections). We explore different models for detecting significant overrepresentation of known functional brain annotations using simulated and real data. We implemented our methods in a tool called RichMind, which provides both statistical significance reports and brain visualization. We demonstrate the abilities of RichMind by revisiting two previous fMRI studies. In both studies RichMind automatically highlighted most of the findings that were reported in the original studies as well as several additional findings that were overlooked. Hence, RichMind is a valuable new tool for rigorous inference from neuroimaging results.

Published
2016
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14. Dissection of regulatory networks that are altered in disease via differential co-expression.

Author

David Amar, Hershel Safer, and Ron Shamir

Subjects
Biology (General), QH301-705.5
Abstract

Comparing the gene-expression profiles of sick and healthy individuals can help in understanding disease. Such differential expression analysis is a well-established way to find gene sets whose expression is altered in the disease. Recent approaches to gene-expression analysis go a step further and seek differential co-expression patterns, wherein the level of co-expression of a set of genes differs markedly between disease and control samples. Such patterns can arise from a disease-related change in the regulatory mechanism governing that set of genes, and pinpoint dysfunctional regulatory networks. Here we present DICER, a new method for detecting differentially co-expressed gene sets using a novel probabilistic score for differential correlation. DICER goes beyond standard differential co-expression and detects pairs of modules showing differential co-expression. The expression profiles of genes within each module of the pair are correlated across all samples. The correlation between the two modules, however, differs markedly between the disease and normal samples. We show that DICER outperforms the state of the art in terms of significance and interpretability of the detected gene sets. Moreover, the gene sets discovered by DICER manifest regulation by disease-specific microRNA families. In a case study on Alzheimer's disease, DICER dissected biological processes and protein complexes into functional subunits that are differentially co-expressed, thereby revealing inner structures in disease regulatory networks.

Published
2013
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15. Transcriptional and proteomic analysis of the Aspergillus fumigatus ΔprtT protease-deficient mutant.

Author

Shelly Hagag, Paula Kubitschek-Barreira, Gabriela W P Neves, David Amar, William Nierman, Itamar Shalit, Ron Shamir, Leila Lopes-Bezerra, and Nir Osherov

Subjects
Medicine, Science
Abstract

Aspergillus fumigatus is the most common opportunistic mold pathogen of humans, infecting immunocompromised patients. The fungus invades the lungs and other organs, causing severe damage. Penetration of the pulmonary epithelium is a key step in the infectious process. A. fumigatus produces extracellular proteases to degrade the host structural barriers. The A. fumigatus transcription factor PrtT controls the expression of multiple secreted proteases. PrtT shows similarity to the fungal Gal4-type Zn(2)-Cys(6) DNA-binding domain of several transcription factors. In this work, we further investigate the function of this transcription factor by performing a transcriptional and a proteomic analysis of the ΔprtT mutant. Unexpectedly, microarray analysis revealed that in addition to the expected decrease in protease expression, expression of genes involved in iron uptake and ergosterol synthesis was dramatically decreased in the ΔprtT mutant. A second finding of interest is that deletion of prtT resulted in the upregulation of four secondary metabolite clusters, including genes for the biosynthesis of toxic pseurotin A. Proteomic analysis identified reduced levels of three secreted proteases (ALP1 protease, TppA, AFUA_2G01250) and increased levels of three secreted polysaccharide-degrading enzymes in the ΔprtT mutant possibly in response to its inability to derive sufficient nourishment from protein breakdown. This report highlights the complexity of gene regulation by PrtT, and suggests a potential novel link between the regulation of protease secretion and the control of iron uptake, ergosterol biosynthesis and secondary metabolite production in A. fumigatus.

Published
2012
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16. PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.

Author

Haim Sharon, David Amar, Emma Levdansky, Gabriel Mircus, Yana Shadkchan, Ron Shamir, and Nir Osherov

Subjects
Medicine, Science
Abstract

Aspergillus fumigatus is the most commonly encountered mold pathogen of humans, predominantly infecting the respiratory system. Colonization and penetration of the lung alveolar epithelium is a key but poorly understood step in the infection process. This study focused on identifying the transcriptional and cell-signaling responses activated in A549 alveolar carcinoma cells incubated in the presence of A. fumigatus wild-type and ΔPrtT protease-deficient germinating conidia and culture filtrates (CF). Microarray analysis of exposed A549 cells identified distinct classes of genes whose expression is altered in the presence of germinating conidia and CF and suggested the involvement of both NFkB and MAPK signaling pathways in mediating the cellular response. Phosphoprotein analysis of A549 cells confirmed that JNK and ERK1/2 are phosphorylated in response to CF from wild-type A. fumigatus and not phosphorylated in response to CF from the ΔPrtT protease-deficient strain. Inhibition of JNK or ERK1/2 kinase activity substantially decreased CF-induced cell damage, including cell peeling, actin-cytoskeleton damage, and reduction in metabolic activity and necrotic death. These results suggest that inhibition of MAPK-mediated host responses to treatment with A. fumigatus CF decreases cellular damage, a finding with possible clinical implications.

Published
2011
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25. Enhancement of photovoltaic array characteristics and global maximum power using Padovan transform‐based image encryption strategy.

Author

Naik, Kanasottu Anil, Raj, Rayappa David Amar, Babu, Thanikanti Sudhakar, and Aljafari, Belqasem

Subjects
*STATISTICAL hypothesis testing, *IMAGE encryption
Abstract

Summary: During shading, the mismatch between the panels in the photovoltaic (PV) array mitigates the global maximum power (GMP). Besides, the mismatch in the irradiation levels of distinct rows of the PV array instigates multiple power peaks (MPPs) in the array characteristics. Distinguishing the local and global peaks among MPPs for tracking the GMP is highly challenging for maximum power point tracking (MPPT) controllers. So, to mitigate the MPPs and enhance the GMP, array reconfiguration is preferred. Nevertheless, most existing reconfiguration techniques exhibit poor shade dispersal, distorted electrical characteristics, multiple MPPs, increased mismatch, scalability issues, etc. To overcome these challenges, this paper proposes a new Padovan transform‐based encryption strategy for array reconfiguration. The proposed method was evaluated for both symmetric and unsymmetrically sized arrays. Its performance has also been compared to that of 23 other strategies. The proposed reconfiguration strategy integrated with MPPT is validated experimentally using a prototype model. A nonparametric statistical hypothesis test with a p‐value of 0.05 has been used for a pairwise fair comparison study among the examined approaches. The proposed approach constantly outperforms the current methods because of its unique shade dispersion generated through intelligent reconfiguration offering the GMP improvement of 34.429%, 12.51%, 5.05%, and 37.40%, 22.93%, 16.51% for 9 × 9 and 4 × 8 PV arrays, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Amiodarone with or withoutN-Acetylcysteine for the Prevention of Atrial Fibrillation after Thoracic Surgery: A Double-blind, Randomized Trial

Author

David Amar, Hao Zhang, Mina K. Chung, Kay See Tan, Dawn Desiderio, Bernard J. Park, Alessia Pedoto, Nancy Roistacher, James M. Isbell, Daniela Molena, Ginger L. Milne, Bryan F. Meyers, Gregory W. Fischer, Valerie W. Rusch, and David R. Jones

Subjects
Anesthesiology and Pain Medicine
Abstract

BackgroundPostoperative atrial fibrillation may identify patients at risk of subsequent atrial fibrillation, with its greater risk of stroke. This study hypothesized that N-acetylcysteine mitigates inflammation and oxidative stress to reduce the incidence of postoperative atrial fibrillation.MethodsIn this double-blind, placebo-controlled trial, patients at high risk of postoperative atrial fibrillation scheduled to undergo major thoracic surgery were randomized to N-acetylcysteine plus amiodarone or placebo plus amiodarone. On arrival to the postanesthesia care unit, N-acetylcysteine or placebo intravenous bolus (50 mg/kg) and then continuous infusion (100 mg/kg over the course of 48 h) was administered plus intravenous amiodarone (bolus of 150 mg and then continuous infusion of 2 g over the course of 48 h). The primary outcome was sustained atrial fibrillation longer than 30 s by telemetry (first 72 h) or symptoms requiring intervention and confirmed by electrocardiography within 7 days of surgery. Systemic markers of inflammation (interleukin-6, interleukin-8, tumor necrosis factor α, C-reactive protein) and oxidative stress (F2-isoprostane prostaglandin F2α; isofuran) were assessed immediately after surgery and on postoperative day 2. Patients were telephoned monthly to assess the occurrence of atrial fibrillation in the first year.ResultsAmong 154 patients included, postoperative atrial fibrillation occurred in 15 of 78 who received N-acetylcysteine (19%) and 13 of 76 who received placebo (17%; odds ratio, 1.24; 95.1% CI, 0.53 to 2.88; P = 0.615). The trial was stopped at the interim analysis because of futility. Of the 28 patients with postoperative atrial fibrillation, 3 (11%) were discharged in atrial fibrillation. Regardless of treatment at 1 yr, 7 of 28 patients with postoperative atrial fibrillation (25%) had recurrent episodes of atrial fibrillation. Inflammatory and oxidative stress markers were similar between groups.ConclusionsDual therapy comprising N-acetylcysteine plus amiodarone did not reduce the incidence of postoperative atrial fibrillation or markers of inflammation and oxidative stress early after major thoracic surgery, compared with amiodarone alone. Recurrent atrial fibrillation episodes are common among patients with postoperative atrial fibrillation within 1 yr of major thoracic surgery.Editor’s PerspectiveWhat We Already Know about This TopicWhat This Article Tells Us That Is New

Published
2022
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37. The mitochondrial multi-omic response to exercise training across tissues

Author

Bingqing Zhao, Archana Natarajan Raja, Shruti Marwaha, David Amar, David Jimenez Morales, Charles Burant, and Megan Ramaker

Abstract

Mitochondria are adaptable organelles with diverse cellular functions critical to whole-body metabolic homeostasis. While chronic endurance exercise training is known to alter mitochondrial activity, these adaptations have not yet been systematically characterized. Here, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) mapped the longitudinal, multi-omic changes in mitochondrial analytes across 19 tissues in male and female rats endurance trained for 1, 2, 4 or 8 weeks. Training elicited substantial changes in the adrenal gland, brown adipose, colon, heart and skeletal muscle, while we detected mild responses in the brain, lung, small intestine and testes. The colon response was characterized by non-linear dynamics that resulted in upregulation of mitochondrial function that was more prominent in females. Brown adipose and adrenal tissues were characterized by substantial downregulation of mitochondrial pathways. Training induced a previously unrecognized robust upregulation of mitochondrial protein abundance and acetylation in the liver, and a concomitant shift in lipid metabolism. The striated muscles demonstrated a highly coordinated response to increase oxidative capacity, with the majority of changes occurring in protein abundance and post-translational modifications. We identified exercise upregulated networks that are downregulated in human type 2 diabetes and liver cirrhosis. In both cases HSD17B10, a central dehydrogenase in multiple metabolic pathways and mitochondrial tRNA maturation, was the main hub. In summary, we provide a multi-omic, cross-tissue atlas of the mitochondrial response to training and identify candidates for prevention of disease-associated mitochondrial dysfunction.

Published
2023
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40. Proceedings of Réanimation 2017, the French Intensive Care Society International Congress

Author

Bougouin, Wulfran, Marijon, Eloi, Planquette, Benjamin, Karam, Nicole, Dumas, Florence, Celermajer, David, Jost, Daniel, Lamhaut, Lionel, Beganton, Frankie, Cariou, Alain, Meyer, Guy, Jouven, Xavier, Bureau, Côme, Charpentier, Julien, Salem, Omar Ben Hadj, Guillemet, Lucie, Arnaout, Michel, Ferre, Alexis, Geri, Guillaume, Mongardon, Nicolas, Pène, Frédéric, Chiche, Jean-Daniel, Mira, Jean-Paul, Labro, Guylaine, Belon, François, Luu, Vinh-Phuc, Chenet, Julien, Besch, Guillaume, Puyraveau, Marc, Piton, Gaël, Capellier, Gilles, Martin, Maëlle, Lascarrou, Jean-Baptiste, Le Thuaut, Aurélie, Lacherade, Jean-Claude, Martin-Lefèvre, Laurent, Fiancette, Maud, Vinatier, Isabelle, Lebert, Christine, Bachoumas, Konstantinos, Yehia, Aihem, Henry-Laguarrigue, Matthieu, Colin, Gwenhaël, Reignier, Jean, Privat, Elodie, Escutnaire, Joséphine, Dumont, Cyrielle, Baert, Valentine, Vilhelm, Christian, Hubert, Hervé, Robert-Edan, Vincent, Lakhal, Karim, Quartin, Andrew, Hobbs, Brian, Cely, Cynthia, Bell, Cynthia, Pham, Tai, Schein, Roland, Geng, Yimin, Ng, Chaan, Ehrmann, Stephan, Gandonnière, Charlotte Salmon, Boisramé-Helms, Julie, Le Tilly, Olivier, De Bretagne, Isabelle Benz, Mercier, Emmanuelle, Mankikian, Julie, Bretagnol, Anne, Meziani, Ferhat, Halimi, Jean Michel, Le Guellec, Chantal Barin, Gaudry, Stéphane, Hajage, David, Tubach, Florence, Pons, Bertrand, Boulet, Eric, Boyer, Alexandre, Chevrel, Guillaume, Lerolle, Nicolas, Carpentier, Dorothée, de Prost, Nicolas, Lautrette, Alexandre, Mayaux, Julien, Nseir, Saad, Ricard, Jean-Damien, Dreyfuss, Didier, Robert, René, Garzotto, Franscesco, Kipnis, Eric, Tetta, Ciro, Ronco, Claudio, Schnell, David, Aurelie, Bourmaud, Reynaud, Marie, Clec’h, Christophe, Benyamina, Mourad, Vincent, François, Mariat, Christophe, Bornstain, Caroline, Rouleau, Stephane, Leroy, Christophe, Cohen, Yves, Morel, Jerome, Legrand, Matthieu, Terreaux, Jeremy, Darmon, Michaël, Cantier, Marie, Morisot, Adeline, Guérot, Emmanuel, Canet, Emmanuel, De Montmollin, Etienne, Voiriot, Guillaume, Neuville, Mathilde, Timsit, Jean-François, Sonneville, Romain, Fayssoil, Abdallah, Stojkovic, Tania, Behin, Anthony, Ogna, Adam, Lofaso, Frédéric, Laforet, Pascal, Wahbi, Karim, Prigent, Helene, Duboc, Denis, Orlikowski, David, Eymard, Bruno, Annane, Djillali, Le Guennec, Loic, Cholet, Clémentine, Bréchot, Nicolas, Hekimian, Guillaume, Besset, Sébastien, Lebreton, Guillaume, Nieszkowska, Ania, Trouillet, Jean Louis, Leprince, Pascal, Combes, Alain, Luyt, Charles-Edouard, Griton, Marion, Sesay, Musa, De Panthou, Nadia Sibaï, Bienvenu, Thomas, Biais, Matthieu, Nouette-Gaulain, Karine, Fossat, Guillaume, Baudin, Florian, Coulanges, Cécile, Bobet, Sabrine, Dupont, Arnaud, Courtes, Léa, Benzekri, Dalila, Kamel, Toufik, Muller, Grégoire, Bercault, Nicolas, Barbier, François, Runge, Isabelle, Skarzynski, Marie, Mathonnet, Armelle, Boulain, Thierry, Jouan, Youenn, Teixera, Noémie, Hassen-Khodja, Claire, Guillon, Antoine, Gaborit, Christophe, Grammatico-Guillon, Leslie, Rebière, Cécile, Azoulay, Elie, Misset, Benoit, Ruckly, Stephane, Garrouste-Orgeas, Maïté, Kentish-Barnes, Nancy, Duranteau, Jacques, Thuong, Marie, Joseph, Liliane, Renault, Anne, Lesieur, Olivier, Larbi, Anne-Gaelle Si, Viquesnel, Gérald, Zuber, Benjamin, Marque, Sophie, Kandelman, Stanislas, Pichon, Nicolas, Floccard, Bernard, Galon, Marion, Chevret, Sylvie, Kentish-Barnes, Nancy, Seegers, Valérie, Legriel, Stéphane, Jaber, Samir, Lefrant, Jean Yves, Reuter, Danielle, Guisset, Olivier, Cracco, Christophe, Seguin, Amélie, Durand-Gasselin, Jacques, Thirion, Marine, Cohen-Solal, Zoé, Foulgoc, Hélène, Rogier, Julien, Delobbe, Elsa, Schortgen, Frédérique, Asfar, Pierre, Julie, Boisramé-Helms, Grimaldi, David, Fabien, Grelon, Anguel, Nadia, Sigismond, Lasocki, Matthieu, Henry-Lagarrigue, Gonzalez, Frédéric, François, Legay, Guitton, Christophe, Schenck, Maleka, Jean-Marc, Doise, Radermacher, Peter, Kentish-Barnes, Nancy, Makunza, Joseph Nsiala, Nathalie, Mejeni Kamdem, Pierre, Akilimali, Adolphe, Kilembe Manzanza, Mahieu, Rafael, Reydel, Thomas, Jamet, Angéline, Chudeau, Nicolas, Huntzinger, Julien, Grange, Steven, Courte, Anne, Lemarie, Jérémie, Gibot, Sébastien, Champey, Julia, Dellamonica, Jean, Du Cheyron, Damien, Contou, Damien, Tadié, Jean-Marc, Cour, Martin, Beduneau, Gaetan, Marchalot, Antoine, Guérin, Laurent, Jochmans, Sebastien, Terzi, Nicolas, Preau, Sebastien, Brun-Buisson, Christian, Dessap, Armand Mekontso, Vedrenne-Cloquet, Meryl, Breinig, Sophie, Jung, Camille, Brussieux, Maxime, Marcoux, Marie-Odile, Durrmeyer, Xavier, Blondé, Renaud, Angoulvant, François, Grasset, Jérôme, Naudin, Jérôme, Dauger, Stéphane, Remy, Solenn, Kolev-Descamp, Karine, Demaret, Julie, Monneret, Guillaume, Javouhey, Etienne, Chomton, Maryline, Sauthier, Michaël, Vallieres, Emilie, Jouvet, Philippe, Geslain, Guillaume, Guellec, Isabelle, Rambaud, Jérôme, Schmidt, Matthieu, Schellongowski, Peter, Dorget, Amandine, Patroniti, Nicolo, Taccone, Fabio Silvio, Miranda, Dinis Reis, Reuter, Jean, Prodanovic, Hélène, Pierrot, Marc, Balik, Martin, Park, Sunghoon, Guérin, Claude, Papazian, Laurent, Jean, Reignier, Ayzac, Louis, Loundou, Anderson, Forel, Jean-Marie, Mezidi, Mehdi, Aublanc, Mylène, Perinel-Ragey, Sophie, Lissonde, Floriane, Louf-Durier, Aurore, Tapponnier, Romain, Yonis, Hodane, Coudroy, Remi, Frat, Jean-Pierre, Boissier, Florence, Thille, Arnaud W., Richard, Flore, Le Gullou-Guillemette, Hélène, Fahri, Jonathan, Kouatchet, Achille, Bodet-Contentin, Laetitia, Garot, Denis, Le Pennec, Déborah, Vecellio, Laurent, Tavernier, Elsa, Dequin, Pierre François, Messika, Jonathan, Martin, Yolaine, Maquigneau, Natacha, Puechberty, Christelle, Stoclin, Annabelle, Villard, Serge, Dechanet, Aline, De Jong, Audrey, Monnin, Marion, Girard, Mehdi, Chanques, Gérald, Molinari, Nicolas, Decavèle, Maxens, Campion, Sébastien, Ainsouya, Roukia, Niérat, Marie-Cécile, Raux, Mathieu, Similowski, Thomas, Demoule, Alexandre, Razazi, Keyvan, Tchir, Martial, May, Faten, Carteaux, Guillaume, Pauline, Rougevin-Baville, Marc, Andronikof, Bedos, Jean Pierre, Mehrsa, Koukabi, Mauger-Briche, Carole, Mijon, François, Trouiller, Pierre, Sztrymf, Benjamin, Cretallaz, Pierre, Mermillod-Blondin, Romain, Savary, Dominique, Sedghiani, Ines, Doghri, Hamdi, Jendoubi, Asma, Hamdi, Dhekra, Cherif, Mohamed Ali, Hechmi, Youssef Zied El, Zouheir, Jerbi, Persico, Nicolas, Maltese, Francois, Ferrigno, Cécile, Bablon, Amandine, Marmillot, Cécile, Roch, Antoine, Sedghiani, Ines, Papin, Grégory, Gainnier, Marc, Argaud, Laurent, Christophe, Adrie, Souweine, Bertrand, Goldgran-Toledano, Dany, Marcotte, Guillaume, Dumenil, Anne Sylvie, Carole, Schwebel, Cecchini, Jerôme, Tuffet, Samuel, Fartoukh, Muriel, Roux, Damien, Thyrault, Martial, Armand, Mekontso Dessap, Chauveau, Simon, Wesner, Nadège, Monnier-Cholley, Laurence, Bigé, Naïke, Ait-Oufella, Hafid, Guidet, Bertrand, Dubée, Vincent, Labroca, Pierre, Lemarié, Jérémie, Chiesa, Gérard, Laroyenne, Isabelle, Borrini, Léo, Klotz, Rémi, Sy, Quoc Phan, Cristina, Marie-Christine, Paysant, Jean, Fillâtre, Pierre, Gacouin, Arnaud, Revest, Matthieu, Tattevin, Pierre, Flecher, Erwan, Le Tulzo, Yves, Jamme, Matthieu, Daviaud, Fabrice, Marin, Nathalie, Thy, Michael, Duceau, Baptiste, Ardisson, Fanny, Sandrine, Valade, Venot, Marion, Schlemmer, Benoît, Zafrani, Lara, Pons, Stéphanie, Styfalova, Lenka, Bouadma, Lila, Radjou, Aguila, Lebut, Jordane, Mourvillier, Bruno, Dorent, Richard, Dilly, Marie-Pierre, Nataf, Patrick, Wolff, Michel, Le Gall, Aëlle, Bourcier, Simon, Tandjaoui-Lambiotte, Yacine, Das, Vincent, Alves, Mikael, Bigé, Naïke, Kamilia, Chtara, Rania, Ammar, Baccouch, Najeh, Turki, Olfa, Ben, Hmida Chokri, Bahloul, Mabrouk, Bouaziz, Mounir, Dupuis, Claire, Perozziello, Anne, Letheulle, Julien, Valette, Marc, Herrmann-Storck, Cécile, Crosby, Laura, Elkoun, Khalid, Madeux, Benjamin, Martino, Frédéric, Migueres, Hélène, Piednoir, Pascale, Posch, Matthias, Thiery, Guillaume, Huynh-Ky, Minh-Tu, Bouchard, Pierre Alexandre, Sarrazin, Jean-François, Lellouche, François, Nay, Mai-Anh, Lortat-Jacob, Brice, Rozec, Bertrand, Colnot, Marion, Belin, Nicolas, Barrot, Loïc, Navellou, Jean-Christophe, Patry, Cyrille, Chaignat, Claire, Claveau, Melanie, Claude, Frédéric, Aubron, Cécile, Mcquilten, Zoe, Bailey, Michael, Board, Jasmin, Buhr, Heidi, Cartwright, Bruce, Dennis, Mark, Forrest, Paul, Hodgson, Carol, Mcilroy, David, Murphy, Deirdre, Murray, Lynnette, Pellegrino, Vincent, Pilcher, David, Sheldrake, Jayne, Tran, Huyen, Vallance, Shirley, Cooper, Jamie, Bombled, Camille, Vidal, Charles, Margetis, Dimitri, Amour, Julien, Coart, Domien, Dubois, Jasperina, Van Herpe, Tom, Mesotten, Dieter, Bailly, Sébastien, Lucet, Jc, Lepape, Alain, L’hériteau, François, Aupée, Martine, Bervas, Caroline, Boussat, Sandrine, Berger-Carbonne, Anne, Machut, Anaïs, Savey, Anne, Tudesq, Jean-Jacques, Valade, Sandrine, Galicier, Lionel, De Bazelaire, Cédric, Munoz-Bongrand, Nicolas, Mignard, Xavier, Biard, Lucie, Mokart, Djamel, Nyunga, Martine, Bruneel, Fabrice, Rabbat, Antoine, Perez, Pierre, Meert, Anne Pascale, Benoit, Dominique, Mariotte, Eric, Ehooman, Franck, Hamidfar-Roy, Rebecca, Hourmant, Yannick, Mailloux, Arnaud, Beurton, Alexandra, Teboul, Jean-Louis, Girroto, Valentina, Laura, Galarza, Richard, Christian, Monnet, Xavier, Dubée, Vincent, Merdji, Hamid, Dang, Julien, Preda, Gabriel, Baudel, Jean-Luc, Desnos, Cyrielle, Zeitouni, Michel, Belaroussi, Ines, Parrot, Antoine, Blayau, Clarisse, Fulgencio, Jean-Pierre, Quesnel, Christophe, Labbe, Vincent, De Chambrun, Marc Pineton, Beloncle, François, Merceron, Sybille, Fedun, Yannick, Lecomte, Bernard, Devaquet, Jérôme, Puidupin, Marc, Verdière, Bruno, Amoura, Zahir, Vuillard, Constance, Xavier, Jais, Bourlier, Delphine, David, Amar, Caroline, Sattler, David, Montani, Gerald, Simmoneau, Olivier, Sitbon, Humbert, Marc, Laurent, Savale, Dujardin, Olivier, Bouglé, Adrien, Ait, Hamou Nora, Salem, Joe Elie, El-Helali, Najoua, Coppere, Zoé, Gibelin, Aude, Taconet, Clementine, Djibre, Michel, Maamar, Adel, Colobert, Elen, Fillatre, Pierre, Uhel, Fabrice, Camus, Christophe, Moraly, Josquin, Dahoumane, Redouane, Maury, Eric, Tan, Boun Kim, Emmanuel, Vivier, Pauline, Misslin, Laurence, Parmeland, Philippe, Poirié, Zahar, Jean-Ralph, Catherine, Haond, Christian, Pommier, Karim, Ait-Bouziad, Mounia, Hocine, Laura, Témime, Rasoldier, Vero Hanitra, Mager, Guy, Eraldi, Jean-Pierre, Gelinotte, Stéphanie, Bougerol, François, Dehay, Julien, Rigaud, Jean-Philippe, Declercq, Pierre Louis, Michel, Julien, Aissa, Nejla, Henard, Sandrine, Guerci, Philippe, Latar, Ichraq, Levy, Bruno, Girerd, Nicolas, Kimmoun, Antoine, Abdallah, Saousen Ben, Nakaa, Sabrine, Hraiech, Kmar, Braiek, Dhouha Ben, Adhieb, Ali, M’ghirbi, Abdelwaheb, Ousji, Ali, Hammouda, Zeineb, Abroug, Fekri, Sellami, Walid, Hajjej, Zied, Samoud, Walid, Labbene, Iheb, Ferjani, Mustapha, Medhioub, Fatma Kaaniche, Allela, Rania, Algia, Najla Ben, Cherif, Samar, Attia, Delphine, Herinjatovo, Andrianjafy, Francois, Xavier Laborne, Bouhouri, Med Aziz, Slaoui, Mohamed Taoufik, Soufi, A., Khaleq, K., Hamoudi, D., Nsiri, A., Harrar, R., Maury, Eric, Goursaud, Suzanne, Gauberti, Maxime, Labeyrie, Paul-Emile, Gaberel, Thomas, Agin, Véronique, Maubert, Eric, Vivien, Denis, Gakuba, Clément, Armel, Anwar, Abdou, Rchi, Kalouch, Samira, Yaqini, Khalid, Chlilek, Aziz, Sellami, Walid, Yedder, Soumaya Ben, Tonnelier, Alexandre, Hervé, Fabien, Halley, Guillaume, Frances, Jean-Luc, Moriconi, Mickael, Saoli, Mathieu, Garnero, Aude, Demory, Didier, Arnal, Jean Michel, Canoville, Bertrand, Daubin, Cédric, Brunet, Jennifer, Ghezala, Hassen Ben, Snouda, Salah, Ben, Chiekh Imen, Kaddour, Moez, Ouanes, Islem, Marzouk, Mahdi, Haniez, Françoise, Jaillet, Hélène, Maas, Henri, Andrivet, Pierre, Darné, Christian, Viau, François, Ghezala, Hassen Ben, Ouanes, Islem, Dangers, Laurence, Montlahuc, Claire, Perbet, Sébastien, Ouanes, Islem, Hamouda, Zeineb, Nakee, Sabrine, Ouanes-Besbes, Lamia, Meddeb, Khaoula, Khedher, Ahmed, Sma, Nesrine, Ayachi, Jihene, Khelfa, Messaouda, Fraj, Nesrine, Lakhal, Hend Ben, Hammed, Hedia, Boukadida, Raja, Hafsa, Hajer, Chouchene, Imed, Boussarsar, Mohamed, Ben, Braiek Dhouha, Ouanes-Besbes, Lamia, Benatti, Kaoutar, Dafir, A., Aissaoui, W., Elallame, W., Haddad, W., Cherkab, R., Elkettani, C., Barrou, L., Hamou, Zakaria Ait, Repessé, Xavier, Charron, Cyril, Aubry, Alix, Paternot, Alexis, Maizel, Julien, Slama, Michel, Vieillard-Baron, Antoine, Trifi, Ahlem, Abdellatif, Sami, Fatnassi, Meriem, Daly, Foued, Nasri, Rochdi, Ismail, Khaoula Ben, Lakhal, Salah Ben, Bazalgette, Florian, Daurat, Aurelien, Roger, Claire, Muller, Laurent, Doyen, Denis, Plattier, Rémi, Robert, Alexandre, Hyvernat, Hervé, Bernardin, Gilles, Jozwiak, Mathieu, Gimenez, Julia, Mercado, Pablo, Depret, François, Tilouch, Najla, Mater, Houda, Habiba, Ben Sik Ali, Jaoued, Oussama, Gharbi, Rim, Hassen, Mohamed Fekih, Elatrous, Souheil, Pasquier, Pierre, Vuillemin, Quentin, Schaal, Jean-Vivien, Martinez, Thibault, Duron, Sandrine, Trousselard, Marion, Schwartzbrod, Pierre-Eric, Baugnon, Thomas, Dupic, Laurent, Gout, Caroline Duracher, De Saint Blanquat, Laure, Séguret, Sylvie, Le Ficher, Gaelle, Orliaguet, Gilles, Hubert, Philippe, Bigé, Naïke, Leblanc, Guillaume, Briand, Raphael, Brousse, Lucas, Brunet, Valentine, Chatelain, Léonard, Prat, Dominique, Jacobs, Frédéric, Demars, Nadège, Hamzaoui, Olfa, Moneger, Guy, Sztrymf, Benjamin, Duburcq-Gury, Emilie, Satre-Buisson, Léa, Duburcq, Thibault, Poissy, Julien, Robriquet, Laurent, Jourdain, Merce, Sécheresse, Thierry, Miquet, Mattéo, Simond, Alexis, Usseglio, Pascal, Hamdaoui, Yamina, Boussarsar, Mohamed, Desailly, Victoire, Brun, Patrick, Iglesias, Pauline, Huet, Jérémie, Masseran, Clémence, Claudon, Antoine, Ebeyer, Clément, Truong, Thomas, Tesnière, Antoine, Mignon, Alexandre, Gaudry, Stéphane, Resiere, Dabor, Valentino, Ruddy, Fabre, Julien, Roze, Benoit, Ferge, Jean-Louis, Charbatier, Cyrille, Marie, Sabia, Scholsser, Michel, Aitsatou, Signate, Raad, Mathieu, Cabie, Andre, Mehdaoui, Hossein, Cousin, Clement, Rousseau, Christophe, Llitjos, Jean-François, Alby-Laurent, Fanny, Toubiana, Julie, Belaidouni, Nadia, Cherruault, Marlène, Tamburini, Jérome, Bouscary, Didier, Fert, Sarah, Delile, Eugénie, Besnier, Emmanuel, Coquerel, David, Nevière, Rémi, Richard, Vincent, Tamion, Fabienne, Wei, Chaojie, Louis, Huguette, Margaux, Schmitt, Eliane, Albuisson, Sophie, Orlowski, Kimmoun, Antoine, Riad, Zakaria, Coroir, Marine, Rémy, Bernard, Camille, Bombled, Joffre, Jeremie, Aegerter, Philippe, Ilic, Dejan, Ginet, Marc, Pignard, Caroline, Nguyen, Philippe, Mourey, Guillaume, Samain, Emmanuel, Pili-Floury, Sebastien, Jouffroy, Romain, Nicolas, Caill, Alvarez, Jean-Claude, Tomasso, Maraffi, Philippe, Pascal, Raphalen, Jean-Herlé, Frédéric, J. Baud, Vivien, Benoit, Pierre, Carli, Baud, Frederic, Fredj, Hana, Blel, Youssef, Brahmi, Nozha, Ghezala, Hassen Ben, Hanak, Anne-Sophie, Malissin, Isabelle, Poupon, Joel, Risede, Patricia, Chevillard, Lucie, Megarbane, Bruno, Barghouth, Manel, M’rad, Aymen, Hmida, Marwa Ben, Thabet, Hafedh, Liang, Hao, Callebert, Jacques, Lagard, Camille, Megarbane, Bruno, Habacha, Sahar, Chatbri, Bassem, Camillerapp, Christophe, Labat, Laurence, Soichot, Marion, Garçon, Pierre, Goury, Antoine, Kerdjana, Lamia, Voicu, Sebastian, Deye, Nicolas, Megarbane, Bruno, Armel, Anwar, Anas, Benqqa, Othman, Mezgui, Moumine, S., Kalouch, S., Yakini, K. K., Chlilek, A., Hajji, Ahmed, Louati, Assaad, Khaldi, Ammar, Borgi, Aida, Ghali, Nargess, Bouziri, Asma, Menif, Khaled, Ben, Jaballah Najla, Armel, Anwar, Brochon, Jeanne, Dumitrescu, Mihaela, Thévenot, Sarah, Saulnier, Jean-Pascal, Husseini, Khaled, Laland, Catherine, Cremniter, Julie, Bousseau, Anne, Castel, Olivier, Brémaud-Csizmadia, Cassandra, Diss, Margot, Portefaix, Aurélie, Berthiller, Julien, Gillet, Yves, Aoul, Nabil Tabet, Douah, Ali, Addou, Zakaria, Youbi, Houari, Moussati, Mohamed, Belhabiche, Kamel, Mir, Souad, Abada, Sanaa, Amel, Zerhouni, Aouffen, Nabil, Bouzit, Zina, Grati, Ahmed H., Dhonneur, Gilles F., Boussarsar, Mohamed, Lau, Nicolas, Mezhari, Ilham, Roucaud, Nicolas, Le Meur, Matthieu, Paulet, Rémi, Coudray, Jean-Michel, Ghomari, Wahiba Imène, Boumlik, Reda, Peigne, Vincent, Daban, Jean-Louis, Boutonnet, Mathieu, Lenoir, Bernard, Yassine, Hafiani, Mohamed, Cheikh Chaigar, Khalid, Allali, Ihssan, Moussaid, Said, Elyoussoufi, Said, Salmi, Jazia, Amira Ben, Fatima, Jaziri, Wafa, Skouri, Maha, Bennasr, Khaoula, Ben Abdelghni, Sami, Turki, Abdallah Taeib, B., Medhioub, Fatma Kaaniche, Rollet-Cohen, Virginie, Sachs, Philippe, Merchaoui, Zied, Renolleau, Sylvain, Oualha, Mehdi, Eloi, Maxime, Jean, Sandrine, Demoulin, Maryne, Valentin, Cécile, Guilbert, Julia, Walti, Hervé, Carbajal, Ricardo, Leger, Pierre-Louis, Karaca-Altintas, Yasemin, Botte, Astrid, Labreuche, Julien, Drumez, Elodie, Devos, Patrick, Bour, Franck, Leclerc, Francis, Ahmed, Ayari, khaled, Menif, Louati, Assaad, Aida, Borgi, Ammar, Khaldi, Narjess, Ghali, Ahmed, Hajji, Asma, Bouziri, Jaballah, Nejla Ben, Leger, Pierre-Louis, Pansiot, Julien, Besson, Valérie, Palmier, Bruno, Baud, Olivier, Cauli, Bruno, Charriaut-Marlangue, Christiane, Mansuy, Amélie, Michel, Fabrice, Le Bel, Stéphane, Boubnova, Julia, Ughetto, Fabrice, Ovaert, Caroline, Fouilloux, Virginie, Paut, Olivier, Jacquet-Lagrèze, Matthias, Tiebergien, Nicolas, Hanna, Najib, Evain, Jean-Noël, Baudin, Florent, Courtil-Teyssedre, Sonia, Bompard, Dominique, Lilot, Marc, Chardonal, Laurent, Fellahi, Jean-Luc, Claverie, Claire, Pouessel, Guillaume, Dorkenoo, Aimée, Renaudin, Jean-Marie, Eb, Mireille, Deschildre, Antoine, Leteurtre, Stéphane, Yassine, Hafiani, Kamal, Belkadi, Adil, Oboukhlik, Ouafa, Aalalam, Mouhamed, Moussaoui, Rachid, Charkab, Lahoucine, Barrou, Dachraoui, Fahmi, Nakkaa, Sabrine, Zaineb, Hammouda, Mlika, Dorra, Gloulou, Olfa, Boussarsar, Mohamed, Zelmat, Setti-Aouicha, Batouche, Djamila-Djahida, Chaffi, Belkacem, Mazour, Fatima, Benatta, Nadia, Fathallah, Ines, Aloui, Rafaa, Zoubli, Aymen, Kouraichi, Nadia, Fathallah, Ines, Kouraichi, N., Salem, Shireen, Vicaut, Eric, Megarbane, Bruno, Ambroise, David, Loriot, Anne-Marie, Bourgogne, Emmanuel, Megarbane, Bruno, Ghadhoune, Hatem, Jihene, Guissouma, Trabelsi, Insaf, Allouche, Hend, Brahmi, Habib, Samet, Mohamed, Ghord, Hatem El, Lebeau, Rodolphe, Laplanche, Jean-Louis, Benturquia, Nadia, Megarbane, Bruno, Blel, Youssef, M’rad, A., Essafi, Fatma, Benabderrahim, A., Jouffroy, Romain, Resiere, Dabor, Sanchez, Bruno, Inamo, Jocelyn, Megarbane, Bruno, Batouche, Djamila-Djahida, Zerhouni, Amel, Tabeliouna, Kheira, Negadi, Amine, Mentouri, Zahia, Le Gall, Fanny, Hanouz, Jean-Luc, Normand, Hervé, Khoury, Abdo, Sall, Fatimata Seydou, De Luca, Alban, Pugin, Aurore, Pazart, Lionel, Vidal, Chrystelle, Leroux, Franck, Khoury, Abdo, L’Her, Erwan, Marjanovic, Nicolas, Khoury, Abdo, Desmettre, Thibault, Lambert, Christophe, Ragey, Sophie Perinel, Baboi, Loredana, Bazin, Jean-Etienne, Koffel, Catherine, Dhonneur, Gilles, Bouzit, Zina, Bradai, Larbi, Ayed, Issam Ben, Aissa, Fethi, Haouache, Hakim, Marechal, Yoann, Biston, Patrick, Piagnerelli, Michael, Bortolotti, Perrine, Colling, Delphine, Colas, Vincent, Voisin, Benoit, Dewavrin, Florent, Onimus, Thierry, Girardie, Patrick, Saulnier, Fabienne, Urbina, Tomas, Nguyen, Yann, Druoton, Anne-Lise, Soudant, Marc, Barraud, Damien, Conrad, Marie, Cravoisy-Popovic, Aurélie, Nace, Lionel, Bollaert, Pierre-Edouard, Martin, Ruste, Bitker, Laurent, Richard, Jean-Christophe, Brossier, David, Goyer, Isabelle, Marquis, Christopher, Lampin, Marie, Duhamel, Alain, Béhal, Hélène, Dhaoui, Tahar, Godeffroy, Véronique, Devouge, Eve, Evrard, Dominique, Delepoulle, Florence, Racoussot, Sylvie, Grandbastien, Bruno, Lampin, Marie, Heilbronner, Claire, Roy, Emeline, Masson, Alexandra, Hadchouel-Duvergé, Alice, Rigourd, Virginie, Delacroix, Elise, Wroblewski, Isabelle, Pin, Isabelle, Ego, Anne, Payen, Valerie, Debillon, Thierry, Millet, Anne, Denot, Julien, Berthelot, Véronique, Thueux, Emilie, Reymond, Marie, De Larrard, Alexandra, Amblard, Alain, Leger, Pierre-Louis, Aoul, Nabil Tabet, Lemiale, Virginie, Oziel, Johanna, Brule, Noelle, Moreau, Anne-Sophie, Marhbène, Takoua, Sellami, Salma, Jamoussi, Amira, Ayed, Samia, Mhiri, Emna, Slim, Leila, Khelil, Jalila Ben, Besbes, Mohamed, Chawki, Sylvain, Hamdi, Aicha, Ciroldi, Magali, Cottereau, Alice, Obadia, Edouard, Zerbib, Yoann, Andrejak, Claire, Ricome, Sylvie, Dupont, Hervé, Baudin, François, Dureau, Pauline, Tanguy, Audrey, Arbelot, Charlotte, Ben, Hassen Kais, Charfeddine, Ahmed, Granger, Benjamin, Laporte, Lucile, Hermetet, Coralie, Regaieg, Kais, Khemakhem, Rim, Chelly, Hedi, Cheikh, Chaigar Mohammed, Mountij, Hamid, Rghioui, Kawtar, Haddad, Wafae, Cherkab, Rachid, Barrou, Houcine, Naima, Aitmouden, bennani, Othmani M., Regaieg, Kais, Douib, Ahmed, Samet, Amal, Cungi, Pierre-Julien, Nguyen, Cédric, Cotte, Jean, D’aranda, Erwan, Meaudre, Eric, Avaro, Jean-Phillipe, Slaoui, Mohamed Taoufik, Mokline, Amel, Rahmani, Imene, Laajili, Achraf, Amri, Helmi, Gharsallah, Lazheri, Gasri, Bahija, Tlaili, Sofiene, Hammouda, Rym, Messadi, Amen Allah, Sudden Death Expertise Center, AKIKI Study Group, DO-RE-MI-FA Group, ENCEPHALITICA Study Group, for the HYPER2S Investigators and REVA Research Network, for the Purpura Fulminans Study Group, GFRUP RMEF, REVA ECMOnet, REA-RAISIN Study Group, for the EurêClark Study Group, and Groupe Communication et Simulation en Pédiatrie

Published
2017
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41. Oncogenic context shapes the fitness landscape of tumor suppression

Author

Lily M. Blair, Joseph M. Juan, Lafia Sebastian, Vy B. Tran, Wensheng Nie, Gregory D. Wall, Mehmet Gerceker, Ian K. Lai, Edwin A. Apilado, Gabriel Grenot, David Amar, Giorgia Foggetti, Mariana Do Carmo, Zeynep Ugur, Debbie Deng, Alex Chenchik, Maria Paz Zafra, Lukas E. Dow, Katerina Politi, Jonathan J. MacQuitty, Dmitri A. Petrov, Monte M. Winslow, Michael J. Rosen, and Ian P. Winters

Abstract

Tumors acquire alterations in oncogenes and tumor suppressor genes in an adaptive walk through the fitness landscape of tumorigenesis. However, the features of this landscape remain poorly understood and cannot be revealed by human cancer genotyping alone. Here, we use a multiplexed, autochthonous mouse platform to model and quantify the initiation and growth of more than one hundred genotypes of lung tumors across four oncogenic contexts: KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R. The resulting fitness landscape is rugged (the effect of tumor suppressor inactivation often switches between beneficial and deleterious depending on the oncogenic context), shows no evidence of diminishing-returns epistasis within variants of the same oncogene, and is inconsistent with expectations of a simple linear signaling relationship among these three oncogenes. Our findings suggest that tumor suppressor effects are strongly context-specific, which limits the set of evolutionary paths that can be taken through the fitness landscape.

Published
2022
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43. Genetic architecture of cardiac dynamic flow volumes

Author

Bruna Gomes, Aditya Singh, Jack W O’Sullivan, David Amar, Mykhailo Kostur, Francois Haddad, Michael Salerno, Victoria N. Parikh, Benjamin Meder, and Euan A. Ashley

Abstract

Cardiac blood flow is a critical determinant of human health. However, definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep learning system to extract cardiac flow and volumes from phase contrast cardiac magnetic resonance imaging. A mixed linear model applied to 37,967 individuals from the UK Biobank reveals novel genome-wide significant associations across cardiac dynamic flow volumes including aortic forward velocity, total left ventricular stroke volume, forward left ventricular flow and aortic regurgitation fraction. Mendelian randomization using CAUSE reveals a causal role for aortic root size in aortic valve regurgitation. The most significant contributing variants (near ELN, FBN1 and ULK4) are implicated in connective tissue and blood pressure pathways. DeepFlow cardiac flow phenotyping at scale, combined with population-level genotyping data in the UK Biobank, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function in the general population.

Published
2022
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44. Temporal dynamics of the multi-omic response to endurance exercise training across tissues

Author

Jose Juan Almagro Armenteros, Sue Bodine, David Amar, Nasim Bararpour, Pierre Jean Beltran, and Charles Burant

Abstract

Regular exercise promotes whole-body health and prevents disease, yet the underlying molecular mechanisms throughout a whole organism are incompletely understood. Here, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome, and immunome in whole blood, plasma, and 18 solid tissues in Rattus norvegicus over 8 weeks of endurance exercise training. The resulting data compendium encompasses 9466 assays across 19 tissues, 25 molecular platforms, and 4 training time points in young adult male and female rats. We identified thousands of shared and tissue- and sex-specific molecular alterations. Temporal multi-omic and multi-tissue analyses demonstrated distinct patterns of tissue remodeling, with widespread regulation of immune, metabolism, heat shock stress response, and mitochondrial pathways. These patterns provide biological insights into the adaptive responses to endurance training over time. For example, exercise training induced heart remodeling via altered activity of the Mef2 family of transcription factors and tyrosine kinases. Translational analyses revealed changes that are consistent with human endurance training data and negatively correlated with disease, including increased phospholipids and decreased triacylglycerols in the liver. Sex differences in training adaptation were widespread, including those in the brain, adrenal gland, lung, and adipose tissue. Integrative analyses generated novel hypotheses of disease relevance, including candidate mechanisms that link training adaptation to non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health, and tissue injury and recovery. The data and analysis results presented in this study will serve as valuable resources for the broader community and are provided in an easily accessible public repository (https://motrpac-data.org/).HighlightsMulti-tissue resource identifies 35,439 analytes regulated by endurance exercise training at 5% FDR across 211 combinations of tissues and molecular platforms.Interpretation of systemic and tissue-specific molecular adaptations produced hypotheses to help describe the health benefits induced by exercise.Robust sex-specific responses to endurance exercise training are observed across multiple organs at the molecular level.Deep multi-omic profiling of six tissues defines regulatory signals for tissue adaptation to endurance exercise training.All data are available in a public repository, and processed data, analysis results, and code to reproduce major analyses are additionally available in convenient R packages.

Published
2022
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45. Ventilation during Lung Resection and Critical Care: Comparative Clinical Outcomes

Author

Spencer P. Walsh, David Shaz, and David Amar

Subjects
Anesthesiology and Pain Medicine, Critical Care, Humans, Pulmonary Surgical Procedures, Lung, One-Lung Ventilation
Abstract

Recent evidence suggests that outcomes do not meaningfully differ between thoracic surgery patients who are ventilated with a low or higher tidal volume and the effects of low versus higher positive end-expiratory pressure are unclear.

Published
2022

46. Liposomal Bupivacaine Versus Bupivacaine Hydrochloride for Intercostal Nerve Blockade in Minimally Invasive Thoracic Surgery

Author

Jovanka Noel, David Amar, Bernard J. Park, and Alessia Pedoto

Subjects
medicine.medical_specialty, Intercostal nerves, 030204 cardiovascular system & hematology, 03 medical and health sciences, 0302 clinical medicine, 030202 anesthesiology, medicine, Humans, Anesthetics, Local, Bupivacaine hydrochloride, Retrospective Studies, Pain, Postoperative, business.industry, Thoracic Surgery, Perioperative, Liposomal Bupivacaine, Bupivacaine, Analgesics, Opioid, Anesthesiology and Pain Medicine, Opioid, Cardiothoracic surgery, Anesthesia, Cohort, Intercostal Nerves, Cardiology and Cardiovascular Medicine, business, medicine.drug, Cohort study
Abstract

Objectives The objective of this study was to compare the effects of liposomal bupivacaine (Lipo-B) and bupivacaine hydrochloride (B-HCl), in the presence of multimodal analgesia, on postoperative analgesia and opioid consumption in minimally invasive thoracic surgery (MITS) lobectomy. Design Retrospective observational cohort study. Setting Tertiary care cancer center. Participants A total of 60 patients who underwent MITS lobectomy and received intercostal nerve blockade (ICNB) with either 0.66% Lipo-B (n = 29) or 0.5% B-HCl (n = 31). Interventions All patients received intravenous patient-controlled analgesia for the first 12 hours postoperatively, followed by opioids and nonsteroidal anti-inflammatory drugs as needed. Measurements and Main Results Perioperative opioid and nonopioid consumption and pain scores were compared between groups at 12-hour intervals for the first 72 hours. Between the two groups, there were no statistically significant differences in demographic characteristics, intraoperative (p = 0.46) and postoperative opioid consumption, Richmond Agitation-Sedation Scale scores and pain scores upon postanesthesia care unit arrival and after four hours, length of postanesthesia care unit stay (p = 0.84), or length of hospital stay (p = 0.55). Both groups received intra- and postoperative multimodal analgesia. Conclusions In this cohort, no differences in opioid consumption or pain scores were observed in the immediate postoperative period following MITS lobectomy between patients given ICNB with Lipo-B and those given ICNB with B-HCl in the presence of multimodal analgesia.

Published
2021
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48. Thoracic Metastasectomy in Germ Cell Tumor Patients Treated With First-line Versus Salvage Therapy

Author

George J. Bosl, Gaetano Rocco, Manjit S. Bains, David R. Jones, Samuel Funt, Daniela Molena, Raul Caso, David Amar, Darren R. Feldman, Joel Sheinfeld, Victor E. Reuter, Gregory W. Fischer, Gregory D. Jones, and Kay See Tan

Subjects
Adult, Male, Pulmonary and Respiratory Medicine, medicine.medical_specialty, medicine.medical_treatment, Salvage therapy, 030204 cardiovascular system & hematology, Gastroenterology, Disease-Free Survival, Article, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Testicular Neoplasms, Interquartile range, Internal medicine, Humans, Medicine, Neoplasm Metastasis, Neoplasm Staging, Retrospective Studies, Salvage Therapy, Chemotherapy, business.industry, Hazard ratio, Metastasectomy, Neoplasms, Germ Cell and Embryonal, Thoracic Surgical Procedures, Prognosis, medicine.disease, Primary tumor, 030228 respiratory system, Surgery, Lymph Nodes, Teratoma, Cardiology and Cardiovascular Medicine, business, Brain metastasis
Abstract

BACKGROUND Outcomes after thoracic metastasectomy in patients with testicular germ cell tumors (GCTs) who received first-line chemotherapy alone versus salvage chemotherapy remain unexplored. METHODS We conducted a retrospective review of patients who underwent thoracic metastasectomy for residual GCT between 1997 and 2019 at a single tertiary center. Factors associated with progression-free survival (PFS) and overall survival (OS) were assessed using multivariable Cox regression. RESULTS Of 251 patients, 191 received only first-line chemotherapy (76%) and 60 received salvage chemotherapy (24%). Median follow-up was 3.45 years (interquartile range, 1-7.93 years). Among first-line patients without teratoma in the primary tumor, with necrosis in the retroperitoneal nodes and normalized or decreasing serum tumor markers, 17 of 20 had intrathoracic necrosis (85%). Among first-line and salvage patients, respectively, 5-year OS was 93% (95% confidence interval [CI], 89%-98%) versus 63% (95% CI, 51%-78%; P < .001), and 5-year PFS was 69% (95% CI, 62%-77%) versus 40% (95% CI, 29%-56%; P < .001). On multivariable analysis, multiple lung lesions (hazard ratio [HR] = 3.01; 95% CI, 1.50-6.05; P = .002) and brain metastasis (HR = 4.51; 95% CI, 2.34-8.73; P < .001) at diagnosis, salvage chemotherapy (HR = 1.85; 95% CI, 1.10-3.13; P = .021), teratoma (HR = 2.68; 95% CI, 1.50-4.78; P = .001), and viable malignancy (HR = 4.34; 95% CI, 2.44-7.71; P < .001) were associated with worse PFS. CONCLUSIONS Although GCT patients treated with salvage chemotherapy followed by thoracic metastasectomy have more aggressive disease and poorer PFS, they can achieve encouraging OS. Our findings highlight the integral role of aggressive thoracic metastasectomy in the treatment of GCT patients with residual thoracic disease after first line-only or salvage chemotherapy.

Published
2021
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50. The genetic etiology of periodic limb movement in sleep

Author

Jacob L Edelson, Logan D Schneider, David Amar, Andreas Brink-Kjaer, Katie L Cederberg, Zoltán Kutalik, Erika W Hagen, Paul E Peppard, Priscila Farias Tempaku, Sergio Tufik, Daniel S Evans, Katie Stone, Greg Tranah, Brian Cade, Susan Redline, Jose Haba-Rubio, Raphael Heinzer, Pedro Marques-Vidal, Peter Vollenweider, Juliane Winkelmann, James Zou, and Emmanuel Mignot

Subjects
periodic limb movements, genome-wide association study, Neurology & Neurosurgery, Movement, Prevention, Psychology and Cognitive Sciences, Biological Sciences, Medical and Health Sciences, Cohort Studies, Genome Wide Association Study, Mendelian Randomization, Periodic Leg Movement, Restless Leg Syndrome, Restless Legs Syndrome, Sleep Initiation and Maintenance Disorders, Physiology (medical), Mendelian randomization, Genetics, Humans, 2.1 Biological and endogenous factors, Neurology (clinical), restless leg syndrome, Aetiology, Sleep, Sleep Research, Sleep, Health, and Disease
Abstract

Study Objectives Periodic limb movement in sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a genome-wide association study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of four cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6843 total subjects. Methods The MrOS study and Wisconsin Sleep Cohort Study (N = 1745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The causality and direction of the relationships between PLMS and RLS was evaluated using Mendelian randomization. Results We found 2 independent loci were significantly associated with PLMS: rs113851554 (p = 3.51 × 10−12, β = 0.486), an SNP located in a putative regulatory element of intron eight of MEIS1 (2p14); and rs9369062 (p = 3.06 × 10−22, β = 0.2093), a SNP located in the intron region of BTBD9 (6p12); both of which were also lead signals in RLS GWAS. PLMS is genetically correlated with insomnia, risk of stroke, and RLS, but not with iron deficiency. Pleiotropy adjusted Mendelian randomization analysis identified a causal effect of RLS on PLMS. Conclusions Because PLMS is more common than RLS, PLMS may have multiple causes and additional studies are needed to further validate these findings.

Published
2022
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