Les effets des débats à visée philosophique à partir d'œuvres de littérature de jeunesse sur le rapport au savoir

Partant de la difficulté scolaire, ce mémoire a pour objectif de mesurer les effets des débats à visée philosophique à partir d'œuvres de littérature de jeunesse sur le rapport au savoir. À travers un cadre théorique qui explore trois dimensions liées à ce sujet, le rapport au savoir, les débats à visée philosophique et la littérature de jeunesse, nous avons pu faire émerger une problématique : la réflexion à visée philosophique à partir d'œuvres de littérature de jeunesse porteuses de sens peut-elle favoriser un rapport au savoir positif ? Celle-ci nous a amené à élaborer une méthodologie de recherche qui lie théorique et pratique, à travers des observations sur le terrain et des entretiens avec des acteurs de l'éducation. Nous avons pu ainsi recueillir des données qui ont été exploitées et analysées afin de répondre à cette question

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Developments and opportunities with Workflow4Metabolomics

International audienceMetabolomics data analysis is a complex, multistep process, constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. Workflow4Metabolomics[1] is a collaborative portal dedicated to metabolomics data processing, analysis and annotation for the Metabolomics community. In the latest version of W4M, the core team proposes new upgrades for LC-MS, GC-MS and NMR pipelines, including new preprocessing steps, as well as enhancement of statistical analysis and annotation tools. W4M aims to promote open science in Metabolomics and facilitate knowledge dissemination by providing community resources

Update on technological developments and opportunities with Workflow4Metabolomics

International audienceIntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw34

Developments and opportunities with Workflow4Metabolomics

International audienceMetabolomics data analysis is a complex, multistep process, constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. Workflow4Metabolomics[1] is a collaborative portal dedicated to metabolomics data processing, analysis and annotation for the Metabolomics community. In the latest version of W4M, the core team proposes new upgrades for LC-MS, GC-MS and NMR pipelines, including new preprocessing steps, as well as enhancement of statistical analysis and annotation tools. W4M aims to promote open science in Metabolomics and facilitate knowledge dissemination by providing community resources

Update on technological developments and opportunities with Workflow4Metabolomics

International audienceIntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw34

Update on technological developments and opportunities with Workflow4Metabolomics

International audienceIntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw34

Update on technological developments and opportunities with Workflow4Metabolomics

International audienceIntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw34

Developments and opportunities with Workflow4Metabolomics

International audienceMetabolomics data analysis is a complex, multistep process, constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. Workflow4Metabolomics[1] is a collaborative portal dedicated to metabolomics data processing, analysis and annotation for the Metabolomics community. In the latest version of W4M, the core team proposes new upgrades for LC-MS, GC-MS and NMR pipelines, including new preprocessing steps, as well as enhancement of statistical analysis and annotation tools. W4M aims to promote open science in Metabolomics and facilitate knowledge dissemination by providing community resources