Source: Annual Congress 2013 –Infection, sepsis and outcomes in ICU



Rating:

Share or cite this content

Citations should be made in the following way:
L. Su, Y. Huang, Y. Zhu, K. Xiao, L. Cao, L. Xie (Sanyan, Tianjin, Beijing, Shenzhen, China). Discrimination of sepsis metabolic profiles revealed by LC/MS-MS based metabonomics approach. Eur Respir J 2013; 42: Suppl. 57, 2444

Member's Comments

No comment yet.

Related content which might interest you: Preliminary proteomics analysis for sepsis biomarkers with iTRAQ labeling and LC-MS/MS Source: Annual Congress 2013 –Research questions on how viruses affect the respiratory system Year: 2013 High-throughput analysis of induced sputum from the U-BIOPRED study using novel proteomic and data mining approaches Source: Annual Congress 2013 –Origins and diagnosis of asthma Year: 2013 Plasma metabolomic signature in COPD patients: Associations to proteomic profile and clinical outcomes Source: Annual Congress 2013 –COPD mechanisms Year: 2013 Proteome fingerprints define groups with distinct clinico-pathological phenotypes in the U-BIOPRED asthma study Source: International Congress 2016 – What's new in biomarker analysis? Year: 2016 Sputum supernatant profiling reveals inflammasome-associated signatures in severe asthmatics in U-BIOPRED Source: International Congress 2015 – Advances in the future treatment of severe asthma Year: 2015 Metabolomic profiling of clinical sputum samples reveals novel biomarkers for the early identification of lung cancer patients Source: International Congress 2014 – Improving diagnosis of thoracic tumours Year: 2014 Metabolomic profiling differences among asthma, COPD and healthy controls: a LC-MS-based metabolomics analysis Source: International Congress 2019 – Evaluation of basic science in airway diseases Year: 2019 New approaches to tuberculosis diagnosis through the study of metabolomic profile in urine Source: Annual Congress 2013 –Tuberculosis diagnosis Year: 2013 Metabolomic fingerprinting in the identification of biomarkers in COPD patients Source: Annual Congress 2012 - Basic and translational studies in COPD Year: 2012 Unbiased cluster analysis of severe asthma based on metabolomics by the U-BIOPRED electronic nose platform Source: Annual Congress 2013 –Asthma and COPD: diseases with different phenotypes Year: 2013 Mass spectrometry methods for biomarker research for chronic lung allograft dysfunction (CLAD) in systems prediction of CLAD (SysCLAD) Source: International Congress 2014 – Novel approaches in the management of lung transplant candidates and recipients Year: 2014 A multi-omics data integration approach to identify a predictive molecular signature of CLAD Source: International Congress 2015 – Predictors of lung transplant complications Year: 2015 Large-scale quantitative proteomic analysis identifies pathways in COPD-associated lung cancer Source: International Congress 2015 – Cell biology of lung cancer and new biomarkers Year: 2015 Benchtop NMR-based metabolomic analysis as a diagnostic tool for tuberculosis in clinical urine samples Source: International Congress 2019 – Tuberculosis: diagnosis Year: 2019 Identification of serum biomarkers associated with asthma phenotypes through Combinatorial Hexapeptide Ligand Libraries (CPLLs) and iTRAQ-coupled LC-MS/MS. Source: International Congress 2019 – Modelling and monitoring of airway diseases Year: 2019 The identification of asthma phenotypes by categorical PCA: Combinatorial analysis of clinical parameters and dysfunctional blood eosinophils Source: International Congress 2014 – Non inflammatory monitoring of airway diseases Year: 2014 Exploiting metabolomic approaches to aid in the diagnosis of lung cancer Source: International Congress 2016 – Prognostic variables in lung cancer II Year: 2016 LSC Abstract – Systemic and local metabolomics profiling reveals novel insights into the progression of emphysema Source: International Congress 2016 – New therapies and therapeutic targets Year: 2016 Novel proteomic biomarkers in the evaluation of childhood asthma Source: Annual Congress 2013 –Monitoring asthma: genes, cells and molecules Year: 2013