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10.1007/s00018-021-03808-8 http://scihub22266oqcxt.onion/10.1007/s00018-021-03808-8 33715015!7955698!33715015     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Cell+Mol+Life+Sci 2021 ; 78 (8): 3987-4002 Nephropedia Template TP {{tp|p=33715015|t=2021. High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients |pdf=|usr=}}{{33715015}} gab.com Text High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients JO: Cell Mol Life Sci http://www.kidney.de/pget.php?&tw=1&pmid=33715015 #FOAvip The COVID-19 pandemic poses a major burden on healthcare and economic systems across the globe. Even though a majority of the population develops only minor symptoms upon SARS-CoV-2 infection, a significant number are hospitalized at intensive care units (ICU) requiring critical care. While insights into the early stages of the disease are rapidly expanding, the dynamic immunological processes occurring in critically ill patients throughout their recovery at ICU are far less understood. Here, we have analysed whole blood samples serially collected from 40 surviving COVID-19 patients throughout their recovery in ICU using high-dimensional cytometry by time-of-flight (CyTOF) and cytokine multiplexing. Based on the neutrophil-to-lymphocyte ratio (NLR), we defined four sequential immunotypes during recovery that correlated to various clinical parameters, including the level of respiratory support at concomitant sampling times. We identified classical monocytes as the first immune cell type to recover by restoration of HLA-DR-positivity and the reduction of immunosuppressive CD163 + monocytes, followed by the recovery of CD8 + and CD4 + T cell and non-classical monocyte populations. The identified immunotypes also correlated to aberrant cytokine and acute-phase reactant levels. Finally, integrative analysis of cytokines and immune cell profiles showed a shift from an initially dysregulated immune response to a more coordinated immunogenic interplay, highlighting the importance of longitudinal sampling to understand the pathophysiology underlying recovery from severe COVID-19. Twit Text FOAVip High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients ????Cell Mol Life Sci http://www.kidney.de/pget.php?&tw=1&pmid=33715015 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33715015 #FOAvip English Wikipedia <ref>{{Cite pmid|33715015}}</ref> High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients #MMPMID33715015 Penttila PA; Van Gassen S; Panovska D; Vanderbeke L; Van Herck Y; Quintelier K; Emmaneel A; Filtjens J; Malengier-Devlies B; Ahmadzadeh K; Van Mol P; Borras DM; Antoranz A; Bosisio FM; Wauters E; Martinod K; Matthys P; Saeys Y; Garg AD; Wauters J; De Smet F Cell Mol Life Sci 2021[Apr]; 78 (8): 3987-4002 PMID33715015show ga The COVID-19 pandemic poses a major burden on healthcare and economic systems across the globe. Even though a majority of the population develops only minor symptoms upon SARS-CoV-2 infection, a significant number are hospitalized at intensive care units (ICU) requiring critical care. While insights into the early stages of the disease are rapidly expanding, the dynamic immunological processes occurring in critically ill patients throughout their recovery at ICU are far less understood. Here, we have analysed whole blood samples serially collected from 40 surviving COVID-19 patients throughout their recovery in ICU using high-dimensional cytometry by time-of-flight (CyTOF) and cytokine multiplexing. Based on the neutrophil-to-lymphocyte ratio (NLR), we defined four sequential immunotypes during recovery that correlated to various clinical parameters, including the level of respiratory support at concomitant sampling times. We identified classical monocytes as the first immune cell type to recover by restoration of HLA-DR-positivity and the reduction of immunosuppressive CD163 + monocytes, followed by the recovery of CD8 + and CD4 + T cell and non-classical monocyte populations. The identified immunotypes also correlated to aberrant cytokine and acute-phase reactant levels. Finally, integrative analysis of cytokines and immune cell profiles showed a shift from an initially dysregulated immune response to a more coordinated immunogenic interplay, highlighting the importance of longitudinal sampling to understand the pathophysiology underlying recovery from severe COVID-19. |*Critical Illness[MESH] |*Leukocyte Count[MESH] |*SARS-CoV-2[MESH] |Acute-Phase Proteins/analysis[MESH] |Antigens, CD/analysis[MESH] |COVID-19/blood/*immunology[MESH] |Convalescence[MESH] |Cytokines/blood[MESH] |Female[MESH] |Follow-Up Studies[MESH] |HLA-DR Antigens/analysis[MESH] |Humans[MESH] |Intensive Care Units/statistics & numerical data[MESH] |Length of Stay/statistics & numerical data[MESH] |Lymphocyte Count[MESH] |Lymphocyte Subsets[MESH] |Male[MESH] |Middle Aged[MESH] |Monocytes[MESH] |Neutrophils[MESH] |Pandemics[MESH] |Prognosis[MESH]High dimensional profiling identifies specific immune types along the (epmc).pdf DeepDyve Pubget Overpricing