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10.1016/j.compbiomed.2021.104792 http://scihub22266oqcxt.onion/10.1016/j.compbiomed.2021.104792 34478921!8390121!34478921     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Comput+Biol+Med 2021 ; 137 (ä): 104792 Nephropedia Template TP {{tp|p=34478921|t=2021. Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients |pdf=|usr=}}{{34478921}} gab.com Text Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients JO: Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=34478921 #FOAvip Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the global coronavirus disease 2019 (COVID-19) pandemic. Despite several single-cell RNA sequencing (RNA-seq) studies, conclusions cannot be reached owing to the small number of available samples and the differences in technology and tissue types used in the studies. To better understand the cellular landscape and disease severity in COVID-19, we performed a meta-analysis of publicly available single-cell RNA-seq data from peripheral blood and lung samples of COVID-19 patients with varying degrees of severity. Patients with severe disease showed increased numbers of M1 macrophages in lung tissue, while the number of M2 macrophages was depleted. Cellular profiling of the peripheral blood showed a marked increase of CD14(+), CD16(+) monocytes and a concomitant depletion of overall B cells and CD4(+), CD8(+) T cells in severe patients when compared with moderate patients. Our analysis indicates the presence of faulty innate-to-adaptive switching, marked by a prolonged innate immune response and a dysregulated adaptive immune response in severe COVID-19 patients. Furthermore, we identified cell types with a transcriptome signature that can be used as a prognostic biomarker for disease state prediction and the effective therapeutic management of COVID-19 patients. Twit Text FOAVip Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients ????Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=34478921 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34478921 #FOAvip English Wikipedia <ref>{{Cite pmid|34478921}}</ref> Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients #MMPMID34478921 Hasan MZ; Islam S; Matsumoto K; Kawai T Comput Biol Med 2021[Oct]; 137 (ä): 104792 PMID34478921show ga Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the global coronavirus disease 2019 (COVID-19) pandemic. Despite several single-cell RNA sequencing (RNA-seq) studies, conclusions cannot be reached owing to the small number of available samples and the differences in technology and tissue types used in the studies. To better understand the cellular landscape and disease severity in COVID-19, we performed a meta-analysis of publicly available single-cell RNA-seq data from peripheral blood and lung samples of COVID-19 patients with varying degrees of severity. Patients with severe disease showed increased numbers of M1 macrophages in lung tissue, while the number of M2 macrophages was depleted. Cellular profiling of the peripheral blood showed a marked increase of CD14(+), CD16(+) monocytes and a concomitant depletion of overall B cells and CD4(+), CD8(+) T cells in severe patients when compared with moderate patients. Our analysis indicates the presence of faulty innate-to-adaptive switching, marked by a prolonged innate immune response and a dysregulated adaptive immune response in severe COVID-19 patients. Furthermore, we identified cell types with a transcriptome signature that can be used as a prognostic biomarker for disease state prediction and the effective therapeutic management of COVID-19 patients. |*COVID-19[MESH] |*RNA[MESH] |CD8-Positive T-Lymphocytes[MESH] |Humans[MESH] |SARS-CoV-2[MESH]Meta-analysis of single-cell RNA-seq data reveals phenotypic switching(epmc).pdf DeepDyve Pubget Overpricing