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10.1038/s41467-022-28505-3 http://scihub22266oqcxt.onion/10.1038/s41467-022-28505-3 35169146!8847593!35169146     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       Nat+Commun 2022 ; 13 (1): 882 Nephropedia Template TP {{tp|p=35169146|t=2022. Cell specific peripheral immune responses predict survival in critical COVID-19 patients |pdf=|usr=}}{{35169146}} gab.com Text Cell specific peripheral immune responses predict survival in critical COVID-19 patients JO: Nat Commun http://www.kidney.de/pget.php?&tw=1&pmid=35169146 #FOAvip SARS-CoV-2 triggers a complex systemic immune response in circulating blood mononuclear cells. The relationship between immune cell activation of the peripheral compartment and survival in critical COVID-19 remains to be established. Here we use single-cell RNA sequencing and Cellular Indexing of Transcriptomes and Epitomes by sequence mapping to elucidate cell type specific transcriptional signatures that associate with and predict survival in critical COVID-19. Patients who survive infection display activation of antibody processing, early activation response, and cell cycle regulation pathways most prominent within B-, T-, and NK-cell subsets. We further leverage cell specific differential gene expression and machine learning to predict mortality using single cell transcriptomes. We identify interferon signaling and antigen presentation pathways within cDC2 cells, CD14 monocytes, and CD16 monocytes as predictors of mortality with 90% accuracy. Finally, we validate our findings in an independent transcriptomics dataset and provide a framework to elucidate mechanisms that promote survival in critically ill COVID-19 patients. Identifying prognostic indicators among critical COVID-19 patients holds tremendous value in risk stratification and clinical management. Twit Text FOAVip Cell specific peripheral immune responses predict survival in critical COVID-19 patients ????Nat Commun http://www.kidney.de/pget.php?&tw=1&pmid=35169146 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35169146 #FOAvip English Wikipedia <ref>{{Cite pmid|35169146}}</ref> Cell specific peripheral immune responses predict survival in critical COVID-19 patients #MMPMID35169146 Amrute JM; Perry AM; Anand G; Cruchaga C; Hock KG; Farnsworth CW; Randolph GJ; Lavine KJ; Steed AL Nat Commun 2022[Feb]; 13 (1): 882 PMID35169146show ga SARS-CoV-2 triggers a complex systemic immune response in circulating blood mononuclear cells. The relationship between immune cell activation of the peripheral compartment and survival in critical COVID-19 remains to be established. Here we use single-cell RNA sequencing and Cellular Indexing of Transcriptomes and Epitomes by sequence mapping to elucidate cell type specific transcriptional signatures that associate with and predict survival in critical COVID-19. Patients who survive infection display activation of antibody processing, early activation response, and cell cycle regulation pathways most prominent within B-, T-, and NK-cell subsets. We further leverage cell specific differential gene expression and machine learning to predict mortality using single cell transcriptomes. We identify interferon signaling and antigen presentation pathways within cDC2 cells, CD14 monocytes, and CD16 monocytes as predictors of mortality with 90% accuracy. Finally, we validate our findings in an independent transcriptomics dataset and provide a framework to elucidate mechanisms that promote survival in critically ill COVID-19 patients. Identifying prognostic indicators among critical COVID-19 patients holds tremendous value in risk stratification and clinical management. |Aged[MESH] |Aged, 80 and over[MESH] |COVID-19/genetics/*immunology/mortality[MESH] |Critical Illness[MESH] |Female[MESH] |Gene Expression[MESH] |Humans[MESH] |Immunity, Cellular/genetics/*immunology[MESH] |Leukocytes, Mononuclear/immunology[MESH] |Longitudinal Studies[MESH] |Male[MESH] |Middle Aged[MESH] |Prognosis[MESH] |Reproducibility of Results[MESH] |SARS-CoV-2/pathogenicity[MESH] |Single-Cell Analysis[MESH]Cell specific peripheral immune responses predict survival in critical(epmc).pdf DeepDyve Pubget Overpricing