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10.26508/lsa.202101099 http://scihub22266oqcxt.onion/10.26508/lsa.202101099 34226277!8321673!34226277     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Life+Sci+Alliance 2021 ; 4 (9): ä Nephropedia Template TP {{tp|p=34226277|t=2021. A serum proteome signature to predict mortality in severe COVID-19 patients |pdf=|usr=}}{{34226277}} gab.com Text A serum proteome signature to predict mortality in severe COVID-19 patients JO: Life Sci Alliance http://www.kidney.de/pget.php?&tw=1&pmid=34226277 #FOAvip Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-alpha-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria. Twit Text FOAVip A serum proteome signature to predict mortality in severe COVID-19 patients ????Life Sci Alliance http://www.kidney.de/pget.php?&tw=1&pmid=34226277 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34226277 #FOAvip English Wikipedia <ref>{{Cite pmid|34226277}}</ref> A serum proteome signature to predict mortality in severe COVID-19 patients #MMPMID34226277 Vollmy F; van den Toorn H; Zenezini Chiozzi R; Zucchetti O; Papi A; Volta CA; Marracino L; Vieceli Dalla Sega F; Fortini F; Demichev V; Tober-Lau P; Campo G; Contoli M; Ralser M; Kurth F; Spadaro S; Rizzo P; Heck AJ Life Sci Alliance 2021[Sep]; 4 (9): ä PMID34226277show ga Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-alpha-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria. |*Severity of Illness Index[MESH] |Aged[MESH] |COVID-19/*blood/*mortality/virology[MESH] |Cohort Studies[MESH] |Female[MESH] |Hospitalization[MESH] |Humans[MESH] |Immunoglobulins/blood[MESH] |Male[MESH] |Proteome/*metabolism[MESH] |SARS-CoV-2/physiology[MESH]A serum proteome signature to predict mortality in severe COVID-19 pat(epmc).pdf DeepDyve Pubget Overpricing