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10.3389/fimmu.2016.00126 http://scihub22266oqcxt.onion/10.3389/fimmu.2016.00126 C4827377!4827377!27148254     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Immunol 2016 ; 7 (ä): ä Nephropedia Template TP {{tp|p=27148254|t=2016. PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients |pdf=|usr=}}{{27148254}} gab.com Text PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients JO: Front Immunol http://www.kidney.de/pget.php?&tw=1&pmid=27148254 #FOAvip We tested whether multi-parameter immune phenotyping before or after renal ­transplantation can predict the risk of rejection episodes. Blood samples collected before and weekly for 3?months after transplantation were analyzed by multi-parameter flow cytometry to define 52 T cell and 13 innate lymphocyte subsets in each sample, producing more than 11,000 data points that defined the immune status of the 28 patients included in this study. Principle component analysis suggested that the patients with histologically confirmed rejection episodes segregated from those without rejection. Protein death 1 (PD-1)-expressing subpopulations of regulatory and conventional T cells had the greatest influence on the principal component segregation. We constructed a statistical tool to predict rejection using a support vector machine algorithm. The algorithm correctly identified 7 out of 9 patients with rejection, and 14 out of 17 patients without rejection. The immune profile before transplantation was most accurate in determining the risk of rejection, while changes of immune parameters after transplantation were less accurate in discriminating rejection from non-rejection. The data indicate that pretransplant immune subset analysis has the potential to identify patients at risk of developing rejection episodes, and suggests that the proportion of PD1-expressing T cell subsets may be a key indicator of rejection risk. Twit Text FOAVip PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients ????Front Immunol http://www.kidney.de/pget.php?&tw=1&pmid=27148254 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27148254 #FOAvip English Wikipedia <ref>{{Cite pmid|27148254}}</ref> PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients #MMPMID27148254 Pike R; Thomas N; Workman S; Ambrose L; Guzman D; Sivakumaran S; Johnson M; Thorburn D; Harber M; Chain B; Stauss HJ Front Immunol 2016[]; 7 (ä): ä PMID27148254show ga We tested whether multi-parameter immune phenotyping before or after renal ­transplantation can predict the risk of rejection episodes. Blood samples collected before and weekly for 3?months after transplantation were analyzed by multi-parameter flow cytometry to define 52 T cell and 13 innate lymphocyte subsets in each sample, producing more than 11,000 data points that defined the immune status of the 28 patients included in this study. Principle component analysis suggested that the patients with histologically confirmed rejection episodes segregated from those without rejection. Protein death 1 (PD-1)-expressing subpopulations of regulatory and conventional T cells had the greatest influence on the principal component segregation. We constructed a statistical tool to predict rejection using a support vector machine algorithm. The algorithm correctly identified 7 out of 9 patients with rejection, and 14 out of 17 patients without rejection. The immune profile before transplantation was most accurate in determining the risk of rejection, while changes of immune parameters after transplantation were less accurate in discriminating rejection from non-rejection. The data indicate that pretransplant immune subset analysis has the potential to identify patients at risk of developing rejection episodes, and suggests that the proportion of PD1-expressing T cell subsets may be a key indicator of rejection risk. äPD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Trans(epmc).pdf DeepDyve Pubget Overpricing