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10.1186/s12967-018-1584-6 http://scihub22266oqcxt.onion/10.1186/s12967-018-1584-6 C6053779!6053779!30029606     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Transl+Med 2018 ; 16 (ä): ä Nephropedia Template TP {{tp|p=30029606|t=2018. GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection |pdf=|usr=}}{{30029606}} gab.com Text GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection JO: J Transl Med http://www.kidney.de/pget.php?&tw=1&pmid=30029606 #FOAvip Background: Acute renal allograft rejection is a common complication after renal transplantation that often leads to chronic rejection and ultimate graft loss. While renal allograft biopsy remains the gold standard for diagnosis of acute rejection, the possibility of biopsy-associated complications cannot be overlooked. The development of noninvasive methods for accurate detection of acute renal allograft rejection is thus of significant clinical importance. Methods: Gas chromatography?mass spectrometry (GC/MS) was employed for analysis of urine metabolites in 15 renal allograft recipients with acute rejection and 15 stable renal transplant recipients. Partial least squares (PLS) regression and leave-one-out analyses were performed to ascertain whether the metabolites identified could be exploited to distinguish acute rejection from stable groups as well as their sensitivity and specificity. Results: Overall, 14 metabolites were significantly altered in the acute rejection group (11 and 3 metabolites displayed higher and lower levels, respectively) relative to the stable transplant group. Data from PLS and leave-one-out analyses revealed that the differential metabolites identified not only distinguished acute rejection from stable transplant recipients but also showed high sensitivity and specificity for diagnosis of renal allograft recipients with acute rejection. Conclusion: Urine metabolites identified with GC/MS can effectively distinguish acute rejection from stable transplant recipients, supporting the potential utility of metabolome analysis in non-invasive diagnosis of acute rejection. Twit Text FOAVip GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection ????J Transl Med http://www.kidney.de/pget.php?&tw=1&pmid=30029606 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=30029606 #FOAvip English Wikipedia <ref>{{Cite pmid|30029606}}</ref> GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection #MMPMID30029606 Zheng L; Wang J; Gao W; Hu C; Wang S; Rong R; Guo Y; Zhu T; Zhu D J Transl Med 2018[]; 16 (ä): ä PMID30029606show ga Background: Acute renal allograft rejection is a common complication after renal transplantation that often leads to chronic rejection and ultimate graft loss. While renal allograft biopsy remains the gold standard for diagnosis of acute rejection, the possibility of biopsy-associated complications cannot be overlooked. The development of noninvasive methods for accurate detection of acute renal allograft rejection is thus of significant clinical importance. Methods: Gas chromatography?mass spectrometry (GC/MS) was employed for analysis of urine metabolites in 15 renal allograft recipients with acute rejection and 15 stable renal transplant recipients. Partial least squares (PLS) regression and leave-one-out analyses were performed to ascertain whether the metabolites identified could be exploited to distinguish acute rejection from stable groups as well as their sensitivity and specificity. Results: Overall, 14 metabolites were significantly altered in the acute rejection group (11 and 3 metabolites displayed higher and lower levels, respectively) relative to the stable transplant group. Data from PLS and leave-one-out analyses revealed that the differential metabolites identified not only distinguished acute rejection from stable transplant recipients but also showed high sensitivity and specificity for diagnosis of renal allograft recipients with acute rejection. Conclusion: Urine metabolites identified with GC/MS can effectively distinguish acute rejection from stable transplant recipients, supporting the potential utility of metabolome analysis in non-invasive diagnosis of acute rejection. äGC/MS-based urine metabolomics analysis of renal allograft recipients (epmc).pdf DeepDyve Pubget Overpricing