A potential tool for diagnosis of XXXX : Plasma metabolomics based on GC-MS.

@entity1 @entity323 @entity249 @entity3264 @entity4810 @entity23 @entity854 @entity72219 @entity72218 @entity880 @entity165
@entity4810 has become an important public health problem worldwide. Nowadays the diagnosis of @entity4810 frequently depends on the results of semen quality or requires more invasive surgical intervention. Therefore, it is necessary to develop a novel approach for early diagnosis of @entity4810 . According to the presence or absence of normal sexual function, the @entity4810 is classified into two phenotypes, @entity323 ( @entity323 ) and @entity854 ( @entity854 ). The aim of this study was to investigate the GC-MS plasma profiles of @entity249 male having @entity323 ( @entity323 ) and having @entity854 ( @entity854 ) and discover the potential biomarkers. The plasma samples from @entity23 ( @entity23 ) (n=61) and @entity249 @entity1 with @entity323 (n=26) or with @entity854 (n=44) were analyzed by gas chromatography-mass spectrometry (GC-MS) for discrimination and screening potential biomarkers. The partial least squares-discriminant analysis (PLS-DA) was performed on GC-MS dataset. The results showed that @entity23 could be discriminated from @entity249 cases having @entity854 (AUC=86.96%, sensitivity=78.69%, specificity=84.09%, accuracy=80.95%) and @entity249 cases having @entity323 (AUC=94.33%, sensitivity=80.33%, specificity=100%, accuracy=87.36%). Some potential biomarkers were successfully discovered by two commonly used variable selection methods, variable importance on projection (VIP) and original coefficients of PLS-DA (b). @entity72218 and @entity72219 were identified as the potential biomarkers for distinguishing @entity23 from the @entity4810 @entity1 . Meanwhile, @entity880 , @entity3264 and @entity165 were the found to be the important variables to distinguish between @entity1 with @entity323 from those with @entity854 . The plasma metabolomics may be developed as a novel approach for fast, noninvasive, and acceptable diagnosis and characterization of @entity4810 .
