BACKGROUND Conversion into androgen-hypersensitive state and adaptation to the low concentration of androgen during ADT cause relapse of prostate cancer (PCa). It is important to identify differentially expressed genes between PCa and normal prostate tissues and to reveal the function of these genes that are involved in progression of PCa. METHODS We performed cDNA microarray analysis to iden...

Observational studies have suggested an association between human papillomavirus (HPV) infection and the risk of prostate cancer (PCa). However, the association between HPV infection and the risk of PCa remains unclear. The aim of the present meta-analysis study was to investigate whether HPV serves a role in increasing the risk of PCa. Relevant previous studies up to May 2015 were searched in ...

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented...

BACKGROUND Interleukin (IL)-35 is a novel inhibitory cytokine and has recently been implicated in tumor immunity. However, the role of IL-35 in prostate cancer (PCa) has not been elucidated. OBJECTIVE To evaluate the role of plasma IL-35 in the diagnosis and prognosis of PCa in Chinese patients undergoing initial prostate biopsy. MATERIALS AND METHODS Using ELISA, plasma IL-35 levels were m...

Although estrogen receptor beta (ERβ) has been implicated in prostate cancer (PCa) progression, its potential role in health disparity of PCa remains elusive. The objective of this study was to examine serum estrogens and prostate tumor ERβ expression and examine their correlation with clinical and pathological parameters in African American (AA) versus Caucasian American (CA) men. The circulat...

Though numerous studies have been conducted to investigate the associations between five 8q24 polymorphisms (rs6983267 T>G, rs1447295 C>A, rs16901979 C>A, rs6983561 A>C and rs10090154 C>T) and prostate cancer (PCa) risk, the available results remained contradictory. Therefore, we performed a comprehensive meta-analysis to derive a precise estimation of such associations. We searched electronic ...

Principal Component Analysis (PCA) is a well-established technique in image processing and pattern recognition. Incremental PCA and robust PCA are two interesting problems with numerous potential applications. However, these two issues have only been separately addressed in the previous studies. In this paper, we present a novel algorithm for incremental and robust PCA by seamlessly integrating...

We propose a unified framework for making a wide range of PCA-like algorithms – including the standard PCA, sparse PCA and non-negative sparse PCA, etc. – robust when facing a constant fraction of arbitrarily corrupted outliers. Our analysis establishes solid performance guarantees of the proposed framework: its estimation error is upper bounded by a term depending on the intrinsic parameters o...

This paper proposes a new gait recognition method using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is first applied to 1D time-varying distance signals derived from a sequence of silhouette images to reduce it’s dimensionality. Then, LDA is performed to optimize the pattern class ificovtion..And,Spatiotemporal Correlation (STC) and Normalized Euclidean Distan...

Our contribution briefly outlines the basics of the well-established technique in data mining, namely the principal component analysis (PCA), and a rapidly emerging novel method, that is, the independent component analysis (ICA). The performance of PCA singular value decomposition-based and stationary linear ICA in blind separation of artificially generated data out of linear mixtures was criti...