Metastasis is the primary cause of death in prostate cancer (PCa) patients. Small nucleolar RNAs (snoRNAs) have long been considered "housekeeping" genes with no relevance for cancer biology. Emerging evidence has challenged this assumption, suggesting that snoRNA expression is frequently modulated during cancer progression. Despite this, no study has systematically addressed the prognostic and...

Prostate cancer (PCa) is a leading cause of mortality and morbidity in men worldwide, and emerging evidence suggests that the CD44high prostate tumor-initiating cells (TICs) are associated with its poor prognosis. Although microRNAs are frequently dysregulated in human cancers, the influence of microRNAs on PCa malignancy and whether targeting TIC-associated microRNAs inhibit PCa progression re...

PURPOSE Advanced metastatic prostate cancer (PCa) is a fatal disease, with only palliative therapeutic options. Though almost 80% of cases of metastatic PCa present bone metastasis, our current understanding of the molecular mechanisms that govern this metastatic dissemination remains fragmentary. The main objective of the present study was to identify microRNA (miRNA) genes that regulate metas...

Objective. To compare the performance of multiparametric resonance imaging/ultrasound fusion targeted biopsy (MRI/US-TBx) to a combined biopsy strategy (MRI/US-TBx plus 24-core transperineal template saturation mapping biopsy (TTMB)). Methods. Between May 2012 and October 2015, all patients undergoing MRI/US-TBx at our institution were included for analysis. Patients underwent MRI/US-TBx of sus...

BACKGROUND We investigated associations between statin use begun before prostate cancer (PCa) diagnosis and PCa recurrence/progression and PCa-specific mortality (PCSM) in a prospective, population-based cohort study. METHODS The analysis included 1,001 PCa patients diagnosed in 2002-2005 in King County, Washington. Statin use was assessed at the time of diagnosis using a detailed in-person i...

Previous studies have associated higher milk intake with greater prostate cancer (PCa) incidence, but little data are available concerning milk types and the relation between milk intake and risk of fatal PCa. We investigated the association between intake of dairy products and the incidence and survival of PCa during a 28-y follow-up. We conducted a cohort study in the Physicians' Health Study...

Extending the classical principal component analysis (PCA), the kernel PCA (Schölkopf, Smola and Müller, 1998) effectively extracts nonlinear structures of high dimensional data. But similar to PCA, the kernel PCA can be sensitive to outliers. Various approaches have been proposed in the literature to robustify the classical PCA. However, it is not immediately clear how these approaches can be ...

ABSTRACT Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis are called principal components. Since Kernel PCA is just a PCA in feature space F , the projection of an image in input space can be reconstructed from its principal components in feature space. This enables us...

74 P&T® • February 2012 • Vol. 37 No. 2 Errors in initiating PCA infusions can occur at any point in the programming process. By using a limited number of standard concentrations, standardizing order forms, implementing smart PCA pumps with dose error-reduction software (DERS), and requiring an independent double-check of the PCA programming, hospitals can develop effective tools to help reduce...

In this paper, we consider a technique called the generic Principal Component Analysis (PCA) which is based on an extension and rigorous justification of the standard PCA. The generic PCA is treated as the best weighted linear estimator of a given rank under the condition that the associated covariance matrix is singular. As a result, the generic PCA is constructed in terms of the pseudo-invers...