Prostate cancer is the most frequent occurring malignancy in men in many Western countries. Unfortunately, only a few studies on occupational risk factors have been published. Thus, the aim of this study was to investigate possible occupational risk factors in a former center of coal, iron, and steel industries the greater Dortmund area, located in the western part of Germany.
View Article and Find Full Text PDFMotivation: Proteomics has particularly evolved to become of high interest for the field of biomarker discovery and drug development. Especially the combination of liquid chromatography and mass spectrometry (LC/MS) has proven to be a powerful technique for analyzing protein mixtures. Clinically orientated proteomic studies will have to compare hundreds of LC/MS runs at a time.
View Article and Find Full Text PDFBackground: Analysis of exhaled breath, especially of volatile organic compounds (VOCs), is of increasing interest in the diagnosis of lung cancer. Compared with other methods of breath analysis, ion mobility spectrometry (IMS) offers a tenfold higher detection rate of VOCs. By coupling the ion mobility spectrometer with a multicapillary column as a pre-separation unit, IMS offers the advantage of an immediate twofold separation of VOCs with visualisation in a three-dimensional chromatogram.
View Article and Find Full Text PDFJ Toxicol Environ Health A
July 2008
The relationship between exposure to carcinogenic substances and development of bladder cancer was assessed from a case-control study conducted in North Rhine-Westphalia, Germany. The study consisted of 156 cases with bladder cancer and 336 controls with prostate cancer. The primary focus was the role of polycyclic aromatic hydrocarbons (PAHs), since most individuals were considered exposed mainly to substances in this group.
View Article and Find Full Text PDFMost proteomics experiments make use of 'high throughput' technologies such as 2-DE, MS or protein arrays to measure simultaneously the expression levels of thousands of proteins. Such experiments yield large, high-dimensional data sets which usually reflect not only the biological but also technical and experimental factors. Statistical tools are essential for evaluating these data and preventing false conclusions.
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