A new rule-based algorithm for identifying metabolic markers in prostate cancer using tandem mass spectrometry.

MOTIVATION: Prostate cancer is the most prevalent tumor in males and its incidence is expected to increase as the population ages. Prostate cancer is treatable by excision if detected at an early enough stage. The challenges of early diagnosis require the discovery of novel biomarkers and tools for prostate cancer management. RESULTS: We developed a novel feature selection algorithm termed as associative voting (AV) for identifying biomarker candidates in prostate cancer data measured via targeted metabolite profiling MS/MS analysis. We benchmarked our algorithm against two standard entropy-based and correlation-based feature selection methods [Information Gain (IG) and ReliefF (RF)] and observed that, on a variety of classification tasks in prostate cancer diagnosis, our algorithm identified subsets of biomarker candidates that are both smaller and show higher discriminatory power than the subsets identified by IG and RF. A literature study confirms that the highest ranked biomarker candidates identified by AV have independently been identified as important factors in prostate cancer development. AVAILABILITY: The algorithm can be downloaded from the following http://biomed.umit.at/page.cfm?pageid=516.

Evaluation of cardiac scoring models for an Austrian cardiac register.

The Austrian Health 2006 Structural Plan of 28 June 2006 requires that reference centres for heart surgery 'participate in result-quality registers (e.g. cardiac registers)'. The aim of the present study was to identify a suitable scoring model for the Austrian register during the run-up to its creation. During the period from November 2004 to December 2005 a survey was done of the actual situation, the organisational and economic possibilities, and the requirements of all Austrian heart centres. General and also specific Austrian basic conditions were defined. Scoring models were then classified and evaluated. The characteristics 'national and international comparability', the associated 'distribution of the scoring system' and 'detailed scientific discussion of the applicability' were found as the main criteria for selection. Economic aspects such as survey and analysis costs, and the everyday practicability of gathering data in the actual situation revealed by the survey, were also included in the evaluation framework. It could be demonstrated that under the given circumstances, the EuroSCORE represented the suitable predictive model.

Systematic analysis of signaling pathways using an integrative environment.

INTRODUCTION: Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. METHODS: This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. RESULTS: The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. CONCLUSION: The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

Single-beat noninvasive imaging of cardiac electrophysiology of ventricular pre-excitation.

OBJECTIVES: The aim of this study was to determine whether noninvasive imaging of cardiac electrophysiology (NICE) is feasible in patients with Wolff-Parkinson-White (WPW) syndrome in the clinical setting of a catheter laboratory and to test the accuracy of the noninvasively obtained ventricular activation sequences as compared with that of standard invasive electroanatomic mapping. BACKGROUND: NICE of ventricular activation could serve as a useful tool in the treatment of cardiac arrhythmias and might help improve our understanding of arrhythmia mechanisms. METHODS: NICE works by fusing the data from high-resolution electrocardiographic mapping and a model of the patient's cardiac anatomy obtained by magnetic resonance imaging. The ventricular activation sequence was computed with a bidomain theory-based heart model to solve this inverse problem. Noninvasive imaging of cardiac electrophysiology was performed in 7 patients with WPW syndrome undergoing catheter ablation of the accessory pathway. The position error of NICE was defined as the distance between the site of earliest activation computed by NICE and the successful ablation site identified by electroanatomic mapping (CARTO; Biosense Webster, Diamond Bar, California) for normal atrioventricular (AV) conduction as well as for adenosine-induced AV block. RESULTS: The error introduced by geometric coupling of the CARTO data and the NICE model was 5 +/- 3 mm (model discretization 10 mm). All ventricular accessory pathway insertion sites were identified with an accuracy of 18.7 +/- 5.8 mm (baseline) and 18.7 +/- 6.4 mm (adenosine). CONCLUSIONS: The individual cardiac anatomy model obtained for each patient enables accurate noninvasive electrocardiographic imaging of ventricular pre-excitation in patients with WPW syndrome. Noninvasive imaging of cardiac electrophysiology might be used as a complementary noninvasive approach to localize the origin and help identify and understand the underlying mechanisms of cardiac arrhythmias.