Entropy in Image Analysis III

Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future

Investigating new genetic susceptibility loci in osteoarthritis

Primary osteoarthritis (OA) is a late-onset, degenerative condition of synovial joints, and is the major cause of pain and disability in older persons. OA represents a significant disease burden and focus of research, especially as no disease-modifying therapies exist to manage the condition. The genetic influence to OA is complex and polygenic. The arcOGEN study, the most powerful genome-wide association study yet to investigate OA in humans, identified the 9q33.1 locus to be significantly associated with hip OA in females. TRIM32 lies within the 9q33.1 susceptibility locus and may have strong biological relevance to OA; it encodes a protein with E3 ubiquitin ligase activity. Sanger sequencing of TRIM32 in the youngest 500 female patients with hip OA from the arcOGEN study was performed to identify rare variants in TRIM32 that are associated with OA of the hip in females. Polymorphisms were identified in the proximal promoter, and 3’untranslated regions (3’UTR) of TRIM32 that are disproportionately represented in female patients with hip OA, compared to the control population. In vitro studies identified expression of TRIM32 in human femoral head cartilage; reduced expression of TRIM32 was also demonstrated in femoral head primary articular chondrocytes from patients with hip OA compared to control patients. Trim32 knockout resulted in increased aggrecanolysis in murine femoral head explants. Murine chondrocytes deficient in Trim32 also exhibited increased expression of markers of a mature chondrocyte phenotype in response to anabolic cytokine stimulation, and increased expression of markers of a hypertrophic chondrocyte phenotype upon catabolic cytokine stimulation. In vivo studies of joint degeneration in Trim32 knockout mice demonstrated increased cartilage degradation and tibial epiphyseal bone changes after surgically induced knee joint instability, compared to wild-type mice. Increased cartilage degradation and medial knee subchondral bone changes were also identified upon ageing of Trim32 knockout mice. These results further implicate TRIM32 in the genetic predisposition to OA, and indicate a role for TRIM32 in the joint degeneration evident in OA. These results support the further study of TRIM32 in the pathophysiology of OA and development of novel therapeutic strategies to manage OA

A cumulative index to the 1976 issues of a continuing bibliography on Aerospace Medicine and Biology

This publication is a cumulative index to the abstracts contained in Supplements 151 through 162 of Aerospace Medicine and Biology: A continuing bibliography. It includes three indexes - subject, personal author, and corporate source

New Statistical Algorithms for the Analysis of Mass Spectrometry Time-Of-Flight Mass Data with Applications in Clinical Diagnostics

Mass spectrometry (MS) based techniques have emerged as a standard forlarge-scale protein analysis. The ongoing progress in terms of more sensitive machines and improved data analysis algorithms led to a constant expansion of its fields of applications. Recently, MS was introduced into clinical proteomics with the prospect of early disease detection using proteomic pattern matching. Analyzing biological samples (e.g. blood) by mass spectrometry generates mass spectra that represent the components (molecules) contained in a sample as masses and their respective relative concentrations. In this work, we are interested in those components that are constant within a group of individuals but differ much between individuals of two distinct groups. These distinguishing components that dependent on a particular medical condition are generally called biomarkers. Since not all biomarkers found by the algorithms are of equal (discriminating) quality we are only interested in a small biomarker subset that - as a combination - can be used as a fingerprint for a disease. Once a fingerprint for a particular disease (or medical condition) is identified, it can be used in clinical diagnostics to classify unknown spectra. In this thesis we have developed new algorithms for automatic extraction of disease specific fingerprints from mass spectrometry data. Special emphasis has been put on designing highly sensitive methods with respect to signal detection. Thanks to our statistically based approach our methods are able to detect signals even below the noise level inherent in data acquired by common MS machines, such as hormones. To provide access to these new classes of algorithms to collaborating groups we have created a web-based analysis platform that provides all necessary interfaces for data transfer, data analysis and result inspection. To prove the platform's practical relevance it has been utilized in several clinical studies two of which are presented in this thesis. In these studies it could be shown that our platform is superior to commercial systems with respect to fingerprint identification. As an outcome of these studies several fingerprints for different cancer types (bladder, kidney, testicle, pancreas, colon and thyroid) have been detected and validated. The clinical partners in fact emphasize that these results would be impossible with a less sensitive analysis tool (such as the currently available systems). In addition to the issue of reliably finding and handling signals in noise we faced the problem to handle very large amounts of data, since an average dataset of an individual is about 2.5 Gigabytes in size and we have data of hundreds to thousands of persons. To cope with these large datasets, we developed a new framework for a heterogeneous (quasi) ad-hoc Grid - an infrastructure that allows to integrate thousands of computing resources (e.g. Desktop Computers, Computing Clusters or specialized hardware, such as IBM's Cell Processor in a Playstation 3)