Diagnostic Accuracy of Protein Glycation Sites in Long-Term Controlled Patients with Type 2 Diabetes Mellitus and Their Prognostic Potential for Early Diagnosis

Current screening tests for type 2 diabetes mellitus (T2DM) identify less than 50% of undiagnosed T2DM patients and provide no information about how the disease will develop in prediabetic patients. Here, twenty-nine protein glycation sites were quantified after tryptic digestion of plasma samples at the peptide level using tandem mass spectrometry and isotope-labelled peptides as internal standard. The glycation degrees were determined in three groups, i.e., 48 patients with a duration of T2DM exceeding ten years, 48 non-diabetic individuals matched for gender, BMI, and age, and 20 prediabetic men. In long-term controlled diabetic patients, 27 glycated peptides were detected at significantly higher levels, providing moderate diagnostic accuracies (ACCs) from 61 to 79%, allowing a subgrouping of patients in three distinct clusters. Moreover, a feature set of one glycated peptides and six established clinical parameters provided an ACC of 95%. The same number of clusters was identified in prediabetic males (ACC of 95%) using a set of eight glycation sites (mostly from serum albumin). All patients present in one cluster showed progression of prediabetic state or advanced towards diabetes in the following five years. Overall, the studied glycation sites appear to be promising biomarkers for subgrouping prediabetic patients to estimate their risk for the development of T2DM

The word landscape of the non-coding segments of the Arabidopsis thaliana genome

<p>Abstract</p> <p>Background</p> <p>Genome sequences can be conceptualized as arrangements of motifs or words. The frequencies and positional distributions of these words within particular non-coding genomic segments provide important insights into how the words function in processes such as mRNA stability and regulation of gene expression.</p> <p>Results</p> <p>Using an enumerative word discovery approach, we investigated the frequencies and positional distributions of all 65,536 different 8-letter words in the genome of <it>Arabidopsis thaliana</it>. Focusing on promoter regions, introns, and 3' and 5' untranslated regions (3'UTRs and 5'UTRs), we compared word frequencies in these segments to genome-wide frequencies. The statistically interesting words in each segment were clustered with similar words to generate motif logos. We investigated whether words were clustered at particular locations or were distributed randomly within each genomic segment, and we classified the words using gene expression information from public repositories. Finally, we investigated whether particular sets of words appeared together more frequently than others.</p> <p>Conclusion</p> <p>Our studies provide a detailed view of the word composition of several segments of the non-coding portion of the <it>Arabidopsis </it>genome. Each segment contains a unique word-based signature. The respective signatures consist of the sets of enriched words, 'unwords', and word pairs within a segment, as well as the preferential locations and functional classifications for the signature words. Additionally, the positional distributions of enriched words within the segments highlight possible functional elements, and the co-associations of words in promoter regions likely represent the formation of higher order regulatory modules. This work is an important step toward fully cataloguing the functional elements of the <it>Arabidopsis </it>genome.</p

Reverse Engineering of Computer-Based Navy Systems

The financial pressure to meet the need for change in computer-based systems through evolution rather than through revolution has spawned the discipline of reengineering. One driving factor of reengineering is that it is increasingly becoming the case that enhanced requirements placed on computer-based systems are overstressing the processing resources of the systems. Thus, the distribution of processing load over highly parallel and distributed hardware architectures has become part of the reengineering process for computer-based Navy systems. This paper presents an intermediate representation (IR) for capturing features of computer-based systems to enable reengineering for concurrency. A novel feature of the IR is that it incorporates the mission critical software architecture, a view that enables information to be captured at five levels of granularity: the element/program level, the task level, the module/class/package level, the method/procedure level, and the statement/instruction level. An approach to reverse engineering is presented, in which the IR is captured, and is analyzed to identify potential concurrency. Thus, the paper defines concurrency metrics to guide the reengineering tasks of identifying, enhancing, and assessing concurrency, and for performing partitioning and assignment. Concurrency metrics are defined at several tiers of the mission critical software architecture. In addition to contributing an approach to reverse engineering for computer-based systems, the paper also discusses a reverse engineering analysis toolset that constructs and displays the IR and the concurrency metrics for Ada programs. Additionally, the paper contains a discussion of the context of our reengineering efforts within the United States Navy, by describing two reengineering projects focused on sussystems of the AEGIS Weapon System

The development and application of bioinformatics core competencies to improve bioinformatics training and education

Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans