Modeling Adaptive Hypermedia with An Object-Oriented Approach and XML

This work presents an Application Domain model for Adaptive Hypermedia Systems and an architecture for its support. For the description of the high-level structure of the application domain we propose an object-oriented model based on the class diagrams of the Unified Modeling Language, extended with (i) a graph-based formalism for capturing navigational properties of the hypermedia and (ii) a logic-based formalism for expressing further semantic properties of the domain. The model makes use of XML for the description of metadata about basic information fragments and "neutral" pages to be adapted. Moreover, we propose a three-dimensional approach to model di#erent aspects of the adaptation model, based on di#erent user's characteristics: an adaptive hypermedia is modeled with respect to such dimensions, and a view over it corresponds to each potential position of the user in the "adaptation space". In particular, a rule-based method is used to determine the generation and deliver process that best fits technological constraints

Plasma microRNA ratios associated with breast cancer detection in a nested case–control study from a mammography screening cohort

Abstract Mammographic breast cancer screening is effective in reducing breast cancer mortality. Nevertheless, several limitations are known. Therefore, developing an alternative or complementary non-invasive tool capable of increasing the accuracy of the screening process is highly desirable. The objective of this study was to identify circulating microRNA (miRs) ratios associated with BC in women attending mammography screening. A nested case–control study was conducted within the ANDROMEDA cohort (women of age 46–67 attending BC screening). Pre-diagnostic plasma samples, information on life-styles and common BC risk factors were collected. Small-RNA sequencing was carried out on plasma samples from 65 cases and 66 controls. miR ratios associated with BC were selected by two-sample Wilcoxon test and lasso logistic regression. Subsequent assessment by RT-qPCR of the miRs contained in the selected miR ratios was carried out as a platform validation. To identify the most promising biomarkers, penalised logistic regression was further applied to candidate miR ratios alone, or in combination with non-molecular factors. Small-RNA sequencing yielded 20 candidate miR ratios associated with BC, which were further assessed by RT-qPCR. In the resulting model, penalised logistic regression selected seven miR ratios (miR-199a-3p_let-7a-5p, miR-26b-5p_miR-142-5p, let-7b-5p_miR-19b-3p, miR-101-3p_miR-19b-3p, miR-93-5p_miR-19b-3p, let-7a-5p_miR-22-3p and miR-21-5p_miR-23a-3p), together with body mass index (BMI), menopausal status (MS), the interaction term BMI * MS, life-style score and breast density. The ROC AUC of the model was 0.79 with a sensitivity and specificity of 71.9% and 76.6%, respectively. We identified biomarkers potentially useful for BC screening measured through a widespread and low-cost technique. This is the first study reporting circulating miRs for BC detection in a screening setting. Validation in a wider sample is warranted. Trial registration: The Andromeda prospective cohort study protocol was retrospectively registered on 27-11-2015 (NCT02618538)