Moa and the multi-model architecture: a new perspective on XNF2

Advanced non-traditional application domains such as geographic information systems and digital library systems demand advanced data management support. In an effort to cope with this demand, we present the concept of a novel multi-model DBMS architecture which provides evaluation of queries on complexly structured data without sacrificing efficiency. A vital role in this architecture is played by the Moa language featuring a nested relational data model based on XNF2, in which we placed renewed interest. Furthermore, extensibility in Moa avoids optimization obstacles due to black-box treatment of ADTs. The combination of a mapping of queries on complexly structured data to an efficient physical algebra expression via a nested relational algebra, extensibility open to optimization, and the consequently better integration of domain-specific algorithms, makes that the Moa system can efficiently and effectively handle complex queries from non-traditional application domains

A source path contribution analysis on tire noise using particle velocity sensors

Road tire noise is an important topic of research where acoustic particle velocity based testing techniques can be expected to bring new insights. Modal analysis can be carried out using non contact particle velocity sensors, and PU sound probes can be used to measure the radiated sound without a need to use anechoic testing conditions. A further breakdown of the overall sound pressure levels measured in to its various sources can be made by applying a source path contribution analysis, using the PU probes to measure velocity, sound intensity and, for determining the reciprocal transfer path, the sound pressure. The concept of using this type of transfer path analysis will be outlined and illustrated by a tire noise case

The Role of ATP-Binding Cassette Transporters in Neuro-Inflammation: Relevance for Bioactive Lipids

ATP-binding cassette (ABC) transporters are highly expressed by brain endothelial cells that form the blood-brain barrier (BBB). These efflux pumps play an important role in maintaining brain homeostasis as they actively hinder the entry of unwanted blood-derived compounds into the central nervous system (CNS). Consequently, their high activity at the BBB has been a major hurdle for the treatment of several brain diseases, as they prevent numerous drugs to reach their site of action within the brain. Importantly, recent data indicate that endogenous substrates for ABC transporters may include inflammatory mediators, such as prostaglandins, leukotrienes, cytokines, chemokines and bioactive lipids, suggesting a potential role for ABC transporters in immunological responses, and more specifically in inflammatory brain disorders, such as multiple sclerosis (MS). In this review, we will give a comprehensive overview of recent findings that illustrate this novel role for ABC transporters in neuro-inflammatory processes. Moreover, we will provide first insights into underlying mechanisms and focus on the importance for bioactive lipids, in particular platelet-activating factor (PAF), herein. A thorough understanding of these events may form the basis for the development for selective treatment modalities to dampen the neuro-inflammatory attack in MS and thereby reducing tissue damage

Moa and the Multi-model architecture: a new perspective on XNF 2

Advanced non-traditional application domains such as geographic information systems and digital library systems demand advanced data management support. In an effort to cope with this demand, we present the concept of a novel multi-model DBMS architecture which provides evaluation of queries on complexly structured data without sacrificing efficiency. A vital role in this architecture is played by the Moa language featuring a nested relational data model based on XNF2 , in which we placed renewed interest. Furthermore, extensibility in Moa avoids optimization obstacles due to black-box treatment of ADTs. The combination of a mapping of queries on complexly structured data to an efficient physical algebra expression via a nested relational algebra, extensibility open to optimization, and the consequently better integration of domain-specific algorithms, makes that the Moa system can efficiently handle complex queries from non-traditional application domains

Urgent bedreigde typische soorten en vegetatietypen van Natura 2000-habitattypen

Dit rapport is de weerslag van een onderzoek naar de urgent bedreigde en potentieel urgent bedreigde typische soorten en de urgent bedreigde en potentieel urgent bedreigde vegetatietypen van de habitattypen van de Natura 2000-gebieden. In totaal zijn 67 typische soorten als Urgent Bedreigd gecategoriseerd; nog eens 26 soorten zijn gecategoriseerd als Potentieel Urgent Bedreigd. Voor de vegetatietypen geldt dat er 15 (sub)associaties Urgent bedreigd zijn. Op een bijbehorende cdrom wordt voor al deze soorten en vegetaties de huidige verspreiding gegeven, of herstel binnen of buiten Natura 2000 zou moeten plaatsvinden, wat de knelpunten hierbij zijn en waar de beste herstellocaties gelegen zijn

Trends of cutaneous melanoma in the Netherlands: increasing incidence rates among all Breslow thickness categories and rising mortality rates since 1989

Abstract: Background: It has been debated that the epidemic of melanoma is largely due to overdiagnosis, since increases in incidence were mainly among thin melanomas and mortality rates remained stable. Our objective was to examine this controversy in the Netherlands. Patients and Methods: Information on newly diagnosed melanoma patients was obtained from the Netherlands Cancer Registry (NCR). European Standardised Rates (ESR) and Estimated Annual Percentage Change (EAPC) were calculated for the period 1989-2008.Cohort-based, period-based and multivariate survival analyses were performed. Results: The incidence rate of melanoma increased with 4.1% (95% CI: 3.6-4.5) annually. Incidence rates of both thin melanomas (. 1mm) and thick melanomas (> 4 mm) increased since 1989. Mortality rates increased mainly in older patients (>65 years). Ten-year relative survival of males improved significantly from 70% in 1989-1993 to 77% in 2004-2008 (p < 0.001) and for females the 10-year relative survival increased from 85% to 88% (p < 0.01). Recently diagnosed patients had a better prognosis even after adjusting for all known prognostic factors. Conclusion: Since incidence of melanomas among all Breslow thickness categories increased as well as the mortality rates, the melanoma epidemic in the Netherlands seems to be real and not only due to overdiagnosis

Machine learning-based analysis of [¹⁸F]DCFPyL PET radiomics for risk stratification in primary prostate cancer

PURPOSE: Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [18F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features. METHODS: In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [18F]DCFPyL PET-CT. Primary tumors were delineated using 50-70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ≥ 8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC. RESULTS: The radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p < 0.01), nodal or distant metastasis (AUC 0.86 ± 0.14, p < 0.01), Gleason score (0.81 ± 0.16, p < 0.01), and ECE (0.76 ± 0.12, p < 0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance. CONCLUSION: Machine learning-based analysis of quantitative [18F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice

Utility of Animal Models to Understand Human Alzheimer's Disease, Using the Mastermind Research Approach to Avoid Unnecessary Further Sacrifices of Animals

To diagnose and treat early-stage (preclinical) Alzheimer's disease (AD) patients, we need body-fluid-based biomarkers that reflect the processes that occur in this stage, but current knowledge on associated processes is lacking. As human studies on (possible) onset and early-stage AD would be extremely expensive and time-consuming, we investigate the potential value of animal AD models to help to fill this knowledge gap. We provide a comprehensive overview of processes associated with AD pathogenesis and biomarkers, current knowledge on AD-related biomarkers derived from on human and animal brains and body fluids, comparisons of biomarkers obtained in human AD and frequently used animal AD models, and emerging body-fluid-based biomarkers. In human studies, amyloid beta (Aβ), hyperphosphorylated tau (P-tau), total tau (T-tau), neurogranin, SNAP-25, glial fibrillary acidic protein (GFAP), YKL-40, and especially neurofilament light (NfL) are frequently measured. In animal studies, the emphasis has been mostly on Aβ. Although a direct comparison between human (familial and sporadic) AD and (mostly genetic) animal AD models cannot be made, still, in brain, cerebrospinal fluid (CSF), and blood, a majority of similar trends are observed for human AD stage and animal AD model life stage. This indicates the potential value of animal AD models in understanding of the onset and early stage of AD. Moreover, animal studies can be smartly designed to provide mechanistic information on the interrelationships between the different AD processes in a longitudinal fashion and may also include the combinations of different conditions that may reflect comorbidities in human AD, according to the Mastermind Research approach.Pharmacolog