Are Dutch dental students and dental-care providers competent prescribers of drugs?

Dental students and dental-care providers should be able to prescribe drugs safely and effectively. As it is unknown whether this is the case, we assessed and compared the prescribing competence of dental students and dental-care providers in the Netherlands. In 2017, all Dutch final-year dental students and a random sample of all qualified general dental practitioners and dental specialists (oral and maxillofacial surgeons and orthodontists) were invited to complete validated prescribing knowledge-assessment and skills-assessment instruments. The knowledge assessment comprised 40 multiple-choice questions covering important drug topics. The skills assessment comprised three common clinical case scenarios. For the knowledge assessment, the response rates were 26 (20%) dental students, 28 (8%) general dental practitioners, and 19 (19%) dental specialists, and for the skills assessment the response rates were 14 (11%) dental students, eight (2%) general dental practitioners, and eight (8%) dental specialists. Dental specialists had higher knowledge scores (78% correct answers) than either dental practitioners (69% correct answers) or dental students (69% correct answers). A substantial proportion of all three groups made inappropriate treatment choices (35%-49%) and prescribing errors (47%-70%). Although there were some differences, dental students and dental-care providers in the Netherlands lack prescribing competence, which is probably because of poor prescribing education during under- and postgraduate dental training. Educational interventions are urgently needed

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics

A transient liquid-like phase in the displacement cascades of zircon, hafnon and thorite

The study of radiation effects in solids is important for the development of 'radiation-resistant' materials for fission-reactor applications'. The effects of heavy-ion irradiation in the isostructural orthosilicates zircon (ZrSiO4), hafnon (HfSiO4) and thorite (ThSiO4) are particularly important because these minerals are under active investigation for use as a waste form for plutonium-239 resulting from the dismantling of nuclear weapons(2-4). During ion irradiation, localized 'cascades' of displaced atoms can form as a result of ballistic collisions in the target material, and the temperature inside these regions may for a short time exceed the bulk melting temperature. Whether these cascades do indeed generate a localized liquid state(5-8) has, however, remained unclear. Here we investigate the irradiation-induced decomposition of zircon and hafnon, and find evidence for formation of a liquidlike state in the displacement cascades. Our results explain the frequent occurrence of ZrO2 in natural amorphous zircong(9-12) Moreover, we conclude that zircon-based nuclear waste forms should be maintained within strict temperature Limits, to avoid potentially detrimental irradiation-induced amorphization or phase decomposition of the zircon.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62853/1/395056a0.pd

Genetic Traces of Recent Long-Distance Dispersal in a Predominantly Self-Recruiting Coral

Understanding of the magnitude and direction of the exchange of individuals among geographically separated subpopulations that comprise a metapopulation (connectivity) can lead to an improved ability to forecast how fast coral reef organisms are likely to recover from disturbance events that cause extensive mortality. Reef corals that brood their larvae internally and release mature larvae are believed to show little exchange of larvae over ecological times scales and are therefore expected to recover extremely slowly from large-scale perturbations.Using analysis of ten DNA microsatellite loci, we show that although Great Barrier Reef (GBR) populations of the brooding coral, Seriatopora hystrix, are mostly self-seeded and some populations are highly isolated, a considerable amount of sexual larvae (up to approximately 4%) has been exchanged among several reefs 10 s to 100 s km apart over the past few generations. Our results further indicate that S. hystrix is capable of producing asexual propagules with similar long-distance dispersal abilities (approximately 1.4% of the sampled colonies had a multilocus genotype that also occurred at another sampling location), which may aid in recovery from environmental disturbances.Patterns of connectivity in this and probably other GBR corals are complex and need to be resolved in greater detail through genetic characterisation of different cohorts and linkage of genetic data with fine-scale hydrodynamic models

Breast cancer oestrogen independence mediated by BCAR1 or BCAR3 genes is transmitted through mechanisms distinct from the oestrogen receptor signalling pathway or the epidermal growth factor receptor signalling pathway

INTRODUCTION: Tamoxifen is effective for endocrine treatment of oestrogen receptor-positive breast cancers but ultimately fails due to the development of resistance. A functional screen in human breast cancer cells identified two BCAR genes causing oestrogen-independent proliferation. The BCAR1 and BCAR3 genes both encode components of intracellular signal transduction, but their direct effect on breast cancer cell proliferation is not known. The aim of this study was to investigate the growth control mediated by these BCAR genes by gene expression profiling. METHODS: We have measured the expression changes induced by overexpression of the BCAR1 or BCAR3 gene in ZR-75-1 cells and have made direct comparisons with the expression changes after cell stimulation with oestrogen or epidermal growth factor (EGF). A comparison with published gene expression data of cell models and breast tumours is made. RESULTS: Relatively few changes in gene expression were detected in the BCAR-transfected cells, in comparison with the extensive and distinct differences in gene expression induced by oestrogen or EGF. Both BCAR1 and BCAR3 regulate discrete sets of genes in these ZR-75-1-derived cells, indicating that the proliferation signalling proceeds along distinct pathways. Oestrogen-regulated genes in our cell model showed general concordance with reported data of cell models and gene expression association with oestrogen receptor status of breast tumours. CONCLUSIONS: The direct comparison of the expression profiles of BCAR transfectants and oestrogen or EGF-stimulated cells strongly suggests that anti-oestrogen-resistant cell proliferation is not caused by alternative activation of the oestrogen receptor or by the epidermal growth factor receptor signalling pathway

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

Composition and diversity analysis of the lung microbiome in patients with suspected ventilator-associated pneumonia.

BackgroundVentilator-associated pneumonia (VAP) is associated with high morbidity and health care costs, yet diagnosis remains a challenge. Analysis of airway microbiota by amplicon sequencing provides a possible solution, as pneumonia is characterised by a disruption of the microbiome. However, studies evaluating the diagnostic capabilities of microbiome analysis are limited, with a lack of alignment on possible biomarkers. Using bronchoalveolar lavage fluid (BALF) from ventilated adult patients suspected of VAP, we aimed to explore how key characteristics of the microbiome differ between patients with positive and negative BALF cultures and whether any differences could have a clinically relevant role.MethodsBALF from patients suspected of VAP was analysed using 16s rRNA sequencing in order to: (1) differentiate between patients with and without a positive culture; (2) determine if there was any association between microbiome diversity and local inflammatory response; and (3) correctly identify pathogens detected by conventional culture.ResultsThirty-seven of 90 ICU patients with suspected VAP had positive cultures. Patients with a positive culture had significant microbiome dysbiosis with reduced alpha diversity. However, gross compositional variance was not strongly associated with culture positivity (AUROCC range 0.66-0.71). Patients with a positive culture had a significantly higher relative abundance of pathogenic bacteria compared to those without [0.45 (IQR 0.10-0.84), 0.02 (IQR 0.004-0.09), respectively], and an increased interleukin (IL)-1β was associated with reduced species evenness (rs = - 0.33, p s = 0.28, p = 0.013). Untargeted 16s rRNA pathogen detection was limited by false positives, while the use of pathogen-specific relative abundance thresholds showed better diagnostic accuracy (AUROCC range 0.89-0.998).ConclusionPatients with positive BALF culture had increased dysbiosis and genus dominance. An increased caspase-1-dependent IL-1b expression was associated with a reduced species evenness and increased pathogenic bacterial presence, providing a possible causal link between microbiome dysbiosis and lung injury development in VAP. However, measures of diversity were an unreliable predictor of culture positivity and 16s sequencing used agnostically could not usefully identify pathogens; this could be overcome if pathogen-specific relative abundance thresholds are used

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Microbial volatiles as diagnostic biomarkers of bacterial lung infection in mechanically ventilated patients.

BackgroundEarly and accurate recognition of respiratory pathogens is crucial to prevent increased risk of mortality in critically ill patients. Microbial-derived volatile organic compounds (mVOCs) in exhaled breath could be used as non-invasive biomarkers of infection to support clinical diagnosis.MethodsIn this study, we investigated the diagnostic potential of in vitro confirmed mVOCs in the exhaled breath of patients under mechanically ventilation from the BreathDx study. Samples were analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS).ResultsPathogens from bronchoalveolar lavage (BAL) cultures were identified in 45/89 patients and S. aureus was the most commonly identified pathogen (n = 15). Out of 19 mVOCs detected in the in vitro culture headspace of four common respiratory pathogens (Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae and Escherichia coli), 14 were found in exhaled breath samples. Higher concentrations of two mVOCs were found in the exhaled breath of patients infected with S. aureus compared to those without (3-methylbutanal p ConclusionsThis study demonstrates the capability of using mVOCs to detect the presence of specific pathogen groups with potential to support clinical diagnosis. Although not all mVOCs were found in patient samples within this small pilot study, further targeted and qualitative investigation is warranted using multi-centre clinical studies