The Development of a Point of Care Clinical Guidelines Mobile Application Following a User-Centred Design Approach

This paper describes the development of a point of care clinical guidelines mobile application. A user-centred design approach was utilised to inform the design of a smartphone application, this included: Observations; a survey; focus groups and an analysis of popular apps utilised by clinicians in a UK NHS Trust. Usability testing was conducted to inform iterations of the application, which presents clinicians with a variety of integrated tools to aid in decision making and information retrieval. The study found that clinicians use a mixture of technology to retrieve information, which is often inefficient or has poor usability. It also shows that smartphone application development for use in UK hospitals needs to consider the variety of users and their clinical knowledge and work pattern. This study highlights the need for applying user-centred design methods in the design of information presented to clinicians and the need for clinical information delivery that is efficient and easy to use at the bedside

Advancing brain barriers RNA sequencing: guidelines from experimental design to publication

Background: RNA sequencing (RNA-Seq) in its varied forms has become an indispensable tool for analyzing differential gene expression and thus characterization of specific tissues. Aiming to understand the brain barriers genetic signature, RNA seq has also been introduced in brain barriers research. This has led to availability of both, bulk and single-cell RNA-Seq datasets over the last few years. If appropriately performed, the RNA-Seq studies provide powerful datasets that allow for significant deepening of knowledge on the molecular mechanisms that establish the brain barriers. However, RNA-Seq studies comprise complex workflows that require to consider many options and variables before, during and after the proper sequencing process.Main body: In the current manuscript, we build on the interdisciplinary experience of the European PhD Training Network BtRAIN (https://www.btrain-2020.eu/) where bioinformaticians and brain barriers researchers collaborated to analyze and establish RNA-Seq datasets on vertebrate brain barriers. The obstacles BtRAIN has identified in this process have been integrated into the present manuscript. It provides guidelines along the entire workflow of brain barriers RNA-Seq studies starting from the overall experimental design to interpretation of results. Focusing on the vertebrate endothelial blood–brain barrier (BBB) and epithelial blood-cerebrospinal-fluid barrier (BCSFB) of the choroid plexus, we provide a step-by-step description of the workflow, highlighting the decisions to be made at each step of the workflow and explaining the strengths and weaknesses of individual choices made. Finally, we propose recommendations for accurate data interpretation and on the information to be included into a publication to ensure appropriate accessibility of the data and reproducibility of the observations by the scientific community.Conclusion: Next generation transcriptomic profiling of the brain barriers provides a novel resource for understanding the development, function and pathology of these barrier cells, which is essential for understanding CNS homeostasis and disease. Continuous advancement and sophistication of RNA-Seq will require interdisciplinary approaches between brain barrier researchers and bioinformaticians as successfully performed in BtRAIN. The present guidelines are built on the BtRAIN interdisciplinary experience and aim to facilitate collaboration of brain barriers researchers with bioinformaticians to advance RNA-Seq study design in the brain barriers community

The crossroads between cancer stem cells and aging

The cancer stem cell (CSC) hypothesis suggests that only a subpopulation of cells within a tumour is responsible for the initiation and progression of neoplasia. The original and best evidence for the existence of CSCs came from advances in the field of haematological malignancies. Thus far, putative CSCs have been isolated from various solid and non-solid tumours and shown to possess self-renewal, differentiation, and cancer regeneration properties. Although research in the field is progressing extremely fast, proof of concept for the CSC hypothesis is still lacking and key questions remain unanswered, e.g. the cell of origin for these cells. Nevertheless, it is undisputed that neoplastic transformation is associated with genetic and epigenetic alterations of normal cells, and a better understanding of these complex processes is of utmost importance for developing new anti-cancer therapies. In the present review, we discuss the CSC hypothesis with special emphasis on age-associated alterations that govern carcinogenesis, at least in some types of tumours. We present evidence from the scientific literature for age-related genetic and epigenetic alterations leading to cancer and discuss the main challenges in the field

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

BACKGROUND: Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. RESULTS AND DISCUSSION: Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large 'omics' datasets are increasingly being used in the area of rheumatology. CONCLUSIONS: Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery

Biomarkers of Chondrocyte Apoptosis and Autophagy in Osteoarthritis

Cell death with morphological and molecular features of apoptosis has been detected in osteoarthritic (OA) cartilage, which suggests a key role for chondrocyte death/survival in the pathogenesis of OA. Identification of biomarkers of chondrocyte apoptosis may facilitate the development of novel therapies that may eliminate the cause or, at least, slow down the degenerative processes in OA. The aim of this review was to explore the molecular markers and signals that induce chondrocyte apoptosis in OA. A literature search was conducted in PubMed, Scopus, Web of Science and Google Scholar using the keywords chondrocyte death, apoptosis, osteoarthritis, autophagy and biomarker. Several molecules considered to be markers of chondrocyte apoptosis will be discussed in this brief review. Molecular markers and signalling pathways associated with chondroycte apoptosis may turn out to be therapeutic targets in OA and approaches aimed at neutralizing apoptosis-inducing molecules may at least delay the progression of cartilage degeneration in OA

Biomarkers of Chondrocyte Apoptosis and Autophagy in Osteoarthritis

© 2015 by the authors; licensee MDPI, Basel, Switzerland. Cell death with morphological and molecular features of apoptosis has been detected in osteoarthritic (OA) cartilage, which suggests a key role for chondrocyte death/survival in the pathogenesis of OA. Identification of biomarkers of chondrocyte apoptosis may facilitate the development of novel therapies that may eliminate the cause or, at least, slow down the degenerative processes in OA. The aim of this review was to explore the molecular markers and signals that induce chondrocyte apoptosis in OA. A literature search was conducted in PubMed, Scopus, Web of Science and Google Scholar using the keywords chondrocyte death, apoptosis, osteoarthritis, autophagy and biomarker. Several molecules considered to be markers of chondrocyte apoptosis will be discussed in this brief review. Molecular markers and signalling pathways associated with chondroycte apoptosis may turn out to be therapeutic targets in OA and approaches aimed at neutralizing apoptosis-inducing molecules may at least delay the progression of cartilage degeneration in OA