The academic radiography workforce: Age profile, succession planning and academic development.

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Introduction: Academia is one area of practice in which radiographers can specialise; they compile approximately 2% of the total radiography profession in the UK, but are highly influential and essential for the education and development of the workforce in addition to undertaking research. However, the academic environment is very different to clinical practice and a period of transition is required. Methods: Data were collated to explore the age and retirement profile of the academic radiography workforce in the UK; to understand the research time allocated to this workforce; the time required to develop a clinical radiographer into an academic and the mentorship and succession planning provisions nationally. An online UK wide survey was conducted and sent to all 24 Universities delivering radiography education within the UK. Results: Eighteen out of 24 Universities in the UK responded to the survey. Approximately 30% of radiography academics are due to retire over the next ten years, with over 25% of radiographers who currently hold a doctorate qualification included within this figure. Those entering academia have notably lower qualifications as a group than those who are due to retire. Developing clinical radiographers into academics was thought to take 1-3 years on average, or longer if they are required to undertake research. Conclusion: There is vulnerability in the academic radiography workforce. Higher education institutions need to invest in developing the academic workforce to maintain research and educational expertise, which is underpinned by master’s and doctorate level qualifications

Morphogenetic Theory and the Constructivist Institutionalist Challenge

This article engages with two meta-theoretical approaches to social analysis, ‘morphogenetic theory’ and ‘constructivist institutionalism’, and specifically explores how the former fares under the critical scrutiny of the latter. The key proponent of constructivist institutionalism, Colin Hay, has offered two detailed critiques of morphogenesis that criticise its position on the foundational sociological issues of structure-agency and material-ideational. Although Hay’s critiques are largely rejected in an overall defence of the morphogenetic approach, the process of engagement is seen to be particularly useful for morphogenetic theory because it allows a number of important clarifications to be made and it also opens up space for theoretical development. In the course of this debate, accessible introductions are given to both theories, and the similarities and differences between them are outlined, providing clarity to both. Therefore, although this article ultimately operates as a defence of morphogenetic theory, especially in the form proposed by Margaret Archer and Douglas Porpora, it finds a great deal of fruitful discussion in the constructivist institutionalist challenge

Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation

InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models

The InterPro protein families database: the classification resource after 15 years.

The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012

Expression of VjbR under Nutrient Limitation Conditions Is Regulated at the Post-Transcriptional Level by Specific Acidic pH Values and Urocanic Acid

VjbR is a LuxR homolog that regulates transcription of many genes including important virulence determinants of the facultative intracellular pathogen Brucella abortus. This transcription factor belongs to a family of regulators that participate in a cell-cell communication process called quorum sensing, which enables bacteria to respond to changes in cell population density by monitoring concentration of self produced autoinducer molecules. Unlike almost all other LuxR-type proteins, VjbR binds to DNA and activates transcription in the absence of any autoinducer signal. To investigate the mechanisms by which Brucella induces VjbR-mediated transcriptional activation, and to determine how inappropriate spatio-temporal expression of the VjbR target genes is prevented, we focused on the study of expression of vjbR itself. By assaying different parameters related to the intracellular lifestyle of Brucella, we identified a restricted set of conditions that triggers VjbR protein expression. Such conditions required the convergence of two signals of different nature: a specific pH value of 5.5 and the presence of urocanic acid, a metabolite involved in the connection between virulence and metabolism of Brucella. In addition, we also observed an urocanic acid, pH-dependent expression of RibH2 and VirB7, two additional intracellular survival-related proteins of Brucella. Analysis of promoter activities and determination of mRNA levels demonstrated that the urocanic acid-dependent mechanisms that induced expression of VjbR, RibH2, and VirB7 act at the post-transcriptional level. Taken together, our findings support a model whereby Brucella induces VjbR-mediated transcription by modulating expression of VjbR in response to specific signals related to the changing environment encountered within the host

Gene Ontology annotations and resources.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources