Developing the research infrastructure for design and technology education in England (and beyond)

This paper summarises initiatives taken by a partnership of Loughborough University and the Design and Technology Association in order to support action research by teachers in England. The theoretical and international contexts surrounding these initiatives as well as the initiatives themselves are described. These included an open access online journal, conference, archive and hub (www.dater.org.uk), specialist publications, a poster and conferences/workshops for tutors in Initial Teacher Education. Data is presented from Google Analytics monitoring of the online resources from July 2008 to July 2009, from a pilot questionnaire (N=33) and follow-up interviews. Research into this infrastructure continues, but the initial findings reported suggest the need for improved marketing and internet linking and the redesign of the IDATER Online home page. The online journal in particular has found much international use, having been accessed from 112 countries during the year. The on-going research will consider the quality of the resources themselves, as well as the infrastructure and its further development, of which they are part

VIPER: a visualisation tool for exploring inheritance inconsistencies in genotyped pedigrees

Pedigree genotype datasets are used for analysing genetic inheritance and to map genetic markers and traits. Such datasets consist of hundreds of related animals genotyped for thousands of genetic markers and invariably contain multiple errors in both the pedigree structure and in the associated individual genotype data. These errors manifest as apparent inheritance inconsistencies in the pedigree, and invalidate analyses of marker inheritance patterns across the dataset. Cleaning raw datasets of bad data points (incorrect pedigree relationships, unreliable marker assays, suspect samples, bad genotype results etc.) requires expert exploration of the patterns of exposed inconsistencies in the context of the inheritance pedigree. In order to assist this process we are developing VIPER (Visual Pedigree Explorer), a software tool that integrates an inheritance-checking algorithm with a novel space-efficient pedigree visualisation, so that reported inheritance inconsistencies are overlaid on an interactive, navigable representation of the pedigree structure

Visualising errors in animal pedigree genotype data

Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experimental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, which introduce inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of the genotype inheritance patterns in the context of the pedigree structure. Existing visualisations of pedigree structures are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, current table-based viewers of genotype marker information can highlight where errors become apparent but lack the functionality and interactive visual feedback to enable users to locate the underlying source of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why eventually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the ‘sandwich view’, is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task

An XML transfer schema for exchange of genomic and genetic mapping data: implementation as a web service in a Taverna workflow

<p>Abstract</p> <p>Background</p> <p>Genomic analysis, particularly for less well-characterized organisms, is greatly assisted by performing comparative analyses between different types of genome maps and across species boundaries. Various providers publish a plethora of on-line resources collating genome mapping data from a multitude of species. Datasources range in scale and scope from small bespoke resources for particular organisms, through larger web-resources containing data from multiple species, to large-scale bioinformatics resources providing access to data derived from genome projects for model and non-model organisms. The heterogeneity of information held in these resources reflects both the technologies used to generate the data and the target users of each resource. Currently there is no common information exchange standard or protocol to enable access and integration of these disparate resources. Consequently data integration and comparison must be performed in an <it>ad hoc </it>manner.</p> <p>Results</p> <p>We have developed a simple generic XML schema (GenomicMappingData.xsd – GMD) to allow export and exchange of mapping data in a common lightweight XML document format. This schema represents the various types of data objects commonly described across mapping datasources and provides a mechanism for recording relationships between data objects. The schema is sufficiently generic to allow representation of any map type (for example genetic linkage maps, radiation hybrid maps, sequence maps and physical maps). It also provides mechanisms for recording data provenance and for cross referencing external datasources (including for example ENSEMBL, PubMed and Genbank.). The schema is extensible via the inclusion of additional datatypes, which can be achieved by importing further schemas, e.g. a schema defining relationship types. We have built demonstration web services that export data from our ArkDB database according to the GMD schema, facilitating the integration of data retrieval into Taverna workflows.</p> <p>Conclusion</p> <p>The data exchange standard we present here provides a useful generic format for transfer and integration of genomic and genetic mapping data. The extensibility of our schema allows for inclusion of additional data and provides a mechanism for typing mapping objects via third party standards. Web services retrieving GMD-compliant mapping data demonstrate that use of this exchange standard provides a practical mechanism for achieving data integration, by facilitating syntactically and semantically-controlled access to the data.</p

Optimising efficacy of antibiotics against systemic infection by varying dosage quantities and times

Mass production and use of antibiotics has led to the rise of resistant bacteria, a problem possibly exacerbated by inappropriate and non-optimal application. Antibiotic treatment often follows fixed-dose regimens, with a standard dose of antibiotic administered equally spaced in time. But are such fixed-dose regimens optimal or can alternative regimens be designed to increase efficacy? Yet, few mathematical models have aimed to identify optimal treatments based on biological data of infections inside a living host. In addition, assumptions to make the mathematical models analytically tractable limit the search space of possible treatment regimens (e.g. to fixed-dose treatments). Here, we aimed to address these limitations by using experiments in a Galleria mellonella (insect) model of bacterial infection, to create a fully parametrised mathematical model of a systemic Vibrio infection. We successfully validated this model with biological experiments, including treatments unseen by the mathematical model. Then, by applying artificial intelligence, this model was used to determine optimal antibiotic dosage regimens to treat the host to maximise survival while minimising total antibiotic used. As expected, host survival increased as total quantity of antibiotic applied during the course of treatment increased. However, many of the optimal regimens tended to follow a large initial ‘loading’ dose followed by doses of incremental reductions in antibiotic quantity (dose ‘tapering’). Moreover, application of the entire antibiotic in a single dose at the start of treatment was never optimal, except when the total quantity of antibiotic was very low. Importantly, the range of optimal regimens identified was broad enough to allow the antibiotic prescriber to choose a regimen based on additional criteria or preferences. Our findings demonstrate the utility of an insect host to model antibiotic therapies in vivo and the approach lays a foundation for future regimen optimisation for patient and societal benefits

Crowdsourcing citation-screening in a mixed-studies systematic review: a feasibility study

Abstract: Background: Crowdsourcing engages the help of large numbers of people in tasks, activities or projects, usually via the internet. One application of crowdsourcing is the screening of citations for inclusion in a systematic review. There is evidence that a ‘Crowd’ of non-specialists can reliably identify quantitative studies, such as randomized controlled trials, through the assessment of study titles and abstracts. In this feasibility study, we investigated crowd performance of an online, topic-based citation-screening task, assessing titles and abstracts for inclusion in a single mixed-studies systematic review. Methods: This study was embedded within a mixed studies systematic review of maternity care, exploring the effects of training healthcare professionals in intrapartum cardiotocography. Citation-screening was undertaken via Cochrane Crowd, an online citizen science platform enabling volunteers to contribute to a range of tasks identifying evidence in health and healthcare. Contributors were recruited from users registered with Cochrane Crowd. Following completion of task-specific online training, the crowd and the review team independently screened 9546 titles and abstracts. The screening task was subsequently repeated with a new crowd following minor changes to the crowd agreement algorithm based on findings from the first screening task. We assessed the crowd decisions against the review team categorizations (the ‘gold standard’), measuring sensitivity, specificity, time and task engagement. Results: Seventy-eight crowd contributors completed the first screening task. Sensitivity (the crowd’s ability to correctly identify studies included within the review) was 84% (N = 42/50), and specificity (the crowd’s ability to correctly identify excluded studies) was 99% (N = 9373/9493). Task completion was 33 h for the crowd and 410 h for the review team; mean time to classify each record was 6.06 s for each crowd participant and 3.96 s for review team members. Replicating this task with 85 new contributors and an altered agreement algorithm found 94% sensitivity (N = 48/50) and 98% specificity (N = 9348/9493). Contributors reported positive experiences of the task. Conclusion: It might be feasible to recruit and train a crowd to accurately perform topic-based citation-screening for mixed studies systematic reviews, though resource expended on the necessary customised training required should be factored in. In the face of long review production times, crowd screening may enable a more time-efficient conduct of reviews, with minimal reduction of citation-screening accuracy, but further research is needed

ArkMAP: integrating genomic maps across species and data sources

BACKGROUND: The visualisation of genetic and genomic maps aligned within and between species and across data sources can be used to inform studies of genome evolution, assist genome assembly projects and aid gene discovery and identification. Whilst annotation, integration and exploration of assembled genome sequences is well supported, there are fewer tools available which can display genetic maps for less well-characterized species, and integrate these maps with annotated reference genomes to support cross species comparisons. RESULTS: We have developed a desktop application to draw and align genetic and genomic maps, retrieved from remote data sources or loaded as local files. Maps can be retrieved from our public map database ArkDB or from any Ensembl data source (i.e. Ensembl and Ensembl Genomes). By using the JEnsembl API, maps can be drawn for any release version of any of the thousands of species present in Ensembl data sources, allowing not only inter-specific comparisons, but also comparisons between different versions/revisions of assembled genomes. Maps can be aligned by relating identical or synonymous markers across maps, or through the gene homology/orthology relationship data stored in the Ensembl Compara databases, allowing ready visualization of regions of conserved synteny between species. The map drawing canvas is highly configurable, supports interactive exploration of maps, markers and relationships and allows export of publication quality graphics. CONCLUSIONS: ArkMAP allows users to draw and interactively explore gene and variation maps for any version of any annotated genome curated in the Ensembl data sources, and to integrate local mapping data. The maps and inter-map relationships drawn are highly configurable and ArkMAP may be used to produce publication quality graphics. ArkMAP is freely available as an auto-updating Java ‘Web Start’ application, or as a standalone archived application

Deception has no acute or residual effect on cycling time trial performance but negatively effects perceptual responses.

Feedback deception is used to explore the importance of expectations on pacing strategy and performance in self-paced exercise. The deception of feedback from a previous performance explores the importance of experience knowledge on exercise behaviour. This study aimed to explore the acute and residual effects of the deception of previous performance speed on perceptual responses and performance in cycling time trials.A parallel-group design.Twenty cyclists were assigned to a control or deception group and performed 16.1km time trials. Following a ride-alone baseline time trial (FBL), participants performed against a virtual avatar representing their FBL performance (PACER), then completed a subsequent ride-alone time trial (SUB). The avatar in the deception group, however, was unknowingly set 2% faster than their FBL.Both groups performed faster in PACER than FBL and SUB (p<0.05), but SUB was not significantly different to FBL. Affect was more negative and Ratings of Perceived Exertion (RPE) were higher in PACER than FBL in the deception group (p<0.05).The presence of a visual pacer acutely facilitated time trial performance, but deceptive feedback had no additional effect on performance. The deception group, however, experienced more negative affect and higher RPE in PACER, whereas these responses were absent in the control group. The performance improvement was not sustained in SUB, suggesting no residual performance effects occurred

Global agricultural intensification during climate change: a role for genomics

Agriculture is now facing the ‘perfect storm’ of climate change, increasing costs of fertilizer and rising food demands from a larger and wealthier human population. These factors point to a global food deficit unless the efficiency and resilience of crop production is increased. The intensification of agriculture has focused on improving production under optimized conditions, with significant agronomic inputs. Furthermore, the intensive cultivation of a limited number of crops has drastically narrowed the number of plant species humans rely on. A new agricultural paradigm is required, reducing dependence on high inputs and increasing crop diversity, yield stability and environmental resilience. Genomics offers unprecedented opportunities to increase crop yield, quality and stability of production through advanced breeding strategies, enhancing the resilience of major crops to climate variability, and increasing the productivity and range of minor crops to diversify the food supply. Here we review the state of the art of genomic-assisted breeding for the most important staples that feed the world, and how to use and adapt such genomic tools to accelerate development of both major and minor crops with desired traits that enhance adaptation to, or mitigate the effects of climate change