The peptide motif of the single dominantly expressed class I molecule of the chicken MHC can explain the response to a molecular defined vaccine of infectious bursal disease virus (IBDV)

In contrast to typical mammals, the chicken MHC (the BF-BL region of the B locus) has strong genetic associations with resistance and susceptibility to infectious pathogens as well as responses to vaccines. We have shown that the chicken MHC encodes a single dominantly expressed class I molecule whose peptide-binding motifs can determine resistance to viral pathogens, such as Rous sarcoma virus and Marek’s disease virus. In this report, we examine the response to a molecular defined vaccine, fp-IBD1, which consists of a fowlpox virus vector carrying the VP2 gene of infectious bursal disease virus (IBDV) fused with ?-galactosidase. We vaccinated parental lines and two backcross families with fp-IBD1, challenged with the virulent IBDV strain F52/70, and measured damage to the bursa. We found that the MHC haplotype B15 from line 15I confers no protection, whereas B2 from line 61 and B12 from line C determine protection, although another locus from line 61 was also important. Using our peptide motifs, we found that many more peptides from VP2 were predicted to bind to the dominantly expressed class I molecule BF2*1201 than BF2*1501. Moreover, most of the peptides predicted to bind BF2*1201 did in fact bind, while none bound BF2*1501. Using peptide vaccination, we identified one B12 peptide that conferred protection to challenge, as assessed by bursal damage and viremia. Thus, we show the strong genetic association of the chicken MHC to a T cell vaccine can be explained by peptide presentation by the single dominantly expressed class I molecule

Impact Evaluation of an Emerging European Health Project – the MIDAS Model

Background: This paper describes the impact evaluation of a large big data platform initiative that is being undertaken in order to increase the probability of its success. The initiative, MIDAS (Meaningful Integration of Data Analytics and Services), is a European health-based Horizon 2020 project comprising a consortium of members from various universities, research institutions, and government agencies. Objectives: The purpose of the paper is to present a pioneering platform that will support healthcare policymakers in their decision-making by enabling greater and more efficient use of their data. The goal is to present and evaluate the results of the MIDAS project across four countries. Methods/Approach: The literature is replete with examples of worthwhile technology projects that have failed due to user resistance. In order to avoid such failure, and ensure the success of the final MIDAS platform, a detailed impact evaluation is being undertaken at timed periods of development. Results: This paper describes the impact evaluation process, outlining the use of Q-methodology and the development of a 36-item concourse using the HTMLQ system for that purpose. Conclusions: This research contributes to the overall understanding of how impact evaluation can be undertaken at timed periods during the development of an innovative technology for organisational purposes

Transforming Health through Big Data: Challenges and Considerations

Modern healthcare is increasingly dependent on good data, and effective information systems, for care delivery, and to develop and evaluate health policy. The context of big data differs in significant ways from traditional types of health data, while the use of big data for epidemiology and public health is becoming more common, the use of these tools for health service planning and health policy making lags behind. A large EU funded project (titled MIDAS) that focuses on merging, analysing and visualising data from heterogeneous sources to support health policy makers work in using and accessing health data across EU countries is underway. This paper briefly describes the key challenges that must be met to access, use and make sense of this big data in healthcare, focusing on legal, governance and ethical issues. Unless these issues are dealt with, the promise of Big Data for health, will never be fulfilled

Logic Model Early Stage Evaluation of a European Public Health Data Analytic Framework

The multi-national MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate utilisation of a wide range of health and social care data to enable integration of heterogeneous data sources, providing analytics, forecasting tools and bespoke visualisations of actionable epidemiological data. An evaluation framework starting with a logic model and semi-structured interviews using the principles of realist evaluation was developed working with end users and software developers. Parallel case studies were used to address the requirements of stakeholders at critical time points during the project. The objective was to ensure IT systems development is in line with end user requirements. Overall, the early stage interviews findings indicated the logic model is an effective framework for the evaluation of the project

The effects of physiological and injurious hydrostatic pressure on murine ex vivo articular and growth plate cartilage explants:an RNAseq study

Chondrocytes are continuously exposed to loads placed upon them. Physiological loads are pivotal to the maintenance of articular cartilage health, while abnormal loads contribute to pathological joint degradation. Similarly, the growth plate cartilage is subject to various loads during growth and development. Due to the high-water content of cartilage, hydrostatic pressure is considered one of the main biomechanical influencers on chondrocytes and has been shown to play an important role in the mechano-regulation of cartilage. Herein, we conducted RNAseq analysis of ex vivo hip cap (articular), and metatarsal (growth plate) cartilage cultures subjected to physiological (5 MPa) and injurious (50 MPa) hydrostatic pressure, using the Illumina platform (n = 4 replicates). Several hundreds of genes were shown to be differentially modulated by hydrostatic pressure, with the majority of these changes evidenced in hip cap cartilage cultures (375 significantly upregulated and 322 downregulated in 5 MPa versus control; 1022 upregulated and 724 downregulated in 50 MPa versus control). Conversely, fewer genes were differentially affected by hydrostatic pressure in the metatarsal cultures (5 significantly upregulated and 23 downregulated in 5 MPa versus control; 7 significantly upregulated and 19 downregulated in 50 MPa versus control). Using Gene Ontology annotations for Biological Processes, in the hip cap data we identified a number of pathways that were modulated by both physiological and injurious hydrostatic pressure. Pathways upregulated in response to 50 MPa versus control, included those involved in the generation of precursor metabolites and cellular respiration. Biological processes that were downregulated in this tissue included ossification, connective tissue development, and chondrocyte differentiation. Collectively our data highlights the divergent chondrocyte phenotypes in articular and growth plate cartilage. Further, we show that the magnitude of hydrostatic pressure application has distinct effects on gene expression and biological processes in hip cap cartilage explants. Finally, we identified differential expression of a number of genes that have previously been identified as osteoarthritis risk genes, including Ctsk, and Chadl. Together these data may provide potential genetic targets for future investigations in osteoarthritis research and novel therapeutics. [Abstract copyright: Copyright © 2023 Bourne, Hesketh, Sharma, Bucca, Bush and Staines.

A Computed Microtomography Method for Understanding Epiphyseal Growth Plate Fusion

The epiphyseal growth plate is a developmental region responsible for linear bone growth, in which chondrocytes undertake a tightly regulated series of biological processes. Concomitant with the cessation of growth and sexual maturation, the human growth plate undergoes progressive narrowing, and ultimately disappears. Despite the crucial role of this growth plate fusion ‘bridging’ event, the precise mechanisms by which it is governed are complex and yet to be established. Progress is likely hindered by the current methods for growth plate visualisation; these are invasive and largely rely on histological procedures. Here we describe our non-invasive method utilising synchrotron X-ray computed microtomography for the examination of growth plate bridging, which ultimately leads to its closure coincident with termination of further longitudinal bone growth. We then apply this method to a dataset obtained from a benchtop microcomputed tomography scanner to highlight its potential for wide usage. Furthermore, we conduct finite element modelling at the micron-scale to reveal the effects of growth plate bridging on local tissue mechanics. Employment of these 3D analyses of growth plate bone bridging is likely to advance our understanding of the physiological mechanisms that control growth plate fusion

Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach

Despite advances in technology and medical science, modern health-based projects are open to systemic failure due to many factors. These include I.T. developer’s lack of awareness with regard to end-user needs, poor communication amongst all parties concerned and inappropriate or inadequate tests of the emerging system. Other issues may be external (e.g. political and legal) such as sharing of patient data and issues surrounding consent. The goal of this paper is to take a major health-based European model in current development and explore how it addresses the needs of four institutions in four different countries, and how it will meet their respective needs. The evaluation was designed within a Logic Model, and uses the Framework approach, and Q-Methodology to assess both impact and evaluation. Data will be collected through longitudinal semi-structured interviews and Q-scoring with principal stakeholders and developers at each stage of the project. This approach, recurring interviews with the same key players in the project, will help ensure that there is mutual understanding between I.T. developers and end-users of the system. The final system is meant to provide effective health-based decision support systems for policy makers. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Q-Method Evaluation of a European Health Data Analytic End User Framework

MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate the utilisation of a wide range of health and social care data to support better policy making. Our aim is to explore the use of Q-methodology as part of the evaluation of the implementation of the MIDAS project. Q-methodology is used to identify perspectives and viewpoints on a particular topic. In our case, we defined a concourse of statements relevant to project implementation and goals, by working from a logic model previously developed for the evaluation, and structured interviews with project participants. A 36-item concourse was delivered to participants, using the HTMLQ system. Analysis was done in the qmethod package. Participants had a range of professional backgrounds, and a range of roles in the project, including developers, end-users, policy staff, and health professionals. The q-sort is carried out at 14 months into the project, a few months before the intended first release of the software being developed. Sixteen people took part, 6 developers, 5 managers, 2 health professionals and 3 others. Three factors (distinct perspectives) were identified in the data. These were tentatively labelled ‘Technical optimism’, ‘End-user focus’ and ‘End-user optimism’. These loaded well onto individuals, and there were few consensus statements. Analysis of these factors loaded well onto individuals with a significant number of consensus statements identified. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p