Identifying research priorities for chronic disease management in primary care: results of an Irish James Lind Alliance Priority Setting Partnership.

Background: Chronic conditions are extremely common, with approximately 1 million people in Ireland currently affected by the four most common chronic conditions alone. This is expected to significantly increase in the near future due to Ireland's aging population. Identifying the priorities of patients, carers, and healthcare professionals for primary care research in chronic condition management could ensure future work is relevant and that resulting service changes and policy decisions align with the needs of those most affected.

Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study.

Background: This paper discusses how collective intelligence (CI) methods can be implemented to improve government data infrastructures, not only to support understanding and primary use of complex national data but also to increase the dissemination and secondary impact of research based on these data. The case study uses the Northern Ireland Longitudinal Study (NILS), a member of the UK family of census/administrative data longitudinal studies (UKLS).

Methods: A stakeholder-engaged CI approach was applied to inform the transformation of the NILS Research Support Unit (RSU) infrastructure to support researchers in their use of government data, including collaborative decision-making and better dissemination of research outputs.

Acute stress symptoms 1-2 weeks after stroke predict the subsequent development of post-traumatic stress symptoms: A prospective cohort study.

Objective: To date no research has examined the potential influence of acute stress symptoms (ASD) on subsequent development of post-traumatic stress disorder (PTSD) symptoms in stroke survivors. Our objective was to examine whether acute stress symptoms measured 1-2 weeks post-stroke predicted the presence of post-traumatic stress symptoms measured 6-12 weeks later.

Design: Prospective within-groups study.

Ethically cleared to launch?

Rules are needed for human research in commercial spaceflight.

Designing an e-learning tool to support health practitioners caring for patients taking multiple medications.

Population ageing and improvements in healthcare mean the number of people living with two or more chronic conditions, or 'multimorbidity', is rapidly increasing. This presents a challenge to current disease-specific care delivery models. Adherence to prescribed medications appears particularly challenging for individuals living with multimorbidity, given the often-complex drug regimens required to treat multiple conditions.

The identification of needs and development of best practice guidance for the psychological support of frontline healthcare workers during and after COVID-19: A protocol for the FLoWS project.

Recent estimates suggest that up to 34% of frontline workers in healthcare (FLWs) at the forefront of the COVID-19 pandemic response are reporting elevated symptoms of psychological distress due to resource constraints, ineffective treatments, and concerns about self-contamination. However, little systematic research has been carried out to assess the mental health needs of FLWs in Europe, or the extent of psychological suffering in FLWs within different European countries of varying outbreak severity. Accordingly, this project will employ a mixed-methods approach over three work packages to develop best-practice guidelines for alleviating psychological distress in FLWs during the different phases of the pandemic.

The relative effectiveness of psychotherapeutic techniques and delivery modalities for chronic pain: a protocol for a systematic review and network meta-analysis.

: There is increasing evidence for the use of psychotherapies, including cognitive behavioural therapy, acceptance and commitment therapy, and mindfulness based stress reduction therapy, as an approach to management of chronic pain. Similarly, online psychotherapeutic interventions have been shown to be efficacious, and to arguably overcome practical barriers associated with traditional face-to-face treatment for chronic pain. This is a protocol for a systematic review and network meta-analysis aiming to evaluate and rank psychotherapies (delivered in person and online) for chronic pain patients.

Analysis of Conformational B-Cell Epitopes in the Antibody-Antigen Complex Using the Depth Function and the Convex Hull.

The prediction of conformational b-cell epitopes plays an important role in immunoinformatics. Several computational methods are proposed on the basis of discrimination determined by the solvent-accessible surface between epitopes and non-epitopes, but the performance of existing methods is far from satisfying. In this paper, depth functions and the k-th surface convex hull are used to analyze epitopes and exposed non-epitopes.

An ensemble method for prediction of conformational B-cell epitopes from antigen sequences.

Epitopes are immunogenic regions in antigen protein. Prediction of B-cell epitopes is critical for immunological applications. B-cell epitopes are categorized into linear and conformational.

A large-scale comparison of computational models on the residue flexibility for NMR-derived proteins.

As an alternative to X-ray crystallography, nuclear magnetic resonance (NMR) has also emerged as the method of choice for studying both protein structure and dynamics in solution. However, little work using computational models such as Gaussian network model (GNM) and machine learning approaches has focused on NMR-derived proteins to predict the residue flexibility, which is represented by the root mean square deviation (RMSD) with respect to the average structure. We provide a large-scale comparison of computational models, including GNM, parameter-free GNM and several linear regression models using local solvent exposures as inputs, based on a dataset of 1609 protein chains whose structures were resolved by NMR.