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Entry to the poster competition ran during Northumbria's Open Research and Reproducibility Conference 2023. Poster entries showcase open research practice in student work.

Entries to the poster competition ran during Northumbria's Open Research and Reproducibility Conference as part of Open Research Week 2023. Poster entries showcase open research practice in student and academic work. Titles WINNER Positive expressive writing interventions, subjective health and wellbeing: A systematic review, Lauren Hoult, Dr Michael Smith, Prof Mark Wetherell & Dr Trudi Edginton WINNER Micro-detectives: Forensic profiling with microbes, Nengi Ogbanga, Andrew Nelson, Darren Smith & Noemi Procopio WINNER Cementochronology: About the “tree rings” in our teeth, Valentina Perrone, Patrick Randolph-Quinney & Noemi Procopio Larger, more powerful studies: More work. But big rewards!, David Smailes Promote (or learn about) open research via a Reproducibilitea Journal Club, David Smailes To explore how a Breastfeeding Closed Facebook group administered by volunteers with additional breastfeeding training influences women’s experiences, particularly for those women for whom breastfeeding is not their cultural norm, Deborah Wade Impact of symptoms and disease severity on digital mobility outcomes in COPD, D. Megaritis, J. Buekers, T. Bonci, E. Hume, L. Alcock, A. Yarnall, E. M. Amigo, P. Brown, C. Buckley, S. Del Din, C. Echevarria, C. Mazzà, L. Rochester, J. Garcia Aymerich & I. Vogiatzis Growing my research village, Fiona Crouch Dying to Care. A constructivist grounded theory study identifying what factors prepare student nurses to care for dying patients, Helen Merlane Development of Innovative MODular Building System with Enhanced Fire, Environmental, Structural and Thermal Performance (MOD-FEST), Heshachanaa Rajanayagam How does garment cut influence the perception of attractiveness in the male somatotype? A comparative study of the focus of attraction on specific areas of the male body and its adaptation to inform garment cut in the UK, Jenni Moore The more-than-digital scrapmap: Exploring the generative possibilities of qualitative digital data, Joanna Hume Technological visuo-cognitive training in Parkinson’s disease: Preliminary findings from a pilot randomised controlled trial, Julia Das, Gill Barry, Rodrigo Vitorio, Richard Walker, Claire McDonald, Rosie Morris & Samuel Stuart Library support for open research: How the University Library can support you to make your work more open…, Leah Maughan & Rachel Branson A Phenomenological study into the experience of training to perform Intermittent Self Catheterisation (ISC) from the perspective of the Patient and the Nurse, Marion Haskin Be thankful to be joyful: Gratitude writing for wellbeing, Michael A. Smith & Yasmin Colborne Improving cultural understanding and 21st century skills with COIL, Ngoc D. Nguyen, Vilma B. Liwan & Thao T. P. Mai ‘It helps make the fuzzy go away’: Autistic adults’ reflections upon nature and wellbeing during the Covid-19 pandemic and across the life course, Dr Samantha Friedman Diagnosing relativistic electron distributions in the Van Allen radiation belts, S. Killey, I.J. Rae, S. Chakraborty, A.W. Smith, S.N. Bentley, M. R. Bakrania, R. Wainwright, C.E.J. Watt, & J. K. Sandhu

The impact of radial diffusion in storm time radiation belt dynamics is well-debated. In this study we quantify the changes and variability in radial diffusion coefficients during geomagnetic storms. A statistical analysis of Van Allen Probes data (2012–2019) is conducted to obtain measurements of the magnetic and electric power spectral densities for Ultra Low Frequency (ULF) waves, and corresponding radial diffusion coefficients. The results show global wave power enhancements occur during the storm main phase, and continue into the recovery phase. Local time asymmetries show sources of wave power are both external solar wind driving and internal sources from coupling with ring current ions and substorms. Wave power enhancements are also observed at low L values (L

No abstract available.

Aims: To provide insights into pathogenesis of disease progression and potential novel treatment targets for patients with heart failure by investigation of the plasma proteome using network analysis. Methods and results: The plasma proteome of 50 patients with heart failure who died or were rehospitalised were compared with 50 patients with heart failure, matched for age and sex, who did not have an event. Peptides were analysed on two-dimensional liquid chromatography coupled to tandem mass spectrometry (2D LC ESI-MS/MS) in high definition mode (HDMSE). We identified and quantified 3001 proteins, of which 51 were significantly up-regulated and 46 down-regulated with more than two-fold expression changes in those who experienced death or rehospitalisation. Gene ontology enrichment analysis and protein–protein interaction networks of significant differentially expressed proteins discovered the central role of metabolic processes in clinical outcomes of patients with heart failure. The findings revealed that a cluster of proteins related to glutathione metabolism, arginine and proline metabolism, and pyruvate metabolism in the pathogenesis of poor outcome in patients with heart failure who died or were rehospitalised. Conclusions: Our findings show that in patients with heart failure who died or were rehospitalised, the glutathione, arginine and proline, and pyruvate pathways were activated. These pathways might be potential targets for therapies to improve poor outcomes in patients with heart failure. © 2019 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.

The fundamental eigenfrequencies of standing Alfvén waves on closed geomagnetic field lines are estimated for the region spanning 5.9≤L < 9.5 over all MLT (Magnetic Local Time). The T96 magnetic field model and a realistic empirical plasma mass density model are employed using the time-of-flight approximation, refining previous calculations that assumed a relatively simplistic mass density model. An assessment of the implications of using different mass density models in the time-of-flight calculations is presented. The calculated frequencies exhibit dependences on field line footprint magnetic latitude and MLT, which are attributed to both magnetic field configuration and spatial variations in mass density. In order to assess the validity of the time-of-flight calculated frequencies, the estimates are compared to observations of FLR (Field Line Resonance) frequencies. Using IMAGE (International Monitor for Auroral Geomagnetic Effects) ground magnetometer observations obtained between 2001 and 2012, an automated FLR identification method is developed, based on the cross-phase technique. The average FLR frequency is determined, including variations with footprint latitude and MLT, and compared to the time-of-flight analysis. The results show agreement in the latitudinal and local time dependences. Furthermore, with the use of the realistic mass density model in the time-of-flight calculations, closer agreement with the observed FLR frequencies is obtained. The study is limited by the latitudinal coverage of the IMAGE magnetometer array, and future work will aim to extend the ground magnetometer data used to include additional magnetometer arrays.

Background: Current risk prediction models in heart failure (HF) including clinical characteristics and biomarkers only have moderate predictive value. The aim of this study was to use matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling to determine if a combination of peptides identified with MALDI-MS will better predict clinical outcomes of patients with HF. Methods: A cohort of 100 patients with HF were recruited in the biomarker discovery phase (50 patients who died or had a HF hospital admission vs. 50 patients who did not have an event). The peptide extraction from plasma samples was performed using reversed phase C18. Then samples were analysed using MALDI-MS. A multiple peptide biomarker model was discovered that was able to predict clinical outcomes for patients with HF. Finally, this model was validated in an independent cohort with 100 patients with HF. Results: After normalisation and alignment of all the processed spectra, a total of 11,389 peptides (m/z) were detected using MALDI-MS. A multiple biomarker model was developed from 14 plasma peptides that was able to predict clinical outcomes in HF patients with an area under the receiver operating characteristic curve (AUC) of 1.000 (p = 0.0005). This model was validated in an independent cohort with 100 HF patients that yielded an AUC of 0.817 (p = 0.0005) in the biomarker validation phase. Addition of this model to the BIOSTAT risk prediction model increased the predictive probability for clinical outcomes of HF from an AUC value of 0.643 to an AUC of 0.823 (p = 0.0021). Moreover, using the prediction model of fourteen peptides and the composite model of the multiple biomarker of fourteen peptides with the BIOSTAT risk prediction model achieved a better predictive probability of time-to-event in prediction of clinical events in patients with HF (p = 0.0005). Conclusions: The results obtained in this study suggest that a cluster of plasma peptides using MALDI-MS can reliably predict clinical outcomes in HF that may help enable precision medicine in HF. © 2018 The Author(s).

International audience; Understanding changes in the magnetospheric mass density during disturbed geomagnetic conditions provides valuable insight into the dynamics and structure of the environment. The mass density plays a significant role in a variety of magnetospheric processes, such as wave propagation, magnetic reconnection rates, and radiation belt dynamics. In this study, the spatial variations of total plasma mass density are explored through the analysis of Cluster observations. Data from the WHISPER (Waves of High frequency and Sounder for Probing of Electron density by Relaxation) and CODIF (ion Composition and Distribution Function analyzer) instruments, on board the four Cluster spacecraft for a time interval spanning 2001-2012, are used to determine empirical models describing the distribution of the total plasma mass density along closed geomagnetic field lines. The region considered covers field lines within 5.9≤L < 9.5, corresponding to the outer plasmasphere, plasmatrough, and near-Earth plasma sheet. This study extends previous work to examine and quantify spatial variations in the electron density, average ion mass, and total plasma mass density with Dst index. The results indicate that during periods of enhanced ring current strength, electron density is observed to decrease and average ion mass is observed to increase, compared with quiet geomagnetic conditions. The combination of these variations shows that although heavy ion concentration is enhanced, the decrease in plasma number density results in a general decrease in total plasma mass density during disturbed geomagnetic conditions. The observed decrease in mass density is in contrast to prevailing understanding and, due to the dependence of the Alfvén speed on mass density, has important implications for a range of plasma processes during storm time conditions (e.g., propagation of wave modes).