Molecular Insights into α-Synuclein Fibrillation:A Raman Spectroscopy and Machine Learning Approach

The aggregation of α-synuclein is crucial to the development of Lewy body diseases, including Parkinson's disease and dementia with Lewy bodies. The aggregation pathway of α-synuclein typically involves a defined sequence of nucleation, elongation, and secondary nucleation, exhibiting prion-like spreading. This study employed Raman spectroscopy and machine learning analysis, alongside complementary techniques, to characterize the biomolecular changes during the fibrillation of purified recombinant wild-type α-synuclein protein. Monomeric α-synuclein was produced, purified, and subjected to a 7-day fibrillation assay to generate preformed fibrils. Stages of α-synuclein fibrillation were analyzed using Raman spectroscopy, with aggregation confirmed through negative staining transmission electron microscopy, mass spectrometry, and light scattering analyses. A machine learning pipeline incorporating principal component analysis and uniform manifold approximation and projection was used to analyze the Raman spectral data and identify significant peaks, resulting in differentiation between sample groups. Notable spectral shifts in α-synuclein were found in various stages of aggregation. Early changes (D1) included increases in α-helical structures (1303, 1330 cm-1) and β-sheet formation (1045 cm-1), with reductions in COO- and CH2 bond regions (1406, 1445 cm-1). By D4, these structural shifts persist with additional β-sheet features. At D7, a decrease in β-sheet H-bonding (1625 cm-1) and tyrosine ring breathing (830 cm-1) indicates further structural stabilization, suggesting a shift from initial helical structures to stabilized β-sheets and aggregated fibrils. Additionally, alterations in peaks related to tyrosine, alanine, proline, and glutamic acid were identified, emphasizing the role of these amino acids in intramolecular interactions during the transition from α-helical to β-sheet conformational states in α-synuclein fibrillation. This approach offers insight into α-synuclein aggregation, enhancing the understanding of its role in Lewy body disease pathophysiology and potential diagnostic relevance.</p

From fear to empowerment: the impact of employees AI awareness on workplace well-being – a new insight from the JD–R model

PurposeThe primary purpose of the study was to explore the impact of health workers’ awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD–R) model, the study aimed to provide insights into how health workers’ perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study’s findings could inform strategies for supporting healthcare workers during technological transformations.Design/methodology/approachThe study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling.FindingsThe study findings revealed that health workers’ AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers’ workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers’ AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour.Research limitations/implicationsWhile the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables.Practical implicationsThe study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers’ AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives.Originality/valueThe study contributes to the existing literature by addressing a relatively unexplored area – the impact of AI awareness on healthcare workers’ well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers’ perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD–R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations

Reimagining Higher Education Learning Spaces:Assembling Theory, Methods, and Practice

The Higher Education (HE) sector faces an increasingly challenging environment with key themes identified as: the economic and social fallout from the Covid-19 pandemic,shifting politics, changing expectations around education, and technological advances(Marshall et al., 2024). There are particular concerns about aspects including: a mismatch between tuition fee caps and inflation, reduced government grants (Atherton et al., 2024),decreasing numbers of international students (Bolton et al., 2024), concerns over pensions, pay, and working conditions (University and College Union, 2022), new thresholds for student outcomes (Office for Students, 2022), and gaps around research funding(Butland, 2022)

Effectiveness of interventions for psychological distress following traumatic injury:A systematic review

BackgroundTraumatic injury poses significant physical and psychological challenges, often resulting in psychological distress, encompassing symptoms of anxiety, depression and post-traumatic stress. Despite the recognised need for psychological care in trauma rehabilitation, there is limited empirical evidence of effective interventions tailored specifically for individuals with traumatic injuries, leading to a practice-evidence gap.ObjectivesThis review aimed to evaluate the effectiveness of psychological and behavioural interventions for reducing psychological distress in adults following traumatic injury.MethodsThis systematic review followed a published protocol (CRD4202342946) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist and the Synthesis Without Meta-analysis (SWiM) in systematic reviews reporting items. Peer-reviewed studies were identified through searches of MEDLINE, APA PsycInfo, CINAHL and Embase databases. Eligible studies involved adults aged 18 and older who had experienced physical trauma requiring immediate medical attention. Studies involving participants with neurological injuries and/or military personnel were not included. Both English- and non-English-language articles were considered. Effect direction was employed as the method of synthesis and risk of bias was assessed using the Cochrane Effective Practice and Organisation of Care (EPOC 9) nine-item assessment tool.ResultsA total of six studies met the review eligibility criteria. There was considerable heterogeneity across the interventions in terms of their nature, timing and duration, however all interventions were delivered within 3-months post-injury. Most studies reported positive intervention effects, with no adverse effects reported. Cognitive Behavioural Therapy (CBT) was the most reported intervention across the studies.ConclusionsThe review findings highlight the preliminary evidence supporting CBT as a viable option for reducing psychological distress following traumatic injury. However, this may be explained by the dominance of CBT in the literature due to its structured nature, availability and suitability for research, potentially limiting the visibility of alternative therapeutic approaches. Further, these findings are constrained by study limitations, including small sample sizes, heterogeneity of injury types and severity, reliance on self-reported outcomes, and limited follow-up data. Future research should aim to include longitudinal follow-up assessments and explore alternative therapeutic approaches to contribute to our understanding of meaningful trauma rehabilitation methods

Developing and implementing whole systems approaches to reduce inequalities in childhood obesity:A mixed methods study in Dundee, Scotland

Background: UK local authorities are developing and implementing Whole Systems Approaches to childhood obesity to tackle persistent and complex health inequalities. However, there is a lack of research on the practical application of these approaches. This paper reports on findings of a study into the initial implementation of this approach in Dundee, Scotland. Study design/methods: We applied a mixed methods research design: 1) semi-structured interviews (n = 9) with partnership members; 2) training members as peer researchers to interview their wider networks; n = 17); 3) an online survey among wider stakeholders (n = 27); and 4) two action learning sets with decision makers. Interview data was analysed using thematic framework analysis and survey data was analysed using descriptive statistics. Results: Dundee stakeholders stated that they had good knowledge of childhood obesity prevention efforts, but their engagement with working groups around identified priority themes was still limited, due to a lack of awareness about existing structures and knowledge about sustainable, impactful strategies, which were not always well-aligned between key organisations. Conclusions: Our findings extend current literature on facilitators for Whole Systems Approaches in public health by highlighting that understanding of strategies and wider structures are crucial to build capacity and maintain engagement to address inequalities. We identified an ongoing need for targeted communication and diverse involvement opportunities for different stakeholder groups.</p

REBEL REBEL:The graphic biography of David Bowie: Chapter 15

Set in 1967, this chapter focuses on David Bowie’s intensive mime training with his mentor Lindsay Kemp, his first theatrical stage appearances in the mime production Pierrot in Turquoise, and the beginning of his affair with the play’s costume designer Natasha Korniloff

Advancements in Vibration Testing:Effects on Thermal Performance and Degradation of Modern Batteries

Lithium-ion cells are increasingly being used as central power storage systems for modern applications, i.e., e-bikes, electric vehicles (EVs), satellites, and spacecraft, and they face significant and constant vibrations. This review examines how these vibrations affect the batteries’ mechanical, thermal, and electrical properties. Vibrations can cause structural issues, such as the separation of electrodes and the deformation of separators. These problems raise internal resistance and lead to localized heat generation. As a result, thermal management becomes more complicated, battery aging accelerates, and safety risks arise, including short circuits and thermal runaways. To tackle these challenges, we need more realistic testing protocols that consider the combined effects of vibrations, temperature, and mechanical stress. Improving thermal management systems (TMSs) using advanced cooling techniques and materials, e.g., phase change solutions, can help to alleviate these problems. It is also essential to design batteries with vibration-resistant materials and enhanced structural integrity to boost their durability. Moreover, vibrations play a significant role in various degradation mechanisms, including dendrite formation, self-discharge, and lithium plating, all of which can reduce battery capacity and lifespan. Our current research builds on these insights using a multiscale physics-based modelling approach to investigate how vibrations interact with thermal behaviour and contribute to battery degradation. By combining computational models with experimental data, we aim to develop strategies and tools to enhance lithium-ion batteries’ safety, reliability, and longevity in challenging environments