Probing and manipulating the gut microbiome with chemistry and chemical tools

The human gut microbiome represents an extended “second genome” harbouring about 1015 microbes containing >100 times the number of genes as the host. States of health and disease are largely mediated by host-microbial metabolic interplay, and the microbiome composition also underlies the differential responses to chemotherapeutic agents between people. Chemical information will be the key in order to tackle this complexity and discover specific gut microbiome metabolism for creating more personalised interventions. Additionally, rising antibiotic resistance and growing awareness of gut microbiome effects iscreating a need for non-microbicidal therapeutic interventions. We classify chemical interventions for the gut microbiome into categories like molecular decoys, bacterial conjugation inhibitors, colonization resistance-stimulating molecules, “prebiotics” to promote the growth of beneficial microbes and inhibitors of specific gut microbial enzymes. Moreover, small molecule probes including click chemistry probes, artificial substrates for assaying gut bacterial enzymes and receptor agonists/antagonists which engage host receptors interacting with the microbiome, are some other promising developments in the expanding chemical toolkit for probing and modulating the gut microbiome. This review explicitly excludes ‘biologics’ such as probiotics, bacteriophages, and CRISPR to concentrate on chemistry and chemical tools like chemoproteomics in the gut-microbiome context

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

Spatiotemporal diversity in molecular and functional abnormalities in the mdx dystrophic brain

Duchenne muscular dystrophy (DMD) is characterized by progressive muscle degeneration and neuropsychiatric abnormalities. Loss of full-length dystrophins is both necessary and sufficient to initiate DMD. These isoforms are expressed in the hippocampus, cerebral cortex (Dp427c), and cerebellar Purkinje cells (Dp427p). However, our understanding of the consequences of their absence, which is crucial for developing targeted interventions, remains inadequate. We combined RNA sequencing with genome-scale metabolic modelling (GSMM), immunodetection, and mitochondrial assays to investigate dystrophic alterations in the brains of the mdx mouse model of DMD. The cerebra and cerebella were analysed separately to discern the roles of Dp427c and Dp427p, respectively. Investigating these regions at 10 days (10d) and 10 weeks (10w) followed the evolution of abnormalities from development to early adulthood. These time points also encompass periods before onset and during muscle inflammation, enabling assessment of the potential damage caused by inflammatory mediators crossing the dystrophic blood-brain barrier. For the first time, we demonstrated that transcriptomic and functional dystrophic alterations are unique to the cerebra and cerebella and vary substantially between 10d and 10w. The common anomalies involved altered numbers of retained introns and spliced exons across mdx transcripts, corresponding with alterations in the mRNA processing pathways. Abnormalities in the cerebra were significantly more pronounced in younger mice. The top enriched pathways included those related to metabolism, mRNA processing, and neuronal development. GSMM indicated dysregulation of glucose metabolism, which corresponded with GLUT1 protein downregulation. The cerebellar dystrophic transcriptome, while significantly altered, showed an opposite trajectory to that of the cerebra, with few changes identified at 10 days. These late defects are specific and indicate an impact on the functional maturation of the cerebella that occurs postnatally. Although no classical neuroinflammation markers or microglial activation were detected at 10 weeks, specific differences indicate that inflammation impacts DMD brains. Importantly, some dystrophic alterations occur late and may therefore be amenable to therapeutic intervention, offering potential avenues for mitigating DMD-related neuropsychiatric defects.</p

Prevalence of Being Obese, Overweight, and Underweight Among Jordanian Children and Adolescents Based on International Growth Standards

Objectives: The rise of obesity and other nutrition-related conditions among children and adolescents is a global challenge, particularly in the Middle East. This study aimed to determine the prevalence of being underweight, overweight, and obese among Jordanian children and adolescents using the body mass index (BMI) percentiles of the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) standards. Methods: This retrospective cross-sectional/longitudinal study analyzed 58,474 (42.6% males; 57.4% females) height, weight, and BMI-for-age records from 31508 healthy Jordanian children and adolescents aged 2–19 years. The data were retrieved from the Ministry of Health’s nationwide electronic database (2017–2023) and assessed using the CDC and WHO growth standards. Logistic regression was performed to assess the variables associated with overweight/obese status. Results: The prevalence of being underweight, overweight, and obese varied by the reference used, as more cases of being obese and underweight were reported when applying the CDC standards. The regression models showed the males had significantly lower odds of being overweight and obese than the females. Increased age was associated with higher odds of being overweight and obese, with annual increases observed across all age groups. Conclusions: Using the WHO and CDC standards, the prevalence of being underweight was higher in the males aged 6 years and older, while being overweight and obese was more prevalent in the females. The observed annual increase in the prevalence of being overweight and obese underscores the need for targeted strategies. Growth references tailored to regional profiles may improve national nutrition policies for Jordanian children and adolescents

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

Burdens of type 2 diabetes and cardiovascular disease attributable to sugar-sweetened beverages in 184 countries

The consumption of sugar-sweetened beverages (SSBs) is associated with type 2 diabetes (T2D) and cardiovascular diseases (CVD). However, an updated and comprehensive assessment of the global burden attributable to SSBs remains scarce. Here we estimated SSB-attributable T2D and CVD burdens across 184 countries in 1990 and 2020 globally, regionally and nationally, incorporating data from the Global Dietary Database, jointly stratified by age, sex, educational attainment and urbanicity. In 2020, 2.2 million (95% uncertainty interval 2.0–2.3) new T2D cases and 1.2 million (95% uncertainty interval 1.1–1.3) new CVD cases were attributable to SSBs worldwide, representing 9.8% and 3.1%, respectively, of all incident cases. Globally, proportional SSB-attributable burdens were higher among men versus women, younger versus older adults, higher- versus lower-educated adults, and adults in urban versus rural areas. By world region, the highest SSB-attributable percentage burdens were in Latin America and the Caribbean (T2D: 24.4%; CVD: 11.3%) and sub-Saharan Africa (T2D: 21.5%; CVD: 10.5%). From 1990 to 2020, the largest proportional increases in SSB-attributable incident T2D and CVD cases were in sub-Saharan Africa (+8.8% and +4.4%, respectively). Our study highlights the countries and subpopulations most affected by cardiometabolic disease associated with SSB consumption, assisting in shaping effective policies and interventions to reduce these burdens globally.</p

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

Validation of the Arabic Version of the Long-Term Conditions Questionnaire (LTCQ):A Study of Factor and Rasch Analyses

Abstract: Background: Patient-reported outcome measures (PROMs) are essential for capturing the lived experiences of individuals managing chronic diseases. However, few PROMs have been culturally adapted and validated for Arabic-speaking populations. Aim This study aimed to translate, culturally adapt, and validate the Long-Term Conditions Questionnaire (LTCQ) for use among Arabic-speaking adults living with chronic diseases in Jordan. Methods Following forward-backward translation and ex-pert review, a cross-sectional survey of 1,057 adults with chronic illnesses was con-ducted. Psychometric evaluation involved exploratory and confirmatory factor analyses (EFA, CFA) and Rasch modeling. While the original LTCQ assumed a unidimensional structure, EFA and CFA supported a two-factor solution: Empowerment and Functional Wellbeing, and Health-Related Psychosocial Distress. Results Rasch analysis confirmed ordered thresholds, good item targeting, and no differential item functioning (DIF) by gender. Removal of one poorly performing item resulted in a refined 19-item scale with strong reliability and validity. Conclusion The Arabic LTCQ demonstrated robust psychometric properties and cultural relevance, supporting its use in clinical care, research, and policy initiatives. Future work should examine longitudinal responsiveness and further validate the tool across diverse Arabic-speaking populations