The 2025 European Cystic Fibrosis Society position statement on physical activity assessment in cystic fibrosis

Background: Recent advances in the measurement of physical activity have significantly enhanced the analyses and interpretation in relation to health and well-being. Thus, we sought to revise and expand the 2015 position statement on the measurement of physical activity and provide guidance to clinicians and researchers for measuring physical activity in cystic fibrosis (CF) clinical practice and research. Methods: This study was registered with the International Prospective Register of Systematic Review (PROSPERO) database (CRD42022292165). Three databases (Medline, Embase and Cumulative Index to Nursing and Allied Health Literature) were searched for studies investigating the measurement of physical activity and sedentary time in people with CF irrespective of age or duration. The Quality Assessment for Diverse Studies was used to assess methodological concern. A mixed-methods framework synthesis was used to extract, map, chart, categorise and aggregate study findings. Results: In total, 7439 potentially relevant publications were identified. Following screening of titles and abstracts, 422 full texts were retrieved and assessed for eligibility, with 90 studies included. There was considerable variation in the methods of assessment, data processing and analytical interpretation of data. Conclusion: It is recommended that device-based physical activity metrics are presented as time spent in different intensity categories (e.g., light, moderate and vigorous) and to include sedentary and sleep time. For data analysis, the data resolution should be at least 1 s (minimum 30 Hz) to enable clinical teams to obtain representative categorisation of patients’ physical activity patterns. Validated questionnaires (e.g., the Habitual Activity Estimation Scale) offer additional opportunities to assess physical activity, whilst diaries can add context but should be viewed as secondary outcome measurements

Volatile odours reflect breeding status but not social group membership in captive Damaraland mole-rats

In mammals, olfaction plays a key role in social behaviour, for example, in identifying mating opportunities and potential rivals. However, we still have a limited understanding of how social information is encoded in animal odours, including the social determinants of chemical similarity and diversity. Here, we used gas chromatography to analyse the chemical composition of swabs taken from the facial and anogenital regions of Damaraland mole-rats, Fukomys damarensis, a highly social subterranean mammal that relies almost exclusively on olfactory and tactile social cues. We found no sign of individual identity across the two body areas sampled; samples from the facial region and samples of the anogenital region from the same individual were not similar to each other, suggesting that these regions carry different information. However, chemical profiles varied significantly by sex and breeding status; female breeders differed from nonbreeders in their anogenital profiles and had higher chemical diversity in their facial profiles compared with both males and nonbreeders. Interestingly, we found no signals of social group identity. Instead, individual identity may be conveyed through signature mixes that are learned through frequent contact, rather than through specific odours associated with genetic kinship or social group membership. Our results highlight the complexity of chemical communication systems in social species and suggest that signals of group level identity are not necessary for behavioural responses based on group membership

A new validated Lymphoedema-specific Patient Reported Outcome Measure (LYMPROM) for adults with Lymphoedema

Background: A new lymphoedema-specific Patient Reported Outcome Measure (LYMPROM©) was developed to help patients easily report the impact of their lymphoedema and enable lymphoedema therapists to understand what matters most to patients. Aims: This paper describes the validation of LYMPROM© for adults with lymphoedema. Methods: A multi-phased iterative review was undertaken to investigate the reliability and validity of LYMPROM©. Face and content validity were reviewed by surveying patient representatives and healthcare professionals, along with the validity of LYMPROM© Cymraeg, a Welsh translation. Following COSMIN guidelines, validation study phases used anonymised routinely collected data to examine internal consistency, structural validity, construct validity (compared with the EQ5D-5L), measurement error, test-retest reliability and responsiveness. Results: LYMPROM© demonstrated validity (content and construct) and reliability (test-retest, internal consistency). All items were regarded as relevant, comprehensive and clear, with item content validity index (CVI) between 0.83 to 1.00, and average overall assessment of 0.94. Robust development of LYMPROM© Cymraeg ensured appropriate translation into Welsh. LYMPROM© item scores, with means and medians generally in the lower half of the scale, were positively correlated, as were three (Physical health, Social health and Emotional health) domain scores (domain correlations: 0.595 to 0.812). LYMPROM© total and domain scores showed moderate negative correlations (-0.577 to -0.435) with EQ5D-5L measures. LYMPROM© total and domain scores showed good test-retest (within two weeks) properties, with little or no change in mean or median scores, and strong positive correlations between test and retest scores (Total: 0.919; Physical health domain: 0.922; Social health domain: 0.889; Emotional health domain: 0.820). LYMPROM© showed good responsiveness, with strong, positive correlations between total and domain initial and repeat (between four weeks and seven months later) scores, with a slight reduction in scores (-3.8 to -2.0 units) and some indication of relationships between reduction and time interval (Total: p = 0.025; Physical health domain: 0.034; Social health domain: 0.181; Emotional health domain: 0.009). Conclusion: Evidence shows that LYMPROM© offers a reliable and valid tool for use in clinical practice. Scores on three domains allow a more granular assessment of the patient’s view of their condition; these scores and the total LYMPROM© score exhibit moderate correlations with more generic EQ5D-5L measures. Further research will explore relationships between patient-level characteristics and LYMPROM© responses, and extend initial work on its cross-cultural validity

Understanding the Drivers of Industry 4.0 Technologies to Enhance Supply Chain Sustainability: Insights from the Agri-Food Industry

The sustainability of agri-food supply chains (AFSCs) is severely threatened by regional and global events (e.g., conficts, natural and human-made disasters, climate crises). In response, the AFSC industry is seeking digital solutions using Industry 4.0 (I4.0) technologies to enhance resilience and efciency. However, why I4.0 adoption remains stubbornly low in the agri-food industry remains poorly understood. To address this gap, this study draws on middle-range theory (MRT) and uses thematic analysis, the fuzzy analytic hierarchy process, total interpretive structural modelling, and fuzzy cross-impact matrix multiplication applied to classifcation to produce insights from nine case studies in China that have invested in I4.0 technologies to improve their AFSC sustainability. New drivers of I4.0 unique to the agri-food industry are identifed, showing how I4.0 can contribute to the environmental, economic, and social dimensions of AFSC sustainability. The results have implications for AFSC researchers and practitioners with an interest in supply chain sustainability

Stability of holographic confinement with magnetic fluxes

We analyze the stability properties of a simple holographic model for a confining field theory. The gravity dual consists of an Abelian gauge field, with non-trivial magnetic flux, coupled to six- dimensional gravity with a negative cosmological constant. We construct a one-parameter family of regular solitonic solutions, where the gauge field carries flux along a compact circle that smoothly shrinks. Thefreeenergyofthesesolitonicbackgroundsiscomparedtothatofdomain-wallsolutions. This reveals a zero-temperature first-order phase transition in the dual field theory, separating confining and conformal phases. We compute the spectrum of bound states by analysing field fluctuations in the gravity background, after dimensional reduction on the circle. A tachyonic instability emerges near a turning point in the free energy. The phase transition prevents the realisation of this instability. Near the phase transition and beyond, in metastable and unstable regions, we find evidence that the lightest scalar may be interpreted as an approximate dilaton

Graphene-Based Electronic Sensors for Gas Detection

This thesis describes the development of graphene-based sensor arrays, focusing on signal enhancement through innovative surface modification techniques, whilst leveraging graphene's unique properties. Awareness of the dangers posed by toxic gases has increased the demand for advanced gas sensors, which are critical for monitoring harmful gases. Gas sensor arrays, or "electronic noses," offer advantages over single sensors, including the ability to detect multiple analytes simultaneously with greater accuracy.Since its discovery in 2004, graphene has attracted significant interest due to its exceptional mechanical, chemical, and electrical properties, which make it ideal for miniaturized, low-cost sensors with high sensitivity and selectivity. However, graphene's high sensitivity poses a challenge, as it interacts with a wide range of molecules. Managing this sensitivity and selectivity through advanced surface modification techniques is crucial for enhancing the performance of graphene-based sensors.In this thesis, various surface modification techniques were explored to enhance the selectivity and sensitivity of graphene-based sensors, specifically targeting the detection of nitrogen dioxide, ammonia, nitric oxide, methane, and carbon dioxide. These modifications aimed to improve sensor selectivity while maintaining a strong response. One notable technique involved integrating metal phthalocyanines, known for their gas sensitivity, with graphene to create a hybrid sensor. For instance, a graphene sensor functionalized with tetra-tert-butyl copper phthalocyanine was developed for real-time detection of nitrogen dioxide (NO2), achieving a linear response and a detection limit of 31 ppb, showcasing its potential as a highly selective and effective NO2 detector.Polymers of intrinsic microporosity (PIMs), although well-established in gas separation, have not been extensively explored for gas sensing. This thesis presents a PIM-modified graphene sensor array that demonstrated high selectivity and sensitivity towards NO2, with a detection limit of 0.7 ppb, indicating its suitability for highly sensitive NO2 detection.The development of the graphene sensor array began with exploring electrochemical functionalization across different pixels, allowing each graphene element to respond to the same gas with different magnitudes. This proof-of-concept array demonstrated that these distinct responses could potentially be integrated with pattern recognition software to identify unknown gases. Beyond detecting environmental gases, the graphene sensors can also be adapted for the detection of volatile organic compounds(VOCs).To test the arrays, a gas sensing system was developed to enable simultaneous, real- time resistance measurements for each graphene pixel. The iterative development of this system is reported, highlighting challenges and limitations.A proof-of-concept bioelectronic nose based on a graphene resistor has been fabricated and evaluated. Functionalized with 1,5-diaminonaphthalene and immobilized with human olfactory receptor 2AG1, it selectively detected amyl butyrate at 0.5 pM, indicating the potential of bioelectronic noses using olfactory receptors, which can recognize multiple VOCs, thus reducing the required number of sensors in an array

Novel stereo DIC characterisation of microneedle and hypodermic needle insertion

Microneedles are minimally invasive devices, designed for pain-free drug delivery. Until now, the degree of strain exerted on the skin during microneedle insertion, in comparison to gold standard hypodermic needles, has not been quantified. This paper presents experimental results from a novel digital image correlation setup to quantify maximum normal strain exerted on a skin-mimicking membrane by hollow silicon microneedles and 25-gauge stainless steel hypodermic needles through contact, deformation, rupture, and device insertion. Findings here have shown 1x5 hollow silicon microneedle arrays exert significantly lower maximum normal strain compared to 25-gauge hypodermic needles. There is an average of 75% decrease in the maximum normal strain experienced by the membrane when using microneedle devices in comparison to that of the 25-gauge hypodermic needles. This quantification of strain has been discretised to each individual needle in the microneedle device, allowing for informed design choices for future device iterations. These findings suggest the hollow microneedle devices to be a gentler alternative for transdermal applications, potentially improving patient comfort and reducing tissue trauma when compared to the gold standard, traditional 25-gauge hypodermic needle

Optimising Human Trust in Robots: A Reinforcement Learning Approach

This study explores optimising human-robot trust using reinforcement learning (RL) in simulated environments. Establishing trust in human-robot interaction (HRI) is crucial for effective collaboration, but misaligned trust levels can restrict successful task completion. Current RL approaches mainlyprioritise performance metrics without directly addressing trust management. To bridge this gap, we integrated a validated mathematical trust model into an RL framework and conducted experiments in two simulated environments: Frozen Lake and Battleship. The results showed that the RL model facilitated trust by dynamically adjusting it based on task outcomes, enhancing task performance and reducing the risks of insufficient or extreme trust. Our findings highlight the potential of RL to enhance human-robot collaboration (HRC) and trust calibration in different experimental HRI settings