National University of Ireland

Abstract Background Randomised controlled trials (RCTs) are the gold standard for evaluating clinical interventions. However, in practice, many RCTs face challenges achieving consistent delivery across sites, risking under-recruitment, protocol deviations, and reduced validity. Strategies to support effective implementation are therefore essential for optimising intervention uptake and producing reliable evidence in busy healthcare environments. As a pragmatic cluster RCT involving emergency surgical teams as participants, CLARITY presents an opportunity to assess these strategies. Aim We aimed to identify and characterise practical strategies for improving site engagement with CLARITY (ISRCTN: 16757238) to generate a transferable framework for implementing multicentre RCTs in complex clinical settings. Methods A structured virtual World Café was conducted with CLARITY site coordinators, principal and associate investigators, and regional leads to explore experiences of trial delivery (n = 11). Breakout discussions were recorded and analysed using Braun and Clarke’s reflexive thematic analysis. Coding was guided deductively by the Consolidated Framework for Implementation Research and supplemented by inductive analysis to capture emergent, site-specific strategies. Results Discussions generated a framework emphasising embedding socially-mediated, low cognitive-load strategies into clinical routines. Role-specific tailoring strategies, distributed leadership, and informal communication channels sustained engagement, while ‘local champions’ anchored delivery. Interdepartmental collaboration was strengthened by staffing continuity, confidence in intervention value, and flexibility to context. Recruitment and data processes benefitted from diverse team structures, workflow alignment, and accessible support mechanisms. Conclusions This co-produced framework demonstrates that successful multicentre RCTs require deliberate and context-sensitive engagement strategies. These insights provide transferable guidance for enhancing fidelity, scalability, and engagement across diverse trial settings.

Microwave vacuum dehydration (MVD) has emerged as a preferred alternative to conventional methods such as hot air drying, offering faster dehydration rates while better preserving product quality. Despite these advantages, challenges remain in implementing effective real-time monitoring systems and accurate dehydration prediction methods during the MVD process. This study investigated the feasibility of using terahertz time-domain spectroscopy (THz-TDS) to continuously monitor the drying kinetics of beef, beetroot, and banana slices during MVD without interrupting the dehydration process. Polytetrafluoroethylene (PTFE) was demonstrated as the most suitable airhose material among polyethene (PE), PTFE, and quartz with the highest transmittance of 0.824. Using the deep learning model of transformer-based neural network (TbNN) introduces the self-attention mechanisms to extract features at characteristic frequencies. It successfully correlated THz-TDS transmittance data with actual moisture loss of samples with a prediction accuracy of 0.96, which shows excellent generalisation capability of this TbNN model on such a small dataset size. Besides, the calibration strategy successfully improves the accuracy from 0.94 to 0.96, with a regression coefficient of R = 0.98328. The integration of these sensing and analytical techniques offers a valuable framework for improving industrial processing control while broadening the applications of THz-TDS technology across agricultural and food production sectors. • THz-TDS enables continuous, non-invasive monitoring of MVD drying kinetics. • TbNN achieve 0.96 prediction accuracy for moisture loss. • The calibration strategy improves model accuracy from 0.94 to 0.96 • TbNN shows excellent generalisation capability despite a limited dataset size. • Integration of THz-TDS and AI offers new potential for food processing control.

Over half of the global population resides in urban areas and a vast majority of adults worldwide own smartphones, which increasingly become pervasive sensing and intervention platforms, positioning human–computer interaction at the center of everyday behavior change (Harari & Gosling, 2023; Pawar, 2025; Ritchie et al., 2025). Building on this opportunity (An et al., 2023; Gao et al., 2024; Wang et al., 2023), we propose a scoping review that maps how digital health via smartphone (i.e., mobile health) uses artificial intelligence (AI) systems to assess and promote physical activity (PA) in urban areas (see Figure 1). The review will pay explicit attention to psychosocial theory integration, inclusivity and ethical considerations as well as sustainability aspects of AI systems. We will synthesize literature that spans mobile sensing, machine learning assessment, and AI-enabled interventions, while emphasizing design considerations for responsible, human-centered real-world deployment. The aims are to (1) chart the landscape of AI-enabled systems on smartphones as mobile health assessment (e.g., passive sensing, computer vision, natural language processing) and intervention (e.g., just-in-time adaptive interventions, on-device/in-cloud causal reasoning); (2) identify how psychosocial theory (e.g., Integrated Behavior-Change Model, Social-Cognitive Theory, Behavior Change Techniques) is operationalized in algorithms, interfaces, and user journeys; (3) reflect on surface equity, ethical considerations, accessibility practices (e.g., language, ability, context constraints), and existing gaps; and (4) articulate sustainability levers (e.g., energy-aware modelling, on-device vs. in-cloud computing). Following the PRISMA-ScR framework, we will implement a transparent, reproducible protocol with the following eligibility choices (Peters et al., 2022; Tricco et al., 2018): (a) Population: adults (18+), Concept: smartphone-based AI systems for PA - assessment and intervention - plus system development processes - psychosocial theory, inclusivity, ethics, and sustainability -, Context: urban areas globally; (b) Source databases spanning health and technology research (e.g., PubMed, PsycINFO, SportDiscus, Web of Science, Scopus, IEEE Xplore, ACM Digital Library) plus targeted citation searching on seed references (Hirt et al., 2024); (c) Timeframe includes studies from the first AI deployed on smartphones onward (i.e., Siri in 2011; Bosch, 2018) in English and German; (d) Data charting extracts methodological variables (e.g., design, sample, context) and outcome domains aligned with our conceptual framework: Technology (i.e., AI-type; on-device vs. cloud; sensing modalities), PA outcomes (e.g., exercise, daily activity, sedentary behavior disruption, active transport), psychosocial theory factors (e.g., intention, habit), inclusivity and ethics (e.g., accessibility, subgroup tailoring), sustainability (e.g., energy/climate considerations, nature-linked activity design), and system idea/development process (e.g., assessment or intervention, research vs. business, co-creation). Analysis will be descriptive (e.g., frequencies, evidence maps) with a conceptual synthesis of AI system designs and disseminations as mobile health via smartphones in urban areas. This review thus covers mobile health in applied contexts (i.e., PA promotion and behavior maintenance through AI via smartphones as everyday technology) and provides a rigorous map of current mobile health research, populations which are targeted, and conditions under which mobile health is implemented. A forward-looking agenda for informed, inclusive, ethical, and sustainable human–computer interaction in mobile health research and practice for the AI era concludes the review.

This special issue marking the University of Bath's 60th anniversary offers an opportunity to reflect on nearly a decade of research into the evolution of gene regulatory networks (GRNs) from members of the lab and elsewhere. Our goal is to understand how GRNs rewire and how new transcription factor (TF) functions evolve. Using an experimental evolution model system with the soil bacterium Pseudomonas fluorescens, we have been able to observe TF rewiring in real time, providing unique insights into the principles of GRN evolution. In this perspective, we highlight three central discoveries from this system: a hierarchical pattern of TF rewiring, in which some regulators act as preferred "first responders"; the critical influence of expression level and mutational accessibility on whether a TF can be recruited for novel function; and the role of crosstalk (non-cognate binding) as the raw material for adaptive innovation. Together, these findings reveal why evolutionary pathways are often constrained and thus strikingly repeatable. By identifying what makes a TF evolvable, we are beginning to predict, and potentially direct, evolutionary outcomes. Finally, we consider open questions and emerging technologies that have the potential to transform our understanding of GRN rewiring and its relationship with evolvability.

Intravascular imaging (IVI) was introduced 35 years ago to assess coronary artery pathology and plaque vulnerability. However, from its first applications it became apparent that it can also be useful in percutaneous coronary intervention (PCI) planning and optimizing PCI results. In the early days of PCI, IVI was used to examine the efficacy of emerging endovascular devices and the vessel wall response to therapy, while in the drug-eluting stent (DES) era, IVI was used to guide DES implantation and assess final results post-intervention. The first studies assessing the role of IVI in guiding PCI with DES have failed to demonstrate a prognostic benefit for the use of IVI; however, more recent large-scale randomized trials have underscored its value in this setting. IVI, with its high resolution, allows optimal stent sizing, prompt identification and correction of common causes of stent failure, and it has been shown that it improves outcomes in complex procedures. This review summarizes the evidence supporting the role of IVI in PCI planning in DES era, synopsizes the studies that have highlighted the value of IVI in predicting stent failure, discusses the limitations of the first randomized trials that failed to demonstrate a prognostic benefit from its use, and presents the results of the more recent large-scale outcome studies that underscored its role in complex PCI planning.

The next-generation of wireless communication is anticipated to integrate sensing and communication using a unified yet versatile waveform, capable of providing not only reliable data communication, but also localization and sensing functionality. Given the chirp-based structure of the recently proposed orthogonal chirp division multiplexing (OCDM), it has shown robustness against frequency selectiveness for communication but also suitability for sensing because of the inherent pulse compression property of the chirps. Although OCDM-based spectral resolution algorithms have been explored, polynomial root-based multiple signal classification (MUSIC) poses the issues of high-dimensionality and correct estimation assignment, especially for highly correlated multiple targets. In this paper, a computationally efficient two-dimensional high-resolution algorithm is proposed for joint range-velocity estimation for the OCDM-based Radar-Communication (RadCom) system. The proposed frequency domain radar processing for OCDM utilizes the eigen-decomposition property of the Fresnel transform through a reduced polynomial-based root MUSIC algorithm, in conjunction with Gaussian pulses, to jointly localize synchronized targets. Polynomial dimensionality has been reduced by transforming the nonlinear polynomial into a linear eigenvalue problem. The eigen structure of the signal subspace is utilized to resolve the issue of estimation assignment for highly correlated multiple targets by minimizing the residual projection error. The numerical results for the proposed chirp-based pilot sensing demonstrate a significant improvement in sidelobes reduction over the typical 2D-FFT and 2D-MUSIC approach, for uncorrelated and highly correlated targets. Moreover, the algorithm avoids 2D exhaustive search as in conventional 2D-MUSIC, meanwhile, reducing the computational overhead of traditional OCDM radar processing.

Background:This study aimed to develop consensus on the core elements of the Community Specialist Teams for Older People (CST OP) service model.Methods:This study utilised a modified Delphi approach. World Café Focus Groups (n = 97) were facilitated to develop and refine statements which were included in a Real-Time Delphi survey.Results:Four key themes were produced from the World Café Focus Groups data: Fundamentals of service design, Access and transitions of care, Team Functions and Quality improvement. Themes produced informed the CST OP Real-Time Delphi survey, which was completed by 77 participants, representing a response rate of 78%.Conclusion:The modified Delphi approach has resulted in the refinement and agreement of a set of core CST OP statements that outline the key components of the CST OP service model which will guide future implementation and delivery of the CST OP model of care, ensuring consistency in the design and implementation of the CST OP model.

Mesozooplankton (netplankton > 250 µm) were sampled during nine cruises over one year at three stations in the Shannon estuary system, Ireland. A net with three mesh sizes was used to capture a wider range of plankton sizes than a standard single-mesh net. An innovation was the incorporation factorial analysis of celestial (seasonal) variables, spring equinox (Spr) and summer solstice (Sum), together with physicochemical and biological variables, without presuming cause or effect. Over the year, water temperature and salinity were closely positively related to each other and to the occurrence of most of the taxa. The approximate trophic impact of by major taxa was estimated from abundance and published clearance rates. Overall, the mean herbivorous/detritivorous grazing by mesozooplankton was 54 L m−3 d−1. Among the mesozooplankters and mysids, Mesopodopsis slabberi (predominantly April–November) contributed 96.3% and the appendicularian Oikopleura dioica (May–October) contributed 2.0% (nano- and picoplankton), while copepods only provided 0.98%. The ctenophore Pleurobrachia pileus (present April–October) grazed 2.0% (carnivorous grazing mysids and copepods contributed additional unquantified carnivorous grazing). These data, collected 45 years ago, provide a valuable baseline for assessing subsequent ecological changes.

This study presents the in vitro and preliminary ex vivo development of a novel microneedle-based pH sensor for continuous intrapartum fetal monitoring. The objective was to evaluate the feasibility of using microneedle sensors to monitor fetal pH during labour and to develop a proof-of-principle microneedle pH sensor that meets clinical requirements such as high sensitivity to small pH changes (0.05 units) within a relevant range (6.50-7.45), minimal tissue disruption, and a compact design suitable for transcervical placement on the fetal scalp (<40 mm diameter). Platinum microneedles were passivated with ArCare medical adhesive and coated with iridium oxide via electrodeposition. Sensitivity was tested in phosphate buffered saline (PBS) and artificial interstitial fluid (ISF), using both external Ag/AgCl and internal platinum pseudo-reference electrodes. In PBS, the sensor exhibited linear responses in increments of 0.05 pH units over the clinically relevant range (6.5-7.45), with slopes of -60.49 mV/pH (R2 = 0.946, accuracy = 97.65%) and -63.2 mV/pH (R2 = 0.910, accuracy = 93.70%) in the external and internal configurations, respectively. In ISF, a slope of -25.5 mV/pH (R2 = 0.979) was obtained. Ex vivo testing on human skin confirmed successful microneedle penetration without visible iridium oxide transfer or tissue damage, as indicated by methylene blue staining. These findings support the potential for continuous minimally invasive fetal pH monitoring during labour, representing a significant step toward more objective and specific intrapartum assessment.