Background Genetic disorders affect millions worldwide, yet fewer than 10% of patients currently receive effective treatment. While gene therapies offer significant promise, their clinical translation is hindered by technical, regulatory, and societal challenges. Low enrolment rates in clinical trials, ethical concerns surrounding inclusion criteria, and uncertainty about preventive applications all contribute to slow progress. Public perception plays a crucial role in shaping trial participation and the integration of gene therapies into healthcare systems. This study examines public attitudes in Belgium to support the responsible development and implementation of gene therapy trials. Methodology A cross-sectional online survey using convenience sampling was conducted in Belgium with adults (18+) recruited through local pharmacies. The survey included 12 items assessing self-reported knowledge of gene therapy and willingness to accept gene therapy. To evaluate willingness to accept, hypothetical vignettes were used, which varied by treatment characteristics (e.g., side effects, efficacy, limited evidence), patient age (5, 20, 65 years), and symptomatic status (symptomatic, asymptomatic with uncertain or expected future symptoms). Descriptive statistics summarised all items included in the questionnaire. Results The sample included 289 participants, of whom 67% had completed higher education, 64% had children, and 87% had heard of gene therapy before. Overall willingness was high. Attitudes were generally positive, with limited concerns about its experimental features (e.g., unknown side effects (12%), long-term effects (8%), and uncertain effectiveness (8%)). However, key barriers included fears of altered identity (39%), external pressure (38%), and skepticism about its novelty (31%). Uncertainty about symptom development consistently reduced willingness. Patients’ age played a secondary role, with younger individuals generally receiving higher support for gene therapy than older adults. Conclusion Public attitudes toward gene therapy were largely positive, guided by perceived benefits over scientific certainty. Support favored curative over preventive use, with participants balancing autonomy and medical guidance in shared decision-making.

Background This article examines contemporary debates linking care and socially situated artistic practices, proposing care as an ethical-political framework which fosters collective support, repair, interdependence, and vulnerability. Drawing on feminist care theory and interdisciplinary perspectives, it argues for integrating care into institutional cultural contexts in order to cultivate collective and relational modes of creation often overlooked by dominant aesthetic paradigms. In the context of global crises, artistic practices are positioned as tools for material, emotional, and communal care that respond to inequality, violence, and the erosion of care ethics. Methods Through the case study of the (Un) Open Archive project, the article investigates how the ethics of care can transform artistic methodologies and contribute to broader social change. Results The interdisciplinary analysis identifies care as a generative principle which sustains collective creation, mitigates institutional precarity, and nurtures new relational and affective modes of production. These practices reveal care as both a material and symbolic framework for reshaping artistic and social relationships. Conclusions Integrating the ethics of care into artistic practice reorients art aesthetically, ethically, and politically in response to systemic crises. By positioning care at the centre of creation and coexistence, art emerges as a site of collective maintenance, repair, and transformation, offering renewed pathways for community engagement and institutional resilience.

Italy has often been described as a 'laboratory of populism', however, its Eurosceptic turn is more recent. This country report, prepared as part of the EUPopLink COST Action, traces the relationship between populism and Euroscepticism in the Italian party system. It introduces the main populist and Eurosceptic actors in Italy, and considers the nexus between populism and Euroscepticism in the Italian context. It also considers mainstream responses to the rise of populist euroscepticism.

Background Trust in artificial intelligence (AI) systems is critical for ethical and effective adoption, particularly among non-expert users. This review aimed to identify factors influencing trust and practical considerations for designing explainable AI (XAI) systems. Methods We systematically reviewed the literature following PRISMA 2020 guidelines and using backward and forward citation searches. The primary search was carried out in Web of Science (WoS), with the final search completed in January 2025. Eligible studies were peer-reviewed publications examining trust in AI among non-expert users and/or design considerations for XAI. Exclusion criteria removed studies focused solely on expert users or unrelated to trust or explainability. Results 35 studies involving diverse non-expert populations were included. We used a thematic synthesis approach to identify 33 trust-related factors grouped into personal characteristics, sociocultural influences, design and interaction attributes, and system-level properties (e.g., age, emotions, digital literacy, social norms, usability, aesthetics, explanation type, accuracy, transparency, regulatory compliance). Additionally, 120 design considerations were extracted across nine domains, including type and form of explanation; user experience and interaction; trust, transparency and human oversight; robustness, safety and reliability; data, traceability and the AI lifecycle; regulation and compliance; ethics, values and social responsibility; evaluation methods and metrics; and usage context and organizational factors. Conclusions The review synthesizes emerging perspectives on AI trust and explainability and identifies six domains that warrant further research to support the responsible design and deployment of XAI systems. Limitations include heterogeneous evaluation practices and inconsistent operationalization of trust among non-expert users, which complicates comparability across studies and hinder the responsible deployment of XAI systems.

This work describes the development and validation of new Primary Reference Materials (PRMs) for trace impurities in carbon dioxide (CO 2 ), addressing a key metrological gap for carbon capture, utilisation, and storage (CCUS) applications. CO 2 streams captured from industrial sources inevitably contain impurities such as water, sulfur oxides, nitrogen oxides, hydrogen, and hydrocarbons. Accurate and traceable quantification of these species is essential to protect transport infrastructure, ensure compliance with project specifications, and enable safe long-term geological storage. International and project-specific guidelines, including ISO/TR 27913, Porthos, and Northern Lights, define stringent impurity limits, underscoring the need for reliable gas standards for calibration and validation of analytical instruments. Binary and multi-component PRMs were prepared by VSL, NPL, CMI, IPQ, and SINTEF ER using ISO 6142-1 gravimetric methods. The mixtures covered sulfur dioxide, hydrogen sulfide, nitrogen dioxide, nitrous oxide, water, dimethyl sulfide, ethanol, and non-condensable gases (N 2 , Ar, H 2 , O 2 , CH 4 , and CO) at amount fractions relevant to CCUS specifications. In parallel, dynamic preparation systems and a portable trace gas generator were validated as alternative approaches for producing low-level mixtures of reactive species such as ammonia. PRM stability was investigated over a two-year period. Sulfur dioxide, hydrogen sulfide, dimethyl sulfide, ethanol, and nitrous oxide demonstrated stability within their expanded uncertainties. In contrast, sulfur dioxide, nitrogen dioxide, and nitric oxide in multi-component mixtures exhibited significant degradation, indicating pronounced reactivity and wall effects. Dynamic dilution systems developed by VSL and NPL produced mixtures consistent with static PRMs within 1–5%, while the portable trace gas generator achieved ammonia generation in CO 2 with a relative uncertainty of approximately 2%. These results establish a robust metrological basis for impurity analysis in CO 2 . The PRMs developed within MetCCUS provide traceable calibration capabilities aligned with European CO 2 quality specifications, supporting reliable monitoring and safe operation of CCUS infrastructure.

Background Reducing reliance on pesticides is a key objective for sustainable crop production. Integrated Pest Management (IPM) promotes preventative and non-chemical approaches to manage pests, weeds, and diseases while maintaining yield alongside targeted use of pesticides where needed. However, the relationship between preventative practices, pesticide use, and profitability in UK winter wheat remains poorly quantified. Methods Data from 144 winter wheat fields were analysed, combining entries from the IPM Network (IPMnet) and Yield Enhancement Network (YEN) spanning 2016–2024. Farmers provided agronomic details, pesticide applications, and yield data. Pesticide use was expressed as Treatment Frequency Index (TFI), calculated from application rates relative to registered label doses. Linear Mixed Effects Models were used to identify factors influencing herbicide, fungicide, and insecticide TFI, yield, and margin after crop protection spend. Results Median overall TFI was 7.5 (range: 3.27–14.15), with fungicides contributing most to pesticide use. Median yield was 10.9 t/ha, and median crop protection spend was £30/ha. Three non-chemical practices correlated with reduced pesticide use: ploughing was associated with lower herbicide TFI by 1.06 units; higher varietal resistance ratings were associated with lowered fungicide TFI; and cover crops were associated with a 0.92-unit reduction in insecticide TFI. Overall TFI showed a positive association with yield, but not with profit margin, indicating that higher pesticide inputs did not translate into greater economic returns. Conclusions The findings suggest that preventative IPM actions can reduce pesticide inputs without compromising yield or profitability. While higher pesticide use was linked to slightly higher yields, economic benefits were not evident after accounting for input costs. These results provide benchmarks for pesticide use in the UK and highlight opportunities for integrating non-chemical strategies into winter wheat production. Further research should explore pest pressure data and long-term impacts of IPM adoption on farm economics and environmental outcomes.

This paper introduces a novel approach to self-calibrating online inertial human motion capture designed for dense IMU configurations. By combining model-based sensor fusion with deep learning, the proposed method eliminates the need for static pose or functional calibration, enabling automatic IMU-to-segment (I2S) orientation and position calibration during dynamic activities such as walking. The approach integrates the previously established JointTracker framework with a novel probabilistic deep learning module for I2S orientation prediction. The JointTracker estimates global IMU orientations and joint positions from synchronized IMU measurements using recursive filtering, while the calibration module extracts kinematic features, employs probabilistic sequence-to-sequence prediction with an ensemble network trained in a self-supervised manner, and applies active selection of I2S updates based on predicted uncertainties to ensure robust performance under unseen motions. The evaluation demonstrates that the proposed method achieves comparable accuracy to existing static pose or functional calibration methods performed under supervised conditions. Notably, it performs on par or surpasses previous self-calibration approaches in accuracy on simulated and real IMU data and is, to the best of our knowledge, the first method to estimate I2S orientations and positions on the fly. The training works on kinematic data from real human motions, no real IMU data needed, making it easily adaptable to different motion scenarios. Qualitative results on newly collected motion data with simulated gait deviations further validate the method’s practical applicability. This research advances inertial motion capture by offering a robust and flexible solution broadening the potential for deployment in diverse applications where dynamic calibration is essential.

The increase in livestock and agricultural production has led to the widespread use of veterinary drugs, including antibiotics, antiparasitic, nonsteroidal anti-inflammatory drugs (NSAIDs), hormones, and pesticides, to accelerate productivity and control disease. After excretion, these compounds remain unmetabolized and can contaminate the surrounding environment through uncontrolled use of manure, wastewater, and direct treatment practices. This review focuses on the multiple environmental exposure pathways through which pharmaceuticals and agrochemicals may contaminate ecosystems, particularly emphasizing the impact that this problem may have on the health of pollinators. For example, honeybees can be exposed to pharmaceutical residues through contaminated soil, water, nectar, and pollen, which often leads to acute toxicity and sublethal effects on reproduction, immune function, and behavior. The persistence of these residues in the environment exacerbates antimicrobial resistance, which poses a global threat. In addition, this study reveals different methods of extraction and detection of pharmaceutical residues from honey, encompassing advanced analytical techniques such as liquid chromatography coupled with mass spectrometry detection. This review highlights the chronic and synergistic effects of pharmaceuticals on bee health and emphasizes risk assessment strategies to mitigate the ecological impact of pharmaceuticals on livestock production.

<ns3:p>Background CRANE is a Horizon 2020 Pre-Commercial Procurement project. The aim is to develop an integrated and flexible self-management system for treating chronic patients at home in rural areas. Learning and improvements running CRANE have been part of the development process. Objective This Lessons Learned study aims to help the partners with knowledge sharing and improvements in running the early phase of the CRANE PCP process. The suggested learnings and improvements can be useful for other internet and digital-based Pre-Commercial Procurement projects. Methods A Lessons Learned workshop including follow up activities are the basis for the data presented and analyzed in this study. The workshop was conducted digitally and led by the corresponding author. Notes were taken by a dedicated member of the CRANE management team. The participants were CRANE Partners, i.e. professionals working within healthcare. Results Positive- and negative factors are identified connected to cooperation and teamwork, and to the deliverables in the start and first phase of the CRANE Pre-Commercial Procurement process. These were the basis for a list of improvements. Conclusion It is important to make the process flexible and agile in designing and running complex projects like the CRANE project. Including the process itself, the deliverables, and the organization. Several positive and negative factors have been identified during the early phase of CRANE PCP. The main improvement is that it’s important to build a common level of understanding and it’s important to make and adjust detailed plans. This includes having a good follow-up structure. It’s also important to have frequent meetings, especially in the early phase of the process, ensuring trust and a common level of understanding of expectations and roles.</ns3:p>

The reference genome of Pyrrhula murina's reference genome will substantially enhance the current monitoring of genetic diversity and population viability and will allow us to understand the effective population size trends throughout time and recent bottlenecks and population expansions. A total of 42 contiguous chromosomal pseudomolecules were assembled from the genome sequence, using ONT, HI-C and Illumina data. This chromosome-level assembly encompasses 1.2 Gb, composed of 65 contigs and 60 scaffolds, with contig and scaffold N50 values of 65 Mb and 76 Mb, respectively.