Search Results (301)

Ensuring sustainable food systems is an urgent global priority as populations grow and environmental pressures mount. Technological innovations such as genetic engineering (GE) and nanotechnology (nano) have been promoted as promising pathways for achieving greater sustainability in agriculture and food production. Yet, the sustainability of these technologies is not defined by technical performance alone; it hinges on how they are perceived by key stakeholders and how well they align with broader societal values. This study addresses the critical question of how expert stakeholders evaluate the sustainability of GE and nano-based food and agriculture (agrifood) products. Using a multi-method online platform, we engaged 42 experts across academia, government, industry, and NGOs in the United States to assess six real-world case studies—three using GE and three using nano—across ten different dimensions of sustainability. We show that nano-based products were consistently rated more favorably than their GE counterparts in terms of environmental, economic, and social sustainability, as well as across ethical and societal dimensions. Like prior studies, our results reveal that stakeholders see meaningful distinctions between nanotechnology and biotechnology, likely due to underlying value-based concerns about animal welfare, perceived naturalness, or corporate control of agrifood systems. The fruit coating and flu vaccine—both nano-enabled—received the most positive ratings, while GE mustard greens and salmon were the most polarizing. These results underscore the importance of incorporating stakeholder perspectives in technology assessment and innovation governance. These results also suggest that responsible innovation efforts in agrifood systems should prioritize communication, addressing meaningful societal needs, and the contextual understanding of societal values to build trust and legitimacy. Full article

Marine biomass represents a valuable yet underexploited resource for the development of high-value biomaterials. Recent advances have highlighted the significant potential of marine-derived polysaccharides, proteins, and peptides in biomedical applications, most notably in drug delivery and wound healing. This review provides a comprehensive synthesis of current research on the extraction, processing and pharmaceutical valorization of these biopolymers, with a focus on their structural and functional properties that allow these materials to be engineered into nanocarriers, hydrogels, scaffolds, and smart composites. Key fabrication strategies such as ionic gelation, desolvation, and 3D bioprinting are critically examined for their role in drug encapsulation, release modulation, and scaffold design for regenerative therapies. The review also covers preclinical validation, scale-up challenges, and relevant regulatory frameworks, offering a practical roadmap from sustainable sourcing to clinical application. Special attention is given to emerging technologies, including stimuli-responsive biomaterials and biosensor-integrated wound dressings, as well as to the ethical and environmental implications of marine biopolymer sourcing. By integrating materials science, pharmaceutical technology and regulatory insight, this review aims to provide a multidisciplinary perspective for researchers and industrial stakeholders seeking sustainable and multifunctional pharmaceutical platforms for precision medicine and regenerative therapeutics. Full article

Plant-derived vesicle-like nanoparticles (PDVLNs) are bioactive nanovesicles secreted by plant cells, emerging as a novel therapeutic tool for tissue repair and regeneration due to their low immunogenicity, intrinsic bioactivity, and potential as drug delivery carriers. This review examines PDVLNs’ biogenesis mechanisms, isolation techniques, and compositional diversity, emphasizing their roles in promoting essential regenerative processes—cell proliferation, differentiation, migration, immune modulation, and angiogenesis. We explore their therapeutic applications across multiple tissue types, including skin, bone, neural, liver, gastrointestinal, cardiovascular, and dental tissues, using both natural and engineered PDVLNs in various disease models. Compared to mammalian exosomes, PDVLNs offer advantages such as reduced immune rejection and ethical concerns, enhancing their sustainability and appeal for regenerative medicine. However, challenges in clinical translation, including scalability, standardization, and safety remain. This paper consolidates current knowledge on PDVLNs, highlighting their versatility and providing insights into engineering strategies to optimize efficacy, ultimately outlining future research directions to advance their clinical potential. Plant vesicle-like nanoparticles (PDVLNs) may become a new avenue for the treatment of tissue injury, promoting tissue repair and regeneration through their intrinsic bioactivity or as drug delivery carriers. In addition, PDVLNs can be engineered and modified to achieve better results. Full article

Background/Objectives: Artificial intelligence (AI) holds great potential to reshape the academic paradigm. They can process large volumes of information, assist in academic literature reviews, and augment the overall quality of scientific discourse. This narrative review examines the application of various AI tools in surgical research, its present capabilities, future directions, and potential challenges. Methods: A search was performed by two independent authors for relevant studies on PubMed, Cochrane Library, Web of Science, and EMBASE databases from January 1901 until March 2025. Studies were included if they were written in English and discussed the use of AI tools in surgical research. They were excluded if they were not in English and discussed the use of AI tools in medical research. Results: Forty-two articles were included in this review. The findings underscore a range of AI tools such as writing enhancers, LLMs, search engine optimizers, image interpreters and generators, content organization and search systems, and audio analysis tools, along with their influence on medical research. Despite the multitude of benefits presented by AI tools, risks such as data security, inherent biases, accuracy, and ethical dilemmas are of concern and warrant attention. Conclusions: AI could offer significant contributions to medical research in the form of superior data analysis, predictive abilities, personalized treatment strategies, enhanced diagnostic accuracy, amplified research, educational, and publication processes. However, to unlock the full potential of AI in surgical research, we must institute robust frameworks and ethical guidelines. Full article

Background/Objectives: This paper introduces a pedagogically grounded framework for transforming canonical literary texts in primary education through generative AI. Guided by multiliteracies theory, Vygotskian pedagogy, and epistemic justice, the system aims to enhance interpretive literacy, developmental alignment, and cultural responsiveness among learners aged 7–12. Methods: The proposed system enables educators to perform age-specific text simplification, visual re-narration, lexical reinvention, and multilingual augmentation through a suite of modular tools. Central to the design is the Ethical–Pedagogical Validation Layer (EPVL), a GPT-powered auditing module that evaluates AI-generated content across four normative dimensions: developmental appropriateness, cultural sensitivity, semantic fidelity, and ethical transparency. Results: The framework was fully implemented and piloted with primary educators (N = 8). The pilot demonstrated high usability, curricular alignment, and perceived value for classroom application. Unlike commercial Large Language Models (LLMs), the system requires no prompt engineering and supports editable, policy-aligned controls for normative localization. Conclusions: By embedding ethical evaluation within the generative loop, the framework fosters calibrated trust in human–AI collaboration and mitigates cultural stereotyping and ideological distortion. It advances a scalable, inclusive model for educator-centered AI integration, offering a new pathway for explainable and developmentally appropriate AI use in literary education. Full article

Although consumption is a key engine of economic growth, it is also one of the main drivers of environmental degradation. In this context, a deeper understanding of consumers’ perceptions and behavior regarding sustainable products is essential for promoting a more sustainable future, with behavioral change being crucial to achieving it. This research study explores consumer behavior regarding sustainable egg consumption, a sector where production is frequently associated with environmental and ethical concerns such as animal welfare and intensive resource use. Based on a sample of 197 valid responses from Portuguese egg consumers collected through an online survey distributed between 27 February and 17 March, of the year 2025, and applying the Theory of Planned Behavior (TPB) framework through a structural equation modeling (SEM) approach, this study finds that consumers’ intention to consume sustainable eggs is influenced by their attitudes and subjective norms. Furthermore, actual consumption behavior is driven by both the intention to consume sustainable eggs and perceived behavioral control. By providing an in-depth analysis of consumer behavior related to sustainable egg consumption, this study contributes to the advancement of the scientific literature on the subject. It also aims to support policymakers and other stakeholders in designing and implementing more effective strategies to promote environmentally responsible consumption practices. Full article

Presenteeism, characterized by going to work sick, has become increasingly prevalent in nursing, a profession with high social and interpersonal demands. It is associated with a deterioration of the health of nurses, a reduction in the excellence of care, and a decrease in safety for users. Burnout is related to stress and mental overload and is characterized by exhaustion and fatigue. Objective: To map the evidence on the relationship between presenteeism and burnout in nurses. Methods: A literature review was carried out using the EBSCOHost Research search engine in various databases. Eight studies were selected and analyzed. Results: The studies identify a consistent relationship between burnout and presenteeism in nurses. Emotional exhaustion, resulting from burnout, can lead nurses to go to work despite being ill, due to a sense of responsibility, ethical duty, or organizational pressures. Most studies are cross-sectional, which limits the ability to establish causal relationships and identify specific interventions to reduce burnout-related presenteeism in nursing. Conclusions: It is essential to invest in health management policies for nurses to reduce burnout and minimize the consequences of presenteeism. Full article

The demographic shift toward an aging population calls for innovative strategies to ensure independence, health, and quality of life in later years. In this context, Ambient Assisted Living (AAL) solutions, supported by Information and Communication Technologies (ICTs), offer promising advances for non-invasive and continuous support. Commonly, ICTs are evaluated only from the perspectives related to key performance indicators (KPIs); nevertheless, the design and implementation of such technologies must account for important psychological, social, and ethical dimensions. Radar-based sensing systems are emerging as an option due to their unobtrusive nature and capacity to operate without direct user interaction. This work explores how radar technologies, particularly those operating in the millimeter wave (mmWave) spectrum, can provide core key value indicators (KVIs) essential to aging societies, such as human dignity, trustworthiness, fairness, and sustainability. Through a review of key application domains, the paper illustrates the practical contributions of mmWave radar in Ambient Assisting Living (AAL) contexts, underlining how its technical attributes align with the complex needs of elderly care environments and produce value for society. This work uniquely integrates key value indicator (KVI) frameworks with mmWave radar capabilities to address unmet ethical needs in the AAL domain. It advances existing literature by proposing a value-driven design approach that directly informs technical specifications, enabling the alignment of engineering choices with socially relevant values and supporting the development of technologies for a more inclusive and ethical society. Full article

Adeno-associated virus (AAV) vectors have emerged as the leading platform for retinal gene therapy due to their favorable safety profile, low immunogenicity, and ability to mediate long-term transgene expression within the immune-privileged ocular environment. By integrating diverse strategies such as gene augmentation and gene editing, AAV-based therapies have demonstrated considerable promise in treating both inherited and acquired retinal disorders. However, their clinical translation remains limited by several key challenges, including restricted packaging capacity, suboptimal transduction efficiency, the risk of gene therapy-associated uveitis, and broader societal concerns such as disease burden and ethical oversight. This review summarizes recent advances aimed at overcoming these barriers, with a particular focus on delivery route-specific disease applicability, multi-vector systems, and capsid engineering approaches to enhance payload capacity, targeting specificity, and biosafety. By synthesizing these developments, we propose a conceptual and technical framework for a more efficient, safer, and broadly applicable AAV platform to accelerate clinical adoption in retinal gene therapy. Full article

The increasing integration of large language models (LLMs) into healthcare presents significant opportunities, but also critical risks related to patient safety, accuracy, and ethical alignment. Despite these concerns, no standardized framework exists for systematically evaluating and stress testing LLM behavior in clinical decision-making. The PIEE cycle—Planning and Preparation, Information Gathering and Prompt Generation, Execution, and Evaluation—is a structured red-teaming framework developed specifically to address artificial intelligence (AI) safety risks in healthcare decision-making. PIEE enables clinicians and informatics teams to simulate adversarial prompts, including jailbreaking, social engineering, and distractor attacks, to stress-test language models in real-world clinical scenarios. Model performance is evaluated using specific metrics such as true positive and false positive rates for detecting harmful content, hallucination rates measured through adapted TruthfulQA scoring, safety and reliability assessments, bias detection via adapted BBQ benchmarks, and ethical evaluation using structured Likert-based scoring rubrics. The framework is illustrated using examples from plastic surgery, but is adaptable across specialties, and is intended for use by all medical providers, regardless of their backgrounds or familiarity with artificial intelligence. While the framework is currently conceptual and validation is ongoing, PIEE provides a practical foundation for assessing the clinical reliability and ethical robustness of LLMs in medicine. Full article

Synthetic biology (SynBio) is an emerging interdisciplinary field that applies engineering principles to the design and construction of novel biological systems or the redesign of existing natural systems for new functions. As autotrophs with complex cellular architectures, plants possess inherent capabilities to serve as “living factories” for SynBio applications. Recent advancements in genetic engineering, genome editing, and transformation techniques are improving the precision and programmability of plant systems. Innovations, such as CRISPR systems, prime editing strategies, and in planta and nanoparticle-mediated delivery, are expanding the SynBio toolkit for plants. However, the efficient delivery of genetic constructs remains a barrier due to plant systems’ complexity. To address these limitations, SynBio is increasingly integrating iterative Design–Build–Test–Learn (DBTL) cycles, standardization, modular DNA assembly systems, and plant-optimized toolkits to enable predictable trait engineering. This review explores the technological foundations of plant SynBio, including genome editing and transformation methods, and examines their integration into engineered systems. Applications, such as biofuel production, pharmaceutical biosynthesis, and agricultural innovation, are highlighted, along with their ethical, technical, and regulatory challenges. Ultimately, SynBio could offer a transformative path toward sustainable solutions, provided it continues to align technological advances with public interest and global sustainability goals. Full article

This entry reviews the evolution from Digital Twins (DT) to Predictive Digital Twins (PDT) and Digital Triplets (DTr), culminating in Predictive Digital Ecosystems, which focus on economic and financial decision-making. It discusses historical developments, technical foundations, practical applications, ethical and regulatory challenges, and future directions. The overview integrates mature knowledge from engineering, data science, and economic domains to provide a structured reference framework for understanding and deploying Predictive Digital Ecosystems. Full article

The fast growth of artificial intelligence during recent years has resulted in its implementation across various sectors. The broad implementation of AI systems has generated substantial ethical issues because AI algorithm decisions can affect basic rights such as privacy, fairness, security and individual autonomy. With these concerns, governments, international organizations, and academic institutions have established guidelines and regulations to ensure that artificial intelligence systems are designed and implemented in a manner that upholds fundamental ethical principles. This work presents the results of a Systematic Literature Review using the PRISMA approach and aims to identify which approaches/methods are the most suitable ones for being used to integrate ethics and trustworthiness into AI tools for industrial engineering applications. Therefore, the review considered 38 pertinent scientific works published between 2019 and the end of August 2024. Full article

The emergence of generative artificial intelligence (GenAI) chatbots, such as ChatGPT, presents unique challenges and opportunities in an educational setting; however, they lack empirical evidence as teaching and learning tools. This study sought to investigate the impact of teacher-led AI-focused interventions in higher education institutions in different subject areas. Our aims were to support student engagement, explore the impact of AI tools for learning engagement and efficiency and skill development, and promote awareness of the strengths and limitations of GenAI tools in an educational context. This study was carried out with three distinct cohorts; Physiology, Initial Teacher Education, and Engineering, with year 3 and 4 undergraduate students. Each cohort received two 50 min teacher-led AI-focused interventions, including practical exercises relevant to the specific discipline. Following the interventions, students from all three cohorts received a common (optional) survey that quantitatively and qualitatively evaluated their experiences. Data from the three cohorts was pooled for analysis, with individual cohort analyses for Physiology, Initial Teacher Education, and Engineering provided. Our data indicates that teacher-led introductions to AI tools have positive effects on student engagement with peers, educators, and most notably the subject the students engage in. Students also reported very positive supportive effects with respect to learning engagement, learning efficiency, and critical thinking skills. Students found GenAI tools most useful for gathering knowledge and research purposes, while notable limitations included challenges associated with generating prompts and the accuracy of information. Students noted plagiarism as a significant ethical concern. Taken together, our data collected from diverse teaching and learning contexts support the use of teacher-led AI-focused interventions, specifically ChatGPT, in third-level education. Approaches like this are highly relevant to the university teaching of Physiology, Initial Teacher Education, and Engineering but are also more broadly applicable to third-level education in general to inform opportunities, limitations, and ethical considerations of GenAI in education. Full article

The recent birth of genetically modified canids phenotypically resembling the extinct dire wolf (Aenocyon dirus) was hailed as a landmark in synthetic biology. Using genome editing and cloning, the biotech company Colossal Biosciences created three such animals from gray wolf cells, describing the project as an effort in “functional de-extinction”. This case raises significant questions regarding animal welfare, moral justification, and regulatory governance. We used the five domains model framework to assess the welfare risks for the engineered animals, the surrogate mothers used in reproduction, and other animals potentially affected by future reintroduction or escape scenarios. Ethical implications are examined through utilitarian, deontological, virtue, relational, and environmental ethics. Our analysis suggests that the project suffers from ontological ambiguity: it is unclear whether the animals created are resurrected species, hybrids, or novel organisms. While the current welfare of the engineered animals may be manageable, their long-term well-being, particularly under rewilding scenarios, is likely to be compromised. The moral arguments for reviving long-extinct species are weak, particularly in cases where extinction was not anthropogenic. Legally, the current EU frameworks lack the clarity and scope to classify, regulate, or protect genetically engineered extinct animals. We recommend that functional de-extinction involving sentient beings be approached with caution, supported by revised welfare tools and regulatory mechanisms. Full article