Search Results (1,401)

The integration of artificial intelligence (AI) into medicine, oncology, and radiology represents a marked shift in the diagnosis, prognostication, and management of hepatocellular carcinoma (HCC), a malignancy with high global incidence and poor prognosis. This review examines the application of AI, including machine learning (ML) and deep learning (DL), across the spectrum of HCC care. As AI advances, new convolutional neural networks (CNNs) and other models are enhancing diagnostic accuracy, reducing interpretation times, and improving the characterization of liver lesions across major imaging modalities including ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI). Beyond diagnosis, the transformative role of AI in prognostication is also improving, where AI can now noninvasively predict critical factors such as microvascular invasion, genetic mutation status, tumor recurrence, and treatment response. Furthermore, AI has shown promise in facilitating patient-specific treatment planning by stratifying patients for interventions such as transarterial chemoembolization (TACE) and stereotactic body radiation therapy (SBRT). The review also addresses the emerging fields of pathomics and the use of AI in positron emission tomography (PET), while critically evaluating the cost-effectiveness of these technologies. Despite its promise, the widespread clinical adoption of AI faces challenges, including limited generalizability, maintaining patient privacy, ethical considerations, and the need for robust prospective validation. Ultimately, this review illustrates that the future of HCC management lies in a collaborative, hybrid-intelligence model, where AI-driven insights augment clinical expertise to optimize diagnostic pathways, personalize therapy, and improve patient outcomes. Full article

Digital Twins (DTs) are virtual, patient-specific representations that integrate real-time data to model, predict, and optimize biological and clinical processes. In neonatology, DTs are gaining attention as powerful tools for managing the profound physiological complexity and variability of newborns, particularly preterm infants requiring intensive care. Emerging applications include cardiopulmonary modeling, prediction of sepsis and necrotizing enterocolitis (NEC), optimization of mechanical ventilation, individualized nutrition, and longitudinal monitoring of neuromotor development. This review synthesizes current research on neonatal digital twins, highlighting clinical use cases and ethical considerations. We discuss persistent challenges, including limited data availability, rapid developmental change, model validation, and regulatory oversight. Finally, we outline a roadmap for integrating DTs into neonatal intensive care units (NICUs) and identify future research priorities, including multi-organ integration, predictive closed-loop systems, and personalized life-course care trajectories. Full article

Three-dimensional (3D) bioprinting has rapidly emerged as a transformative technology at the interface of biomedical engineering and regenerative medicine. By enabling the spatially controlled deposition of living cells, biomaterials, and bioactive molecules, it offers an unprecedented potential to fabricate functional tissues and potentially whole organs in the future. This review explores recent advances in bioprinting materials, processes, and applications, emphasizing the integration of bioinks, printing methods, and mechanical design principles that underpin tissue functionality. Natural and synthetic biomaterials such as hydrogels (e.g., collagen, alginate), polyethylene glycol (PEG), and polyesters like PLGA are evaluated in terms of biocompatibility, printability, and degradation behavior. Key bioprinting modalities, including extrusion, inkjet, and laser-assisted bioprinting, are compared based on printing resolution, cell viability, and scalability. Structural considerations such as scaffold architecture, mechanical stability, and biomimetic design are discussed in relation to native tissue mechanics and requirements. The review also surveys emerging applications in tissue engineering (e.g., bone, cartilage, skin replacements), organ-on-a-chip systems for drug testing, and patient-specific implants, while addressing persistent challenges such as standardization of biofabrication, regulatory and ethical considerations, and manufacturing scale-up. Finally, future trends, including the integration of artificial intelligence (AI) and robotic automation, multi-material and four-dimensional (4D) bioprinting, and the maturation of personalized bioprinting strategies, are highlighted as pathways toward more autonomous and clinically relevant bioprinting systems. Collectively, these developments signify a paradigm shift in how biological constructs are designed and manufactured, bridging the gap between laboratory research and clinical translation. Full article

Xenotransplantation, particularly the use of genetically modified pigs for kidney transplantation, is gaining attention as a potential solution to the organ shortage. Pigs are ideal donors due to their physiological similarity to humans and rapid reproduction rates. Advances in gene editing technologies like CRISPR have enabled the development of genetically modified pigs that express human-compatible molecules while lacking xenogeneic antigens, such as Galα1-3Gal, which trigger strong immune responses. These modifications significantly reduce the risks of hyperacute and acute rejection, major barriers to successful xenotransplantation. Preclinical studies involving non-human primates and deceased human donors have shown promising short-term results, indicating that pig kidneys can function in human recipients. However, there are no documented cases of long-term survival, and the long-term effects of such transplants remain uncertain. Additionally, concerns about zoonotic disease transmission from pigs to humans necessitate robust pathogen detection systems to ensure safety. More research is also needed to understand immune responses to xenogeneic organs and develop effective immunosuppressive therapies. Ethical considerations surrounding the use of animal organs require ongoing societal dialog. Continued research is essential to establish xenotransplantation as a viable treatment for patients with renal failure. Full article

The forestry extractivist model has systematically transgressed and violated Mapuche territories, thereby generating tensions, crises, and socioenvironmental injustices. The following objectives were proposed: (a) Unveil the implications of forestry extractivism on bodies of water in rural Mapuche territories. (b) Investigate Mapuche knowledge, sociocultural activities, and their relationship with preservation and sustainability of water in Mapuche and non-Mapuche territories. A qualitative methodology was employed, framed within constructivist grounded theory. To collect the information, in-depth interviews and participant observation were used. The study subjects corresponded to 51 kimeltuchefes (People with knowledge, experience and ancestral wisdom). Regarding objective (a), the findings reveal that pine and eucalyptus forestry extractivism has considerably deteriorated natural (sacred) spaces and the soil. Along with this, it has caused water scarcity, which in turn has reduced medicinal plant and food production and, in general, has deteriorated the ixofil mogen (a concept similar to biodiversity). It was concluded that the forestry extractivist model threatens the existence of all forms of life that cohabit in nature (material and immaterial); it deteriorates Mapuche culture; likewise, it poses a considerable risk to the health and survival of the Mapuche population. Regarding objective (b), the findings reveal that the knowledge of az mapu, ngülam, pepilkantün, rakizuam, llellipun and kümelkawün, and the sociocultural activities, trawün and kelluwün, constitute essential contributions for the preservation and sustainability of water. These forms of knowledge and activities are founded on ethical and moral principles that underlie the normative, legal, social, and educational frameworks of the Mapuche people. It was concluded that sociocultural knowledge and activities are essential for conserving and ensuring water in a sustainable, equitable, and efficient manner for both the Mapuche and non-Mapuche populations and for all life; likewise, they safeguard and promote Mapuche culture. Indeed, these forms of knowledge and sociocultural activities must be incorporated into environmental public policies. Full article

Point-of-care electroencephalography (POC-EEG) has emerged as a practical tool for the rapid detection of non-convulsive seizures (NCS) and non-convulsive status epilepticus (NCSE) in acute neurological settings where access to conventional EEG is often delayed. This narrative review synthesizes current evidence on the clinical applications, tech-no-logical evolution, and limitations of POC-EEG systems across adult and pediatric populations. Available data suggest that POC-EEG is associated with earlier seizure identification, more timely antiseizure treatment decisions, and reduced dependence on inter-facility transfers in selected healthcare settings. Beyond seizure detection, POC-EEG has shown potential utility in the assessment of acute encephalopathy due to conditions such as stroke, traumatic brain injury, delirium, and post-cardiac arrest states. Recent advances in device portability and artificial intelligence-assisted interpretation have expanded accessibility, enabling use by non-specialist clinicians; however, reduced spatial resolution, artifact susceptibility, and variable performance in focal or low-burden epileptiform activity remain important limitations. Automated detection algorithms show high accuracy for sustained seizure burden but require cautious interpretation and further prospective validation. Ethical and health-system considerations, including equitable access, diagnostic stewardship, and data governance, are increasingly relevant as adoption grows. Overall, POC-EEG represents a promising adjunct to conventional EEG that may improve early diagnostic workflows in acute neurological care, while definitive impacts on long-term outcomes warrant further study. Full article

Engineering education is increasingly shaped by two converging developments: accelerating sustainability transitions and rapid advances in artificial intelligence (AI). However, in many application-oriented undergraduate programs, sustainability learning remains fragmented, methodologically limited, and weakly connected to authentic engineering decision-making. To address this gap, this study proposes AI-SEE (Artificial Intelligence-Integrated Sustainable Engineering Education), a pedagogical framework that integrates AI across the curriculum as both a cognitive scaffold and a resource for system-level analysis. Emphasizing human–AI collaboration, AI-SEE is designed to be feasible and scalable within application-oriented higher education contexts. The framework comprises four interrelated pillars: intelligence-driven, green-empowered, responsibility-leading, and practice-integrated. Drawing on an empirical case from transportation-related programs at Nantong University, the study employs a qualitative comparative design and conducts semi-structured interviews with 144 undergraduates at the end of their eighth semester (control group n = 70; pilot group n = 74). Interview data were analyzed using thematic analysis informed by constructivist grounded theory and the Gioia coding approach. The findings suggest that participation in AI-SEE is associated with differentiated patterns of sustainability consciousness. At the knowledge level, students reported more systematic and interdisciplinary understandings that extended beyond environmentally reductionist perspectives to include life-cycle thinking, social equity, and long-term considerations. At the attitudinal level, students described enhanced ethical reflexivity and evolving professional self-concepts, shifting from a focus on technical execution toward broader value-oriented roles. At the behavioral level, students reported more extensive knowledge-to-action translation across personal, academic, and career-related domains. Overall, AI-SEE provides a transferable pedagogical pathway for integrating AI into engineering education to support the development of sustainability consciousness in higher education. Full article

Background: Early excision and autologous split-thickness skin grafting are the cornerstone of surgical management in severe burn injuries. In patients with extremely extensive deep burns, the lack of available donor sites represents a major life-threatening limitation. In the exceptional situation of monozygotic twins, skin isografting offers a unique solution by providing immunologically compatible skin without the risk of rejection. Case report: We report the case of a 33-year-old man who sustained flame burns involving 95% of his total body surface area, resulting in an extremely poor initial prognosis (ABSI 14, UBS 245). After early resuscitation and staged surgical excisions, the absence of sufficient autologous donor sites precluded definitive coverage using conventional techniques. On day 3, the existence of a monozygotic twin brother was identified. HLA genotyping confirmed complete identity, and skin donation was authorized by an independent ethics committee. Methods: Definitive wound coverage was achieved using staged split-thickness skin isografts harvested from the donor twin. Ultra-thin grafts (<0.2 mm) were obtained in three procedures (days 7, 11, and 45), primarily from the scalp, thighs, and back, and applied following sequential excisions. Results: All grafts survived without immunological rejection. Donor-site morbidity was minimal, with rapid healing and only mild residual hypopigmentation. The patient was discharged to rehabilitation on day 145. At 5-year follow-up, wounds were fully healed, functional outcome was satisfactory, and quality of life was good, with return to work and full independence. Conclusions: Skin isografting from a monozygotic twin is a rare but effective salvage strategy for patients with massive deep burns when autologous donor sites are insufficient, provided that ethical, legal, and donor safety considerations are rigorously addressed. Full article

The purpose of this article is to present a systematic reflection on my experience teaching international English as a Second Language (ESL) students about Indigenous rights and reconciliation in a year-long university ESL course in Canada during the COVID-19 pandemic. Teaching materials and activities originally aimed to engage students in a pre-political form of intercultural citizenship engagement with the historical struggles and contemporary realities of Indigenous communities in Canada. Over a six-week period, I engaged in a journaling process to (1) explore the opportunities and challenges of teaching this topic in an online course environment and (2) reflect on my attempts to support and challenge students to critically examine their views and assumptions about cultural diversity in Canada and within their own cultural contexts. A qualitative analysis of the reflective notes revealed that students’ engagement with the course activities designed for this theme was limited. While students completed all required tasks, their discussions and artifacts suggest that engaging with reconciliation from a distance constitutes a complex demand for their intercultural learning. This complexity was reflected in students’ reliance on surface-level engagement rather than sustained critical or dialogic exploration. These findings raise questions about the pedagogical framing of the activities, the temporal and experiential distance of the learning context, and the role these factors may have played in constraining students’ ability to meaningfully engage with reconciliation as a lived and ethically charged process. Drawing on scholarship addressing the ethical challenges of the teacher role and positionality in teaching sensitive topics within intercultural citizenship education (ICE), this article concludes with a reflexive discussion of instructional intentions, ethical tensions, and design considerations that may inform future intercultural citizenship pedagogy in similarly constrained teaching and learning contexts. Full article

Background: Managing end-of-life decisions in canine chronic kidney disease (CKD) remains one of the most significant challenges in veterinary nephrology, requiring a delicate balance between clinical data and ethical considerations. Objective: This study introduces a novel decision-making algorithm designed to guide clinicians and owners through the complexities of end-of-life care, focusing on the assessment of Quality of Life (QoL) and disease progression. Methods: The tool integrates IRIS staging with a multi-parameter QoL checklist, categorizing patients into three distinct clinical pathways: Tier A (Active Palliative Care), Tier B (Intensive Monitoring/Ambiguous Zone), and Tier C (Compassionate Euthanasia). Results and Discussion: The algorithm defines Tier A as a proactive palliative pathway grounded in systematic clinical evaluation and continuous QoL assessment, aimed at preserving patient comfort and dignity. Across all tiers, QoL functions as a dynamic and central parameter, guiding transitions between clinical pathways in conjunction with objective indicators of disease progression. Tier C delineates the threshold of therapeutic futility, where declining QoL and biological resilience converge, and euthanasia is framed as an ethically appropriate option to prevent refractory suffering. Conclusions: By providing methodological transparency and clear clinical thresholds, this tool facilitates communication between veterinarians and owners. It ensures that palliation is approached with high-standard medical rigor while safeguarding the animal’s dignity when biological resilience is exhausted. Full article

Scholars in family therapy are increasingly calling for family-centered interventions for trauma-affected refugees, as many trauma-informed therapies favor individual models of treatment. Research contributes to the study and implementation of family-centered care models. However, for methodological reasons, research on family therapy with displaced populations is limited. In response to scholars’ call, this paper argues for the use of documentary film as qualitative research data in refugee family therapy research. Documentary films have historically been used in the social sciences to examine people’s lived experiences and to address data gaps in hard-to-reach populations. This paper outlines key methodological considerations inherent in research with refugee populations, including challenges related to recruitment and retention, language and cultural barriers, insecure and unstable living conditions affecting participants, research design constraints, and ethical complexities. It then discusses how the use of documentary film can help mitigate these challenges through careful epistemological positioning, research design, data selection and analysis strategies, and attention to ethical and research trustworthiness considerations. By doing so, the paper contributes to the development of qualitative research skills necessary for studying refugee family well-being and supporting the growth of family-centered therapeutic approaches. Full article

This study advances understanding of public trust in artificial intelligence (AI) by distinguishing between overall trust in AI as a system and trust in specific AI components, and by disentangling the roles of perceived capacity, risk, and personhood. Drawing on nationally representative survey data from 1099 U.S. adults collected in 2023 (AIMS dataset), the study estimates multiple regression models to examine how these evaluations shape trust across technical, organizational, and institutional dimensions. The results show that perceived cognitive capacity is the strongest positive predictor of both overall and component-level trust, while emotional and autonomous capacity primarily enhances trust in specific system components. Perceived social risk consistently undermines trust across all levels, whereas perceived personal risk mainly erodes trust in technical components. Importantly, support for granting AI legal or institutional status significantly increases trust, while moral consideration of AI exhibits limited direct effects, highlighting a critical distinction between institutional accountability and ethical concern. Together, these findings demonstrate that public trust in AI is not a unitary attitude but reflects multidimensional judgments about capability, risk, and governance. The study underscores the importance of institutional accountability and risk mitigation—alongside transparent communication about AI capabilities—for fostering sustainable public trust in AI. Full article

Ventricular arrhythmias are among the most life-threatening cardiac rhythm disturbances. Owing to their complex pathophysiology and high mortality risk, they remain a major focus of research aimed at elucidating underlying mechanisms and improving prevention and therapeutic strategies. In this context, animal models—particularly large-animal models—are of pivotal importance because they more closely recapitulate human cardiac anatomy and electrophysiology. The most commonly used species include dogs, cats, pigs, sheep and goats. Dogs have historically played a prominent role in ventricular arrhythmia research; however, their use is increasingly constrained by legal regulations and ethical–societal considerations. Sheep and goats, although employed less frequently, have also contributed meaningfully to advances in the field. Among large-animal models, swine are regarded as especially promising, largely due to the similarity between porcine and human hearts and the feasibility of reliably inducing ventricular arrhythmias, particularly under conditions of acute ischemia associated with coronary artery occlusion. Large-animal models are also indispensable for the preclinical evaluation of novel drugs, therapeutic approaches, and medical devices prior to translation into human studies. In this article, we review selected investigations employing large-animal models of ventricular arrhythmias, with particular emphasis on the materials and methods reported in the cited literature. Full article

Telemedicine has the potential to substantially improve the care of children and adolescents with chronic respiratory diseases, including asthma, cystic fibrosis, bronchiectasis, and chronic respiratory failure. Digital health interventions—such as remote monitoring, virtual consultations, adherence-support tools, and educational platforms—can enhance disease control, continuity of care, and access to specialized services. Despite these opportunities, the implementation of telemedicine in pediatric respiratory care remains fragmented and uneven across healthcare systems. A central barrier to progress is the marked heterogeneity of outcome measures used to evaluate telemedicine interventions. Inconsistent definitions, variable endpoints, and limited follow-up reduce comparability across studies, hinder evidence synthesis, and impede translation into clinical guidelines, reimbursement models, and policy decisions. Consequently, telemedicine is often confined to isolated pilot projects rather than embedded within standard care pathways. This narrative review issues a Call to Action for the coordinated implementation and harmonization of telemedicine in pediatric chronic respiratory diseases. We advocate for the urgent development and adoption of a Core Outcome Set (COS) to standardize outcome measurement across clinical trials and real-world evaluations. In addition, we highlight the importance of integrating implementation science, economic evaluation, ethical oversight, and equity considerations into telemedicine research and deployment. Addressing regulatory fragmentation, ensuring interoperability, and aligning accreditation with reimbursement and Health Technology Assessment requirements are essential for sustainable scale-up. Finally, we emphasize the need for international collaboration among clinicians, researchers, policymakers, payers, technology developers, and patient advocacy groups to accelerate learning and promote equitable, evidence-based digital care models. Through coordinated action, telemedicine can evolve from a promising innovation into a reliable and accessible standard of care for children with chronic respiratory diseases. Full article

Obstetric critical care encompasses the management of pregnant and postpartum women with life-threatening conditions, requiring integration of intensive care principles with pregnancy-specific physiological, ethical, and organizational considerations. Although pregnancy is a physiological state, profound maternal adaptations may mask early signs of clinical deterioration, allowing rapid progression to a critical illness condition. This review provides a comprehensive overview of the foundations of obstetric intensive care, addressing maternal–fetal physiology, recognition of severity, organ support strategies, and contemporary models of care. Key aspects discussed include cardiovascular, respiratory, renal, and hematological adaptations of pregnancy; principles of airway management and mechanical ventilation; hemodynamic support; transfusion strategies guided by viscoelastic testing; renal replacement therapy; extracorporeal support, including extracorporeal membrane oxygenation and cardiopulmonary bypass; and the safe use of diagnostic imaging involving ionizing radiation. The role of point-of-care ultrasonography, structured early warning systems, and advanced monitoring in early detection and management of clinical deterioration is emphasized. Special attention is given to maternal–fetal interactions, fetal monitoring in the intensive care unit (ICU), and complex decision-making regarding timing and mode of delivery. The review also highlights the importance of multidisciplinary and multiprofessional collaboration, ethical challenges inherent to dual-patient care, and emerging strategies to expand access to specialized care, including tele–ICU models and artificial intelligence–assisted surveillance. Across all scenarios, maternal stabilization remains the primary determinant of fetal outcome. A structured approach grounded in maternal–fetal physiology and ethical principles is essential to reduce preventable maternal and perinatal morbidity and mortality in high-complexity settings. Full article