Search Results (10,706)

Background/Objectives: With global population aging, long-term care (LTC) facilities play an essential role in supporting older adults. However, residents are vulnerable to dignity loss in these institutional settings. Understanding dignity from the perspectives of residents, staff, and relatives is critical for informing person-centered care and policy. This review aimed to synthesize qualitative evidence on dignity in LTC facilities across multiple stakeholders. Methods: Following the PRISMA guidelines, we systematically searched six databases (PubMed, Scopus, Web of Science, Wan Fang, VIP, and CNKI) for qualitative studies published in 2010–2023. Eligible studies explored experiences of dignity among older LTC residents, staff, or relatives. Methodological quality was appraised using the Critical Appraisal Skills Programme (CASP) checklist. Data were analysed through thematic synthesis, and findings were compared across stakeholder groups. Results: A total of 1948 records were identified, of which 27 qualitative studies met the inclusion criteria. Two themes emerged from residents’ perspectives: institutionalization and resilience in preserving dignity. From staff perspectives, three themes were identified: understaffing and workload pressures, general approaches to dignity care, and person-centered care. Relatives’ accounts highlighted two themes: uneasiness regarding indignity and ethical expectations in a caring culture. Integrating these perspectives, we propose a triangular model in which residents, staff, and relatives collaboratively sustain dignity. Conclusions: Older adults’ dignity in LTC is shaped by complex interactions among institutional conditions, caregiving practices, and family involvement. Enhancing dignity requires adequate staffing, structural support for person-centered care, and greater involvement of relatives in decision-making. The proposed triangular model offers a framework for guiding interventions, staff training, and policy reforms aimed at safeguarding dignity in LTC facilities. Full article

Introduction of immune checkpoint inhibitors and targeted agents has markedly improved outcomes and extended survival in urothelial and renal cell carcinoma. However, the substantial subset of cases are treatment-resistant. Emerging strategies aim to enhance the effectiveness of immunotherapy. One area of growing interest and promise is the microbiome. The microbiome plays a complex and dynamic role in regulating the immune system, and represents a new frontier as a promising target for modulating response to immunotherapy. This review summarizes recent advances in our understanding of the microbiome, its interactions with immunotherapy, novel avenues for microbiome modification, and potential implications for the treatment of urothelial and renal cell carcinoma. Full article

Exosomes are extracellular vesicles that play a central role in mediating intercellular communication within the tumor microenvironment (TME). Cancer-derived exosomes carry proteins, nucleic acids, and lipids that reshape the phenotype and function of surrounding stromal and immune cells, thereby promoting tumor progression, angiogenesis, metastasis, and resistance to therapy. At the same time, exosomes derived from TME components, including macrophages, dendritic cells, B cells, T cells, fibroblasts, neutrophils, and NK cells, reciprocally influence tumor growth and immune evasion. These bidirectional interactions highlight exosomes as both drivers of tumor progression and regulators of antitumor immunity. In this review, we synthesize current evidence on the diverse mechanisms by which exosomes reprogram immune and stromal cells, with a focus on their dual roles in cancer biology. We also discuss emerging therapeutic strategies to inhibit exosome biogenesis, release, and function, underscoring their translational potential as novel targets for cancer diagnosis and treatment. Full article

Growing age-related epidemiology, together with an increasing burden of cardiac co-pathology and comorbidities, has progressively subverted the clinical paradigm of Aortic Stenosis (AS) towards a multifaceted scenario. Timely surgical or transcatheter valve replacement is paramount to reduce morbidity and mortality in AS patients provided that the obstruction is hemodynamically important and responsible for the symptoms across a variety of clinical contexts. Despite its recognized role in AS assessment severity, transvalvular gradient (TVG) reflects complex interplay among anatomical, mechanical and fluid-dynamic factors, challenging the ultimate recognition of significant aortic valve obstruction. Careful phenotyping of TVG by assessing its underlying variables may enhance diagnostic work-up, risk stratification and management of AS. Emerging imaging modalities, such as three-dimensional echocardiography, automatic flow and myocardial function assessment, and advanced fluid dynamics analysis are promising for refining multifaceted TVG phenotypes. A deeper understanding of the substrate underlying TVG may add new insight into the trajectory of valve obstruction and its interaction with left ventricular function, thereby supporting the tailoring of TVG-guided clinical strategies of the evolving scenario of AS. Full article

Current autonomous vehicles require human drivers to take over control during emergencies or in environments the system cannot handle. During other periods, drivers are permitted to engage in non-driving-related tasks. It is essential to investigate how the immersion in non-driving-related tasks affects drivers’ takeover performance under different scenarios. To address this, a mixed-design simulated driving experiment was conducted with 40 participants, incorporating three non-driving-related tasks (no task, watch video, play game), three takeover request lead times (3 s, 5 s, 7 s), and two obstacle types (dynamic, static). The takeover process was divided into three phases: preparation, obstacle avoidance, and recovery. Analysis of the areas of interest showed that engaging in non-driving-related tasks substantially reduced drivers’ visual attention tothe road ahead during the preparation phase. The Generalized Estimating Equations method was employed to investigate the effects of various factors on takeover performance. Model results showed that scenarios with static obstacles and longer takeover request times led to a significant reduction in mean lane deviation but a significant increase in the standard deviation of lane deviation, suggesting improved lateral control performance. A significant interaction was observed between the watch video task and static obstacles, which corresponded to a notable decrease in the mean vehicle speed during obstacle avoidance. Performance in the recovery phase was strongly predicted by that in the obstacle avoidance phase, indicating that the stability of the avoidance maneuver is a critical determinant of the subsequent recovery. These findings offer valuable insights for managing non-driving-related tasks and setting appropriate takeover request timings in automated driving systems. Full article

The assessment of animal welfare in rehabilitation settings is a critical aspect of effective care, yet typical metrics often fail to fully capture rehabilitating animals’ emotional experiences in a non-invasive way. Anticipatory behavior has emerged as a promising animal welfare indicator, reflecting an animal’s perceived need for rewards based on available opportunities in their environment. By tracking anticipatory responses, caretakers can gain insight into an animal’s reward sensitivity and use this information to guide management interventions. This study investigated the effects of enrichment type on anticipatory behavior in fourteen, rehabilitating harbor seal pups (Phoca vitulina richardii). We provided pups with daily sessions of either structural or cognitive enrichment and recorded their behavioral responses. During scheduled feeding sessions, we identified behaviors that emerged as anticipatory, then measured the frequency and duration of anticipatory behavior prior to the feeds to assess how enrichment types influenced the seals’ reward sensitivity, and thus their welfare. While enrichment interaction did not directly modulate anticipatory behavior, we observed a trend suggesting that exposure to cognitive enrichment reduced anticipatory behavior duration compared to structural enrichment. These findings align with previous research in zoo settings, where cognitive enrichment has been linked to improved welfare through reduced anticipatory behavior, though this effect has not been explored in a wildlife rehabilitation context. This study highlights the value of anticipatory behavior as a practical welfare assessment tool in rehabilitation settings and underscores the potential for enrichment, particularly cognitive, to improve welfare in rehabilitating marine mammals. Full article

Generative artificial intelligence (AI) is reshaping creative practices, yet many systems rely on traditional interfaces, limiting intuitive and embodied engagement. This study presents a qualitative observational analysis of participant interactions with a real-time generative AI installation designed to co-create Ukiyo-e-style artwork through embodied inputs. The system dynamically interprets physical presence, object manipulation, body poses, and gestures to influence AI-generated visuals displayed on a large public screen. Drawing on systematic video analysis and detailed interaction logs across 13 sessions, the research identifies core modalities of interaction, patterns of co-creation, and user responses. Tangible objects with salient visual features such as color and pattern emerged as the primary, most intuitive input method, while bodily poses and hand gestures served as compositional modifiers. The system’s immediate feedback loop enabled rapid learning and iterative exploration and enhanced the user’s feeling of control. Users engaged in collaborative discovery, turn-taking, and shared authorship, frequently expressing a positive effect. The findings highlight how embodied interaction lowers cognitive barriers, enhances engagement, and supports meaningful human–AI collaboration. This study offers design implications for future creative AI systems, emphasizing accessibility, playful exploration, and cultural resonance, with the potential to democratize artistic expression and foster deeper public engagement with digital cultural heritage. Full article

The CITED proteins function as transcriptional modulators that are essential for vertebrate development. These proteins interact with numerous partners, notably transcription factors and co-activators. The hallmark of the CITED family is their conserved carboxy-terminal domain, which interacts strongly with the CBP/p300 co-activators. The expression of CITED genes is detected early during embryogenesis within embryonic and foetal regions critical for cardiac morphogenesis, among other developmental processes. Notably, CITED2 loss of function is strongly associated with congenital heart malformations in mice and zebrafish embryos, as well as congenital heart disease (CHD) in humans, whereas other CITED family members are not critical for cardiogenesis. Emerging evidence implicates CITED2 and CITED4 in regulating heart physiological adaptations and protective responses to pathological stress. This review provides a detailed analysis of CITED proteins and their interactors, focusing on CITED-target genes relevant for cardiogenesis and heart disease. We also highlight recent findings indicating that CITED2 and CITED4 may be instrumental for the development of novel therapeutic strategies to mitigate CHD and preserve adult cardiac function. Full article

Background: During postoperative recovery, patients and their caregivers often lack crucial information, leading to numerous repetitive inquiries that burden healthcare providers. Traditional discharge materials, including paper handouts and patient portals, are often static, overwhelming, or underutilized, leading to patient overwhelm and contributing to unnecessary ER visits and overall healthcare overutilization. Conversational chatbots offer a solution, but Natural Language Processing (NLP) systems are often inflexible and limited in understanding, while powerful Large Language Models (LLMs) are prone to generating “hallucinations”. Objective: To combine the deterministic framework of traditional NLP with the probabilistic capabilities of LLMs, we developed the AI Virtual Assistant (AIVA) Platform. This system utilizes a retrieval-augmented generation (RAG) architecture, integrating Gemini 2.0 Flash with a medically verified knowledge base via Google Vertex AI, to safely deliver dynamic, patient-facing postoperative guidance grounded in validated clinical content. Methods: The AIVA Platform was evaluated through 750 simulated patient interactions derived from 250 unique postoperative queries across 20 high-frequency recovery domains. Three blinded physician reviewers assessed formal system performance, evaluating classification metrics (accuracy, precision, recall, F1-score), relevance (SSI Index), completeness, and consistency (5-point Likert scale). Safety guardrails were tested with 120 out-of-scope queries and 30 emergency escalation scenarios. Additionally, groundedness, fluency, and readability were assessed using automated LLM metrics. Results: The system achieved 98.4% classification accuracy (precision 1.0, recall 0.98, F1-score 0.9899). Physician reviews showed high completeness (4.83/5), consistency (4.49/5), and relevance (SSI Index 2.68/3). Safety guardrails successfully identified 100% of out-of-scope and escalation scenarios. Groundedness evaluations demonstrated strong context precision (0.951), recall (0.910), and faithfulness (0.956), with 95.6% verification agreement. While fluency and semantic alignment were high (BERTScore F1 0.9013, ROUGE-1 0.8377), readability was 11th-grade level (Flesch–Kincaid 46.34). Conclusion: The simulated testing demonstrated strong technical accuracy, safety, and clinical relevance in simulated postoperative care. Its architecture effectively balances flexibility and safety, addressing key limitations of standalone NLP and LLMs. While readability remains a challenge, these findings establish a solid foundation, demonstrating readiness for clinical trials and real-world testing within surgical care pathways. Full article

Synthetic biology, an emergent interdisciplinary field integrating principles from biology, engineering, and computer science, endeavors to rationally design and construct novel biological systems or reprogram extant ones to achieve predefined functionalities. The conventional approach relies on an iterative Design-Build-Test-Learn (DBTL) cycle, a process frequently hampered by the intrinsic complexity, non-linear interactions, and vast design space inherent to biological systems. The advent of Artificial Intelligence (AI), and particularly its subfields of Machine Learning (ML) and Deep Learning (DL), is fundamentally reshaping this paradigm by offering robust computational frameworks to navigate these formidable challenges. This review elucidates the strategic integration of AI/ML/DL across the synthetic biology workflow, detailing the specific algorithms and mechanisms that enable rational design, autonomous experimentation, and pathway optimization. Their advanced applications are specifically underscored across critical facets, including de novo rational design, enhanced predictive modeling, intelligent high-throughput data analysis, and AI-driven laboratory automation. Furthermore, pivotal challenges, such as data sparsity, model interpretability, the “black box” problem, computational resource demands, and ethical considerations, have been addressed, while concurrently forecasting future trajectories for this rapidly advancing and convergent domain. The synergistic convergence of these disciplines is demonstrably accelerating biological discovery, facilitating the creation of innovative and scalable biological solutions, and fostering a more predictable and efficient paradigm for biological engineering. Full article

Dioxins are legacy and persistent environmental pollutants that pose complex and far-reaching risks to human, animal, and ecosystem health. As unintentional byproducts of industrial and combustion processes, dioxins accumulate in the environment, biomagnify through food webs, and exert toxic effects even at low concentrations. This review applies a One Health lens to synthesize current knowledge on dioxin sources, environmental fate, exposure pathways, and toxicological impacts across species. We have critically examined existing surveillance systems, regulatory frameworks, and policy responses, highlighting both achievements and persistent gaps. A fully integrated One Health approach, linking environmental, animal, and human health domains, is essential for effective monitoring, risk assessment, and mitigation. It includes cross-sectoral collaboration, harmonized biomonitoring, evidence-based policy interventions, and transparent risk communication. Emerging evidence on climate-driven dioxin remobilization and microplastic interactions further underscores the urgency of adaptive, system-based strategies. Strengthening global capacity through such integrative approaches is vital to safeguard planetary health from these enduring contaminants. Quantitative insights and illustrative examples support these conclusions. Full article

Background: Genome sequencing is transforming infectious-disease diagnostics, surveillance, and precision therapy by enabling rapid, high-resolution pathogen identification, transmission tracking, and genomic-informed antimicrobial stewardship. Methods: We review contemporary sequencing platforms (short- and long-read), targeted and metagenomic approaches, and operational workflows that connect laboratory outputs to clinical and public health decision-making. We highlight strengths and limitations of genomic AMR prediction, the role of plasmids and mobile elements in resistance and virulence, and practical steps for clinical translation, including validation, reporting standards, and integration with electronic health records. Results: Comparative and population genomics reveal virulence determinants and host–pathogen interactions that correlate with clinical outcomes, improving risk stratification for high-risk infections. Integrating sequencing with epidemiological and clinical metadata enhances surveillance, uncovers cryptic transmission pathways, and supports infection control policies. Despite these advances, clinical implementation faces technical and interpretative barriers, as well as challenges related to turnaround time, data quality, bioinformatic complexity, cost, and ethical considerations. These issues must be addressed to realize routine, point-of-care sequencing. Conclusions: Emerging solutions, including portable sequencing devices, standardized pipelines, and machine-learning models, promise faster, more actionable results and tighter integration with electronic health records. The widespread adoption of sequencing in clinical workflows has the potential to shift infectious disease management toward precision medicine, thereby improving diagnostics, treatment selection, and public health responses. Full article

Effective communication is a core competence in sustainable policing, yet training programs often fail to prepare officers for the emotional and relational complexity of real-world encounters. This study explored how police officers from Lithuania, the Czech Republic, and Romania (n = 109) evaluate their communication training and identify the interactions they find most difficult. Using a convergent mixed-methods design, the research integrated quantitative assessments of training coverage with qualitative analysis of officers’ narratives. Findings reveal consistent gaps in emotional regulation, empathy, negotiation, and de-escalation skills, especially in encounters with intoxicated or mentally distressed individuals, and in internal communication within hierarchical structures. Viewed through the lens of organizational sustainability, communication competence emerges as a key form of human capital that enhances officer well-being, reduces operational risks, and strengthens public trust. The study highlights the need to embed experiential, scenario-based learning into police curricula to align training with the emotional realities of field practice. Full article

Optineurin (OPTN) is a multifunctional adaptor protein that regulates diverse cellular processes, including inflammatory signaling, autophagy, vesicular trafficking, and immune responses. This multifaceted role of OPTN is made possible by the presence of a complex structure comprising multiple domains that interact with different proteins to exert various functions important for modulating key signaling processes. Mutations in OPTN are linked with several human pathologies including glaucoma, Paget’s disease of bone, Crohn’s disease, and neurodegenerative diseases such as amyotrophic lateral sclerosis, and dementia. Emerging evidence suggests that OPTN has a complex and context-dependent role in cancer biology as well. It is upregulated in pancreatic ductal adenocarcinoma and hepatocellular carcinoma but downregulated in lung and colorectal cancers, indicating its dual role as a potential oncogene or tumor suppressor depending on the cellular environment. Additionally, OPTN plays a critical role in preventing immune evasion in colorectal cancer by maintaining interferon-gamma receptor 1 (IFNGR1) expression and supporting dendritic cell-mediated T-cell priming, thereby enhancing antitumor immune responses. Despite its significance in oncogenic pathways and immune regulation, the therapeutic potential of targeting OPTN in cancer remains largely unexplored. This review aims to provide a comprehensive understanding of OPTN’s pleiotropic functions, highlighting its role in autophagy, inflammation, immune surveillance, and cancer progression. By elucidating its diverse regulatory mechanisms, we seek to encourage further research into the therapeutic implications of OPTN in cancer treatment and immunotherapy. Full article

Electoral abstention has emerged as a critical challenge to democratic legitimacy, with rising rates observed globally. For example, in Portugal, the turnout declined from 91.5% in 1975 to 51.4% in 2022. This systematic review synthesizes multidisciplinary literature to identify key determinants of voter nonparticipation and their interactions, aiming to inform adaptive strategies to enhance civic engagement amid social, organizational, and technological changes. Following PRISMA guidelines, we searched five databases (Academic Search Complete, MEDLINE, Psychology and Behavioral Sciences Collection, PsycINFO, and Web of Science) from 2000 to August 2025 using terms such as “electoral abstention” and “non-voting.” Inclusion criteria prioritized quantitative empirical studies in peer-reviewed journals in English, Portuguese, Spanish, or French, yielding 23 high-quality studies (assessed via MMAT, with scores ≥ 60%) from 13 countries, predominantly the USA and France. Results reveal abstention as a multidimensional phenomenon driven by three interconnected categories: individual factors (e.g., health issues like smoking and mental health trajectories, institutional distrust); institutional factors (e.g., electoral reforms such as biometric registration reducing abstention by up to 50% in local contexts, but with mixed outcomes in voluntary voting systems); and contextual factors (e.g., economic inequalities and urbanization correlating with lower turnout, exacerbated by events like COVID-19). This review underscores the need for integrated public policies addressing these factors to boost participation, particularly among youth and marginalized groups. By framing abstention as an adaptive response to contemporary challenges, this work contributes to the political psychology and democratic reform literature, advocating interdisciplinary approaches to resilient electoral systems. Full article