Age-based licensing renewal policies are implemented in aging societies to protect vulnerable road users (VRUs), yet the rationale for selecting age thresholds remains uncertain. This study examined whether age 70 represents a threshold for VRU case fatality among crash-involved older drivers and whether license status modifies this association. This population-based cross-sectional study analyzed Taiwanese police-reported crash data from 2011 to 2024 involving nonprofessional car drivers aged ≥ 50 years and VRUs. Driver age was modeled categorically and continuously using restricted cubic splines (RCSs). License status was examined as an exploratory effect modifier. A prespecified primary linear-spline analysis directly tested for a change in slope at age 70, while supporting RCS analyses evaluated overall nonlinearity. Multivariable logistic regression with cluster-robust standard errors estimated adjusted odds ratios (AORs) and 95% confidence intervals (CIs). Among 602,782 crash-involved VRUs, 2,789 sustained fatal injuries (0.46%). The prespecified analysis did not detect a change in slope at age 70 (change-in-slope AOR per year, 1.001; 95% CI, 0.977–1.025; P = 0.95), and the selected 3-knot RCS specification provided no evidence of overall nonlinearity (P = 0.24). Compared with drivers aged 50–64 years, odds of VRU case fatality were higher among drivers aged 65–69 years (AOR 1.15; 95% CI, 1.03–1.28) and ≥ 70 years (AOR 1.14; 95% CI, 1.01–1.29). However, among drivers aged 65–99 years, age ≥ 70 years was not independently associated with VRU case fatality (AOR 1.08; 95% CI, 0.93–1.25; P = 0.32). Unlicensed driving was associated with higher odds of VRU case fatality (AOR, 1.92; 95% CI, 1.62–2.28). Overall, the prespecified analysis did not detect a change in slope at age 70, while the association with unlicensed driving highlights a potentially important correlate of VRU case fatality among crash-involved older drivers.
Human brain organoids (HBOs) are three-dimensional structures derived from human stem cells that model aspects of brain development and function, offering potentially unprecedented opportunities for studying neurological disorders and for developing treatments. This consensus paper presents recommendations from the Asia Pacific Neuroethics Working Group, developed through interdisciplinary collaboration among scientists, bioethicists, philosophers, and legal scholars who convened in Singapore in November 2024. We provide a comprehensive analysis of the ethical, legal, and sociocultural dimensions of HBO research, addressing both current realities and future possibilities. The paper examines key ethical considerations, including the potential moral status of HBOs, particularly regarding sentience and consciousness, while identifying and dispelling common misconceptions and “ethical red herrings” arising from sensationalized portrayals. We analyze consent frameworks for cell donation, privacy concerns, dual-use risks, and questions of distributive justice. Legal challenges are explored, including the categorical ambiguity of HBOs within existing regulatory frameworks, intellectual property issues, and cross-border inconsistencies in standards. Sociocultural perspectives emphasize the importance of public understanding, cross-cultural engagement, and empirical research on diverse community attitudes toward HBO research. In our recommendations, we advocate for evidence-based ethical discussions, anticipatory frameworks addressing potential future developments, contextualized analysis comparing HBOs to related experimental models, robust informed consent processes, proportionate responses to consciousness concerns, development of adaptive regulatory frameworks, responsible science communication to manage public expectations, and sustained interdisciplinary collaboration. We emphasize a balanced approach that promotes scientific innovation while maintaining rigorous ethical oversight, recognizing HBOs’ significant potential for advancing neuroscience and medicine. This represents the first comprehensive ethical framework for HBO research from the Asia Pacific region, helping to establish foundational principles for responsible development of this rapidly advancing field.
Tumor stemness is increasingly recognized as a key contributor to tumor heterogeneity, immune regulation, and therapeutic resistance in colorectal cancer (CRC). In this study, we developed a stemness-based risk model using bulk transcriptomic data from The Cancer Genome Atlas and evaluated its prognostic and therapeutic relevance through integrative analyses. The proposed risk score robustly stratified patients into distinct prognostic groups and remained an independent predictor of overall survival after adjustment for clinicopathological variables. Stemness-high tumors exhibited altered immune infiltration patterns and coordinated upregulation of immune checkpoint-related genes. Although the association between stemness score and immune evasion potential was modest, its clinical relevance was supported by validation in independent immunotherapy-treated cohorts, where low-risk patients demonstrated improved survival and higher response rates. Single-cell RNA sequencing (scRNA-seq) analysis further revealed that enhanced stemness and dedifferentiation were predominantly localized within malignant epithelial cells. Together, these findings establish tumor stemness as a central determinant of prognosis, immune regulation, and therapeutic vulnerability in CRC.
Osteoporosis is a major and growing health concern in the Asia-Pacific region, y et it remains widely underdiagnosed and undertreated due to limited access to dual-energy X-ray absorptiometry (DXA) in many areas. Artificial intelligence (AI) offers new opportunities to improve osteoporosis screening and management, but unvalidated tools pose risks of inconsistent care. This consensus was developed to provide regionally harmonized guidance on the safe, effective, and equitable use of AI in osteoporosis care. Purpose The aim of this work was to establish expert consensus recommendations on the role of AI in osteoporosis screening and management in the Asia-Pacific region. Key objectives were to define appropriate applications of AI (e.g., imaging-based bone assessment and fracture risk prediction) and specify minimum standards for validation and reporting, addressing region-specific implementation challenges and ensuring that AI use aligns with clinical guidelines and ethical principles. Methods This consensus was developed through multidisciplinary collaboration among experts across the Asia-Pacific region. Each participant reviewed draft statements, contributed feedback during virtual meetings, and provided insights based on clinical experience and current evidence. Consensus was reached iteratively until full agreement was achieved for all statements. The process integrated global best practices and regional adaptations, drawing from peer-reviewed studies, international AI guidelines, and local fracture registry data. The final recommendations emphasize the validation, transparency, and ethical implementation of AI within regional healthcare systems, ensuring compatibility with local regulations. Ultimately, twelve consensus statements were established to guide the responsible use of AI for osteoporosis screening and management in the Asia-Pacific region. Results The panel produced 12 consensus statements covering the role of AI as an adjunct for opportunistic osteoporosis screening rather than a diagnostic tool, requirements for imaging quality and AI model transparency, standards for validation and performance reporting, integration of AI with clinical risk stratification, demonstration of clinical utility in real-world settings, adherence to data protection laws and ethical AI principles, training of clinicians in AI use, strategies for implementation and monitoring (including post-market surveillance and feedback loops), and recognition of technical, clinical, and equity limitations of AI. All 12 statements give extensive recommendations for using AI to improve osteoporosis management while ensuring patient safety, accuracy, and equity. Conclusion This first Asia-Pacific consensus on AI in osteoporosis concludes that AI, when appropriately validated and implemented, can help bridge the osteoporosis care gap by identifying high-risk patients who would otherwise remain undiagnosed, thus facilitating earlier intervention. It emphasizes that AI should complement-not replace-standard diagnostic methods and clinical judgment. The guidance emphasizes validation, transparency, and ethical oversight to facilitate early intervention while minimizing risks associated with unvalidated or premature AI adoption.
Hypoxia in tumor niche is one of important factors to start regeneration of blood vessels, leading to increase survival, proliferation, and invasion in cancer cells. Under hypoxia microenvironment, furthermore, steadily increased hypoxia-inducible factor-1α (HIF-1α) is observed, and can increase vascular endothelial growth factor (VEGF) expression and promote angiogenesis. Zinc protoporphyrin (ZnPP), a heme oxygenase-1 (HO-1) inhibitor, is potential to inhibit tumor proliferation and progression. However, the mechanism of ZnPP in inhibition of tumor is not completely clear. We hypothesize that ZnPP may modulate HIF-1α through inhibiting HO-1, and then inhibit angiogenesis and tumor progression. This study aimed to dissect the mechanism of ZnPP in tumor suppression.
