Search Results (3,038)

Secreted frizzled-related protein 4 (sFRP4) has traditionally been regarded as a Wnt antagonist with tumor-suppressive properties. However, growing evidence indicates that its role in cancer is far more complex and highly context-dependent. Depending on tumor type, molecular subtype, epigenetic state, and microenvironmental conditions, sFRP4 may exert either inhibitory or tumor-promoting effects. This functional heterogeneity has important implications for understanding cancer biology and for evaluating the clinical relevance of sFRP4. In this review, we summarize current knowledge of the structural features, regulatory mechanisms, and signaling functions of sFRP4, and discuss how these factors shape its diverse roles across malignancies. We further examine its potential significance in diagnosis, prognosis, therapeutic stratification, and systemic metabolic regulation. A clearer understanding of the context-specific behavior of sFRP4 may help refine its value as a biomarker and support the development of more precise and mechanism-informed therapeutic strategies. Full article

Diffusion models have achieved remarkable success in image generation, but their iterative denoising process requires repeated evaluations of large neural networks, resulting in high inference latency. Recent training-free acceleration methods, such as DeepCache, exploit temporal redundancy in U-Net features by caching and reusing high-level representations across adjacent denoising steps. However, existing caching strategies usually adopt a static skip-branch selection throughout the sampling trajectory, ignoring the stage-dependent frequency evolution of diffusion sampling. In this paper, we propose an interval-guided adaptive branch routing strategy to improve training-free feature reuse. Motivated by the observation that low-frequency global structures change rapidly in early denoising stages while high-frequency details dominate later refinement, our method dynamically adjusts the skip branch according to the timestep. It preserves deeper computation in early stages for semantic reconstruction and progressively shifts to shallower branches in later stages to reduce redundant computation while maintaining fine-grained details. The proposed method requires no retraining and can be directly applied to pretrained U-Net-based diffusion models. Experiments show that FreqCache achieves up to 1.93× speedup on CIFAR-10, 1.50× speedup on LSUN-Bedroom and LSUN-Churches, and 10.60× speedup on ImageNet 256 × 256 compared with the baseline, while maintaining an Fréchet Inception Distance (FID) score comparable to or slightly better than DeepCache at the same cache interval. Full article

Online apparel size recommendation remains difficult because consumers cannot physically assess garment fit before purchase. It is a multi-dimensional fit evaluation problem, particularly for complex garments such as jackets, where multiple body areas jointly influence perceived fit. Existing methods often rely on limited anthropometric measures, heuristic rules, or behavioral data, restricting both accuracy and interpretability. To address this issue, this study proposes an interpretable multi-dimensional fit evaluation framework based on garment ease theory. The framework defines ideal ease as the target fit condition and quantifies deviations through a segment-based weighting mechanism. Section-level mappings between body and garment measurements are established, and differentiated penalties are assigned according to the semantic fit interval of each body area. Section-specific evaluations are aggregated into an overall fit score (OFS) for candidate size ranking and Top-K recommendation, while also providing detailed fit feedback. Experiments involving 270 female participants and two jacket styles show high recommendation accuracy, achieving Top-3 accuracies of 99.6% for the regular-fit jacket and 98.9% for the tight-fit jacket. Compared with traditional heuristic methods, the proposed approach demonstrates clear advantages in both performance and interpretability, offering a practical solution that balances accuracy, transparency, and deployability. Full article

Fire is the core safety threat to the survival and development of timber-framed buildings, and passive fire prevention intervention is the core foundation of fire protection systems for timber-framed buildings. Existing reviews suffer from limitations such as incomplete scenario coverage, insufficient breakdown of intervention mechanisms, and a lack of methodological standardization. This study strictly followed the PRISMA 2020 systematic review guidelines, searching the relevant literature from January 2016 to April 2026 on the Web of Science, Scopus, and Science Direct databases. After standardized screening, 89 valid articles were finally included and a systematic study was conducted through bibliometric analysis, keyword visualization, and multi-dimensional classification coding. The results show that the number of publications in this field has been continuously increasing from 2016 to 2025, with China accounting for 31.46% of the total, ranking first globally. The study constructed a core intervention mechanism system for passive fire prevention in timber-framed buildings, covering four categories: intrinsic flame-retardant modification, isolation protection, structural optimization, and spatial control. The working principles, application effects, advantages and disadvantages, and engineering application scenarios of each mechanism were clarified. This study systematically sorts out the core intervention mechanisms of passive fire prevention in timber-framed buildings, clarifies the research status and development trends in this field, and can provide evidence-based support for the design optimization, technology development, and engineering practice of passive fire protection for timber buildings. Full article

To explore the associations between protein-level ratios (rQLTs) and duodenal ulcer (DU) risk using Mendelian randomization (MR), colocalization, and pathway analysis approaches. A bidirectional MR approach was used to identify molecular targets linking rQLTs with DU, employing the inverse variance weighted (IVW) method for causal estimation. Colocalization analysis ensured the reliability of inferred causal relationships. Gene interaction networks were constructed via STRING, and key regulatory hub-genes were identified through Cytoscape analysis. Significant inverse associations were found between rQLT-ACE2/GGT1 (Angiotensin-converting enzyme 2/γ-glutamyl transpeptidase 1) (IVW, OR (95% CI) = 0.754 (0.674–0.843), adjusted P_IVW = 0.0005), and DU risk in the East Asian (Japanese) population. No statistically significant associations were observed in the European population. The findings indicate a genetic inverse association between rQLT-ACE2/GGT1 and DU risk in the East Asian (Japanese) population, while no corresponding association was observed in Europeans. These results provide genetic evidence consistent with a potential association rather than causal inference or biomarker validation. This study does not support conclusions regarding diagnostic or therapeutic utility at this stage. Full article

This study examines whether green finance promotes green development across Chinese prefecture-level cities from 2005 to 2019. We find a positive association between green finance and green development using panel regressions with city and year fixed effects. This result remains robust after accounting for potential endogeneity and implementing a series of robustness checks. Further heterogeneity analysis shows that this positive effect is stronger in regions characterized by high fiscal capacity and within the Yangtze River Economic Belt. Additionally, green finance drives regional green development by promoting green innovation. Environmental decentralization moderates the relationship, with a stronger positive effect at higher levels of decentralization. This study offers empirical evidence regarding how green finance shapes green development outcomes. Full article

Population aging has increased the need for public open spaces that older adults can use safely, comfortably, and confidently. In many urban parks and community squares, however, resting facilities are still designed as standardized street furniture, with cold materials, insufficient hand support, limited wheelchair-inclusive space, and weak support for everyday social interaction. This study examines age-friendly public facilities as micro-scale spatial elements that shape sitting, standing, staying, communication, and willingness to remain in small urban open spaces. Drawing on field observation, behavioral analysis, semi-structured interviews, and a multi-criteria design-evaluation process, the study identifies older adults’ key facility-use needs and translates them into design indicators and alternative facility schemes. The results show that physical support and inclusive spatial use are the most important design priorities. Standing-up assistance, sitting-posture support, perceived structural stability, and age-appropriate dimensional adaptation were more influential than purely decorative or auxiliary functions. Among the three alternative schemes, the modular pergola system performed best because it combined stable hand support, independent seating, an age-friendly interactive table, shaded resting space, wheelchair-inclusive layout, and wood-based sensory comfort. The sensitivity analysis further confirmed that this scheme maintained a stable advantage under most weight-adjustment conditions. The findings suggest that age-friendly public facility design should move beyond the improvement of individual furniture products and instead integrate bodily support, spatial accessibility, social interaction, material comfort, and environmental pattern quality. This study provides a design-decision framework for improving the inclusiveness, accessibility, and health-supportive capacity of urban public open spaces for older adults. Full article

Cross-market risk transmission in U.S. energy markets has become increasingly complex as fossil fuel prices, electricity markets, and clean energy financial exposure respond differently to stress episodes. Identifying whether dynamic spillover information contains forward-looking diagnostic value is therefore important for energy market risk monitoring. This study examines a daily six-market U.S. energy return panel covering WTI crude oil, Henry Hub natural gas, Brent crude oil, RBOB gasoline, PJM West electricity, and CELS clean-energy equity exposure from 2016 to 2025. We first estimate time-varying total, directional, and net connectedness using a TVP-VAR-DY framework and then transform the resulting connectedness measures into spillover-based features for supervised high-DSV20-state classification. The results show that energy-market connectedness is clearly time-varying, with crude oil benchmarks occupying central positions and market-level net spillover roles changing across market conditions. Under the retained label-80 Random Forest specification, connectedness-based features provide moderate diagnostic value for identifying future high-DSV20 states. Net WTI, Net Henry Hub, and Net CELS are the most informative spillover-role variables. Additional validation checks indicate that the evidence is best interpreted as support for diagnostic risk monitoring rather than as a high-accuracy forecasting system. The findings highlight the usefulness of dynamic connectedness measures as transparent inputs for energy-market risk assessment. Full article

Early-age temperature rise in mass concrete can generate substantial thermal gradients and increase the risk of cracking. In this study, a temperature-rise suppression concrete was developed by partially replacing conventional coarse aggregate with steel-encapsulated superabsorbent polymer (SAP)–water phase-change aggregates. Semi-adiabatic temperature-rise tests were conducted to characterize the early-age thermal response, and the corresponding adiabatic temperature-rise histories were reconstructed using a heat-loss compensation method. The results showed that the incorporation of steel-encapsulated SAP–water aggregates reduced the temperature rise and delayed the thermal peak under semi-adiabatic conditions. For SAP-15, the peak core temperature in the validated finite element simulation decreased from 51 °C to 44 °C, while the maximum adiabatic temperature rise decreased to 40.5 °C. Engineering-scale simulation of a bridge pile-cap foundation further showed reductions in internal peak temperature, temperature difference, and thermal stress. These findings demonstrate that steel-encapsulated SAP–water phase-change aggregates provide an effective material-based strategy for moderating early-age thermal accumulation and mitigating thermal cracking risk in mass concrete. Full article

This study evaluated a synergistic intervention integrating school social work and ethnic education for reducing dropout-related risk among male students in Zhuang vocational secondary schools in central Guangxi, China. Using a quasi-experimental mixed-methods design with baseline, post-intervention, and follow-up assessments, 457 students were enrolled and 435 were included in the final analysis. Compared with usual support, the intervention group showed a larger reduction in the dropout risk index at follow-up, β = −0.37, SE = 0.08, 95% CI [−0.52, −0.22], p < 0.001, and a lower likelihood of chronic absenteeism, OR = 0.56, 95% CI [0.34, 0.91], p = 0.020. The retention difference was positive but less precise, OR = 1.70, 95% CI [0.79, 3.67], p = 0.174. The intervention group also reported higher school belonging, β = 0.33, SE = 0.06, p < 0.001, and academic self-efficacy, β = 0.30, SE = 0.06, p < 0.001. Parallel mediation analysis suggested that these two protective factors accounted for part of the intervention-associated difference in dropout risk, with a total indirect effect of −0.20, 95% CI [−0.28, −0.12], p < 0.001. The findings suggest that culturally responsive practices, when combined with tiered case management and family engagement, may help strengthen protective processes and slow the accumulation of dropout-related risks. This study provides context-sensitive evidence for designing school retention interventions in vocational schools serving ethnic minority communities, while the quasi-experimental design warrants cautious interpretation. Full article

Transcriptional bursting, the stochastic production of mRNA in episodic pulses, is a fundamental source of cell-to-cell heterogeneity. In pluripotent stem cells (PSCs), these bursting dynamics at core pluripotency loci are not just noise but critical determinants of identity maintenance and lineage commitment. This review synthesizes current quantitative frameworks for dissecting bursting kinetics and elaborates on the multilayered regulatory hierarchy that governs them, ranging from promoter-intrinsic features and 3D genome architecture to the formation of transcriptional condensates via liquid–liquid phase separation (LLPS). By integrating findings from genomic profiling and live-cell imaging, we highlight how the integrated action between super-enhancers and epigenetic states shapes the unique bursting dynamics in PSCs. Furthermore, we explore the functional consequences of these kinetics in pluripotency surveillance and cell fate decisions. Collectively, this review establishes a unified regulatory framework, providing novel insights for understanding stem cell heterogeneity and offering key insights for regenerative medicine. Full article

As the global population continues to age, mental health issues such as depression, anxiety, stress, loneliness, and social isolation among older adults are receiving increasing attention. The built environment is closely associated with older adults’ daily mobility, environmental perception, social participation, and mental health and well-being, but the evidence remains heterogeneous across spatial contexts, environmental indicators, and study designs. Previous umbrella reviews have summarized broad links between the built environment and healthy aging, but less attention has been paid to recent original empirical studies published after the COVID-19 pandemic, the distinction between objective environmental exposure and subjective environmental perception, and the role of social participation as a pathway linking environmental conditions to mental health and well-being. This study employs a systematic literature review approach, searching and screening peer-reviewed empirical studies published between 2015 and January 2026 that focus on the associations between the built environment and older adults’ mental health and well-being. PubMed, Scopus, and Web of Science databases were used for searching, supplemented by manual searching. After title and abstract screening and full-text evaluation, a total of 60 studies were included. Subsequently, a comprehensive analysis was conducted on aspects such as research design, spatial scale, environmental indicators, types of mental health outcomes, and potential pathways of action. In this review, core mental health and well-being outcomes included negative outcomes, such as depression, anxiety, stress, psychological distress, loneliness, and social isolation, and positive outcomes, such as life satisfaction, subjective well-being, psychological well-being, and mental well-being. Social participation was examined as a behavioral and psychosocial pathway rather than as a core outcome. Emerging methods, including street-view image analysis, FCN-based semantic segmentation, and XGBoost-SHAP, were examined because they can refine environmental exposure measurement and support variable-importance interpretation, rather than because they provide causal evidence. The main synthesis suggests that several built environment factors are associated with older adults’ mental health and well-being, although the strength and consistency of evidence vary across outcome types, spatial contexts, and study designs. (1) Exposure to green and blue spaces, quality of public open spaces, walkability and accessibility, accessibility of neighborhood facilities and services, housing and living conditions, and positive environmental perception are mostly associated with lower levels of depression, anxiety, stress, and loneliness, as well as higher levels of life satisfaction, subjective well-being, and psychological well-being. (2) Conversely, adverse environmental exposures such as proximity to roads, pollution, non-vegetated spaces, and high-intensity urbanization are more likely to exacerbate negative psychological outcomes. Existing evidence also suggests that social participation is one of the important behavioral pathways through which the built environment is linked to the mental health of older adults, but it is not the only mechanism. (3) In addition, the direction and intensity of environmental associations remain heterogeneous under different spatial scales, indicator types, and research methods. Overall, this review contributes by organizing recent empirical evidence into a built environment–social participation–mental health and well-being framework, while emphasizing that most findings should be interpreted primarily as evidence of association rather than as stable or uniform causal effects. Full article

Reliance on standalone accuracy limits credible assessment of fundus-focused large vision–language models (LVLMs), as high scores often stem from linguistic shortcuts rather than real visual reasoning. This work develops the Cognitive Audit Framework (CAF), a four-module automated auditing pipeline that dissects model reasoning flaws: Visual–Linguistic Decoupling (textual dependency via modality ablation), Hierarchical Logical Consistency (lesion–diagnosis contradiction detection), Reasoning Fidelity Gap (chain-of-thought unfaithfulness scoring), and Contextual Robustness (positional bias under option permutation). Experiments on six 7B–31B LVLMs over FunBench reveal a notable gap between benchmark accuracy and reasoning quality: high accuracy coexists with measurable textual dependency, logical inconsistencies across diagnostic levels, limited chain-of-thought faithfulness, and non-trivial positional sensitivity. CAF serves as a reproducible complement to pure accuracy metrics for validating clinical competence of ophthalmic multimodal models. Full article

Unmanned aerial vehicle (UAV) object detection plays an essential role in modern visual perception, but it remains challenging because UAV imagery typically contains extremely small, densely distributed objects embedded in complex backgrounds. Conventional detectors, including the recent YOLOv12, are prone to losing critical spatial details during downsampling and often exhibit task misalignment between classification and localization, particularly under severe scale variations. To address these problems, this study proposes SPTD-YOLO, a small-object-aware pyramidal and task-aligned dynamic detector. Specifically, a Small Object Enhanced Pyramid (SOEP) is developed by incorporating SPDConv and CSPOmniKernel to preserve and refine shallow, fine-grained features. In addition, a high-resolution P₂ detection layer is introduced to increase spatial grid density and strengthen the structural representation of tiny objects. Furthermore, a Task-Aligned Dynamic Detection Head (TADDH) is designed to decouple and coordinate classification and regression through dynamic convolution and a synergistic dual-gating mechanism. Experiments on VisDrone2019 show that SPTD-YOLO improves mAP@0.5 by 8.37% and mAP@0.5:0.95 by 5.11% over YOLOv12 while maintaining practical efficiency for UAV edge deployment. Full article

Secure data collaboration among mutually distrustful organizations requires more than encrypted storage: it also needs accountable ownership control, auditable access governance, privacy-preserving transaction execution, and reliable settlement when data are exchanged as digital assets. This paper proposes TrustTrade, a unified multi-party secure data management and transaction framework designed for cross-organization data sharing, trading, and compliance-sensitive analytics. TrustTrade integrates policy-bound data capsules, a tamper-evident provenance ledger, adaptive threshold escrow, verifiable data-payment settlement, and selective audit with revocation rebinding. On four real-dataset-derived workloads, TrustTrade reaches a $90.4$–$94.8\%$ settlement rate, with a $92.5\%$ average that is $6.4$ percentage points higher than the strongest baseline average. Under adversarial request injection, TrustTrade reduces unauthorized release to $0.31\%$ and atomicity violation to $0.38\%$, corresponding to $93.6\%$ and $93.0\%$ reductions compared with Plain-Market, respectively; compared with Fixed-Escrow, unauthorized release is reduced by $77.4\%$. TrustTrade also achieves $96.7\%$ dispute-resolution accuracy while maintaining practical settlement latency. These results indicate that jointly designing secure data management and secure data transaction protocols offers a practical path toward trustworthy multi-party data ecosystems. Full article