Search Results (1,316)

The overdose mortality landscape has shifted from predominantly opioid exposures to a polysubstance epidemic increasingly driven by illicit fentanyl and fentanyl analogs combined with other centrally active agents. Among the co-intoxicants, veterinary α₂-adrenoceptor (α₂AR) agonists such as xylazine have emerged as clinically confounding adulterants. Recent reports from forensic toxicology, medical examiners, and border/interdiction agencies indicate that medetomidine, a veterinary sedative racemate with the highly selective α₂AR agonist enantiomer dexmedetomidine, is increasingly being detected together with fentanyl and its analogs in seized materials and postmortem assays. Prior reviews have covered these aspects. The current review synthesizes current evidence and clinical experience relevant to fentanyl + medetomidine co-exposure-induced respiratory depression—a primary cause of death. We focus on convergent µ-opioid receptor (MOR) and α₂AR signaling within key physiological substrates, including respiratory rhythm-generating networks, ascending arousal pathways, chemosensory reflex control of ventilation, and autonomic cardiovascular regulation, integrating mechanistic pharmacology, respiratory and cardiovascular toxicology, emergency-room treatment, and emerging public-health implications. Available evidence supports a model in which combined MOR and α₂AR activation produces additive-to-synergistic suppression of ventilation and consciousness, attenuation of hypoxic ventilatory drive and CO₂ responsiveness, with marked sympatholysis manifested as bradycardia and hypotension, all of which can persist beyond presumptive opioid reversal with a MOR antagonist. We discuss the implications for prehospital and emergency care. In sum, the increasing detection of medetomidine in the illicit fentanyl supply represents an emerging and potentially high-risk co-exposure pattern that may be only partially naloxone-responsive. Lastly, we highlight potential future pharmacologic countermeasures for polysubstance overdose, such as the BK-channel antagonist ENA-001, which may address naloxone-insensitive ventilatory suppression in opioid-dominant polysubstance overdose. Full article

Head-mounted (“virtual reality”) perimeters (HMPs), based on standard consumer electronic hardware, are a cheaper alternative to standard automated perimetry. They have not been validated in patients with inherited retinal disease (IRDs), yet. We evaluated the Iowa-HMP in a first pilot study. It consists of a legacy smartphone, a headset, and freely available, open-source software. We used the 10-2 grid, the ZEST algorithm, and a background of 10 cd/m² to measure central visual fields in one normal subject, and in patients with occult macular dystrophy (n = 2), Stargardt’s disease (n = 3) and retinitis pigmentosa (n = 6). Results were compared with those from an Octopus 900 perimeter. The typical patterns of visual field loss were clearly discernible, but head-mounted perimeters generally have a limited dynamic range. Within the dynamic range of the Iowa-HMP (14 to 30 dB Octopus sensitivity), the Limits of Agreement (Bland-Altman) were ±7.5 dB. The Iowa-HMP had a diagnostic sensitivity of 0.67 for detecting locations with low perimetric sensitivity (<14 dB in the Octopus perimetry) with a diagnostic specificity of 0.95. Although the Iowa-HMP cannot be directly compared to standard perimetry in IRDs, open software greatly facilitates research in this area. Full article

This study proposes an integrated façade design framework that harmonizes the creative divergence of Generative AI with the economic efficiency of Design for Manufacturing and Assembly (DfMA). To address low productivity in the construction industry, a stepwise pipeline is developed, synthesizing image generation via Midjourney, automated coding using ChatGPT, and quantitative optimization. Central to this process is the Hamming Distance algorithm, which evaluates image similarity to implement core DfMA principles: standardization and simplification. The study introduces a multidimensional decision-making model utilizing Grid Size (GS), Replacement Rate (RR), and Hamming Threshold (HT) indices to visualize the trade-off between component minimization and design fidelity. This process transforms abstract 2D patterns into manufacturable geometric panels, bridging the gap between conceptual design and constructability. The results demonstrate that algorithmic optimization significantly reduces component count, contributing to potential cost savings and schedule reduction. Ultimately, this research establishes a collaborative model where architects’ qualitative insights complement AI’s quantitative analysis, enabling designers to regain agency over digital tools and realize creative visions within technical constraints. Full article

The conflict between the economy and the ecological environment is prominent in China’s coastal cities, and these cities contend with heightened uncertainty. Therefore, this study uses the econometric model to analyze the spatial–temporal pattern characteristics and affecting factors of the coupling coordination level between urban economic resilience (ER) and urban ecological resilience (EcR) in China’s coastal cities based on improvement of the evaluation index system, thus advancing policy suggestions. The main conclusions are as follows: (1) The coupling coordination degree (CCD) between ER and EcR across different types of coastal cities strongly correlates with their spatial distribution patterns of economic development. From the East China Sea to the South China Sea and Yellow and Bohai Sea Coast cities and from central cities to industrial cities, other types of cities, and resource-based cities, CCD exhibits an overall declining trajectory. (2) The gap in CCD in China’s coastal cities generally shows an expanding trend. (3) The spatial distribution pattern of the centrality of CCD in China’s coastal cities has a relatively high consistency. Urban spillover roles are highly consistent with levels of economic development. (4) The number and diversity of dominant influencing factors have steadily increased. Full article

Exploring the lunar complex and extreme terrain presents formidable challenges for conventional lunar rovers. To address these limitations, this study proposes a novel hexapod jumping hybrid robot that incorporates a “figure-of-eight” (butterfly-shaped) six-branched wheel-legged mechanism and a jumping system that stores elastic energy via deformation of its elastic body. Inspired by the multimodal locomotion of grasshoppers, the robot dynamically switches between two operational modes: high-efficiency wheeled locomotion on relatively flat surfaces and agile jumping to traverse steep slopes and surmount large obstacles. A bio-inspired gait, inspired by the crawling patterns of a hexapod insect, is implemented using a Central Pattern Generator (CPG)-based controller to produce coordinated, rhythmic limb movements. Dynamic simulations of the jumping mechanism were conducted to optimize the critical parameters of the elastic structure and its associated control strategy. Experiments on a physical prototype were conducted to validate the robot’s wheeled mobility and jumping performance. The results demonstrate that the robot exhibits excellent adaptability to rugged terrains and obstacle-dense environments. The integration of multimodal locomotion and adaptive gait control significantly enhances the robot’s operational robustness and survivability in the harsh lunar environment, opening new possibilities for future lunar exploration missions. Full article

Idiopathic central precocious puberty (CPP) is increasingly observed in girls. Premature thelarche (PT) and exaggerated thelarche (ET) are early pubertal variants that can be challenging to distinguish from CPP in clinical practice. Exosomal microRNAs are stable biomarkers capable of crossing the blood–brain barrier. Although miR-30b-5p has been reported to increase in pubertal boys and girls, human studies investigating microRNAs in CPP and puberty remain limited. To investigate exosomal microRNA expression profiles and associated pathways in early pubertal development, we conducted a cross-sectional study of 28 girls aged 6–8 years. Serum exosomal microRNA expression was analyzed using next-generation sequencing. Differentially expressed microRNAs (DEmiRNAs) between groups were identified, followed by pathway enrichment analysis. Distinct exosomal miRNA expression patterns were observed among the CPP, ET, and control groups, with 307 DEmiRNAs identified. The CPP, PT, and ET groups exhibited distinct miRNA expression profiles compared with the control group. miR-30b-5p was upregulated in the CPP, ET, and PT groups compared with the control group. Pathway enrichment analysis revealed the involvement of various signaling pathways including AGE–RAGE, MAPK, and mTOR signaling pathways. Serum exosomal microRNAs may serve as biomarkers for early puberty and provide insight into metabolic influences on pubertal development. Full article

As extreme heat events become increasingly frequent worldwide, there is an urgent need for fine-scale assessment of urban heat risk and for identifying its key determinants. Conventional approaches often struggle to capture complex intra-urban spatial heterogeneity, limiting effective heat risk governance and resource allocation. This study applies the Hazard–Exposure–Vulnerability–Adaptation (HEVA) framework by integrating remote sensing, road network, and socio-demographic data. Using the CRITIC weighting method, we quantify and map a street-level heat risk index (HRI) in Tianjin, China. We further employ geographically weighted machine learning models to identify dominant drivers and to characterise nonlinear effects, interaction patterns, and spatially varying relationships. Model reliability is assessed by benchmarking geographically weighted models against global nonlinear baselines under three-fold cross-validation; GW-XGBoost achieves comparable explanatory power to the best global model (R² = 0.672) while yielding lower prediction errors (MAE = 0.142), supporting robust spatial inference. Results show that elevated heat risk is not confined to the urban core; instead, it is more pronounced in peripheral transitional zones around central districts. These areas often exhibit coincident heat stress and high population exposure, a higher concentration of vulnerable groups and ageing residential neighbourhoods, and comparatively limited access to medical and cooling resources. Mechanistically, greater development intensity is generally associated with higher heat risk, whereas higher vegetation cover tends to reduce risk; however, the strength and, in some locations, the direction of these effects vary substantially across streets. These findings suggest that heat risk management should prioritise peripheral transitional zones. Targeted interventions should balance development intensity, expand effective greening and shading, and improve the provision and accessibility of healthcare and cooling services to reduce street-level heat risk. Full article

To address the challenge of disconnection between cultural and ecological values in Linear Cultural Heritage (LCH) conservation, this study examines the Jinzhong section of the Great Tea Road to develop a dual-dimensional framework for corridor identification and collaborative governance. The research establishes a dual-value evaluation system encompassing cultural and ecological dimensions, applied to grade 422 heritage sites. A potential corridor network is subsequently generated using the Minimum Cumulative Resistance (MCR) model. The study innovatively integrates the Multiple Centrality Analysis (MCA) model, employing heritage site values as network weights to identify and classify two primary corridor types: “culture-dominant” and “ecology-dominant” corridors. Through spatial overlay analysis, a ‘culture–ecology composite corridor’ network is ultimately constructed. The results demonstrate that the cultural value network exhibits a “monocentric” clustering pattern, whilst the ecological value network displays a “multicentric, networked” configuration, revealing significant spatial disjunction between the two systems. This analysis enables the identification of three corridor typologies—culturally dominant, ecologically dominant, and composite corridors integrating both values—alongside the positioning of key connectivity hubs and network vulnerability points across distinct value zones. The proposed “dual-dimension Multiple Centrality Analysis analytical framework” transforms the abstract concept of cultural–ecological value coupling into a quantifiable spatial analysis pathway, thereby addressing existing research gaps. This framework provides refined decision-making support for both conservation practices and World Heritage nomination processes of the Jinzhong section of the Great Tea Road, whilst offering a replicable scientific methodology for conserving comparable linear heritage sites globally. Full article

To advance human society towards a fully inclusive and accessible digital future, it is essential to foster the comprehensive and balanced development of digital villages, thereby addressing rural residents’ aspirations for a digitally enriched life. This study systematically investigates the spatiotemporal differentiation patterns and spatial spillover effects of China’s Digital Rural Development (DRD). Utilizing panel data from 31 provinces in China from 2013 to 2022, we construct a comprehensive evaluation framework covering digital infrastructure, economic digitization, governance digitization, and life digitization. The empirical analysis integrates entropy weighting, Dagum Gini coefficient decomposition, Moran’s I index, and spatial Durbin models. The findings indicate that China’s DRD has exhibited sustained overall improvement, progressing through three distinct phases: slow growth, rapid advancement, and fluctuating ascent. Significant regional disparities persist, with eastern regions consistently outperforming central, western, and northeastern areas. Inter-regional differences constitute the primary source of overall variation, and this gap has progressively widened over time. Spatially, DRD demonstrates a significant positive agglomeration effect alongside a negative spatial spillover effect (ρ = −1.3209), suggesting that advancements in neighboring regions may inhibit local development progress. Mechanism analysis identifies technological innovation, rural population size, and age structure as key local determinants, whereas industrial upgrading generates significant positive spillover effects on surrounding regions. Based on these results, at the same time, in order to ensure the sustainable development of DRD, we propose the following policy recommendations: implement regionally differentiated interventions, enhance the alignment of core local drivers, establish interregional coordination mechanisms, and develop dynamic monitoring and adjustment systems. These measures are expected to promote more balanced urban–rural and regional development, offering empirical evidence and policy insights for other developing countries pursuing similar pathways of rural digital transformation. Full article

Against the dual backdrop of the rural revitalization strategy and the pursuit of high-quality, balanced urban–rural education, optimizing rural campus spaces has emerged as an important lever for addressing educational resource disparities and improving pedagogical quality. However, conventional evaluation of campus space optimization faces two systemic dilemmas. First, top-down decision-making often neglects the authentic needs of diverse stakeholders and place-based knowledge, resulting in spatial interventions that lose regional distinctiveness. Second, routine public participation is constrained by geographical barriers, time costs, and sample-size limitations, which can amplify professional cognitive bias and impede comprehensive feedback formation. The compounded effect of these challenges contributes to a disconnect between spatial optimization outcomes and perceived needs, thereby constraining the distinctive development of rural educational spaces. To address these constraints, this study proposes a novel method that integrates regional spatial feature recognition with digital media-based public perception assessment. At the data collection and ethical governance level, the study strictly adheres to platform compliance and academic ethics. A total of 12,800 preliminary comments were scraped from major social media platforms (e.g., Douyin, Dianping, and Xiaohongshu) and processed through a three-stage screening workflow—keyword screening–rule-based filtering–manual verification—to yield 8616 valid records covering diverse public groups across China. All user-identifying information was fully anonymized to ensure lawful use and privacy protection. At the analytical modeling level, we develop a Transformer-based deep learning system that leverages multi-head attention mechanisms to capture implicit spatial-sentiment features and metaphorical expressions embedded in review texts. Evaluation on an independent test set indicates a classification accuracy of 89.2%, aligning with balanced and stable scoring performance. Robustness is further strengthened by introducing an equal-weight alternative strategy and conducting stability checks to indicate the consistency of model outputs across weighting assumptions. At the scenario interpretation level, we combine grounded-theory coding with semantic network analysis to establish a three-tier spatial analysis framework—macro (landscape pattern/hydro-topological patterns), meso (architectural interface), and micro (teaching scenes/pedagogical scenarios)—and incorporate an interpretive stakeholder typology (tourists, residents, parents, and professional groups) to systematically identify and quantify key features shaping public spatial perception. Findings show that, at the macro level, naturally integrated scenarios—such as “campus–farmland integration” and “mountain–water embeddedness”—exhibit high affective association, aligning with the “mountain-water-field-village” spatial sequence logic and suggesting broad public endorsement of ecological campus concepts, whereas vernacular settlement-pattern scenarios receive relatively low attention due to cognitive discontinuities. At the meso level, innovative corridor strategies (e.g., framed vistas and expanded corridor spaces) strengthen the building–nature interaction and suggest latent value in stimulating exploratory spatial experience. At the micro level, place-based practice-oriented teaching scenes (e.g., intangible cultural heritage handcraft and creative workshops) achieve higher scores, aligning with the compatibility of vernacular education’s “differential esthetics,” while urban convergence-oriented interdisciplinary curriculum scenes suggest an interpretive gap relative to public expectations. These results indicate an embedded relationship between public perception and regional spatial features, which is further shaped by a multi-actor governance process—characterized by “Government + Influencers + Field Study”—that mediates how rural educational spaces are produced, communicated, and interpreted in digital environments. The study’s innovative value lies in integrating sociological theories (e.g., embeddedness) with deep learning techniques to fill the regional and multi-actor perspective gap in rural campus POE and to promote a methodological shift from “experience-based induction” toward a “data-theory” dual-drive model. The findings provide inferential evidence for rural campus renewal and optimization; the methodological pipeline is transferable to small-scale rural primary schools with media exposure and salient regional ecological characteristics, and it offers a new pathway for incorporating digital media-driven public perception feedback into planning and design practice. The research methodology of this study consists of four sequential stages, which are implemented in a systematic and progressive manner: First, data collection was conducted: Python and the Octopus Collector were used to crawl online comment data related to Fuwen Township Central Primary School, strictly complying with the user agreements of the Douyin, Dianping, and Xiaohongshu platforms. Second, semantic preprocessing was performed: The evaluation content was segmented to generate word frequency statistics and semantic networks; qualitative analysis was conducted using Origin software, and quantitative translation was realized via Sankey diagrams. Third, spatial scene coding was carried out: Combined with a spatial characteristic identification system, a macro–meso–micro three-tier classification system for spatial scene characteristics was constructed to encode and quantitatively express the textual content. Finally, sentiment quantification and correlation analysis was implemented: A deep learning model based on the Transformer framework was employed to perform sentiment quantification scoring for each comment; Sankey diagrams were used to quantitatively correlate spatial scenes with sentiment tendencies, thereby exploring the public’s perceptual associations with the architectural spatial environment of rural campuses. Full article

This study investigates the genesis of gold mineralization at the Rodruin prospect in the central Eastern Desert (CED) of Egypt, with the aim of constraining the relative contributions of metamorphic and magmatic fluids to ore formation. Gold mineralization at Rodruin is hosted by quartz–carbonate veins emplaced within a shear zone that transects low-grade metasedimentary sequences intruded by Ediacaran post-tectonic granitoids. It exhibits characteristics transitional between orogenic turbidite-hosted and polymetallic vein-type mineralization. Although metamorphic devolatilization is interpreted to have generated the dominant ore-forming fluids, adjacent granitoid intrusions acted primarily as a thermal engine, with only a limited direct input of magmatic-hydrothermal fluids. This interpretation is supported by the occurrence of magmatic-affiliated mineral inclusions (monazite, cassiterite, and zircon) coupled with generally low concentrations of trace elements typically enriched in granitic magmatic-hydrothermal fluids (Sb, Bi, Mo, W, Sn, Nb, and Ta), collectively indicating a subordinate magmatic contribution. Rare earth element (REE) patterns of the ore samples closely resemble those of the nearby granitoids, displaying LREE enrichment; however, a distinct positive Eu anomaly is restricted to the ore assemblages and is attributed to hydrothermal feldspar alteration supporting magmatic involvement in ore formation. Carbon and oxygen isotope compositions (δ¹³C = −6.6 to −2.36‰; δ¹⁸O = +15.7 to +19.7‰), together with REE signatures comparable to primitive mantle values and textural evidence for synchronous sulfide–carbonate precipitation, manifested by rhythmic banding of carbonates and sulfides unequivocally indicate a hydrothermal–metasomatic origin. Collectively, these lines of evidence support a hybrid metamorphic–magmatic model in which gold and associated base metals were predominantly transported by metamorphic fluids, whose mobilization and focusing were enhanced by the thermal influence of Younger granitic intrusions, whereas magmatic-hydrothermal fluids contributed only a minor proportion to the overall metal budget. Full article

Intergenerational wealth transfer represents a central mechanism through which genealogical bonds, family continuity, and economic stability are maintained across generations. This article examines inheritance law and financial regulation from a genealogical perspective, focusing on the role of family property as both a legal institution and a socio-economic structure rooted in kinship and lineage. By integrating approaches from genealogy, legal studies, and financial analysis, the study explores how inheritance frameworks shape intergenerational relations, preserve family identity, and influence patterns of economic inequality. The article analyzes inheritance law as a key instrument through which genealogical continuity is institutionalized, highlighting the ways in which legal norms regulate the transmission of assets, rights, and obligations within families. Particular attention is given to the interaction between financial regulation and family-based wealth, demonstrating how legal structures affect long-term economic sustainability and social cohesion. The study adopts a qualitative and theoretical methodology, supported by comparative references to selected legal traditions, in order to illustrate how inheritance systems reflect broader cultural, historical, and genealogical values. By situating inheritance and wealth transfer within the broader framework of genealogical relations, this article contributes to interdisciplinary discussions on family, law, and the economy. It argues that inheritance law should be understood not merely as a financial or legal mechanism, but as a genealogical process that shapes intergenerational bonds, social structures, and economic outcomes over time. Full article

Amid the compounded impacts of climate change, economic volatility, and sudden shocks, small and medium-sized cities (SMSCs) have become a critical yet frequently overlooked weak link in urban resilience research. Objective assessment of resilience in SMSCs is essential for improving the design and effectiveness of resilience-building policies. Following China’s official city-size classification criteria—i.e., using urban-district resident population as the statistical basis and defining SMSCs as cities with less than 1 million urban-district residents—this study examines 510 Chinese SMSCs from 2012 to 2023. An entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is employed to construct an urban resilience index. Subsequently, spatiotemporal disparities are characterized using nonparametric kernel density estimation and Dagum Gini coefficient decomposition. The results indicate that: (1) from 2012 to 2023, the resilience index of Chinese SMSCs rose from 0.1108 to 0.1121, with an average annual growth rate of 0.1067%. Overall resilience remains low, and the increase is modest, showing a clear regional gradient of Eastern > Central > Western > Northeastern China. (2) Spatiotemporal differentiation reveals the fastest growth in the Eastern region, a similar trajectory in the Central region, slower growth in the Western region, and a decline in the Northeastern region, reinforcing a pattern of gradient divergence. Within-region disparities generally converged, whereas between-region disparities expanded markedly; nonetheless, the transvariation (overlapping) component remained the primary contributor to overall inequality. (3) The resilience of Chinese SMSCs may face a potential Matthew-effect risk driven by the interaction of scale disadvantage and regional disadvantage. These findings provide evidence to support policies aimed at enhancing resilience in SMSCs and inform the development of differentiated resilience-building strategies across regions. Full article

The direct photolithographic patterning of quantum dots (QDs) presents a promising route for high-resolution displays, while the associated loss in electroluminescence efficiency remains a significant challenge. This work addresses this challenge by introducing a fluorinated bisazide-derived photo-crosslinker, which enables high-fidelity patterning while preserving optoelectronic properties. Central to our strategy, this molecularly engineered crosslinker undergoes efficient nitrene-mediated crosslinking upon i-line (365 nm) exposure, forming robust networks between the QDs’ native ligands without compromising their electrical functionality. This approach achieves high-fidelity red, green, and blue (RGB) patterns with individual pixel sizes of 24 μm × 24 μm and a narrow pixel spacing of 2.5 μm. Combined with a Zn_1−xMg_xO electron-transport layer to optimize interfacial charge balance, the resulting red quantum-dot light-emitting diodes (QLEDs) retain an external quantum efficiency of 10.88%, representing 85.67% retention compared to unpatterned devices. This strategy is universally applicable, as demonstrated by the successful operation of green (8.46% external quantum efficiency (EQE)) and blue (2.25% EQE) devices. Our work establishes a scalable, lithography-compatible platform that effectively bridges the gap between high-resolution patterning and high-performance electroluminescence, paving the way for next-generation full-color microdisplays. Full article

Gliomas are the most prevalent primary malignant neoplasms of the central nervous system, distinguished by their high recurrence rates and poor prognosis. Aerobic glycolysis in tumors generates excess lactate, which promotes lactylation, a post-translational modification (PTM). Although accumulating evidence implicates lactylation in glioma initiation and progression, previous lactylation-focused prognostic studies lacked single-cell resolution and broad validation, limiting their generalizability and clinical relevance. Single-cell and bulk RNA sequencing (RNA-seq) data were integrated to identify lactylation-enriched tumor cell populations and derive candidate genes. A risk model was developed using univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO), and its predictive performance was validated in independent cohorts from the China Glioma Genome Atlas (CGGA). To improve clinical applicability, a nomogram integrating the risk score incorporating key clinical variables was constructed and externally validated. The risk groups showed distinct immune microenvironment profiles and differential drug sensitivity patterns. In this study, we established and validated a lactylation-related gene signature, with the derived risk score serving as a reliable prognostic biomarker for glioma. Furthermore, the model not only predicts overall survival (OS) but also exhibits the potential to inform drug selection and stratify patients for more precise and personalized therapeutic interventions. Full article