Search Results (4,671)

Groundwater drainage-induced karst collapse is a major geohazard in coal-mining regions of central Hunan, threatening residential safety and infrastructure. This study focuses on the Tuoshan minefield in the Jinzhushan mining area by integrating multi-source field data, including surveys of 170 collapse points, long-term groundwater monitoring at six boreholes, and high-density electrical geophysics. A topographically corrected MODFLOW seepage-field model is developed and calibrated for 2014 (RMSE = 0.32 m; NSE = 0.85) and validated for 2015–2016 (RMSE = 0.41 m; NSE = 0.81). To address the large groundwater-level simulation errors commonly encountered in subtropical hilly karst mining settings, the model incorporates a topographic correction, improving simulation accuracy by 12% relative to an uncorrected model. The simulations capture rapid “steep rise–slow fall” groundwater dynamics: Heavy rainfall (>100 mm/day) raises groundwater levels by 2.8–3.1 m within 2–3 days, whereas pumping (200 m³/h) causes a 1.9–2.2 m decline within one week. A 1.2 km drawdown funnel forms and overlaps with 89% of collapse points, indicating that seepage-field evolution and groundwater-level decline control collapse clustering, with soil suffusion and soil–water–rock interaction acting as key amplifying processes. Based on Terzaghi’s effective stress principle and the Theis solution, a collapse prediction formula is derived and validated using measured events (accuracy = 87.5%), and a region-specific critical hydraulic gradient (i_n = 0.85) is determined, lower than values reported for North China. The proposed workflow provides quantitative thresholds and model-based guidance for karst collapse prevention in subtropical mining areas. Full article

This study maps the global scholarly landscape on digital parenting and children’s digital device use through bibliometric analysis of 628 Scopus articles (2010–2025). Using PRISMA-guided screening and science-mapping visualisations (VOSviewer and CiteSpace), the review identifies publication growth, influential sources, intellectual structures, and thematic clusters shaping the field. The mapped knowledge structure is dominated by health and media-effects traditions, with major research fronts centred on parental mediation, screen-time outcomes, online safety, and digital wellbeing. Crucially, the analysis shows that parenting perspectives remain weakly represented within this global corpus, with limited engagement with faith-based concepts that could shape mediation practices and moral reasoning in households. This underrepresentation contributes to a Western-centric evidence base, indicating a need for Islamically situated digital parenting research that integrates developmental concerns with ethics and culturally grounded mediation strategies. The study concludes by proposing a focused research agenda to strengthen theory building and empirical work in family contexts. Full article

Intramuscular fat (IMF) marbling is a key determinant of beef quality, yet predicting how breed-specific gene expression translates into tissue-scale fat patterning remains a major challenge. Using a small public transcriptomic dataset (n = 3 per breed), this study presents a proof-of-concept omics-to-tissue modeling framework that converts RNA-seq data into biophysically interpretable parameters governing intramuscular adipogenesis. Using transcriptomic profiles from GSE161967 (Japanese Black Wagyu versus Chinese Red Steppes), we derived composite indices capturing the adipogenic commitment (φ) and lipid droplet capacity (ψ) from curated gene modules. These indices were mapped via calibrated linear functions to a Cellular Potts Model (CPM), parameterizing the fibro-adipogenic progenitor (FAP) differentiation probability, lipogenesis rate, adipocyte cohesion, and progenitor abundance. The gene-derived parameters placed Wagyu in a high-adipogenic regime ($p_{F\to A}^{\mathrm{base}}$ = 0.65; $k_{lipogenesis}$ = 0.12), while Chinese Red Steppes resided in a low-adipogenic regime (0.25; 0.04). The CPM simulations revealed a sharp, predictive threshold at $p_{F\to A}^{\mathrm{base}}$ ≈ 0.55, below which IMF remained negligible and above which stable adipocyte clusters and 8–9% IMF emerged. Without post hoc tuning, the gene-derived parameters correctly predicted robust marbling in Wagyu and a lean phenotype in Chinese Red Steppes. A sensitivity analysis identified the adipogenic commitment as the primary control parameter, with lipogenesis acting as an amplifier. Together, these results demonstrate that transcriptomic measurements can quantitatively predict emergent marbling phenotypes through a small set of interpretable biophysical parameters, establishing a generalizable framework for forecasting complex tissue traits from omics data. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a major public health challenge, and several lifestyle-related factors associated with later T2DM may already emerge during the secondary school years. Socioeconomic status (SES), nutrition-related behaviors, physical activity, and basic diabetes-related knowledge may shape these early risk-related patterns. This study examined the relationships between SES, adapted FINDRISC-based T2DM-related risk patterns, and diabetes-related knowledge among Hungarian secondary school students aged 16–20 years. Methods: A nationwide, cross-sectional questionnaire survey was conducted among students attending Hungarian Baptist secondary schools (N = 1585). SES was classified by Two-Step cluster analysis based on parental education, parental occupation, number of books in the household, and frequency of travel abroad. Relative T2DM-related risk patterns were described using an age-adapted FINDRISC-based screening approach, and basic diabetes-related knowledge was assessed using a 12-item questionnaire. Associations were examined using cross-tabulation and regression analyses in SPSS version 27.0. Results: Most respondents fell into the lower categories of the adapted FINDRISC-based screening framework, whereas 7.4% were classified into the moderate or high adapted FINDRISC-based screening categories. SES was significantly associated with adapted FINDRISC-based screening categories (p < 0.001). Compared with the medium-SES group, students in the low-SES group had higher odds of belonging to a higher adapted FINDRISC-based screening category (OR = 1.81; 95% CI: 1.27–2.57; p = 0.001). SES was also significantly associated with basic diabetes-related knowledge profiles (p = 0.015); students with high SES were less likely to be in the low-knowledge group than in the high-knowledge group (OR = 0.62; p = 0.039). Conclusions: Social inequalities in T2DM-related risk patterns and diabetes-related knowledge are already visible among secondary school students aged 16–20 years. The adapted FINDRISC-based approach may be useful as a school-based, non-invasive descriptive screening framework for characterizing relative T2DM-related risk patterns, but it is not a validated risk prediction instrument for this age group. Full article

Critical-sized bone defects represent a major clinical challenge, as defects of this magnitude do not heal spontaneously without regenerative intervention. This study aimed to evaluate the osteoinductive effects of recombinant human bone morphogenetic protein-2 (rhBMP-2)loaded β-tricalcium phosphate (β-TCP) scaffolds on bone regeneration and vascularization in a rabbit calvarial critical-sized defect model. Eighteen male New Zealand White rabbits were used, and four standardized circular defects (5 mm in diameter) were created in the calvaria of each animal. The defects were assigned to four groups: control (unfilled), β-TCP + 5 µg rhBMP-2, β-TCP + 10 µg rhBMP-2, and β-TCP + 20 µg rhBMP-2. Bone healing was evaluated at 2, 4, and 8 weeks using histological, histomorphometric, and cluster of differentiation 31 (CD31) immunohistochemical analyses. The results demonstrated that rhBMP-2–loaded β-TCP scaffolds significantly enhanced bone regeneration compared with the control group, with a progressive increase in bone formation observed with increasing rhBMP-2 doses. The β-TCP + 20 µg rhBMP-2 group exhibited the highest levels of new bone formation, more advanced bone maturation, improved collagen organization, and increased vascularization. However, no statistically significant differences were observed between the 10 µg and 20 µg groups at later time points (p > 0.05), suggesting a dose-dependent saturation (plateau) effect. In conclusion, rhBMP-2–loaded β-TCP scaffolds promote bone regeneration and angiogenesis in a dose-related manner up to a threshold, beyond which additional increases in dose do not result in proportional improvements. These findings emphasize that optimal rhBMP-2 dosing is critical to maximize regenerative outcomes while avoiding unnecessary dose escalation. Full article

The common bean (Phaseolus vulgaris L.) is a major food legume and an important plant genetic resource for sustainable agriculture. Effective use of this diversity requires integrated evaluation of phenotypic variation and agronomic performance, with preliminary assessments of line performance across seasons. In this study, phenotypic diversity was evaluated in a subsample of the INCREASE R-core collection, a large and well-defined core set of common-bean SSD lines derived from heterogeneous germplasm lines. A total of 507 lines were characterized using 57 agro-morphological traits. Multivariate analyses revealed wide phenotypic diversity structured mainly by growth habit, phenology, and yield-related traits, with clear differentiation among lines. Mixed-data clustering identified cluster 4 as the main phenotypic group associated with higher seed- and yield-related performance and composed predominantly of indeterminate climbing landraces. Multi-trait selection indices generally ranked lines from this group highest, while early, small-seeded types tended to show lower overall performance. Evaluation of a selected subset of 19 lines across two growing seasons revealed marked year-to-year variation in yield performance, indicating contrasting responses among otherwise high-performing lines. The multi-trait genotype–ideotype distance index further distinguished lines with balanced performance across traits and years. Overall, this study shows that large-scale phenotypic characterization combined with multi-trait evaluation can provide a useful exploratory basis for identifying breeding-relevant ideotypes and promising lines for further validation for common-bean improvement. Full article

The synergistic effects of soil acidification and heavy metal pollution present major challenges for global agroecosystems. To systematically trace the evolution of research and identify key topics in this field, this study employed CiteSpace to visualize and analyze 691 records from the China National Knowledge Infrastructure (CNKI) and 6747 highly relevant articles or reviews from the Web of Science (WOS) Core Collection database from 2005 to 2025. The results indicate a steady to rapid rise in global publications, with China contributing the largest share, at 2468 publications. This has produced a research cluster centered around the Chinese Academy of Sciences (CAS); however, the centrality of its international cooperation remains limited. Studies in the CNKI database are driven by agricultural needs, focusing on national food security, rice yield stability, improvement of arable land, and heavy metal passivation and remediation, with a concentration on basic agricultural science. By contrast, research in the WOS database emphasizes fundamental mechanisms and interdisciplinary integration, addressing aluminum toxicity, microbial communities, the nitrogen cycle, and global climate change, intersecting fields such as environmental science, soil science, ecology, and microbiology. The evolution of research hotspots shows a clear trajectory: from acidity regulation and chemical speciation analysis of heavy metals (2005–2013), to heavy metal passivation, remediation, and phytoremediation (2014–2018), and then to biochar materials, microbiome analysis, and the synergistic role of carbon sequestration (2019–2025). This study argues that future research should move beyond single remediation measures and adopt integrated strategic management to jointly improve bioremediation efficiency, promote soil carbon sequestration and soil health, and enhance microbial adaptation to global climate change. Full article

Generally, forest trees with medicinal value present diverse chemotypes considered key determinants of efficacy, safety, and commercial valuation. Such heterogeneity varies among tissues, genotypes, and seasons, and stress exposure. This review summarizes how regulatory controls and genome architecture affect the stability and synthesis of secondary metabolites in woody medicinally important taxa. Detailed haplotypic and chromosomal analyses have recently identified diverse and repeatable architectural drivers. Among these, LTR/transposon-mediated revamping, neofunctionalization, biosynthetic gene clusters, and tandem duplication play a special role in reshaping pathway capacity. The enzymatic regulation of these drivers translates this “capacity” into harvest-pertinent chemistry by employing conserved TF modules, hormone crosstalk, and emergent chromatin/epigenetic layers. Nevertheless, major parameters pertaining to the tissue-specific storage, transport, and compartmentalization of these chemotypes are contextualized with certain limitations. In this review, the integration of GWAS/eQTL/TWAS with multi-tissue is explained in addition to the replacement of a single reference with pangenome/haplotype frameworks, and explicit modeling of G × E further strengthen genotype-to-chemotype mapping. Therefore, in this review we summarize practical workflows for chemotype discovery utilizing staged validation models of heterologous reconstitution, isotope/spatial evidence, and chemistry. These findings were supported by data on saponins, alkaloids, iridoids, and defense response. Such an integration links mechanistic understanding to authentication, standardization, and sustainable utilization strategies in woody medicinal trees. Full article

Background/Objectives: Peritoneal micrometastases (micromets) remain a major barrier to durable cytoreduction in ovarian and other intra-abdominal cancers because lesions are difficult to visualize and are often resistant to systemic therapy. Liposomal doxorubicin (Dox) improves pharmacokinetics but can be limited by slow intratumoral release. Porphyrin-phospholipid (PoP) liposomes enable near-infrared light–triggered release of Dox (chemophototherapy (CPT)), creating an opportunity for intraoperative fluorescence-guided treatment planning and monitoring. Here, we evaluate a laparoscopic fluorescence imaging platform for quantifying light-triggered drug delivery. Methods: LC-Dox-PoP was applied to SCC2095sc and SKOV-3 cultures in 2D monolayers and 3D spheroid clusters. Dox fluorescence was quantified using a laparoscopic fluorescence imaging system over 1–9 μg/mL concentrations and compared with standard well-plate reader measurements. Porphyrin fluorescence was monitored to assess spheroid localization and photobleaching after activation light exposure. Results: For both cell lines, Dox fluorescence exhibited an approximate 4-fold increase at the maximum administered LC-Dox-PoP concentration, following a linear trend in both SCC2095sc and SKOV-3 cultures (R² = 0.97, 0.98 for 2D and R² = 0.98, 0.98 for spheroids). Laparoscope-derived fluorescence measurements agreed with well-plate reader measurements (R² = 0.89–0.96). Porphyrin fluorescence provided stronger complementary contrast for localizing spheroid constructs and decreased after activation light exposure, consistent with photobleaching during triggered release. Conclusions: These results support a quantitative imaging framework for fluorescence-guided monitoring of light-triggered liposomal drug release and may enable individualized CPT dosimetry for peritoneal micrometastases. Findings in SCC2095sc additionally suggest potential relevance of fluorescence-guided CPT for head and neck/oral cancer, where localized post-resection adjuvant treatment may improve control of residual disease. Full article

This study aims to identify and synthesize the major global trends that shaped 2025 by applying the DeflyCompass methodology to a curated corpus of strategic foresight reports. The study synthesizes insights from 23 strategic reports published by leading international organizations, including the World Economic Forum, Accenture, Euromonitor, and major technology firms. Methodologically, DeflyCompass operationalizes a structured hybrid human–AI pipeline comprising the deployment of multi-agent AI systems, automated knowledge graph construction, semantic clustering, and hybrid human–AI validation processes, reducing an initial set of 816 preliminary signals to a validated catalog of 50 high-priority trends across six PESTEL domains: Political, Economic, Social, Technological, Environmental, and Legal/Governance. Key findings indicate that artificial intelligence functions as a systemic enabling technology across all domains, climate and sustainability imperatives permeate multiple domains, geopolitical fragmentation introduces systemic tension, and trust deficits emerge as a critical vulnerability. The study contributes a replicable and scalable framework for global-level strategic foresight that operationalizes human–AI integration within a rigorous expert-driven validation process, complementing existing hybrid analytical approaches in the literature. Implications extend to decision-making in technology governance, sustainability strategy, social adaptation, and scenario planning, highlighting the necessity of integrating AI augmentation with human expertise for effective future-oriented planning. Full article

Despite its potential to enhance construction quality, efficiency, and sustainability, modular construction continues to experience defects that hinder its broader adoption. Understanding and mitigating defects is essential for maximising the sustainability benefits of modular construction by reducing material waste, minimising rework and improving lifecycle performance. Existing research remains fragmented, with limited synthesis integrating defects with their root causes across the project lifecycle. To address this gap, this study investigates defect types, lifecycle-based causes, and mitigation strategies in modular building projects through a PRISMA-guided systematic literature review of 61 peer-reviewed journal articles published between 2015 and 2025 and retrieved from Scopus and Web of Science. Six major defect categories were identified: geometric and dimensional; material and component; joint and connection integrity; envelope performance and durability; structural; and mechanical, electrical, and plumbing (MEP) defects, with geometric and dimensional defects emerging as the most prevalent, accounting for 26.7% of reported cases. Lifecycle root-cause mapping indicates that poor workmanship during on-site assembly is the dominant contributor, accounting for 44.1% of identified root causes, with manufacturing errors (26.8%) and design limitations (13.4%) acting as critical upstream sources. Mitigation strategies cluster into three groups: general recommendations (39% of reported strategies), mainly focusing on low-cost organisational measures such as logistics coordination and workforce training; structured risk-management frameworks (9.1%), including assembly sequencing and tolerance planning; and digital and data-driven technologies (51.9%), such as laser scanning, AI-based inspection, and digital twins, enabling proactive quality assurance across the lifecycle. The study proposes an integrated lifecycle–defect–mitigation framework to strengthen quality governance and advance sustainable modular delivery. Full article

Listeria monocytogenes remains a major foodborne pathogen associated with ready-to-eat (RTE) products, including smoked fish. This study investigated the occurrence, molecular characteristics, virulence gene profiles, and antimicrobial susceptibility of L. monocytogenes isolated from retail smoked fish in Poland. A total of 46 samples (cold- and hot-smoked products) collected from 15 producers and five retail chains were analyzed using ISO 11290-1:2017 for qualitative detection and ISO 11290-2:2017 for enumeration. Listeria spp. were detected in 5/46 samples (10.9%), including 4 isolates confirmed as L. monocytogenes (8.7%). All positive samples originated from cold-smoked salmon, with a prevalence of 4/13 (30.8%) in this product category. The quantitative analysis indicated that contamination levels in all positive samples were below 100 CFU/g. Molecular serogrouping and multiplex PCR demonstrated the presence of key virulence-associated genes, including hlyA, prfA, plcB, and actA, consistent with potentially pathogenic profiles. Pulsed-field gel electrophoresis (PFGE) revealed clustering of isolates, indicating genetic relatedness among strains obtained from different retail sources. Antimicrobial susceptibility testing using the MICRONAUT system showed that all L. monocytogenes isolates were susceptible to first-line therapeutic agents, including ampicillin and penicillin, according to EUCAST/CLSI criteria. Although contamination levels were low and isolates remained susceptible to clinically relevant antimicrobials, the detection of virulence-associated strains in RTE smoked fish highlights the need for continuous monitoring and strict hygienic control in the production and retail chain. These findings contribute to regional surveillance data on L. monocytogenes in smoked fish products in Poland. Full article

Glycosylation is one of the most prevalent post-translational modifications of membrane proteins and plays a central role in regulating their structure and function. Unlike many existing reviews that address glycosylation in a system-wide context, this review focuses specifically on membrane proteins and examines how glycosylation shapes their functional behavior and clinical relevance. Because membrane proteins are exposed to the extracellular environment, glycans on their surface directly influence protein folding, receptor organization, and interactions with ligands and immune components. These diverse effects can be understood within a common mechanistic framework in which glycosylation modulates protein conformation, receptor clustering, and membrane organization, thereby altering signaling, adhesion, transport, and immune recognition. We discuss how N-linked and O-linked glycosylation regulate major classes of membrane proteins across these processes. Particular attention is given to disease-associated alterations in glycosylation, especially in cancer, immune and inflammatory disorders, and metabolic disease. For instance, glycosylation-dependent stabilization of PD-L1 and modulation of receptor signaling, such as EGFR, illustrate how glycan modifications contribute to immune evasion and therapeutic response. We further consider the clinical implications of membrane protein glycosylation, including its roles in biomarker development and as a potential target for therapeutic intervention. Advances in glycoproteomic technologies have enabled increasingly detailed characterization of site-specific glycosylation, although significant analytical challenges remain, particularly for membrane proteins. Overall, this review highlights membrane protein glycosylation as a dynamic regulatory layer that links molecular mechanisms to functional outcomes and clinical applications. Full article

Background: Fruit texture is a major component of plum quality, affecting both consumer acceptance and postharvest behavior. Pectin methylesterases (PMEs) play important roles in cell-wall pectin modification and are therefore likely to contribute to plum fruit texture development and ripening-associated softening. However, the PME gene family has not yet been comprehensively investigated in plum (Prunus salicina L.). Methods: In the present study, a chromosome-level plum genome was used to survey this gene family at the whole-genome scale. Phylogenetic relationships, chromosomal positions, exon–intron organization, conserved motifs, domain architectures, gene duplication, and cis-elements were analyzed. Four flesh texture traits were measured in 55 plum accessions to characterize texture variation and select two representative cultivars with contrasting flesh textures for further molecular analysis. Based on the clustering results, ‘WSCL’ and ‘FR’ were selected for expression profiling during fruit development and subsequent correlation analysis with texture traits. Results: A total of 46 PsPME genes were identified. Phylogenetic analysis classified them into four major subgroups. Structural analyses indicated an overall conserved family framework, although noticeable variation was retained among individual members. Dispersed duplication made the largest contribution to family expansion, and most duplicated pairs appeared to have evolved under purifying selection. Correlation analysis showed that PsPME20, PsPME22, and PsPME25 were significantly negatively correlated with flesh firmness, while PsPME20 was additionally linked to flesh compactness and flesh fragility. Conclusions: Overall, this study clarifies the structural and evolutionary characteristics of the PsPME family and identifies candidate genes that may contribute to texture differences in plum, offering a basis for future functional studies and breeding programs. Full article

Background: Postoperative neurocognitive disorders (PND) are frequent complications in the elderly surgical patients, with aging recognized as a major risk factor. This study aimed to identify electrophysiological markers and establish an exploratory machine learning framework for PND-related vulnerability prediction using anesthetic electroencephalography (EEG) features in aged mice. Methods: Young and aged mice underwent laparotomy under isoflurane anesthesia with EEG recording. Neurocognitive performance was quantified by 16 standardized behavioral fractions. A semi-supervised K-means algorithm, anchored on young-surgery mice, stratified aged-surgery mice into PND and non-PND clusters. EEG dynamics during anesthesia maintenance and emergence were analyzed, and machine learning models were trained to predict PND from EEG features. Results: At baseline, neurocognitive function was comparable across groups. After anesthesia/surgery, aged mice exhibited selective spatial and contextual memory impairments, with two-thirds classified as PND. During emergence, PND mice displayed elevated δ power and reduced α and β ratios. A Multi-layer Perceptron classifier showed discriminatory performance for PND classification in one evaluation setting (AUC = 0.94). Conclusions: This study identifies emergence-related EEG features associated with postoperative neurocognitive vulnerability in aged mice and provides an exploratory machine learning framework for preclinical risk stratification. These findings support further mechanistic investigation and warrant future validation in human perioperative EEG datasets. Full article