Search Results (12,733)

Sustainable groundwater management is essential for water security and human health protection. Fluoride contamination is a serious concern for the sustainable drinking water supply in many parts of Pakistan, including Balochistan, where arid climate conditions and geological formations support the enrichment of fluoride. The toxic nature of fluoride contamination has resulted in negative health impacts on the local population. Conventional geostatistical techniques are usually ineffective to delineate the nonlinear relationships that affect the distribution of fluoride. This study aims to develop a machine learning-driven spatial modelling framework for classifying the spatial distribution of fluoride contamination in groundwater across the study area. The model will help to understand the spatial variability of fluoride contamination and its controlling factors, essential for effective mitigation and early warning systems. Physiochemical elements were used as predictive features in this study, utilizing a unified feature importance framework combining hydrogeochemical analysis, spatial distribution assessment, and ensemble SHAP-based interpretation to identify consistent predictors. Model performance was evaluated using a nested cross-validation framework, followed by validation on an independent geology-informed spatial holdout test set to ensure realistic generalization. Among machine learning models, the Logistic Regression (LR), Support Vector Classifier (SVC), XGBoost (XGB), Decision Tree (DT), Gaussian Naïve Bayes (GNB), and K-Nearest Neighbours (KNN) were evaluated. Support Vector Classifier (SVC) demonstrated a high predictive performance. On the independent spatial holdout dataset, SVC achieved an overall accuracy of 0.75 and an area under the receiver operating characteristic curve (AUC) of 0.821. In addition to classification, a human health risk assessment was conducted using chronic daily intake (CDI) and hazard quotient (HQ) calculations for children and adults, identifying several high-risk water supply schemes. The prediction maps successfully delineated high-risk fluoride points across specific areas, offering a tool for sustainable groundwater management. This study helps to achieve a Sustainable Development Goal (Clean Water and Sanitation, SDG#6) and promotes long-term sustainable planning in water-stressed areas by integrating spatial machine learning mapping and health risk assessment. Full article

Background: Gastrointestinal (GI) cancers remain a major global health concern, where timely and accurate interpretation of endoscopic findings plays a decisive role in patient outcomes. In recent years, deep learning–based decision support systems have shown considerable potential in assisting GI diagnosis; however, their broader adoption is often limited by patient privacy regulations, uneven data availability, and the fragmented nature of clinical data across institutions. Federated learning (FL) offers a practical solution by enabling collaborative model training while keeping patient data local to each hospital. Methods: Vision Transformers (ViTs) are particularly well suited for endoscopic image analysis due to their ability to capture long-range contextual information. Nevertheless, their high computational and communication costs pose a significant challenge in federated settings, especially when data distributions vary across clients. To address this issue, we propose a privacy-preserving federated framework that combines ViTs with a Clinical-Entropy Guided Quantum Evolutionary Algorithm (CEQEA) for adaptive token pruning. The CEQEA leverages the diagnostic diversity of each client’s local dataset to guide population initialization, evolutionary updates, and mutation strength, allowing the pruning strategy to adapt naturally to different clinical profiles. Results: The proposed framework was evaluated on curated upper- and lower-GI tract subsets of the HyperKVASIR dataset under realistic non-IID federated conditions. On the final test sets, the model achieved a mean micro-averaged accuracy of 92.33% for lower-GI classification and 90.19% for upper-GI classification, while maintaining high specificity across all diagnostic classes. At the same time, the adaptive pruning strategy reduced the number of tokens processed by approximately 40% and decreased the number of required federated communication rounds by 33% compared to ViT-based federated baselines. Conclusions: Overall, these results indicate that entropy-aware, quantum-inspired evolutionary optimization can effectively balance diagnostic performance and efficiency, making transformer-based models more practical for privacy-preserving, multi-institutional gastrointestinal endoscopy. Full article

The coronavirus disease 19 pandemic disrupted pediatric respiratory infections through non-pharmaceutical interventions and altered contact patterns. Long-term comparisons across the pandemic timeline in children remain limited. In this study, we analyzed 15,657 respiratory specimens from patients ≤ 18 years at Dankook University Hospital (2007–2023) using multiplex polymerase chain reaction assays targeting 15 viruses. Age-stratified positivity rates were compared across pandemic phases. Children ≤ 6 years comprised 88.61% of the study population. Human rhinovirus showed the highest detection rate (24.06%), followed by adenovirus (12.33%), respiratory syncytial virus-subtypes A and B (RSV-A: 11.13%; RSV-B: 8.65%), human parainfluenza virus-type 3 (HPIV-3; 6.21%), human metapneumovirus (HMPV; 5.33%), and enterovirus (2018–2023; EV; 10.96%). Monthly distributions differed (p < 0.001). RSV peaked in late autumn and winter; influenza and seasonal coronaviruses in winter and spring; HMPV, HPIV-3, EV, and human bocavirus in summer and fall. Positivity declined during the pandemic, rebounding in 2023, most prominently among children aged 1–6 years (84.91%). HPIV-3 and EV increased (p < 0.001). RSV-A predominated pre-pandemic, whereas RSV-B showed a non-significant relative increase post-pandemic; no subtype differences occurred during the pandemic. Findings demonstrate pathogen-specific shifts in predominance and seasonality and support ongoing surveillance and pediatric care planning. Full article

The Early Cretaceous Hongshanwan landform in the Lanzhou Basin hosts distinctive multicolored rhythmic sedimentary layers, yet the factors controlling their coloration remain debated. This study integrates mineralogical observations, whole-rock geochemistry, and detrital zircon U-Pb geochronology to investigate the controls on sediment coloration and basin evolution. Sharp and stratigraphically consistent color boundaries indicate that coloration was largely established during sedimentation and early diagenesis, with limited influence from late-stage weathering. Geochemical data suggest that the sediments were predominantly derived from intermediate-to-mafic igneous rocks under low-to-moderate chemical weathering and dominantly oxidizing conditions. Reddish-brown strata are mainly colored by fine-grained authigenic hematite formed during early diagenesis, whereas bluish-gray and pale-yellow layers inherit their colors from calcareous and mafic components with limited post-depositional alteration. Detrital zircon age distributions reveal three principal age populations (1322–1994 Ma, 331–376 Ma and 217–286 Ma), providing first-order constraints on provenance evolution and episodic sediment supply linked to multiple orogenic cycles in a back-arc foreland basin setting. Overall, the multicolored stratigraphy reflects a coupled influence of provenance composition, depositional redox state, diagenetic processes, and tectonic forcing, offering new insights into the origin and evolution of continental red-bed systems in inland basins of northern China. Full article

Tuberculosis (TB) remains a major public health challenge in Peru, where interindividual variability in treatment response and drug-induced hepatotoxicity may be influenced by host genetic background. This study aimed to characterize clinically relevant polymorphisms in NAT2, CYP2E1, and SLCO1B1 in a cohort of TB patients from Southern Peru, a genetically underrepresented Andean population. Thirty-five adults receiving first-line therapy (isoniazid and rifampicin) underwent targeted Sanger sequencing of key functional variants among these three genes. NAT2 acetylator phenotypes were predominantly intermediate (68.6%), followed by rapid (20%) and slow (11.4%) profiles, with high minor allele frequencies for rs1041983 and rs1801280. CYP2E1 functional promoter variants were infrequent, whereas SLCO1B1 exhibited notable allelic heterogeneity, suggesting potential variability in rifampicin transport. Comparative analysis with previously reported Peruvian data revealed regional differences in acetylator distribution, supporting population-specific pharmacogenomic stratification. Although clinical toxicity outcomes were not evaluated, the high prevalence of reduced acetylation genotypes suggests a substantial proportion of patients may benefit from genotype-informed isoniazid dosing strategies. These findings provide foundational data for implementing precision medicine approaches using affordable and targeted technologies in TB management within Andean populations and support the integration of pharmacogenomics into national TB control programs. Full article

This study aimed to establish normative in-shoe plantar foot temperature patterns across three static postures—lying, sitting, and standing—in healthy individuals, providing a clinically relevant baseline for interpreting in-shoe thermograms in diabetic or peripheral arterial disease (PAD) populations. A single-center prospective study included 20 healthy adults (40 limbs; 22–74 years) who underwent vascular and neurological screening prior to data collection. Plantar temperature was continuously recorded using Tarsos^® Smart Insoles with 21 embedded sensors per foot during three consecutive 10 min phases: supine, sitting, and standing. Data were analyzed for regional differences across the toes, metatarsals, arch, and heel using statistical and visual methods. Distinct posture-related temperature patterns were observed. The arch consistently exhibited the highest temperatures, while the toes remained cooler across all phases. Supine positioning resulted in relatively uniform temperature increases, whereas sitting and standing demonstrated more-stable but region-specific patterns, with slower rates of temperature change and more pronounced regional variation. Compared with barefoot thermography, the in-shoe condition showed greater heat retention and reduced evaporative cooling, highlighting the importance of context-specific baseline data. These findings demonstrate the influence of posture on plantar thermal distribution in the in-shoe environment and support the use of embedded monitoring systems for continuous assessment where surface thermography is not feasible. Full article

Background: Klebsiella pneumoniae is a Gram-negative bacterium that is found in human microbiota and in diverse environments. This opportunistic pathogen exhibits a highly variable genetic background and is responsible for a broad range of hospital- and community-acquired, multidrug-resistant infections worldwide. To track transmission pathways and understand genetic diversity, single-nucleotide polymorphism (SNP) clustering has become an essential tool. Methods: This study examines data from 2018 to 2024 in the NCBI Pathogen Detection database to determine the temporal and spatial distribution of SNP clusters in clinical K. pneumoniae across Middle East and North Africa (MENA) countries. Results: Among 1858 isolates, a heterogeneous population structure was observed. Of the 478 identified SNP clusters, a few dominant clusters accounted for 37% of the isolates, and numerous low-frequency lineages were detected. The descriptive yearly snapshot revealed a diverse representation of top clusters. Geographical analysis showed the presence of both localized and limited cross-border distribution patterns. Countries with diverse clusters also exhibit higher diversity of carbapenem- and ESBL-resistant genes. Conclusions: These findings provide valuable insights into the dominant, regionally concentrated K. pneumoniae lineage across MENA countries, assisting future genomic surveillance and efforts to combat clinical K. pneumoniae infections in this region. Full article

Hopea celebica Burck is an endangered dipterocarp endemic to Sulawesi, Indonesia, occurring in two ecologically contrasting habitats: karst and ultrabasic forests. These environments differ markedly in soil composition and topography, potentially driving ecological specialization and genetic divergence. To investigate the genetic variation and genetic structure of this species, we applied newly developed microsatellite (SSR) markers, together with the chloroplast DNA sequences of the trnL–trnF region. Genotypes at 15 SSR loci were determined for 255 individuals collected from six populations covering the range of the species’ distribution across karst and ultrabasic forests. Genetic diversity was consistently higher in karst than in ultrabasic populations. DIYABC and VarEff analyses revealed a historical bottleneck and earlier recovery in the karst populations. Analysis of molecular variance (AMOVA) revealed that 35% of the genetic variation was partitioned between habitat types (F_RT = 0.345, p = 0.001). Bayesian clustering (STRUCTURE), principal coordinate analysis (PCoA), and UPGMA dendrograms consistently showed two distinctive clusters corresponding to habitat type. Chloroplast haplotypes differed between populations in the karst and ultrabasic forests. These results suggest that populations in the karst and ultrabasic forests have undergone a long history of differentiation without migration. The strong habitat-related genetic structure likely reflects ecological isolation and early-stage speciation. We recommend treating the karst and ultrabasic populations as distinct conservation units to preserve the evolutionary potential and adaptive capacity of H. celebica under ongoing environmental change. Full article

Background/Objectives: Retinoblastoma represents the most common intraocular malignancy in childhood; however, the clinical applicability of mitomycin C (MMC) is restricted by dose-dependent ocular toxicity. Consequently, the development of pharmacological strategies that sensitize tumor cells to MMC while allowing dose reduction remains an unmet therapeutic objective. In this context, quercetin, a bioactive flavonoid with pleiotropic anticancer properties, has emerged as a potential chemosensitizing agent. Methods: Human retinoblastoma cell lines Y79 and WERI-Rb1 were exposed to MMC and quercetin, administered either individually or in fixed-ratio combinations. Cytotoxic responses were quantified through dose–response modeling and IC₅₀ determination following 24 and 48 h of treatment. Drug–drug interactions were quantitatively characterized using the Chou–Talalay combination index (CI) approach and isobologram analysis. Cell cycle distribution was assessed by propidium iodide (PI)-based flow cytometric analysis to evaluate treatment-associated alterations in cell cycle progression. Apoptotic cell death was assessed by Annexin V-FITC/PI flow cytometry, while transcriptional modulation of genes associated with apoptosis, cell cycle regulation, and oxidative stress (BAX, BCL-2, TP53, CASP3, CDKN1A, and HMOX1) was evaluated by qRT-PCR. Modulation of tumor-supportive signaling was examined by measuring VEGF and IL-6 secretion. Translational relevance was further investigated using a three-dimensional (3D) tumor spheroid model, and the functional contribution of reactive oxygen species (ROS) was interrogated through N-acetyl-L-cysteine (NAC) rescue experiments. Results: Quercetin significantly enhanced the cytotoxic activity of MMC in both retinoblastoma cell lines, with CI values below 1 across IC₅₀–IC₉₀ effect levels, indicating a synergistic pharmacological interaction. PI–FACS analysis revealed that combined MMC and quercetin treatment induced a pronounced accumulation of cells in the G2/M phase, consistent with cell cycle arrest, with a more marked effect observed in Y79 cells compared with WERI-Rb1 cells. Combination treatment resulted in a pronounced increase in apoptotic cell populations compared with single-agent exposure and triggered a coordinated pro-apoptotic transcriptional response, characterized by increased expression of BAX, TP53, CASP3, CDKN1A, and HMOX1, alongside suppression of BCL-2 and a marked shift in the BAX/BCL-2 ratio. Concurrently, VEGF and IL-6 secretion were significantly reduced, reflecting attenuation of pro-angiogenic and pro-inflammatory signaling. Notably, synergistic cytotoxicity was maintained in 3D tumor spheroids, where combined treatment induced spheroid shrinkage, architectural disruption, and reduced viability. NAC pretreatment diminished ROS accumulation and partially restored cell viability, indicating that oxidative stress contributes to, but does not solely account for, the observed synergistic cytotoxic effect. Conclusions: Collectively, these findings indicate that quercetin appears to function as an effective chemosensitizing adjuvant to MMC in retinoblastoma models, through transcriptional changes consistent with p53-associated apoptotic signaling at the transcriptional level, G2/M cell cycle arrest, and partial involvement of ROS-related cellular stress responses, along with suppression of tumor-supportive signaling pathways. The preservation of synergistic activity in 3D tumor spheroids supports the potential preclinical relevance of this combination. However, these findings are based on transcriptional and phenotypic analyses and should be interpreted as hypothesis-generating, requiring further validation through protein-level and in vivo studies before translational application. Full article

With the continuous renewal of urban greening, pollen released by allergenic tree species has become a prominent environmental issue affecting residents’ health. However, existing research still lacks city-wide, rapidly replicable methods for identifying allergenic tree species and assessing exposure risks. Taking Beijing’s central urban districts as a case study, this research establishes a method for the automated identification of allergenic tree species and the assessment of pollen exposure risks based on high-resolution satellite imagery. This study coupled tree species distribution results derived from model inference with population density per unit area to delineate three tiers of exposure risk zones. Subsequently, these risk zones were overlaid with the road network within the study area to determine the distribution of roads with low, medium, and high exposure risk. Public transport stop locations were then introduced as a proxy variable for areas of high population mobility. Lorenz curves and Gini coefficients were calculated to quantify the spatial equity of pollen exposure risk. The results indicate that the model reliably identifies target tree species, with approximately 117,000 valid targets. Exposure risks exhibit significant clustering characteristics and can form continuous expansions along road networks. Incorporating population factors shows minimal change in risk concentration, suggesting pollen exposure risk is primarily driven by the spatial clustering of allergenic tree species and their accessibility within road networks. This risk is highly correlated with the spatial distribution patterns and accessibility characteristics of allergenic tree species, rather than being solely determined by population size. This study provides foundational data and methodological support for urban tree species identification, pollen exposure risk management, and optimised greening configurations. Full article

Postural balance is a foundational component of human motor behavior, yet it remains conceptually ambiguous and methodologically heterogeneous across the clinical, educational, and sport sciences. This narrative review aims to provide an integrative framework that clarifies key concepts (postural control vs. postural balance), synthesizes the main sensorimotor and biomechanical mechanisms underpinning balance, and organizes current assessment approaches and functional implications across populations. Narrative literature synthesis was conducted to integrate evidence covering multisensory integration and sensory reweighting, central neural control (spinal, brainstem, cerebellar, and cortical contributions), neuromuscular and biomechanical strategies (e.g., ankle/hip/stepping), and cognitive influences (e.g., dual-task effects). We further summarize commonly used instrumental outcomes derived from force-platform center-of-pressure metrics and widely adopted clinical and functional balance tests, highlighting their typical applications and limitations across the lifespan including pediatric, general adults, older adults, and athletic populations. This review proposes a closed-loop, systems-based model in which postural balance is conceptualized as an emergent functional outcome arising from distributed postural control processes shaped by task, environmental, and individual constraints. In conclusion, integrating mechanistic understanding with population-specific assessment enhances interpretability and supports more precise, context-sensitive balance evaluation and intervention in both health and performance settings. Full article

Perilla frutescens(L.) Britt. (P. frutescens) is an important medicinal and aromatic plant, whose leaf color and chemotype strongly influence its medicinal quality and economic value. All the previously discovered perillene (PL)-type P. frutescens are double-sided green, and whether the PL-type trait is tightly linked with the green-leaf trait in genetics remains to be clarified. This study aimed to address this question and attempt to create purple-leaf PL-type germplasm through perillaldehyde (PA) × PL hybridization. Three parallel experiments were conducted using purple-leaf PA-type P. frutescens as male parents and green-leaf PL-type P. frutescens as female parents. Chemotypes were identified by gas chromatography (GC). Association analyses between leaf color and chemotype were performed in segregating F₂ populations. Genes involved in leaf color formation and PL biosynthesis were mapped onto the published Hoko-3 reference genome to provide genomic evidence for the genetic relationship between the two traits. All F₁ individuals were uniformly PA-type. The three F₂ populations exhibited distinct leaf color–chemotype association patterns: Z01 (n = 118) showed a strong association (Fisher’s exact p = 9.13 × 10⁻¹⁰; φ = 0.564), Z02 (n = 117) showed no detectable association (p = 0.9; φ = 0.012), and Z03 (n = 88) showed a moderate association (p = 0.00669; φ = 0.289). Importantly, purple-leaf PL-type recombinants were obtained in F₂ populations and stably maintained through subsequent generations (F₃–F₅), demonstrating that the PL-type trait is not tightly linked with the green-leaf trait in P. frutescens. Genomic mapping genes related to leaf color and PL biosynthesis are distributed across multiple chromosomes and usually present as multiple loci, which is consistent with the pattern of incomplete linkage. The PL-type trait is recessive and not genetically tightly linked to the green-leaf traits in P. frutescens. The successful creation of a purple-leaf PL-type germplasm breaks the historical phenotypic constraint and provides a novel material for further dissection of the molecular mechanisms regulating secondary metabolism and organ coloration in P. frutescens. Full article

In this study, we investigated the long-term evolutionary dynamics of human norovirus GII.17[P17] using the RNA-dependent RNA polymerase (RdRp) region and the VP1 capsid gene, integrating phylogenetics, time-scaled inference, phylodynamics, and structure-based analyses. Maximum-likelihood phylogenies of both genomic regions consistently resolved four major clades (Clades 1–4). VP1 patristic-distance distributions indicated higher within-clade diversity in the phylogenetically basal Clades 1 and 3, whereas Clades 2 and 4 showed lower diversity, consistent with recent demographic expansion. Similarity-plot analysis identified pronounced variability in the VP1 P2 domain, while the S and P1 domains remained comparatively conserved, supporting P2 as the primary hotspot of diversification. Bayesian time-scaled analyses estimated the most recent common ancestor around 1993 (VP1) and 2000 (RdRp) and revealed two major lineages (Clade 1/2 and Clade 3/4), with the split between Clades 3 and 4 occurring around 2016–2017. Bayesian skyline plots showed a marked increase in effective population size after 2013, and substitution-rate estimates indicated faster evolution in VP1 than in RdRp, with higher VP1 rates in the Clade 3/4 lineage than in Clade 1/2. Capsid dimer modeling further mapped high-confidence conformational B-cell epitopes and positively selected residues predominantly to the distal surface of P2, with broadly conserved spatial patterns across clades. Compared with the Clade 1 reference (Kawasaki323), Clade 2 accumulated numerous P2 substitutions, whereas Clades 3 and 4 retained fewer changes and remained closer to Clade 1 at the amino-acid level. Together, these results suggest lineage turnover within GII.17[P17] driven by constrained diversification at the P2 surface, potentially contributing to the recent predominance of the Clade 3/4 lineage. Full article

Urban green spaces (UGSs) provide critical ecosystem services (ESs) in rapidly urbanising cities but are increasingly threatened by land-use change, population growth, and socio-economic pressures. This study assessed spatial and temporal changes in UGS in Zomba City, Malawi, from 1998 to 2021 using geospatial and remote sensing methods. Landsat imagery from 1998, 2007, 2013, and 2021 was analysed through post-classification change detection to map land-use/land-cover (LULC) transitions, while the relationship between ward-level population density and vegetation condition was evaluated using the Normalised Difference Vegetation Index (NDVI). Results show a decline in total UGS cover from 60% in 1998 to 51% in 2021, primarily due to the expansion of built-up areas. Tree cover increased from 11% to 18%, with NDVI values rising from 0.700 to 0.947; these changes may reflect both natural vegetation growth and targeted restoration, indicating localised improvements in vegetation condition. An inverse relationship was observed between population density and NDVI, though some high-density wards exhibited NDVI gains associated with restoration initiatives. These findings underscore the role of both institutional and community efforts in sustaining urban vegetation and highlight the potential of ecological restoration to mitigate UGS loss and support ESs. Policymakers and planners should prioritise the protection, restoration, and equitable distribution of UGS, particularly in dense and underserved areas, as strategic urban greening enhances city resilience and human well-being. Full article

Exit location can influence evacuation efficiency without changing the number of exits, yet its mechanism lacks quantitative characterization. Using a complex single-floor hospital outpatient department floor plan with 186 occupants as the case study, based on a direction-aware cellular automaton (CA) model, this study constructed two exit layout scenarios within the same complex building floor plan and independently repeated 50 simulations for each scenario under identical occupant population and model parameters. A mechanism-oriented analysis was conducted from the perspectives of evacuation efficiency, structural fairness, behavioral fairness, and structure–behavior deviation. The results showed that, in this case, exit relocation shortened the total evacuation time by approximately 20% ($p<0.001$) and significantly reduced the concentration of exit utilization, whereas the service area distribution changed only slightly, and local peak density did not increase significantly. This indicates that exit location improves evacuation efficiency by restructuring the crowd-splitting structure rather than by a simple balancing of structural service coverage. This study provides quantitative evidence for performance-based evacuation design and sustainable safety optimization in complex spaces. Full article