Search Results (24,056)

Background/Objectives: Clinically node-negative (cN0) neck management in cT1–T2 oral cavity squamous cell carcinoma continues to be a subject of controversy. The eighth edition AJCC has incorporated depth of invasion (DOI) as a significant factor in staging and consideration for possible neck dissection. Establishment of accurate DOI thresholds and their clinical relevance is crucial to maximize oncological outcomes with reduced unnecessary morbidity. Methods: A comprehensive analysis of clinical research assessing elective neck dissection (END) techniques in oral cavity cancers classified by DOI in cT1–T2N0 patients was carried out. The included studies reported occult nodal metastasis rates, overall survival, disease-specific survival, disease-free survival, and regional control. Results: With hazard ratios favoring END for overall survival (HR 0.64; 95% CI 0.45–0.92) and disease-free survival (HR 0.45; 95% CI 0.34–0.59), elective neck dissection provided advantages in both survival and regional control. In a national registry, DOI ≥ 5 mm independently raised the risk of nodal failure (HR 2.099; 95% CI 1.346–3.271), while END enhanced neck control in comparison to observation (HR 1.749; 95% CI 1.141–2.680). With ROC-derived cut-offs like 4.59 mm producing positive predictive values for nodal metastasis up to 41.7%, diagnostic thresholds clustered around 4 mm. Conclusions: Under DOI guidance, elective neck dissection consistently showed oncologic benefit, with practical thresholds convergent around 4 mm for sites in the mixed oral cavity and 3 mm for high-risk subsites. The synthesized results confirmed that DOI is the primary determinant of END when combined with histopathologic and subsite-specific risk factors. Full article

Enterobiasis, caused by the nematode Enterobius vermicularis, remains a widespread public health issue, yet data regarding its genetic structure in Southeast Europe are scarce. This study presents the first molecular and phylogenetic characterization of E. vermicularis isolates from Bulgaria. Between 2022 and 2025, perianal tape test samples were collected from 128 individuals (92.2% of whom were children) with enterobiasis from 17 regions of the country. Molecular identification was performed via nested PCR targeting a 324 bp fragment of the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene, followed by Sanger sequencing. Phylogenetic relationships were analyzed using Maximum Likelihood (IQ-TREE), and population genetic indices were calculated using DnaSP v6. Phylogenetic analysis revealed that all 128 Bulgarian isolates belong to genotype B, clustering closely with sequences from other European and Asian countries. Genetic diversity analysis showed remarkably low variation, with a haplotype diversity (Hd) of 0.1507 ± 0.0416 and a nucleotide diversity (π) of 0.00082 ± 0.00015. Among the 11 identified haplotypes, a single dominant haplotype (Hap_1) accounted for 92.2% of all samples and was distributed across all sampled geographic regions. Tajima’s D was significantly negative (−2.314, < 0.05), suggesting a recent population expansion or purifying selection. The dominance of genotype B and the extremely low genetic diversity suggest a recent introduction or clonal expansion of E. vermicularis in Bulgaria. These findings provide essential baseline data for monitoring transmission dynamics and implementing effective control strategies in the Balkan region. Full article

Fibrosis is a hallmark of the tumor microenvironment in many solid cancers, driving tumor progression, immune evasion, and treatment resistance; however, the molecular and cellular mechanisms underlying fibrogenesis—particularly stromal–immune crosstalk across organs—remain incompletely understood, compounded by organ-specific heterogeneity and a lack of reliable immune-related biomarkers. To address this, we performed an integrative single-cell RNA sequencing (scRNA-seq) analysis of fibrotic tissues from four major organs—liver, lung, heart, and kidney—alongside non-fibrotic controls, applying unsupervised clustering, trajectory inference, cell–cell communication modeling, and gene set variation analysis (GSVA) to map the fibro-immune landscape. Our analysis revealed both conserved and organ-specific features: fibroblasts were the dominant extracellular matrix (ECM)-producing cells in liver and lung, whereas endothelial-derived stromal populations prevailed in heart and kidney. Immune profiling uncovered distinct infiltration patterns—macrophages displayed organ-specific polarization states; T cells were enriched for tissue-resident subsets in lung and mucosal-associated invariant T (MAIT) cells in liver; and B cells exhibited marked heterogeneity, including a pathogenic interferon-responsive subset prominent in pulmonary fibrosis. GSVA further identified divergent signaling programs across organs and lineages, including TGF-β/TNF-α in the heart, NOTCH/mTOR in the kidney, glycolysis/ROS in the lung, and KRAS/interferon pathways in the liver. Cell–cell communication analysis highlighted robust crosstalk between macrophages, T/B cells, and stromal cells mediated by collagen, laminin, and CXCL signaling axes. Together, this cross-organ atlas delineates a highly heterogeneous fibro-immune ecosystem in human fibrotic diseases, revealing shared mechanisms alongside organ-specific regulatory networks, with immediate translational implications for precision anti-fibrotic therapy, immunomodulatory drug repurposing, and the development of context-specific biomarkers for clinical stratification and therapeutic monitoring. Full article

The taxonomic status of Arbutus pavarii Pamp., a rare and geographically restricted species endemic to northeastern Libya, has long been debated, with some treatments considering it a synonym of A. unedo. To resolve this uncertainty, we applied an integrative molecular framework that combined multilocus DNA barcoding, phylogenetic inference, and multivariate statistical analyses. Five barcode loci—nrITS, matK, rbcL, trnH–psbA, and rps16—were analyzed using barcode-gap diagnostics, TaxonDNA identification tests, and single-locus and concatenated phylogenetic analyses. Barcode-gap analyses based on Kimura 2-parameter distances revealed clear and reproducible separation between intra- and interspecific variation for A. pavarii, particularly for nrITS and the concatenated multilocus dataset, whereas conserved plastid loci showed limited discriminatory power when used individually. Phylogenetic reconstructions consistently recovered A. pavarii as a strongly supported monophyletic lineage, distinct from A. unedo and other Mediterranean congeners, with congruent topologies across the nuclear, plastid, and combined datasets. Multivariate analyses, including principal component analysis and heatmap clustering, further corroborate the genetic cohesion and distinctiveness of A. pavarii samples. Collectively, these results provide robust molecular evidence supporting the recognition of Arbutus pavarii as a distinct evolutionary lineage, rather than an intraspecific variant of A. unedo. This study established a reproducible multilocus framework for species delimitation in Arbutus and highlighted the importance of integrating nuclear and plastid markers to resolve complex taxonomic relationships. The clarified taxonomic status of A. pavarii has important implications for biodiversity assessment and conservation planning in the Mediterranean region, particularly in the Cyrenaican floristic province. Full article

Background: Extracellular vesicles (EVs) have emerged as promising cell-free therapeutic agents in regenerative medicine due to their ability to deliver bioactive molecules with enhanced stability and low immunogenicity. Their potential to replicate stem cell functions without the risks of live-cell transplantation has catalyzed a surge in global research. Objective: This study aims to perform a scientometric analysis of EV-based regenerative medicine research from 2014 to 2024, identifying publication trends, influential contributors, thematic clusters, and translational challenges. Methods: Data were retrieved from the Web of Science Core Collection and analyzed using CiteSpace software. The analysis included journal impact mapping, co-authorship networks, co-citation analysis, and thematic cluster identification. Metrics such as citation bursts, total link strength, and silhouette values were used to assess influence and thematic coherence. Results: The most prolific journals were Stem Cell Research & Therapy and International Journal of Molecular Sciences. China led in publication volume, while the USA dominated citation impact. Foundational works by Théry and Lai, including the MISEV guidelines, shaped methodological standards. Nine thematic clusters were identified, including oxidative stress, small EVs, mesenchymal stromal cells, muscle regeneration, and chronic kidney disease. A strategic shift toward engineered EVs and novel sources such as iPSCs and macrophages was evident. Key translational barriers include lack of standardization, scalability issues, and regulatory ambiguity. Conclusions: EV-based therapies are transitioning from foundational research to clinical application. Overcoming methodological and regulatory challenges will be critical to realizing their full therapeutic potential in regenerative medicine. Full article

Background: Apical periodontitis (AP) is a common inflammatory condition of the periapical tissues, most often associated with persistent endodontic infection. Conventional two-dimensional radiography may underestimate AP because of anatomical superimposition and limited sensitivity. Cone-beam computed tomography (CBCT) allows three-dimensional visualization of periapical structures and has been increasingly used in epidemiological research. Objective: This study aimed to evaluate the prevalence and distribution of apical periodontitis, with particular emphasis on apical periodontitis associated with root canal-treated teeth (AP-RCT), in a Saudi subpopulation using CBCT imaging. Methods: This retrospective cross-sectional study analyzed CBCT scans of Saudi patients obtained for routine diagnostic purposes between 2017 and 2021. Apical periodontitis was identified using standardized radiographic criteria requiring the presence of periapical radiolucency in more than one imaging plane. Demographic and clinical variables were recorded. Descriptive statistics were used to estimate prevalence. Associations between demographic factors and AP-RCT counts were evaluated using multivariable negative binomial regression. Regional tooth distribution was analyzed using generalized estimating equation models accounting for within-participant clustering. Results: A total of 320 CBCT scans were analyzed. Apical periodontitis was detected in 231 participants (72.2%) and in 667 teeth (8.3% of examined teeth). Of the affected teeth, 457 (68.5%) were associated with root canal treatment. The mean number of AP-RCT per participant was 1.36 ± 1.81 (median: 1; IQR: 0–2). Multivariable analysis identified age as the only significant predictor of AP-RCT. Compared with individuals aged 21–30 years, higher AP-RCT rates were observed in the 31–40-year and 41–50-year age groups, while participants ≤20 years showed lower rates. Tooth-level analysis demonstrated higher AP-RCT prevalence in maxillary premolars, maxillary molars, and mandibular molars, whereas mandibular anterior teeth showed the lowest prevalence. Conclusions: Apical periodontitis, particularly AP-RCT, was frequently observed in this Saudi subpopulation when assessed using CBCT. Age and tooth location were the primary determinants of disease distribution. These findings provide population-level epidemiological data on the prevalence and anatomical distribution of apical periodontitis in root canal-treated teeth. Clinical Significance: CBCT-based epidemiological assessment enables detailed evaluation of the distribution of apical periodontitis in dentate populations and may assist in characterizing disease patterns in anatomically complex regions, without implying comparative diagnostic accuracy or treatment outcome assessment. Full article

Diagnosis of primary hyperparathyroidism (PHPT) relies on the detection of hypercalcemia and increased circulating parathormone (PTH) levels. However, the disease induces a deep deregulation of phosphate metabolism. A total of 960 PHPT patients (848 females, 112 males) were retrospectively enrolled; biochemical and clinical data were collected at PHPT diagnosis. At variance with previous studies, hypophosphatemia was diagnosed using sex- and age-specific serum phosphate reference range. Reduced serum phosphate levels were detectable in 49% of PHPT males and 55% of PHPT females. Moderate hypophosphatemia (≤2.0 mg/dL) was more frequent in men than in women, and serum phosphate levels were lower in postmenopausal than premenopausal PHPT women. Vitamin D status did not alter the prevalence of hypophosphatemia. Serum phosphate levels negatively correlated with ionized calcium and PTH levels across PHPT premenopausal women, postmenopausal women, and men. Cluster analysis integrating the three interrelated parameters identified three distinct PHPT phenotypes: bone and kidney complications were more frequent in patients with more severe hypercalcemia and hypophosphatemia, though fractures were more abundant in the less severe phenotypes. Finally, considering the whole cohort, ionized calcium and PTH levels displayed a negative non-linear correlation with phosphate levels. In conclusion, hypophosphatemia in PHPT patients is common, and moderate hypophosphatemia is more frequent in males compared to females. Menopausal status is associated with less severe hypophosphatemia and PHPT disease. Hypophosphatemia is mainly determined by parathyroid tumor cells’ dysfunction. The non-linear negative relationships between phosphate, PTH and ionized calcium may suggest heterogeneous insensitivity of tumor parathyroid cells to extracellular phosphate. Full article

River basins are not merely geographical spaces but also cultural-historical ecosystems, where the spatial patterns of Intangible Cultural Heritage (ICH) profoundly reflect the long-term interaction between human and environment, as well as contemporary transformations. While international research on ICH has evolved from conceptual clarification to interdisciplinary theory-building, and spatial quantitative methods have been widely applied to cultural heritage analysis, the spatial patterns, multi-scale structures, and “natural-human” driving mechanisms of ICH in continental arid river basins—particularly in the Tarim River Basin (TRB, China’s largest inland river and a key corridor of the Silk Road)—remain underexplored. To address this gap, this study takes 313 ICH items in the TRB as the research object. It uses ArcGIS 10.8.1 to visualize their spatial distribution and employs an integrated methodology—including global Moran’s I, kernel density estimation (KDE), DBSCAN spatial clustering, and geographical detector (Geodetector)—to systematically reveal their spatial characteristics and influencing factors. The findings indicate that: (1) The distribution of ICH exhibits a multi-scale feature of “global randomness with local clustering”: spatial autocorrelation is not significant at the county level, while at the micro-geographical scale, a dendritic structure characterized by “one axis, three cores, denser in the north and sparser in the south” emerges, which is highly coupled with the river network. DBSCAN clustering further identifies a “mainstem axis–tributary node” cluster system and a relatively high proportion of peripheral “noise” heritage points. (2) Agglomeration patterns vary significantly across different ICH categories, with traditional craftsmanship showing high clustering, while traditional sports, entertainment, and acrobatics display highly fragmented distributions. (3) The study reveals and validates a ternary “Water–Tourism–Urbanization” driving framework that predominantly shapes the spatial heterogeneity of ICH: water resources constitute a fundamental ecological threshold, whereas tourism development and urbanization have emerged as more explanatory social driving forces, with widespread nonlinear enhancement interactions between natural and human factors. This research moves beyond the traditional view of river basins as static cultural “containers,” providing empirical evidence for their dynamic nature as “cultural-ecological co-evolutionary systems.” The proposed ternary framework not only offers a new perspective for understanding the spatial resilience of ICH in arid regions and the potential risks of “spectacularization” and “spatial polarization” amid rapid changes, but also provides a scientific basis for spatial governance, culture-tourism integration, and the formulation of conservation strategies for ICH at the basin scale. Full article

Angular Distribution Models (ADMs) are essential for converting observed radiances from satellite sensors to the energy-budget–relevant quantity of irradiance. In preparation for the NASA Libera mission, this study presents a data-driven framework to identify optimal groupings of International Geosphere–Biosphere Programme (IGBP) surface types for Libera’s split-shortwave ADMs, in an effort to minimize the uncertainty associated with radiance-to-irradiance conversions while maintaining operational feasibility. Using data from the Clouds and the Earth’s Radiant Energy System (CERES) Flight Model 5 (FM-5), K-means clustering is applied within angular bins to capture viewing-geometry-dependent radiometric behavior. These angular clustering solutions are then assessed via hierarchical consensus clustering to derive consistent surface groups. The analysis suggests seven surface groups (K = 7) optimize the surface clustering space. The resulting classifications are broadly consistent with historical CERES–TRMM ADM surface definitions, preserving radiometrically distinct surfaces such as water bodies and snowy surfaces while highlighting opportunities to consolidate vegetative IGBP surface classes. This study provides an objective and physically grounded basis for defining Libera ADM surface groups, ensuring a robust balance between model accuracy and operational simplicity. Full article

Monitoring small water body coverage spatiotemporal evolution in karst areas of complex hydrogeology is pivotal for water resource management and disaster assessment. With recent infrastructure expansion, intensive tunnel excavation has occurred in Chongqing’s Geleshan, a typical karst region with fragile aquifers. It has disrupted hydrogeological systems, triggering ground subsidence, groundwater leakage, and subsequent reservoir desiccation, as well as threatening regional water security and ecology. Thus, monitoring reservoir coverage evolution is critical to clarify dynamics and driving mechanisms. Synthetic Aperture Radar (SAR) is ideal for water body mapping, enabling data acquisition independent of illumination and weather. However, traditional SAR-based water extraction methods are hampered by low-scatter noise and poor adaptability to hydrological fluctuations. To address this, a two-stage dual-polarization SAR clustering algorithm (TSDPS-Clus) was developed using 452 time-series Sentinel-1 images (7 February 2017–24 August 2025). Specifically, the Kolmogorov–Smirnov test via pixel-wise time-series statistics screened core water areas, built candidate regions, and mitigated noise. Subsequently, dual-polarization and positional features were fused via singular value decomposition (SVD) to generate a high-discrimination low-dimensional feature set, followed by the Iterative Self-Organizing Data Analysis Techniques Algorithm (ISODATA) clustering for high-precision extraction. Results demonstrate that the algorithm suits reservoir storage-desiccation dynamics; dual-polarization complementarity boosts accuracy and clarifies six reservoirs’ spatiotemporal evolution. Notably, post-2023, tunnel excavation-induced land subsidence increased drying frequency and duration, with a 24-month maximum cumulative desiccation period. Full article

Drought stress severely compromises the physiological integrity and secondary metabolism of medicinal plants. This study integrated physiological, biochemical, and ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) analyses to investigate the effects of exogenous methyl jasmonate (MeJA) on drought-stressed Ilex rotunda seedlings. Drought reduced relative water content by 29% and chlorophyll by >50%, while elevating H₂O₂ (76%) and malondialdehyde (120%). MeJA application mitigated these impairments, reducing oxidative markers by 25% and enhancing non-enzymatic antioxidant capacity, as shown by a 74% increase in DPPH radical scavenging activity and a 141% rise in total phenolic content. Hierarchical clustering analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA), and pathway mapping confirmed a significant reprogramming of the phenolic metabolome, particularly within phenylpropanoid and benzoate biosynthesis pathways. Drought + MeJA-treated plants exhibited a distinct and enriched profile compared to both well-watered control and drought-stressed groups. This reprogramming specifically elevated key hydroxycinnamates, including verbascoside and neochlorogenic acid (increased by 50% and 52%, respectively), while suppressing alternative phenolic branches. These findings demonstrate that MeJA orchestrates a shift from enzymatic scavenging to a potent metabolite-based antioxidant system, positioning it as an effective elicitor for enhancing drought resilience and enriching the high-value phytochemicals in I. rotunda. Full article

We present a comprehensive study of host galaxies of radio sources within the 1.35$R_{200}$ of the Coma cluster by combining deep $144\mathrm{MHz}$ observations from the LOFAR Two-Metre Sky Survey (LoTSS-DR2) with optical spectroscopy and photometry from DESI and SDSS. We identify 79 spectroscopically confirmed cluster members with reliable radio emission and classify them into compact, extended, and tailed subsamples according to their radio morphologies. By combining their radio and optical properties, we find compact radio sources are predominantly associated with massive, quiescent galaxies driven by $\mathrm{AGN}$ activity, while tailed sources are largely hosted by star-forming galaxies, tracing ongoing ram pressure stripping ($\mathrm{RPS}$). Using phase-space analysis and a projected infall time proxy ($d_R$), we find that extended sources are preferentially located in the cluster outskirts ($d_R>1$), while tailed sources are concentrated in the intermediate infall region ($0.4<d_R<1.0$), highlighting the influence of the dense intracluster medium. Full article

Historic towns serve as vital carriers of both tangible and intangible cultural heritage, preserving unique historical memories. Quantitative analysis of their architectural facades is crucial for scientific conservation and cultural continuity. While existing studies predominantly employ qualitative descriptions or small-sample analyses, a systematic and replicable quantitative methodology remains elusive. To address this gap, this study innovatively proposes an integrated framework combining UAV oblique photogrammetric modeling, multivariate statistics, and spatial time series analysis. This framework aims to establish a methodological system for analyzing the morphological characteristics of building facades in historic districts. The study selected main streets from four ancient towns in the Chengdu Plain—Pingle, Anren, Xinchang, and Yuantong—and performed 3D reconstruction and morphological indicator extraction on 365 contiguous facade samples. Factor analysis was employed to reduce dimensionality, identifying three dimensions influencing facade morphology. Combined with cluster analysis for classification, the study systematically categorized four statistically significant and architecturally meaningful facade types. Furthermore, it quantified the sequential patterns and combination modes of street-facing distributions, providing crucial theoretical support and reference for the preservation, renewal, and sustainable development of ancient towns. Full article

Understanding public stigma against patients (also known as disease stigma)—negative attitudes or discriminatory responses toward individuals with a disease—is essential for improving health outcomes and fostering inclusive communities. In this study, 279 participants rated their responses toward eight disease groups (e.g., HIV/AIDS, COVID-19, and depression). Using multiple factor analysis, we identified three components of disease stigma: exclusionary (e.g., avoidance and harmful evaluation), prosocial (e.g., sympathy and helping), and attribution (blame/responsibility). Confirmatory factor analysis supported this three-component structure. Repeated-measures ANOVAs revealed systematic differences across diseases: COVID-19 and schizophrenia elicited stronger exclusionary responses, depression evoked the strongest prosocial responses, and HIV/AIDS was associated with the highest attribution of blame. Linear mixed-effects models further indicated that perceived cultural tightness was positively associated with the attribution component, self-control was positively associated with the prosocial component, and higher self-esteem was linked to greater exclusionary responses. Furthermore, network analysis showed dense within-component clustering (e.g., trust—negative evaluation; sympathy—helping) and a peripheral positioning of attribution within the stigma network. These findings provide insights into the psychological components of disease stigma and its cultural and personal correlates, providing targets for component-specific stigma reduction strategies. Full article

Background: The human gut microbiota plays a central role in host physiology by influencing digestion, immune function, and metabolism. Characterizing age-associated differences in the organization of microbial metabolism may provide insights into functional variation in the gut microbiome across the human lifespan. Methods: Gut microbiota metabolic organization was analyzed in a cohort of 30 individuals spanning three age groups (infants, adults, and elderly individuals) and comprising 156 stool samples. Community metabolic networks were reconstructed using the metabolic Directed Acyclic Graph (m-DAG) framework derived from KEGG Ortholog annotations. Network topology was characterized to assess whether the resulting networks conform to previously described global structural patterns and to examine age-associated variability. Pairwise m-DAG dissimilarities were computed, and hierarchical clustering was applied to evaluate similarities among samples. Results: All samples revealed a conserved global network organization, alongside marked variability in specific structural features. Hierarchical clustering did not strictly reflect chronological age. A homogeneous cluster composed exclusively of adult samples was identified, whereas elderly samples were distributed across two clusters, one grouping with adults and the other with infants. Exploratory discriminative analyses identified functional reactions contributing to the separation between the adult cluster and the remaining samples, indicating age-associated differences in metabolic network organization. Conclusions: Gut microbiota metabolic networks in adults tend to exhibit lower redundancy and structural complexity, whereas those in infant and elderly samples display more heterogeneous network configurations. This network-based analysis provides a functional perspective on age-associated variation in gut microbiota metabolism and offers a framework for future integrative studies. Full article