Search Results (14,175)

The mountainous regions of southwest China represent one of the world’s most distinctive and sensitive areas. Against the backdrop of rapid urbanization and water conservancy construction, rural landscapes in these regions face challenges such as fragmentation, homogenization, and loss of local distinctiveness. Responding to the initiative of the European Landscape Convention (ELC), this study takes the Longchuan River Basin in Southwest China as a case study, and constructs a rural Landscape Character Assessment (LCA) framework adapted to the multi-level governance system. We established a multi-scale evaluation system covering large scale (county-level), medium scale (township-level), and detailed scale (reservoir area-level). The large scale integrated 6 categories of natural variables, while the medium scale involved 4 categories of natural variables and 4 categories of cultural variables. Using a Principal Component Analysis–Two-Step Clustering coupled method and eCognition software, landscape character types and areas were identified respectively. The results show that 11 landscape character types and 41 landscape character areas were identified at the large scale, and 6 landscape character types and 73 landscape character areas at the medium scale. At the detailed scale, 4 typical reservoir areas were selected for field surveys, which verified the in-depth impact of hydropower construction on landscape characteristics. The study provides a transferable technical pathway and policy recommendations for monitoring and managing rural landscapes in mountainous regions. Supports the long-term sustainability and resilience of rural landscapes in China. Full article

The interplay between TP53 alterations and Wnt/β-catenin signaling in colorectal cancer (CRC) remains unclear regarding mismatch repair (MMR) status, tumor budding (TB), poorly differentiated cluster (PDC), and prognosis. We analyzed 146 resected CRC cases, quantifying p53, Wnt3, and β-CTN indices and assessing MMR by PMS2 and MSH6 immunohistochemistry. p53 overexpression was associated with younger patients, left-sided tumors, nodal metastasis, and advanced stage, whereas wild-type tumors showed more mucinous differentiation. Deficient MMR was enriched among wild-type p53 cases. Principal component analysis identified distinct axes defined by p53, Wnt3, and β-CTN. Despite comparable Wnt3 levels, nuclear β-CTN accumulation was enhanced in tumors with aberrant (overexpression or null) p53 tumors, with increased TB and PDC indices. Low nuclear β-CTN independently predicted recurrence in stage I–III disease and worse overall survival in proficient MMR tumors (HR 3.07 and 2.52; p = 0.03 for both). A composite score integrating p53 binary status (aberrant vs. wild) with Wnt3 and whole β-CTN indices predicted survival beyond stage; each 1-point increase conferred a 2.56- and 1.77-fold higher risk of cancer-specific and overall mortality (p = 0.004 and 0.04). These findings suggest that p53 dysfunction is associated with alterations in Wnt/β-CTN signaling and that integrating signaling markers with staging may improve prognostic assessment in colorectal cancer. Full article

As the European population ages, the sustainability of pension systems faces a trilemma: the structural conflict between achieving benefit adequacy, fiscal stability, and labor market flexibility. This study investigates the primary research hypothesis that these three objectives involve trade-offs under current institutional designs. We examine the structural interrelationships between economic development, population health, and institutional pension characteristics across the EU’s 27 member states. Using cross-sectional data from Eurostat and the OECD from 2023, the study employs a multivariate framework, including Multiple Factor Analysis (MFA) and Principal Component Analysis (PCA), to visualize latent trade-offs. Non-parametric statistical tests were applied to validate structural differences between the Nordic, Continental, Southern, and Central and Eastern European (CEE) welfare regimes. The paper’s central argument is that pension sustainability is less a demographic inevitability and more a path-dependent result of institutional “exit cultures” and regional health-wealth traps. The analysis explains 56.7% of the total variance across two primary dimensions, revealing a persistent east–west divide where GDP per capita and Healthy Life Years (HLYs) at age 65 are strongly coupled. Additionally, the analysis identified a fundamental sustainability trade-off: countries with higher pension expenditures and replacement rates, such as those in the Southern and Continental clusters, have significantly earlier labor market exit ages. Statistical evidence shows that the gender pension gap is the most significant factor in differentiating welfare regimes, with the CEE region showing significantly lower inequality than the Western cluster. Ultimately, the findings contribute to public administration literature by demonstrating that policy interventions must prioritize addressing the culture of early retirement in Western countries and the health-wealth trap in Eastern countries to ensure long-term viability. Full article

Barley remains the fourth most cultivated cereal crop worldwide and is valued for its versatility in malting and brewing, animal feed, human nutrition, and dietary supplements. The identification of genotypes suitable for breeding or specific end-use applications requires multi-environment testing to evaluate agronomic performance, grain quality, and trait stability. In this study, a panel of 50 winter barley genotypes (two-row and six-row) originating from diverse genetic backgrounds was evaluated over three growing seasons (2021–2023) under the environmental conditions of southeastern Romania. Seven traits were analyzed, including three phenological traits (heading time, flowering time and plant height), grain yield, and three quality parameters (thousand-grain weight, protein content, and starch content). Environmental conditions had a strong influence on phenological development and grain yield, whereas grain quality traits showed relatively greater stability, indicating a stronger genetic control. Multivariate analyses (Principal Component Analysis (PCA) and Genotype plus Genotype-by-Environment interaction biplot (GGE biplots)) revealed clear relationships among traits and highlighted contrasting adaptive strategies between the two barley types. In two-row barley, genotypes such as Idra and Sandra combined favorable yield performance with stable grain quality traits and therefore represent promising candidates for breeding programs and large-scale cultivation. In six-row barley, SU-Ellen and LG Zebra showed high productivity and strong starch accumulation, making them valuable genetic resources for yield-oriented breeding, although further improvement in nitrogen use efficiency may be beneficial. The 2022–2023 growing season represented the most restrictive environment, emphasizing the importance of stability under stress conditions. Genotypes located close to the Average Environment Coordination axis (AEC axis) during that season, such as Ametist (six-row) and Lardeya (two-row), may represent promising material for breeding programs targeting drought resilience. Overall, the results expand the phenotypic characterization of winter barley germplasm and identify valuable genetic resources that can support pre-breeding efforts and the development of climate-resilient barley cultivars. Full article

Assessing crop water status during the reproductive development of winter wheat is challenging because soil–plant–atmosphere interactions are strongly influenced by soil physical conditions, and measured soil water content (SWC) does not necessarily reflect plant-accessible water. This study applied an integrated, process-based multisensor approach to evaluate functional crop water status and its relationship to grain yield, combining hyperspectral canopy reflectance, atmospheric observations, in situ SWC, and pedological characterization. Five winter wheat cultivars were monitored at two contrasting pedoclimatic sites in continental Croatia during the 2022/2023 growing season. Hyperspectral canopy reflectance (350–2500 nm) was measured at reproductive stages (BBCH 61–83), and seventeen vegetation indices describing canopy water status, structure, pigments, and senescence were derived. Principal component analysis (PCA) identified location as the dominant source of spectral variability, while cultivar effects were secondary. Although atmospheric conditions were broadly comparable, the sites differed markedly in soil physical properties, resulting in contrasting soil water–air regimes. Despite consistently higher volumetric SWC at one site, hyperspectral indicators revealed lower canopy water status, reduced canopy structure, earlier senescence, and lower grain yield across all cultivars. Water-sensitive indices exploiting near-infrared (700–1300 nm) and shortwave infrared (1300–2400 nm) bands (NDWI, NDMI, NMDI, MSI) consistently indicated greater physiological stress. Conversely, the site with lower SWC but more favorable soil physical conditions exhibited higher values of water- and structure-related indices and achieved higher grain yield, with a mean increase of 669 kg ha⁻¹. The results demonstrate that hyperspectral canopy reflectance captures yield-relevant water stress that cannot be inferred from soil moisture alone, highlighting the importance of multisensor integration for interpreting soil–plant–atmosphere interactions under heterogeneous soil conditions. Full article

7-ketocholesterol (7-KC) is a bioactive oxysterol generated under oxidative stress and may contribute to bone marrow niche reprogramming in acute myeloid leukemia (AML), thereby promoting stress tolerance and therapeutic resistance Bone marrow mesenchymal stromal cells (MSCs) from healthy donors and AML patients were exposed to subtoxic 7-KC concentrations for 24 h. We evaluated the ABC transporters involved in lipid transport, multidrug resistance and membrane microdomain remodeling; Hedgehog pathway proteins; stress–survival signaling; redox balance by glutathione measurements, and mitochondrial function and dynamics, including membrane potential and gene expression of mitochondrial fission and fusion regulators. Results were integrated using principal component analysis (PCA), heatmaps, and correlation-based networks. Multivariate analyses revealed an integrated, lineage-dependent response. Healthy donor MSCs showed greater plasticity of the efflux and microdomain axis and higher oxidative and mitochondrial vulnerability at high 7-KC doses. AML-MSCs exhibited a basal preconditioned state phenotype and preferentially routed the response toward Hedgehog and stress–survival modules, accompanied by glutathione expansion and adaptive mitochondrial remodeling. 7-KC acts as a broad modulator of several MSC functions, linking sterol homeostasis to Hedgehog signaling, stress–survival pathways, redox balance, and mitochondrial remodeling, potentially supporting a pro-survival, more therapy-tolerant leukemic niche. Full article

The objective of this article is to optimise the deposition modes and the content of exothermic additions (EAs) in the core filler in Fe-C-Cr-Ti with Cu additions hardfacing. To achieve this, JMatPro Release 7.0, Sente Software Ltd., 2016 material characterisation software was used to simulate and calculate the equilibrium phase structure and composition of the Fe-C-Cr-Ti-Cu alloy during the welding thermal cycle. A synergistic approach combining the Taguchi–Analysis of Variance (ANOVA)–Factorial design (FD) method with the standard hybrid Taguchi–ANOVA–Principal Component Analysis (PCA)–Grey Relational Analysis (GRA) is used and justified to optimise factors and develop mathematical models for parameters in the L9 orthogonal experimental design. The study examines how the transfers of deoxidisers depend on the content of exothermic additions in the cored wire filler (EA) and the contact tip-to-work distance (CTWD), while the behaviour of carbide formers is influenced by wire feed speed (WFS) and present arc voltage at the power source (U_set). The research specifically investigates the Fe-C-Cr-Ti-Cu system and the role of copper in stabilising austenite. Findings show that high Cu concentrations (7 wt.%) enhance hardenability by 13%, effectively suppressing pearlite transformation and expanding the bainite region. The desired chemical composition of the deposited metal is determined by the distribution of selected factors, as measured by the transfer coefficients of each element. Full article

Uranium mining generates complex multi-element contamination that affects interconnected ecosystem components, posing long-term ecological and sanitary risks; this review places these impacts in a broad environmental context and aims to synthesize current knowledge on the distribution, migration, and accumulation of uranium and associated heavy metals in water, soil, and plants. A structured analysis of international peer-reviewed literature was conducted, focusing on documented pathways of metal release from tailings and waste dumps, geochemical controls on mobility, and biological uptake by vegetation. The reviewed studies consistently show that tailings and disturbed ore-bearing strata act as persistent sources of uranium and heavy metals (e.g., Cd, Pb, Cr, Ni, Zn, Mn, As), which migrate through infiltration, acid mine drainage, and atmospheric dispersion, leading to elevated concentrations in surface and groundwater and long-term accumulation in soils. Soils function as the principal sink controlling metal bioavailability, while vegetation reflects the bioavailable fraction and exhibits pronounced species-specific accumulation patterns. These processes establish an active “soil–water–plant” transfer chain that facilitates entry of contaminants into food webs. The synthesis indicates that combined uranium and heavy metal contamination represents a sustained ecological and public health concern in uranium-mining regions and underscores the need for integrated monitoring of soils, waters, and vegetation, along with quantitative risk assessment and scientifically grounded remediation strategies. Full article

To explore the variation in leaf phenotypic traits and environmental adaptation strategies of Pinus densata in southeastern Xizang, 15 plots were established across five regions—Gongbujiangda County (GB), Bomi County (BM), Bayi District (BY), Milin City (ML), and Lang County (LX)—and 11 leaf traits were measured, including leaf length (LL), width (LD), area (LA), volume (LV), fresh weight (LFW), dry weight (LDW), tissue density (LTD), specific leaf area (SLA), and leaf greenness index (SPAD). Results showed that all traits except LL varied significantly among regions, with moderate variation overall; SPAD exhibited the highest coefficient of variation, while leaf water content was the most stable. Extensive correlations were detected among traits: leaf size and weight traits were positively intercorrelated and all negatively correlated with LTD, and SLA correlated negatively with LTD but positively with SPAD. Principal component analysis and hierarchical clustering further revealed that phenotypic variation aligned with the leaf economic spectrum and grouped the populations into three strategy types. Specifically, GB populations approached the “slow investment–return” end of the spectrum, BY and BM populations the “fast investment–return” end, while ML and LX occupied intermediate positions (transitional strategies), with ML leaning toward the slow end. These findings demonstrate that P. densata in southeastern Xizang has evolved diverse resource use and adaptation strategies through synergistic and trade-off relationships among leaf traits, enabling its persistence in complex high-altitude environments. Full article

Professional basketball entails high physical demands and a complex injury profile in which injury burden and time-loss distribution critically affect player availability. This study explored the association between preseason anthropometric body composition and in-season injury burden in male professional basketball and explored body phenotypes linked to greater injury accumulation. A retrospective longitudinal cohort design was applied using official injury records and standardized ISAK anthropometric assessments collected during preseason. Players from two male professional teams (first team, ACB; second team, LEB Plata) were included. Outcomes were the number of injuries and observed days lost during the season. Associations were assessed using Pearson correlations, principal component analysis (PCA), team-stratified logistic regression, and unsupervised k-means clustering. Injury burden demonstrated a highly skewed distribution, with a small subset of players accounting for a large proportion of total days lost. Preseason adiposity markers showed strong internal coherence, with PCA identifying a dominant component reflecting an adiposity gradient. Higher preseason body fat percentage was associated with a greater likelihood of high injury burden (≥3 injuries/season) in both teams. Clustering revealed two phenotypes: a higher-adiposity, higher-burden profile and a lower-adiposity, lower-burden profile. These exploratory findings suggest that preseason body composition, particularly adiposity, may be related to injury burden in male professional basketball. However, given the limited sample size and exploratory design, the results should be interpreted cautiously and considered hypothesis-generating. Precompetitive body phenotyping may therefore provide preliminary information for identifying players potentially at elevated risk of recurrent injury accumulation and reduced competitive availability. Full article

In order to determine the condition of drinking water sources in Donetsk Region and assess potential threats related to water pollution from mining and industrial wastewater, it is extremely important to monitor surface waters, which should include an assessment of the condition of gydrobionts. Additionally, declining surface water quality in the region contributes to pollution in the coastal waters of the Sea of Azov. This study presents the monitoring results for the southern part of the Kalmius River basin. Analysis of water samples revealed contamination by phenol, sulfates, chlorides, anionic surfactants, iron, elevated water hardness, and significant exceedances of suspended solids and total dissolved solids. The iron concentration at the Kalmius River estuary reached 0.81 mg∙L⁻¹, exceeding the permissible limit by 2.5-fold. Sulfate and total dissolved solids concentrations attained 1673 and 160 mg∙L⁻¹, respectively. Changes in the species composition of phytoplankton were observed in response to variations in iron, manganese, and phenol concentrations in the water. Specifically, elevated iron levels led to increased abundance of the metal-sensitive species Cyclotella meneghiniana Kützing. Principal component analysis of the data revealed a relationship between increased phenol concentrations in the aquatic environment and a mean 20% reduction in phytoplankton cell photosynthetic activity, as well as the influence of manganese ions on cell abundance and photopigment content. Thus, phytoplankton cell fluorescence, alongside shifts in species composition and photosynthetic pigment content, can serve as an additional indicator of surface water pollution by iron and phenol. Full article

Accurately tracing the geographical origin of Zanthoxylum schinifolium Sieb. et Zucc. is important for brand authentication, quality control, and food safety assurance. In this study, the stable isotope ratios (δ¹³C, δ¹⁵N, δ²H, δ¹⁸O) and the contents of 20 elements were analyzed in samples from three major production regions. Significant differences (p < 0.05) were observed in δ¹³C, δ²H, δ¹⁸O and most elemental profiles across origins. Chemometric methods—including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA)—were applied to classify samples by geographical origin. OPLS-DA identified key discriminators (VIP > 1) such as Ca, δ¹³C, Mg, δ²H, B, δ¹⁸O, Cr, Ni, Na, Pb, As, Co, Se, and Zn, achieving a classification accuracy of 96.8%. LDA based on the combined isotope and element datasets showed even higher performance, with an original discrimination rate of 98.4% and a cross-validated rate of 92.8%. The results demonstrate that integrating stable isotope and multi-element fingerprints with supervised classification models provides a reliable and effective approach for verifying the geographical origin of Zanthoxylum schinifolium, supporting its use in traceability systems and fair trade practices. Full article

Seasonal environmental conditions can modulate the chemical composition and biological activity of essential oils from medicinal plants. This study investigated the phytochemical profile, antioxidant potential, cytotoxic activity, and cytoprotective effects of Lippia alba essential oils collected during dry and rainy seasons. Gas chromatography analysis revealed that all samples preserved a citral chemotype. Principal Component Analysis (PCA) confirmed citral as the primary discriminant metabolite, while quantitative seasonal variations were mainly associated with minor oxygenated monoterpenes, particularly geraniol, carvone, and nerolidol. The essential oil obtained during the rainy season (A5T–RS) exhibited significantly higher antioxidant activity, as determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH), reducing power, total antioxidant capacity, and hydrogen peroxide scavenging assays. Intracellular reactive oxygen species (ROS) evaluation using the 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) method demonstrated that both oils reduced oxidative stress in murine fibroblasts—L929, with enhanced cytoprotective effects observed for A5T–RS. Cytotoxicity assays against non-tumor (murine fibroblast-NIH/3T3, L929, Chinese hamster ovary—CHO-K1) and tumor (human cervical carcinoma—HeLa, and human hepatocellular carcinoma—HepG2) cell lines revealed selective antiproliferative activity, with tumor cells displaying greater sensitivity, particularly to the rainy-season oil. These results demonstrate that seasonal metabolomic modulation enhances the biological performance of L. alba essential oil without altering its chemotypic identity, highlighting the importance of environmental factors in the development of bioactive plant-derived products. Full article

Accurate genealogical records are essential in livestock breeding for maintaining genetic diversity, preventing inbreeding, and mapping of economically important traits in beef production. This study aimed to assess parent–offspring relationships within South African Bonsmara and Nguni cattle populations using both traditional pedigree records and genomic data. Hair samples from 119 Nguni and 311 Bonsmara cattle were genotyped using the BovineSNP50 array, and these were imputed to Illumina BovineHD BeadChip using updated SNP coordinates from the assembly genome (ARC—UCSD 1.2). Quality control and data filtering were performed using PLINK v1.9, while relationship inference was conducted using KING v2.2.8 and PLINK v1.9 software for principal component analysis, IBD metrics and Mendelian error-based exclusion. Categories of relatedness through network relationship analysis revealed a predominance of half-sibling relationships in both breeds, with 2317 such relationships identified in Nguni and 1221 in Bonsmara. Inference of parent–offspring pairs showed discrepancies with the recorded pedigrees, with 49 inferred pairs compared to 47 recorded pairs in Nguni, and 62 inferred pairs compared to 75 pairs recorded in Bonsmara. Relationships based on IBD using PLINK with a ‘PI-HAT’ threshold greater than 0.45 revealed unique parent–offspring inferences that differed from those obtained using KING v2.2.8. Phylogenetic network analysis assigned each individual’s genomic origin independent of the pedigree records, supporting the efficiency of SNP data for genetic assignment. These results demonstrated that SNP-based pedigree verification can accurately identify parent–offspring and half-sibling relationships, providing a reliable foundation for recombination analysis and supporting precise trait mapping and informed selection in breeding programs. Full article

Unsaturated polyester resin (UPR)–quartz composites have become increasingly important in structural, sanitary, and architectural applications. However, their manufacturing processes still rely heavily on empirical knowledge. This review compiles recent developments in materials science, curing kinetics, and digital manufacturing, outlining a pathway toward data-driven, adaptive production of quartz-filled thermosets. The chemical and physical fundamentals of UPR polymerization are summarized, including the influence of initiator systems, filler characteristics, and thermal management on network formation. Challenges associated with highly filled formulations—such as viscosity control, dispersion, shrinkage, and exothermic peak prediction—are discussed in detail. Recent advances in digital twins (DTs) and artificial intelligence (AI) are reviewed, demonstrating how physics-based simulations, machine learning models, and hybrid mechanistic–data-driven approaches improve the prediction of rheology, curing behavior, and quality outcomes in thermoset polymer processes. A practical application example demonstrates the prediction of peak time in quartz–UPR composites using Random Forest and Gradient Boosting ensemble models. Two prediction scenarios are evaluated: Scenario A with gel time by Leave-One-Out cross-validation, and Scenario B without gel time, representing post-mixing and pre-process prediction contexts, respectively. Stratified bootstrap augmentation improves Gradient Boosting in both scenarios. Principal component analysis confirms that the curing process is governed by three independent physical dimensions: curing reactivity, thermal environment and resin thermal state. Full article