Search Results (1,060)

Illegal logging is a major threat to tropical forests; however, control mechanisms and efforts to combat illegal logging have not effectively curbed fraud in the production chain, highlighting the need for effective methods to verify the geographic origin of timber. This study investigates the application of multi-elemental analysis combined with Principal Component Analysis (PCA) to discriminate the provenance of tropical timber in the Brazilian Legal Amazon. Wood samples of Hymenaea courbaril L. (Jatobá), Handroanthus sp. (Ipê), and Manilkara huberi (Ducke) A. Chevalier. (Maçaranduba) were taken from multiple sites. Elemental concentrations were determined via Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and CA was applied to evaluate geographic differentiation. Significant differences in elemental profiles were found among locations, particularly when using the intermediate disk portions (25% to 75%), and especially the average of all five sampled portions, which proved most effective in geographic discrimination of the trunk. Elements such as Ca, Sr, Cr, Cu, Zn, and B were especially important for spatial discrimination. These findings underscore the forensic potential of multi-elemental wood profiling as a tool to support law enforcement and environmental monitoring by providing scientifically grounded evidence of timber origin. Full article

The frequency of specific variants associated with the risk of developing cardiovascular diseases has been extensively studied through genome-wide association studies (GWASs). Differences between populations may be caused by the interaction of several factors, such as environmental and genetic backgrounds. Here, we studied 19 SNPs involved in atherosclerosis (AT) and venous thromboembolism (VTE) risk in the Azorean and mainland Portuguese populations and compared their frequencies with other European, Asian, and African populations. Results revealed that, although there was no difference between Azorean and mainland populations, eight SNPs in ADAMTS7, PCSK9, APOE, and LDLR genes showed significant statistical differences (χ², p < 0.05) when compared with the European population. The multilocus genetic profile (MGP) analysis demonstrated that 7.4% of mainlanders and 11.2% of Azoreans have a high-risk of developing atherosclerosis. The opposite tendency was observed for venous thromboembolism risk, where the mainland population presented a higher risk (6.5%) than the Azorean population (4.1%). Significant differences in VTE-MGP distribution were found among the Azorean geographic groups (p < 0.05), with the Eastern group showing the highest VTE risk. Conversely, for the risk AT-MGP, the Central group shows the highest risk (12.9%). Taken together, the data suggest a risk of developing a cardiovascular disease consistent with the European population. However, the Azorean-specific genetic background and socio-cultural habits (dietary and sedentary) may explain the differences observed, validating the need to assess the allelic and genotypic frequencies between different populations, especially in small geographical locations, such as the Azores archipelago. In conclusion, these findings can improve the prevention, diagnosis, and treatment of high-risk individuals, and contribute to reducing the lifelong burden of cardiovascular diseases in the Azorean population. Full article

Background: Social and financial services are essential for the inclusion and well-being of people with disabilities (PWDs), who often rely on family caregivers to access these systems. In Saudi Arabia, where disability inclusion is a strategic goal under Vision 2030, understanding caregiver experiences is crucial to identifying service gaps and improving accessibility. Objectives: This study aimed to explore caregivers’ perspectives on awareness, perceived barriers, and accessibility of social and financial services for PWDs in Saudi Arabia. The analysis is grounded in Andersen’s Behavioural Model of Health Service Use and the WHO’s International Classification of Functioning, Disability and Health (ICF) framework. Methods: A cross-sectional survey was conducted with 3353 caregivers of PWDs attending specialised day schools. The survey collected data on demographic characteristics, service awareness, utilisation, and perceived obstacles. Exploratory Factor Analysis (EFA) identified latent constructs, and Structural Equation Modelling (SEM) was used to test relationships between awareness, barriers, and accessibility. Results: Findings reveal that over 70% of caregivers lacked awareness of available services, and only about 3% had accessed them. Key challenges included technological barriers, complex procedures, and non-functional or unclear service provider platforms. Both User Barriers and Service Barriers were negatively associated with Awareness and Accessibility. Awareness, in turn, significantly predicted perceived Accessibility. Caregiver demographics, such as age, education, gender, and geographic location, also influenced awareness and service use. Conclusions: There is a pressing need for targeted awareness campaigns, accessible digital service platforms, and simplified service processes tailored to diverse caregiver profiles. Inclusive communication, decentralised outreach, and policy reforms are necessary to enhance service access and promote the societal inclusion of PWDs in alignment with Saudi Arabia’s Vision 2030. Full article

Faba bean (Vicia faba L.), a nutrient-rich legume beneficial to human health, is valued for its high L-3,4-dihydroxyphenylalanine (L-DOPA) and phenolic content. This study investigated phytochemical diversity and bioactivity across 29 Chinese faba bean varieties. Phenolics were profiled using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and quantified via high-performance liquid chromatography (HPLC). Antioxidant capacity was evaluated, including DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid)) radical scavenging activity, and ferric reducing antioxidant power (FRAP), along with α-amylase/α-glucosidase inhibitory effects. Twenty-five phenolics were identified, including L-DOPA (11.96–17.93 mg/g, >70% of total content), seven phenolic acids, and seventeen flavonoids. L-DOPA showed potent enzyme inhibition (IC₅₀ values of 22.45 μM for α-amylase and 16.66 μM for α-glucosidase) but demonstrated limited antioxidant effects. Lincan 13 (Gansu) exhibited the strongest antioxidant activity (DPPH, 16.32 μmol trolox/g; ABTS, 5.85 μmol trolox/g; FRAP, 21.38 mmol Fe²⁺/g), which correlated with it having the highest flavonoid content (40.51 mg rutin/g), while Yican 4 (Yunnan) showed the strongest α-amylase inhibition (43.33%). Correlation analysis confirmed flavonoids as the primary antioxidants, and principal component analysis (PCA) revealed geographical trends (e.g., Jiangsu varieties were particularly phenolic-rich). These findings highlight faba beans’ potential as functional foods and guide genotype selection in targeted breeding programs aimed at enhancing health benefits. Full article

The genus Sonchus (Asteraceae) comprises 98 species, including 17 predominantly herbaceous taxa native to the Mediterranean region. These plants have long been utilized as traditional wild food sources due to their high nutritional value, as they are rich in vitamins A, C, and K, essential minerals, and bioactive compounds with antioxidant and anti-inflammatory properties. This review aims to provide a comprehensive synthesis of the taxonomy, geographic distribution, phytochemical composition, traditional uses, historical significance, and pharmacological properties of Sonchus species. A systematic literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies from 1980 to 2024. Inclusion and exclusion criteria were applied, and methodological quality was assessed using standardized tools. A bibliometric analysis of 440 publications (from 1856 to 2025) reveals evolving research trends, with S. oleraceus, S. arvensis, and S. asper being the most extensively studied species. The review provides detailed taxonomic insights into 17 species and 14 subspecies, emphasizing their ecological adaptations and biogeographical patterns. Additionally, it highlights the cultural and medicinal relevance of Sonchus since antiquity while underscoring the threats posed by environmental degradation and changing dietary habits. Sonchus oleraceus and S. tenerrimus dominate the culinary applications of the genus, likely due to favorable taste, wide accessibility, and longstanding cultural importance. The comprehensive nutritional profile of Sonchus species positions these plants as valuable contributors to dietary diversity and food security. Finally, the study identifies current knowledge gaps and proposes future research directions to support the conservation and sustainable utilization of Sonchus species. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

Geographical origin authentication of agrifood products is essential for ensuring their quality, preventing fraud, and maintaining consumers’ trust. In this study, we used proton nuclear magnetic resonance (¹H NMR) and excitation–emission matrix (EEM) fluorescence spectroscopy combined with chemometric methods for the geographical origin characterization of olive drupes and leaves from different Tuscany subregions, where olive oil production is relevant. Single-block approaches were implemented for individual datasets, using principal component analysis (PCA) for data visualization and Soft Independent Modeling of Class Analogy (SIMCA) for sample classification. ¹H NMR spectroscopy provided detailed metabolomic profiles, identifying key compounds such as polyphenols and organic acids that contribute to geographical differentiation. EEM fluorescence spectroscopy, in combination with Parallel Factor Analysis (PARAFAC), revealed distinctive fluorescence signatures associated with polyphenolic content. A mid-level data fusion strategy, integrating the common dimensions (ComDim) method, was explored to improve the models’ performance. The results demonstrated that both spectroscopic techniques independently provided valuable insights in terms of geographical characterization, while data fusion further improved the model performances, particularly for olive drupes. Notably, this study represents the first attempt to apply EEM fluorescence for the geographical classification of olive drupes and leaves, highlighting its potential as a complementary tool in geographic origin authentication. The integration of advanced spectroscopic and chemometric methods offers a reliable approach for the differentiation of samples from closely related areas at a subregional level. Full article

The history of the rabies virus dates back four millennia, with the virus being considered by many to be the first known transmitted between animals and humans. In Brazil, rabies virus variants associated with terrestrial wild animals, marmosets, and different bat species have been identified. In this study, bat samples from different regions of São Paulo State, in Southeast Brazil, were analyzed to identify their genetic variability and patterns. A total of 51 samples were collected over ten years (1999–2009) and submitted to the immunofluorescent technique using monoclonal antibodies for antigenic profile detection (the diagnostic routine used in Latin American countries) and genetic evolution analysis through maximum likelihood approaches. Three antigenic profiles were detected: one related to the rabies virus maintained by hematophagous bat populations (AgV3), part of the monoclonal antibody panel used, and two other profiles not included in the panel (called NC1 and NC2). These antigenic profiles were genetically distributed in five groups. Group I was related to hematophagous bats (AgV3), Groups II and III were related to insectivorous bats (NC1) and Groups IV and V were also related to insectivorous bats (NC2). The results presented herein show that genetic lineages previously restricted to the northwest region of São Paulo State are now found in other state regions, highlighting the need for a comprehensive genetic study of bat rabies covering geographic and temporal space, through expanded genomic analysis using a standard genomic fragment. Full article

Aiming at the problem of accuracy degradation caused by the mixing of spatiotemporal disturbance patterns in sound speed profile (SSP) inversion using the traditional geographic grid division method, this study proposes an acoustic stability pre-clustering framework that integrates principal component analysis and machine learning clustering. Disturbance mode principal component analysis is first used to extract characteristic parameters, and then a machine learning clustering algorithm is adopted to pre-classify SSP samples according to acoustic stability. The SSP inversion experimental results show that: (1) the SSP samples of the South China Sea can be divided into three clusters of disturbance modes with statistically significant differences. (2) The regression inversion method based on cluster attribution reduces the average error of SSP inversion for data from 2018 to 1.24 m/s, which is more than 50% lower than what can be achieved with the traditional method without pre-clustering. (3) Transmission loss prediction verification shows that the proposed method can produce highly accurate sound field calculations in environmental assessment tasks. The acoustic stability pre-clustering technology proposed in this study provides an innovative solution for the statistical modeling of marine environment parameters by effectively decoupling the mixed effect of SSP spatiotemporal disturbance patterns. Its error control level (<1.5 m/s) is 37% higher than that of the single empirical orthogonal function regression method, showing important potential in underwater acoustic applications in complex marine dynamic environments. Full article

Viticis Fructus (VF), a fruit known for its unique flavor profile and various health benefits, demonstrates substantial quality variations depending on its area of production. Traditional methods of production area verification based on internal compound analysis are hampered by a number of technical limitations. This investigation systematically characterized the cuticular wax composition of VF sample from a diverse variety of production areas. Quantitative analyses were conducted to evaluate the spatial distribution patterns of the wax constituents. Significant regional variations were observed: Anhui sample exhibited the highest total wax content (21.39 μg/cm²), with n-alkanes dominating at 76.67%. High-latitude regions showed elevated triterpenoid acid levels, with maslinic acid (0.53 μg/cm²) and ursolic acid (0.34 μg/cm²) concentrations exceeding those of their low-latitude counterparts by four- and three-fold, respectively. Altitudinal influence manifested in long-chain alcohol accumulation, as triacontanol reached 0.87 μg/cm² in high-altitude sample. Five key biomarkers demonstrated direct quality correlations: eicosanoic acid, n-triacontane, dotriacontanol, β-amyrin, and α-amyrin. This study established three novel origin identification protocols: single-component quantification, multi-component wax profiling, and wax ratio analysis. This work not only reveals the latitudinal dependence of VF wax composition, but also provides a scientific framework for geographical authentication. Our findings advance wax-based quality evaluation methodologies for fruit products, offering practical solutions for production area verification challenges in food raw materials. Full article

The ongoing genetic erosion of natural Prunus armeniaca populations in their native habitats underscores the urgent need for targeted conservation and restoration strategies. This study provides the first comprehensive characterization of P. armeniaca populations in the Almaty region of Kazakhstan, integrating morphological descriptors (46 parameters), molecular markers, geobotanical, and remote sensing analyses. Geobotanical and remote sensing analyses enhanced understanding of accession distribution, geological features, and ecosystem health across sites, while also revealing their vulnerability to various biotic and abiotic threats. Of 111 morphologically classified accessions, 54 were analyzed with 13 simple sequence repeat (SSR) markers and four DNA barcoding regions. Our findings demonstrate the necessity of integrated morphological and molecular analyses to differentiate closely related accessions. Genetic analysis identified 11 distinct populations with high heterozygosity and substantial genetic variability. Eight populations exhibited 100% polymorphism, indicating their potential as sources of adaptive genetic diversity. Cluster analysis grouped populations into three geographic clusters, suggesting limited gene flow across Gorges (features of a mountainous landscape) and greater connectivity within them. These findings underscore the need for site-specific conservation strategies, especially for genetically distinct, isolated populations with unique allelic profiles. This study provides a valuable foundation for prioritizing conservation targets, confirming genetic redundancies, and preserving genetic uniqueness to enhance the efficiency and effectiveness of the future conservation and use of P. armeniaca genetic resources in the region. Full article

Ports in the Baltic Sea region play an integral role in advancing sustainable maritime practices in the area, due to their geographic interconnectedness, economic importance, and sensitivity to environmental challenges. While numerous port sustainability assessment methods exist, most of which are grounded in the Triple Bottom Line (TBL) metric, many tend to emphasise whether specific targets have been met, rather than evaluating port sustainability on a scalar basis. This study explores the sustainability strategies of seven selected ports in five Baltic Sea countries using an innovative qualitative evaluation framework developed by the Swedish Maritime Competence Centre (SMCC). The SMCC model integrates the three core pillars of sustainability-environmental, social, and economic dimensions, while incorporating energy efficiency and digitalisation as critical enablers of modern port operations. The findings reveal significant variation in sustainability performance among the selected ports, shaped by regional contexts, operational profiles, and prior engagement with sustainability initiatives. Also, the results bring into light the most common sustainable practices used in the ports, e.g., LED lightning, onshore power supply, and port information systems. Full article

Olive tree leaf is a phenol-rich, high-potential-value biomass that can be used to formulate food additives and supplements. Leaf phenolic content varies depending on numerous factors, like cultivar, geographical origin, year, and season of harvest. The aim of this research was to evaluate the variations in phenolic profile of four major Tuscan cultivars (Frantoio, Leccio del Corno, Leccino, and Moraiolo) over four different phenological phases and across two years. All 96 olive leaf samples were harvested from trees grown in the same orchard located in Florence. After drying, their phenolic profile was characterized using HPLC-DAD-MS, and the obtained data were processed by ANOVA, GA-LDA, and RF methods. A total of 25 phenolic derivatives were analyzed, with total contents ranging 16,674.0–50,594.3 mg/kg and oleuropein (4570.0–27,547.7 mg/kg) being the predominant compound regardless of cultivar, year, and season of harvest. Oleuropein and hydroxytyrosol glucoside showed inverse proportionality and similar behavior across years in all cultivars, and therefore were highlighted as main phenolic compounds correlated with the seasonal variability in studied cultivars. Interesting behavior was also pointed out for apigenin rutinoside. Application of GA-LDA and RF methods allowed pointing out the excellent performance of leaf phenols in discriminating samples based on cultivar, harvest year, and harvesting season. Full article

Background/Objectives: Lactiplantibacillus plantarum is widely utilized in the fermentation industry and offers potential health benefits. However, large-scale comparative genomic analyses aimed at exploring its metabolic functions and conducting safety assessments are still lacking. Methods: In this study, we performed a comparative genomic analysis of 324 L. plantarum strains sourced from various origins and geographical locations. Results: The results revealed that L. plantarum possesses a total of 2403 core genes, of which 12.3% have an unknown function. The phylogenetic analysis revealed a mixed distribution from various origins, suggesting complex transmission pathways. The metabolic analysis demonstrated that L. plantarum strains can produce several beneficial metabolites, including lysine, acetate, and riboflavin. Furthermore, L. plantarum is highly capable of degrading various carbohydrates and proteins, increasing its adaptability. Further, we profiled the antimicrobial peptides (AMPs) in the genomes of L. plantarum. We identified a widely distributed AMP and its variants, presenting in a total of 280 genomes. In our biosafety assessment of L. plantarum, we identified several antibiotic resistance genes, such as Tet(M), ANT(6)-Ia, and mdeA, which may have potential for horizontal gene transfer within the Lactobacillaceae family. Conclusions: This study provides genomic insights into the genetic diversity, metabolic functions, antimicrobial properties, and biosafety of L. plantarum, underscoring its potential applications in biotechnology and environmental adaptation. Full article

Leymus chinensis (Trin.) Tzvel., a vital native forage grass in northern China for ecological restoration and livestock production, faces severe yield losses and grassland degradation due to rust (Puccinia spp.) infection. Current control strategies, reliant on chemical interventions, are limited by evolving resistance risks and environmental concerns, while rust-resistant breeding remains hindered by insufficient molecular insights. To address this, we systematically evaluated rust resistance in 24 L. chinensis germplasms from diverse geographic origins, identifying six highly resistant (HR) and five extremely susceptible (ES) genotypes. Integrating transcriptomics and metabolomics, we dissected molecular responses to Puccinia infection, focusing on contrasting HR (Lc71) and ES (Lc5) germplasms at 48 h post-inoculation. Transcriptomic analysis revealed 1012 differentially expressed genes (DEGs: 247 upregulated, 765 downregulated), with enrichment in cell wall biosynthesis and photosynthesis pathways but suppression of flavonoid synthesis. Metabolomic profiling identified 287 differentially accumulated metabolites (DAMs: 133 upregulated, 188 downregulated), showing significant downregulation of pterocarpans and flavonoids in HR germplasms, alongside upregulated cutin synthesis-related metabolites. Multi-omics integration uncovered 79 co-enriched pathways, pinpointing critical regulatory networks: (1) In the nucleotide metabolism pathway, genes Lc5Ns011910, Lc1Xm057211, and Lc4Xm043884 exhibited negative cor-relations with metabolites Deoxycytidine and Cytosine. (2) In flavonoid biosynthesis, Lc2Xm054924, Lc4Xm044161, novel.8850, Lc2Ns006303, and Lc7Ns021884 were linked to naringenin and naringenin-7-O-glucoside accumulation. These candidate genes likely orchestrate rust resistance mechanisms in L. chinensis. Our findings advance the molecular understanding of rust resistance and provide actionable targets for breeding resilient germplasms. Full article