Search Results (2,756)

Lance nematodes, Hoplolaimus spp., feed on the roots of many kinds of plants, including agronomic crops. In this study, morphological and molecular analyses of several Hoplolaimus species and populations are provided. We were able to collect and characterize the topotype materials of H. galeatus from Arlington, Virginia; H. stephanus syn. n. from Nichols, South Carolina; and H. concaudajuvencus from Pensacola, Florida, and several additional populations and species from the United States, Israel, and India. Phylogenetic analyses of several hundred sequences of the D2–D3 expansion regions of 28S rRNA, ITS rRNA, and COI genes of Hoplolaimus species obtained from published and original datasets were given. Fifty-three new D2–D3 of 28S rRNA, 43 new ITS rRNA, and 47 new COI sequences from 23 isolates of Hoplolaimus spp. and one isolate of Peltamigratus christiei were obtained in this study. New molecular identities for H. concaudajuvencus and H. galeatus were proposed. Hoplolaimus stephanus syn. n. was considered a synonym of H. galeatus based on the morphological and molecular similarity of these two species. Analysis of morphology and molecular data did not reveal significant differences among H. columbus syn. n., H. indicus syn. n., and H. seinhorsti, and the first two species were synonymized with H. seinhorsti. A new species, H. floridensis sp. n., was described from many locations in Florida, USA. It was separated from other representatives of the genus Hoplolaimus by its morphological and molecular characteristics. Maps with geographical distribution of several lance nematode species in North America were reconstructed based on published and original molecular identification of samples. Full article

Background/Objectives: Diabetic neuropathy (DN) is one of the most common and disabling complications of diabetes mellitus (DM), affecting motor, sensory, and autonomic nerves. Genetic factors, particularly polymorphisms in the Angiotensin-converting enzyme (ACE) gene, have been proposed as contributors to DN susceptibility. This study aimed to synthesize the scientific evidence on ACE gene polymorphisms and their association with DN through a scoping review combined with scientometric analysis. Methods: A comprehensive search of PubMed, Scopus, and Web of Science was performed in February 2025, following JBI and PRISMA-ScR guidelines. Observational studies involving individuals with DN and the genotyping of ACE polymorphisms were included. Scientometric mapping was conducted using the Bibliometrix package in RStudio to identify publication trends and key thematic terms. Results: From 100 screened articles, 11 met the inclusion criteria. Most studies (72.7%) addressed diabetic peripheral neuropathy, while 27.3% investigated cardiac autonomic neuropathy. All studies analyzed the I/D polymorphism in intron 16 of the ACE gene. The D allele and DD genotype were associated with increased susceptibility to DN in over half of the studies (6/11), while the II genotype was reported as protective in 3/11. Findings varied by ethnicity and study design. The scientometric analysis identified ‘peripheral diabetic neuropathy’, type 2 diabetes’, and ‘ACE gene polymorphism’ as the most frequently co-occurring terms, indicating that research on this topic has been concentrated around these themes, while showing limited diversity in geographic origin and scope. Conclusions: ACE I/D polymorphism appears to modulate susceptibility to DN, though interethnic variability and methodological heterogeneity challenge definitive conclusions. Broader, standardized studies are needed to validate its utility as a predictive biomarker. Full article

Surrogate models are widely recognized as effective, data-driven predictive tools for storm surge risk assessment. For such applications, surrogate models (referenced also as emulators or metamodels) are typically developed using existing databases of synthetic storm simulations, and once calibrated can provide fast-to-compute approximations of the storm surge for a variety of downstream analyses. The storm surge predictions need to be established for different geographic locations of interest, typically corresponding to the computational nodes of the original numerical model. A number of inland nodes will remain dry for some of the database storm scenarios, requiring an imputation for them to estimate the so-called pseudo-surge in support of the surrogate model development. Past work has examined the adoption of kNN (k-nearest neighbor) spatial interpolation for this imputation. The enhancement of kNN with hydraulic connectivity information, using the grid or mesh of the original numerical model, was also previously considered. In this enhancement, neighboring nodes are considered connected only if they are connected within the grid. This work revisits the imputation of peak storm surge within a surrogate modeling context and examines three distinct advancements. First, a response-based correlation concept is considered for the hydraulic connectivity, replacing the previous notion of connectivity using the numerical model grid. Second, a Gaussian Process interpolation (GPI) is examined as alternative spatial imputation strategy, integrating a recently established adaptive covariance tapering scheme for accommodating an efficient implementation for large datasets (large number of nodes). Third, a data completion approach is examined for imputation, treating dry instances as missing data and establishing imputation using probabilistic principal component analysis (PPCA). The combination of spatial imputation with PPCA is also examined. In this instance, spatial imputation is first deployed, followed by PPCA for the nodes that were misclassified in the first stage. Misclassification corresponds to the instances for which imputation provides surge estimates higher than ground elevation, creating the illusion that the node is inundated even though the original predictions correspond to the node being dry. In the illustrative case study, different imputation variants established based on the aforementioned advancements are compared, with comparison metrics corresponding to the predictive accuracy of the surrogate models developed using the imputed databases. Results show that incorporating hydraulic connectivity based on response similarity into kNN enhances the predictive performance, that GPI provides a competitive (to kNN) spatial interpolation approach, and that the combination of data completion and spatial interpolation emerges as the recommended approach. Full article

Purpose: This study aimed to investigate the migration and distribution characteristics of trace elements in the soil–tea system in the Cuiya tea area of Meitan County, Guizhou Province. Methods: The contents of trace elements (Cd, Fe, La, Mg, Mn, Ni, Se, Pr, Sm, Zn) in tea and soil samples were determined by inductively coupled plasma emission spectrometry (ICP-OES). Results: The average contents of heavy metals in soil and tea from Meitan County were below the Chinese national standards, while also meeting the criteria for selenium enrichment. Within the soil–tea system, Mn in tea leaves exhibited a significant negative correlation with soil Mn, while Cd showed a significant positive correlation with soil Cd. This pattern was consistent across both the topsoil and subsoil. The tea plants exhibited a high enrichment capacity for Mn, Mg, and Zn, but a low capacity for Sm, Fe, and Cd. Among the studied areas, the enrichment effect was most pronounced in SL, XH, and MJ towns. Conclusions: Significant spatial variations were observed in the concentrations of trace elements in both tea and soil across the Meitan tea area. This study provides a scientific basis for understanding the enrichment and migration of trace elements within the soil–tea system of Meitan County, Guizhou, and for tracing the geographical origin of its tea. Full article

Background: Social determinants of health (SDOH) are critical contributors to cancer disparities, influencing prevention, early detection, treatment access, and survival outcomes. Addressing these disparities is essential in achieving equitable oncology care. Artificial intelligence (AI) is revolutionizing oncology by leveraging advanced computational methods to address SDOH-driven disparities through predictive analytics, data integration, and precision medicine. Methods: This review synthesizes findings from systematic reviews and original research on AI applications in cancer-focused SDOH research. Key methodologies include machine learning (ML), natural language processing (NLP), deep learning-based medical imaging, and explainable AI (XAI). Special emphasis is placed on AI’s ability to analyze large-scale oncology datasets, including electronic health records (EHRs), geographic information systems (GIS), and real-world clinical trial data, to enhance cancer risk stratification, optimize screening programs, and improve resource allocation. Results: AI has demonstrated significant advancements in cancer diagnostics, treatment planning, and survival prediction by integrating SDOH data. AI-driven radiomics and histopathology have enhanced early detection, particularly in underserved populations. Predictive modeling has improved personalized oncology care, enabling stratification based on socioeconomic and environmental factors. However, challenges remain, including AI bias in screening, trial underrepresentation, and treatment recommendation disparities. Conclusions: AI holds substantial potential to reduce cancer disparities by integrating SDOH into risk prediction, screening, and treatment personalization. Ethical deployment, bias mitigation, and robust regulatory frameworks are essential in ensuring fairness in AI-driven oncology. Integrating AI into precision oncology and public health strategies can bridge cancer care gaps, enhance early detection, and improve treatment outcomes for vulnerable populations. Full article

This study presents and evaluates three sampling strategies to characterize electricity demand in regions of Colombia with limited metering infrastructure. These areas lack Advanced Metering Infrastructure (AMI), relying instead on traditional monthly consumption records. The objective of the research is to obtain user samples that are representative of the original population and logistically efficient, in order to support energy planning and decision-making. The analysis draws on five years of historical data from 2020 to 2024. It includes monthly energy consumption, geographic coordinates, customer classification, and population type, covering over 500,000 users across four subregions of operation determined by the region grid operator: North, South, Center, and East. The proposed methodologies are based on Shannon entropy, consumption-based probabilistic sampling, and Kullback–Leibler divergence minimization. Each method is assessed for its ability to capture demand variability, ensure representativeness, and optimize field deployment. Representativeness is evaluated by comparing the differences in class proportions between the sample and the original population, complemented by the Pearson correlation coefficient between their distributions. Results indicate that entropy-based sampling excels in logistical simplicity and preserves categorical diversity, while KL divergence offers the best statistical fit to population characteristics. The findings demonstrate how combining information theory and statistical optimization enables flexible, scalable sampling solutions for demand characterization in under-instrumented electricity grids. Full article

Southern tomato virus (STV) or Amalgavirus lycopersici is a persistent virus impacting tomato crops globally. This study identified new STV isolates from Oklahoma and analyzed their evolutionary relationship to global STV isolates. Phylogenetic analyses (complete genomes or individual genes) grouped STV isolates into two distinct clades, independent of geographic origin or host. Notably, Oklahoma isolates formed a separate cluster from previously reported isolates in the United States of America (USA). Coalescent analysis suggested the most recent common ancestor of STV fusion protein emerged around 135 years ago. Genetic diversity among STV isolates was low, with slightly more variability in the RNA-dependent RNA polymerase (RdRp) gene than the p42 gene. Both genes showed strong purifying selection. No recombination events were detected across complete genomes. Structure analysis revealed that the p42 protein, particularly its C-terminal region, displayed higher disorder, indicating a possible role in host interactions and viral adaptability. These findings deepen our understanding of STV’s evolution and highlight the need for ongoing surveillance and broader genomic sampling. Full article

Propolis contains abundant flavonoid and phenolic compounds, whose composition and concentration vary significantly in different geographical origins, thereby affecting its bioactive properties including anti-inflammatory, antioxidant, and antimicrobial activities. In this study, the flavonoid and phenolic content in the ethanol extract of propolis (EEP) from Henan (HN) and Shandong (SD) provinces was quantitatively analyzed, and the results showed that concentrations of both bioactive components in HN were slightly higher than those in SD. The non-targeted metabolomics technology was further employed to analyze the components of EEP, and a total of 10683 metabolites were detected. In the comparison between the samples of HN and SD, there were a total of 1436 differential metabolites, with 553 decreased and 883 increased in the HN sample. Among them, there were 205 differential metabolites related to flavonoids and phenols, with 108 decreased and 97 increased in the HN sample. However, a greater number of carboxylic acids and derivatives, fatty derivatives and organooxygen metabolites were found at higher relative levels in the HN sample. As a result, the EEP of the HN sample was selected to investigate its inhibitory effect on inflammation in lipopolysaccharide (LPS)-induced BV2 microglia cells. The results showed that LPS promoted the M1 polarization of BV2 microglia. However, treatment with EEP at concentrations of 10 µg/mL, 5 µg/mL, and 2.5 µg/mL could partially restore the cell morphology to its non-activated state. Meanwhile, LPS stimulation increased the protein levels of IL-1β, IL-6 and TNF-α significantly, as well as the relative gene expression levels of IL-1β, IL-6, TNF-α, COX-2, iNOS and TLR4. After treatment with the EEP, the expression levels of these three proteins and six genes were significantly decreased. These findings revealed that EEP effectively inhibited the M1 polarization of LPS-induced BV2 cells and decreased the expression of inflammatory factors, indicating its potential as a therapeutic agent for neuroinflammation. Full article

The genus Sclerodermus Latreille (Hymenoptera: Bethylidae) comprises over 80 species of ectoparasitoids of insect pests in forests, agricultural environments, and stored products with a cosmopolitan distribution. Despite its growing significance in biological control, behavioral ecology, and public health, the taxonomy of the genus remains poorly resolved. This is largely due to morphological reduction and simplification among species, outdated or incomplete original descriptions, and limited access to type material. A particularly problematic case is Sclerodermus cereicollis Kieffer, originally described from two geographically disjunct populations: Giglio Island (Italy, Palaearctic) and Annobón Island (Equatorial Guinea, Afrotropical). The syntype series includes morphologically divergent specimens, casting doubt on their conspecificity. In this study, we redescribe S. cereicollis based on both the original syntypes and newly collected material from Italy. A lectotype is designated to stabilize the nomenclature, and we provide the first molecular data for the species to assess genetic cohesion among populations. Comparative morphological and molecular analyses reveal that the Afrotropical syntypes represent a distinct, previously undescribed species. Accordingly, we describe Sclerodermus annobonensis Masini, Colombo & Azevedo sp. nov., designating a holotype. This study refines species boundaries within Sclerodermus and highlights the value of integrative taxonomy, combining historical and contemporary data, in resolving persistent systematic ambiguities in morphologically conservative taxa. Full article

This study analyzes the nutritional quality and mycotoxin contamination of three key feed ingredients—corn, soybean meal (SBM), and sunflower meal (SFM)—imported into Morocco during the years 2019, 2020, and 2021. Samples were collected upon reception at the plant and analyzed in triplicate under standardized laboratory conditions. Chemical composition was evaluated using classical and NIR-based methods, while mycotoxin levels were assessed through ELISA and confirmed by HPLC. Corn samples from Argentina, Brazil, and Ukraine were assessed for their proximate composition and mycotoxin burden. While most nutritional parameters showed no significant differences between origins (p > 0.05), water activity (Aw) and digestible threonine content were significantly affected by origin (p < 0.01). Brazilian corn had the highest Aw (0.716), followed by Argentina (0.680), and Ukraine (0.662), a factor linked to its higher susceptibility to mold and mycotoxin development. Soybean meal from the U.S. and Argentina showed a general positive trend in favor of U.S. imports, with higher average crude protein (the CP content of American soybean meal was 46.912%, compared to 46.610% in Argentine soybean meal), fat, digestible lysine, and metabolizable energy. However, statistical differences were limited to water activity and moisture content (p < 0.05). American soybean meals are generally recognized for their consistent processing quality and superior amino acid digestibility. Sunflower meal, sourced exclusively from Ukraine, showed a steady improvement in crude protein (from 35.97% in 2019 to 36.99% in 2021) and metabolizable energy, alongside reduced crude fiber content, enhancing its nutritional value in poultry diets. The consistent use of Ukrainian SFM in Morocco reflects both supply stability and quality. Regarding mycotoxins, origin had a significant effect on several compounds. Argentine and Brazilian corn showed higher mean levels of fumonisins (1165.26 and 1019.52 ppb), ochratoxin A (2.26 and 3.02 ppb), and zearalenone (36.99 and 21.92 ppb) compared to Ukrainian corn, which consistently had the lowest levels across all major mycotoxins (e.g., fumonisins = 200 ppb; zearalenone = 4.90 ppb). Aflatoxin B1 levels remained constant at 0.2 ppb across all origins. These findings confirm the influence of geographic origin—particularly water activity—on mycotoxin risk in imported maize. Full article

Historically, traditional transportation planning has promoted public policies focused on building and maintaining infrastructure for private cars to improve travel efficiency. This approach presents a significant challenge for cities in the Global South due to their unique socioeconomic conditions and urban development patterns. Dedicated public transport infrastructure can make better use of the road network by moving more people and reducing congestion. Beyond its environmental benefits, it also provides the population with greater accessibility, creating new development opportunities. This study uses Mexicali, Mexico, a medium-sized city with dispersed urban growth and a high dependence on cars, as a case study. The goal is to identify the relationship between the supply of public bus routes and actual work-related commuting patterns. The methodology considers that, given the scarcity of economic resources and prior studies in the Global South, using Geographic Information Systems (GIS) for the spatial analysis of travel is a key tool for redesigning more inclusive and sustainable public transport systems. Specifically, this study utilized origin–destination survey data from 14 urban areas to assess modal coverage, work-related commuting patterns, and the spatial distribution of employment centres. The findings reveal a marked misalignment between the existing public transport network and the population’s travel needs, particularly in marginalized areas. Users face long travel times, multiple transfers, low service frequency, and limited connectivity to key employment areas. This configuration reinforces an exclusionary urban structure, with negative impacts on equity, modal efficiency, and sustainability. The study concludes that GIS-based spatial analysis generates sufficient evidence to redesign the public transport system and reorient urban mobility policy toward sustainability and social inclusion. Full article

Background: The COVID-19 pandemic significantly disrupted patterns of physical activity and participation in mass sporting events, with recreational runners in Latin America among the most affected. In Colombia, pre-existing inequalities in access to sport further exacerbated these impacts. Nevertheless, evidence on post-COVID-19 impact and recovery experiences among regional runners remains limited. Objective: We examined the sociodemographic profiles, athletic experience, and perceptions of COVID-19-related impact and recovery among participants in the 2023 Medellín Marathon, and to assess differences by educational attainment, employment status, age group, and geographic origin. Methods: A cross-sectional descriptive study was undertaken involving 2486 registered marathon runners. An ad hoc questionnaire assessed COVID-19 symptoms and sequelae, perceived respiratory and physical limitations, fears associated with group exercise, and self-reported recovery. Analyses included descriptive statistics, bivariate comparisons and one-way ANOVA tests. Results: Older participants, retirees and those with lower educational levels reported significantly greater COVID-19 impact, longer recovery periods and higher perceived physical and respiratory limitations. In contrast, younger runners and those with a college education showed more complete physical recovery and attributed protective benefits, such as improved cardiorespiratory function and a lower incidence of respiratory symptoms, to their training. Additionally, runners originating from smaller municipalities and other Latin American countries reported higher levels of impact and lower perceptions of recovery. Conclusions: Post-COVID-19 effects among marathon runners are not uniform but vary according to sociodemographic and contextual factors. These findings underscore the importance of tailored support and readaptation strategies—particularly for vulnerable subgroups—to ensure their safe and equitable return to mass endurance events. Full article

This review provides an overview of recent advancements in hyperspectral imaging (HSI) technology for grain quality and safety detection, focusing on its impact on global food security and economic stability. Traditional methods for grain quality assessment are labor-intensive, time-consuming, and destructive, whereas HSI offers a non-destructive, efficient, and rapid alternative by integrating spatial and spectral data. Over the past five years, HSI has made significant strides in several key areas, including disease detection, quality assessment, physicochemical property analysis, pesticide residue identification, and geographic origin determination. Despite its potential, challenges such as high costs, complex data processing, and the lack of standardized models limit its widespread adoption. This review highlights these advancements, identifies current limitations, and discusses the future implications of HSI in enhancing food safety, traceability, and sustainability in the grain industry. Full article

This study explores how Turkish Generation Z adapts their fashion consumption behaviours in response to economic crises, particularly focusing on involuntary anti-consumerism. Through a qualitative methodology using semi-structured interviews and purposive sampling, the research captures the coping strategies and emotional experiences of young consumers in Türkiye. A thematic analysis of fifteen interviews reveals an original “8Rs” framework—Reject, Restrict/Reduce, Reuse/Reclaim, Re-find, Reconsider, Re-framing Discounts, Re-direction of Resources, and Emotional Responses—that illustrates both behavioural and psychological adjustments under financial strain. Notably, the study introduces two novel concepts: “recession rush,” a calculated urgency to purchase before price hikes, and “re-direction of resources,” the reallocation of budget from other categories toward fashion purchases. By focusing on a geographically underrepresented context and a pivotal consumer segment, this research contributes new insights to the literature on anti-consumption, economic adaptation, and youth identity expression in crisis economies. Full article

Background/Objectives: Forced degradation studies are critical for identifying potential degradation pathways of monoclonal antibodies (mAbs), particularly under thermal stress. Due to their structural complexity and sensitivity to elevated temperatures, mAbs are prone to fragmentation, aggregation, and post-translational modifications. This study aimed to evaluate and compare the degradation profiles of biosimilar anti-VEGF mAb and its originator counterparts sourced from both the United States (U.S.) and the European Union (EU) under thermal stress conditions. To our knowledge, this represents one of the few studies conducting a direct head-to-head comparability assessment across biosimilar and two geographically sourced originators, integrating orthogonal analytical approaches. Methods: Biosimilar candidate and originator products (U.S. and EU) were incubated at 37 °C and 50 °C for 3, 7, and 14 days. Fragmentation profiles were assessed using validated non-reduced and reduced capillary electrophoresis–sodium dodecyl sulfate (CE-SDS) methods. Additionally, size-exclusion ultra-performance liquid chromatography (SE-UPLC) and liquid chromatography–tandem mass spectrometry (LC-MS/MS) assays were performed on samples stressed for 14 days to provide deeper insights into degradation pathways. Results: Non-reduced CE-SDS analysis indicated a time- and temperature-dependent increase in low-molecular-weight fragments and a corresponding decrease in the intact form, with more pronounced effects observed at 50 °C. Reduced CE-SDS revealed a more rapid increase in total impurity levels at 50 °C, accompanied by a decrease in total light and heavy chain content. SE-UPLC showed enhanced aggregation under thermal stress, more pronounced at 50 °C. LC-MS/MS analysis identified increased asparagine deamidation in the PENNY peptide and pyroglutamic acid formation (pE) at the N-terminus of the heavy chain. Conclusions: The degradation profiles of the biosimilar and originator mAbs were highly comparable under thermal stress, with no significant qualitative differences detected. By applying a multi-tiered analytical characterization technique, this study provides a comprehensive comparability assessment that underscores the robustness of biosimilarity even under forced degradation conditions. Full article