Search Results (105,179)

Background: Acute kidney injury (AKI) frequently occurs following major liver resection, adversely affecting both short- and long-term outcomes. This study aimed to determine the incidence of AKI post-hepatectomy and identify relevant pre- and intraoperative risk factors. Our secondary objectives were to develop a predictive score for postoperative AKI and assess the associations between AKI, chronic kidney disease (CKD), and 1-year mortality. Methods: This was a retrospective study in a cancer referral center in Marseille, France, from 2018 to 2022. Results: Among 169 patients, 55 (32.5%) experienced AKI. Multivariate analysis revealed several independent risk factors for postoperative AKI, including age, body mass index, the use of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, time to liver resection, intraoperative shock, and bile duct reconstruction. Neoadjuvant chemotherapy was protective. The AKIMEBO score was developed, with a threshold of ≥15.6, demonstrating a sensitivity of 89.5%, specificity of 76.4%, positive predictive value of 61.8%, and negative predictive value of 94.4%. AKI was associated with increased postoperative morbidity and one-year mortality following major hepatectomy. Conclusion: AKI is a common complication post-hepatectomy. Factors such as time to liver resection and intraoperative shock management present potential clinical intervention points. The AKIMEBO score can provide a valuable tool for postoperative risk stratification. Full article

Phubbing, a relatively new phenomenon in the field of digital risks, refers to the act of ignoring someone in favor of focusing on a smartphone during face-to-face interactions. Parental phubbing, a specific form of this behavior, is a prevalent negative parenting practice that can affect parent–child relationships and child development. However, the impact of parental phubbing on the emotional and behavioral development of preschool children remains unclear. This study aims to explore the relationship between parental phubbing and preschoolers’ behavioral problems, as well as test whether parents’ mindful attention awareness (MAA) acts as a mediator between them. Method: A questionnaire was administered to 138 Italian parents (mean age = 38.5, SD = 6.2) of 138 kindergarten preschoolers (mean age = 3.9, SD = 1.03). Questionnaires included the Generic Scale of Phubbing (GSP), the Mindful Attention Awareness Scale (MAAS), and the Strengths and Difficulties Questionnaire (SDQ). Results: Analyses revealed a significant negative correlation between the MAAS and SDQ total scores, a positive correlation between the GSP total score and the SDQ total score, and a negative correlation between the GSP total score and the MAAS total score. The mediation analysis did not show a direct effect of GSP on SDQ, suggesting that parental phubbing did not directly predict children’s behavioral difficulties. Nevertheless, the indirect effect measured by bootstrapping was significant, indicating that parental MAA fully mediated the relationship between parental phubbing and preschoolers’ problematic behaviors. Conclusions: Although further research is needed, parental mindfulness may influence phubbing behaviors in parents providing valuable insights for early interventions aimed at reducing problem behaviors in young children. Full article

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

Forest fires are commonly regarded as negative for ecosystems; however, they also represent a major ecological force shaping the biodiversity of invertebrates and many other organisms. The aim of this study was to better understand how multiple groups of invertebrates respond to wildfire across different forest types in Central Europe. The research was conducted following a large forest fire (ca. 1200 ha) that occurred in 2022. Data were collected over two years (2023 and 2024), from April to September. The research was conducted in coniferous forests and included six pairwise study types: burnt and unburnt dead spruce (bark beetle affected), burnt and unburnt clear-cuts, and burnt and unburnt healthy stands. In total, 96 traps were deployed each year. Across both years, 220,348 invertebrates were recorded (1.Y: 128,323; 2.Y: 92,025), representing 24 taxonomic groups. A general negative trend in abundance following forest fire was observed in the groups Acari, Auchenorhyncha, Blattodea, Dermaptera, Formicidae, Chilopoda, Isopoda, Opiliones, and Pseudoscorionida. Groups showing a neutral response included Araneae, Coleoptera, Collembola, Diplopoda, Heteroptera, Psocoptera, Raphidioptera, Thysanoptera, and Trichoptera. Positive responses, indicated by an increase in abundance, were recorded in Hymenoptera, Orthoptera, Lepidoptera, and Diptera. However, considerable differences among management types (clear-cut, dead spruce, and healthy) were evident, as their distinct characteristics largely influenced invertebrate abundance in both unburnt and burnt variants of the types across all groups studied. Forest fire primarily creates favorable conditions for heliophilous, open-landscape, and floricolous invertebrate groups, while less mobile epigeic groups are strongly negatively affected. In the second year post-fire, the total invertebrate abundance in burnt sites decreased to 59% of the first year’s levels. Conclusion: Forest fire generates a highly heterogeneous landscape from a regional perspective, creating unique ecological niches that persist more than two years after fire. For many invertebrates, successional return toward pre-fire conditions is delayed or incomplete. Full article

The adoption of digital technologies, such as the Internet of Things (IoT), has emerged as a key strategy to improve efficiency, sustainability, and productivity in the agricultural sector, especially in contexts of modernization and digital transformation in developing regions. This study analyzes the key factors influencing the adoption of IoT technologies by farmers in the province of Guayas, Ecuador, and their impact on agricultural yields. The research is grounded in innovation diffusion theory and technology acceptance models, which emphasize the role of perception, usability, training, and economic viability in digital adoption. A total of 250 surveys were administered, with 232 valid responses (92.8% response rate), reflecting strong interest from the agricultural sector in digital transformation and precision agriculture. Using structural equation modeling (SEM), the results confirm that general perception of IoT (β = 0.514), practical functionality (β = 0.488), and technical training (β = 0.523) positively influence adoption, while high implementation costs negatively affect it (β = −0.651), all of which are statistically significant (p < 0.001). Furthermore, adoption has a strong positive effect on agricultural yield (β = 0.795). The model explained a high percentage of variance in both adoption (R² = 0.771) and performance (R² = 0.706), supporting its predictive capacity. These findings underscore the need for public and private institutions to implement targeted training and financing strategies to overcome economic barriers and foster the sustainable integration of IoT technologies in Ecuadorian agriculture. Full article

Glanders is a highly contagious and often fatal zoonotic disease of equids caused by Burkholderia mallei, a pathogen of significant concern due to its potential for bioterrorism. In Brazil, glanders remains endemic, particularly among working equids in the Northeast region. Diagnostic confirmation typically involves serology, culture, and polymerase chain reaction (PCR), although false-negative PCR results have been increasingly reported. This study aimed to evaluate the diagnostic performance and analytical sensitivity of four B. mallei-specific PCR primer sets using samples from 30 seropositive equids. Microbiological cultures were obtained from various organs and swabs, followed by PCR targeting four genomic regions: fliP-IS407A(a), fliP-IS407A(b), Burk457, and Bm17. All animals were confirmed positive for B. mallei via culture, but PCR detection rates varied significantly across primer sets. The fliP-IS407A(b) primer set showed the highest sensitivity, detecting 86% of samples, while the WOAH-recommended fliP-IS407A(a) set had the lowest performance (13.4%). Analytical sensitivity assays confirmed that fliP-IS407A(b) and Bm17 primers detected DNA concentrations as low as 0.007 ng, outperforming the others. These findings suggest that certain widely used primer sets may lack sufficient sensitivity for reliable detection of B. mallei, especially in chronically infected animals with low bacterial loads. The study underscores the need for ongoing validation of molecular diagnostics to improve the detection and control of glanders in endemic regions. Full article

Microbiome analysis has revolutionized our understanding of various biological processes, spanning human health and epidemiology (including antimicrobial resistance and horizontal gene transfer), as well as environmental and agricultural studies. At the heart of microbiome analysis lies the characterization of microbial communities through the quantification of microbial taxa and their dynamics. In the study of bacterial abundances, it is becoming more relevant to consider their relationship, to embed these data in the framework of network theory, allowing characterization of features like node relevance, pathways, and community structure. In this study, we address the primary biases encountered in reconstructing networks through correlation measures, particularly in light of the compositional nature of the data, within-sample diversity, and the presence of a high number of unobserved species. These factors can lead to inaccurate correlation estimates. To tackle these challenges, we employ simulated data to demonstrate how many of these issues can be mitigated by applying typical transformations designed for compositional data. These transformations enable the use of straightforward measures like Pearson’s correlation to correctly identify positive and negative relationships among relative abundances, especially in high-dimensional data, without having any need for further corrections. However, some challenges persist, such as addressing data sparsity, as neglecting this aspect can result in an underestimation of negative correlations. Full article

Background/Objectives: Aging is associated with a gradual decline in physical capabilities, often leading to impaired balance and reduced functional status, which are major contributors to falls in older adults. Although many studies have assessed these variables independently, a limited amount of research has explored the direct relationship between balance and functional status in a healthy geriatric population. The aim of this study was to investigate the relationship between balance and functional capacity and to assess the influence of demographic factors such as age, comorbidities, smoking status, and history of falls. Methods: A sample of community-dwelling older adults (19 women, 16 men) (n = 35), aged 60 years and above (M = 78 years; SD = 9.23) from Sparta, Greece, took part in the present study. Participants were assessed using three validated tools: (a) the Five Times Sit-to-Stand test, (b) the Timed Up-and-Go test, and (c) the Berg Balance Scale. Spearman’s rank correlation coefficient was used for statistical analysis (α = 0.05). Results: Age was positively correlated with poorer performance in the Five Times Sit-to-Stand (r = 0.40; p < 0.01) and the Timed Up-and-Go test (r = 0.47; p < 0.01) and negatively correlated with Berg Balance Scale scores (r = −0.51; p < 0.01). Comorbidities and smoking were also associated with the Berg Balance Scale. A strong negative correlation was observed between balance and the other two functional tests (Five Times Sit-to-Stand: r = −0.51; Timed Up-and-Go: r = −0.66; both p < 0.01). Conclusions: The findings highlight the importance of evaluating both balance and functional capacity in older adults as interrelated factors that can significantly influence quality of life and fall risk. Future research with larger and more diverse populations is recommended to confirm the present findings and to use exercise programs to prevent falls in the geriatric population. Full article

Objective: We evaluated the feasibility of a machine-learning (ML) model based on clinical features and radiomics from [¹⁸F]FDG PET/CT images to differentiate between infected and non-infected intracavitary vascular grafts and endografts (iVGEI). Methods: Three ML models were developed: one based on pre-treatment criteria to diagnose a vascular graft infection (“MAGIC-light features”), another using radiomics features from diagnostic [¹⁸F]FDG-PET scans, and a third combining both datasets. The training set included 92 patients (72 iVGEI-positive, 20 iVGEI-negative), and the external test set included 20 iVGEI-positive and 12 iVGEI-negative patients. The abdominal aorta and iliac arteries in the PET/CT scans were automatically segmented using SEQUOIA and TotalSegmentator and manually adjusted, extracting 96 radiomics features. The best-performing models for the MAGIC-light features and PET-radiomics features were selected from 343 unique models. Most relevant features were combined to test three final models using ROC analysis, accuracy, sensitivity, and specificity. Results: The combined model achieved the highest AUC in the test set (mean ± SD: 0.91 ± 0.02) compared with the MAGIC-light-only model (0.85 ± 0.06) and the PET-radiomics model (0.73 ± 0.03). The combined model also achieved a higher accuracy (0.91 vs. 0.82) than the diagnosis based on all the MAGIC criteria and a comparable sensitivity and specificity (0.70 and 1.00 vs. 0.76 and 0.92, respectively) while providing diagnostic information at the initial presentation. The AUC for the combined model was significantly higher than the PET-radiomics model (p = 0.02 in the bootstrap test), while other comparisons were not statistically significant. Conclusions: This study demonstrated the potential of ML models in supporting diagnostic decision making for iVGEI. A combined model using pre-treatment clinical features and PET-radiomics features showed high diagnostic performance and specificity, potentially reducing overtreatment and enhancing patient outcomes. Full article

Schistosoma mansoni infection is associated with hepatic inflammation and fibrosis, but its systemic metabolic effects remain poorly understood. This study aimed to investigate changes in the serum lipidomic profile associated with S. mansoni infection and parasite load in individuals from an endemic area. This cross-sectional analysis was nested within a longitudinal cohort study conducted in northeastern Brazil. Parasitological diagnosis and quantification were performed using the Kato–Katz technique. A total of 45 individuals were selected and divided into three groups: high parasite load (HL), low parasite load (LL), and uninfected controls (NegE). Serum samples were analyzed using mass-spectrometry-based lipidomics. The most abundant lipid subclasses across all groups were phosphatidylcholines (PC), triacylglycerols (TAG), and phosphatidylethanolamines (PE). However, individuals in the HL group exhibited distinct lipidomic profiles, with increased levels of specific phosphatidylinositols (PI) and reduced levels of certain TAG species compared to the NegE group. These changes may reflect host–parasite interactions and immune–metabolic alterations driven by intense infection. Our findings suggest that S. mansoni infection, particularly at higher parasite burdens, can influence the host’s serum lipid profile and may contribute to metabolic disturbances in endemic populations. Full article

With the growing severity of environmental pollution, people are paying increasing attention to their health. However, naturally occurring wood with health benefits and applications in human healthcare is still scarce. Natural wood exhibits a limited negative oxygen ion release capacity, and this release has a short duration, failing to meet practical application requirements. This study innovatively developed a humidity-responsive, healthy wood material with a high negative oxygen ion release capacity based on fast-growing poplar. Through vacuum cyclic impregnation technology, hexagonal stone powder was infused into the pores of poplar wood, endowing it with the ability to continuously release negative oxygen ions. The healthy wood demonstrated a static average negative oxygen ion release rate of 537 ions/cm³ (peaking at 617 ions/cm³) and a dynamic average release rate of 3,170 ions/cm³ (peaking at 10,590 ions/cm³). The results showed that the particle size of hexagonal stone powder in suspension was influenced by the dispersants and dispersion processes. The composite dispersion process demonstrated optimal performance when using 0.5 wt% silane coupling agent γ-(methacryloxy)propyltrimethoxysilane (KH570), achieving the smallest particle size of 8.93 μm. The healthy wood demonstrated excellent impregnation performance, with a weight gain exceeding 14.61% and a liquid absorption rate surpassing 165.18%. The optimal impregnation cycle for vacuum circulation technology was determined to be six cycles, regardless of the type of dispersant. Compared with poplar wood, the hygroscopic swelling rate of healthy wood was lower, especially in PEG-treated samples, where the tangential, radial, longitudinal, and volumetric swelling rates decreased by 70.93%, 71.67%, 69.41%, and 71.35%, respectively. Combining hexagonal stone powder with fast-growing poplar wood can effectively enhance the release of negative oxygen ions. The static average release of negative oxygen ions from healthy wood is 1.44 times that of untreated hexagonal stone powder, and the dynamic release reaches 2 to 3 times the concentration of negative oxygen ions specified by national fresh air standards. The water-responsive mechanism revealed that negative oxygen ion release surged when ambient humidity exceeded 70%. This work proposes a sustainable and effective method to prepare healthy wood with permanent negative oxygen ion release capability. It demonstrates great potential for improving indoor air quality and enhancing human health. Full article

To explore the characteristics of species diversity and phylogenetic diversity, as well as the dominant processes of community construction, in different forest types (deciduous broad-leaved forest, mixed coniferous and broad-leaved forest, and Chinese fir plantation) in subtropical regions, analyze the specific driving patterns of soil nutrients and other environmental factors on the formation of forest diversity in different forest types, and clarify the differences in response to environmental heterogeneity between natural forests and plantation forests. Based on 48 fixed monitoring plots of 50 m × 50 m in Shouchang Forest Farm, Jiande City, Zhejiang Province, woody plants with a diameter at breast height ≥5 cm were investigated. Species diversity indices (Margalef index, Shannon–Wiener index, Simpson index, and Pielou index), phylogenetic structure index (PD), and environmental factors were used to analyze the relationship between diversity characteristics and environmental factors through variance analysis, correlation analysis, and generalized linear models. Phylogenetic structural indices (NRI and NTI) were used, combined with a random zero model, to explore the mechanisms of community construction in different forest types. Research has found that (1) the deciduous broad-leaved forest had the highest species diversity (Margalef index of 4.121 ± 1.425) and phylogenetic diversity (PD index of 21.265 ± 7.796), significantly higher than the mixed coniferous and broad-leaved forest and the Chinese fir plantation (p < 0.05); (2) there is a significant positive correlation between species richness and phylogenetic diversity, with the best fit being AIC = 70.5636 and R² = 0.9419 in broad-leaved forests; however, the contribution of evenness is limited; (3) the specific effects of soil factors on different forest types: available phosphorus (AP) is negatively correlated with the diversity of deciduous broad-leaved forests (p < 0.05), total phosphorus (TP) promotes the diversity of coniferous and broad-leaved mixed forests, while the diversity of Chinese fir plantations is significantly negatively correlated with total nitrogen (TN); (4) the phylogenetic structure of three different forest types shows a divergent pattern in deciduous broad-leaved forests, indicating that competition and exclusion dominate the construction of deciduous broad-leaved forests; the aggregation mode of Chinese fir plantation indicates that environmental filtering dominates the construction of Chinese fir plantation; the mixed coniferous and broad-leaved forest is a transitional model, indicating that the mixed coniferous and broad-leaved forest is influenced by both stochastic processes and ecological niche processes. In different forest types in subtropical regions, the species and phylogenetic diversity of broad-leaved forests is significantly higher than in other forest types. The impact of soil nutrients on the diversity of different forest types varies, and the characteristics of community construction in different forest types are also different. This indicates the importance of protecting the original vegetation and provides a scientific basis for improving the ecological function of artificial forest ecosystems through structural adjustment. The research results have important practical guidance value for sustainable forest management and biodiversity conservation in the region. Full article

430 stainless steel exhibits soft magnetic properties, excellent formability, and corrosion resistance, making it widely used in industrial applications. This study investigates the effects of different cold working rates on the properties of 430 stainless steel subjected to various magnetic annealing atmospheres (F-1.5Si, F-1.5Si-10%, F-1.5Si-40%, F-1.5Si-10% (MA), F-1.5Si-40% (MA), F-1.5Si-10% (H₂), and F-1.5Si-40% (H₂)). The results indicate that increasing the cold working rate improves the material’s mechanical properties; however, it negatively impacts its magnetic and corrosion resistance properties. Additionally, the magnetic annealing process improves the mechanical properties, while atmospheric magnetic annealing optimizes the overall magnetic performance. In contrast, magnetic annealing in a hydrogen atmosphere does not enhance the magnetic properties as effectively as atmospheric magnetic annealing. Still, it promotes the formation of a protective layer, preserving the mechanical properties and providing better corrosion resistance. Furthermore, regardless of whether magnetic annealing is conducted in an atmospheric or hydrogen environment, materials with 10% cold work rate (F-1.5Si-10% (MA) and F-1.5Si-10% (H₂)) exhibit the lowest coercive force (286 and 293 A/m in the 10 Hz test condition), making them ideal for electromagnetic applications. Full article

Background and Clinical Significance: Neuroleptic malignant syndrome (NMS) is a life-threatening condition usually caused by the exposure to antipsychotics. This case report presents a catatonia syndrome that may have developed in the context of a moderate NMS. Case Presentation: An 18-year-old male patient presented with a treatment-resistant catatonia syndrome that debuted 2 weeks prior to the presentation (creatin kinase levels = 4908 U/lL maximum temperature = 38.9°C, white blood count = 13.20 × 10⁹/L, Bush–Francis Catatonia Rating Scale = 30 points). Possible organic causes of catatonia were ruled out, according to the negative results obtained. The patient’s condition improved under benzodiazepine treatment and he was later discharged. After discharge, the catatonia was attributed to a possible NMS with moderate severity. The diagnosis was supported by NMS Diagnosis Criteria Score = 85 points and the presence of Levenson’s triad. Conclusions: This case highlights the concomitant manifestation of both catatonia and NMS in the same patient and the difficulty of establishing a correct diagnosis involving both entities. Full article

Landslides are destructive geological hazards, making accurate landslide susceptibility assessment essential for disaster prevention and mitigation. However, existing studies often lack scientific rigor in negative sample construction and have unclear model applicability. This study focuses on Ya’an City, Sichuan Province, China, and proposes an innovative approach to negative sample construction using Geographically Weighted Regression (GWR), which is then integrated with Tabular Network (TabNet), a deep learning architecture tailored to structured tabular data, to assess landslide susceptibility. The performance of TabNet is compared against Random Forest, Light Gradient Boosting Machine, deep neural networks, and Residual Networks. The experimental results indicate that (1) the GWR-based sampling strategy substantially improves model performance across all tested models; (2) TabNet trained using the GWR-based negative samples achieves superior performance over all other evaluated models, with an average AUC of 0.9828, exhibiting both high accuracy and interpretability; and (3) elevation, land cover, and annual Normalized Difference Vegetation Index are identified as dominant predictors through TabNet’s feature importance analysis. The results demonstrate that combining GWR and TabNet substantially enhances landslide susceptibility modeling by improving both accuracy and interpretability, establishing a more scientifically grounded approach to negative sample construction, and providing an interpretable, high-performing modeling framework for geological hazard risk assessment. Full article