Search Results (40,821)

Restoration plantations in subtropical regions, often established with fast-growing tree species such as Acacia auriculiformis A. Cunn. ex Benth and Eucalyptus urophylla S. T. Blake, are frequently developed on highly weathered soils characterized by phosphorus deficiency. To investigate strategies for mitigating nutrient imbalances in such ecosystems, a long-term (≥13 years) fertilization experiment was designed. The experiment involved three fertilization regimes: nitrogen fertilizer alone (N), phosphorus fertilizer alone (P), and a combination of nitrogen and phosphorus (NP) fertilizers. The objective of this study was to investigate the effects of long-term fertilization practices on soil quality in subtropical plantations using a soil quality index (SQI). Consequently, all conventional soil physical, chemical, and biological indicators associated with the SQI responses to long-term fertilization treatments were systematically evaluated, and a principal component analysis (PCA) was conducted, along with a literature review, to develop a minimum dataset (MDS) for calculating the SQI. Three physical indicators (silt, clay, and soil water content), three chemical indicators (soil organic carbon, inorganic nitrogen, and total phosphorus), and two biological indicators (microbial biomass carbon and phosphodiesterase enzyme activity) were finally chosen for the MDS from a total dataset (TDS) of eighteen soil indicators. This study shows that the MDS provided a strong representation of the TDS data (R² = 0.81), and the SQI was positively correlated with litter mass (R² = 0.37). An analysis of individual soil indicators in the MDS revealed that phosphorus addition through fertilization (P and NP treatments) significantly enhanced the soil phosphorus pool (64–101%) in the subtropical plantation ecosystem. Long-term fertilization did not significantly change the soil quality, as measured using the SQI, in either the Acacia auriculiformis (p = 0.25) or Eucalyptus urophylla (p = 0.45) plantation, and no significant differences were observed between the two plantation types. These findings suggest that the MDS can serve as a quantitative and effective tool for long-term soil quality monitoring during the process of forest sustainable management. Full article

Digital transformation is the process by which businesses adopt use of digital technologies to fundamentally change operations and customer interactions in order to optimize delivery and service. The UK refers to the United Kingdom which is shorthand for the United Kingdom of Great Britain and Northern Ireland which is a European country that primarily includes England, Wales and Scotland together with the northern part of Ireland. The retail sector includes businesses that sell goods or services directly to consumers for their personal use, opposed to selling to other organizations for business applications. Generation refers to a series of broad age groups that are considered to demonstrate different generalized characteristics. Full article

Organosilica films, composed of a silicon oxide network with terminal methyl groups, are widely utilized in various applications, including microelectronics. Many of these applications require high hydrophobicity and good mechanical properties, which pose a significant challenge because the Si–CH₃ groups disrupt the Si–O–Si network. This issue becomes particularly pronounced in porous films. Here, we investigate whether material properties can be tuned by simply altering the spatial arrangement of methyl groups. To achieve this, we prepared copolymer films with one or two methyl groups bonded to a silicon atom, while maintaining a constant total amount of methyl groups. The films were deposited using a sol–gel technique combined with template self-assembly. The precursor content was varied to compare films with different proportions of Si–CH₃ and Si(–CH₃)₂. Film characterization included FTIR, ellipsometric porosimetry, AFM, and WCA measurements and dielectric constant evaluations. Our findings indicate that precursors containing dimethyl groups enhance the connectivity of the Si–O–Si network, resulting in a higher Young’s modulus and smaller pore size compared to films with an equivalent amount of methyl groups. However, the lower thermal stability of dimethyl bonds limits the thermal budget of these films. Thus, the spatial arrangement of organic groups within the polymer structure can be employed to tune material properties. These results expand the understanding of organic–inorganic hybrid materials and offer novel approaches for their applications. Full article

Background: This study evaluated the effects of veno-arterial (V-A) and veno-venoarterial (V-VA) ECMO in a porcine model of septic endotoxemia-induced acute pulmonary arterial hypertension (PAH). Our hypotheses were as follows: (1) V-VA ECMO lowers pulmonary vascular resistance (PVR) by delivering oxygenated blood to the pulmonary circulation, and (2) both V-A and V-VA ECMO improve perfusion to vital organs while simultaneously unloading the right ventricle (RV). Methods: Acute PAH was induced with Salmonella abortus equi lipopolysaccharide (LPS) in 34 pigs. Animals were randomized to either a control group without ECMO or to two groups receiving V-A or V-VA ECMO. Results: All animals developed PAH after one hour of LPS infusion: mean pulmonary artery pressure (PAP) increased significantly from 26 (24–30) mmHg to 40 (34–46) mmHg (p < 0.0001), and PVR increased from 314 (221–390) to 787 (549–1073) (p < 0.0001). Neither V-A nor V-VA ECMO significantly reduced PVR compared to controls. RV end-diastolic area increased in the control group [6.1 (4.3–8.6) cm vs. 8.5 (7.8–9.7) cm, p = 0.2], but not in the V-A [4.7 (3.3–7.6) cm] and V-VA [4.3 (2.5–8.3) cm] ECMO groups. Blood flow in the cranial mesenteric artery and celiac trunk did not differ significantly with or without ECMO. Conclusions: Elevating pulmonary artery oxygen tension through V-A or V-VA ECMO did not reduce PVR or PAP. However, both ECMO configurations effectively unloaded the RV and maintained perfusion to abdominal organs. Full article

This review provides an overview of the cross-sectional imaging features of gastrointestinal (GI) metastases presenting with a linitis plastica (LP) pattern and illustrates these findings through a series of cases from various primary tumors. It also addresses key diagnostic challenges, with particular attention to differential diagnosis. The term linitis plastica (LP) refers to the macroscopic appearance of a hollow organ with diffuse mural tumor infiltration, leading to loss of parietal distensibility. Although rare, primary LP can occur throughout the gastrointestinal (GI) tract. First described in the stomach—the most common site—it is typically associated with undifferentiated adenocarcinoma composed of poorly cohesive cells, often with signet ring morphology. Beyond primary GI tumors, LP-like metastases may also arise from extragastrointestinal primaries, most notably breast carcinoma (particularly the lobular subtype), as well as urinary bladder and prostate carcinomas. LP-like GI metastases typically manifest as circumferential, enhancing wall thickenings with exaggerated zonal anatomy and luminal narrowing. Due to diffuse parietal tumor infiltration—often with mucosal preservation—the submucosa and serosa appear disproportionately thickened and show greater enhancement relative to the muscularis propria (MP). This specific imaging appearance is known as the malignant target sign, which must be distinguished from the benign target sign, where the most prominent low-density layer corresponds to edematous submucosa. Additional key features include homogeneous enhancement with loss of layer differentiation on delayed-phase imaging and a concentric ring pattern on MR. Secondary findings may also be present, such as intestinal obstruction and concomitant peritoneal carcinomatosis (PC). Gastrointestinal metastases with an LP pattern present a significant diagnostic challenge, as they can mimic both primary tumors and benign inflammatory or infectious conditions. Accurate diagnosis is critical because management strategies differ substantially. Since the mucosa is often spared, endoscopy and superficial biopsies may yield false-negative results. Therefore, while immunohistochemistry (IHC) remains essential for confirmation, radiologists play a pivotal role in raising suspicion for LP-like GI metastases and recommending deep, extensive biopsies to obtain adequate representative tissue. Furthermore, in cases of an unknown primary tumor, recognition of the LP pattern can provide important clues to the potential site of origin. Full article

Aerogels (AGs) are highly porous, low-density, disordered, ultralight macroscopic materials with immense surface areas. Traditionally synthesized using aqueous sol–gel chemistry, starting by molecular precursors, the nanoparticles (NPs) dispersions gelation method is nowadays the most used procedure to obtain AGs with improved crystallinity and broader structural, morphological and compositional complexity. The Sol–gel process consists of preparing a solution by hydrolysis of different precursors, followed by gelation, ageing and a drying phase, via supercritical, freeze-drying or ambient evaporation. AGs can be classified based on various factors, such as appearance, synthetic methods, chemical origin, drying methods, microstructure, etc. Due to their nonpareil characteristics, AGs are completely different from common NPs, thus covering different and more extensive applications. AGs can be applied in supercapacitors, acoustic devices, drug delivery, thermal insulation, catalysis, electrocatalysis, gas absorption, gas separation, organic and inorganic xenobiotics removal from water and air and radionucleotides management. This review provides first an analysis on AGs according to data found in CAS Content Collection. Then, an AGs’ classification based on the chemical origin of their precursors, as well as the different methods existing to prepare AGs and the current optimization strategies are discussed. Following, focusing on AGs of inorganic origin, silica and metal oxide-based AGs are reviewed, deeply discussing their properties, specific synthesis and possible uses. These classes were chosen based on the evidence that they are the most experimented, patented and marketed AGs. Several related case studies are reported, some of which have been presented in reader-friendly tables and discussed. Full article

Accurate soil organic carbon (SOC) estimation is critical for assessing ecosystem services, carbon budgets, and informing sustainable land management, particularly in ecologically sensitive mountainous regions. This study focuses on modelling the spatial distribution of SOC within the heterogeneous volcanic landscape of the Nevado de Toluca (NdT), central Mexico, an area spanning 535.9 km² and characterised by diverse land uses, altitudinal gradients, and climatic regimes. Using 29 machine learning algorithms, we evaluated the predictive capacity of three key variables: land use, elevation, and the Normalised Difference Vegetation Index (NDVI) derived from satellite imagery. Complementary analyses were performed using the Bare Soil Index (BSI) and the Modified Soil-Adjusted Vegetation Index 2 (MSAVI2) to assess their relative performance. Among the tested models, the Quadratic Support Vector Machine (SVM) using NDVI, elevation, and land use emerged as the top-performing model, achieving a coefficient of determination (R²) of 0.84, indicating excellent predictive accuracy. Notably, 14 models surpassed the R² threshold of 0.80 when using NDVI and BSI as predictor variables, whereas MSAVI2-based models consistently underperformed (R² < 0.78). Validation plots demonstrated strong agreement between observed and predicted SOC values, confirming the robustness of the best-performing models. This research highlights the effectiveness of integrating multispectral remote sensing indices with advanced machine learning frameworks for SOC estimation in mountainous volcanic ecosystems Full article

It is of great significance to analyze the molecular mechanism of rice response to heavy ion irradiation and to mine its key response genes for food security. In this study, the regression equation for the dose survival rate was constructed using heavy ion irradiation on rice pollen. Through an immunofluorescence experiment, it was found that DSBs induced by irradiation could be repaired quickly, but the repair of complex damage required more time. RNA-seq of irradiated pollen showed that the gene expression patterns at different time points were significantly different. A total of 5,556 differentially expressed genes (DEGs) were screened out, and the number of DEGs decreased with time. DEGs were mainly involved in stress response, protein folding, DNA repair, and other damage response processes at 0–1 h. At 6 h, the cells turned to normal metabolism functions, such as organic synthesis and protein activity. Combined with weighted gene co-expression network analysis (WGCNA) and trend analysis, the key transcription factor OsERF110 was identified in response to heavy ion irradiation, which acts on the nucleus and cell membrane. A total of 45,680 OsERF110 binding peaks were identified by DNA affinity purification sequencing (DAP-seq) in the whole genome. When this method was combined with RNA sequencing (RNA-seq), 62 OsERF110 target genes were further screened. These target genes were involved in DNA repair, stress response, redox, metabolic regulation, and other processes, forming the OsERF110 mediated radiation response regulatory network. The results of this study provide a new target for rice mutation breeding and lay a theoretical foundation for radiation biology research. Full article

Improving the innovation performance of mega projects has become a central concern in both engineering project management theory and practice. Organizational structure and culture are key contextual factors that can facilitate tacit knowledge sharing across organizations, thereby enhancing innovation outcomes. Based on the data of 243 questionnaires, this paper systematically analyzes the influence mechanism of organizational context factors on innovation performance by using the structural equation model (SEM). The results show that organizational structure exerts a significant negative effect on both tacit knowledge sharing and innovation performance. Among the dimensions of organizational culture, trust climate and organizational support have significant positive effects on both tacit knowledge sharing and innovation performance. While the level of cooperation enhances tacit knowledge sharing, its direct impact on innovation performance is not statistically significant. Furthermore, in the organizational context and innovation performance, tacit knowledge sharing also plays different mediating roles. The results can provide theoretical guidance for mega projects to break through the obstacle of technological transformation and enhance innovation efficiency. Full article

The aim of the research was to investigate several xylem sap parameters (onset, sap bleeding duration and intensity, and main chemical components) in four cultivars (‘Cabernet Sauvignon’, ‘Merlot’, ‘Muscat Ottonel’, and ‘Pinot Noir’) grown in the climate of western Romania over three consecutive growing seasons (2022–2024). Understanding early-season sap characteristics is relevant for optimizing vineyard management and improving grape output in fluctuating environmental conditions. Sap onset and duration differed significantly among cultivars and years (p < 0.05), with warmer springs resulting in earlier and longer sap bleeding. ‘Pinot Noir’ consistently exhibited the highest and earliest xylem sap flow (8.2–10.8 mL/vine/day). Chemical profiling revealed cultivar- and year-dependent variation in soluble solids, macro- and micronutrients, proteins, organic acids, and phenolic compounds. ‘Muscat Ottonel’ and ‘Pinot Noir’ had higher phenolic contents, while ‘Merlot’ displayed lower metabolic activity inferred from sap composition. Years with higher precipitation showed reduced phenolic acid and resveratrol concentrations. Principal component analysis highlighted strong effects of both cultivar and season on sap chemistry, with warmer years favoring nutrient- and metabolite-rich profiles, particularly in ‘Pinot Noir’ and ‘Muscat Ottonel’. These findings confirm that xylem sap bleeding is a sensitive indicator of grapevine reactivation, shaped by genotype and climate. Monitoring sap traits at dormancy release can serve as an early diagnostic tool to guide pruning, irrigation, and fertilization and supports the selection of climate-resilient cultivars and rootstock–scion combinations. Full article

Understanding microhabitat preferences of endangered species and the drivers involved in this selection are crucial for understanding their ecology and implementing conservation actions. This issue gains more importance with amphibians, which are known to be constrained by specific environmental conditions and are among the most threatened organisms globally. We assessed shelter preference of Speleomantes strinatii in three different contiguous habitats (mixed broadleaf forest, transitional mixed-chestnut and a chestnut forest used both for fruit and coppice), located at different distances from an Apennine first-order stream. We placed 22 plots in these three habitats and searched for salamanders under the potential available shelters (logs and rocks). Using a Bayesian generalized linear mixed-effects model, we assessed the role of distance from watercourse, shelter type and area in salamanders’ microhabitat selection. As expected, salamanders were mostly found in the plots near the stream. However, stream distance seemed to not be a crucial driver of amphibians’ detection under a shelter. Indeed, salamanders increasingly used wood shelters at greater distances from the stream relative to rocks, suggesting that logs seemed to compensate for the distance from the stream. In the managed habitat, trunks and branches cut during coppicing or chestnut harvest, as well as naturally fallen wood, were often left on the ground, thereby increasing the availability of shelter for salamanders. Our findings highlight how properly managed forests may enable the persistence of forest salamanders, even in human-exploited environments, representing a cost-effective solution for maintaining soil and forest biodiversity. Full article

Human cytomegalovirus (HCMV) is the leading viral cause of congenital infections and causes substantial morbidity and mortality in neonates and immunosuppressed people. Generating an anti-HCMV vaccine is required for preventing viral-associated diseases and infections. Oral vaccines based on attenuated Salmonella are an attractive solution, since these vaccines can be applied orally and easily for mass immunization. In this report, we constructed an attenuated Salmonella strain for the expression of the murine cytomegalovirus (MCMV) M43 protein and studied its ability as an oral vaccine candidate to stimulate antiviral immunity in mice. In orally immunized mice, the constructed vaccine, Sal-M43, elicited both serum IgG and mucosal IgA levels as well as T cell responses that were specific against the MCMV M43 protein. Moreover, the Sal-M43 immunization substantially inhibited the viral growth and infection in various organs and tissues and offered complete immune protection against both intraperitoneal and intranasal MCMV challenges. Thus, the Salmonella-based vaccine expressing the M43 antigen is effective in inducing anti-MCMV immunity. These findings also reveal the promise of developing oral anti-CMV vaccines based on attenuated Salmonella vectors expressing different viral antigens. Full article

Rapid and non-destructive acquisition of soil nutrient information is crucial for precision fertilization and soil quality monitoring. This study aims to establish a Raman spectroscopy-based framework for predicting key soil fertility indicators, including alkali-hydrolyzable nitrogen (AN), total nitrogen (TN), total phosphorus (TP), and organic matter (OM). The framework systematically integrates three typical spectral preprocessing methods (Standard Normal Variate transformation (SNV), Savitzky–Golay first derivative (SG_D1), and wavelet transform (Wavelet)), three feature selection strategies (Recursive Feature Elimination, XGBoost importance, and Random Forest importance), and 14 mainstream regression models to construct a multi-combination modeling system. Model performance was evaluated using five-fold cross-validation, with 80% of samples used for training and 20% for validation in each fold. Preprocessed Raman spectral features served as input variables, while the corresponding nutrient contents were used as outputs. Results showed significant differences in prediction performance across various combinations of preprocessing methods and regression algorithms for the four soil nutrient indicators. For AN prediction, the combination of Raw_SNV preprocessing with ElasticNet and BayesianRidge models achieved the best performance, with Test R² values of 0.713 and 0.721, and corresponding Test NRMSE as low as 0.092. For OM prediction, the same Raw_SNV preprocessing with ElasticNet and BayesianRidge also performed well, yielding Test R² values of 0.825 and 0.832, and Test NRMSE of 0.100 and 0.098, respectively. In TN prediction, both ElasticNet and BayesianRidge under Raw_SNV preprocessing achieved consistent Test R² of 0.74 and Test NRMSE around 0.20, indicating stable reliability. For TP prediction, the BayesianRidge model with Raw_SNV preprocessing outperformed all others with a Test R² of 0.71 and Test NRMSE of just 0.089, followed closely by ElasticNet (Test R² = 0.70, Test NRMSE = 0.092). Overall, the Raw_SNV preprocessing method demonstrated superior performance compared to SG_D1_SNV and Wavelet_SNV. Both BayesianRidge and ElasticNet consistently achieved high R² and low NRMSE across multiple targets, showcasing strong generalization and robustness, making them optimal model choices for Raman spectroscopy-based soil nutrient prediction. This study demonstrates that Raman spectroscopy, when combined with appropriate preprocessing and modeling techniques, can effectively predict soil organic matter and nitrogen in specific soil types under laboratory conditions. These results provide initial methodological insights for future development of intelligent soil nutrient diagnostics. Full article

This study investigates the relationship between land use and soil organic carbon (SOC) storage in tropical Andean ecosystems, introducing a socio-ecological perspective to assess how community conservation perceptions influence SOC storage and contribute to climate change mitigation strategies. Background and Objectives: Land-use change reduces carbon stocks in tropical ecosystems. Focusing on the Las Piedras River basin (Popayan, Colombia), we evaluated SOC storage under four plant cover types—riparian forests (RFs), ecological restoration (ER), natural regeneration (NR), and livestock pastures (LSs)—and examined its association with local conservation perceptions. Materials and Methods: SOC storage at 30 cm depth, carbon inputs and outputs, and soil physicochemical properties were measured across land-use types. Conservation perceptions were assessed through 65 community surveys. Data analyses included ANOVA, principal component analysis, and multinomial logistic regression. Results: SOC storage was highest in RFs (148.68 Mg ha⁻¹), followed by ER and LSs, and lowest in NR (97.30 Mg ha⁻¹). A positive relationship was observed between high conservation perception and greater SOC content. Conclusions: SOC storage is strongly influenced by land use and community conservation values. Active restoration efforts, coupled with environmental education, are essential for enhancing the socio-ecological resilience of these ecosystems. Full article

The combined effects of soil properties, zinc (Zn), and chloride ion (Cl⁻) concentrations on Zn distribution across soil fractions are poorly understood, even though zinc chloride (ZnCl₂) contamination in industrial soils is a major source of mobile Zn and poses significant environmental risks. This study aimed to (1) assess how the soil type, physicochemical properties, and Zn concentration affect Zn distribution in Community Bureau of Reference (BCR)-extracted fractions; (2) evaluate the impact of Cl⁻ on Zn mobility; and (3) develop predictive models for mobile and stable Zn fractions based on soil characteristics. Zn mobility was analyzed in 18 soils differing in Zn and Cl⁻, pH, specific surface area (SSA), organic matter (OM), and texture (sand, silt, clay (CLY)), using a modified BCR method. Zn fractions were measured by atomic absorption spectroscopy (AAS). Analysis of Covariance was used to assess Zn distribution across soil types, while Zn fractions were modeled using non-linear regression (NLR). The results showed that mobile Zn increased with the total Zn, and that the soil type and Zn levels influenced Zn distribution in soils contaminated with ZnCl₂ (Zn 304–2136 mg·kg⁻¹ d.m.; Cl⁻ 567–2552 mg·kg⁻¹; pH 3.5–7.5; CLY 11–22%; SSA 96–196 m²·g⁻¹; OM 0–4.8%). Although Cl⁻ enhanced Zn mobility, its effect was weaker than that of Zn. Predictive models based on the total Zn, SSA, and CLY accurately estimated Zn in mobile and stable fractions (R > 0.92), whereas the effects of the pH and OM, although noticeable, were not statistically significant. Full article