Search Results (178)

This study investigates the presence, origin, and associated ecological and human health risks of polycyclic aromatic hydrocarbons (PAHs) in soils from uncultivated lands and beach sediments within the Yellow River Delta (YRD), China. The measured concentrations of 16 priority PAHs in soils spanned 24.97–326.42 ng/g (mean: 130.88 ng/g), while concentrations in sediments ranged from 46.17 to 794.32 ng/g, averaging 227.22 ng/g. In terms of composition, low-molecular-weight PAHs predominated in soil samples, whereas high-molecular-weight compounds were more prevalent in sediments. The positive matrix factorization (PMF) model results suggested that petroleum pollution and fuel combustion were the main sources of PAHs in soils, whereas the contribution in sediments was derived from petroleum and traffic pollution. The ecological risk assessment results indicated that there existed no obvious ecological risk of soil PAHs, but sediment PAHs could negatively impact the surrounding ecological environment, especially in the northern coastal beach area. In addition, soil PAHs posed no potential carcinogenic risk to humans. Further pollution prevention and management measures are required in this region to ensure the safety of the environment. Full article

Leaf loss caused by pest infestations poses a serious threat to forest health. The leaf loss rate (LLR) refers to the percentage of the overall tree-crown leaf loss per unit area and is an important indicator for evaluating forest health. Therefore, rapid and accurate acquisition of the LLR via remote sensing monitoring is crucial. This study is based on drone hyperspectral and LiDAR data as well as ground survey data, calculating hyperspectral indices (HSI), multispectral indices (MSI), and LiDAR indices (LI). It employs Savitzky–Golay (S–G) smoothing with different window sizes (W) and polynomial orders (P) combined with recursive feature elimination (RFE) to select sensitive features. Using Random Forest Regression (RFR) and Convolutional Neural Network Regression (CNNR) to construct a multidimensional (horizontal and vertical) estimation model for LLR, combined with LiDAR point cloud data, achieved a three-dimensional visualization of the leaf loss rate of trees. The results of the study showed: (1) The optimal combination of HSI and MSI was determined to be W11P3, and the LI was W5P2. (2) The optimal combination of the number of sensitive features extracted by the RFE algorithm was 13 HSI, 16 MSI, and hierarchical LI (2 in layer I, 9 in layer II, and 11 in layer III). (3) In terms of the horizontal estimation of the defoliation rate, the model performance index of the CNNR_HSI model (MPI = 0.9383) was significantly better than that of RFR_MSI (MPI = 0.8817), indicating that the continuous bands of hyperspectral could better monitor the subtle changes of LLR. (4) The I-CNNR_HSI+LI, II-CNNR_HSI+LI, and III-CNNR_HSI+LI vertical estimation models were constructed by combining the CNNR_HSI model with the best accuracy and the LI sensitive to different vertical levels, respectively, and their MPIs reached more than 0.8, indicating that the LLR estimation of different vertical levels had high accuracy. According to the model, the pixel-level LLR of the sample tree was estimated, and the three-dimensional display of the LLR for forest trees under the pest stress of larch caterpillars was generated, providing a high-precision research scheme for LLR estimation under pest stress. Full article

The Zhurong rover of the Tianwen-1 mission has detected sulfates in its landing area. The analysis of these sulfates provides scientific evidence for exploring past hydration conditions and atmospheric evolution on Mars. As a non-contact technique with long-range detection capability, Laser-Induced Breakdown Spectroscopy (LIBS) is widely used for elemental identification on Mars. However, quantitative analysis of anionic elements using LIBS remains challenging due to the weak characteristic spectral lines of evaporite salt elements, such as sulfur, in LIBS spectra, which provide limited quantitative information. This study proposes a quantitative analysis method for sulfur in sulfate-containing Martian analogs by leveraging spectral line correlations, full-spectrum information, and prior knowledge, aiming to address the challenges of sulfur identification and quantification in Martian exploration. To enhance the accuracy of sulfur quantification, two analytical models for high and low sulfur concentrations were developed. Samples were classified using infrared spectroscopy based on sulfur content levels. Subsequently, multimodal deep learning models were developed for quantitative analysis by integrating LIBS and infrared spectra, based on varying concentrations. Compared to traditional unimodal models, the multimodal method simultaneously utilizes elemental chemical information from LIBS spectra and molecular structural and vibrational characteristics from infrared spectroscopy. Considering that sulfur exhibits distinct absorption bands in infrared spectra but demonstrates weak characteristic lines in LIBS spectra due to its low ionization energy, the combination of both spectral techniques enables the model to capture complementary sample features, thereby effectively improving prediction accuracy and robustness. To validate the advantages of the multimodal approach, comparative analyses were conducted against unimodal methods. Furthermore, to optimize model performance, different feature selection algorithms were evaluated. Ultimately, an XGBoost-based feature selection method incorporating prior knowledge was employed to identify optimal LIBS spectral features, and the selected feature subsets were utilized in multimodal modeling to enhance stability. Experimental results demonstrate that, compared to the BPNN, SVR, and Inception unimodal methods, the proposed multimodal approach achieves at least a 92.36% reduction in RMSE and a 46.3% improvement in R². Full article

The artificial ground freezing method (AGF) is widely used in underground construction to reinforce the ground and ensure construction safety. This study systematically evaluates the implementation of the artificial ground freezing method in the construction of a metro tunnel cross-passage, with a focus on analyzing the soil’s thermo-mechanical behavior and assessing safety performance throughout the construction process. A combined approach integrating field monitoring and refined three-dimensional numerical simulation using FLAC3D is adopted, considering critical factors, such as freezing pipe inclination, thermo-mechanical coupling, and ice–water phase transitions. Both field data and simulation results demonstrate that increasing the density of freezing pipes accelerates temperature reduction and intensifies frost heave-induced displacements near the pipes. After 45 days of active freezing, the freezing curtain reaches a thickness of 3.7 m with an average temperature below −10 °C. Extending the freezing duration beyond this period yields negligible improvement in curtain performance. Frost heave deformation develops rapidly during the initial phase and stabilizes after approximately 25 days, with maximum vertical displacements reaching 12 cm. Significant stress concentrations occur in the soil adjacent to the freezing pipes, with shield tunnel segments experiencing up to 5 MPa of stress. Thaw settlement is primarily concentrated in areas previously affected by frost heave, with a maximum settlement of 3 cm. Even after 45 days of natural thawing, a frozen curtain approximately 3.3 m thick remains intact, maintaining sufficient structural strength. The refined numerical model accurately captures the mechanical response of soil during the freezing and thawing processes under realistic engineering conditions, with field monitoring data validating its effectiveness. This research provides valuable guidance for managing construction risks and ensuring safety in similar cross-passage and cross-river tunnel projects, with broader implications for underground engineering requiring precise control of frost heave and thaw settlement. Full article

Meloxicam has been identified as an adjuvant therapeutic component in the management of bovine uterine diseases, exhibiting anti-inflammatory and antioxidant effects. However, the mechanisms underlying its antioxidant actions in the context of bovine uterine diseases remain incompletely understood. The objective of this research was to determine whether meloxicam exerts its antioxidant effects through the Nrf2/HO-1 signaling pathway. By employing N-acetylcysteine (NAC), a scavenger of reactive oxygen species (ROS), along with inhibitors directed against heme oxygenase-1 (HO-1) or nuclear factor erythroid 2-related factor 2 (Nrf2), we investigated the dynamic changes in oxidative stress markers (ROS and malondialdehyde) and antioxidant indices (comprising catalase, superoxide dismutase, and glutathione), as well as the expression profiles of Nrf2 and inflammation-associated genes and proteins in bovine endometrial epithelial cells (BEECs) subjected to lipopolysaccharide (LPS) stimulation. As a result, meloxicam alleviated the LPS-induced elevation of oxidative stress marker levels and the reduction in antioxidant enzyme activities and antioxidant substance contents in BEECs. Compared to NAC, meloxicam demonstrated superior efficacy in activating the Nrf2 pathway, with the promotion of NRF2 expression (~1.6-fold) and nuclear translocation. The pretreatment of cells with HO-1 or Nrf2 inhibitors markedly attenuated the antioxidant activity of meloxicam. In summary, meloxicam primarily alleviates LPS-induced oxidative stress through the activation of the Nrf2/HO-1 pathway in BEECs. Full article

Background/Objectives: Individuals with childhood obesity exhibit significant metabolic heterogeneity, necessitating precise biomarkers for risk stratification and assessment. This multi-omics investigation characterizes metabolic and microbial signatures underlying divergent metabolic phenotypes in the context of pediatric obesity. Methods: We analyzed 285 Chinese children (5–7 years) stratified into five groups: wasting (WAS, n = 55), metabolically healthy/unhealthy and normal weight (MHWH, n = 54; MUWH, n = 67), and metabolically healthy/unhealthy obesity (MHO, n = 36; MUO, n = 73). Untargeted metabolomics (Orbitrap ID-X Tribrid™) and 16S rRNA sequencing were integrated with multivariate analyses (OPLS-DA with VIP > 1, FDR < 0.05; Maaslin 2 with TSS normalization and BH correction, FDR < 0.10). Results: Analysis identified 225 differential metabolites and 12 bacterial genera. The proportion of steroids and their derivatives among differential metabolites in the MUO/MHO group was significantly lower than that in the OVOB/NOR and OVOB/WAS groups (2.12% vs. 7.9–14.1%). MUO displayed elevated C17 sphinganine and LysoPC (O-18:0) levels but reduced PI (16:0/14:1) levels. In contrast, OVOB showed upregulated glycerol phospholipids (LPCs and PSs) and downregulated PE species (e.g., PE(16:0/16:0)) as well as gut microbiota dysbiosis characterized by a higher Firmicutes/Bacteroidetes (F/B) ratio (2.07 vs. 1.24 in controls, p = 0.009) and reduced α diversity (Ace index, Chao1 index, and Shannon index values were lower in the OVOB group, Shannon index: 2.96 vs. 3.45, p = 0.03). SCFA-producing genera were negatively correlated with the OVOB group, while positively associated with PE(16:0/16:0). Internal validation showed differential metabolites had potential predictive efficacy for MUO/MHO (AUC = 0.967) and OVOB/NOR (AUC = 0.888). Conclusions: We identified distinct lipid disruptions characterizing obesity subtypes, including steroid/terpene deficits and sphingolipid/ether lipid dysregulation in the MUO/MHO groups as well as phospholipid imbalance (↑LPC/PS↓PE) in the OVOB/NOR groups. The gut microbiota exhibited a profile characterized by low diversity, an increased F/B ratio, and a reduced abundance of SCFA-producing genera. These findings suggest potential biomarkers for childhood obesity stratification, though further validation is warranted. Full article

Freshwater fish is facing a great crisis due to the looming threat of biodiversity loss. Certain important target areas are difficult to survey owing to their accessibility, making them susceptible to data deficiencies. In this study, we surveyed 52 sites using environmental DNA techniques to investigate fish biodiversity in the Chishui River Basin of the Yangtze River, China. A total of 96,031 valid fish sequences were read, resulting in the identification of 77 species belonging to six orders, 62 genera, and 18 families. The dominant orders were Cypriniformes, Siluriformes, and Perciformes. Among the identified fishes, 71 were native and six were exotic, with the native fishes including 16 endemic fishes from the upper reaches of the Yangtze River. The Shannon–Wiener and richness indices of the tributaries in the upstream section were significantly higher than those of the tributaries in the downstream section. The Datong River is the most diverse secondary tributary of the Chishui River. Among the environmental factors in the Chishui River Basin, altitude and electrical conductivity had the greatest influence on fish diversity (p < 0.01). Our findings highlight the application of environmental DNA technology to modern biodiversity surveys and illustrate that the Chishui River Basin is primarily affected by environmental factors at this stage. However, continuing efforts are needed to protect freshwater biodiversity, and additional research is required to better understand the complex interplay between human activity and environmental factors. Full article

Meat color is the most intuitive measure of meat quality and has a significant impact on consumer preference. To explore the molecular mechanisms affecting duck pectoralis meat color, the phenotypic traits of Cherry Valley duck (CV, eight males and eight females) and Huai Fu duck (HF, eight males and eight females) were compared; three males and three females of each variety were later selected for transcriptomic and metabolomic analyses to reveal key molecular processes. This study found that the expression level of CA3 (carbonic anhydride enzyme 3) is positively correlated with the meat color phenotype, suggesting that it may play a positive regulatory role in the formation of meat color. The expression trend of the ST13 gene is opposite to the phenotype, suggesting that it may play a negative regulatory role. With the participation of CA3 and NDUF family genes (such as NDUFC2, NDUFB2, etc.), the oxidative phosphorylation pathway plays a key role in meat color formation by regulating the oxygenation/deoxygenation state of myoglobin and intracellular pH value. Although the effects of these genes and pathways on meat color have been discovered, their specific genetic mechanisms and molecular functions still need further verification. This provides important clues for further understanding the molecular mechanism of meat color formation and may offer potential molecular targets for improving meat color or breeding new varieties. Full article

Leaf area index (LAI) serves as a critical indicator for evaluating crop growth and guiding field management practices. While spectral information (vegetation indices and texture features) extracted from multispectral sensors mounted on unmanned aerial vehicles (UAVs) holds promise for LAI estimation, the limitations of single-texture features necessitate further exploration. Therefore, this study conducted field experiments over two consecutive years (2021–2022) to collect winter oilseed rape LAI ground truth data and corresponding UAV multispectral imagery. Vegetation indices were constructed, and canopy texture features were extracted. Subsequently, a correlation matrix method was employed to establish novel randomized combinations of three-dimensional texture indices. By analyzing the correlations between these parameters and winter oilseed rape LAI, variables with significant correlations (p < 0.05) were selected as model inputs. These variables were then partitioned into distinct combinations and input into three machine learning models—Support Vector Machine (SVM), Backpropagation Neural Network (BPNN), and Extreme Gradient Boosting (XGBoost)—to estimate winter oilseed rape LAI. The results demonstrated that the majority of vegetation indices and texture features exhibited significant correlations with LAI (p < 0.05). All randomized texture index combinations also showed strong correlations with LAI (p < 0.05). Notably, the three-dimensional texture index NDTTI exhibited the highest correlation with LAI (R = 0.725), derived from the spatial combination of DIS5, VAR5, and VAR3. Integrating vegetation indices, texture features, and three-dimensional texture indices as inputs into the XGBoost model yielded the highest estimation accuracy. The validation set achieved a determination coefficient (R²) of 0.882, a root mean square error (RMSE) of 0.204 cm²cm⁻², and a mean relative error (MRE) of 6.498%. This study provides an effective methodology for UAV-based multispectral monitoring of winter oilseed rape LAI and offers scientific and technical support for precision agriculture management practices. Full article

Background: In dairy cows, the stress-related cortisol level increases the susceptibility to postpartum uterine diseases. Oxidative stress is an important component of the disease process and causes morphological and functional alterations in the bovine endometrium. Selenium (Se) has an antioxidant property, and an appropriate Se supplementation is recommended to enhance bovine disease resistance. Methods and results: Here, we aimed to answer two questions: (1) how does cortisol affect the oxidative status of bovine endometrial cells; and (2) does Se supplementation protect cells from oxidative injury with a high cortisol condition? The oxidative stress of primary bovine endometrial epithelial cells (BEECs) was established by Escherichia coli lipopolysaccharide (LPS) stimulation, as marked by the increased oxidative markers and the suppressions of antioxidant indicators and Nrf2 signaling. In the absence of LPS, cortisol levels of 15 ng/mL showed a more significant antioxidative effect than cortisol levels of 5 and 30 ng/mL. In the presence of LPS, cortisol levels of 15 and 30 ng/mL elicited antioxidation, whereas 5 ng/mL of cortisol did not. Regardless of LPS stimulation, Se pretreatment of 1, 2, and 4 μM protected BEEC from oxidative stress, as evidenced by the decreased oxidative markers, increased antioxidant indices, and the activated Nrf2 signaling. With the presence of 30 ng/mL of cortisol, there was an enhanced Se antioxidant effect, which can be abolished by the block of cortisol receptor. Conclusions: Both cortisol and Se elicited antioxidant properties in BEEC through the Nrf2 pathway. In addition, the Se antioxidation was enhanced by cortisol. Full article

This paper presents an E-band four-channel multiplexer based on a turnstile junction. The proposed multiplexer consists of a power distribution unit featuring a turnstile junction topology and four Chebyshev bandpass filters. Thanks to the implementation of a rotating gate connection structure as the distribution unit, the overall compactness was enhanced, and the complexity of optimization was significantly reduced. Furthermore, this configuration offers a well-organized spatial port distribution, facilitating scalability for additional channels. According to the frequency band planning and design requirements of the communication system, an E-band four-channel multiplexer was designed and manufactured using high-precision computer numerical control (CNC) milling technology, achieving an error margin of ±5 μm. The experimental results indicate that the passbands are 70.6–73.07 GHz, 73.7–76.07 GHz, 82.55–82.9 GHz, and 83.4–85.9 GHz. The in-band insertion loss of each channel is below 1.7 dB, while the return loss at the common port exceeds 12 dB. The measured results align closely with simulations, demonstrating promising potential for practical applications. Full article

In order to investigate the changes in winter wheat yield and the factors influencing it, five meteorological factors—such as rainfall and soil moisture—collected from the experimental area between 2010 and 2022 were used as characteristic features. A combined model of GNN (Graph Neural Network), based on the Fourier transform and the Random Forest algorithm was developed to predict winter wheat yield. Matrix multiplication in Fourier space was performed to predict yield, while the Random Forest algorithm was employed to quantify the contribution of various yield factors to winter wheat yield. The combined model effectively captured the dynamic dependencies between yield factors and time series, improving predictive accuracy by 5.00%, 10.00%, and 27.00%, and reducing the root mean square error by 26.26%, 29.31%, and 88.20%, respectively, compared to the StemGNN, Informer, and Random Forest models. The predicted outputs ranged from 520 to 720 g/m², with an average error of 2.69% compared to the actual measure outputs. Under the insufficient real-time irrigation mode, winter wheat yield was highest at 90% irrigation upper limit and 70% irrigation lower limit, with a medium fertilization level (850 mg/kg). The yield showed an overall decreasing trend as both irrigation limits and fertilizer application decreased. Rainfall and soil moisture were the most significant factors influencing winter wheat yield, followed by air temperature and evapotranspiration. Solar radiation and sunshine duration had the least impact. The results of this study provide a valuable reference for accurately predicting winter wheat yield. Full article

During the postpartum period, domestic ruminants suffer elevated endogenous cortisol levels, which are associated with an increased risk of uterine infections. Selenium is a trace mineral nutrient with beneficial impacts on animals. The study aimed to investigate whether selenium yeast (SeY) could attenuate Escherichia coli (E. coli)-induced endometrial injury in goats with high cortisol background. Goats were examined after oral SeY administration for 21 days and were treated with glacial acetic acid, E. coli, and hydrocortisone to establish an endometritis model with high cortisol background. The results showed that endometrial injury caused by E. coli was aggravated under high cortisol background. Supplementation with SeY alleviated endometrial inflammation and serum LDH content. The mRNA expression of pro-inflammatory cytokines and defensin beta 2 and the phosphorylation level of the mitogen-activated protein kinase (MAPK) and nuclear factor kappa-b (NF-κB) signaling pathways were decreased by SeY supplementation. Total antioxidant capacity and antioxidant enzymes activities were increased by SeY supplementation, but malondialdehyde and 4-hydroxynonenal content were decreased. Moreover, nuclear factor erythroid-2 related factor 2 (NRF2) in the nucleus, heme oxygenase-1, and NAD(P)H quinone dehydrogenase 1 were increased by SeY supplementation. So, supplementation with SeY alleviated E. coli-induced endometritis in goats by activating the NRF2 pathway and inhibiting the activation of the MAPK and NF-κB pathways under postpartum stress. Full article

Environmental DNA (eDNA) metabarcoding is a powerful method for monitoring aquatic biodiversity and evaluating ecosystem health. In this study, we applied eDNA metabarcoding and a multi-species biotic integrity index (Mt-IBI), constructed by selecting and screening core metrics to capture key ecological responses, to assess the Irtysh River Basin in Xinjiang, China, analyzing samples from 52 sites. The community structure showed high sensitivity to environmental stressors, with dissolved oxygen (DO), total nitrogen (TN), and elevation being key factors, while alien fish richness negatively impacted ecosystem health. These findings highlight the importance of maintaining environmental parameters and controlling invasive species, demonstrating the potential of the Mt-IBI for early detection of ecological degradation and guiding freshwater conservation. Full article

Phosphogypsum (PG), a by-product of phosphoric acid production, contains high levels of fluorine and phosphorus impurities, which negatively impact the strength and setting time of PG-based cement materials and pose environmental risks. This study explores a dual approach combining physical adsorption using zeolite powder and chemical modification with quicklime (CaO) to immobilize these impurities. The composition of 90 wt.% PG, 5 wt.% zeolite powder, and 5 wt.% quicklime reduces the soluble phosphorus to below the detection limits and significantly lowers the free water content in the PG. Through SEM, XRD, and FT-IR analyses, it was found that zeolite powder adsorbs fluorine and phosphorus through encapsulation, while quicklime chemically reacts to form insoluble calcium phosphate and calcium fluoride. This transformation decreases the solubility, mitigating potential environmental contamination. The combination of physical adsorption and chemical conversion provides a sustainable strategy to reduce environmental hazards and enhance PG’s suitability for cement-based materials. The findings from this research offer a promising pathway for the sustainable utilization of PG, providing a mechanism for its safe incorporation into building materials, while addressing both environmental and material performance concerns. Full article