Search Results (787)

This study was conducted to investigate the effects of puffed jujube powder (PJP) supplementation in the diet on the slaughter characteristics, growth performance, meat quality, and serum antioxidant capacity of Hainan Black (HB) goats. Twenty-four healthy male HB goats, three months old with an initial body weight of 15.12 ± 3.67 kg, were randomly divided into three groups: the 10% PJP group (basal diet plus 10% PJP); the 20% PJP group (basal diet plus 20% PJP); and the control group (basal diet only). After a 10-day adaptation period, a feeding trial was carried out for 90 days in an ad libitum diet environment. The results show that the final body weight of the 20% PJP group was markedly higher (p < 0.05) than that of the control group (22.58 ± 0.94 kg vs. 20.45 ± 1.01 kg). The average daily gain of the 20% PJP group was 83.44 ± 1.78 g/d, which was substantially greater (p < 0.05) than the 59.22 ± 2.13 g/d of the control group. The feed intake of the 20% PJP group was 713.10 ± 4.54 g/d, notably higher (p < 0.05) than the 498.20 ± 4.33 g/d of the control group. In terms of slaughter characteristics, the carcass weight of the 20% PJP group was 13.99 ± 1.22 kg, considerably heavier (p < 0.05) than the 11.79 ± 1.38 kg of the control group. The muscle weight of the 20% PJP group was 11.43 ± 1.42 kg, distinctly greater (p < 0.05) than the 9.59 ± 1.99 kg of the control group. The slaughter rate of the 20% PJP group was 42.41%, showing a notable increase (p < 0.05) compared with the 37.42% of the control group, and the net meat rate of the 20% PJP group was 34.65%, with a significant rise (p < 0.05) compared with the 30.43% of the control group. Regarding serum antioxidant capacity and meat quality, the activities of serum antioxidant enzymes, superoxide dismutase (SOD) and catalase (CAT), were conspicuously increased (p < 0.05) in the 20% PJP group. The meat shear force of the 20% PJP group was decreased by 12.9%, and the cooking loss was improved by 8.9% in comparison with the control group. In conclusion, the supplementation of 20% PJP in the diet was demonstrated to enhance the growth performance, improve the meat quality, and boost the antioxidant status of HB goats, thus presenting a feasible strategy for optimizing tropical goat production systems. Full article

Fecal microbiota transplantation (FMT) promotes growth performance and intestinal development in yellow-feathered broilers, but whether the virome and metabolites contribute to its growth-promoting effect remains unclear. This study removed the microbiota from FMT filtrate using a 0.45 μm filter membrane, retaining the virome and metabolites to perform fecal virome transplantation (FVT), aiming to investigate its regulatory role in broiler growth. Healthy yellow-feathered broilers with high body weights (top 10% of the population) were used as FVT donors. Ninety-six 8-day-old healthy male yellow-feathered broilers (95.67 ± 3.31 g) served as FVT recipients. Recipient chickens were randomly assigned to a control group and an FVT group. The control group was gavaged with 0.5 mL of normal saline daily, while the FVT group was gavaged with 0.5 mL of FVT solution daily. Growth performance, immune and antioxidant capacity, intestinal development and related gene expression, and microbial diversity were measured. The results showed that FVT improved the feed utilization rate of broilers (the feed conversion ratio decreased by 3%; p < 0.05), significantly increased jejunal length (21%), villus height (69%), and crypt depth (84%) (p < 0.05), and regulated the jejunal barrier: insulin-like growth factor-1 (IGF-1) (2.5 times) and Mucin 2 (MUC2) (63 times) were significantly upregulated (p < 0.05). FVT increased the abundance of beneficial bacteria Lactobacillales. However, negative effects were also observed: Immunoglobulin A (IgA), Immunoglobulin G (IgG), Immunoglobulin M (IgM), Interleukin-1 beta (IL-1β), Interleukin-6 (IL-6), Tumor Necrosis Factor-alpha (TNF-α), and Interferon-gamma (IFN-γ) in broilers were significantly upregulated (p < 0.05), indicating immune system overactivation. Duodenal barrier-related genes Mucin 2 (MUC2), Occludin (OCLN), Claudin (CLDN1), and metabolism-related genes solute carrier family 5 member 1 (SLC5A1) and solute carrier family 7 member 9 (SLC7A9) were significantly downregulated (p < 0.05). The results of this trial demonstrate that, besides the microbiota, the gut virome and metabolites are also functional components contributing to the growth-promoting effect of FMT. The differential responses in the duodenum and jejunum reveal spatial heterogeneity and dual effects of FVT on the intestine. The negative effects limit the application of FMT/FVT. Identifying the primary functional components of FMT/FVT to develop safe and targeted microbial preparations is one potential solution. Full article

The transition from conchocelis to conchosporangia in Pyropia haitanensis represents a pivotal stage in its life cycle. As a commercially vital red alga, P. haitanensis plays a dominant role in global nori production. The transition governing its sporulation efficiency is pivotal for aquaculture success, yet the underlying regulatory mechanisms, especially their integration with metabolic cues such as polyamines, remain poorly understood. This study uncovered a critical role for the polyamine spermine (SPM) in promoting conchosporangial formation, mediated through the signaling activity of superoxide anions (O₂·⁻). Treatment with SPM markedly elevated O₂·⁻ levels, an effect that was effectively inhibited by the NADPH oxidase inhibitor diphenyliodonium chloride (DPI), underscoring the role of O₂·⁻ as a key signaling molecule. Transcriptomic analysis revealed that SPM enhanced photosynthesis, carbon assimilation, and respiratory metabolism, while simultaneously activating antioxidant enzymes, such as superoxide dismutase (SOD), ascorbate peroxidase (APX), and catalase (CAT), to regulate hydrogen peroxide (H₂O₂) levels and maintain redox homeostasis. Furthermore, SPM upregulated genes associated with photosynthetic carbon fixation and the C₂ oxidative photorespiration pathway, supplying the energy and metabolic resources necessary for this developmental transition. These findings suggested that SPM orchestrated O₂·⁻ signaling, photosynthetic activity, and antioxidant defenses to facilitate the transition from conchocelis to conchosporangia in P. haitanensis. Full article

Huanglongbing (HLB), caused by Candidatus Liberibacter asiaticus (CLas), is the most devastating disease threatening global citrus production. Although no commercial citrus varieties exhibit complete HLB resistance, genotype-specific tolerance variations remain underexplored. This study conducted a comparative transcriptomic profiling of six commercially citrus cultivars in South China, four susceptible cultivars (C. reticulata cv. Tankan, Gongkan, Shatangju, and C. sinensis Osbeck cv. Newhall), and two tolerant cultivars (C. limon cv. Eureka; C. maxima cv Guanxi Yu) to dissect molecular mechanisms underlying HLB responses. Comparative transcriptomic analyses revealed extensive transcriptional reprogramming, with tolerant cultivars exhibiting fewer differentially expressed genes (DEGs) and targeted defense activation compared to susceptible genotypes. The key findings highlighted the genotype-specific regulation of starch metabolism, where β-amylase 3 (BAM3) was uniquely upregulated in tolerant varieties, potentially mitigating starch accumulation. Immune signaling diverged significantly: tolerant cultivars activated pattern-triggered immunity (PTI) via receptor-like kinases (FLS2) and suppressed ROS-associated RBOH genes, while susceptible genotypes showed the hyperactivation of ethylene signaling and oxidative stress pathways. Cell wall remodeling in susceptible cultivars involved upregulated xyloglucan endotransglucosylases (XTH), contrasting with pectin methylesterase induction in tolerant Eureka lemon for structural reinforcement. Phytohormonal dynamics revealed SA-mediated defense and NPR3/4 suppression in Eureka lemon, whereas susceptible cultivars prioritized ethylene/JA pathways. These findings delineate genotype-specific strategies in citrus–CLas interactions, identifying BAM3, FLS2, and cell wall modifiers as critical targets for breeding HLB-resistant cultivars through molecular-assisted selection. This study provides a foundational framework for understanding host–pathogen dynamics and advancing citrus immunity engineering. Full article

Stable oxygen isotopes in tree rings (δ¹⁸O) serve as important proxies for climate change and offer unique advantages for climate reconstruction in arid and semi-arid regions. We established an annual δ¹⁸O chronology spanning 1964–2023 using Juniperus excelsa tree-ring samples collected from the Alborz Mountains in Iran. We analyzed relationships between δ¹⁸O and key climate variables: precipitation, temperature, Palmer Drought Severity Index (PDSI), vapor pressure (VP), and potential evapotranspiration (PET). Correlation analysis reveals that tree-ring δ¹⁸O is highly sensitive to hydroclimatic variations. Tree-ring cellulose δ¹⁸O shows significant negative correlations with annual total precipitation and spring PDSI, and significant positive correlations with spring temperature (particularly maximum temperature), April VP, and spring PET. The strongest correlation occurs with spring PET. These results indicate that δ¹⁸O responds strongly to the balance between springtime moisture supply (precipitation and soil moisture) and atmospheric evaporative demand (temperature, VP, and PET), reflecting an integrated signal of both regional moisture availability and energy input. The pronounced response of δ¹⁸O to spring evaporative conditions highlights its potential for capturing high-resolution changes in spring climatic conditions. Our δ¹⁸O series remained stable from the 1960s to the 1990s, but showed greater interannual variability after 2000, likely linked to regional warming and climate instability. A comparison with the δ¹⁸O variations from the eastern Alborz Mountains indicates that, despite some differences in magnitude, δ¹⁸O records from the western and eastern Alborz Mountains show broadly similar variability patterns. On a larger climatic scale, δ¹⁸O correlates significantly and positively with the Niño 3.4 index but shows no significant correlation with the Arctic Oscillation (AO) or the North Atlantic Oscillation (NAO). This suggests that ENSO-driven interannual variability in the tropical Pacific plays a key role in regulating regional hydroclimatic processes. This study confirms the strong potential of tree-ring oxygen isotopes from the Alborz Mountains for reconstructing hydroclimatic conditions and high-frequency climate variability. Full article

The rapid integration of complex sensors and electronic control units (ECUs) in autonomous vehicles significantly increases cybersecurity risks in vehicular networks. Although the Controller Area Network (CAN) is efficient, it lacks inherent security mechanisms and is vulnerable to various network attacks. The traditional Intrusion Detection System (IDS) makes it difficult to effectively deal with the dynamics and complexity of emerging threats. To solve these problems, a lightweight vehicular network intrusion detection framework based on Dynamic Feature Fusion Federated Learning (DFF-FL) is proposed. The proposed framework employs a two-stream architecture, including a transformer-augmented autoencoder for abstract feature extraction and a lightweight CNN-LSTM–Attention model for preserving temporal and local patterns. Compared with the traditional theoretical framework of the federated learning, DFF-FL first dynamically fuses the deep feature representation of each node through the transformer attention module to realize the fine-grained cross-node feature interaction in a heterogeneous data environment, thereby eliminating the performance degradation caused by the difference in feature distribution. Secondly, based on the final loss $L_{AE}\left(X,\widehat{X}\right)$ index of each node, an adaptive weight adjustment mechanism is used to make the nodes with excellent performance dominate the global model update, which significantly improves robustness against complex attacks. Experimental evaluation on the CAN-Hacking dataset shows that the proposed intrusion detection system achieves more than 99% F1 score with only 1.11 MB of memory and 81,863 trainable parameters, while maintaining low computational overheads and ensuring data privacy, which is very suitable for edge device deployment. Full article

The goal of single-image super-resolution (SISR) tasks is to generate high-definition images from low-quality inputs, with practical uses spanning healthcare diagnostics, aerial imaging, and surveillance systems. Although cnns have considerably improved image reconstruction quality, existing methods still face limitations, including inadequate restoration of high-frequency details, high computational complexity, and insufficient adaptability to complex scenes. To address these challenges, we propose an Omni-dimensional Dynamic Convolutional Network (ODConvNet) tailored for SISR tasks. Specifically, ODConvNet comprises four key components: a Feature Extraction Block (FEB) that captures low-level spatial features; an Omni-dimensional Dynamic Convolution Block (DCB), which utilizes a multidimensional attention mechanism to dynamically reweight convolution kernels across spatial, channel, and kernel dimensions, thereby enhancing feature expressiveness and context modeling; a Deep Feature Extraction Block (DFEB) that stacks multiple convolutional layers with residual connections to progressively extract and fuse high-level features; and a Reconstruction Block (RB) that employs subpixel convolution to upscale features and refine the final HR output. This mechanism significantly enhances feature extraction and effectively captures rich contextual information. Additionally, we employ an improved residual network structure combined with a refined Charbonnier loss function to alleviate gradient vanishing and exploding to enhance the robustness of model training. Extensive experiments conducted on widely used benchmark datasets, including DIV2K, Set5, Set14, B100, and Urban100, demonstrate that, compared with existing deep learning-based SR methods, our ODConvNet method improves Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), and the visual quality of SR images is also improved. Ablation studies further validate the effectiveness and contribution of each component in our network. The proposed ODConvNet offers an effective, flexible, and efficient solution for the SISR task and provides promising directions for future research. Full article

Intestinal inflammation involves barrier impairment, immune hyperactivation, and oxidative stress imbalance. Bioactive polysaccharides universally alleviate inflammation via anti-inflammatory, antioxidant, and microbiota-modulating effects, yet exhibit distinct core mechanisms. Elucidating these differences is vital for targeted polysaccharide applications. This research examines distinct regulatory pathways through which diverse bioactive polysaccharides mitigate lipopolysaccharide-triggered intestinal inflammation in male Kunming (KM) mice. This experiment employed Lentinula edodes polysaccharide (LNT), Auricularia auricula polysaccharide (AAP), Cordyceps militaris polysaccharide (CMP), Lycium barbarum polysaccharide (LBP), and Brassica rapa polysaccharide (BRP). The expression levels of biomarkers associated with the TLR4 signaling pathway, oxidative stress, and intestinal barrier function were quantified, along with comprehensive gut microbiota profiling. The results showed that all five polysaccharides alleviated inflammatory responses in mice by inhibiting inflammatory cytokine release, reducing oxidative damage, and modulating gut microbiota, but their modes of action differed: LBP significantly suppressed the TLR-4/MyD88 signaling pathway and its downstream pro-inflammatory cytokine expression, thereby blocking inflammatory signal transduction and reducing oxidative damage; LNT and CMP enhanced the body’s antioxidant capacity by increasing antioxidant enzyme activities and decreasing malondialdehyde (MDA) levels; AAP and BRP enriched Akkermansia (Akk.) within the Verrucomicrobia (Ver.) phylum, upregulating tight junction protein expression to strengthen the intestinal mucosal barrier and indirectly reduce oxidative damage. This research demonstrates that different polysaccharides alleviate inflammation through multi-target synergistic mechanisms: LBP primarily inhibits inflammatory pathways; AAP and BRP focus on intestinal barrier protection and microbiota modulation; and LNT and CMP exert effects via antioxidant enzyme activation. These data support designing polysaccharide blends that leverage complementary inflammatory modulation mechanisms. Full article

The structural memory effect is normally considered one of the most important properties of LDHs. However, certain anions can have adverse effects on it. In this study, three types of CLDHs (Mg2Al1-CLDH, Mg2Al0.5Fe0.5-CLDH, Mg2Fe1-CLDH) were obtained and used to observe their regeneration behaviors in the presence of sulfate, silicate, and phosphate, respectively, at initial pH values of 10 and 13. The samples were characterized by X-ray diffraction (XRD), thermogravimetric analysis (TGA-DTG), scanning electron microscope (SEM), and N2 adsorption–desorption isotherm (BET). The results suggested that silicate and phosphate have significant impacts on the regeneration of CLDHs, while sulfate does not. Specifically, phosphate and silicate reacted with MgO to generate magnesium silicate and magnesium phosphate dibasic, which were covered on the surface of particles and hindered the hydroxylation of metal oxides. However, a higher pH can suppress the formation of new substances and promote the regeneration of LDHs. Moreover, the CLDHs with high specific surface area had a stronger anti-interference performance regarding the effects of phosphate and silicate. Full article

Environmental contaminants exhibit heterogeneous neurotoxicity profiles, yet systematic comparisons between legacy neurotoxicants and emerging pollutants remain scarce. To address this gap, we implemented an integrative transcriptome meta-analysis framework that harmonized eight transcriptomic datasets spanning in vivo and in vitro neural models exposed to two legacy neurotoxicants (bisphenol A [BPA], 2, 2′, 4, 4′-tetrabromodiphenyl ether [BDE-47]) and polystyrene nanoplastics (PSNPs) as an emerging contaminant. Our analysis revealed a substantial overlap (68% consistency) in differentially expressed genes (DEGs) between BPA and PSNPs, with shared enrichment in extracellular matrix disruption pathways (e.g., “fibronectin binding” and “collagen binding”, p < 0.05). Network-based toxicogenomic mapping linked all three contaminants to six neurological disorders, with BPA showing the strongest associations with Hepatolenticular Degeneration. Crucially, a sex-stratified analysis uncovered male-specific transcriptional responses to BPA (e.g., lipid metabolism and immune response dysregulation), whereas female models showed no equivalent enrichment. This highlights the sex-specific transcriptional characteristics of BPA exposure. This study establishes a novel computational toxicology workflow that bridges legacy and emerging contaminant research, providing mechanistic insights for chemical prioritization and gender-specific risk assessment. Full article

To address the poor thermal shock resistance and high brittleness of traditional ceramic tools, a novel Si₃N₄/Sc₂W₃O₁₂ (SNS) composite ceramic material was developed via in situ synthesis using WO₃ and Sc₂O₃ as precursors and consolidated by spark plasma sintering. Sc₂W₃O₁₂ with negative thermal expansion was introduced to compensate for matrix shrinkage and modulate interfacial stress. The effects of varying Sc₂W₃O₁₂ content on thermal expansion, residual stress, microstructure, and mechanical properties were systematically investigated. Among the compositions, SNS3 (12 wt.% Sc₂W₃O₁₂) exhibited the best overall performance: relative density of 98.8 ± 0.2%, flexural strength of 712.4 ± 30 MPa, fracture toughness of 7.5 ± 0.3 MPa·m^1/2, Vickers hardness of 16.3 ± 0.3 GPa, and an average thermal expansion coefficient of 2.81 × 10⁻⁶·K⁻¹. The formation of a spherical chain-like Sc-W-O phase at the grain boundaries created a “hard core–soft shell” interface that enhanced crack resistance and stress buffering. Cutting tests showed that the SNS3 tool reduced workpiece surface roughness by 32.91% and achieved a cutting distance of 9500 m. These results validate the potential of this novel multiphase ceramic system as a promising candidate for high-performance and thermally stable ceramic cutting tools. Full article

Since the early 21st century, urban shrinkage has become a significant global phenomenon. Dongguan, in Guangdong Province, China, is known as a “world factory”. It experienced notable urban shrinkage following the 2008 financial crisis. However, the city demonstrated remarkable recovery and ongoing development in subsequent years. On that basis, this study focuses on the following three points: (1) identifying the spatiotemporal factors contributing to the growth and shrinkage of manufacturing cities, taking Dongguan as an example; (2) explaining the influencing factors of the growth and shrinkage of Dongguan City during three critical periods, 2008–2014 (post-crisis), 2015–2019 (as machinery replaced human work), and 2020–2023 (the COVID-19 pandemic and recovery); and (3) selecting representative towns and streets for on-site observation and investigation, analyzing the measures they have taken to cope with growth and shrinkage during different periods. The key findings include the following: (1) The spatial dynamics of growth and shrinkage in Dongguan show significant temporal patterns, with traditional manufacturing areas shrinking from 2008 to 2014, central urban areas recovering from 2015 to 2019, and renewed shrinkage from 2020 to 2023. However, some regions maintained stability through strategic innovations. (2) Various factors, particularly industrial upgrading and technological innovation, drove the urban dynamics, enhancing economic resilience. (3) The case study of Houjie Town revealed successful adaptive mechanisms supported by policy while facing challenges like labor mismatches and inadequate R&D investment. This research offers insights for improving urban resilience and promoting sustainable development in Dongguan. Full article

Under the impetus of digital rural development and the rapid advancement of smart logistics, intelligent terminal delivery technologies are gradually expanding into rural areas. This study employs a three-phase mixed research approach to systematically investigate the factors influencing and mechanisms underlying rural residents’ willingness to adopt smart logistics in Hebei Province. In the first phase, grounded theory is employed to identify seven key perceived factors: perceived usefulness, perceived ease of use, sensitivity to collective evaluation, cultural conservatism, infrastructure quality, facilitating conditions, and technological trust. In the second phase, integrating the TAM and the UTAUT, this study incorporates context-specific variables and conducts empirical analysis using SEM and the bootstrap method on 451 valid questionnaire responses. The results indicate that all factors except infrastructure quality significantly influence adoption willingness, with cultural conservatism exerting a negative effect. In the third phase, fsQCA is applied to identify eight configurations that lead to high adoption willingness, further supplementing and enriching the explanatory power of the SEM results. This research expands the theoretical understanding of smart logistics technology adoption mechanisms in rural areas and offers practical guidance for the promotion and application of related technologies. Full article

This study investigated the accumulation characteristics and associated health risks of 11 trace elements (Al, Rb, Cr, Ni, Mo, Sr, Pb, Ba, Ag, As, and Ga) in four crucian carp varieties: gene-edited intermuscular bone-free crucian carp (Carassius auratus, WUCI) and its sibling wild-type (Carassius auratus, WT), Fangzheng silver crucian carp (Carassius gibelio var Fangzheng, FZYJ), and Songpu silver crucian carp (Carassius gibelio var Songpu, SPYJ). Results showed that Al and Rb were the most abundant elements across all groups. WUCI exhibited distinct accumulation patterns, including significantly higher hepatic Mo concentrations (0.265 ± 0.032 mg/kg) and muscle/liver Rb levels (muscle: 8.74 ± 1.21 mg/kg; liver: 12.56 ± 2.05 mg/kg) compared to other varieties (p < 0.05), which supports the hypothesis of genotype-specific differences in heavy metal accumulation. Correlation analysis revealed that WUCI exhibited similar elemental interactions with WT and SPYJ (e.g., Al-Ni positive correlation, |rs| ≥ 0.8), while SPYJ displayed distinct patterns with fifteen negative correlations compared to three to five in others varieties, suggesting a potential alteration in elemental homeostasis. Pollution index (P_i) assessments indicated mild contamination for Pb in SPYJ liver (P_i = 0.265) and Cr/As in WUCI muscle (P_i = 0.247/0.218). Despite these values, all hazard indices remained below the established safety thresholds (THQ < 0.1, HI < 0.25, TCR < 10⁻⁶), reinforcing the overall safety of the tested fish. Notably, muscle As levels (0.86 ± 0.15 mg/kg) exceeded hepatic concentrations (0.52 ± 0.09 mg/kg), potentially due to differential detoxification mechanisms. These findings demonstrate the food safety of all tested varieties, while highlighting genotype-specific metabolic adaptations, providing critical data for evaluating gene edited aquatic products. Full article

Target detection is the key technology of the apple-picking robot. To overcome the limitations of existing apple target detection methods, including low recognition accuracy of multi-species apples in complex orchard environments and a complex network architecture that occupies large memory, a lightweight apple recognition model based on the improved YOLO11 model was proposed, named YOLO-WAS model. The model aims to achieve efficient and accurate automatic multi-species apple identification while reducing computational resource consumption and facilitating real-time applications on low-power devices. First, the study constructed a high-quality multi-species apple dataset and improved the complexity and diversity of the dataset through various data enhancement techniques. The YOLO-WAS model replaced the ordinary convolution module of YOLO11 with the Adown module proposed in YOLOv9, the backbone C3K2 module combined with Wavelet Transform Convolution (WTConv), and the spatial and channel synergistic attention module Self-Calibrated Spatial Attention (SCSA) combined with the C2PSA attention mechanism to form the C2PSA_SCSA module was also introduced. Through these improvements, the model not only ensured lightweight but also significantly improved performance. Experimental results show that the proposed YOLO-WAS model achieves a precision (P) of 0.958, a recall (R) of 0.921, and mean average precision at IoU threshold of 0.5 (mAP@50) of 0.970 and mean average precision from IoU threshold of 0.5 to 0.95 with step 0.05 (mAP@50:95) of 0.835. Compared to the baseline model, the YOLO-WAS exhibits reduced computational complexity, with the number of parameters and floating-point operations decreased by 22.8% and 20.6%, respectively. These results demonstrate that the model performs competitively in apple detection tasks and holds potential to meet real-time detection requirements in resource-constrained environments, thereby contributing to the advancement of automated orchard management. Full article