Search Results (1,429)

The roots of Baphicacanthus cusia (Nees) Bremek, commonly known as Nan-Ban-Lan-Gen, have been used for a long time in traditional Chinese medicine to manage inflammatory and infectious diseases. However, the structural features and bioactive potential of its polysaccharides have not been extensively studied. In the present study, a novel homogeneous polysaccharide (BcP-b2) was isolated from the roots of B. cusia, and its bioactivity was evaluated using an activity-guided purification strategy. Multi-dimensional structural analysis identified BcP-b2 as a highly branched galactoarabinan with a molecular weight of ~38.1 kDa, featuring a well-defined backbone and a variety of side chains. In vitro and in vivo assays demonstrated that BcP-b2 attenuated the accumulation of reactive oxygen species (ROS) and enhanced the activities of endogenous antioxidant enzymes, including superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px). Additionally, BcP-b2 activated macrophages under basal conditions and alleviated lipopolysaccharide (LPS)-induced cytotoxicity and inflammatory mediator release. Transcriptomic and Western blot analyses revealed that these dual effects were achieved through the simultaneous suppression of the PI3K/Akt inflammatory axis and activation of the Nrf2/HO-1 antioxidant pathway, concomitant with enhanced nuclear translocation of Nrf2. These findings provide a molecular basis for the ethno-pharmacological use of Nan-Ban-Lan-Gen and identify BcP-b2 as a promising candidate for further investigation as a potential therapeutic agent. Full article

Background/Objectives: The stability of complete dentures is strongly influenced by the biomechanical properties of the oral mucosa, whose heterogeneity results in non-uniform load distribution, while its clinical evaluation remains predominantly qualitative. This article proposes a theoretical differential hypothesis aimed at providing a conceptual mathematical framework for interpreting the relationship between mucosal resilience and load distribution in complete dentures. Methods: The denture-mucosa system was represented along a one-dimensional coordinate, defining resilience R(x) and pressure P(x) as continuous functions related by a first-order differential equation, interpreted through elementary principles of differential calculus. Results: A theoretical simulation based on physiological parameters (F = 50 N, Young’s modulus 19.75 MPa, R = 2 mm) highlights that areas of thinner mucosa tend to behave as stress concentration points, while spatial variability of resilience generates deformation gradients potentially associated with prosthetic instability. Conclusions: The model, although simplified and non-predictive, provides a coherent interpretative framework and can support the integration of biomechanical parameters into clinical reasoning and prosthetic planning. No clinical recommendations should be derived from this model until experimental validation has been performed. Full article

Monitoring urban biodiversity is essential for designing resilient and sustainable cities. Urban trees provide a wide range of ecosystem services (ESs), including air pollution reduction, urban heat island mitigation, and psychological benefits for citizens. Accurate and updated tree inventories are therefore essential tools for urban environmental monitoring. However, existing urban tree inventories are often incomplete or outdated, especially in private areas, limiting accurate ES assessment and urban planning. Earth observation satellite missions, particularly very-high-resolution multispectral (VHR-MS) imagery, offer a valuable alternative to field surveys for gathering information on urban environments. This work proposes a deep learning (DL) framework based on VHR-MS satellite imagery for the automatic generation of accurate urban tree inventories. DL models reduce human effort and save operational time by automatically learning complex representations and patterns from satellite imagery. The proposed encoder–decoder architecture extends prior point-based detection approaches by integrating a ResNet-50 backbone and a percentile-based threshold calibration procedure. Given the lack of suitable training data covering heterogeneous and densely vegetated urban environments, a dedicated dataset was constructed from VHR-MS satellite imagery acquired over the Lombardy region (Italy). The dataset encompasses a wide range of land uses and land covers, including residential and industrial zones, public parks, private gardens, and agricultural areas. Through the photointerpretation of more than 2800 images, precise coordinates for more than 50,000 manually annotated trees were obtained. The DL model is trained with point-level annotations, enabling precise localization of individual trees while reducing annotation ambiguity in dense urban contexts. On the Lombardy dataset at 30 cm/px resolution, the proposed framework achieves 86.72% Precision, 66.92% Recall, an F1-score of 75.54%, and a localization error of 1.473 m. Full article

Unmanned aerial vehicle (UAV) visual navigation relies critically on robust image matching between UAV-acquired aerial imagery and pre-existing satellite reference maps. However, extreme cross-domain heterogeneity—encompassing temporal, radiometric, viewpoint, and sensor variations—causes severe performance degradation in existing deep learning-based matchers trained on conventional benchmarks. Furthermore, manual annotation of ground-truth correspondences is prohibitively expensive. This paper proposes a semi-supervised saliency-aware image matching framework with bi-level meta-learning. Our approach comprises two synergistic stages: (1) automated dense correspondence generation via parameterized geometric synthesis, which constructs a large-scale coarse dataset ${\mathcal{D}}_c$ (approximately 50,000 pairs) without dense manual point annotation, serving as the primary training corpus for the feature matching network; (2) expert-validated meta-data curation producing a high-quality meta-dataset ${\mathcal{D}}_m$ (500 pairs) that supervises the training of a Saliency Judgment Network through bi-level meta-optimization, enabling the network to identify and prioritize geometrically reliable correspondences. Experimental results on the proposed RS-Hetero-50K benchmark and cross-domain FuJian-Mountain dataset demonstrate substantial improvements over representative sparse and detector-free matchers, including LoFTR, SuperGlue, and LightGlue. The complete CNN-attention and saliency-aware framework achieves 95.4% matching precision, which is consistent with the best result reported in the experimental section. The plug-and-play experiments further confirm that the proposed saliency module consistently improves representative sparse and detector-free matchers, indicating that the performance gain stems from both stronger feature representation and saliency-guided correspondence selection. The largest terrain-specific gain is observed in gobi scenes, where the AUC@5 px improves by 16.8% relative to the LoFTR baseline, demonstrating improved robustness in weakly textured remote sensing environments. Full article

Hurdle technique analysis requires accurate identification of key phases and kinematic features, but conventional biomechanical methods are often costly, equipment-dependent, and difficult to apply in front-line training. This study developed a low-cost monocular-video-based framework for rapid hurdle clearance analysis in practical training settings. Thirty-seven physical education college students with different hurdling skill levels were recruited as participants, and side-view videos of their hurdle clearance were recorded. The proposed pipeline combined YOLO26 hurdle detection, RTMPose markerless pose estimation, rule-based key-event detection, phase segmentation, and phase-specific kinematic feature extraction. The results showed that the hurdle detection model achieved high accuracy, with bounding-box mAP@0.5 of 0.992 and mask mAP@0.5 of 0.971. Pose estimation showed good agreement with manual annotations, with an overall RMSE of 8.25 px and PCK of 97.64%. The rule-based phase segmentation method achieved an overall event localization MAE of 0.74 frames and RMSE of 1.55 frames, outperforming LSTM and TCN temporal baselines. Core distance and most angle variables also showed high agreement with manually recalculated values. These findings indicate that monocular video and markerless pose estimation can provide an accurate, low-cost, and practical tool for hurdle phase segmentation and kinematic assessment in routine training contexts. Full article

Lithium-ion batteries with high energy density and long cycle life have been widely used as secondary batteries in electric vehicles and energy storage systems. With the growing demand for high energy density in lithium-ion batteries, silicon-based materials, which possess a high theoretical specific capacity (4200 mAh g⁻¹), are regarded as core candidates for anode materials. However, Si-based materials undergo severe volume expansion (up to 300%), which leads to the collapse of the electrode structure, inducing pulverization of the active material and capacity loss, thereby hindering the commercial application of silicon-based materials. To address these issues, scholars from various countries have developed many silicon-based materials with different compositions and three-dimensional structures, and have made some research progress. This review first elaborates on the lithium storage mechanisms and advantages of diverse silicon-based anode materials by taking Si, SiO_x, SiN_x, and SiP_x as representative examples with distinct characteristics. Subsequently, from the two aspects of dimensional design (0D, 1D, 2D and 3D) and architecture design (core–shell, sandwich-like and network structure), the design strategies for various silicon-based anode structures and their enhancement on electrochemical performance are analyzed. Finally, this review elucidated the challenges faced by silicon-based anodes from the perspectives of mechanism elucidation, structural customization, industrialization, and full-cell applications. It also proposed future development directions for silicon anodes by combining actual challenges and focusing on aspects such as structure optimization, machine learning, advanced characterization techniques, and mechanistic analysis. Full article

Hydrogen-rich water (HRW) is an aqueous solution containing dissolved molecular hydrogen. This study evaluated its effects on juvenile largemouth bass (Micropterus salmoides) under acute low-temperature stress. A total of 480 juveniles (2.4 ± 0.5 g) were randomly assigned to four groups: the control group was reared in standard water; the treatment groups were exposed to different hydrogen concentrations, specifically H1 (0.3 mg/L), H2 (0.5 mg/L), and H3 (0.9 mg/L). The fry were reared at 26 ± 0.5 °C for 30 days, followed by acute low-temperature stress (11 ± 0.5 °C) for 48 h. Samples were collected at 0, 8, 24, and 48 h. Results showed that after 30 days of HRW rearing, the final body weight (FBW), specific growth rate (SGR), and condition factor (CF) of the H1 group were significantly increased, while the H3 group only increased CF. No significant differences were observed in hepatopancreas somatic index (HSI) and survival rate (SR) among groups. Acute low-temperature stress induced liver and intestinal damage, which were alleviated in the H1 group. The H1 group exhibited significantly increased SOD, CAT, and GSH-Px activities in the liver, as well as CAT and SOD in the intestine and gills, while reducing MDA levels, thereby enhancing the antioxidant capacity. The H1 group significantly upregulated the antioxidant genes expression (sod, cat, and gsh-px mRNA levels) in the liver and gills but downregulated them in the intestine. 16S rDNA analysis revealed that HRW increased intestinal microbiota and the relative abundance of Bacillota. In conclusion, the H1 group significantly improved growth performance, mitigated acute low-temperature damage, enhanced antioxidant capacity, and increased the relative abundance of Bacillota in the intestines. This provides an innovative, safe, and effective solution for aquaculture industries confronting low-temperature challenges. Full article

This study evaluated the effects of dietary coenzyme Q10 (CoQ10) supplementation on growth performance, slaughter performance, meat quality, antioxidant capacity, serum profiles, and intestinal morphology in Minxinan black rabbits. A total of 250 rabbits were allocated to five dietary treatments containing 0, 30, 60, 120, or 240 mg/kg CoQ10 for 14 weeks after a 1-week adaptation period. Results indicated that supplementation with 60 mg/kg CoQ10 resulted in the highest final body weight (2.83 kg) and average daily gain (29.54 g/day), with a significantly reduced feed-to-gain ratio and mortality rate compared to the control group. Regarding slaughter performance, the 60 mg/kg group significantly reduced the abdominal fat rate. In terms of meat quality, the 60 and 120 mg/kg groups showed significantly reduced drip loss and shear force, while meat lightness (L*) increased in all supplemented groups. Cooking loss was significantly reduced in the 60 mg/kg group. Antioxidant capacity in cardiac muscle and longissimus thoracis et lumborum (LTL) muscle was enhanced, particularly at 60 mg/kg, with significantly elevated activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px), and total antioxidant capacity (T-AOC), alongside reduced malondialdehyde (MDA) content. Furthermore, the 60 mg/kg group increased LTL muscle polyunsaturated fatty acid (PUFA) content, elevated serum levels of triiodothyronine (T3), growth hormone (GH), and insulin-like growth factor-1 (IGF-1), enhanced immunoglobulin concentrations, and improved intestinal morphology. In conclusion, dietary supplementation with 60 mg/kg CoQ10 improved growth performance, carcass leanness, PUFA content, and antioxidant status in broiler rabbits. Full article

Plant polysaccharides, such as Astragalus polysaccharide (APS) and Glycyrrhiza polysaccharide (GPS), have potential as functional feed additives. This study investigated the effects of dietary APS and GPS on growth-related traits, serum biochemical and immune indices, antioxidant capacity, intestinal health, and microbial diversity in early-weaned squabs. A total of 192 15-day-old Silver King squabs were randomly divided into four groups: the control group (CK), the 800 mg/kg APS group, the 450 mg/kg GPS group, and the APS + GPS combination group (AG group), with 12 replicates per group and 4 squabs per replicate. The experiment lasted for 28 days. The results showed that final body weight tended to be higher in the APS, GPS, and AG groups, whereas breast width and breast depth were significantly increased in the GPS and AG groups (p < 0.01). The GPS and AG groups exhibited increased serum immunoglobulin A (IgA; p < 0.05) and immunoglobulin G (IgG; p < 0.01) levels, as well as reduced levels of pro-inflammatory cytokines, including interleukin-6 (IL-6), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α; p < 0.01). All treatments increased serum total antioxidant capacity (T-AOC; p < 0.01), while the AG group reduced malondialdehyde (MDA) levels and increased total superoxide dismutase (T-SOD) and glutathione peroxidase (GSH-Px) activities (p < 0.01). Duodenal and jejunal T-AOC increased in all treatment groups (p < 0.01), and APS and AG increased ileal T-AOC (p < 0.01). However, intestinal MDA concentrations increased in several segments, indicating a complex and segment-specific oxidative response. The AG group also increased jejunal lipase activities (p < 0.05). Microbiome analysis suggested that Helicobacter was correlated with immune-related indicators, while Lactobacillus was identified as an important core genus in the microbial co-occurrence network. These findings suggest that dietary APS and GPS may regulate immune function, oxidative–antioxidant responses, intestinal function, and gut microbial composition, thereby supporting physiological adaptation in early-weaned squabs. Full article

Background and Objectives: Diabetes mellitus (DM) is frequently associated with impaired wound healing due to persistent oxidative stress, chronic inflammation, and dysregulated proteasome activity, leading to delayed tissue repair and increased risk of chronic ulcers. The present study aimed to investigate the role of the immunoproteasome system in diabetic wound healing, with a particular focus on its involvement in oxidative stress and inflammatory pathways, and to evaluate whether pharmacological inhibition with ONX-0914 improves tissue repair. Materials and Methods: Experimental diabetes was induced in rats using streptozotocin (STZ), and the animals were allocated to three groups: healthy control, STZ-induced diabetic, and STZ + ONX-0914 treatment. Wound healing was evaluated by macroscopic analysis of wound closure and histopathological examination at days 3, 7, and 14. Oxidative stress and antioxidant status were assessed by measuring malondialdehyde (MDA) levels and antioxidant enzyme activities (SOD, CAT, and GSH-Px) in serum and wound tissues. Proteasome activity was analyzed fluorometrically, while systemic and local inflammatory responses were determined by ELISA and Western blot analysis of IL-1β, TNF-α, and IL-6. Results: STZ-induced diabetes significantly delayed wound closure, increased lipid peroxidation, reduced antioxidant enzyme activities, and elevated systemic and tissue inflammatory cytokine levels. Treatment with ONX-0914 markedly accelerated wound closure and improved histological healing parameters, including re-epithelialization, granulation tissue formation, and angiogenesis. Moreover, ONX-0914 significantly reduced MDA levels while restoring SOD, CAT, and GSH-Px activities in both serum and wound tissues. The treatment also inhibited proteasome activity and significantly suppressed the expression of IL-1β, TNF-α, and IL-6. Conclusions: ONX-0914 significantly improves diabetic wound healing by restoring antioxidant defenses, reducing oxidative damage, and attenuating inflammatory signaling pathways. These findings suggest that immunoproteasome inhibition represents a promising therapeutic strategy for enhancing tissue repair in diabetic conditions. Full article

To address the issues of low efficiency and large errors in traditional dimensional measurement strategies for fuel nozzles, this paper proposes an improved region-constrained Random Sample Consensus (RANSAC) circle fitting method for high-precision measurement of the inner hole cone angle. Three-dimensional point clouds are extracted using a shape-from-focus method. The point cloud slices are then projected onto a two-dimensional plane, and the slice edges are extracted. Based on the edge shape distribution, the candidate point selection strategy of RANSAC is optimized: the initial circle is divided into eight sector regions, and three points are randomly selected from three distinct regions to fit candidate circles. After multiple iterations, the optimal fitting circle is obtained. A comparative analysis is conducted among the least squares method, standard RANSAC, and the proposed algorithm, with three quantitative metrics—residual standard deviation (σ), root mean square error (RMSE), and inlier ratio (ε)—introduced to evaluate the fitting quality. Experimental results show that the proposed region-constrained RC-RANSAC method achieves the best performance among the three, yielding σ = 2.826 px, RMSE = 2.826 px, and ε = 95.2%, and attains a cone angle deviation of only 1.0°, which closely agrees with Keyence ultra-depth measurements (error 0.8°). This method provides a new approach for accurate and robust cone angle measurement of fuel nozzle inner holes. Full article

The urban tree canopy is an important resource that spans public and private property and whose form and quantity change over short distances. Although remote sensing and deep learning approaches have been used to map urban tree canopy, the high cost of commercial imagery and the technical complexity of model development have limited their adoption by urban forestry practitioners. We developed a structured and reproducible deep learning workflow optimized for freely available USDA National Agriculture Imagery Program (NAIP) imagery. The workflow incorporates a reproducible U-Net segmentation model for canopy delineation and a YOLOv9e object detection model for individual tree identification, enabling complementary estimation of the canopy extent and individual tree locations. Across two neighborhoods in Los Angeles, the optimized U-Net achieved a Dice coefficient of 0.824 for canopy segmentation, while YOLOv9e reached an F1-score of 0.687 for individual tree detection on a held-out test set with 17,466 annotated trees. A data sufficiency experiment showed that model performance stabilizes when approximately 130 trees are annotated per 320 × 320 pixel (px) tile, corresponding to about 25,379 training and 2641 validation labels, providing a practical target for annotation effort. Additional experiments demonstrate a structured workflow for spatial sampling, training data requirements, and the use of model inferences to estimate tree canopy extent and individual tree locations. The workflow also shows encouraging evidence of transferability to previously unseen urban areas without retraining. By relying solely on NAIP-optimized approaches, this new workflow bridges the gap between complex deep learning techniques and the practical needs of urban foresters; empowers local stakeholders to create accurate, affordable, and timely urban tree inventories; and fosters data-driven decision-making for the sustainable management of urban green infrastructure. Full article

Mori Cortex Radicis (MCR), which is abundant in resources and low in cost, is a Chinese herbal medicine with antitussive, anti-inflammatory, analgesic, and hypoglycemic effects; however, its application in the prevention and control of aquatic pathogens remains understudied. In this study, a MCR water extract (MCR-WE) was prepared, and its contents of polysaccharides, polyphenols, and proteins were found to be 0.63%, 1.17%, and 2.79%, respectively. LC-MS metabolomics revealed that L(+)-Arginine, 9,12,13-Todea, Citric acid, 1-Deoxynojirimycin, and 4-Guanidinobutanoic acid were the most abundant compounds. Subsequently, by feeding the MCR-WE to crucian carp (Carassius auratus) and challenging them with Aeromonas veronii, it was found that the MCR-WE enhanced the activities of immune factors (AKP, ACP, LZM) and the phagocytic activity of leukocytes (p < 0.05). Furthermore, the MCR-WE improved the survival rate of crucian carp (p < 0.05), reduced the bacterial load in the kidneys (p < 0.05), decreased the mRNA expression of inflammatory factors (IL-6, IL-1β, TNF-α), and lowered the expression levels of antioxidant-related factors (CAT, GSH-Px, SOD, MDA) and the mRNAs of oxidative stress pathway factors (Nrf2, HO-1, Keap1) (p < 0.05). Histopathological sections and immunofluorescence assays showed that the MCR-WE maintained the structural integrity of internal organs and reduced renal cell apoptosis and DNA damage. Therefore, MCR-WE is rich in immunologically active substances, can activate the immune response of crucian carp, reduce fish mortality, exert anti-inflammatory and antioxidant activities, and maintain the structural and functional integrity of internal organs. Thus, the MCR-WE holds promise as a therapeutic agent against A. veronii infection in fish. Full article

The exact mechanisms of skin involvement in type 1 diabetes (DM1) remain poorly understood. This study aimed to evaluate the relationship between antioxidants, oxidative stress, protein glycation, and glycoxidation, as well as matrix metalloproteinase (MMP) activity, in the skin of rats with DM1, while investigating whether insulin administration improves skin homeostasis. Male Wistar rats were assigned to three groups: control, diabetes, and diabetes treated with insulin. Significantly higher expression of GSH (gluthatione) and GSH-Px (glutathione peroxidase), elevated levels of AGE (Advanced Glycation End products), DT (dityrosine), KN (kynurenine), NFKN (N-formylkynurenine) and ONOO- (peroxynitrite), as well as increased activity of GLU (β-D-glucuronidase), NADPH oxidase (NOX) and MMP-1, -2, -3, -7, -9, -11 and -13 were observed in the skin of rats with DM1. Insulin treatment normalizes the skin’s antioxidant barrier and eliminates oxidative stress. It also reduces the intensity of protein glycation and glycoxidation, though not to the levels observed in the control group. Summarizing, in diabetic skin there is a complex interaction between the thiol antioxidant barrier, oxidative damage, protein glycation and glycoxidation as well as MMP expression. Insulin restores physiological balance in skin cells; however, glycation and ECM remodeling are still more pronounced than in healthy skin. Full article

Silicon (Si) is an essential trace element involved in multiple physiological processes of animals. This study aimed to investigate the dose-dependent effects of dietary silica (SiO₂) supplementation on production performance and key blood parameters in laying hens. A total of 360 hens were randomly assigned to five groups (6 replicates/group, 12 hens/replicate) and fed basal diets supplemented with 0% (control), 0.1%, 0.2%, 0.4%, or 0.8% SiO₂ for 8 weeks. Laying performance, egg quality, serum immune indices, reproductive hormone levels, antioxidant status, and serum trace element concentrations were determined. The results showed that dietary SiO₂ supplementation significantly affected egg production rate (p < 0.05), with the 0.2% group achieving the highest rate compared to the control. For egg quality, yolk weight and yolk thickness were significantly reduced only in the 0.8% group (p < 0.05), while other parameters were unaffected (p > 0.05). Dietary supplementation with 0.2%, 0.4%, and 0.8% silica significantly increased serum levels of IL-2 and IL-4 (p < 0.05), whereas the 0.8% supplementation decreased IL-1 levels (p < 0.05). Compared with the control group, serum IgA and IgG levels were elevated in the 0.2%, 0.4%, 0.8% silica-supplemented groups (p < 0.05), and serum IgM levels were higher in the 0.4% and 0.8% groups (p < 0.05). Regarding reproductive hormones, dietary SiO₂ significantly increased serum concentrations of β-endorphin, estradiol, growth hormone, luteinizing hormone, and progesterone (p < 0.05), with follicle-stimulating hormone elevated in the 0.4% and 0.8% groups (p < 0.05). Dietary silica supplementation did not affect serum activities of SOD, GSH-Px, CAT, or T-AOC. Serum POD activity decreased gradually and was significantly lower in the 0.2%, 0.4%, and 0.8% groups than in the control group (p < 0.05). Furthermore, SiO₂ supplementation significantly altered serum Cu and Zn levels (p < 0.05), with the 0.8% group having the highest Ca concentration and the 0.1–0.8% groups showing increased Zn levels compared to the control; no effects on Fe and Mn were observed (p > 0.05). In conclusion, dietary supplementation with 0.2–0.4% SiO₂ effectively improves egg production rate, along with enhancing immune function, modulating reproductive hormone secretion, and regulating serum Cu/Zn homeostasis in late-phase laying hens. Full article