Search Results (221)

In the renewable energy conversion system, water electrolysis technology is widely regarded as the core means to achieve clean hydrogen production. However, the anodic oxygen evolution reaction (OER) has become a key bottleneck limiting the overall water splitting efficiency due to its slow kinetic process and high overpotential. This study proposes a novel Co₃O₄-TiO₂/CNTs p-n heterojunction catalyst, which was synthesized by hydrothermal method and significantly improved OER activity by combining heterojunction interface regulation and light field enhancement mechanism. Under illumination conditions, the catalyst achieved an overpotential of 390 mV at a current density of 10 mA cm⁻², which is superior to the performance of the dark state (410 mV) and single component Co₃O₄-TiO₂ catalysts. The material characterization results indicate that the p-n heterojunction structure effectively promotes the separation and migration of photogenerated carriers and enhances the visible light absorption capability. This work expands the design ideas of energy catalytic materials by constructing a collaborative electric light dual field regulation system, providing a new strategy for developing efficient and low-energy water splitting electrocatalysts, which is expected to play an important role in the future clean energy production and storage field. Full article

The barbel chub (Squaliobarbus curriculus) exhibits remarkable resistance to grass carp reovirus (GCRV), a devastating pathogen in aquaculture. To reveal the molecular basis of this resistance, we investigated complement factor D (DF)—a rate-limiting serine protease governing alternative complement pathway activation. Molecular cloning revealed that the barbel chub DF (ScDF) gene encodes a 1251-bp cDNA sequence translating into a 250-amino acid protein. Crucially, bioinformatic characterization identified a unique N-glycosylation site at Asn¹³⁹ in ScDF, representing a structural divergence absent in grass carp (Ctenopharyngodon idella) DF (CiDF). While retaining a conserved Tryp_SPc domain harboring the catalytic triad (His⁶¹, Asp¹⁰⁹, and Ser²⁰⁴) and substrate-binding residues (Asp¹⁹⁸, Ser²¹⁹, and Gly²²¹), sequence and phylogenetic analyses confirmed ScDF’s evolutionary conservation, displaying 94.4% amino acid identity with CiDF and clustering within the Cyprinidae. Expression profiling revealed constitutive ScDF dominance in the liver, and secondary prominence was observed in the heart. Upon GCRV challenge in S. curriculus kidney (SCK) cells, ScDF transcription surged to a 438-fold increase versus uninfected controls at 6 h post-infection (hpi; p < 0.001)—significantly preceding the 168-hpi response peak documented for CiDF in grass carp. Functional validation showed that ScDF overexpression suppressed key viral capsid genes (VP2, VP5, and VP7) and upregulated the interferon regulator IRF9. Moreover, recombinant ScDF protein incubation induced interferon pathway genes and complement C3 expression. Collectively, ScDF’s rapid early induction (peaking at 6 hpi) and multi-pathway coordination may contribute to barbel chub’s GCRV resistance. These findings may provide molecular insights into the barbel chub’s high GCRV resistance compared to grass carp and novel perspectives for anti-GCRV breeding strategies in fish. Full article

Brucellosis is caused by Brucella spp.; it can result in fetal loss and abortion, resulting in economic losses and negative effects on human health. Herein, a cross-sectional study on the epidemiology of Brucella spp. in aborted livestock in Ningxia from 2022 to 2023 was conducted. A total of 749 aborted tissue samples from 215 cattle and 534 sheep were collected from farmers who reported abortions that were supported by veterinarians trained in biosecurity. The samples were analyzed using qPCR and were cultured for Brucella spp. when a positive result was obtained; the samples were speciated using AMOS-PCR. MLST and MLVA were employed for genotype identification. The results demonstrated that 8.68% of the samples were identified as being positive for Brucella spp. based on qPCR results. In total, 14 field strains of Brucella spp. were subsequently isolated, resulting in 11 B. melitensis, 2 B. abortus, and 1 B. suis. being identified via AMOS-PCR. Four sequence types were identified via MLST—ST7 and ST8 (B. melitensis), ST2 (B. abortus), and ST14 (B. suis)—with ST8 predominating. Five MLVA-8 genotypes and seven MLVA-11 genotypes were identified, with MLVA-11 GT116 predominating in livestock. Thus, at least three Brucella species are circulating in aborted livestock in Ningxia. This suggests a significant risk of transmission to other animals and humans. Therefore, disinfection and safe treatment procedures for aborted livestock and their products should be carried out to interrupt the transmission pathway; aborted livestock should be examined to determine zoonotic causes and targeted surveillance should be strengthened to improve the early detection of infectious causes, which will be of benefit to the breeding industry and public health security. Full article

Against the backdrop of increasing extreme weather events associated with global climate change, regulating carbon dioxide emissions, a primary contributor to atmospheric warming, has emerged as a pressing global challenge. Focusing on China as a representative case study of major developing economies, this research examines industrial carbon emission patterns during 2001–2022. Methodologically, it introduces an innovative analytical framework that integrates the Generalized Divisia Index Method (GDIM) with the Low Emissions Analysis Platform (LEAP) to both decompose industrial emission drivers and project future trajectories through 2040. Key findings reveal that:the following: (1) Carbon intensity in China’s industrial sector has been substantially decreasing under green technological advancements and policy interventions. (2) Industrial restructuring demonstrates constraining effects on carbon output, while productivity gains show untapped potential for emission abatement. Notably, the dual mechanisms of enhanced energy efficiency and cleaner energy transitions emerge as pivotal mitigation levers. (3) Scenario analyses indicate that coordinated policies addressing energy mix optimization, efficiency gains, and economic restructuring could facilitate achieving industrial carbon peaking before 2030. These results offer substantive insights for designing phased decarbonization roadmaps, while contributing empirical evidence to international climate policy discourse. The integrated methodology also presents a transferable analytical paradigm for emission studies in other industrializing economies. Full article

Ningxia has emerged as a strategic hub for China’s photovoltaic (PV) industry by leveraging abundant solar energy resources and geoclimatic advantages. This study analyzed the spatiotemporal expansion trends and microclimatic impacts of PV installations (2015–2024) using Gaofen-1 (GF-1) and Landsat8 satellite imagery with deep learning algorithms and multidimensional environmental metrics. Among semantic segmentation models, DeepLabV3+ had the best performance in PV extraction, and the Mean Intersection over Union, precision, and F1-score were 91.97%, 89.02%, 89.2%, and 89.11%, respectively, with accuracies close to 100% after manual correction. Subsequent land surface temperature inversion and spatial buffer analysis quantified the thermal environmental effects of PV installation. Localized cooling patterns may be influenced by albedo and vegetation dynamics, though further validation is needed. The total PV site area in Ningxia expanded from 59.62 km² to 410.06 km² between 2015 and 2024. Yinchuan and Wuzhong cities were primary growth hubs; Yinchuan alone added 99.98 km² (2022–2023) through localized policy incentives. PV installations induced significant daytime cooling effects within 0–100 m buffers, reducing ambient temperatures by 0.19–1.35 °C on average. The most pronounced cooling occurred in western desert regions during winter (maximum temperature differential = 1.97 °C). Agricultural zones in central Ningxia exhibited weaker thermal modulation due to coupled vegetation–PV interactions. Policy-driven land use optimization was the dominant catalyst for PV proliferation. This study validates “remote sensing + deep learning” framework efficacy in renewable energy monitoring and provides empirical insights into eco-environmental impacts under “PV + ecological restoration” paradigms, offering critical data support for energy–ecology synergy planning in arid regions. Full article

This research implemented a miniaturized near-infrared spectroscopy (NIRS) system integrated with machine learning approaches for the quantitative evaluation of dry gluten content (DGC), wet gluten content (WGC), and the gluten index (GI) in wheat flour in a noninvasive manner. Five different algorithms were employed to mine the relationship between the full-range spectra (900–1700 nm) and three parameters, with support vector regression (SVR) demonstrating the best prediction performance for all gluten parameters (R_P = 0.9370–0.9430, RMSEP = 0.3450–0.4043%, and RPD = 3.1348–3.4998). Through a comparative evaluation of five wavelength selection techniques, 25–30 optimal wavelengths were identified, enabling the development of optimized SVR models. The improved whale optimization algorithm iWOA-based SVR (iWOA-SVR) model exhibited the strongest predictive capability among the five optimal wavelengths-based models, achieving comparable accuracy to the full-range spectra SVR for all gluten parameters (R_P = 0.9190–0.9385, RMSEP = 0.3927–0.5743%, and RPD = 3.0424–3.2509). The model’s robustness was confirmed through external validation and statistical analyses (p > 0.05 for F-test and t-test). The results highlight the effectiveness of micro-NIRS combined with iWOA-SVR for the nondestructive gluten quality assessment of wheat flour, providing a more valuable reference for expanding the use of NIRS technology and developing portable specialized NIRS equipment for industrial-level applications in the future. Full article

The objective of this study was to identify the AlkB family genes in poultry using bioinformatics, and to explore their molecular characteristics, evolutionary relationships, and expression patterns to clarify their potential functions in poultry. (1) Methods: The study utilized the NCBI database to obtain chicken genome data, and screened and validated AlkB family members (ALKBH1-5, ALKBH8, and FTO) by hmmsearch and TBtools. MEGA 11.0 was used for phylogenetic analysis, PHYRE2 and I-TASSER predicted protein structures, and the String database was used to construct an interoperability network. Finally, the tissue expression profiles were analyzed by using The Human Protein Atlas online database and qRT-PCR. (2) Results: Phylogenetic analysis revealed distinct avian and mammalian clusters, with chicken AlkB proteins exhibiting low sequence homology but conserved 3D structures compared to mammals. Chromosomal synteny and conserved domains highlighted evolutionary divergence, with ALKBH4 lacking typical AlkB structural motifs. Protein interaction networks linked ALKBH1/2/3/5/8/FTO, underscoring functional coordination in poultry adaptation. Tissue-specific expression showed high AlkB levels in brain tissues, while ALKBH5 dominated in muscle. During differentiation, ALKBH3, ALKBH5, and FTO expression significantly increased during myoblast differentiation. (3) Conclusions: This study identified seven AlkB family genes in poultry, revealing their phylogenetic classification into two subfamilies, conserved structural domains, chromosomal synteny, and tissue-specific expression patterns. Full article

Solid-state thermal decomposition in the Cu-13.3Ti-3.8Zr (at.%) alloy was studied using a synthesized method, including the temperature–concentration gradient and differential scanning calorimetry experiments within a single experimental cycle, as well as first principle calculations. Experimentally, the decomposition pathway and the solid solubility of Ti/Zr in the Cu matrix in the temperature range of 820 °C to 801.5 °C were observed in the Cu-13.3Ti-3.8Zr (at.%) alloy. The primary solid phase is (Cu) phase and subsequently precipitated Cu₅₁Zr₁₄ and Cu₄Ti phases. These features are valuable for understanding the thermal stability and solid-state phase equilibria of the alloy. First principle calculations, including formation enthalpy, charge density, and electron localization function analyses, were conducted to evaluate the thermal, structural, and electrical stability of Cu₅₁Zr₁₄ with and without Ti doping, as well as Cu₄Ti. The present work introduces an effective strategy for determining both the solid-state thermal decomposition pathway and the phase diagram within the solid-state region within a single experimental cycle. Full article

Background: Opportunistic screening is one major screening approach for esophageal squamous cell carcinoma (ESCC). We aimed to develop a score-based risk stratification model to assess the risk of ESCC and precancerous lesions in opportunistic screening and to validate it in an external population. Methods: The study was a secondary analysis of a published esophageal cancer screening trial. The trial was conducted in 39 secondary or tertiary hospitals in China, with 14,597 individuals including 71 high-grade intraepithelial neoplasia (HGIN) and 182 ESCC, enrolled for opportunistic screening. Additionally, questionnaires and endoscopy were performed. The primary outcome was histology-confirmed high-grade esophageal lesions, including HGIN and ESCC. The predictors were selected using univariable and multivariable logistic regression. Model performance was primarily measured with the area under the receiver operating characteristic curve (AUROC). Results: The score-based prediction model contained 8 variables on a 21-point scale. The model demonstrated an AUROC of 0.833 (95% CI, 0.803–0.862) and 0.828 (95% CI, 0.793–0.864) for detecting high-grade lesions in the training and validation cohorts, respectively. Using the cut-off score determined in the training cohort (≥9), the sensitivity reached 70.0% (95% CI, 50.6–85.3%), 81.3% (95% CI, 63.6–92.8%), and 81.1% (95% CI, 64.9–92.0%) in the validation cohort for detecting HGIN, early ESCC, and advanced ESCC, respectively, at a specificity of 76.4% (95%CI, 75.4–77.4%). The score-based model exhibited satisfactory calibration in the calibration plots. The model could result in 75.6% fewer individuals subjected to endoscopy. Conclusions: This score-based model demonstrated superior discrimination for esophageal high-grade lesions. It has the potential to inform referral decisions in an opportunistic screening setting. Full article

In recent years, bifunctional ingredients extracted and utilized from waste by-products as raw materials have received significant attention in the food production process. Previous studies have found that bovine livers possess both antioxidant and emulsifying potential; therefore, enhancing these dual properties is a current research focus. In this study, three different types of polyphenols (epigallocatechin gallate [EGCG], gallic acid [GA] and tannin [TA]) provide a reference on how to achieve better complexation of polyphenols with bovine liver hydrolysates (BLHs). Based on the molecular weight results, it was shown that the bovine liver peptides bind to polyphenols to form complexes with higher molecular weights. Furthermore, the binding affinities among the three complexes were as follows: TA > EGCG > GA. The emulsions stabilized by the coupling compounds contained more homogeneous and dense droplets (optical microscopy). Both the antioxidant properties and the emulsifying activity of all complexes were superior to those of bovine liver hydrolysates (BLHs) (p < 0.05), confirming synergistic effects that either flavonoids, phenolic acids or tannins possess with bovine liver hydrolysates. This combination provides an effective strategy for developing novel foods with specific functions. Full article

Ophiocordyceps sinensis, is an entomopathogenic fungus renowned for its medicinal properties, thriving in the frigid and high-altitude regions of the Qinghai–Tibet plateau. Given the limited availability of wild resources and the increasing recognition of their medicinal value, the cultivation of O. sinensis was initiated. However, there is a paucity of research investigating the disparities in their quality. This study evaluated the primary physiological indicators of both wild and cultivated O. sinensis. It also employed proteome and untargeted metabolome approaches to elucidate the differences in quality and underlying mechanisms between the two types. The results revealed that the contents of key representative components, including polysaccharide, crude protein, adenosine, and mannitol, were higher in wild O. sinensis than in cultivated O. sinensis. A total of 499 differentially expressed proteins (DEPs), including 117 up-regulated and 382 down-regulated DEPs, were identified in wild and cultivated O. sinensis. Additionally, 369 up-regulated differentially accumulated metabolites (DAMs) and 737 down-regulated DAMs were also identified. Wild O. sinensis had higher relative levels of lysophospholipid metabolites, while cultivated O. sinensis had higher relative levels of aldehydes and carboxylic acids. Correlation analysis revealed that different habitats altered 47 pathways shared between the proteome and metabolome, including carbohydrate metabolism and energy metabolism. β-glucosidase and α-galactosidase play essential roles in carbohydrate catabolism and may indirectly influence amino acid synthesis through energy metabolic pathways. The differential expression of polyamine oxidase (PAO) could reflect variations in polyamine metabolism and ammonia production between wild and cultivated O. sinensis. These variations may consequently affect nitrogen homeostasis and the biosynthesis of nitrogen-containing compounds, ultimately leading to differences in nutritional quality. In conclusion, these findings offer a novel perspective on the applications of O. sinensis and serve as a reference for the targeted development of cultivated O. sinensis. Full article

To address the challenges of high missed detection rates for minute transmission line defects, strong complex background interference, and limited computational power on edge devices in UAV-assisted power line inspection, this paper proposes a lightweight improved YOLOv12 real-time detection model. First, a Bidirectional Weighted Feature Fusion Network (BiFPN) is introduced to enhance bidirectional interaction between shallow localization information and deep semantic features through learnable feature layer weighting, thereby improving detection sensitivity for line defects. Second, a Cross-stage Channel-Position Collaborative Attention (CPCA) module is embedded in the BiFPN’s cross-stage connections, jointly modeling channel feature significance and spatial contextual relationships to effectively suppress complex background noise from vegetation occlusion and metal reflections while enhancing defect feature representation. Furthermore, the backbone network is reconstructed using ShuffleNetV2’s channel rearrangement and grouped convolution strategies to reduce model complexity. Experimental results demonstrate that the improved model achieved 98.7% mAP@0.5 on our custom transmission line defect dataset, representing a 3.0% improvement over the baseline YOLOv12, with parameters compressed to 2.31M (8.3% reduction) and real-time detection speed reaching 142.7 FPS. This method effectively balances detection accuracy and inference efficiency, providing reliable technical support for unmanned intelligent inspection of transmission lines. Full article

Background: Yiqi Zengmian (YQZM) functions as an immunopotentiator by enhancing both cellular and humoral immunity. However, its pharmacodynamic active constituents, particularly those absorbed into the bloodstream, and mechanism of action remain unclear. This study aimed to investigate the immunopotentiating effects and mechanisms of YQZM in mice immunized with the BBIBP-CorV (Beijing Bio-Institute of Biological Products Coronavirus Vaccine). Methods: Serum pharmacochemistry and ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) were employed to identify bioavailable components of YQZM. The mice received the BBIBP-CorV twice on days 1 and 14, while YQZM was orally administered for 28 days. Neutralization assays and ELISA quantified antigen-specific antibodies (abs), flow cytometry (FC) and intracellular cytokine staining (ICS) were used to assess immune cell populations and their cytokines, and an enzyme-linked immunospot assay (ELISpot) quantified memory T and B cells (MBs and MTs). To identify underlying mechanisms, network pharmacology, RNA sequencing (RNA-Seq), molecular docking, Western blotting (WB), and quantitative reverse transcription PCR (RT-qPCR) were performed. Results: YQZM significantly enhanced antigen-specific antibody titers, immune cell proportions, cytokine levels, and memory lymphocyte functions. UPLC-MS/MS analysis identified 31 bioactive compounds in YQZM. KEGG enrichment analysis based on RNA-Seq and network pharmacology implicated the TLR-JAK-STAT signaling pathway in YQZM’s immune-enhancing effects. WB and RT-PCR validated that YQZM upregulated the expression of critical nodes in the TLR-JAK-STAT signaling pathway. Furthermore, molecular docking indicated that YQZM’s primary active components exhibited strong binding affinity for critical proteins. Conclusions: YQZM effectively enhances vaccine-induced innate and adaptive immunity via a multi-component, multi-target mechanism, among which the TLR-JAK-STAT signaling pathway is a validated molecular target. Full article

Ophiocordyceps sinensis is a medicinal fungus with significant nutritional and utilization value. Temperature is a crucial factor influencing its growth, as temperature changes can impact enzyme activity, metabolite content, and gene expression during fungal cultivation. Currently, there are limited reports on the effects of temperature on the quality of fungal fermentation. This study focuses on O. sinensis and conducts temperature stress culture experiments. The results indicate that the optimal culture temperature range is between 18 and 23 °C, with extreme temperatures negatively affecting the morphology, growth rate, sporulation, and antioxidant systems of the strains. Further metabolomic and transcriptomic analyses revealed that differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) were primarily enriched in four metabolic pathways: linoleic acid metabolism, arginine and proline metabolism, and lysine degradation. Many significantly enriched metabolites across various pathways appear to be predominantly regulated by ribosomal and RNA polymerase genes. Furthermore, we cultured O. sinensis mycelium at various temperatures and observed that a significant number of genes and metabolites associated with apoptosis and senescence were expressed at 28 °C. This led to cell damage, excessive energy consumption, and ultimately inhibited mycelial growth. In summary, this study elucidates the response mechanisms of O. sinensis to key metabolic pathways under different temperature growth conditions and explores factors contributing to strain degradation. Full article

In this investigation, we established an intelligent computational framework comprising a novel starfish-optimization-algorithm-optimized support vector regression (SOA-SVR) model and a multi-algorithm joint strategy to evaluate the processing applicability of wheat flour in terms of sedimentation value (SV) and falling number (FN) using near-infrared (NIR) data (900–1700 nm) obtained using a miniaturized NIR spectrometer. By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R_P and RMSE_P) of 0.9605 and 0.2681 mL. Additionally, RFE, in combination with the iWOA, identified 30 MIWs and enabled the RFE/iWOA-SOA-SVR model to predict the FN with an R_P and RMSE_P of 0.9224 and 0.3615 s. The robustness and reliability of the two SOA-SVR models were further validated using 50 independent samples per index, a statistical two-sample F-test, and a t-test. In conclusion, the combination of a portable miniaturized NIR spectrometer and an SOA-driven SVR algorithm demonstrated technical feasibility in quantifying the SV and FN of wheat flour, thus providing a novel strategy for the on-site assessment of wheat flour processing applicability. Full article