Search Results (3,735)

Tuber encompasses ectomycorrhizal fungi (EMF) of significant ecological and economic importance. This study reports the first controlled synthesis of ectomycorrhizae between the near-threatened species T. umbilicatum and Quercus glauca, confirmed through molecular analysis and detailed morphological characterization. Colonization dynamics, assessed over eight months, revealed substantial physiological benefits for the host. At six months post-inoculation, seedling height and above-ground biomass increased by 20.8% and 27.1%, respectively; these increments persisted to eight months, with above-ground biomass remaining 16.9% higher and below-ground biomass elevated by 25.4%. Concomitantly, the photosynthetic performance was markedly improved: a net photosynthetic rate (A) rose by 136.8% and stomatal conductance (g_s) by 36.5% at six months. Available phosphorus (AP) in the mycorrhizosphere was concurrently enhanced, exhibiting a 10.9% increment at eight months. These results underscore the agronomic and conservation utility of T. umbilicatum inoculation for Q. glauca and provide a critically experimental foundation for the ex situ preservation and sustainable truffle cultivation of this threatened fungal taxon. Full article

The Sentinel-3 Ocean and Land Colour Instrument (OLCI) is designed for water monitoring. Its 21-spectral bands serve as the basis for the precise retrieval of water quality parameters. However, its coarse resolution restricts the depiction of the spatial distribution of water quality parameters in small inland water bodies. Spatial–spectral fusion is a common method to address the inherent constraints between the spatial and spectral resolutions of sensors. Central to the popular methods is the deep learning-based method. Nonetheless, deep-learning-based models still face challenges in fusing Sentinel-2 Multi-Spectral Instrument (MSI) and Sentinel-3 OLCI data. Here, we propose a Multi-Scale-Attention-based Unsupervised Generative Adversarial Network (MSA-UGAN), which effectively integrates OLCI’s spectral advantage and MSI’s spatial resolution. Quantitative evaluation was conducted against five benchmark methods, including traditional approaches (GS, SFIM, MTF-GLP) and deep learning models (SRCNN, UCGAN). The results show that MSA-UGAN achieves the best overall performance: QNR (0.9709) and SSIM (0.9087) are the highest, while SAM (1.1331), spatial distortion (D_S = 0.0389), and spectral distortion (D_λ = 0.0252) are the lowest. This shows that MSA-UGAN can better preserve the spatial details of S2 MSI and the spectral features of S3 OLCI data. Moreover, ERGAS (2.2734) also performs excellently in the comparative experiments. The experiment of Chlorophyll-a inversion using the fused image in Chen Lake revealed a spatial gradient ranging from 3.25 to 19.33 µg/L, with the highest concentrations in the southwestern nearshore waters, likely associated with aquaculture. These results jointly indicate that MSA-UGAN can generate high-spatial-resolution multispectral images, and the fused images can be effectively utilized for water quality monitoring, thereby providing essential data support for the precision management and scientific decision-making regarding inland lakes. Full article

Rice (Oryza sativa L.) grain quality is a critical determinant of market value, consumer acceptance, and nutritional security. This multifaceted trait is governed by the dynamic interaction of genotype (G), environment (E), and management practices (M). In this review, we synthesize recent advances in understanding these multifaceted determinants. We first delineate the genetic architecture, emphasizing key genes and quantitative trait loci (QTLs) such as Wx, ALK, Chalk5, and the GS3/GW families, which control starch composition, gelatinization temperature, chalkiness, and grain dimensions, forming the foundational blueprint for quality potential. We examine how this genetic potential is influenced by environmental factors, focusing on the detrimental impacts of abiotic stresses, particularly high temperatures during grain filling and drought, which impair milling yield, increase chalkiness, and modify starch and protein profiles. Furthermore, we discuss how optimized agronomic strategies—including precision water management (e.g., alternate wetting and drying), balanced nitrogen fertilization, and targeted micronutrient (e.g., silicon) application—can mitigate these adverse effects and potentially improve specific quality parameters. Post-harvest handling is identified as the final determinant of product quality. We conclude that achieving high and stable rice quality under climate variability requires an integrated G × E × M approach. Prospects include next-generation breeding for climate-resilient quality, precision agronomy guided by real-time sensing, synergistic soil health management, and the integration of systems biology with digital agriculture to design sustainable, high-quality rice production systems. Full article

This study aimed to investigate the effects of feeding high-moisture corn (HMC) on weight performance, serum immune and antioxidant indices, rumen fermentation, microbial community, and metabolomics in Kazakh rams. A total of 32 healthy Kazakh rams were randomly divided into a control group (CT, diet with only ordinary crushed corn) and an experimental group (GS, diet with 50% ordinary crushed corn + 50% HMC), following a 7-day adaptation period and a 120-day trial period. Results showed that the F/G was significantly lower in the GS group than in the CT group (p < 0.05). FBW, net weight gain and ADG increased by 4.58%, 8.69%, and 8.70%, respectively, while ADFI decreased by 7.04% (p > 0.05). Regarding serum immune indices, IgA in the GS group was significantly higher at 40 d (p < 0.01), and IgM was significantly higher at 40, 80, and 120 d (p < 0.05). For antioxidant indices, the SOD activity in the GS group was significantly higher than that in the CT group at 120 d (p < 0.01). The CAT activity in the GS group was significantly higher at 40, 80, and 120 d (p < 0.01). Among rumen fermentation parameters, the concentration of butyric acid in the GS group was significantly lower than in the CT group (p < 0.01). Microbial diversity analysis indicated no significant differences in Alpha- and Beta-diversity of rumen microorganisms between the two groups. However, the relative abundance of Firmicutes_A at the phylum level was significantly higher in the GS group (p < 0.05), and the abundance of Cryptobacteroides was significantly higher than in the CT group (p < 0.01). Rumen metabolomic analysis identified a total of 1357 differential metabolites, among which 1130 showed significant differences, with 459 upregulated and 671 downregulated. These were mainly enriched in pathways such as Glutathione metabolism, Beta-alanine metabolism, Sphingolipid metabolism, and lysine degradation. In conclusion, feeding HMC can improve feed conversion efficiency and weight performance in Kazakh rams, regulate the structure of dominant rumen microorganisms, and enhance immune and antioxidant capacities. Full article

Road transportation is a major contributor to global CO₂ emissions, yet the influence of road geometry on vehicular emissions remains insufficiently quantified under real-world conditions. This study investigates the effects of horizontal and vertical alignments on CO₂ emissions of a light-duty gasoline passenger vehicle using Portable Emissions Measurement System (PEMS) data collected along a 62.4 km highway section. Six geometric parameters longitudinal grade, cross slope, horizontal curve radius, horizontal curve length, vertical curve radius, and vertical curve length were analyzed in combination with second-by-second vehicle dynamics. The results indicate that transient CO₂ emissions exhibit substantial variability, with instantaneous emission rates exceeding 7.0 g/s under high-load conditions. Longitudinal slope gradient shows the strongest linear association with emission rate (r = 0.63), while speed and acceleration exhibit weaker but statistically significant correlations (r = 0.21 and r = 0.28, respectively). Vehicle Specific Power (VSP), representing integrated tractive power demand, demonstrates stronger association with instantaneous CO₂ emissions than individual kinematic variables. In contrast, cross slope and horizontal curvature parameters display minimal direct correlations under the tested highway conditions. A nonlinear polynomial regression model modestly improves explanatory performance relative to a linear formulation (R² = 0.21 versus 0.15; RMSE approximately 56 g/km), although a substantial portion of variability remains unexplained, reflecting the complexity of transient real-world processes. Overall, vertical alignment and transient driving conditions dominate CO₂ emission variability, while horizontal parameters play supplementary roles. These findings provide empirical evidence for refining emission models and highlight the importance of incorporating vertical alignment into sustainable roadway design and carbon reduction strategies. Full article

Salt stress is a critical abiotic constraint affecting wheat yield and quality. In this study, we employed pot experiments under controlled salinity (2.8‰ NaCl) and multi-omics approaches to elucidate the regulatory mechanisms underlying grain quality formation in a strong-gluten wheat variety, Jinan 17. Key findings revealed that salt stress caused a significant 41.27% reduction in 1000-kernel weight, while protein content increased by 13.82%. However, bread volume and bread score were reduced by 16.85% and 13.08%, respectively. Multi-omics integration uncovered that salt stress repressed the expression of starch synthesis-related genes (e.g., TraesCS2A03G0349200), diverting carbon skeletons toward amino acid metabolism pathways. This metabolic reprogramming disrupted the glutenin/gliadin ratio (down 14.35%), with high molecular weight glutenin subunits (HMW-GS) synthesis being suppressed, while low molecular weight glutenin subunits (LMW-GS) and gliadin accumulated by 19.28% and 24.76%, respectively, forming a “high extensibility but low elasticity” gluten network. Furthermore, transcriptomic analysis identified significant upregulation of arginine metabolism genes (e.g., TraesCS6A03G0029900), which enhanced osmolyte biosynthesis and exacerbated carbon–nitrogen partitioning imbalances. This study provides novel insights into the molecular mechanisms of flour quality deterioration under saline conditions and identifies critical regulatory nodes for simultaneous improvement of starch synthesis and gluten network architecture in salt-affected wheat breeding programs. Full article

Multi-view 3D reconstruction is essential for smart city, supporting applications such as smart city planning and autonomous navigation. While traditional reconstruction pipelines and recent neural implicit methods, such as NeRF, achieve high visual fidelity, they often struggle with geometric accuracy and sparse-view scenarios. To address this challenge, we present DiffLiGS, a novel multi-modal 3D reconstruction framework that integrates LiDAR point clouds and LiDAR-guided diffusion-based priors into the 3D Gaussian Splatting (3DGS) pipeline, enabling high-fidelity and geometrically accurate models. Our method first densifies sparse LiDAR depths using a diffusion model and refines them through multi-view geometric constraints, producing dense LiDAR depth maps that provide robust supervision for 3DGS optimization. Leveraging these dense depth maps, we guide a Stable Video Diffusion model to synthesize novel view images, which are incorporated into training to enhance reconstruction completeness and visual realism. By jointly fusing rich appearance cues from multi-view images with precise LiDAR-derived geometry and diffusion priors, DiffLiGS achieves unified, geometry-aware 3D scene representations. Our extensive experiments demonstrate that our approach significantly improves both geometric accuracy and rendering quality compared to existing 3D reconstruction methods, enabling real-time, high-precision modeling of complex urban environments. Full article

Efficient microbial assimilation of high-concentration ammonium nitrogen and its conversion into value-added bioproducts represent a pivotal yet underexplored strategy for sustainable nitrogen management. Here, we report a newly isolated Bacillus velezensis strain, GY1, with a robust intrinsic capacity for simultaneous NH₄⁺-N assimilation and γ-polyglutamic acid (γ-PGA) biosynthesis. Under optimized conditions (37 °C, pH 7.0, C/N = 12:1), GY1 achieved 76.5% removal of ammonium nitrogen (400 mg/L) with negligible nitrite accumulation (<0.02 mg/L), indicating assimilation rather than nitrification. Transcriptomic analysis revealed a coordinated metabolic flux wherein the glutamine synthetase - glutamate synthase pathway GS-GOGAT pathway supplies glutamate for γ-PGA synthesis, while polymerization further facilitates ammonium sequestration via electrostatic interactions. GY1 produced up to 612.8 mg/L γ-PGA, and genetic overexpression of capB synchronized these pathways, enhancing both ammonium assimilation (87.4%) and γ-PGA yield (843.9 mg/L). Notably, this metabolic coupling remained resilient in complex substrates, achieving 68.8% ammonium removal and 220.7 mg/L γ-PGA production in untreated biogas slurry. Together, these findings establish GY1 as a metabolically robust platform linking nitrogen assimilation with biopolymer synthesis, offering a mechanistic framework for circular nitrogen economies. Full article

Steel surface defects significantly impact product quality and safety in industrial settings. Traditional defect detection methods suffer from inefficiencies and limitations. This study introduces an innovative deep learning architecture, CTG-YOLO, designed to enhance multi-scale defect detection accuracy on steel surfaces. By integrating a CBY parallel network structure, a TFF-PANet neck network, and a GS-Head detection head, our model achieves superior feature extraction and fusion capabilities. Experimental results on the NEU-DET and GC10-DET datasets demonstrate significant improvements, with mean Average Precision (mAP) scores of 76.55% and 69.94%, respectively, outperforming the original YOLOv8s by 3.72% and 3.14%. This research provides a robust foundation for industrial defect detection applications. Full article

In this study, we dissect the genetic effects of two major rice heading date genes, Heading date 1 (Hd1) and Grain number, plant height, and heading date 7 (Ghd7), in the regulation of six photosynthesis-related traits: the chlorophyll a/b contents, net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO₂ concentration (Ci), and transpiration rate (Tr). Using two sets of near-isogenic lines (Z43 and Z44) derived from a Zhenshan97/Milyang46 cross, functional Hd1 increased the chlorophyll contents but decreased the photosynthesis-related parameters; however, functional Ghd7 consistently inhibited all six traits. More importantly, there is a significant epistatic interaction between them: Hd1 only enhances the photosynthetic capacity under the non-functional background of ghd7 but intensifies its photosynthesis inhibition under the functional background of Ghd7. Transcriptome analysis showed that functional Ghd7 mainly down-regulated the expression of genes related to photosynthesis and chloroplast development, and the inhibitory effect was significantly enhanced in the presence of functional Hd1. GO enrichment analysis further confirmed that the chlorophyll synthesis, photosystem assembly, and electron transfer pathways were downregulated in the bifunctional allele combination. Although Hd1 promotes chlorophyll accumulation, it reduces the actual photosynthetic efficiency, indicating that it has different regulatory paths for chlorophyll synthesis and photosynthetic function. Both physiological and molecular evidence showed that the Hd1-Ghd7 module coordinated the regulation of the heading date and photosynthetic capacity, forming a trade-off relationship between “early heading–high photosynthesis” and “late heading–low photosynthesis”. This study reveals the pleiotropy of genes at the heading stage and provides a theoretical basis for the optimization of the source–sink balance in high-yield rice breeding. Full article

In recent years, plant genotyping has been shifting from the accumulation of whole-genome data toward their effective use in breeding programs This review examines key genotyping platforms, including single-nucleotide polymorphism (SNP) arrays, reduced-representation sequencing methods such as genotyping-by-sequencing (GBS) and restriction site-associated DNA sequencing (RAD-seq), targeted genotyping approaches, and whole-genome sequencing (WGS), analyzing their informativeness, cost, and computational limitations. The transition to pangenome-based genotyping and graph genomes is discussed, as these approaches reduce reference bias and increase sensitivity for detecting structural variants, introgressions, and rare alleles that are important for adaptation and breeding. The growing role of AI/ML is highlighted in modeling complex genotype–phenotype relationships, integrating genomic and phenotypic data, and improving the accuracy and interpretability of genomic predictions. Full article

Background: There is limited information about treatment success and outcomes in retrovirus-positive cats diagnosed with feline infectious peritonitis (FIP). Methods: A survey was distributed to caretakers of cats with feline leukemia virus (FeLV) and/or feline immunodeficiency virus (FIV) that were treated with GS-441524 for presumptive effusive FIP based on survey responses. Results: Cats with FIV developed FIP at an older age and longer after retrovirus infection than cats with FeLV. The average starting dosage (7 mg/kg/d) was increased in 65% of cats, and treatment was extended in 35%. Three cats relapsed (18%). There was a 94% (16/17) twelve-week survival rate and 82% (14/17) one-year survival rate. Seven cats were alive at follow-up, a median of 1306 days (range 983–2069) after FIP diagnosis, but many cats succumbed to neoplasia. Conclusions: Treatment success for retrovirus-positive cats with presumptive FIP was similar to previously reported outcomes for FIP alone. This could support current evidence of successful antiviral therapy for similar populations, if noncurrent, unstandardized protocols and unlicensed product use are considered. Additional studies are needed to determine ideal protocols for rapid resolution of FIP, good long-term survival, and limited relapse in retrovirus-positive cats, and the impact of the FeLV proviral load. Full article

Oxidative stress is a hallmark of carcinogenesis, yet the epigenetic mechanisms linking the lifestyle-based Oxidative Balance Score (OBS) to cancer risk remain poorly understood. This study investigated the epigenetic bridge between OBS and pan-cancer susceptibility using a multi-cohort approach integrating population-based and cancer genomic data. We calculated OBS based on 16 dietary and lifestyle factors (including dietary fiber, vitamins, minerals, physical activity, smoking, alcohol, and BMI) for 2749 participants from the Korean Genome and Epidemiology Study (KoGES) and identified OBS-associated CpG sites via epigenome-wide association analysis. These markers were validated against The Cancer Genome Atlas (TCGA) pan-cancer dataset using a novel Hybrid Pi-score (HyPi) to quantify the directional consistency between OBS-driven methylation in healthy individuals and cancer-specific epigenetic alterations across three clinical comparisons: normal vs. tumor, survival outcomes, and tumor stage. We observed profound sex-specific epigenetic signatures, with zero overlap in the top 200 OBS-associated CpG sites between males and females, underscoring fundamental sexual dimorphism in oxidative stress-epigenome interactions. Notably, the top 20 OBS-associated CpGs demonstrated strong directional consistency with multiple cancer types in TCGA, particularly in kidney renal clear cell carcinoma and lung adenocarcinoma, exhibiting methylation patterns inversely correlated with tumorigenesis. Mechanistically, these findings support the role of one-carbon metabolism and vitamin C-dependent DNA demethylation pathways in mediating OBS effects. Our study provides the first evidence of an epigenetic link between lifestyle-based oxidative balance and pan-cancer risk, highlighting the utility of the HyPi score as a novel sex-specific predictive biomarker for cancer prevention. These results suggest that optimizing oxidative balance through precision nutrition may epigenetically modulate cancer susceptibility, opening new avenues for personalized prevention strategies. Full article

Heat stress is a significant problem in dairy production that has detrimental effects on milk production, animal well-being and reproductive function. These effects are predicted to worsen due to climate change. With a focus on South African production systems, this review assesses the potential of combining precision livestock farming (PLF) and genomic selection (GS) technology to identify, measure and reduce heat stress in dairy cattle. In addition to PLF tools like wearable sensors, rumen boluses, infrared thermography, GPS- and weather-based decision-support systems, pertinent literature was reviewed to evaluate genomic approaches such as heritability estimates and genome-wide association studies identifying selection signatures for thermotolerance. While advances in genomic techniques have improved the identification of thermotolerance markers and the accuracy of breeding values for heat tolerance, evidence from recent studies shows that PLF technologies can accurately detect early physiological and behavioural indicators of heat stress in real time. The ability to select climate-resilient animals under realistic farm conditions is improved by combining high-resolution phenotypic data from PLF systems with genetic data. Overall, the review concludes that combining PLF and GS provides a useful and complementary approach to enhance the detection of heat stress, facilitate well-informed management choices and hasten the development of thermotolerant dairy cattle, all of which contribute to more sustainable dairy production under rising temperatures. Full article

Excessive fertilizer application is a common practice in agricultural production in the North China Plain. To determine an optimal fertilization strategy for summer maize with nitrogen-fixing bacterial inoculation, we conducted a two-year field experiment (2022–2023) using the conventional fertilization rate (600 kg ha⁻¹ NPK; N:P₂O₅:K₂O = 28:8:10; 100F by default) as a control and examined the effects of fertilizer reduction (at 90%, 80%, 62.5%, and 50% of 100F) combined with Azotobacter chroococcum inoculation on maize plants and soil. Although fertilizer reduction increased free amino acid content, soluble sugars, proteins, and fatty acids contents were reduced. However, bacterial inoculation significantly enhanced all the above nutritional indices in maize leaves. Bacterial inoculation under fertilizer reduction conditions can enhance the activity of key nitrogen metabolism enzymes (i.e., GS and GOGAT), which further supports nitrogen, sugar, and lipid metabolism in maize plants. Additionally, bacterial inoculation promoted root development, biomass accumulation, and grain nutritional value while significantly increasing yield under reduced fertilizer conditions. The highest yield (11,454 kg ha⁻¹) was achieved with bacterial inoculation at approximately 87F (≈522 kg ha⁻¹ NPK), while the non-inoculated control reached a peak yield (11,032 kg ha⁻¹) only at around 90.5F (≈543 kg ha⁻¹). The complementary effects of bacterial inoculation with fertilizer reduction resulted in improved nutrient supply and modulation of soil microbial diversity. Inoculation of A. chroococcum increased soil ammonium and nitrate levels and decreased soil pH, though it was associated with a decline in overall bacterial richness, which may have persistent and adverse effects on the soil. Both fertilizer reduction and bacterial inoculation significantly altered microbial community structure, with notable interannual variation. Collectively, our findings suggest that moderate fertilizer reduction (9.5–13%) combined with nitrogen-fixing bacteria inoculation can support sustainable maize production by maintaining higher yield, enhancing nutrient use efficiency, and improving soil health. However, due to pH-lowering effects, long-term monitoring is necessary to assess the ecological impact of nitrogen-fixing bacteria inoculation on soil microbial balance. Full article