Search Results (9,341)

Microorganisms, as abundant biological resources, offer significant potential in the development of selenium-enrichment technologies. Selenium-enriched microorganisms not only absorb, reduce, and accumulate selenium efficiently but also produce various selenium compounds without relying on synthetic chemical processes. In particular, nano-selenium produced by these microorganisms during cultivation has garnered attention due to its unique physicochemical properties and biological activity, making it a promising raw material for functional foods and pharmaceutical products. This paper reviews selenium-enriched microorganisms, focusing on their classification, selenium metabolism, and transformation mechanisms. It explores how selenium is absorbed, reduced, and transformed within microbial cells, analyzing the biochemical processes by which inorganic selenium is converted into organic and nano-selenium forms. Finally, the broad applications of selenium-enriched microbial products in food, medicine, and agriculture are explored, including their roles in selenium-rich foods, nano-selenium materials, and disease prevention and treatment. Full article

To address the demand of equivalent self-noise suppression in a distributed hydroacoustic sensing system, this study proposes a method to enhance the acoustic sensitivity and signal-to-noise ratio (SNR) using space division multiplexed (SDM) technology based on multi-core fiber (MCF). Specifically, a dual-channel demodulation system for distributed acoustic sensing is designed using MCF. The responses of different cores in MCF are almost consistent under external acoustic pressure, while their self-noise is inconsistent. Accordingly, the acoustic pressure phase sensitivity (APPS) and SNR gain based on the accumulation of dual-channel signals are analyzed, which are verified by experiments. It is shown that the self-noise correlation coefficient between the two cores is 0.11, increasing the noise power by 3.46 dB. The APPS is increased by 5.97 dB re 1 rad/μPa after the accumulation of two-core signals, which is close to the theoretical value (6 dB). The equivalent self-noise is reduced by 2.54 dB. The experimental results reveal that the enhancement of acoustic pressure phase shift sensitivity and SNR can be achieved by the space division multiplexing (SDM) of multi-core signals, which is of great significance for suppressing the equivalent self-noise of the system and realizing the acoustic pressure detection of weak underwater signals. Full article

Arthrobotrys flagrans is a typical nematode-trapping fungus that captures nematodes by producing three-dimensional networks. FlbD is a DNA-binding protein containing a Myb domain, which plays a significant role in fungal development. However, the biological function of FlbD in nematode-trapping fungi remains unknown. In this study, we analyzed the physicochemical properties and conserved domains of AfFlbD and constructed the AfFlbD knockout strains (ΔAfFlbD) using homologous recombination. Our functional analysis revealed that the mutants produced more cottony aerial mycelia at the colony center. Additionally, the cell length of the mutants was reduced, indicating that AfFlbD regulates cell morphology in A. flagrans. Chemical stress tolerance assays of the mutants demonstrated reduced sensitivity to NaCl and sorbitol stresses but increased sensitivity to SDS and H₂O₂ stresses compared to the WT strain. Interestingly, the mutants spontaneously produced traps, and its pathogenicity to nematodes was significantly enhanced, suggesting that AfFlbD negatively regulates the pathogenicity of A. flagrans. Furthermore, the number of chlamydospores produced by the mutants was markedly reduced, though their morphology remained unchanged. Fluorescence localization analysis showed that AfFlbD localizes to the nuclei of chlamydospores, thereby regulating chlamydospore formation. This study provides important theoretical insights into the biological function of the FlbD transcription factor and offers new perspectives for the application of nematode-trapping fungi as a method of controlling plant-parasitic nematodes. Full article

Combining antibiotics with propolis is an effective method to combat bacterial drug resistance. Nanoparticles are of interest in the antimicrobial field because of their higher drug stability, solubility, penetration power, and treatment efficacy. In this study, propolis nanoparticles (PNPs) were synthesized, and their antibacterial and anti-biofilm activities against methicillin-resistant Staphylococcus aureus (MRSA) in combination with ampicillin sodium (AS) were analyzed. The PNPs had an average particle diameter of 118.0 nm, a polydispersity index of 0.129, and a zeta potential of −28.2 mV. The fractional inhibitory concentration indices of PNPs and AS against tested MRSA strains highlighted this synergy, ranging between 0.375 and 0.5. Crystal violet staining showed that combined PNPs and AS significantly inhibited biofilm formation and reduced existing biofilm biomass. We then discovered that PNPs inhibited bacterial adhesion, extracellular polysaccharide synthesis, and mecR1, mecA, blaZ, and icaADBC gene expression. These results indicated that PNPs exerted a synergistic antibacterial effect with AS by inhibiting mecR1, mecA, and blaZ gene expressions to reduce the drug resistance of MRSA. Meanwhile, PNPs weakened bacterial adhesion and aggregation by suppressing icaADBC gene expression, allowing antibiotics to penetrate the biofilm, and exhibiting significant synergistic anti-biofilm activity. In summary, PNPs are promising candidates for combating MRSA-related diseases. Full article

With rapid global urbanization development, impermeable surface increase, urban population growth, building area expansion, and rising energy consumption, the urban heat island (UHI) effect is becoming increasingly serious. However, the spatial distribution of the UHI cannot be accurately extracted. Therefore, we focused on Luoyang City as the research area and combined the Getis-Ord-Gi* statistic and the greenest image to extract the UHI based on the Google Earth Engine using land surface temperature–spatial autocorrelation characteristics and seasonal changes in vegetation. As bare land considerably influenced the UHI extraction results, we combined the greenest image with the initial extraction results and applied the maximum normalized difference vegetation index threshold method to remove this effect on UHI distribution extraction, thereby achieving improved UHI extraction accuracy. Our results showed that the UHI of Luoyang continuously expanded outward, increasing from 361.69 km² in 2000 to 912.58 km² in 2023, with a continuous expansion rate of 22.95 km²/year. Furthermore, the urban area had a higher UHI area growth rate than the county area. Analysis indicates that the UHI effect in Luoyang has increased in parallel with the expansion of the building area. Intensive urban construction is a primary driver of this growth, directly exacerbating the UHI effect. Additionally, rising temperatures, population growth, and gross domestic product accumulation have collectively contributed to the ongoing expansion of this phenomenon. This study provides scientific guidance for future urban planning through the accurate extraction of the UHI effect, which promotes the development of sustainable human settlements. Full article

In relay-assisted Industrial Internet of Things (IIoT) systems with ultra-reliable low-latency communication (uRLLC) requirements, finite blocklength coding imposes stringent resource constraints. In this work, the packet error probability (PEP) and blocklength allocation across two-hop links are jointly optimized to minimize total blocklength (resource consumption) while satisfying reliability, latency, and throughput requirements. The original multi-variable problem is decomposed into two tractable subproblems. In the first subproblem, for a fixed total blocklength, the achievable rate is maximized. A near-optimal PEP is first derived via theoretical analysis. Subsequently, theoretical analysis proves that blocklength must be optimized to equalize the achievable rates between the two hops to maximize system performance. Consequently, the closed-form solution to optimal blocklength allocation is derived. In the second subproblem, the total blocklength is minimized via a bisection search method. Simulation results show that by adopting near-optimal PEPs, our approach reduces computation time by two orders of magnitude while limiting the achievable rate loss to within 1% compared to the exhaustive search method. At peak rates, the hop with superior channel conditions requires fewer resources. Compared with three baseline algorithms, the proposed algorithm achieves average resource savings of 21.40%, 14.03%, and 17.18%, respectively. Full article

The Tibetan Plateau (TP) is experiencing higher warming rates than elsewhere, which may affect regional vegetation growth. Particularly on the Eastern Tibetan Plateau (ETP), where the topography is diverse and rich in biodiversity, it is necessary to clarify the drivers of climate and topography on vegetation cover. In this research, we selected the Shaluli Mountains (SLLM) in the ETP as the study area, monitored the spatial and temporal dynamics of the regional vegetation cover using remote sensing methods, and quantified the drivers of vegetation change using Geodetector (GD). The results showed a decreasing trend in annual precipitation (PRE) (−2.4054 mm/year) and the Palmer Drought Severity Index (PDSI) (−0.1813/year) in the SLLM. Annual maximum temperature (TMX) on the spatial and temporal scales showed an overall increasing trend, and the regional climate tended to become warmer and drier. Since 2000, fractional vegetation cover (FVC) has shown a fluctuating upward trend, with an average value of 0.6710, and FVC has spatially shown a pattern of “low in the middle and high in the surroundings”. The areas with non-significant increases (p > 0.05) and significant increases (p < 0.05) in FVC accounted for 46.03% and 5.76% of the SLLM. Altitude (q = 0.3517) and TMX (q = 0.3158) were the main drivers of FVC changes. As altitude and TMX increased, FVC showed a trend of increasing and then decreasing. The results of this study help us to clarify the influence of climate and topography on the vegetation ecosystem of the ETP and provide a scientific basis for regional biodiversity conservation and sustainable development. Full article

Radar is one of the primary means of monitoring maritime targets. Compared to electro-optical systems, radar offers the advantage of all-weather, day-and-night operation. However, existing radar target detection algorithms predominantly achieve binary detection (i.e., determining the presence or absence of a target) and are unable to accurately classify target types. This limitation is particularly significant for coastal-deployed maritime surveillance radars, which must contend with not only maritime vessels but also various land-based and island targets within their monitoring range. This paper aims to enhance the informational breadth of existing binary detection methods by proposing a land–sea classification method of radar targets based on dynamic dense connections. The core idea behind this method is to merge the interlayer output features of the network and to augment and weigh them through dynamic convolutional combinations to improve the feature extraction capability of the network. The experimental results demonstrate that the proposed attribute recognition method outperforms current deep network architectures. Full article

Introduction: Osteoarthritis (OA), a leading cause of disability among the elderly, is characterized by progressive joint tissue destruction. Fucoidan, a sulfated polysaccharide with known anti-inflammatory and antioxidant properties, has been investigated for its potential to protect against interleukin-1 beta (IL-1β)-induced articular tissue damage. Methods: Human primary chondrocytes and synovial fibroblasts were pre-treated with 100 μg/mL fucoidan before stimulation with 1 ng/mL of IL-1β. The protective effects of fucoidan were assessed by measuring oxidative stress markers and catabolic enzyme levels. These in vitro findings were corroborated using a rat anterior cruciate ligament transection-induced OA model. To explore the underlying mechanisms, particularly the interaction between microRNAs (miRs) and heme oxygenase-1 (HO-1), five candidate miRs were identified in silico and experimentally validated. Luciferase reporter assays were used to confirm direct interactions. Results: Fucoidan exhibited protective effects against IL-1β-induced oxidative stress and catabolic processes in both chondrocytes and synovial fibroblasts, consistent with in vivo observations. Fucoidan treatment restored HO-1 expression while reducing inducible nitric oxide synthase and matrix metalloproteinase levels in IL-1β-stimulated cells. Notably, this study revealed that fucoidan modulates the miR-22/HO-1 pathway, a previously uncharacterized mechanism in OA. Specifically, miR-22 was upregulated by IL-1β and subsequently attenuated by fucoidan. Luciferase reporter assays confirmed a direct interaction between miR-22 and HO-1. Conclusion: The results demonstrate that fucoidan mitigates OA-related oxidative stress in chondrocytes and synovial fibroblasts through the novel modulation of the miR-22/HO-1 axis. The miR-22/HO-1 pathway represents a crucial therapeutic target for OA, and fucoidan may offer a promising therapeutic intervention. Full article

Kiwifruit (Actinidia spp.) is a globally important economic fruit with high nutritional value. Fruit peelability, defined as the mechanical ease of separating the peel from the fruit flesh, is a critical quality trait influencing consumer experience and market competitiveness and has emerged as a critical breeding target in fruit crop improvement programs. The present review systematically synthesized existing studies on kiwifruit peelability, and focused on its evolutionary trajectory, genotypic divergence, quantitative evaluation, possible underlying mechanisms, and artificial manipulation strategies. Kiwifruit peelability research has advanced from early exploratory studies in New Zealand (2010s) to systematic investigations in China (2020s), with milestones including the development of evaluation metrics and the identification of genetic resources. Genotypic variation exists among kiwifruit genera. Several Actinidia eriantha accessions and the novel Actinidia longicarpa cultivar ‘Guifei’ exhibit superior peelability, whereas most commercial Actinidia chinensis and Actinidia deliciosa cultivars exhibit poor peelability. Quantitative evaluation highlights the need for standardized metrics, with “skin-flesh adhesion force” and “peel toughness” proposed as robust, instrument-quantifiable indicators to minimize operational variability. Mechanistically, peelability is speculated to be governed by cell wall polysaccharide metabolism and phytohormone signaling networks. Pectin degradation and differential distribution during fruit development form critical “peeling zones”, whereas ethylene, abscisic acid, and indoleacetic acid may regulate cell wall remodeling and softening, collectively influencing skin-flesh adhesion. Owing to the scarcity of easy-to-peel kiwifruit cultivars, artificial manipulation methods, including manual peeling benchmarking, lye treatment, and thermal peeling, can be employed to further optimize kiwifruit peelability. Currently, shortcomings include incomplete genotype-phenotype characterization, limited availability of easy-peeling germplasms, and a fragmented understanding of the underlying mechanisms. Future research should focus on methodological innovation, germplasm development, and the elucidation of relevant mechanisms. Full article

To investigate the evolution of the optothermal properties of lithium niobate with ion beam irradiation parameters, the thermal effect theory was analyzed, and ion beam irradiation technology was used to modify lithium niobate samples. The transmittance of lithium niobate crystals after ion beam irradiation and the relationship between their optothermal properties and transmittance were studied. The results show that the average surface optothermal signal of lithium niobate exhibits a significant dependence on ion beam parameters. When the ion beam voltage is 800 V, the ion beam current is 30 mA, and the irradiation time is 60 s, a distinct absorption peak is observed on the surface of lithium niobate, with an average surface optothermal signal of 5377.34 ppm, demonstrating potential for all-optical modulation. Full article

As the penetration rate of new energy continues to increase, the active voltage support capability of the power system is decreasing. The grid-forming static var generator (GFM-SVG) features the advantages of fast dynamic response, strong reactive power support, and high overload capacity, which play an important role in maintaining voltage stability. However, the parameters of the GFM-SVG are often unknown due to trade secret reasons. Meanwhile, the parameters may be changed during the long-term operation of the system, which brings challenges to the system stability analysis and control. Aiming at this problem, a parameter identification method based on trajectory sensitivity analysis and the proximal policy optimization (PPO) algorithm is proposed in this paper. Firstly, through trajectory sensitivity analysis, the key influential parameters on the output characteristics of the GFM-SVG can be selected, which can reduce the dimensionality of the identification parameters and improve the identification efficiency. Then, a parameter identification framework based on the PPO algorithm is constructed for GFM-SVGs, which utilizes its adaptive learning capability to achieve accurate identification of the key parameters of the system. Finally, the effectiveness of the proposed parameter identification method is verified through simulation examples. The simulation results show that the identification error of the parameters in the GFM-SVG is small. The proposed method can characterize the output response of the GFM-SVG under different operating conditions. Full article

During the process of oil and gas drilling, due to the existence of pores or micro-cracks, drilling fluid is prone to invade the formation. Under the action of hydration expansion of clay in the formation and liquid pressure, wellbore instability occurs. In order to reduce the wellbore instability caused by drilling fluid intrusion into the formation, this study proposed a method of forming a dynamic hydrogen bond cross-linked network weak gel structure with modified nano-silica and P(AM-AAC). The plugging performance of the drilling fluid and the performance of inhibiting the hydration of shale were evaluated through various experimental methods. The results show that the gel composite system (GCS) effectively optimizes the plugging performance of drilling fluid. The 1% GCS can reduce the linear expansion rate of cuttings to 14.8% and increase the recovery rate of cuttings to 96.7%, and its hydration inhibition effect is better than that of KCl and polyamines. The dynamic cross-linked network structure can significantly increase the viscosity of drilling fluid. Meanwhile, by taking advantage of the liquid-phase viscosity effect and the physical blocking effect, the loss of drilling fluid can be significantly reduced. Mechanism studies conducted using zeta potential measurement, SEM analysis, contact angle measurement and capillary force assessment have shown that modified nano-silica stabilizes the wellbore by physically blocking the nano-pores of shale and changing the wettability of the shale surface from hydrophilic to hydrophobic when the contact angle exceeds 60°, thereby reducing capillary force and surface free energy. Meanwhile, the dynamic cross-linked network can reduce the seepage of free water into the formation, thereby significantly lowering the fluid loss of the drilling fluid. This research provides new insights into improving the stability of the wellbore in drilling fluids. Full article

The rhizosphere microbiome plays an important role in carbon- and nitrogen-cycling in soil and in the stress response of plants. It also affects the function of the ammonium transporter (AmtB) that senses nitrogen levels inside and outside the cells of the associative nitrogen-fixing bacterium GXGL-4A. However, the potential mechanism of the interaction between the AmtB deletion mutant of GXGL-4A (∆amtB) and microorganisms in the rhizosphere of plants under low-nitrogen stress is still unclear. As revealed by transcriptome analyses, mutation of the amtB gene in GXGL-4A resulted in a significant up-regulation of many functional genes associated with nitrogen fixation and transportation at transcription level. The application of ∆amtB changed the nitrogen level in the rhizosphere of cucumber seedlings and reshaped the microbial community structure in the rhizosphere, enriching the relative abundance of Actinobacteriota and Gemmatimonadota. Based on bacterial functional prediction analyses, the metabolic capacities of rhizobacteria were improved after inoculation of cucumber seedlings with the original strain GXGL-4A or the ∆amtB mutant, resulting in the enhancement of amino acids, lipids, and carbohydrates in the cucumber rhizosphere, which promoted the growth of cucumber plants under a low-nitrogen stress condition. The results contribute to understanding the biological function of gene amtB, revealing the regulatory role of the strain GXGL-4A on cucumber rhizosphere nitrogen metabolism and laying a theoretical foundation for the development of efficient nitrogen-fixing bacterial agents for sustainable agricultural production. Full article

The resilience concept is well established in engineering, but the quantitative studies of vessel impact resilience for bridge structures remain limited. This paper presents an integrated framework for assessing vessel impact resilience under combined rebar corrosion and vessel collision effects. First, a corroded reinforced concrete bridge is considered for nonlinear static analysis to quantify initial corrosion damage and for nonlinear dynamic analysis to evaluate post-impact function loss. Then, recovery for each damage state is modeled by using both negative exponential and triangular recovery functions to estimate restoration times and to obtain a vessel impact resilience index. The results show that increasing corrosion severity markedly reduces resilience capacity. Furthermore, resilience indices obtained from the negative exponential function generally exceed those from the triangular function, and this improvement becomes more significant at lower resilience levels. Resilience indices calculated by using negative exponential and triangular recovery functions show negligible differences when the concrete bridge is in the uncorroded initial state and the vessel impact velocity is below 1.5 m/s. However, as reinforcement corrosion increases, the maximum discrepancy between these two recovery functions also increases, reaching a value of 67% at a corrosion level of 15.0%. From the numerical results obtained from a case study, it is important to select an appropriate recovery model when assessing vessel impact resilience. For rapid initial restoration followed by slower long-term recovery, the negative exponential model yields greater resilience gains compared to the triangular model. The proposed method thus provides an effective tool for engineers and decision makers to evaluate and improve the vessel impact resilience of aging bridges under the combined corrosion and impact effects. This proposes a quantitative metric for resilience-based condition assessment and maintenance planning. Full article