Search Results (302)

Artificial gynogenesis is an essential technique for aquaculture breeding. Fertile offspring of the WuLi carp (Cyprinus carpio var. Quanzhounensis, 2n = 100, WLC) were successfully produced via gynogenesis using ultraviolet-irradiated sperm from the blunt snout bream (Megalobrama amblycephala, 2n = 48, BSB). As anticipated, gonadal section examination confirmed that all gynogenetic WuLi carp (2n = 100, GWB) were female. To investigate whether paternal DNA fragments from BSB were integrated into the GWB genome, comparative analyses of morphological traits, DNA content, chromosomal numbers, 5S rDNA sequences, microsatellite DNA markers, fluorescence in situ hybridization (FISH), growth performance and nutritional composition were systematically conducted between GWB and maternal WLC. The results revealed pronounced maternal inheritance patterns across morphological characteristics, DNA quantification, chromosomal configurations, 5S rDNA sequences and FISH signals, while microsatellite detection unequivocally confirmed paternal BSB DNA fragment integration into the GWB genome. Remarkably, GWB demonstrated significantly superior growth performance and elevated unsaturated fatty acid content relative to the maternal line. This approach not only addressed germplasm degradation in WLC but also provided valuable theoretical foundations for breeding programs in this commercially significant species. Full article

The mechanism by which quorum sensing (QS) enhances stress resistance in enterohemorrhagic Escherichia coli (E. coli) O157:H7 remains unclear. We employed optimized exogenous QS signal N-acyl-homoserinelactones (AHL) (100 μM 3-oxo-C6-AHL, 2 h) in EHEC O157:H7 strain EDL933, which was validated with endogenous yenI-derived AHL, to investigate QS-mediated protection against acid stress. RNA-seq transcriptomics identified key upregulated genes (e.g., rmf). Functional validation using isogenic rmf knockout mutants generated via λ-Red demonstrated abolished stress resistance and pan-stress vulnerability. Mechanistic studies employing qRT-PCR and stress survival assays established Ribosomal Hibernation Factor (RMF) as a non-redundant executor in a SdiA–RMF–RpoS axis, which activates ribosomal dormancy and SOS response to enhance EHEC survival under diverse stresses. For the first time, we define ribosomal hibernation as the core adaptive strategy linking QS to pathogen resilience, providing crucial mechanistic insights for developing EHEC control measures against foodborne threats. Full article

Forensic entomotoxicology is a subdiscipline that utilizes necrophagous insects as bioindicators for detecting drugs and toxicants in decomposed remains, particularly in cases where conventional biological matrices are no longer available. Toxic substances can profoundly alter insect development, physiology, and community succession, potentially impacting the accuracy of postmortem interval (PMI) estimation. This review systematically summarizes the effects of various xenobiotics, including pesticides, illicit drugs, sedatives, heavy metals, and antibiotics on larval growth, physiological traits, and gut microbial composition in forensically relevant flies. However, most studies to date have relied primarily on phenotypic observations, with limited insight into underlying molecular mechanisms. Significant interspecies and dose-dependent variability also exists in the absorption, metabolism, and physiological responses to xenobiotics. We highlight recent advances in multi-omics technologies that facilitate the identification of molecular biomarkers associated with xenobiotic exposure, particularly within the insect detoxification system. Key components such as cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs), and ATP-binding cassette (ABC) transporters play essential roles in xenobiotic metabolism and insecticide resistance. Additionally, the insect fat body serves as a central hub for detoxification, hormonal regulation, and energy metabolism. It integrates signals related to xenobiotic exposure and modulates larval development, making it a promising model for future mechanistic studies in insect toxicology. Altogether, this review offers a comprehensive and reliable framework for understanding the complex interactions between toxic substance exposure, insect ecology, and decomposition in forensic investigations. Full article

Metabolic dysfunction-associated fatty liver disease (MAFLD), a recently proposed term to replace non-alcoholic fatty liver disease (NAFLD), emphasizes the critical role of metabolic dysfunction and applies broader diagnostic criteria. Diagnosis of MAFLD requires evidence of hepatic steatosis combined with obesity, type 2 diabetes mellitus, or other metabolic dysregulation conditions, all of which significantly elevate the risk of chronic kidney disease (CKD). This review discusses the pathological mechanisms of lipid accumulation and insulin resistance in MAFLD and CKD, highlighting their mechanistic connections. Specifically, ectopic fat accumulation triggered by metabolic reprogramming, oxidative stress and inflammation induced by energy overload, modified lipids, uremic toxins, and senescence, as well as insulin resistance pathways activated by pro-inflammatory factors and lipotoxic products, collectively exacerbate simultaneous hepatic and renal injury. Moreover, interactions among hyperinsulinemia, the sympathetic nervous system, the renin–angiotensin system (RAS), and altered adipokine and hepatokine profiles further amplify insulin resistance, ectopic lipid deposition, and systemic damage. Finally, the review explores potential therapeutic strategies targeting lipid metabolism, insulin sensitivity, and RAS activity, which offer promise for dual-organ protection and improved outcomes in both hepatic and renal systems. Full article

Background: Huang Qin Decoction (HQD) is a well-established Traditional Chinese Medicine (TCM) formulation recognized for its application in the treatment of colorectal cancer (CRC). However, the precise therapeutic mechanisms remain inadequately defined. Methods: This study integrates metabolomics from a mouse model and network pharmacology to screen potential targets and bio-active ingredients of HQD. The pharmacological activity of HQD for CRC was evidenced via single-cell RNA sequencing (scRNA-seq), molecular docking, and molecular dynamics simulations. Atomic force microscopy (AFM) assays and cellular experimental validation were used to confirm the relative mechanisms. Results: The metabolite profile undergoes significant alterations, with metabolic reprogramming evident during the malignant progression of CRC liver metastasis. Network pharmacology analysis identified that HQD regulates several metabolic pathways, including arginine biosynthesis, alanine, aspartate, and glutamate metabolism, nitrogen metabolism, phenylalanine metabolism, and linoleic acid metabolism, by targeting key proteins such as aspartate aminotransferase (GOT1), cytochrome P450 1A2 (CYP1A2), and carbonic anhydrase 2 (CA2). ScRNA-seq analysis indicated that HQD may enhance the functionality of cytotoxic T cells, thereby reversing the immunosuppressive microenvironment. Virtual verification revealed a strong binding affinity between the identified hub targets and active constituents of HQD, a finding subsequently corroborated by AFM assays. Cellular experiments confirmed that naringenin treatment inhibits the proliferation, migration, and invasion of CRC cells by downregulating GOT1 expression and disrupting glutamine metabolism. Conclusions: Computational prediction and in vitro validation reveal the active ingredients, potential targets, and molecular mechanisms of HQD against CRC liver metastasis, thereby providing a scientific foundation for the application of TCM in CRC treatment. Full article

Biomass-derived growth stimulants are widely recognized as green and economical solutions that can significantly enhance microalgae culture efficiency and optimize the biomanufacturing process of target products. In this paper, we investigated the effect of ethanol synergized with guaiacol (GA) on biomass and β-1,3 glucan accumulation in edible microalgae, namely Euglena gracilis. The ethanol-induced mixotrophic mode significantly increased biomass and paramylon production by 12.68 and 6.43 times, respectively, compared to the autotrophic control group. GA further exerted toxic excitatory effects (hormesis) on top of ethanol mixotrophic nutrition. At the optimal concentration of 10 mg·L⁻¹ GA, chlorophyll a, carotenoids, and paramylon production increased by 8.96%, 11.75%, and 16.67%, respectively, compared to the ethanol-treated group. However, at higher concentrations, the biomass and paramylon yield decreased significantly. This study not only establishes an effective combinatorial strategy for enhancing paramylon biosynthesis but also provides novel insights into the hormesis mechanism of phenolic compounds in microalgae cultivation. The developed approach demonstrates promising potential for sustainable production of high-value algal metabolites while reducing cultivation costs, which could significantly advance the commercialization of microalgae-based biorefineries in food and pharmaceutical industries. Full article

Traditional project scheduling tools like Gantt charts struggle with dynamic adjustments and real-time optimization in complex construction projects, leading to inefficiencies and delays. This study addresses this challenge by proposing a dynamic optimization framework that integrates Building Information Modeling (BIM) and Artificial Intelligence (AI) to enhance schedule management. The framework comprises three layers: a data layer for collecting BIM and real-time site data, an analysis layer powered by AI algorithms for predictive analytics and optimization, and an application layer for visualizing progress and supporting decision-making. Through a case study on a large-scale water reservoir tunnel project in China, the framework demonstrated significant improvements in identifying schedule risks, optimizing resource allocation, and enabling real-time adjustments. Key innovations include a 4-in-1 Network Diagram Engine and a Blueprint Engine, which facilitate intuitive progress monitoring and automated task management. However, limitations in personnel skill matching, interface complexity, and mobile system performance were identified. This research advances the theoretical foundation of BIM-AI integration and provides practical insights for improving scheduling efficiency and project outcomes in the construction industry. Future work should focus on enhancing human resource management modules and refining system usability for broader adoption. Full article

Bacterial wilt (BW) is a globally serious soil-borne disease in a wide range of plants, caused by diverse strains of Ralstonia solanacearum. However, there are few research reports on melatonin regulating plant resistance against R. solanacearum. N-acetyltransferase SlSNAT2 is a rate-limiting enzyme in plant melatonin synthesis. This study elucidates the mechanisms of SlSNAT2 modulating tomato resistance to BW. SlSNAT2 was expressed in tomato roots, stems, and leaves and induced upon R. solanacearum inoculation. Knocking out SlSNAT2 significantly decreased the melatonin content in CRISPR/Cas9 mutant slsnat2. With R. solanacearum inoculation, the morbidity and disease index value of slsnat2 were significantly higher than those of the tomato wild-type plant Micro-Tom (MT) according to the wilt rate and severity. The chlorophyll levels, photosynthetic rates, and callus deposition quantity in slsnat2 were notably lower while the reactive oxygen species (ROS) level was considerably higher than those in the MT after inoculation. Additionally, the SlSNAT2 deficiency depressed the expression of the mitogen-activated protein kinase (MAPK) pathway genes (SlMPK1, SlMKK2), salicylic acid pathway genes (SlGluA, SlPR-1a), jasmonic acid pathway gene SlPin2, and pathogenesis-related (PR) protein genes (SlPR-STH2a, SlPR-STH2b, SlPR-STH2c, SlPR-STH2d). These results revealed SlSNAT2 enhanced the tomato resistance against R. solanacearum by orchestrating ROS homeostasis, callose deposition, MAPK signaling, hormone pathways, and PR gene transcripts. Full article

Accurately monitoring coupled water–nitrogen stress is critical for wheat (Triticum aestivum L.) productivity under climate change. This study developed a machine learning framework utilizing multimodal leaf electrophysiological signals––intrinsic resistance, impedance, capacitive reactance, inductive reactance, and capacitance––to decouple water and nitrogen stress signatures in wheat. A parallel modelling strategy was implemented employing Gradient Boosting, Random Forest, and Ridge Regression, selecting the optimal algorithm per feature based on predictive performance. Controlled pot experiments revealed IZ as the paramount biomarker across leaf positions, indicating its sensitivity to ion flux perturbations under abiotic stress. Crucially, algorithm-feature specificity was identified: Ridge Regression excelled in modeling linear responses due to its superior noise suppression, while GB effectively captured nonlinear dynamics. Flag leaves during reproductive stages provided significantly more stable predictions compared to vegetative third leaves, aligning with their physiological primacy as source organs. This framework offers a robust, non-invasive approach for real-time water and nitrogen stress diagnostics in precision agriculture. Full article

In recent years, micro-combs, due to their compact structure and high efficiency, have proven to be a practical solution for optical sources. In this paper, an approach to flexibly modulating micro-combs is proposed, and a simulation platform based on ${\mathrm{Si}}_3{\mathrm{N}}_4$ micro-combs with highly integrated, tunable, and reconfigurable features is built. By means of the Lugiato–Lefever equation model, the dynamic evolution process of micro-combs is analyzed, and a micro-ring resonator is designed with a free spectral range of 7.24 nm, an effective mode area of $1.0829{\mu \mathrm{m}}^2$, and coherent comb lines spanning over 125 THz. Cascaded silicon nitride micro-ring filters are utilized to obtain reconfigurable modulation effects for Kerr-frequency micro-combs. Due to the significance of flexibly controlled optical sources with high-repetition rates and multiple channels for system-on-chip, our proposal has potential in photonic integrated circuit systems, such as high-density photonic computing and large-capacity optical communications, in the future. Full article

Sedimentary facies identification constitutes a cornerstone of reservoir engineering. Traditional facies interpretation methods, reliant on manual log-response parameter analysis, are constrained by interpreter subjectivity, reservoir heterogeneity, and inefficiencies in resolving thin interbedded sequences and concealed fluvial sand bodies—issues marked by high interpretive ambiguity, prolonged cycles, and elevated costs. This study focuses on the Lower Cretaceous Yaojia Formation Member 1 (K2y1) in the satellite oilfield of the Songliao Basin, integrating sequence stratigraphy into a machine learning framework to propose an innovative convolutional neural network (CNN)-based facies recognition method using log-curve image groups by graphically transforming five log curves and establishing a CNN model that correlates log responses with microfacies. Results demonstrate the model’s capability to identify six microfacies types (e.g., subaqueous distributary channels, estuary bars, sheet sands) with 83% accuracy, significantly surpassing conventional log facies analysis. This breakthrough in interpreting complex heterogeneous reservoir lithofacies establishes a novel technical avenue for intelligent exploration of subtle hydrocarbon reservoirs. Full article

Understanding how clonal plants modulate their reproductive strategies under environmental fluctuations is critical for assessing their resilience amid rapid global change. Phragmites australis, a dominant clonal plant species in coastal wetlands worldwide, provides vital ecological and agricultural services. As coastal wetlands are currently impacted by sea level rise, P. australis faces both salinity and tidal level changes. However, the effects of the combined influences of these two abiotic factors on the reproductive strategy of P. australis remain unclear. We conducted a mesocosm experiment to examine how P. australis allocates resources between clonal and sexual reproduction under different salinity and tidal level conditions. We found increased salinity negatively impacted both sexual and clonal reproductive metrics and shifted reproductive allocation toward clonal reproduction; increasing tidal level had positive effects on the sexual reproductive metrics, but negatively affected the clonal reproductive metrics, leading to a shift toward greater allocation in sexual reproduction. Higher tidal levels could reduce the negative impact of salinity on the plant’s most reproductive metrics. These results highlighted the flexibility of P. australis in adapting its reproductive strategies to environmental changes, suggesting that it could be a promising component for sustainable wetland agriculture, offering significant economic value amid rapid global change. Full article

This work investigates multi-UAV navigation tasks where multiple drones need to reach initially unassigned goals in a limited time. Reinforcement learning (RL) has recently become a popular approach for such tasks. However, RL struggles with low sample efficiency when directly exploring (nearly) optimal policies in a large exploration space, especially with an increased number of drones (e.g., 10+ drones) or in complex environments (e.g., a 3D quadrotor simulator). To address these challenges, this paper proposes Multi-UAV Scalable Graph-based Planner (MASP), a goal-conditioned hierarchical planner that reduces space complexity by decomposing the large exploration space into multiple goal-conditioned subspaces. MASP consists of a high-level policy that optimizes goal assignment and a low-level policy that promotes goal navigation. MASP uses a graph-based representation and introduces an attention-based mechanism as well as a group division mechanism to enhance cooperation between drones and adaptability to varying team sizes. The results demonstrate that MASP outperforms RL and planning-based baselines in task and execution efficiency. Compared to planning-based competitors, MASP improves task efficiency by over 27.92% in a 3D continuous quadrotor environment with 20 drones. Full article

In this study, a novel silicon carbide (SiC) double-trench MOSFET (DT-MOS) combined Schottky barrier diode (SBD) and MOS-channel diode (MCD) is proposed and investigated using TCAD simulations. The integrated MCD helps inactivate the parasitic body diode when the device is utilized as a freewheeling diode, eliminating bipolar degradation. The adjustment of SBD position provides an alternative path for reverse conduction and mitigates the electric field distribution near the bottom source trench region. As a result of the Schottky contact adjustment, the reverse conduction characteristics are less influenced by the source oxide thickness, and the breakdown voltage (BV) is largely improved from 800 V to 1069 V. The gate-to-drain capacitance is much lower due to the removal of the bottom oxide, bringing an improvement to the turn-on switching rise time from 2.58 ns to 0.68 ns. These optimized performances indicate the proposed structure with both SBD and MCD has advantages in switching and breakdown characteristics. Full article

Peroxymonosulfate (PMS)-based advanced oxidation technology has emerged as an effective means for removing organic pollutants from water due to its strong oxidizing ability. However, enhancing the activation efficiency of PMS represents a key challenge at present. SrTiO₃, a typical perovskite metal oxide, holds potential in the field of the photocatalytic degradation of pollutants, yet its application is limited by the wide bandgap and fast carrier recombination rates. This study optimized the photocatalytic performance of SrTiO₃ by regulating its electronic structure and optical properties through cobalt (Co) doping. Experimental results (TRPL, TPV, UV–Vis DRS, ESR, etc.) and DFT calculations (GGA-PBE) demonstrated that Co doping shifted the d-band center of SrTiO₃ upwards, optimized the adsorption energy of SO₄⁻, enhanced the sunlight response range, and significantly improved carrier extraction efficiency. Under visible light irradiation, 2,4-dichlorophenol (2,4-DCP) could be effectively degraded within 60 min in a wide pH range. Through Fukui function calculation (B3LYP/6-31G*) and experimental characterization analysis (HPLC-MS and IC), the possible degradation pathways of 2,4-DCP and the mechanism for photocatalysis were investigated. The toxicity analysis (T.E.S.T) confirmed the reduced toxicity of the degradation products of 2,4-DCPs. This study provides a reference for the catalyst design and optimization strategy of PMS-based advanced oxidation technology. Full article