Search Results (42,413)

An integrated study was conducted to evaluate quality loss in small marine fish—sardine (Sardina pilchardus), horse mackerel (Trachurus trachurus), and megrim (Lepidorhombus whiffiagonis)—during a 9-day chilled storage. A progressive increase in microbial counts was observed in all species; aerobic mesophiles exceeded the spoilage limit (7 log CFU·g⁻¹) only in horse mackerel by day 9 (7.02 log CFU·g⁻¹), while remaining below this threshold in sardine (4.49 log CFU·g⁻¹) and megrim (5.42 log CFU·g⁻¹). Lipid oxidation showed species-specific behaviour, with sardine and horse mackerel exhibiting higher peroxide values (up to 19.73 and 10.73 meq O₂·kg⁻¹ lipids, respectively) and TBARS formation, whereas megrim showed limited primary and secondary oxidation but a marked increase in tertiary products (ca. six-fold). Lipid hydrolysis increased significantly, with free fatty acids rising by factors of approximately 4.1 (sardine), 13.7 (horse mackerel), and 18.6 (megrim). Similarly, trimethylamine formation increased markedly, with values rising by factors of about 13.1, 19.0, and 51.8, respectively. Sensory evaluation indicated that all species remained acceptable up to day 6 but were unacceptable by day 9, establishing a shelf life of approximately 6 days. Overall, horse mackerel showed the fastest deterioration, highlighting the need for species-specific shelf life assessment strategies. Full article

Epidemiological investigations have indicated that females are particularly susceptible to perfluorooctane sulfonate (PFOS)-induced cognitive impairment, yet the mechanisms underlying this sex-specific vulnerability remain obscure. Estrogen and estrogen receptor β (ERβ) signaling are essential for female brain function, but their role in PFOS-induced neurotoxicity has not been explored. We therefore hypothesized that disruption of astrocyte-derived estrogen–ERβ signaling, leading to downregulation of N-myc downstream-regulated gene 2 (NDRG2) and subsequent synaptic dysfunction, contributes to PFOS-induced neurotoxicity in females. Female rats were exposed to PFOS for 30 days, followed by behavioral tests and hippocampal analysis. PC12 cells were treated with astrocyte-conditioned medium (ACM) to assess synaptic injury. Molecular docking was further performed to predict the binding affinity between PFOS and ERβ. In vivo, PFOS exposure impaired cognitive performance and caused hippocampal dysfunction, accompanied by decreased levels of estradiol (E2), aromatase (AROM), ERβ, N-myc downstream regulated gene 2 (NDRG2), and AMPA receptors (AMPARs), together with increased glial fibrillary acidic protein (GFAP) and Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) in the hippocampus. In vitro, PFOS-exposed C6 cells showed reduced E2, AROM, ERβ, and NDRG2, along with elevated GFAP and extracellular glutamate concentration. PC12 cells treated with PFOS-ACM exhibited decreased synaptophysin (SYP), postsynaptic density protein 95 (PSD-95), and AMPARs, as well as increased CaMKII, indicative of synaptic injury. Pretreatment with E2 or the ERβ agonist diarylpropionitrile (DPN) could reverse these molecular alterations and mitigate neuronal dysfunction. Molecular docking revealed a strong binding affinity between PFOS and ERβ. Collectively, these findings support our hypothesis that PFOS impairs cognitive function in female rats by disrupting astrocyte-derived estrogen–ERβ–NDRG2 signaling, with NDRG2 as a potential downstream effector. This provides a mechanistic basis for the heightened female susceptibility to PFOS neurotoxicity and highlighting ERβ as a potential therapeutic target. Full article

(-)-Epigallocatechin gallate (EGCG) possesses potent bioactivities but its applications in functional cosmetics is severely limited by its poor water solubility and chemical instability. To overcome these challenges, this study engineered a recombinant levansucrase from Vibrio natriegens to catalyze the transfructosylation of EGCG. The conversion rate of EGCG to fructoside reached 65.59%. The purified product was unequivocally identified as EGCG-1F, with a fructosyl group linked to the 3′-hydroxyl group. Compared to pristine EGCG, EGCG-1F exhibited remarkably enhanced water solubility (96.6-fold that of EGCG) and aqueous stability under acidic and thermal conditions. Biological evaluation revealed that EGCG-1F significantly enhanced HaCaT cell migration, upregulated the expression of basement membrane-associated collagens in ultraviolet B-damaged HaCaT cells, and modulated ultraviolet A-induced senescence in human dermal fibroblasts by type I collagen, type III collagen and matrix metalloproteinase-1 balance. This study demonstrates that enzymatic fructosylation is an effective approach to generate a stable and safe EGCG derivative with potential applications in skin barrier repair and anti-aging functional cosmetics. Full article

Three-dimensional surface reconstruction is essential for accurately acquiring the external quality parameters of watermelons, such as size, volume, and defect area. Binocular stereo vision provides a low-cost and easily deployable solution for the single-view 3D reconstruction of watermelons. However, watermelons present highly similar surface textures, and as typical spheroid-like objects, the excessive angle between surface normals of edge regions and the camera optical axis leads to insufficient feature representation. Consequently, directly applying existing stereo matching algorithms often introduces matching ambiguities, and lightweight networks struggle to balance real-time performance with matching accuracy. This study focuses on the high-precision single-view point cloud generation of Kirin watermelons. To address these issues, we first construct a cross-modal, high-precision Kirin watermelon stereo matching dataset. Building upon the Fast-ACVNet+ architecture, we then propose MI-ACVNet, a lightweight stereo matching network tailored for high-precision watermelon point cloud acquisition. In the feature extraction stage, a Multi-Scale Stereo Feature Extraction (MSFE) module is adapted. By incorporating the re-parameterized network MobileOne and Epipolar-Enhanced Coordinate Attention (E2CA), MSFE improves the discriminative capability for weak and similar textures without compromising inference speed. For cost computation, a Coarse-to-Fine Cascaded Residual Correction (C2F-CRC) strategy is incorporated to construct a fine-grained cost volume via sub-pixel interpolation, enhancing the network’s ability to capture subtle surface fluctuations. Furthermore, a Semantics-Guided Region-Aware Loss (SGRA-Loss) is formulated, leveraging semantic masks to apply differentiated supervision weights across edge, center, and background regions to significantly improve edge matching accuracy. Ablation studies validate the effectiveness of the MSFE, C2F-CRC, and SGRA-Loss components. Compared to the baseline model, the full MI-ACVNet reduces the End-Point Error (EPE) by 19.5% and the Bad-0.5 error rate by 34.5% in the watermelon region. Furthermore, when compared against five mainstream algorithms (StereoNet, AANet, HSMNet, LightStereo-L, and NMRF-swint), MI-ACVNet achieves state-of-the-art performance: EPE and Bad-0.5 are reduced to 0.091 pixels and 1.159%, respectively, with a single-frame inference time of only 46 ms. The average depth error of the reconstructed point clouds is merely 0.26 mm. By ensuring both real-time efficiency and high-precision depth estimation, this method demonstrates promising potential for deployment in industrial Kirin watermelon sorting lines, driving sorting equipment toward higher precision and intelligence. Full article

When a large language model (LLM) answers a question using retrieved documents, retrieval-augmented generation (RAG) is the standard approach. Retrieving more documents improves answer accuracy but increases cost and response time; retrieving fewer documents saves resources but may miss critical information. Most existing RAG systems sidestep this dilemma by applying the same retrieval setting to every query, regardless of how simple or complex the question is. This wastes budget allocation on easy questions and under-serves hard ones. This paper introduces Cost-Aware RAG (CA-RAG), a routing framework that solves this problem by treating each query individually. For every incoming question, CA-RAG selects the most suitable retrieval strategy from a fixed menu of four options, ranging from no retrieval to fetching the top $k=10$ most-relevant documents. The selection is driven by a scoring formula that balances expected answer quality against predicted cost and response time. The weights in this formula act as dials: adjusting them shifts the system toward speed, savings, or quality without any retraining. CA-RAG is built on Facebook AI Similarity Search (FAISS) for document retrieval, OpenAI gpt-4o-mini for generation, and text-embedding-3-small for dense retrieval embeddings. We evaluate CA-RAG on a benchmark of 28 queries. The router assigns different strategies to different queries, achieving 26% fewer billed tokens compared to always using heavy retrieval and 34% lower response time compared to always answering without retrieval, while maintaining answer-quality parity in both cases. Further analysis shows that most savings come from simpler queries, where heavy retrieval was unnecessary. All results are reproducible from logged comma-separated value (CSV) files. CA-RAG demonstrates that a small but well-designed set of retrieval strategies combined with lightweight per-query routing can meaningfully reduce the cost and latency of LLM deployments without compromising answer quality. Full article

Sleep deprivation is a recognized risk factor for neuroinflammatory and neurodegenerative disorders. Dopamine signaling through D2 receptors (DRD2) has emerged as a potential immunomodulatory pathway in the central nervous system. The present study investigated whether activation of DRD2 by quinpirole (QUIN) modulates astrocytic and microglial responses and NF-κB nuclear translocation in a murine model of rapid eye movement sleep deprivation (RSD). Male CD1 mice were subjected to 72 h of RSD and treated with QUIN (2 mg/kg/day). GFAP, Iba-1, and NF-κB expression were evaluated in hippocampal subregions (CA1, CA3, dentate gyrus) and the medial parietal cortex using immunofluorescence and confocal microscopy. RSD increased GFAP and Iba-1 expression and induced morphological changes consistent with glial activation. Notably, RSD increased NF-κB nuclear expression in microglia. QUIN administration reduced Iba-1 expression, attenuated microglial morphological alterations, and reduced NF-κB nuclear expression across all analyzed regions, even in RSD-subjected mice. These findings suggest that DRD2 activation exerts anti-inflammatory effects in the brain during REM sleep deprivation and that dopaminergic signaling may represent a key target for neuroinflammation associated with sleep loss. Full article

Root-knot nematodes (RKNs; Meloidogyne spp.) are among the most destructive plant parasites, causing severe yield losses in diverse crops. Reactive oxygen species (ROS), particularly superoxide radicals (O₂•⁻) and hydrogen peroxide (H₂O₂), are central regulators of plant–RKN interactions. This review synthesizes current molecular, biochemical, genetic, transcriptomic, and translational evidence showing that the outcome of infection is determined by the spatiotemporal regulation of H₂O₂ rather than by ROS abundance alone. In resistant interactions, nematode perception activates PTI-associated signaling through selected cell-surface receptor complexes, including some BAK1/SERK3-associated pathways, together with BIK1, Ca²⁺ signaling, and RBOHD/F, generating a sustained oxidative activity associated with salicylic acid-dependent immune signaling and reduced H₂O₂-scavenging capacity and coupled to hypersensitive response, lignin and callose deposition, and feeding site restriction. In susceptible interactions, RKNs deploy ROS-targeting effectors such as Mi-CRT, MjTTL5, CATLe, Mj-NEROSs, and CMII to suppress ROS production, enhance antioxidant scavenging, or weaken SA-dependent defense. Evidence from a cyst-nematode system suggests that RBOH-derived ROS can restrict excessive cell death around syncytia; whether an analogous lower-redox requirement exists in RKN-induced giant cells remains unresolved. Finally, redox-based strategies, including CRISPR/Cas editing, host-induced gene silencing, chemical priming, and biocontrol, are discussed as promising approaches for durable and sustainable nematode resistance. Full article

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by limited treatment options and poor prognosis. Gemcitabine is a commonly used chemotherapy; however, gemcitabine resistance in PDAC poses a critical barrier to effective treatment, as the underlying mechanisms are not yet fully understood. Methods: This study employs an exploratory untargeted metabolomics approach to investigate metabolic differences in PDAC cells in the presence and absence of gemcitabine treatment. HPAF-II, MIA PaCa-2, and BxPC-3 cell lines were used as models for gemcitabine-resistant, moderately responsive, and permissive PDAC cells, respectively. Results: MTT assay results revealed that BxPC-3 cells are highly sensitive to gemcitabine treatment, HPAF-II cells are the most resistant, and MIA PaCa-2 cells exhibit moderate sensitivity. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) of the metabolomics data demonstrated clear differentiation of gemcitabine-treated and untreated (control) cells. When comparing the treated vs. control conditions, 170 metabolites matched to an in-house library of standards were significant (p < 0.05 or fold change ≥ 2 or VIP ≥ 1) differentiators in HPAF-II cells, whereas MIA PaCa-2 and BxPC-3 cells had 178 and 218 differentiating metabolites, respectively. HPAF-II cells treated with gemcitabine had significantly higher levels of N-acetylneuraminic acid and 7-dehydrocholesterol compared with the control group. In contrast, these metabolites were significantly lower or non-significant in BxPC-3 treated cells. Pathway analysis revealed that the steroid biosynthesis pathway was significantly perturbed in HPAF-II cells, whereas amino sugar and nucleotide sugar metabolism was predominantly altered in BxPC-3 cells. Conclusions: Overall, this exploratory study reveals metabolic differences between treated and untreated cells to derive targeted therapeutic strategies that could be used in the future to improve treatment outcomes for PDAC patients. Full article

With the widespread application of microwave technology in communication and medical fields, concerns regarding its biosafety, particularly the effects on the central nervous system, have increased. The brain is considered a sensitive target organ for microwave radiation; however, the molecular mechanisms underlying microwave-induced cognitive impairment remain unclear. The purpose of this study was to evaluate the effects of 4.3 GHz microwave radiation at different power densities on spatial learning and memory in mice, and to identify key molecular changes in the hippocampus associated with cognitive impairment. Mice (male, C57BL/6N) were exposed to 4.3 GHz microwave radiation at power densities of 10 or 30 mW/cm² for 30 min. Spatial learning and memory abilities were assessed using the Morris water maze (MWM). The hippocampal structure was assessed by HE staining at multiple time points following microwave exposure. Integrated RNA-sequencing (RNA-seq) and 4D-data-independent acquisition (4D-DIA) analyses of the hippocampus were performed at 6 h after microwave exposure, and differentially expressed molecules were selected and validated by quantitative polymerase chain reaction (qPCR) and parallel reaction monitoring (PRM). The 4.3 GHz microwave exposure significantly prolonged escape latency in the MWM, indicating impaired spatial learning or navigation ability. Histological examination revealed transient neuronal damage in the hippocampal CA1 and CA3 regions. Multi-omics analysis and subsequent validation revealed molecular alterations. Following microwave radiation, the expression of synaptic plasticity-related genes Arc and Ebf3 was significantly upregulated. At the protein level, significant downregulation was observed for Protein sidekick-2 and IQGAP1, while WNK3 was significantly upregulated. In summary, 4.3 GHz microwave exposure impaired spatial learning or navigation ability, accompanied by structural damage in the hippocampus and molecular alterations in synaptic plasticity-related pathways. Arc, Ebf3, Protein sidekick-2, WNK3, and IQGAP1 might serve as candidate molecules for understanding and mitigating microwave-induced cognitive deficits. Full article

As autonomous driving moves toward large-scale deployment, controllable and efficient simulation testing has become a primary means of ensuring system safety. However, in open-world environments, existing scenario catalogs often fail to cover the full spectrum of potential traffic situations, while rare yet high-risk critical scenarios are even harder to obtain. This scarcity renders traditional random sampling and parameter-sweeping strategies ineffective for identifying unknown risks. This study addresses two core challenges: (1) incomplete scenario catalogs hindering unknown critical scenario recognition and (2) insufficient critical samples, where generated scenarios struggle to balance physical realism and edge case coverage. To tackle the first challenge, we propose an open-world recognition method integrating transformers, random forests, and extreme value theory for precise unseen sample detection. Outlier and validity filtering ensure clustering reliability, and random forest activation patterns cluster unknown samples into meaningful groups to expand the scenario catalog. Experiments show the overall F1_macro improved by 2.3 percentage points over SOTA MDENet, with its clustering accuracy surpassing iterative-AutoNovel by 6.2 percentage points. For the second challenge, we introduce a reinforcement-learning-based maneuver-level generation method. It extracts maneuver semantics from trajectories, constructs a low-dimensional parameter space, and models parameter correlations via a multivariate multimodal distribution. A dual-layer LSTM agent with a composite reward iteratively optimizes policies toward high-risk edge scenarios. The results outperformed RLBE; longitudinal and lateral reconstruction errors were reduced by 32.7% and 15.3%, respectively, while high-risk time steps and the collision rate increased by 4.3% and 5.1%, respectively. Finally, we develop a CARLA-based scenario-driven simulation framework, integrating recognized and generated scenarios into closed-loop testing on high-risk road segments. CAS failure cases validate the generated scenarios’ physical feasibility and extreme challenge. Targeted augmentation of scarce critical scenarios enriches the test library and ensures broader coverage of real-world driving conditions. Full article

Oxide systems with the nominal composition LaCaCuVMnO_7.5 and composites modified with the YBa₂Cu₃O_x phase were synthesized by the solid-state reaction method. The phase composition and structural features were systematically investigated by X-ray diffraction (XRD), Rietveld refinement, and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX). The parent oxide was found to form a two-phase system, consisting of an orthorhombic perovskite-like phase and a cubic manganite–vanadate phase, whereas the introduction of 10 wt.% YBa₂Cu₃O_x resulted in the formation of a three-phase composite containing an additional cuprate phase. Thermophysical investigations in the 298–673 K range revealed λ-type-like anomalies in the heat capacity, which may be associated with possible structural or interphase transformations in the investigated oxide systems. The incorporation of YBa₂Cu₃O_x significantly modified the temperature dependence of heat capacity and increased its values over both low- and high-temperature regions. Electrophysical measurements in the 293–483 K range confirmed the semiconducting nature of conductivity, while the addition of YBa₂Cu₃O_x reduced electrical resistance and enhanced dielectric permittivity. These findings demonstrate that YBa₂Cu₃O_x modification provides an effective route for tuning the thermophysical and electrophysical properties of LaCaCuVMnO_7.5-based oxide systems, suggesting their potential as promising candidates for multifunctional oxide materials with possible electronic and sensor-related applications. Full article

The Tieshilong Pb-Zn polymetallic district is located along the northern margin of the Dongpo ore field in the middle section of the Nanling metallogenic belt, southern Hunan, China. It represents a typical granite-related, fault-controlled hydrothermal vein-type lead–zinc polymetallic deposit in southern Hunan. In recent years, large-scale tin mineralization has been newly discovered during exploration in the deeper and peripheral areas of the district. However, the timing and genetic nature of this tin mineralization remain undetermined, which limits understanding of the characteristics of the deposit’s metallogenic system and its deep exploration potential. In this study, we present in situ cassiterite U–Pb geochronology and trace element data from deep Pb-Zn-Sn orebodies in the Tieshilong mining district. LA-ICP-MS U-Pb analyses of cassiterite yield a Tera–Wasserburg lower-intercept age of 159.2 ± 6.2 Ma (MSWD = 1.4), indicating that Sn mineralization occurred during the Late Jurassic. This age overlaps, within uncertainty, with the main ca. 160~150 Ma W–Sn metallogenic event recognized throughout the Nanling belt. Trace element data reveal that Tieshilong cassiterite is enriched in Fe (1100–5800 ppm) and W (120–11,660 ppm), and depleted in Nb (0.1–87 ppm) and Ta (0–7.1 ppm). The Zr/Hf ratios range from 23 to 52, with a mean value of approximately ~36, which is close to the chondritic values. These geochemical signatures, together with the occurrence of cassiterite intergrown with hydrothermal quartz and its replacement by later sulfides, support precipitation from a granite-related magmatic–hydrothermal system. Based on the findings and the literature, the Tieshilong deposit is therefore interpreted as a Pb–Zn-dominant expression of a Late Jurassic granite-related polymetallic system, in which deeper Sn ± W mineralization was overprinted by later Pb–Zn–Cu sulfide mineralization along fault-controlled fluid pathways. The recognition of cassiterite-bearing, medium- to high-temperature assemblages at depth suggests that down-dip extensions, fault intersections, and strike-inflection zones of the ore-controlling structures represent priority targets for future exploration. Full article

Cyclic adenosine monophosphate (cAMP) is a ubiquitous second messenger downstream of G protein-coupled receptors (GPCRs) and a central regulator of cellular signaling. Genetically encoded exchange proteins directly activated by cAMP (Epac)-based Förster resonance energy transfer (FRET) biosensors enable real-time monitoring of cAMP dynamics in living cells, but commonly used cyan/yellow FRET pairs require short-wavelength excitation, limiting compatibility with multiplex imaging and blue-light optogenetic tools such as bacterial photoactivated adenylyl cyclases (bPACs). Here, we engineered and systematically characterized four red-shifted Epac-based single-chain FRET cAMP sensors combining yellow or orange FRET donors with red fluorescent FRET acceptors. Using ratiometric live-cell imaging, we quantified stimulus-evoked FRET responses and identified Epac_red4 as the best-performing variant, showing an approximately 55% decrease in normalized FRET after forskolin stimulation. Epac_red4 also reliably detected G_i/o-mediated decreases in cAMP following μ-opioid receptor activation. Brief 405 nm light pulses induced graded and reversible cAMP elevations using the low dark-activity variant bPAC-F198Y. Furthermore, Epac_red4 enabled analysis of cAMP recovery kinetics during phosphodiesterase inhibition and multiplex imaging of cAMP and intracellular Ca²⁺ using Fura-2 with minimal spectral and pH-related interference under physiological imaging conditions. Together, Epac_red4 represents a robust red-shifted cAMP sensor for optogenetic and multiplex signaling studies. Full article

This study extends the Absement Method to leaky-aquifer pumping-test analysis by time integrating the Hantush–Jacob governing equation and deriving four complementary operators. Time integrating the Hantush–Jacob equation yields S·s = T∇²A − C·A, with storativity S, drawdown s, transmissivity T, the time (t)-integrated drawdown A(t) (absement), and leakance C. The four operators, A(t), time-averaged A(t)/t, windowed ΔA/Δt, and the normalized absement derivative (NAD), are applied jointly across all available observation wells. In a homogeneous aquifer, the fitted operators and NAD diagnostic provide mutually consistent parameter and flow-regime signatures. In a heterogeneous aquifer, systematic differences between operators become part of the interpretation: T-related variation appears as changes in the ΔA/Δt sliding profile across wells, whereas the leakage factor B = √(T/C)-related variation is identified by divergent A(t)/t asymptotes and NAD type-curve crossing. Monte Carlo assessment under composite noise (N = 50) confirms near-zero parameter bias, with T and S standard deviations approximately 3–4 times smaller for A(t)/t and ΔA/Δt than for A(t). The three field cases are identified: a 14% outward T decline with spatially uniform B (sandstone aquifer); approximately homogeneous T with outward-declining B flagged by NAD type-curve crossing before fitting (sandy aquifer); and T–B coupling resolution through the windowed ΔA/Δt profile (medium-grained sandstone aquifer). The outputs supported sustainable-yield assessment directly from routine pumping-test records. Full article

Landslides are among the most common and destructive geological hazards and pose a significant threat to the long-term stability of infrastructure systems. In particular, long-distance power transmission corridors often traverse mountainous and forested regions, where landslides can endanger tower foundations and transmission line safety. Such landslides predominantly occur in sloped forested areas, where dense vegetation causes severe occlusion that blurs landslide boundaries and creates strong visual similarity with surrounding land covers. Consequently, accurate and efficient landslide identification from remote sensing imagery remains a significant challenge. To address these challenges, we propose a structural constrained contrastive learning network (SC-Net) for reliable landslide extraction from remote sensing images. First, a multi-structural feature extraction module is designed to capture landslide-specific geometric characteristics. These features are further enhanced by fusing multi-scale semantic representations extracted from a pretrained backbone network through an attention-based adaptive feature fusion module. Additionally, a mask-constrained object-level contrastive learning strategy is introduced to enforce global structural consistency at the landslide object-level, thereby improving the discriminability between landslide and non-landslide regions. Extensive experiments conducted on the publicly available CAS landslide dataset demonstrate the effectiveness of the proposed method. The proposed SC-Net achieves IoU scores of 89.89% and 79.76% on the CAS-UAV and CAS-SAT datasets, respectively, outperforming the best-performing baseline by 2.09% and 0.46%. The proposed method provides an effective solution for large-scale landslide monitoring and demonstrates potential for applications in power transmission corridor inspection and infrastructure safety assessment. Full article