Search Results (7,005)

Factor XII (FXII) is a central mediator at the intersection of coagulation, fibrinolysis, inflammation, and immunity. It is activated upon contact with negatively charged surfaces, triggering the intrinsic coagulation pathway and driving thrombus formation and stabilization. Beyond clotting, FXII contributes to activation of the kallikrein–kinin system, generation of bradykinin, and modulation of inflammatory and immune responses. Congenital FXII deficiency does not increase bleeding risk, highlighting its unique role and making FXII inhibition an attractive strategy for anticoagulation and immune modulation with a potentially superior safety profile. Preclinical studies provide compelling evidence for this concept. In models of ischemic stroke and traumatic brain injury, FXII blockade significantly reduced infarct volume, improved neurological outcomes, and attenuated neuroinflammation without increasing hemorrhage. Similarly, in extracorporeal circulation and vascular stent implantation, FXII inhibition prevented thrombus formation and reduced fibrin deposition, achieving effects comparable to heparin but with markedly lower bleeding risk. Several classes of FXII inhibitors are currently in development, including antisense oligonucleotides, peptides, recombinant proteins, and monoclonal antibodies. Among them, Ixodes ricinus contact phase inhibitor (Ir-CPI) and recombinant human albumin-fused Infestin-4 (rHA-Infestin-4) have demonstrated strong antithrombotic efficacy in animal models. Most notably, garadacimab, a monoclonal anti-FXIIa antibody, has completed phase 3 trials and received regulatory approval for hereditary angioedema (HAE) prophylaxis, where it markedly reduces attack frequency with a favorable safety profile. This review summarizes current knowledge on FXII biology and evaluates its translational potential as a novel target for anticoagulant and anti-inflammatory therapies. Full article

The snow module of the HYDROTEL (version 2.8.x-078-00-4.1.15.5551) hydrological model was modified to incorporate a multilayer structure composed of ice and air layers within the snowpack, as well as to account for the impact of freezing rain on snow cover. This study examines whether this enhanced physical representation of snow processes improves the accuracy of streamflow simulations. The analysis was conducted across ten watersheds in Quebec, Canada. The multilayer snow model consistently improved low-flow simulations during both calibration and validation periods and enhanced the representation of the falling limb during the calibration period. However, the monolayer snow model performs slightly better during the rising limb of the freshet season for the calibration phase. In addition, the multilayer configuration reduced the bias of the cumulative freshet volumes and annual maximum freshet discharge. Overall, the multilayer snow model achieved comparable performance to the monolayer model for high-flow simulations while outperforming it for low-flow conditions, leading to a more accurate representation of freshet volumes and falling limb dynamics. Full article

A bidirectional infrared absorber leveraging the Fabry–Perot resonance within a cascaded metal-dielectric nano-film structure is proposed. The absorber integrates a top Ag–VO₂–SiO₂ film stack, an intermediate thin Ag metal layer, and a bottom Al₂O₃–Ti–Al₂O₃ layer, enabling switchable narrowband and broadband absorption under forward and backward illumination, respectively. Under front illumination, the structure exhibits a high narrowband absorption peak of 98% at a wavelength of 1110 nm when VO₂ is in its metallic state. In contrast, when VO₂ transitions to its insulating state, the absorption peak shifts to 1165 nm. Additionally, under back illumination, ultra-broadband absorption is achieved, covering a wavelength range of 1000–2760 nm with an average absorption of 98%. The proposed absorber demonstrates excellent absorption performance with structural simplicity and low manufacturing cost, offering great potential for applications in solar photovoltaic devices, photodetectors, and related fields. Full article

Baroclinic instability is a fundamental mechanism of midlatitude atmospheric variability, and the Eady model remains one of its most useful idealized representations. In this work, we revisit the Eady configuration from the viewpoint of solution-space geometry rather than the classical normal-mode/growth-rate analysis. Starting from the reduced Eady vertical-structure equation, we show that the ratio of two independent solutions satisfies a Schwarzian-type relation that is invariant under homographic transformations, which naturally leads to an SL(2R) projective symmetry of the solution family. On this basis, we introduce a complex amplitude representation and reformulate coherence in terms of phase–amplitude synchronization constrained by projective invariants. Using Riccati-type constructions along geodesic parametrizations, the reduced dynamics are connected to a Stoler-type transform. Numerical exploration of the reduced model shows a systematic dependence on the control parameter $\omega$: small $\omega$ is associated with simple oscillatory or burst-like behavior, intermediate $\omega$ with period-doubling-like behavior, and large $\omega$ with strongly modulated dynamics and more intricate reconstructed attractors. These results should be interpreted as properties of the reduced symmetry-based model, and they suggest that projective invariants may provide a useful framework for classifying organization regimes in Eady-type disturbances, complementary to classical growth-rate analyses. Full article

Coherent diffraction imaging (CDI) is a fast-growing imaging technique. Among all CDI methods, coherent modulation imaging (CMI) has strong potential for dynamic imaging because of its ability to form an image from a single diffraction pattern. However, current CMI methods mostly reconstruct the exit wave distribution behind the object plane, which is seriously affected by the illumination artifact. Recently, some improved CMI methods have been developed to resolve the problem. However, many of these methods still need two diffraction patterns—one empty-sample diffraction pattern and another snapshot measurement. Recent advances in randomized probe imaging have shown that a single diffraction pattern suffices for quantitative reconstruction when the probe is pre-calibrated. Herein, we propose a modified CMI algorithm to reconstruct pure object function with single diffraction pattern, thereby simplifying the experimental process. Moreover, the proposed method can also work in the situation where the modulation effect is weak. Both numerical simulations and optical experiments have been conducted to verify the proposed method. Full article

Jamming pattern identification is a crucial prerequisite for countering jamming. Combined jamming exhibits complex structures and diverse forms, making it difficult for traditional identification methods to extract suitable and stable features for effective discrimination. To address this challenge, this paper proposes a combined jamming identification method based on joint modulation of linear frequency modulation, phase coding and phase coding frequency modulation (LFM-PC-PCFM) waveforms. Building upon the time–frequency entropy features of combined interference, this method enhances the separability of jamming features in the radar-transmitted waveform dimension. The experiment employed the SVM classification algorithm based on particle swarm optimization for validation. Experiments demonstrate that the combined jamming recognition method under LFM-PC-PCFM waveform modulation achieves higher and more stable recognition accuracy than traditional LFM single-waveform modulation under jamming-to-noise ratios ranging from −10 dB to 30 dB. Full article

Dissolved oxygen (DO) is a primary environmental regulator of shrimp physiology and behavior in intensive aquaculture systems. Whether shrimp acoustic emissions quantitatively reflect oxygen-driven behavioral modulation under operational pond conditions, however, remains uncertain due to the difficulty of isolating biologically relevant signals from complex soundscapes. In this study, passive acoustic monitoring was conducted in commercial outdoor ponds culturing Litopenaeus vannamei. A periodic-coding non-negative matrix factorization approach was applied to separate putative shrimp-associated acoustic components from broadband background noise and to obtain stable time–frequency representations of acoustic activity. Temporal variations in the extracted acoustic intensity were compared with simultaneously measured DO concentrations. Rather than relying on global correlation, phase-specific analyses revealed that the putative shrimp-associated acoustic component exhibited consistent positive associations with DO dynamics during both rising and declining phases, whereas background noise showed only weak and non-coherent relationships with DO. These results indicate that the observed acoustic–oxygen relationship is non-stationary and context-dependent. Given the observational nature of the study and potential confounding influences (e.g., aeration and other environmental factors), these findings, which are based on observations from a single pond over a limited recording period (62.85 h) under specific operational conditions, should be interpreted with caution and regarded as a proof-of-concept rather than evidence of general applicability. Nevertheless, the results are consistent with the hypothesis that population-level acoustic activity may reflect environmentally modulated behavioral responses. This highlights the potential of soundscape-based approaches as non-invasive tools for supporting aquaculture monitoring, while emphasizing the need for further validation under controlled and multi-site conditions. Full article

Recent research demonstrates that guilt, as a self-conscious moral emotion, can shape early visual perception. However, the underlying neural mechanisms remain unclear. Using a pre–post experimental design combined with electroencephalography (EEG), we investigated how guilt modulates visual size perception and its neurophysiological correlates. Across four experiments, we confirmed that guilt emotion consistently increased the size overestimation component of the Ebbinghaus illusion. Time–frequency analyses revealed that guilt processing involved decreased prefrontal theta (4 to 7 Hz) power and reduced phase coupling of prefrontal theta and temporo-parieto-occipital alpha (8 to 12 Hz) oscillations. The guilt-related modulation of visual size perception was specifically associated with occipital alpha phase coherence. These results demonstrate that guilt emotion shapes fundamental visual processing through coordinated neural oscillations across large-scale brain networks. The findings advance understanding of emotion–cognition interactions and have implications for guilt-related psychiatric disorders. Full article

Interannual variability of sea level anomalies (SLA) in the South China Sea (SCS) is significantly influenced by large-scale climate modes; however, their temporal evolution and interdecadal modulation mechanisms remain insufficiently understood. Based on observational records and ERA5 reanalysis data spanning 1980–2022, this study employs a Bayesian Dynamic Linear Model (DLM) to quantify the time-varying impacts of El Niño-Southern Oscillation (ENSO) on interannual SLA variability across different subregions of the SCS and further investigates the modulation effect of the Pacific Decadal Oscillation (PDO) background state. The results indicate that ENSO is a key climatic driver of interannual SLA variability in the SCS; nevertheless, its influence exhibits pronounced non-stationarity, with dynamic regression coefficients showing clear phase-dependent fluctuations throughout the study period. The northern and eastern subregions display stronger responses to ENSO forcing, whereas the southern and western subregions exhibit relatively weaker signals. The negative phase of the PDO enhances the ENSO-SLA relationship, while the positive phase weakens it, with sign reversals occurring in certain subregions. Correlation analyses further suggest that ENSO influences SLA primarily through wind stress anomalies induced by sea level pressure (SLP) gradients, which regulate Ekman transport, whereas the PDO exerts an indirect effect mainly by modifying the large-scale background circulation structure. Full article

Improving nitrogen (N) use efficiency in olive cultivation is essential to address the environmental burden of N fertilizers, whose recovery efficiency rarely exceeds 55%. This study evaluates the agronomic and environmental performance of chabazite-rich zeolite as a soil amendment to enable 50% N-fertilizer reduction in olive growing. A seven-year field experiment (2017–2023) was conducted at two sites in Emilia-Romagna (Italy)—one irrigated (Brisighella) and one rainfed (Bertinoro)—comparing four autochthonous varieties under zeolite amendment (ZEO, 50% N) versus conventional fertilization (CNT, 100% N). Vegetative growth, productive parameters, oil quality and environmental impacts (Life Cycle Assessment, ISO 14040/44) were monitored. Under irrigation, ZEO maintained vegetative and productive equivalence with CNT, sustaining commercially viable yields (0.5–2.3 t ha⁻¹). Under rainfed conditions, variety-specific responses emerged: Colombina exhibited 126.2% greater trunk diameter and near-universal fruiting competence (88.9% vs. 29–35% productive plants) under ZEO, while Capolga showed treatment convergence. LCA revealed higher per-unit environmental impacts for ZEO during early orchard phases due to front-loaded extraction burdens, progressively offset by annual N-input reductions. These findings demonstrate that zeolite amendment enables agronomically viable 50% N-fertilizer reduction, with efficacy modulated by water regime and genotype. Full article

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has driven the global COVID-19 pandemic, imposing a tremendous burden on public health. As the virus continually evolves through rapid mutations, the pandemic has transitioned into a prolonged endemic phase. Despite the development of novel drugs and vaccines, clinical outcomes remain suboptimal for vulnerable populations, including the elderly and those with comorbidities or compromised immunity. Tea polyphenols, a class of structurally diverse and bioactive nutraceuticals, may modulate viral entry, replication, and host inflammatory pathways implicated in disease progression through pleiotropic effects on viral attachment, membrane fusion, intracellular replication, and proteolytic processing. Here, we provide an updated chemo-biological perspective on the antiviral and immunomodulatory mechanisms of tea polyphenols against SARS-CoV-2. Current evidence highlights their potential to serve as promising candidates for further mechanistic and translational investigation as adjunctive strategies and nutraceuticals for COVID-19 management. Importantly, no large-scale randomized controlled trials have yet demonstrated clinical benefit of tea polyphenols in COVID-19. Full article

Experimental results suggest a feasible strategy for tuning the superconducting properties of MgB₂ through the incorporation of an electroluminescent inhomogeneous phase. By introducing GaP electroluminescent inhomogeneous phases into MgB₂, the effects of emission intensity variation on the sample structure, superconducting transition temperature, electrical transport behavior, and magnetic properties were systematically investigated. The results show that, at a fixed GaP addition level, the superconducting transition temperature T_c increases steadily from 38.2 K to 39.6 K with increasing emission intensity of the inhomogeneous phase, corresponding to a maximum enhancement of approximately 1.4 K. Meanwhile, the zero-resistance temperature shifts upward synchronously, indicating that the entire superconducting transition region moves toward higher temperatures. Raman measurements show that the peak position and linewidth of the E_2g phonon mode evolve systematically with emission intensity, while the electron–phonon coupling parameter λ exhibits a trend consistent with that of T_c. In addition, the nanoscale dispersed distribution of the GaP inhomogeneous phase, together with the interface/defect structures it introduces, appears to promote sample densification and enhance flux pinning, resulting in an increase in the critical current density J_c by approximately 69% at 20 K in self-field and an enhancement of the irreversibility field H_irr by about 31.5%. These results suggest that, beyond the effect of static inhomogeneous-phase incorporation, the luminescence-activated state under bias excitation is likely involved in modulating the superconducting response of MgB₂. This work provides a new experimental perspective for synergistically regulating the properties of conventional superconductors through the combined effects of inhomogeneous phases and excited states. Full article

Effective wildfire management demands seamless integration of real-time detection and long-term spread forecasting. This paper proposes a novel power-efficient UAV–satellite hybrid pipeline that synergizes the agility of UAVs with the scale of satellite intelligence. The system begins with a dashboard-guided, multi-UAV detection module that scores fire likelihood from historical satellite data and enables scalable, energy-efficient deployment with low-latency onboard processing. This aerial component ensures persistent surveillance and reliable ignition detection, supported by a Dual LoRa (Long Range) communication scheme for robust and low-power connectivity. It achieves an F1-score of 97.4% while minimizing power consumption to extend operational flight times. Following detection, the pipeline transitions to a dynamic perimeter-prediction phase utilizing a custom Canadian boreal dataset. We employ a Squeeze-and-Excitation Residual U-Net (SE-ResUNet) to model spatiotemporal fire propagation based on static terrain and dynamic environmental features. The model was validated using a dynamic simulation framework that evaluates temporal consistency and convergence behavior against final cumulative burned-area masks, effectively addressing the absence of daily ground truth. Under these conditions, the model achieves a recall of 84% and an AUC of 0.97, demonstrating a strong capability to delineate active fire fronts. By coupling dashboard-driven UAV sensing with satellite-based predictive modeling, this work establishes a modular, foundational framework to support data-scarce forecasting in modern wildfire management. Full article

The anticancer ruthenium complex indazolium trans-[tetrachlorobis(1H-indazole) ruthenate (III)—also known as KP1019—inhibits cancer cell proliferation in vitro, causes tumor regression in animal models, and showed no dose-limiting toxicity in a phase I clinical trial. Previous studies found that KP1019 damages DNA in both cancer cells and the budding yeast Saccharomyces cerevisiae. To identify other potential targets of KP1019 along with pathways that modulate the drug’s cellular effects, we screened the yeast gene deletion strain library by quantitative high-throughput cell array phenotyping (Q-HTCP). Fitness differences, as judged by growth curve analysis, identified genes for which loss of function (gene deletion) interacts with (enhances or suppresses) KP1019 effects. Drug-enhancing deletions were enriched for DNA repair functions, consistent with DNA damage being a primary target of KP1019 in yeast. pH homeostasis also modified the effects of KP1019. Drug-suppressing deletions prominently involved ribosomal proteins. A mechanistic link between ribosomal protein function and KP1019 toxicity was supported by dose-dependent accumulation of Rpl7a-GFP in the nucleolus, which is a hallmark of ribosomal biogenesis stress. Furthermore, KP1019 acted synergistically with the TOR pathway inhibitor everolimus to inhibit cell proliferation. The resulting model, wherein KP1019 perturbs ribosome assembly, can inform the design of future combination therapies. Full article

Salient Object Detection (SOD) in Optical Remote Sensing Images (ORSIs) aims to localize and segment visually prominent objects amidst complex backgrounds and extreme scale variations. However, we observe that current frequency-aware methods typically rely on a naive feature aggregation paradigm, merging frequency and spatial features via simple concatenation, addition, or direct combination. This shallow interaction overlooks the inherent semantic misalignment between the two domains, resulting in feature redundancy and poor boundary delineation. To address this limitation, we propose the Cooperative Hybrid Domain Network (CHDNet), a framework designed to facilitate synergistic cooperation between heterogeneous domains. Specifically, we propose the Cross-Domain Multi-Head Self-Attention (CD-MHSA) mechanism as a semantic bridge following the encoder. It employs a dimension expansion strategy to construct a Unified Interaction Manifold and utilizes a Frequency Anchor Interaction mechanism to achieve precise modulation of spatial textures using global spectral cues. Furthermore, to address the dual challenges of lacking explicit interpretation mechanisms for semantic co-occurrence and the susceptibility of topological structures to fracture in complex scenes during the decoding phase, we design a Multi-Branch Cooperative Decoder (MBCD) comprising three parallel paths: edge semantics, global relations, and reverse correction. This module dynamically integrates these heterogeneous clues through a Cooperative Fusion Strategy, combining explicit global dependency modeling with dual-domain reverse mining. Extensive experiments on multiple benchmark datasets demonstrate that the proposed CHDNet achieves performance superior to state-of-the-art (SOTA) methods. Full article