Search Results (546)

Autoimmune diseases result from dysregulated immune responses that mistakenly attack the body’s own tissues, causing chronic inflammation and progressive damage. Macrophages, with their remarkable plasticity, play key roles in both promoting and resolving inflammation, with pro-inflammatory M1 and anti-inflammatory M2 states shaping disease outcomes. Macrophage-derived exosomes have emerged as important mediators of intercellular communication, reflecting the functional state of their parent cells while influencing recipient cell behavior. Exosomes from M1 macrophages amplify inflammation through cytokines and microRNAs, whereas M2-derived exosomes support tissue repair and immune regulation. Studies in rheumatoid arthritis, lupus, multiple sclerosis, inflammatory bowel disease, type 1 diabetes, and psoriasis highlight their dual roles in pathology and resolution. In addition, macrophage exosomes can be engineered to deliver targeted therapeutic molecules, offering cell-free interventions with advantages in specificity, biocompatibility, and immunomodulation. This review summarizes current insights into macrophage-derived exosomes, their role in autoimmune pathogenesis, and emerging strategies to harness their therapeutic potential, highlighting their promise as precision-guided treatments for autoimmune diseases. Full article

Explosions, including those from war weapons, terrorist attacks, etc., can lead to damage and overall collapse of bridges. However, there are no clear guidelines for anti-blast design and protective measures for bridges under blast loading in current bridge design specifications. With advancements in intelligent construction, precast segmental bridge piers have become a major trend in social development. There is a lack of full understanding of the anti-blast performance of precast segmental bridge piers. To study the engineering calculation method for blast load acting on a typical precast segmental reinforced concrete (RC) pier in near-field explosions, an air explosion test of the precast segmental RC pier is firstly carried out, then a fluid–structure coupling numerical model of the precast segmental RC pier is established and the interaction between the explosion shock wave and the precast segmental RC pier is discussed. A numerical simulation of the precast segmental RC pier in a near-field explosion is conducted based on a reliable numerical model, and the distribution of the blast load acting on the precast segmental RC pier in the near-field explosion is analyzed. The results show that the reflected overpressure on the pier and the incident overpressure in the free field are reliable. The simulation results are basically consistent with the experimental results (with a relative error of less than 8%), and the fluid–structure coupling model is reasonable and reliable. The explosion shock wave has effects of reflection and circulation on the precast segmental RC pier. In the near-field explosion, the back and side blast loads acting on the precast segmental RC bridge pier can be ignored in the blast-resistant design. The front blast loads can be simplified and equalized, and a blast-resistant design load coefficient (1, 0.2, 0.03, 0.02, and 0.01) and a calculation formula of maximum equivalent overpressure peak value (applicable scaled distance [0.175 m/kg^1/3, 0.378 m/kg^1/3]) are proposed, which can be used as a reference for the blast-resistant design of precast segmental RC piers. Full article

Training users to correctly identify potential security threats like social engineering attacks such as phishing emails is a crucial aspect of cybersecurity. One challenge in this training is providing useful educational feedback to maximize student learning outcomes. Large Language Models (LLMs) have recently been applied to wider and wider applications, including domain-specific education and training. These applications of LLMs have many benefits, such as cost and ease of access, but there are important potential biases and constraints within LLMs. These may make LLMs worse teachers for important and vulnerable subpopulations including the elderly and those with less technical knowledge. In this work we present a dataset of LLM embeddings of conversations between human students and LLM teachers in an anti-phishing setting. We apply these embeddings onto an analysis of human–LLM educational conversations to develop specific and actionable targets for LLM training, fine-tuning, and evaluation that can potentially improve the educational quality of LLM teachers and ameliorate potential biases that may disproportionally impact specific subpopulations. Specifically, we suggest that LLM teaching platforms either speak generally or mention specific quotations of emails depending on user demographics and behaviors, and to steer conversations away from an over focus on the current example. Full article

The low-pressure edge of a pump-turbine runner blade is more prone to cavitation than other parts. The installation angle of the blade’s low-pressure edge is one of the key parameters affecting the cavitation performance of the pump-turbine. Based on the installation angle of the blade’s low-pressure edge obtained by the principle of normal outflow of the turbine runner, two other installation angles of the low-pressure edge are constructed by increasing the installation angle of the low-pressure edge toward the band direction. Three types of blades are designed based on the parametric design program of the pump-turbine runner. The Zwart cavitation model is adopted to carry out full-channel steady numerical simulations for the three runners. The efficiencies and internal flow fields of the draft tube under turbine operating conditions are compared. The cavitation characteristics in pump mode, the distribution of the turbulent flow field, and the pressure distribution on the blade surface are analyzed. The influence laws of the installation angle of the blade’s low-pressure edge on pump-turbine performance is summarized. A design method for anti-cavitation of Francis pump-turbine runners has been explored. The results show that the LP1 blade can achieve normal outflow under the turbine’s rated operating condition, but due to the large inflow attack angle under pump operating conditions, the cavitation performance in pump mode is very poor. By increasing the installation angle of the blade’s low-pressure edge toward the band direction, the efficiencies and cavitation performances of the pump mode can be improved. The LP3 blade reduces the inflow attack angle while optimizing the pressure distribution on the blade’s suction surface, thereby reducing the superimposed effect of two phenomena under large-discharge pump operating conditions with low cavitation numbers: flow separations on the pressure surface caused by inflow impact, and flow separations on the suction surface of adjacent blades caused by cavitation. As a result, the cavitation performance of the LP3 blade is significantly better than that of the LP1 and LP2 blades. The proposed anti-cavitation design method is simple and effective and can be applied to the research and modification design of Francis pump-turbine runners. Full article

Face anti-spoofing is crucial for protecting biometric authentication systems. Presentation attacks using 3D masks and high-resolution printed images present detection challenges for existing methods. In this paper, we introduce a family of specialized CNN architectures, AttackNet, designed for robust face anti-spoofing with optimized residual connections and activation functions. The study includes the development of four architectures: baseline LivenessNet, AttackNetV1 with concatenation-based skip connections, AttackNetV2.1 with optimized activation functions, and AttackNetV2.2 with efficient addition-based residual learning. Our analysis demonstrates that element-wise addition in skip connections reduces parameters from 8.4 M to 4.2 M while maintaining performance. A comprehensive evaluation was conducted on four benchmark datasets: MSSpoof, 3DMAD, CSMAD, and Replay-Attack. Results show high accuracy (approaching 100%) on the 3DMAD, CSMAD, and Replay-Attack datasets. On the more challenging MSSpoof dataset, AttackNetV1 achieved 99.6% accuracy with an HTER of 0.004, outperforming the baseline LivenessNet (94.35% accuracy, 0.056 HTER). Comparative analysis with state-of-the-art methods confirms the superiority of the proposed approach. AttackNetV2.2 demonstrates an optimal balance between accuracy and computational efficiency, requiring 16.1 MB of memory compared to 32.1 MB for other AttackNet variants. Training time analysis shows twice the speed for AttackNetV2.2 compared to AttackNetV1. Architectural ablation studies highlight the crucial role of residual connections, batch normalization, and suitable dropout rates. Statistical significance testing verifies the reliability of the results (p-value < 0.001). The proposed architectures show excellent generalization ability and practical usefulness for real-world deployment in mobile and embedded systems. Full article

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is characterized by the predominance of optic neuritis, myelitis, acute disseminated encephalomyelitis (ADEM), and cortical encephalitis, and can be diagnosed by the presence of pathogenic immunoglobulin G (IgG) antibodies targeting the extracellular domain of MOG in the serum and cerebrospinal fluid (CSF). Initially considered a variant of multiple sclerosis (MS) or neuromyelitis optica spectrum disorder (NMOSD), it is now widely recognized as a separate entity, supported by converging evidence from serological, pathological, and clinical studies. Patients with MOGAD often exhibit better recovery from acute attacks; however, their clinical and pathological features vary based on the immunological role of MOG-IgG via antibody- or complement-mediated perivenous demyelinating pathology, in addition to MOG-specific cellular immunity, resulting in heterogeneous demyelinated lesions from vanishing benign forms to tissue necrosis, even though MOGAD is not a mild disease. The key is the immunological mechanism of devastating lesion coalescence and long-term degenerating mechanisms, which may still accrue, particularly in the relapsing, progressing, and aggressive clinical course of encephalomyelitis. The warning features of the severe clinical forms are: (1) fulminant acute multifocal lesions or multiphasic ADEM transitioning to diffuse (Schilder-type) or tumefactive lesions; (2) cortical or subcortical lesions related to brain atrophy and/or refractory epilepsy (Rasmussen-type); (3) longitudinally extended spinal cord lesions severely affected with residual symptoms. In addition, it is cautious for patients refractory to acute stage early 1st treatment including intravenous methylprednisolone treatment and apheresis with residual symptoms and relapse activity with immunoglobulin and other 2nd line treatments including B cell depletion therapy. Persistent MOG-IgG high titration, intrathecal production of MOG-IgG, and suggestive markers of higher disease activity, such as cerebrospinal fluid interleukin-6 and complement C5b-9, could be identified as promising markers of higher disease activity, worsening of disability, and poor prognosis, and used to identify signs of escalating treatment strategies. It is promising of currently ongoing investigational antibodies against anti-interleukin-6 receptor and the neonatal Fc receptor. Moreover, due to possible refractory issues such as the intrathecal production of autoantibody and the involvement of complement in the worsening of the lesion, further developments of other mechanisms of action such as chimeric antigen receptor T-cell (CAR-T) and anti-complement therapies are warranted in the future. Full article

Background. We are developing cytotoxic anti-HIV immunoconjugates to attack the reservoir of infected cells that persist after years of fully suppressive anti-retroviral therapy. Methods. We have produced a chimeric fusion protein, J3ExoA, consisting of J3VHH, a broadly reactive anti-gp120 camelid nanobody, joined to the de-immunized PE38 fragment of Pseudomonas exotoxin A. The efficacy of J3ExoA was compared to that of a well-studied anti-gp41 immunotoxin (IT), 7B2-dgA, in cytotoxicity assays and for inhibition of infectivity. Immunogenicity of the ITs was tested in mice. Results. J3ExoA killed cells expressing the HIV envelope with specificity in concentrations in the ng/mL range. Of all anti-HIV ITs we have tested, only J3ExoA compared to 7B2-dgA in cytotoxic efficacy, although there were differences between the two ITs on different target cells. J3ExoA suppressed the spread of HIV infection in tissue culture. J3ExoA was less immunogenic than 7B2-dgA, but mice made antibodies to both portions of the fusion protein. Conclusions. J3ExoA represents a novel IT that may be used to eliminate infected cells in the persistent HIV reservoir of infection, the barrier to an HIV “cure.” Additional approaches for addressing IT immunogenicity are discussed. Full article

Redox balance is essential for maintenance of the hematopoietic stem cell (HSC) pool, which ensures the lifelong hematopoiesis. However, oxidative attack induced by various physiopathological stresses always compromises HSC maintenance, while there remains lack of safe and effective antioxidative measures combating these conditions. Here, we show that ferulic acid (FA), a natural antioxidant abundantly present in Angelica sinensis which is a traditional Chinese herb commonly used for promotion of blood production, distinctively and directly promotes HSC maintenance and thereby boosts hematopoiesis at homeostasis, whether supplemented over the long term in vivo or in HSC culture ex vivo. Using a mouse model of acute myelosuppressive injury induced by ionizing radiation, we further reveal that FA supplementation effectively safeguards HSC maintenance and accelerates hematopoietic regeneration after acute myelosuppressive injury. Mechanistically, FA diminishes ferroptosis susceptibility of HSCs through limiting the labile iron pool (LIP), thus favoring HSC maintenance. In addition, the LIP limitation and anti-ferroptosis activity of FA is independent of nuclear-factor erythroid 2-related factor 2 (NRF2), probably relying on its iron-chelating ability. These findings not only uncover a novel pharmacological action and mechanism of FA in promoting HSC maintenance, but also provides a therapeutic rationale for using FA or FA-rich herbs to treat iron overload- and ferroptosis-associated pathologies such as acute myelosuppressive injury. Full article

Biometric authentication using human physiological and behavioral characteristics has been widely adopted, with speaker verification attracting attention due to its convenience and noncontact nature. Conventional speaker verification systems remain vulnerable to spoofing attacks, however, often requiring integration with separate spoofed speech detection models. In this work, the authors propose an emotion-dependent speaker verification system that integrates speaker characteristics with emotional speech characteristics, enhancing robustness against spoofed speech without relying on additional classification models. By comparing acoustic characteristics of emotions between registered and verification speech using pretrained models, the proposed method reduces the equal error rate compared to conventional speaker verification systems, achieving an average equal error rate of 1.13% for speaker verification and 17.7% for the anti-spoofing task. Researchers additionally conducted a user evaluation experiment to assess the usability of emotion-dependent speaker verification. The results indicate that although emotion-dependent authentication was initially cognitively stressful, participants adapted over time, and the burden was significantly reduced after three sessions. Among the tested emotions (anger, joy, sadness, and neutral), sadness proved most effective, with stable scores, a low error rate, and minimal user strain. These findings suggest that neutral speech is not always the optimal choice for speaker verification and that well-designed emotion-dependent authentication can offer a practical and robust security solution. Full article

Radar networks, composed of multiple radar stations and a fusion center interconnected via communication technologies, are widely used in civil aviation and maritime operations. Ensuring the security of radar networks is crucial. While their strong anti-jamming capabilities make traditional electronic countermeasures less effective, the openness and vulnerability of their network architecture expose them to cybersecurity risks. Current research on radar network security risk analysis from a cybersecurity perspective remains insufficient, necessitating further study to provide theoretical support for defense strategies. Taking centralized radar networks as an example, this paper first analyzes their architecture and potential cybersecurity risks, identifying a threat where attackers could potentially execute false data injection attacks (FDIAs) against the fusion center via man-in-the-middle attacks (MITMAs). A threat model is then established, outlining possible attack procedures and methods, along with defensive recommendations and evaluation metrics. Furthermore, for scenarios involving single-link control without traffic increase, the impact of different false data construction methods is examined. Simulation experiments validate the findings, showing that the average position offset increases from 8.38 m to 78.35 m after false data injection. This result confirms significant security risks under such threats, providing a reference for future countermeasure research. Full article

There is currently no effective therapeutic capable of arresting or inducing regression of primary or metastatic brain cancers. This article presents both pre-clinical and clinical studies supportive that a new bioengineered technology could induce regression and/or elimination of primary and metastatic brain cancers through three disease-modifying mechanisms. Transcranial Radiofrequency Wave Treatment (TRFT) is non-thermal, non-invasive and self-administered in-home to safely provide radiofrequency waves to the entire human brain. Since TRFT has already been shown to stop and reverse the cognitive decline of Alzheimer’s Disease in small studies, evidence is provided that three key mechanisms of TRFT action, alone or in synergy, could effectively treat brain cancers: (1) enhancement of brain meningeal lymph flow to increase immune trafficking between the brain cancer and cervical lymph nodes, resulting in a robust immune attack on the brain cancer; (2) rebalancing of the immune system’s cytokines within the brain or brain cancer environment to decrease inflammation therein and thus make for an inhospitable environment for brain cancer growth; (3) direct anti-proliferation/antigrowth affects within the brain tumor microenvironment. Importantly, these mechanisms of TRFT action could be effective against both visualized brain tumors and those that are yet too small to be identified through brain imaging. The existing animal and human clinical evidence presented in this perspective article justifies TRFT to be clinically tested immediately against both primary and metastatic brain cancers as monotherapy or possibly in combination with immune checkpoint inhibitors. Full article

Achieving reliable navigation is critical for GNSS receivers subject to spoofing attacks. Utilizing the inherent sparsity and inconsistency of spoofing signals, this paper proposes an anti-spoofing framework for GNSS receivers to detect, classify, and recover positions from spoofing attacks without additional devices. A sparse decomposition algorithm with non-negative constraints limited by signal power magnitudes is proposed to achieve accurate spoofing detections while extracting key features of the received signals. In the classification stage, these features continuously refine each channel of the receiver’s code tracking loop, ensuring that it tracks either the authentic or counterfeit signal components. Moreover, by leveraging the inherent inconsistency of spoofing properties, we incorporate the Hausdorff distance to determine the most overlapped position sets, distinguishing genuine trajectories and mitigating spoofing effects. Experiments on the TEXBAT dataset show that the proposed algorithm detects 98% of spoofing attacks, ensuring stable position recovery with an average RMSE of 6.32 m across various time periods. Full article

Digital images have been widely applied in fields such as mobile devices, the Internet of Things, and medical imaging. Although significant progress has been made in image encryption technology, it still faces many challenges, such as attackers using powerful computing resources and advanced algorithms to crack encryption systems. To address these challenges, this paper proposes a novel image encryption algorithm based on one-dimensional sawtooth wave chaotic system (1D-SAW) and the three-strand structure of DNA. Firstly, a new 1D-SAW chaotic system was designed. By introducing nonlinear terms and periodic disturbances, this system is capable of generating chaotic sequences with high randomness and initial value sensitivity. Secondly, a new diffusion rule based on the three-strand structure of DNA is proposed. Compared with the traditional DNA encoding and XOR operation, this rule further enhances the complexity and anti-attack ability of the encryption process. Finally, the security and randomness of the 1D-SAW and image encryption algorithms were verified through various tests. Results show that this method exhibits better performance in resisting statistical attacks and differential attacks. Full article

Federated learning promotes the development of cross-domain intelligent applications under the premise of protecting data privacy, but there are still problems of sensitive parameter information leakage of multi-party data temporal alignment and resource scheduling process, and traditional symmetric encryption schemes suffer from low efficiency and poor security. To this end, in this paper, based on the modified NTRU-type multi-key fully homomorphic encryption scheme, an asymmetric algorithm, a secure computation scheme of multi-party least common multiple and greatest common divisor without full set under the semi-honest model is proposed. Participants strictly follow the established process. Nevertheless, considering that malicious participants may engage in poisoning attacks such as tampering with or uploading incorrect data to disrupt the protocol process and cause incorrect results, a scheme against malicious spoofing is further proposed, which resists malicious spoofing behaviors and not all malicious attacks, to verify the correctness of input parameters or data through hash functions and zero-knowledge proof, ensuring it can run safely and stably. Experimental results show that our semi-honest model scheme improves the efficiency by 39.5% and 45.6% compared to similar schemes under different parameter conditions, and it is able to efficiently process small and medium-sized data in real time under high bandwidth; although there is an average time increase of 1.39 s, the anti-malicious spoofing scheme takes into account both security and efficiency, achieving the design expectations. Full article

Icing on transmission lines in cold regions can cause asymmetry in the conductor cross-section. This asymmetry can lead to low-frequency, large-amplitude oscillations, posing a serious threat to the stability and safety of power transmission systems. In this study, the aerodynamic characteristics of crescent-shaped and sector-shaped iced eight-bundled conductors were systematically investigated over an angle of attack range from 0° to 180°. A combined approach involving wind tunnel tests and high-precision computational fluid dynamics (CFD) simulations was adopted. In the wind tunnel tests, static aerodynamic coefficients and dynamic time series data were obtained using a high-precision aerodynamic balance and a turbulence grid. In the CFD simulations, transient flow structures and vortex shedding mechanisms were analyzed based on the Reynolds-averaged Navier–Stokes (RANS) equations with the SST k-ω turbulence model. A comprehensive comparison between the two ice accretion geometries was conducted. The results revealed distinct aerodynamic instability mechanisms and frequency-domain characteristics. The analysis was supported by Fourier’s fourth-order harmonic decomposition and energy spectrum analysis. It was found that crescent-shaped ice, due to its streamlined leading edge, induced a dominant single vortex shedding. In this case, the first-order harmonic accounted for 67.7% of the total energy. In contrast, the prismatic shape of sector-shaped ice caused migration of the separation point and introduced broadband energy input. Stability thresholds were determined using the Den Hartog criterion. Sector-shaped iced conductors exhibited significant negative aerodynamic damping under ten distinct operating conditions. Compared to the crescent-shaped case, the instability risk range increased by 60%. The strong agreement between simulation and experimental results validated the reliability of the numerical approach. This study establishes a multiscale analytical framework for understanding galloping mechanisms of iced conductors. It also identifies early warning indicators in the frequency domain and provides essential guidance for the design of more effective anti-galloping control strategies in resilient power transmission systems. Full article