Search Results (10,108)

Toxoplasmosis remains one of the most common parasitic infections affecting humans, with significant implications for pregnancy and fetal health. Maternal primary infection during gestation can result in transplacental transmission of Toxoplasma gondii, leading to a wide spectrum of congenital disease. The risk of vertical transmission increases with gestational age, whereas disease severity is inversely related—early infections causing severe neurological and ocular damage, and late infections often resulting in subclinical forms. Advances in serological testing, including IgG avidity assays and molecular diagnostics such as PCR on amniotic fluid, have improved early detection and management. Prenatal treatment with spiramycin or pyrimethamine–sulfadiazine–folinic acid combinations has been associated with reduced transmission and less severe fetal disease in several studies, although the magnitude of benefit remains debated. Long-term follow-up is essential, as late-onset manifestations, particularly chorioretinitis and neurodevelopmental impairment, are common. This narrative review was based on a comprehensive literature search of major medical databases and summarizes current knowledge on the epidemiology, pathophysiology, diagnosis, treatment, and outcomes of toxoplasmosis in pregnancy. Particular emphasis is placed on high-prevalence countries, where greater parasite genetic diversity, distinct epidemiological patterns, and a higher burden of congenital disease pose unique clinical and public health challenges. Despite progress in understanding parasite biology, pathogenesis, and treatment efficacy, congenital toxoplasmosis continues to be underdiagnosed and underreported, especially in low-resource settings. Ongoing challenges include optimizing screening strategies, ensuring access to standardized therapies, and strengthening surveillance systems. Full article

As global populations grow and technology advances, daily life is increasingly shaped by digital systems such as computers and smart devices. However, prolonged device use has contributed to increasing physical and mental health concerns, particularly those associated with poor sitting posture. Posture-related strain is frequently overlooked and contributes to musculoskeletal discomfort, including back, neck, shoulder, and wrist pain, and may also be associated with sleep disturbances and elevated stress levels. To the best of our knowledge and based on the existing literature, this is the first study to introduce a machine learning-based framework for advanced muscle strain severity classification using Internet of Things (IoT) devices that integrates posture monitoring and muscle strain detection into a unified low-cost framework ($23 hardware cost). The primary objective of this work is accurate classification of muscle strain severity, while real-time alerts serve as a secondary ergonomic feedback mechanism. Specifically, this study makes four major contributions. First, we created a novel dataset through real-time acquisition of electromyography (EMG) and posture signals from participants in hospital and industrial environments, capturing diverse muscle strain patterns validated against clinical assessment procedures. Second, we designed a two-part hardware architecture consisting of posture detection (PD) and strain detection (SD) modules using a NodeMCU ESP8266, HC-SR04 ultrasonic sensor, EMG sensor, and buzzer for real-time physiological monitoring, incorporating EMG-specific preprocessing including band-pass filtering, rectification, and RMS smoothing. Third, we proposed and evaluated a hybrid machine learning framework integrating Vision Transformer (ViT) and XGBoost to classify strain severity into three study-specific categories: baseline (EMG RMS < 40 µV), compensatory strain (40–59 µV), and overload (≥60 µV). These categories were used as reproducible severity proxies for machine learning annotation and should not be interpreted as universal biomarkers of structural tissue damage. Finally, the proposed framework achieved a classification accuracy of 99.0% (95% CI: 98.5–99.5%) with an inference latency of 15.2 ms. Full article

Cybersecurity insider threats remain a significant challenge for modern organisations due to their potential to cause substantial financial and reputational damage. This paper presents a systematic review of insider-threat research (2019–2026) using the PRISMA methodology and introduces an empirically validated ensemble framework for insider-threat detection. The proposed approach combines User-Based Sequences (UBS), a self-supervised Transformer trained on next-token prediction and time-gap modelling, and an unsupervised anomaly detection ensemble operating on model-derived behavioural features. An answers directory is incorporated to provide grounded truth for insider entities and episodes within the CERT r6.2 dataset, enabling direct validation of detection outcomes. The framework integrates behavioural theory with machine-learning techniques to improve understanding of insider-threat precursors. Evaluation was performed using a seven-stage Isolation Forest ensemble incorporating multimodal behavioural and technical data streams. The approach successfully identified all insider users, achieving 100% recall and an AUROC of 0.93. Comparative analysis against a previously reported model showed comparable AUROC and perfect recall despite differences in evaluation methodology. While precision remained low (0.004) due to the extreme class imbalance in the full CERT r6.2 population (5 insiders among 4000 users), the results highlight the operational challenges of insider-threat detection in realistic enterprise environments. This research contributes a novel, reproducible framework that combines behavioural theory and advanced machine learning to support the detection and analysis of insider threats. Full article

Background and Clinical Significance: Hyaluronic acid fillers are currently the most widely used materials in aesthetic medicine and represent one of the most frequently performed minimally invasive procedures worldwide. Vascular occlusion is the most severe complication associated with this type if filler injections due to the risk of tissue necrosis and permanent sequelae. Early recognition and precise identification of the affected vascular territory are essential to prevent irreversible damage. Case Presentation: his report describes a case of infraorbital artery occlusion with retrograde extension to the anterior superior alveolar artery and associated gingival ischemia, highlighting the role of high-frequency ultrasound in diagnosis and management. A 60-year-old woman developed vascular occlusion following supraperiosteal HA injection in the medial cheek. Clinical findings included livedo reticularis in the infraorbital and nasal regions, along with ipsilateral gingival anesthesia and mucosal ischemia. High-frequency ultrasound was used to assess the extent and mechanism of vascular involvement. A targeted treatment approach was implemented using low-dose hyaluronidase (100 IU/mL), with 200 IU administered in the infraorbital region and an additional 100 IU delivered under ultrasound guidance to the affected alveolar branch. Ultrasound examination revealed extrinsic compression of the infraorbital artery and secondary occlusion of the anterior superior alveolar artery consistent with retrograde embolization. Following image-guided administration of hyaluronidase, complete reperfusion was achieved, with resolution of both cutaneous and gingival ischemia and no functional or aesthetic sequelae. Conclusions: High-frequency ultrasound provides critical diagnostic information in vascular complications after HA filler injection, allowing for accurate identification of the mechanism and extent of vascular involvement. Ultrasound-guided low-dose hyaluronidase may represent an effective and safe strategy to restore perfusion while minimizing unnecessary enzyme exposure and associated adverse effects. Full article

Microglia are central regulators of Alzheimer’s disease pathogenesis, but their roles cannot be reduced to a simple protective-versus-harmful dichotomy. Genetic, single-cell, and spatial studies have shown that Alzheimer ’s-associated microglia occupy diverse disease-linked states shaped by amyloid plaques, tau pathology, lipid stress, complement activation, astrocyte signaling, aging, and immune genetic risk. Among the regulatory nodes controlling these states, SPI1, which encodes the myeloid transcription factor PU.1, has emerged as a key determinant of microglial identity and disease responsiveness. Human genetic studies suggest that reduced SPI1 expression may be protective, whereas experimental data indicate that excessive PU.1 suppression can impair essential microglial functions. This review examines the emerging concept that partial, plaque-associated reduction in PU.1 may enable a distinct lymphoid-like immunoregulatory microglial program marked by CD28 expression. Recent evidence suggests that PU.1-low CD28-positive microglia may restrain neuroinflammation and amyloid pathology, raising the possibility that Alzheimer’s plaques induce not only inflammatory and phagocytic microglial responses, but also endogenous suppressive programs that limit tissue damage. We discuss this proposed PU.1/CD28 regulatory axis in relation to disease-associated microglia, TREM2–APOE signaling, complement-mediated synapse loss, antigen-presentation pathways, plaque-niche biology, and therapeutic microglial reprogramming. We also highlight major unresolved questions, including whether PU.1-low CD28-positive microglia are present and functional in human Alzheimer’s disease, whether they are specific to amyloid-rich niches or extend to tau and mixed pathologies, and how such states could be safely manipulated without disrupting essential immune surveillance. We propose that lymphoid-like suppressive microglia represent a promising but still unproven framework for understanding protective neuroimmune regulation in Alzheimer’s disease and for developing state-specific microglial therapies. Full article

A massive number of early-constructed small-to-medium-span bridges are collectively entering an “aging” phase in China. Meanwhile, vast amounts of unstructured bottom-level inspection texts remain underutilized. To address them, this paper proposes a data governance method. Large Language Models were leveraged to process unstructured defect data from 18,238 real-world bridges nationwide. The data were structurally cleaned and mapped into discrete features, revealing multidimensional vulnerabilities. On this basis, the Stable Contrastive Pattern Risk (SCPR) intelligent decision-making model was developed. The results demonstrate that, following robust filtration, 6 nationwide common risk rules were extracted from 2064 initial candidate combinations. These rules converge into three core risk patterns: the heavy-duty aging pattern, the substructure-dominated pattern, and the over-water small-span low-seismic-design pattern. Guided by these robust rules and specific damage enrichment characteristics, risk stratification and differentiated management strategies were further formulated for Class III bridges. This research facilitates a paradigm shift in bridge maintenance. It moves from reactive, post-event symptom characterization toward data-driven, proactive early warnings. This shift provides a substantive scientific foundation for optimizing resource allocation and enabling precise investment decisions at the road network level. Full article

Background/Objectives: Acute lung injury (ALI) currently lacks safe and effective therapeutic strategies with low toxicity. Lonicerae japonicae flos, a traditional herb and functional food, contains polyphenols as its principal active components. This study investigated whether Lonicerae japonicae flos polyphenols (LJP) could exert protective effects against lipopolysaccharide (LPS)-induced ALI in mice. Methods: Eighty-four male C57BL/6J mice were randomly divided into seven groups and treated daily for 7 days with LJP (200, 100, or 50 mg/kg), liproxstatin-1 (10 mg/kg), dexamethasone (5 mg/kg), or saline (control and model groups). Subsequently, another thirty-six mice were used for the fecal microbiota transplantation (FMT) experiment. All groups except the control group received intratracheal instillation of LPS (5 mg/kg) to induce ALI. Results: LJP treatment significantly ameliorated lung histopathological damage and gut microbiota dysbiosis. Lung proteomics analysis revealed the enrichment of the NF-κB and ferroptosis pathways. Mechanistically, LJP downregulated pro-inflammatory factors (IL-6, TNF-α, and IL-1β) by suppressing activation of the TLR4/MyD88/NF-κB pathway. Meanwhile, LJP upregulated SOD and GSH levels, thereby suppressing the accumulation of ROS, GSSG, Fe²⁺, and MDA, which were closely related to the activation of the Nrf2/HO-1 and Sirt3/Nrf2/GPX4 pathways. Furthermore, LJP modulated the gut microbiota and promoted short-chain fatty acid (SCFA) production by elevating the relative abundance of Akkermansia muciniphila and Faecalibaculum. Intriguingly, FMT results confirmed that the LJP-derived gut microbiota markedly alleviated lung tissue injury and intestinal barrier damage in ALI mice. Conclusions: This study demonstrated that LJP could reshape the gut microbiota to enhance the production of SCFAs and inhibit inflammation-related ferroptosis in ALI mice. Full article

The results of a multiscale study of fault and fracture geometry, distribution, density, and intensity are reported for Mesozoic platform carbonates cropping out along the axial zones of the southern Apennines fold-and-thrust belt, Italy. By integrating field structural observations with digital outcrop analysis, the study focuses on Cretaceous limestone rocks exposed along natural creeks and artificial trails of the Castelsaraceno area, Raparo Mt., southern Italy. There, the limestone beds are bounded by mm- to cm-thick marly–clayey interbeds, forming a well-layered succession made up of a few m-thick bed packages bounded by several cm-thick clayish interlayers. The carbonate multilayer was first affected by thrust tectonics, with the formation of low-angle intra-carbonate thrust faults and fault bend-folding. Then, the multilayer was crosscut by extensional–transtensional high-angle faults, which displaced the previously formed contractional structural elements, and allowed carbonate exhumation from shallow crustal depths. At outcrop scales, thrust-related deformation was solved by low-angle joints and veins, rare high-angle stylolites, and low-angle sheared fractures displaying reverse kinematics. Quantitative analyses of fracture density (P20) and intensity (P21) conducted on selected portions of the thrust fault zones indicate that the low-angle joints and veins attain their highest values in the vicinity of the main slip surfaces, whereas they are almost absent in the surrounding carbonate host rocks. Plio-Quaternary transtensional deformation was solved by NW–SE- and NE–SW striking faults. The latter fault set, nicely exposed along the flanks of the Raganello Creek, was characterized by right-lateral components of slip. Incipient faults, with ca. 1 cm throw, are made up of vertically discontinuous slip surfaces, which crosscut single bed packages and abut against clayish interlayers. The slip surfaces form conjugate geometries, and are associated to high-angle fractures and veins striking NE–SW, dissecting the bed packages. The fault core is virtually absent, whereas the damage zones are very discontinuous along dip. The P20 values computed for the high-angle fractures and veins increase toward the slip surfaces, whereas the P21 values remain nearly constant. These data are interpreted as being due to fault nucleation processes associated with fracture nucleation within the limestone rocks. NE–SW striking small faults displaying throws between 10 and 60 cm are comprised of through-going main slip surfaces crosscutting multiple bed packages, and poorly developed, discontinuous fault cores flanked by m-thick damage zones. The damage zones include sub-parallel high-angle shear fractures, fractures and veins showing a positive correlation between P20 and P21, whose values increase in the vicinity of the main slip surfaces. Such a positive correlation is interpreted as due to fault growth by linkage and coalescence of pre-existing high-angle fractures, and formation of fault-related joints and veins at the extensional quadrants of single shear fractures. Similarly, large-scale NE–SW striking mature faults with throws on the order of tens of meters, made up of a m-thick fault core and 10 s of m-thick damage zones including sub-parallel fractures and veins, also show a positive P20 and P21 correlation. The main outputs of this work are synthesized into a conceptual model illustrating the transition from thrust-related deformation to extensional–transtensional faulting, documenting the evolution of fracture networks from incipient-to-small-to-mature faults. Full article

Icing phenomena on wind turbine blades and components are a major problem, causing downtimes that increase maintenance costs, reducing the blade’s lifespan, or in severe cases, even leading to component damage. A nanofiber-based bi-layer liquid-infused surface (BLIS) coating was prepared and characterized, combining good adhesion to wind turbine blades with low ice adhesion. The BLIS coating was produced by a new method combining electrospinning and a heat treatment step, containing a poly ethyl-2-cyanoacrylate (PECA)-based adhesive layer, a slippery layer of poly vinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) copolymer, and an infiltrated perfluoropolyether lubricant. Thermogravimetric analysis (TGA) was used to ensure the thermal stability of the polymers in the nanofiber coating layers and to optimize the heat treatment process of the layers. Microstructural changes were studied by scanning electron microscopy (SEM) and surface roughness measurements. Contact angle measurements and sliding velocity tests on wind turbine blade segments at icing conditions of 0 °C and +5 °C indicate that the water sliding properties of the BLIS coating were improved compared to uncoated blades. In addition, coated blade segments showed a 50% lower ice adhesion strength than uncoated blades. Full article

Global freshwater salinization endangers aquatic species, yet its impacts on crustaceans remain poorly understood. This study investigated the hepatopancreatic response of Eriocheir sinensis to carbonate alkalinity stress (0, 4.375, 8.75, 17.5, and 35 mmol/L) over 24, 48, and 96 h, integrating histology, ultrastructure, gene expression (RT-qPCR), and non-specific immune enzyme assays. Histopathological and ultrastructural analyses revealed concentration- and time-dependent damage, including vacuolization, hepatic tubule disintegration, nuclear condensation, mitochondrial reduction, and loss of cellular integrity. Molecular analysis demonstrated upregulation of genes associated with the TLR2-MyD88-NF-κB pathway and inflammatory genes (LITAF, IL-16), alongside increased HSP70 expression, confirming severe inflammation and cellular stress. Furthermore, apoptosis was induced via upregulated Bax and Caspase-3, downregulated Bcl-2, and DNA fragmentation. Non-specific immune responses in the hepatopancreas exhibited dynamic changes: acid phosphatase (ACP) was initially activated at low alkalinity but inhibited at high concentrations, while alkaline phosphatase (AKP) activity increased at 96 h. Notably, the hepatopancreas proved more sensitive to this stress than the hemolymph. Collectively, carbonate alkalinity causes multidimensional hepatopancreatic injury in E. sinensis through structural disruption, inflammation mediated by TLR2-MyD88-NF-κB signaling pathway-related genes, apoptosis induction, and immune enzyme dysregulation, posing a significant threat to crab health in salinized waters. Full article

Low-speed permanent magnet synchronous motors (LS-PMSM) have been widely adopted in fields such as mining and oil extraction due to their excellent stability and high efficiency. In practical applications, current harmonics cause a decline in motor control performance and, in severe cases, can damage the motor. This paper analyzes the mechanism of harmonic generation in LS-PMSM and derives a mathematical model for these harmonics. To address the 5th and 7th harmonics, which are particularly prominent, an improved harmonic voltage compensation module was added to the efficiency-optimized control system. The current averaging method was employed to extract harmonic currents in real time, and a fuzzy PI controller was used to perform closed-loop control of the harmonic currents, thereby obtaining accurate harmonic voltage compensation values. Finally, the control effectiveness of the harmonic voltage compensation was analyzed through simulation. The results indicate that this method can effectively suppress 5th and 7th harmonics and reduce torque ripple. Furthermore, the improved algorithm enhances the accuracy of harmonic current extraction and improves the dynamic performance of the controller. Full article

Tree-derived bio-based polymer materials, including natural rubber, raw lacquer, pine resin, and tree gums, are important renewable resources for sustainable forestry and green manufacturing. However, their collection still largely depends on manual operations, which may cause unstable yield, tree damage, and low operational efficiency. This review examines intelligent identification technologies for tree-derived material collection from the perspectives of multimodal perception and machine learning. The collection requirements and recognition targets of typical materials are first analyzed, including trunk localization, tapping line detection, bark feature extraction, tree state assessment, and safe tool–bark interaction. Visual, RGB-D, LiDAR, spectral, force/tactile, and environmental sensing technologies are then reviewed, and their roles in complex forest perception and robotic operation are discussed. Machine learning methods, including traditional classifiers, object detection, image segmentation, point cloud processing, temporal modeling, few-shot learning, transfer learning, and uncertainty-aware evaluation, are further examined. Representative cases in rubber tapping, lacquer collection, and pine resin harvesting are compared to reveal the transition from single-sensor recognition to perception–decision–execution integration. Key challenges are identified in dataset standardization, model generalization, edge deployment, force-aware control, and biological mechanism integration. Future directions are proposed toward autonomous, low-damage, and high-yield intelligent collection systems. Full article

Background/Objectives: Systemic lupus erythematosus (SLE) is characterized by diverse clinical presentations and complex immunological mechanisms. This study aimed to characterize patient serology associated with disease activity scored using the systemic lupus erythematosus disease activity index (SLEDAI) and investigate the molecular signature of complement activation (measured through C3dg, a complement breakdown product) in SLE patients utilizing high-throughput mass spectrometry and autoantibody profiling. Methods: Plasma samples from 39 SLE patients in four mutually exclusive groups based on either disease activity scores (high/low SLEDAI) or complement activation levels (high/low C3dg) were analyzed using rapid LC-MS/MS, followed by unsupervised and supervised protein expression analysis. Complement activation was evaluated by measuring C3dg levels, and disease activity was scored using SLEDAI. Autoantibody reactivities were profiled using global autoantibody protein microarrays. Data are available via ProteomeXchange with identifier PXD066214. Results: Differential proteomic analyses revealed 25 proteins associated with SLE disease activity (high vs. low SLEDAI scores) and 25 proteins linked to complement activation levels (high vs. low C3dg). Enriched pathways indicated that adaptive immune response, classical complement activation, and immunoglobulin production correlated with disease activity, while complement activation and coagulation cascades were primarily associated with complement activation levels. Autoantibody profiling highlighted distinct reactivity patterns between subgroups, suggesting varying degrees of immune-mediated tissue damage. Conclusions: In this study, disease activity and complement activation markers were associated with overlapping yet non-identical plasma proteomic patterns in SLE. These findings support the feasibility of rapid mass spectrometry-based proteomics and autoantibody profiling for generating candidate molecular signatures in SLE. These findings serve as exploratory signatures that require validation in larger independent cohorts before they can be considered for clinical stratification and decision-making. Full article

Fiber-reinforced polymer (FRP) composites are extensively used in aerospace, civil engineering, and defense applications because of their low density, high specific strength, corrosion resistance, and structural design flexibility. However, prolonged exposure to hygrothermal conditions, ultraviolet (UV) radiation, and thermo-oxidative environments can progressively damage these materials, leading to mechanical degradation and shortened service life. This review examines environmental aging in FRP composites at the levels of the polymer matrix, fiber/matrix interface, and reinforcing fibers. Representative predictive models, finite element methods, and experimental characterization techniques are summarized, together with the evolution of mechanical properties under different aging conditions. Hygrothermal degradation is mainly associated with moisture diffusion, matrix swelling, and interfacial debonding, whereas UV and thermo-oxidative aging are largely governed by photo-oxidation and thermally activated free-radical reactions. These processes may induce chain scission, crosslinking, matrix embrittlement, and interface damage. Under coupled environmental exposure, degradation is not simply additive because moisture transport, oxidation kinetics, and failure pathways may interact. Future research should emphasize multiscale characterization, anti-aging modification, interface engineering, protective coatings, and reliability-oriented lifetime prediction. Full article

Deep unconventional oil and gas reservoirs are critical to hydrocarbon exploration and development in China. However, their complex geological and petrophysical features, including high temperature, high pressure, high salinity, multiple pressure systems, and intricate pore–fracture structures, make them highly susceptible to formation damage during drilling, completion, stimulation, and production. Effective reservoir protection is therefore essential for minimizing damage and improving development efficiency. This paper systematically reviews recent advances in reservoir protection for deep unconventional reservoirs, with a focus on evaluation methods and protective materials. Laboratory evaluation methods, including permeability recovery, nuclear magnetic resonance, pressure decay, and spontaneous imbibition, together with field-based approaches such as well testing and production decline analysis, are summarized and assessed for their applicability to complex damage characterization. Major damage mechanisms, including liquid-phase trapping, solid invasion, sensitivity damage, stress sensitivity, and wettability alteration, are analyzed with emphasis on working fluid–reservoir interactions under multi-field coupling conditions. Recent progress in protective materials is also reviewed, covering polymer-based materials such as gel sealing agents, delayed-swelling hydrogels, water-/oil-soluble temporary plugging agents, and film-forming polymers, as well as ultrafine CaCO₃ and fiber-based materials. In addition, related protection technologies, including temporary plugging, film-forming fluid-loss control, underbalanced drilling, and low-damage completion fluids, are discussed. Existing models developed for conventional sandstone reservoirs are insufficient for deep unconventional systems. Future research should prioritize integrated evaluation and protection methods tailored to deep tight, shale, and fractured–vuggy carbonate reservoirs. This review provides a basis for understanding complex damage mechanisms, developing functional protective materials, and advancing integrated reservoir protection technologies for the efficient development of deep unconventional resources. Full article