Search Results (352)

Neuroblastoma (NB), the most common extracranial solid tumor of childhood, exemplifies one of the most formidable paradigms of tumor immune evasion (TIME) in pediatric oncology. Despite significant advances in multimodal therapy and the clinical integration of immunotherapeutic strategies, high-risk NB (HR-NB) remains largely refractory to durable immune control. This failure reflects not an absence of immune engagement, but the presence of a highly evolved and developmentally wired immune escape architecture. In this review, we synthesize emerging insights from single-cell, multi-omics, and functional studies to define how developmental lineage, cellular plasticity, metabolic rewiring, epigenetic regulation, and therapy-induced adaptation converge to engineer immune blindness in NB. We discuss how NB’s neural crest origin establishes a baseline of low immunogenicity, which is subsequently reinforced through coordinated suppression of antigen presentation, dominance of immune checkpoint signaling, and profound dysfunction of cytotoxic T and natural killer cells within an immunosuppressive tumor microenvironment. Central to this process is tumor-intrinsic plasticity, whereby lineage instability and dedifferentiation, exacerbated by therapeutic pressure, embed immune silence as a stable tumor state. We highlight evidence positioning RD3 as a master upstream regulator linking cellular identity to immune visibility, governing antigen presentation, innate immune sensing, checkpoint expression, and cytotoxic lymphocyte engagement. Beyond tumor-intrinsic mechanisms, we examine the roles of immunosuppressive myeloid populations, tumor-derived exosomes, metabolic stress, hypoxia, and ferroptosis-associated pathways in reinforcing immune paralysis. Finally, we outline emerging therapeutic strategies aimed at dismantling this architecture, including combinatorial checkpoint blockade, metabolic and epigenetic reprogramming, exosome-targeted interventions, and next-generation immune engineering platforms. Together, this review reframes TIME in NB as a programmable, developmentally rooted process and provides a mechanistic roadmap for restoring immune competence and therapeutic susceptibility in HR disease. Full article

Topographic ridges are widely used in wildfire interpretation, suppression planning, and potential control-line design, but the claim that final fire boundaries preferentially follow ridge crests is rarely tested against local terrain availability. Remote-sensing-based burn mapping and DEM-derived terrain metrics now make this question testable at cohort scale, although most Korean wildfire studies have focused on ignition, occurrence probability, or fire-risk prediction rather than final-perimeter geometry. We therefore tested whether 118 final wildfire perimeters in the Republic of Korea (2018–2025) were non-randomly associated with ridge lines derived independently from a 30 m SRTM DEM. Sentinel-2 pre- and post-fire imagery and official fire metadata were used to generate burn masks and perimeters, which were sampled every 20 m and compared with ridge networks using a proximity endpoint (R30) and a joint distance-orientation endpoint (Aθ) under a local translate-and-rotate null model. Most fires were both more ridge-proximal and more strongly ridge-aligned than their local null perimeters, and the directional signal was the stronger of the two (mean enrichment 2.3, versus 1.5 for proximity alone). A valley-inclusive comparator showed no comparable pattern, indicating an association specific to ridges rather than to terrain lines in general. The directional signal was robust to ridge continuity, spatial scale, null design, and the exclusion of road-adjacent ridges. Because the analysis uses final mapped perimeters rather than time-resolved fire fronts, it documents a ridge-specific geometric association rather than proof that ridges stopped individual fires. These results provide an observational benchmark for terrain representation in fire-spread models. Full article

One of the main technological challenges in plasma wakefield acceleration (PWFA) research and development is achieving stable and reproducible acceleration. In particular, for PWFA schemes based on particle-driven plasma wave excitation, beam stability and timing jitter are increasingly critical. In these configurations, magnetic or radio-frequency (RF) compression schemes are often used, and the beam time-of-arrival jitter at the end of the linear accelerator can be strongly correlated with the phase noise of RF accelerating structures operated off-crest. For this reason, since 2008, an RF phase fast-feedback system acting within each RF pulse has been successfully implemented at Laboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare (LNF-INFN) at the Sources for Plasma Accelerators and Radiation Compton with Laser And Beam (SPARC_LAB) facility, operating on both S-band ($2.856$ GHz) and C-band ($5.712$ GHz) klystrons. This paper presents the upgrade and optimization of the fast-feedback system for an S-band klystron powered by a pulse-forming network modulator. This technology introduces significantly higher intrinsic phase noise than, for instance, solid state-based modulators. It is therefore essential to minimize such phase fluctuations to keep the machine stability under control. Both the feedback hardware (electronic boards and RF circuitry) and the software (controller and user interface) have been upgraded. Tests performed at SPARC_LAB achieved a reduction in klystron-induced jitter of a factor of 30, reaching values below 15 fs rms on both power plants. Moreover, adding a remote control of the feedback loop enabled a straightforward optimization of the operating point, allowing the phase stability performance to be pushed close to its practical limits. A detailed analysis of RF phase noise measurements with the fast-feedback loop in operation is also presented. Full article

Chronic atrophic gastritis (CAG) is the principal precursor lesion for gastric adenocarcinoma and represents a key target for endoscopic surveillance and early intervention. Although the global age-standardised incidence of gastric cancer has declined over recent decades, the absolute number of cases continues to rise because of population ageing and increasing incidence in younger individuals. The prognosis remains poor in advanced disease, whereas early gastric cancer (EGC) detected at a mucosal stage is associated with excellent long-term survival and may be curable with endoscopic resection. Consequently, high-quality endoscopic detection of premalignant gastric lesions is essential to reduce gastric cancer mortality. This review summarises current concepts in the endoscopic diagnosis of CAG, gastric intestinal metaplasia (GIM), and EGC, from conventional white-light endoscopy through to advanced imaging and artificial intelligence (AI)-assisted systems. Fundamental principles of high-quality oesophagogastroduodenoscopy are discussed, including adequate inspection time, systematic mucosal assessment, mucosal cleansing, and standardised photo-documentation. Characteristic endoscopic appearances of normal gastric mucosa, atrophy, and intestinal metaplasia are reviewed, alongside established staging systems including the Kimura–Takemoto and EGGIM classifications. The role of image-enhanced endoscopy is examined in detail, including narrow-band imaging, linked colour imaging, texture and colour enhancement imaging, and magnification optical enhancement. These modalities improve visualisation of pit patterns, microvascular architecture, and hallmark features of intestinal metaplasia such as the light blue crest sign, substantially increasing diagnostic sensitivity and specificity compared with conventional white light imaging alone. Advanced imaging combined with magnification also enhances the detection and characterisation of EGC. Emerging evidence regarding AI-assisted endoscopy demonstrates promising diagnostic accuracy for CAG, GIM, and early neoplasia, with improved lesion detection and reduced miss rates in several studies. However, limitations relating to external validation, generalisability, and integration into routine practice remain. Continued advances in optical imaging, structured training, and AI-supported diagnostics are likely to play an increasingly important role in improving early gastric cancer detection and surveillance outcomes worldwide. Full article

Metal hydride (MH) systems offer a compelling route to solid-state hydrogen storage, yet their practical charging rate is fundamentally limited by the low effective thermal conductivity of the hydride bed and the substantial exothermic heat generated during absorption. Addressing this thermal bottleneck without sacrificing hydride volume remains a central challenge in MH reactor design. This study proposes an integrated thermal enhancement strategy in which transverse fins are coupled with a sinusoidal corrugated heat transfer tube, combining the boundary-layer disruption effect of corrugated geometry with the extended heat transfer surface provided by fins. A three-dimensional transient numerical model is developed within a porous-medium framework to compare straight-tube and corrugated-tube reactors equipped with different fin arrangements. The influences of corrugated-tube inlet radius, fin length, and fin inclination angle on hydrogen absorption performance are then systematically evaluated. The results show that positioning transverse fins on the upper side of the wave crests establishes the most direct conductive pathway between the hydride bed and the coolant, while appropriate fin geometry effectively suppresses low-conversion dead zones and improves the spatial uniformity of the reaction field. Compared with the finless sinusoidal corrugated-tube reactor and the conventional transverse-finned straight-tube reactor, the optimized configuration shortens hydrogen storage time by 62.74% and 42.05%, respectively, confirming that the synergistic combination of transverse fins and corrugated-tube geometry constitutes an effective and compact thermal management solution for MH hydrogen storage reactors. Full article

Mesenchymal stem/stromal cells (MSCs) hold promise for treating different equine conditions but enter senescence during culture. Using induced pluripotent stem cells (iPSCs) to derive MSC-like cells (iMSCs) can increase cell availability and diminish the need for invasive and repeated tissue harvesting. While human iMSCs are intensively studied, research on equine iMSCs (eqiMSCs) is very limited and has focused on strategies for spontaneous differentiation to obtain these cells. The aim of this study was to obtain MSC-like cells from equine iPSCs (eqiPSCs) by directing their differentiation via the neural crest pathway. The resulting eqiMSCs downregulated pluripotent gene expression compared to originating eqiPSCs, and the majority of lines met most of the standard criteria for tissue-derived MSCs (immunophenotype and tri-lineage differentiation potential). Nevertheless, eqiMSCs showed some differences from primary equine MSCs, possibly due to their different developmental origin, and displayed certain inter-line variability, which might be related to the different kinetics of independent eqiPSC lines. This study demonstrates for the first time that equine MSC-like cells (eqiMSCs) can be derived from eqiPSCs by directing their differentiation through the neural crest pathway. This constitutes an important advancement towards more sustainable sources of therapeutic cells in veterinary medicine and warrants further exploration of the functional characteristics of these novel cells. Full article

Traditional road geometric design is based on assumptions regarding human perception and reaction, which directly influences Stopping Sight Distance (SSD) and the associated design parameters of vertical curves. Under a future scenario of full autonomous vehicle (AV) deployment, reduced perception–reaction times and modified sensing configurations may change visibility-controlled design requirements. This study presents a structured parametric assessment of SSD and vertical curve lengths under the assumption of full AV operation. Variations are considered in reaction time, sensor height, sensor inclination angle, longitudinal grade, and vehicle operating speed. Default parameter values derived from current design standards, together with ranges reported in the literature, are used to evaluate the geometric implications of full vehicle automation within a controlled analytical framework. The results indicate that reduced reaction times and increased sensor heights of AVs may decrease required SSD values and consequently shorten crest and sag vertical curve lengths compared to conventional human-driven vehicle assumptions. For sag curves in particular, headlight inclination angle is revealed as a significant geometric variable. Overall, the study proposes a framework for examining the interaction between AV sensing characteristics and vertical geometric design, thereby providing a basis for future evaluation of design standards without directly prescribing modifications to current practice. Full article

Freak waves can cause damage or capsize marine structures. The efficient fixed-point generation of target wave trains containing freak waves in laboratories or numerical wave tanks is a crucial method for marine structure design and disaster inversion assessment. This study proposes a local coefficient assignment method. After no more than three iterations of local wave train processing, the method achieves accurate generation of measured freak wave trains at different positions. Among the results, the maximum crest error for the “New Year Wave” is less than 3%, and the simulation achieves excellent agreement in significant wave height, period, and overall wave surface elevation with the target wave surface. The assignment coefficient curve of the typical freak wave event “New Year Wave” within the farthest fixed-point generation range of the numerical simulation in this paper is provided, enabling high-precision one-time generation of the “New Year Wave” at any desired position. The resulting maximum wave height error is less than 5%, satisfying the application requirements of deep-water waves under different water depth conditions. Furthermore, based on the simulation results, wavelet transform analysis is performed on the wave train data to investigate the evolution characteristics of wave energy before, during, and after the occurrence of the freak wave. The findings of this study have strong practical engineering significance for research on the propagation and evolution characteristics of highly nonlinear waves, as well as for the design and analysis of wave loads on marine structures. Full article

The increasing integration of intermittent renewable energy sources (RESs) into islanded Hybrid Power Systems (HPSs) is a critical step towards global energy sustainability; however, it poses significant challenges to frequency stability owing to low system inertia and stochastic power fluctuations. To address these challenges and enable higher penetration of green energy, this study proposes a novel and robust Load Frequency Control (LFC) strategy based on the Crested Porcupine Optimizer (CPO). A customized Mode-Dependent Adaptive Balloon (MDAB) controller is developed, wherein the virtual control gain is dynamically tuned based on the real-time operating modes and disturbance severity. Furthermore, to optimize communication resources and mitigate actuator wear in networked microgrids, an intelligent event-triggered (ET) mechanism is seamlessly integrated into the adaptive logic. The proposed control framework is rigorously validated through comprehensive nonlinear simulations and comparative analyses with state-of-the-art metaheuristic algorithms (GTO, GWO, JAYA, and GO). The evaluation encompasses step load disturbances, severe parametric uncertainties (+25%), realistic 24-h diurnal cycles with solar cloud shading and wind turbulence, and extended practical constraints, including Battery Energy Storage System (BESS) integration and Internet of Things (IoT) communication delays. The results demonstrate the superiority of the CPO-tuned framework, which achieved the fastest transient recovery (settling time of 3.4367 s) and the lowest absolute Integral Absolute Error (IAE). Additionally, the proposed ET-based strategy not only reduced the communication burden but also improved the overall control performance by 37% in terms of IAE compared with continuous approaches. By inherently filtering measurement noise, mitigating control signal chattering, and maintaining resilience under nonideal latency, the proposed architecture offers a highly robust and resource-efficient solution that directly guarantees the operational sustainability and reliability of modern smart microgrids. Full article

This study aimed to enhance the accuracy and interpretability of erosion gully classification within black soil regions by focusing on Changxing Township, Xinxing District, Qitaihe City, Heilongjiang Province as the research site. Utilizing RTK (Real-Time Kinematic) surveying technology, three-dimensional topographic data were collected for 139 actively developing erosion gullies. Key morphological parameters—including gully length, depth, gradient, average top width, average bottom width, and slope gradients on both sides—were extracted to construct interactive features. The variable set was refined through correlation analysis and variance inflation factor (VIF) diagnostics to mitigate multicollinearity. A random forest model was employed as the primary classification approach and benchmarked against logistic regression, support vector machines (SVM), decision trees, and backpropagation neural networks. To address class imbalance, a combination of class weighting, Synthetic Minority Over-sampling Technique (SMOTE), and undersampling methods was implemented. Model tuning and interpretability assessments were performed using cross-validation, grid search optimization, and SHapley Additive exPlanations (SHAP) analysis. The findings demonstrate that the random forest model achieved superior overall performance, with test set accuracy, macro-averaged F1 score, and balanced accuracy values of 0.9143, 0.8087, and 0.8427, respectively. Among imbalance handling techniques, class weighting yielded better results compared to oversampling and undersampling. Feature importance and SHAP analyses identified gully length, average crest width, and their interaction with gully depth as the principal determinants influencing gully grade classification. These results elucidate the synergistic developmental dynamics of gully longitudinal extension, vertical deepening, and lateral widening. The proposed methodology offers valuable technical support for the rapid surveying, classification, and management decision-making processes related to black soil erosion gullies. Full article

Current evidence suggests that achieving the desired level of osseointegration necessitates a hierarchical approach to implant design. This is particularly relevant for osseointegration around implant systems such as those presenting vertical decompression chambers and acid-etched surfaces which could further be augmented by non-thermal plasma (NTP) treatment. Three implant systems were compared in this study: (i) ND (GM Helix Acqua Implant; Neodent^®, Curitiba, PR, Brazil—hybrid, acid-etched thread design treated with isotonic sodium chloride solution), (ii) Sin (Epikut Plus; S.I.N. Implant System, São Paulo, Brazil—V-shaped, acid-etched thread design treated with nano-hydroxyapatite), and (iii) Mp (Maestro; Implacil De Bortoli, São Paulo, Brazil—buttress, acid-etched thread design with decompressing vertical chambers). The ND and Sin implants were used directly as supplied by the manufacturer. For the Mp implants, the manufacturer-supplied surface was subjected to supplemental acid etching with 37% hydrochloric acid followed by Argon-based NTP treatment administered with a pulsed plasma generator prior to implantation into the iliac crest of n = 12 adult female sheep. Histomorphometric analysis was conducted at 3- and 12-week post-implantation (n = 6 sheep per time point) to assess bone-to-implant contact (BIC) and bone area fraction occupancy (BAFO). After 3 weeks in vivo, the healing chambers of all implant groups consisted predominantly of newly forming woven bone. By 12 weeks, bone maturation was observed, with the presence of remodeling sites and some areas of well-organized lamellar structures occupying the healing chambers. At both 3 and 12 weeks, the Mp implants demonstrated significantly higher BAFO values relative to ND (p = 0.015 and p = 0.008, respectively). The combination of vertical healing chambers, acid etching, and NTP treatment promoted early vascular infiltration and sustained bone deposition. Full article

Cranial crests have evolved multiple times in the evolutionary history of vertebrates, serving primarily for visual display. In duck-billed lambeosaurines, one of the most successful dinosaur clades of the Late Cretaceous, the cranial crest became hollow along the paired premaxillae and nasals, and was secondarily selected as a resonating structure atop the skull roof, facilitating acoustic signaling. Here we report the first instance of a hollow supracranial crest in a non-lambeosaurine ornithopod dinosaur, the early-branching hadrosauroid Qianjiangsaurus changshengi, where the paired accessory endonasal cavities just above the nasal cavity proper occur following the dorsoventral thickening of the nasals. This novel nasal cavity configuration is associated with the helmet-like hollow supracranial crest solely formed by the nasals. Comparative resonance modeling suggests that the nasal cavity of Q. changshengi could amplify low-frequency vocalizations similar to those of late-branching lambeosaurines. Seven analogous skull features (including the hollow supracranial crest) and similar low-frequency acoustic capabilities of nasal cavities between Q. changshengi and late-branching lambeosaurines reveal a striking morphological and functional convergence that would likely facilitate safer, more efficient social communication among hadrosauroids. This convergence can be explained by adaptive evolution under similar selection pressures, combined with developmental constraints due to gene pleiotropy. Full article

Battery-balancing circuits are essential for improving the performance, safety, and service life of lithium-ion battery packs in electric vehicles and energy storage systems. This paper proposes a modified multi-port half-bridge DC–DC circuit with a reconfigurable port network and its control method for battery balancing and multi-level DC voltage output. The circuit evolves from traditional inductor-based balancing units, while a new sequential turn-off switching strategy is introduced so that only one switch is turned off at any moment, achieving precise voltage distribution by adjusting the duty cycle. To improve control accuracy, a dual closed-loop voltage-current control strategy with adaptive gain scheduling and nonlinear compensation is employed. Furthermore, a predictive voltage control strategy based on Mamba-Multilayer Perceptron optimized by the Crested Porcupine Optimizer (CPO-Mamba-MLP-PVC) is proposed. This data-driven approach predicts a target voltage that considers battery and circuit losses, thereby optimizing the balancing path. Experimental results obtained from a hardware prototype verify both battery equalization and multi-level DC output functions. Compared with conventional methods, the proposed CPO-Mamba-MLP-PVC strategy reduces the balancing time by 18.03% and increases the energy utilization rate to 90.7%. Full article

Monitoring dam stability is critical to ensure structural safety and operational reliability. This study integrates Persistent Scatterer Interferometry (PSI) based on Sentinel-1 SAR imagery (2020–2023) with Finite Element Method (FEM) simulations to assess the behavior of the Koyna Dam in India. PSI detected crest displacements between −1.0 and −1.8 mm yr⁻¹, while FEM simulations predicted a maximum vertical displacement of approximately −3.2 mm at the crest. Although these results represent different quantities (time-averaged displacement rates versus peak static displacement), both approaches indicate millimeter-scale deformation and a consistent pattern of settlement at the dam crest, supporting the interpretation of hydrologically driven structural response. The observed differences are primarily attributed to differences in spatial resolution and methodology between point-based FEM outputs and pixel-averaged satellite observations. The study demonstrates that combining satellite-based monitoring with numerical simulations provides a robust and cost-effective framework for dam safety assessment. This integrated approach supports improved interpretation of deformation behavior and offers practical value in extreme conditions, such as during flood events or climate-driven hydrological changes. Furthermore, continued advances in remote sensing and numerical modeling are expected to enhance the reliability of such approaches, making this methodology a transferable and sustainable solution for dam management worldwide. Full article

To address the complex calibration parameters and low optimization efficiency of dual-fuel engines, this paper innovatively proposes an optimization calibration method based on a simulation model and the Non-Dominated Sorting Whale Optimization Algorithm (NSWOA). Taking the YC6K dual-fuel engine as the research object, a high-precision simulation model was constructed within the GT-Power environment, and its reliability was confirmed through the external characteristic curve (the maximum deviation of torque and specific fuel consumption rate is less than 5%). A total of 260 parameter samples were generated using a Sobol sequence space-filling experimental design, and a performance prediction model was established by combining the Crested Porcupine Optimization algorithm and the Back-Propagation Neural Network (CPO-BP). The experimental results show that the CPO-BP model exhibits excellent predictive capability, with the coefficient of determination (R²) of nitrogen oxides (NO_x) and brake-specific fuel consumption rate (BSFC) reaching 0.98964 and 0.99501 respectively. Based on this, the NSWOA algorithm was introduced to optimize key parameters such as speed, torque, main injection timing, and rail pressure, with the optimization objectives being NO_x emissions and BSFC. The optimization results show that under 100% load conditions, the reduction in BSFC ranges from 1.5% to 4.3%, and NO_x emissions are reduced by 48.6% to 67.1%. The effectiveness of the optimized parameters was also verified through bench tests, providing an efficient solution for complex engineering optimization problems. Full article