Search Results (20,053)

Pancreatic cancer is among the deadliest malignancies, with limited treatment options and poor prognosis. Novel strategies are therefore urgently needed. Sotorasib, a KRAS G12C-specific inhibitor, offers targeted treatment for a small subset of patients with this mutation. Electrochemotherapy (ECT), which enhances the cytotoxicity of chemotherapeutic agents through electroporation-induced membrane permeabilization, has shown promise in various tumor types, including deep-seated malignancies such as pancreatic cancer. Combining ECT with sotorasib may potentiate antitumor effects in KRAS G12C-mutated pancreatic cancer; however, preclinical data on such combinations are lacking. This proof-of-concept study evaluated the cytotoxic effects of ECT using bleomycin (BLM) or cisplatin (CDDP) in combination with sotorasib in KRAS G12C-mutated MIA PaCa-2 and KRAS G12D-mutated PANC-1 pancreatic cancer cell lines. ECT alone significantly reduced cell viability, particularly in MIA PaCa-2 cells, where electric pulses induced approximately 75% cell death. Combining ECT with sotorasib resulted in an additive effect on KRAS G12C-mutated MIA PaCa-2 cells, though no synergy was observed, likely due to the high intrinsic sensitivity to electric pulses. These results support the potential of combining physical and molecular therapies in a subset of pancreatic cancer patients and lay the groundwork for further in vivo studies to optimize treatment parameters and explore clinical translatability. Full article

Accurate segmentation of densely stacked and weakly textured objects remains a core challenge in robotic depalletizing for industrial applications. To address this, we propose MaskNet, an instance segmentation network tailored for RGB-D input, designed to enhance recognition performance under occlusion and low-texture conditions. Built upon a Vision Transformer backbone, MaskNet adopts a dual-branch architecture for RGB and depth modalities and integrates multi-modal features using an attention-based fusion module. Further, spatial and channel attention mechanisms are employed to refine feature representation and improve instance-level discrimination. The segmentation outputs are used in conjunction with regional depth to optimize the grasping sequence. Experimental evaluations on camshaft depalletizing tasks demonstrate that MaskNet achieves a precision of 0.980, a recall of 0.971, and an F1-score of 0.975, outperforming a YOLO11-based baseline. In an actual scenario, with a self-designed flexible magnetic gripper, the system maintains a maximum grasping error of 9.85 mm and a 98% task success rate across multiple camshaft types. These results validate the effectiveness of MaskNet in enabling fine-grained perception for robotic manipulation in cluttered, real-world scenarios. Full article

Neural networks have shown significant promise in the field of image processing, particularly for tasks such as denoising and restoration, due to their capacity to model complex nonlinear relationships between inputs and outputs. In this study, we explored the application of a complex-valued neural network—a multilayer neural network with multi-valued neurons (MLMVN)—for filtering two types of noise in digital images: additive Gaussian noise and multiplicative speckle noise. The proposed approach involves processing images as a set of overlapping patches in the frequency domain using MLMVN. Training was performed using a batch learning algorithm, which proved to be more efficient for big learning sets: it results in fewer learning epochs and a better generalization capability. Experimental results demonstrated that MLMVN achieves noise filtering quality comparable to well-established methods, such as the BM3D, Lee, and Frost filters. These findings suggest that MLMVN offers a viable framework for image denoising, particularly in scenarios where frequency domain processing is advantageous. Also, complex-valued logistic and hyperbolic tangent activation functions were used for multi-valued neurons for the first time and have shown their efficiency. Full article

Background: Proximal gastrectomy (PG) with double tract reconstruction (DTR) offers organ preservation for early gastric cancers, leading to reduced vitamin B12 deficiency, less weight loss, and improved quality of life. The JCOG1401 study confirmed excellent long-term outcomes for PG in stage I gastric cancer. However, in locally advanced proximal gastric cancer (LAPGC), preserving the gastric body and lymph node station 4d may compromise margin clearance and adequate lymphadenectomy. Methods: We propose a modified PG that removes the distal esophagus, gastroesophageal junction (GEJ), cardia, fundus, and gastric body, preserving only the antrum and performing DTR. Lymphadenectomy is also adapted, removing stations 1, 2, 3a, 4sa, 4sb, 4d, 7, 8, 9, 10 (spleen preserving), 11, and lower mediastinal nodes (stations 19, 20, and 110), while preserving stations 3b, 5, and 6. Indications for this procedure include GEJ (Siewert type II and III) and proximal gastric cancers with ≤2 cm distal esophageal involvement and ≤5 cm gastric involvement. Results: In our initial experience with 14 patients, we achieved R0 resection in all patients, adequate lymph node harvest (median 24 nodes, IQR 18–38), and no locoregional recurrences at a median follow-up of 18 months. We also found favorable postoperative weight loss, reflux, and anemia in the PG cohort. Conclusion: While larger studies and long-term data are still needed, our early results suggest that modified PG—despite sparing only the antrum—retains the key benefits of PG over total gastrectomy, including better weight maintenance and improved hemoglobin levels, while maintaining oncologic outcomes for LAPGC. Full article

The present study aimed to optimize amaranth microgreen production by evaluating key factors such as the seeding density (SD), substrate type (ST), electrical conductivity (EC), and the application intervals of the nutrient solution. A split-plot experimental design was employed, with three EC levels (tap water at 0.3 dS m⁻¹) and nutrient solutions at 1.0 (50% half-strength) and 2.0 dS m⁻¹ (100% full-strength) assigned to the main plots. The subplots combined two ST (coconut fiber and phenolic foam) with four SD (25, 50, 75, and 100 g m⁻²). Two experiments were conducted using this setup, varying the application intervals of water or nutrient solutions for either two or four hours. Asteca amaranth microgreens were cultivated for eight days (a total of 10 days from sowing). The traits analyzed were seedling height (SH), seedling fresh matter (SFM), SFM yield (SFMY), seedling dry matter (SDM), SDM yield (SDMY), water content in seedling, and water productivity of SFM. The results showed that using a half-strength nutrient solution was sufficient for amaranth production compared to using water alone. Coconut fiber outperformed phenolic foam across all evaluated parameters. Based on these findings, we recommend cultivating amaranth microgreens at a SD of 80 g m⁻² on coconut fiber substrate using a nutrient solution of 1.0 dS m⁻¹ EC applied at 2 h intervals. Full article

Background: Type 2 diabetes (T2D) is a major global health concern influenced by sociodemographic and lifestyle factors. This study compared T2D risk scores between commerce and industry sectors and assessed the associations of age, sex, education, physical activity, diet, and smoking with elevated risk. Methods: This cross-sectional study included 56,856 men and 12,872 women employed in the commerce (n = 27,448) and industry (n = 42,280) sectors across Spain. Anthropometric, clinical, and biochemical data were collected. Four validated T2D risk scores (QDscore, Finrisk, Canrisk, and TRAQ-D) were calculated. Multinomial logistic regression models estimated adjusted odds ratios (ORs) for high-risk categories by sociodemographic and lifestyle characteristics. Results: Women in the industrial sector had significantly higher age, BMI, waist circumference, and lipid levels than those in commerce; differences among men were less marked. Across all participants, higher T2D risk scores were independently associated with physical inactivity (OR up to 12.49), poor Mediterranean diet adherence (OR up to 6.62), industrial employment (OR up to 1.98), and older age. Male sex was strongly associated with high Canrisk scores (OR = 6.31; 95% CI: 5.12–7.51). Conclusions: Employment in the industrial sector, combined with sedentary behavior and poor dietary habits, is independently associated with higher predicted T2D risk. Workplace prevention strategies should prioritize multicomponent interventions targeting modifiable risk factors, especially in high-risk subgroups such as older, less-educated, and inactive workers. Full article

Background: Neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD), are genetically complex and often linked to structural genomic variations such as copy number variants (CNVs). Current diagnostic strategies face challenges in interpreting the clinical significance of such variants. Methods: We developed a customized, gene-oriented chromosomal microarray (CMA) targeting 6026 genes relevant to neurodevelopment, aiming to improve diagnostic yield and candidate gene prioritization. A total of 39 patients with unexplained developmental delay, intellectual disability, and/or ASD were analyzed using this custom platform. Systems biology approaches were employed for downstream interpretation, including protein–protein interaction networks, centrality measures, and tissue-specific functional module analysis. Results: Pathogenic or likely pathogenic CNVs were identified in 31% of cases (9/29). Network analyses revealed candidate genes with key topological properties, including central “hubs” (e.g., NPEPPS, PSMG1, DOCK8) and regulatory “bottlenecks” (e.g., SLC15A4, GLT1D1, TMEM132C). Tissue- and cell-type-specific network modeling demonstrated widespread gene involvement in both prenatal and postnatal developmental modules, with glial and astrocytic networks showing notable enrichment. Several novel CNV regions with high pathogenic potential were identified and linked to neurodevelopmental phenotypes in individual patient cases. Conclusions: Customized CMA offers enhanced detection of clinically relevant CNVs and provides a framework for prioritizing novel candidate genes based on biological network integration. This approach improves diagnostic accuracy in NDDs and identifies new targets for future functional and translational studies, highlighting the importance of glial involvement and immune-related pathways in neurodevelopmental pathology. Full article

Due to its superior maneuverability and concealment, the micro flapping-wing aircraft has great application prospects in both military and civilian fields. However, the development and optimization of lightweight materials have always been the key factors limiting performance enhancement. This paper designs the flapping mechanism of a single-degree-of-freedom miniature flapping wing aircraft. In this study, T800 carbon fiber composite material was used as the frame material. Three typical wing membrane materials, namely polyethylene terephthalate (PET), polyimide (PI), and non-woven kite fabric, were selected for comparative analysis. Three flapping wing configurations with different stiffness were proposed. These wings adopted carbon fiber composite material frames. The wing membrane material is bonded to the frame through a coating. Inspired by bionics, a flapping wing that mimics the membrane vein structure of insect wings is designed. By changing the type of membrane material and the distribution of carbon fiber composite materials on the wing, the stiffness of the flapping wing can be controlled, thereby affecting the mechanical properties of the flapping wing aircraft. The modal analysis of the flapping-wing structure was conducted using the finite element analysis method, and the experimental prototype was fabricated by using 3D printing technology. To evaluate the influence of different wing membrane materials on lift performance, a high-precision force measurement experimental platform was built, systematic tests were carried out, and the lift characteristics under different flapping frequencies were analyzed. Through computational modeling and experiments, it has been proven that under the same flapping wing frequency, the T800 carbon fiber composite material frame can significantly improve the stiffness and durability of the flapping wing. In addition, the selection of wing membrane materials has a significant impact on lift performance. Among the test materials, the PET wing film demonstrated excellent stability and lift performance under high-frequency conditions. This research provides crucial experimental evidence for the optimal selection of wing membrane materials for micro flapping-wing aircraft, verifies the application potential of T800 carbon fiber composite materials in micro flapping-wing aircraft, and opens up new avenues for the application of advanced composite materials in high-performance micro flapping-wing aircraft. Full article

Background: Limited data are available regarding the mechanical performance of 3D-printed fixed partial dentures (FPDs) fabricated from different materials and connector geometries. The purpose of this in vitro study was to evaluate the influence of connector size and material type on the fracture resistance of three-unit posterior FPDs fabricated with two commercially available 3D-printable dental resins. Methods: A standardized metal model with two cylindrical abutments was used to design three-unit FPDs. A total of sixty samples were produced, considering three connector sizes (3 × 3 mm, 4 × 4 mm, and 5 × 5 mm) and two different resins: Temp Print (GC Corp., Tokyo, Japan) and V-Print c&b temp (Voco GmbH, Cuxhaven, Germany) (n = 10). Specimens were fabricated with a DLP printer (Asiga MAX UV), post-processed per manufacturer recommendations, and tested for fracture resistance under occlusal loading using a universal testing machine. Data were analyzed using nonparametric tests (Mann–Whitney U and Kruskal–Wallis; α = 0.05). Results: Significant differences were found between material and connector size groups (p < 0.001). Temp Print (GC Corp., Tokyo, Japan) demonstrated higher mean fracture loads (792.34 ± 578.36 N) compared to V-Print c&b temp (Voco GmbH, Cuxhaven, Germany) (359.74 ± 131.64 N), with statistically significant differences at 4 × 4 and 5 × 5 mm connectors. Fracture strength proportionally increased with connector size. FPDs with 5 × 5 mm connectors showed the highest resistance, reaching values above 1500 N. Conclusions: Both connector geometry and material composition significantly affected the fracture resistance of 3D-printed FPDs. Larger connector dimensions and the use of Temp Print (GC Corp., Tokyo, Japan) resin enhanced mechanical performance. Full article

A novel type of multifunctional hybrid membranes combining modified chitosan, functionalized multi-walled carbon nanotubes (MWCNTs), and rare earth element ion-imprinted polymers (REEIIPs) were designed and characterized. The synthesized materials were characterized by thermogravimetric analysis (TGA), scanning electron microscopy (SEM), vibrating sample magnetometry (VSM), X-ray diffraction (XRD), X-ray micro-tomography, and Fourier transform infrared spectroscopy (FTIR). The hybrid membranes were also studied in terms of their mechanical and rheological properties. The key element of the proper preparation of hybrid membranes using the casting method in an external magnetic field was to synthesize membrane components with appropriate magnetic properties. It was found that they showed tunable weak ferromagnetic properties, and the increase in modified nanotube addition caused the rise in the membrane’s saturation magnetization, which for Nd-selective hybrid membranes reached 0.44 emu/g. Also, the increase in thermooxidative stability was noted after introducing functionalized nanotubes into polymer matrices, which, in the case of Gd-selective membranes, were stable even up to 730 °C. The rise in the modified MWCNT addition and selection of appropriate REE ion-imprinted polymers improved mechanical (Rm and E values increase even twice) and rheological parameters (almost double growth of E′ and E″ values) of the tested membranes. Synthesized hybrid membranes showed a high rejection of matrix components and an increase in retention ratio with rising MWCNT-REEIIP addition, ultimately reaching 94.35%, 92.12%, and 90.11% for Nd, Pr, and Gd, respectively. The performed analysis confirmed homogeneous dispersion, phase compatibility, network integration, formation of a complex 3D microstructure, and improved operational stability of created hybrid membranes, which is significant for their future applications in Nd, Pr, and Gd recovery from coal fly ash extracts. Full article

In this paper, we delve into the following nonlinear fractional Kirchhoff-type problem ${(a+b||(-\Delta )}^{{\displaystyle \frac{s}{2}}}{u\left|\right|}_2^2{)(-\Delta )}^{s}u+\lambda u=g\left(u\right)+{\left|u\right|}^{2_s^{*}-2}u$ in ${\mathbb{R}}^3$ with prescribed mass ${\int }_{{\mathbb{R}}^3}{\left|u\right|}^{2}dx=\rho >0,$ where $s\in ({\displaystyle \frac{3}{4}},1),\lambda \in \mathbb{R},2_s^{*}={\displaystyle \frac{6}{3-2s}}$. Under some general growth assumptions imposed on g, we employ minimization of the energy functional on the linear combination of Nehari and Poho$\breve{z}$aev constraints intersected with the closed ball in the $L^2\left({\mathbb{R}}^3\right)$ of radius $\rho$ to prove the existence of normalized ground state solutions to the equation. Moreover, we provide a detailed description for the asymptotic behavior of the ground state energy map. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver condition globally, strongly linked to obesity, insulin resistance, and type 2 diabetes (T2D). Tirzepatide (TZP), a dual GIP/GLP-1 receptor agonist, improves glycemic control and reduces body weight and the liver fat content in patients with obesity and T2D. However, its effect on liver-specific outcomes such as steatosis and fibrosis remains incompletely characterized. Low-energy ketogenic therapy (LEKT), a nutritional strategy characterized by carbohydrate restriction and nutritional ketosis, may enhance hepatic β-oxidation and reduce hepatic lipogenesis. To date, however, the combination of TZP and LEKT has not been studied in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). This study aimed to compare the hepatic and metabolic effects of TZP combined with either LEKT or a conventional low-calorie diet (LCD) over a 12-week period. Methods: Sixty adult patients with MASLD undergoing TZP therapy were prospectively assigned to either an LEKT or a conventional LCD, with 30 participants per group. As primary endpoints, the controlled attenuation parameter (CAP, an index of hepatic steatosis) and liver stiffness measurement (LSM, an index of liver fibrosis) were assessed at the baseline and after 12 weeks using FibroScan^®. Secondary outcomes included changes in body mass index (BMI), glycated hemoglobin (HbA1c), and liver enzymes. Adherence to both diet and pharmacological treatment, as well as tolerability, were systematically monitored throughout the intervention period. Results: Both groups showed significant reductions in body weight (TZP + LEKT, p = 0.0289; TZP + LCD, p = 0.0278), with no significant intergroup difference (p = 0.665). CAP and LSM improved significantly in both groups, but reductions were greater in the TZP + LEKT group (CAP −12.5%, p < 0.001; LSM −22.7%, p < 0.001) versus LCD (CAP −6.7%, p = 0.014; LSM −9.2%, p = 0.022). Between-group differences were statistically significant for both CAP (p = 0.01) and LSM (p = 0.03). Conclusions: Based on these preliminary findings, we support the hypothesis that the combination of TZP and LEKT may be superior to TZP with an LCD in reducing hepatic steatosis and stiffness in individuals with obesity. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

In this paper, the first demonstration of a highly strained In_0.8Ga_0.2As/In_0.2Ga_0.8Sb type-II superlattice structure grown on InAs substrates by molecular beam epitaxy (MBE) for long-wavelength infrared detection was reported. Novel methodologies were developed to optimize the As and Sb flux growth conditions. The quality of the epitaxial layer was characterized using multiple analytical techniques, including differential interference contrast microscopy, atomic force microscopy, high-resolution X-ray diffraction, and high-resolution transmission electron microscopy. The high-quality superlattice structure, with a total thickness of 1.5 μm, exhibited exceptional surface morphology with a root-mean-square roughness of 0.141 nm over a 5 × 5 μm² area. Single-element devices with PIN architecture were fabricated and characterized. At 77 K, these devices demonstrated a 50% cutoff wavelength of approximately 12.1 μm. The long-wavelength infrared PIN devices exhibited promising performance metrics, including a dark current density of 7.96 × 10⁻² A/cm² at −50 mV bias and a high peak responsivity of 4.90 A/W under zero bias conditions, both measured at 77 K. Furthermore, the devices achieved a high peak quantum efficiency of 65% and a specific detectivity (D*) of 2.74 × 10¹⁰ cm·Hz^1/2/W at the peak responsivity wavelength of 10.7 µm. These results demonstrate the viability of this material system for long-wavelength infrared detection applications. Full article

Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. In this paper, image data augmentation was performed using generative adversarial networks and diffusion models, generating images of monitoring areas under different environmental conditions and FOD images of varied types. Additionally, a three-stage image blending method considering size transformation, a seamless process, and style transfer was proposed. The image quality of different blending methods was quantitatively evaluated using metrics such as structural similarity index and peak signal-to-noise ratio, as well as Depthanything. Finally, object detection models with a similarity distance strategy (SimD), including Faster R-CNN, YOLOv8, and YOLOv11, were tested on the dataset. The experimental results demonstrated that realistic FOD data were effectively generated. The Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) of the synthesized image by the proposed three-stage image blending method outperformed the other methods, reaching 0.99 and 45 dB. YOLOv11 with SimD trained on the augmented dataset achieved the mAP of 86.95%. Based on the results, it could be concluded that both data augmentation and SimD significantly improved the accuracy of FOD detection. Full article