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关键词： Angiogenesis   CAM   HBD domain   Invasion   NRP1   Proliferation   SEMA3A   VEGF  

摘要： Background: Angiogenesis plays a critical role in tumor development, with neuropilin receptors (NRPs) involved in this process through their interactions with vascular endothelial growth factor (VEGF) and semaphorins. SEMA3A, a member of class 3 semaphorins, demonstrates strong antiangiogenic potential. In this study, the C-terminal basic domain of SEMA3A was replaced with the heparin-binding domain (HBD) of VEGF₁₆₅, hypothesizing that the resultant chimeric protein SEMA-PSI-IG-HBD would enhance antiangiogenic efficacy by: (1) competing with VEGF for NRPs (2) utilizing the HBD as a molecular anchor to increase the residence time and local concentration of the hybrid within the tumor microenvironment. Methods: To assess the effects of SEMA-PSI-IG-HBD on angiogenesis, a series of in vitro assays including microcapillary network formation, 3D cell spheroid sprouting, proliferation and interaction with NRP1 were carried out, whereas in ovo experiments were performed by using the chicken embryo chorioallantoic membrane (CAM) model. Results: Pull-down assays confirmed that the SEMA-PSI-IG-HBD hybrid specifically interacted with secreted NRP1 in a manner similar to the wild-type SEMA3A, validating the structural integrity of the chimeric protein’s receptor-binding interface. SEMA-PSI-IG-HBD and SEMA3A showed comparable inhibition in 2D microcapillary formation and 3D spheroid sprouting assays. However, the hybrid demonstrated markedly superior anti-angiogenic activity in the complex 3D environment of the CAM model. Conclusions: Our findings demonstrate that by combining competitive occupancy of NRP1 with potent anti-angiogenic signaling, SEMA-PSI-IG-HBD represents a promising therapeutic candidate for the regulation of pathological vascularization in cancer. © The Author(s) 2026.

关键词： Aroma quality monitoring   Interpretable CNN   Odor sensor   Tea processing   Visible near-infrared spectroscopy  

摘要： The accurate prediction of the withering degree is essential for ensuring the aroma quality of black tea. In this study, we present an innovative intelligent platform that integrates a carefully designed colorimetric sensor array (CSA) with visible near-infrared (VNIR) spectroscopy, powered by an interpretable deep learning model (convolutional neural network, CNN) to predict withering degrees. Specifically, eight dyes were selected from sixteen candidates based on correlation analysis (R² > 0.36). These dyes were drop-cast onto filter paper to create the CSA, which was used to capture key volatile organic compounds (VOCs) released during the withering of tea leaves. Spectral data from the CSA were collected and modeled to identify the different withering stages. To further enhance model interpretability, gradient-weighted class activation mapping (Grad-CAM) was applied to highlight the spectral regions most relevant to classification. When compared to conventional models, the Grad-CAM-CNN demonstrated superior performance, achieving 99% accuracy and a computational efficiency of 0.0559 s/100 samples. This approach not only ensures the aroma quality of black tea but also provides an efficient, scalable, and cost-effective solution for real-time process control in tea manufacturing, with potential for adaptation to other food systems.

摘要： Weakly Supervised Semantic Segmentation (WSSS) remains highly challenging because image-level supervision typically produces class activation maps (CAMs) that are incomplete or noisy when used as pixel-level pseudo-labels. Despite the architectural efficiency of one-stage approaches, they are often hindered by tight encoder-label coupling: CAMs and segmentation predictions are derived from the same encoder and optimized jointly, leading to the propagation and reinforcement of initial CAM inaccuracies by the segmentation outputs. To circumvent this limitation, we propose SynerNet, a one-stage dual-branch framework that explicitly mandates complementary yet synergistic objectives: one branch generates broad pseudo-labels to enhance coverage, while the other produces precise pseudo-labels to sharpen localization. With such pseudo-labels, the segmentation network yields simultaneously comprehensive and accurate predictions. The broad branch (B-CAM) leverages global attention to expand foreground coverage by guiding ambiguous regions toward likely foreground, whereas the precise branch (P-CAM) emphasizes fine localization by encouraging unreliable pixels toward the background. Through cross-supervision, the two branches effectively decouple the optimization process, alleviating the risk of error reinforcement inherent in direct coupling. To further integrate their strengths, we introduce a confidence matrix derived from multi-scale ViT features, in which pixels consistently classified across layers are treated as high-confidence, while inconsistent ones are marked as uncertain. This enables a confidence-guided fusion strategy that directly adopts reliable predictions and adaptively blends uncertain regions using contributions from both branches. Such a complementary design mitigates error reinforcement and promotes mutually beneficial learning, enabling the network to generate high-fidelity pseudo-labels in a fully end-t

关键词： Subperiosteal implant   CAD/CAM   Digital workflow   Atrophic maxilla   Peri-implantitis   Oral rehabilitation  

摘要： This case report describes the digital workflow and clinical outcomes of a customized CAD/CAM-assisted subperiosteal implant (SPI) used for the rehabilitation of a severely atrophic maxilla. A 53-year-old female patient presented with advanced peri-implantitis affecting multiple maxillary implants. After implant removal and a healing period, a patient-specific titanium SPI was designed and fabricated using cone-beam computed tomography and CAD/CAM technology. The implant was installed under conscious sedation, supporting a provisional prosthesis, followed by a definitive titanium–composite hybrid restoration. The digital workflow allowed precise adaptation of the implant to the patient’s anatomy, minimizing surgical morbidity and eliminating the need for bone grafting.. This case suggests that a customized CAD/CAM-assisted subperiosteal implant (SPI) may represent a feasible treatment alternative in a single-case salvage scenario, achieving favorable aesthetic and functional outcomes in a severely atrophic maxilla where rehabilitation with conventional endosseous implants is not feasible.

摘要： Skin cancer remains one of the most prevalent and potentially fatal diseases worldwide, emphasizing the need for early and reliable detection. This paper presents an explainable and lightweight convolutional neural network (CNN) model for automatic skin-lesion classification using the HAM10000 dataset. Unlike previous studies that relied on cloud computing or focused on binary melanoma detection, the proposed framework performs real-time, multi-class lesion analysis entirely on-device. The CNN model was optimized through TensorFlow Lite to achieve efficient, privacy-preserving inference on mobile platforms.

关键词： Digital forensics   Anthropometry   Computed tomography   Odontology   Skull-to-face   Reconstruction   Facial approximation   Age reversal  

摘要： This study presents a detailed protocol for reconstructing a realistic youthful face from the skull of an elderly individual, based on Computed Tomography (CT) scans. The methodology addresses critical age-related changes, including mandibular displacement, tooth loss, and the degradation of supporting bone structures. The soft tissue reconstruction adheres to current forensic anthropology standards, utilizing average soft tissue thickness measurements at key landmarks. These measurements are derived from statistical analyses of large datasets that consider factors like ethnicity, age, and Body Mass Index (BMI) to ensure accuracy. Computational workflow integrates open-source facial modeling software with advanced Computer-Aided Design (CAD) techniques typically used in prosthetic dentistry. This approach allows for the functional repositioning of the mandible and the digital reconstruction of missing dentoalveolar structures. The research relies on existing anthropometric databases, with additional soft tissue data sourced from the FACEBASE 3D database to fill any informational gaps. The effectiveness of this developed methodology was demonstrated through a case study: the forensic facial approximation of the youthful appearance of Blessed Giacomo Illirico of Bitetto, who died in 1496. This application served as a real-world test of the protocol's ability to scientifically reverse the effects of aging on facial structure, providing a scientifically grounded visualization of his younger self.

摘要： Accurate and timely cancer diagnosis from histopathological slides is vital for effective clinical decision-making. This paper introduces DepViT-CAD, a deployable AI system for multi-class cancer diagnosis in histopathology. At its core is MAViT, a new Multi-Attention Vision Transformer designed to capture fine-grained morphological patterns across diverse tumor types. MAViT was trained and evaluated on expert-annotated patches from 1283 Whole-Slide Images (comprising 1008 training cases, 139 validation cases, and 275 test cases), covering 11 diagnostic categories, including 10 major cancers and non-tumor tissue. DepViT-CAD was indeed validated on two independent test cohorts: 275 WSIs from The Cancer Genome Atlas and 50 routine clinical cases from pathology labs, achieving diagnostic sensitivities of 94.11% and 92%, respectively. By combining state-of-the-art transformer architecture with large-scale real-world validation, DepViT-CAD offers a robust and scalable approach for AI-assisted cancer diagnostics. To support transparency and reproducibility, software and code will be made publicly available at GitHub.

关键词： Dental materials   Chairside   CAD/CAM   Glass ceramics   Zirconia  

摘要： Chairside CAD/CAM technology enables the fabrication of permanent fixed restorations during a single clinical visit, eliminating the necessary for temporary restorations and multiple appointments. This technology is widely applied in dental restorations, including inlays, onlays, veneers, crowns, and fixed dental prostheses (FDPs). However, reducing treatment time without compromising mechanical and aesthetic properties remains an unresolved dilemma. Given minimally invasive dentistry requirements, the contemporary dental market provides clinicians with an extensive array of chairside CAD/CAM ceramic material options, presenting significant challenges in selecting the most clinically appropriate restorative materials. The main classifications of chairside CAD/CAM materials include feldspathic ceramics, leucite-reinforced ceramics, lithium disilicate ceramics, zirconia-reinforced lithium silicates, resin nanoceramics, polymer-infiltrated ceramic-network and zirconia. Glass ceramics offer excellent aesthetics and high adhesive bond strength, although their mechanical properties require further enhancement. Polycrystalline ceramics exhibit exceptional mechanical performance, while their rapid sintering techniques necessitate further development to optimize processing efficiency. Resin-based ceramics provide clinical advantages in adjustability and reduced antagonist wear, yet their application scope remains limited in restorative dentistry. The aim of this narrative review is to provide an up-to-date overview of chairside CAD/CAM materials used in restorative dentistry, focusing on their classification, mechanical and aesthetic properties, as well as advantages and limitations for different clinical applications.

关键词： Hydraulic motor   Lubrication   Micro-geometric design   Service life  

摘要： The cam-lobe hydraulic motors, as the core actuating components, determine the service life of heavy-duty equipment. Their multiple cam roller-cam ring pairs have become prone to failure with the upgrading of operating pressure level, in which the cam rollers with a 3 cm length will be subjected to an additional force of 1.4 tons. However, traditional cam roller design is difficult to adapt to heavy-load and even alternating conditions caused by the multi-lobe cam ring. For that, this paper proposes the cam roller micro-geometric design integrating full-cycle alternating characteristics, which can homogenize and minimize deformation and pressure distributions of the cam roller-cam ring pair, especially under heavy loads, thereby improving the lifespan of the motor. Specifically, a thermal elastohydrodynamic lubrication model (TEHL) incorporating micro surface morphology is established to obtain pressure and deformation distribution of the cam roller-cam ring pair. On the basis of the results from the TEHL model, a multi-strategy adaptive hybrid optimization (MAHO) algorithm is developed to robustly design the micro-geometric shape of the cam roller, thereby coping with both alternating states in a full cycle and machining error. The designed cam roller achieves a reduction in peak pressure of 24.8–28.3% and increases fatigue life by 17.3–27.8 times theoretically. The actual bench tests of the motors demonstrate that the designed cam roller achieves a service life of 1030 h under high-pressure conditions, representing a 19.4-fold improvement over the original design. Furthermore, the failure mode shifts from “simultaneous rapid damage of cam rollers and cam ring” to “gradual cam ring fatigue preceding cam roller failure”. This study significantly enhances the service life of cam-lobe hydraulic motors under high-pressure conditions, laying a critical technical foundation for the long-term durability and high power density of heavy-duty equipment.