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关键词： Gastric cancer   Rhizoma Paridis   Machine learning   Mechanisms of action   Experimental validation   CAM   Complementary and alternative medicine   CNKI   China national knowledge infrastructure   D-C   Drug-compound   C-T-F   Compound–target–function   DEGs   Differentially expressed genes   GC   GEO   Gene expression omnibus   GO   Gene ontology   KEGG   Kyoto encyclopedia of genes and genomes   MD   Molecular dynamics   ML   NLP   Natural language processing   PPI   Protein–protein interaction   RF   Random forest   RPS   SVM   Support vector machine   TCMSP   Traditional Chinese medicine systems pharmacology   TCM   Traditional Chinese medicine   TIICs   Tumor-infiltrating immune cells   TIMER   Tumor immune estimation resource   t-SNE   t-distributed stochastic neighbor embedding   TISCH   Tumor immune single cell hub   UMAP   Uniform manifold approximation and projection   LC-MS   Liquid chromatography-mass spectrometry technology   UPLC   Ultra-performance liquid chromatography  

摘要： Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, especially in advanced stages with limited treatment efficacy. Rhizoma Paridis (RPS), a traditional Chinese medicinal herb, has shown promising antitumor activity, yet its potential anti-GC mechanisms have not been systematically investigated.

关键词： FAI   Hip pain   Imaging   Arthroscopy  

摘要： To characterize different hip morphology phenotypes in individuals with femoroacetabular impingement (FAI) syndrome with cam morphology.

关键词： Hybrid Additive–Subtractive Manufacturing (HASM)   CNC machining   Polymer machinability   Toolpath planning   CAD-CAM-CNC integration  

摘要： Hybrid additive–subtractive manufacturing (HASM) has emerged as a powerful paradigm for overcoming the intrinsic limitations of standalone additive manufacturing (AM) and subtractive manufacturing (SM) by combining geometric design freedom with the dimensional accuracy and surface quality achievable through CNC machining. Despite significant progress in metal-based hybrid systems, polymer-based HASM remains comparatively underexplored, despite growing industrial demand for high-precision, high-performance polymer components. This review presents a critical and structured analysis of polymer-based HASM from a toolpath-driven and digitally integrated perspective. A systematic literature methodology was employed, screening approximately 210 publications and selecting 114 peer-reviewed studies across seven thematic categories. Particular attention is given to the machinability and surface integrity of engineering polymers including PLA, ABS, PETG, PC, PA, PEEK, photopolymers, and fiber-reinforced composites, along with hybrid toolpath planning, machining allowance management, and CAD–CAM–CNC interoperability. Emerging technologies — artificial intelligence, digital twins, sensor-based monitoring, and adaptive process control — are critically examined as key enablers of next-generation hybrid systems. Based on identified research gaps, a toolpath-driven closed-loop integration framework is proposed, unifying design, additive deposition, subtractive finishing, and real-time feedback within a single cyber-physical manufacturing environment. The findings establish that seamless AM–SM toolpath integration, intelligent process optimization, and standardized quality assessment are the critical enablers for advancing polymer HASM toward industrially scalable, data-driven, and sustainable smart manufacturing.

关键词： Nanotoxicology   Drug delivery systems (DDS)   Advanced in vitro models   Advanced in vivo models   Non-mammalian models   2D   two-dimensional   2,3-Bis-(2-methoxy-4-nitro-5-sulfophenyl)−2H-tetrazolium-5-carboxanilide   XTT   2,4-dinitrophenylhydrazine   DNPH   3-(4,5-dimethylthiazol-2-yl)−2,5-diphenyltetrazolium bromide   MTT assay   AgNPs   silver nanoparticles   AI   artificial intelligence   ALI   air–liquid interface   AuNPs   gold nanoparticles   BBB   blood–brain barrier   CAM   chorioallantoic membrane   CdO-NPs   cadmium oxide nanoparticles   CrO3-NPs   chromium trioxide nanoparticles   Cu-NPs   copper nanoparticles   CuO-NPs   copper oxide nanoparticles   DDS   drug delivery systems   ECM   extracellular matrix   EBB   extrusion-based bioprinting   ESCs   embryonic stem cells   Fe2O3, Fe3O4-NPs   iron oxide nanoparticles   HTS   high-throughput screening   iPSCs   induced pluripotent stem cells   LDH   lactate dehydrogenase   MALIES   modular air–liquid interface exposure system   MCTSs   multicellular tumor spheroids   ML   machine learning   NAMs   new approach methodologies   NEs   nanoemulsions   NPs   nanoparticles   OoC   organ-on-chip   PCTS   precision-cut tissue slices   PD   pharmacodynamic   PE-NPs   polyethylene nanoparticles   PK   pharmacokinetic   PSNPs   polystyrene nanoplastics   QSARs   quantitative structure–activity relationships   QSPRs   quantitative structure–property relationships   SiO2   silica nanoparticles   TiO2-NPs   titanium dioxide nanoparticles   ZnO-NPs   zinc oxide nanoparticles  

摘要： Nanomaterials have been widely used across medical and health sciences due to their unique physicochemical characteristics, versatile functionalisation, and their remarkable capacity to interact with (and often penetrate) biological tissues at the molecular and cellular level. These properties have made nanomaterials particularly attractive for drug delivery systems, improving targeted delivery and therapeutic efficacy. Nevertheless, the same features that make nanomaterials so valuable in biomedical contexts may also give rise to unforeseen biological interactions, including oxidative stress, inflammation, immune responses, and organ accumulation, thereby raising legitimate concerns about their potential toxicological implications.

关键词： 4D printing   Stimuli-responsive materials   Computational intelligence   Biomedical translation   Sustainable manufacturing   4D   Four-Dimensional   3D   Three-Dimensional   ADSC   Adipose-Derived Stem Cell   AI   Artificial Intelligence   ANN   Artificial Neural Network   BEC   Brain Endothelial Cell   BMI   Bismaleimide   BPC   Brain Pericyte   CAM   Continuous Amplitude Modulation   CB   Carbon Black   CBCT   Cone Beam Computed Tomography   CCF   Cell Contractile Forces   CFD   Computational Fluid Dynamics   CI   Computational Intelligence   CNTs   Carbon Nanotubes   CT   Continuous Time   DIW   Direct Ink Writing   DLP   Digital Light Processing   DMD   Digital Micromirror Device   FDM   Fused Deposition Modeling   FEA   Finite Element Analysis   GAN   Generative Adversarial Network   hiPSC   Human Induced Pluripotent Stem Cell   hMSC   Human Mesenchymal Stem Cells   IVC   Inferior Vena Cava   LCEs   Liquid Crystal Elastomers   ML   Machine Learning   MSC   Mesenchymal Stem Cell   MXene   Transition Metal Carbide/Nitride   NIR   Near-Infrared   NPC   Neural Progenitor Cell   PCL   Polycaprolactone   PEG   Polyethylene Glycol   PEVA   Poly(Ethylene-co-Vinyl Acetate)   PGSA-HEMA   Poly(Glycerol Sebacate) Acrylate-co-Hydroxyethyl Methacrylate   PINNs   Physics-Informed Neural Networks   PLA   Polylactic Acid   PM   Pulse Modulation   PNIPAM   Poly(N-Isopropylacrylamide)   R2R   Roll-to-Roll   SMPLA   Shape-Memory Polylactic Acid   SMPs   Shape-Memory Polymers   ST   Segmented Time   TAM   Time-Amplitude Modulation   tBuOH   EA, Tert-Butyl Alcohol, Ethyl Acetate   TPP   Two-Photon Polymerization   VEGF   Vascular Endothelial Growth Factor   VOC   Volatile Organic Compounds   WAAM   Wire-Arc Additive ManufacturingβTCP, Beta-Tricalcium Phosphate  

摘要：

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  4D printing uses time as 4th dimension, enabling adaptive morphologies under stimuli, redefining AM.
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  Stimuli-responsive materials: SMPs, LCEs, hydrogels, ceramics, metals, bioinks – recovery >12 MPa, strain >300%, viability >90%.
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  ML, topology optimization, & surrogate modeling achieve >90% accuracy, >50% cycle reduction, & <7% stiffness error.
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  4D bioprinting enables tissue engineering & implants with >90% cell viability & vascularization within 7 days – translational potential.

关键词： Constructive solid geometry   CAD models   3D generation   Large language models  

摘要：

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  Two-stage CSG framework for interpretable CAD generation from natural language.
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  Structure-aware Transformer with hierarchical supervision and validity loss.
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  Large-scale CSG dataset with paired text for text-driven CAD modeling.

关键词： Mid-surface abstraction   Variable thin-walled models   GPU acceleration  

摘要：

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  End-to-end GPU acceleration for the most critical aspects of Mid-surface abstraction.
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  Full-GPU face pairing with hierarchical culling and fast pruning criteria.
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  Branchless mid-point solver for variable thickness with a bracket-and-bisect kernel.
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  Extensive evaluation of diverse models from different real-world domains.

关键词： Zirconia  

摘要： To evaluate the load-bearing capacity of 3 mol% yttria-stabilized zirconia (3Y-TZP) four-unit fixed dental prostheses (FDPs) fabricated using four different additive manufacturing (AM) workflows representing three different AM technologies compared with subtractive manufacturing (SM), both in a pristine condition (P) and after dynamic loading combined with hydrothermal ageing (L).

关键词： CAD diagram measurement   Complete assembly identification   Electrical element recognition   Graph neural network   Wiring diagram recognition  

摘要： Intelligent recognition of substation building electrical wiring diagrams is a key step to ensure the correctness and safety of substation design and to improve the efficiency of engineering operations. However, existing methods struggle with severe text-graphic interference, extreme scale variations of symbols, and their inability to explicitly model complex, imbalanced topological connections. To solve these challenges, this paper proposes a novel framework for electrical wiring drawing recognition, formulated as a topology-aware graph learning problem. First, we propose a CAD-image fusion strategy that leverages deterministic vector topology to guide visual parsing, effectively suppressing text-graphic interference to extract high-fidelity physical wiring structures. Second, by formalizing heterogeneous devices and their physical connections into a formal graph data structure, we develop a GraphSAGE-based classifier capable of decoding the complex, multi-hop configurations of complete electrical assemblies. Last, to handle unique geometric variations and structural sparsity, domain-tailored optimizations are introduced, including Dynamic Snake Convolution (DSConv) for capturing elongated busbars and a Gated-Attention mechanism to regulate extreme topological imbalance during graph aggregation. Experimental results on real-world 110 kV substation diagrams demonstrate the effectiveness of our framework, achieving 96.4% mAP for element detection, 98.95% edge precision for topology extraction, and 95.47% accuracy for assembly classification.

关键词： Modified compound 511   Nicotine addiction   VTA   PKA   GluN2B   Synaptic plasticity   511   Compound 511   Acq   Acquisition   ADME   Absorption, distribution, metabolism, excretion   Amy   amygdala   Ca2   Calcium ion   CaM   Calmodulin   CaMKII   Calcium/calmodulin-dependent protein kinase II   cAMP   Cyclic adenosine monophosphate   CON   Control group   CPP   Conditioned place preference   CREB   cAMP-response element binding protein   DEG   Differentially expressed gene   GO   Gene ontology   HE   Hematoxylin and eosin   HIP   Hippocampus   IF   Immunofluorescence   KEGG   Kyoto encyclopedia of genes and genomes   LC-MS/MS   Liquid chromatography–tandem mass spectrometry   LTP   Long-term potentiation   M511   MLDS   Mesolimbic dopaminergic system   Nic   Nicotine   nAChRs   Nicotinic acetylcholine receptors   NAc   Nucleus accumbens   NMDAR   N-methyl-D-aspartic acid receptor   OECD   Organisation for economic co-operation and development   PBS   Phosphate-buffered saline   PFA   Paraformaldehyde   Protein kinase A   PPI   Protein-protein interaction   Pre   Precondition   RNA-seq   RNA sequencing   Sal   Saline   SEA   Similarity ensemble approach   SEM   Standard error of the mean   STR   Striatum   STRING   Search tool for the retrieval of interacting genes/proteins   TCM   Traditional Chinese medicine   TCMSP   Traditional chinese medicine systems pharmacology database   TIC   Total ion chromatogram   Var   varenicline   Veh   vehicle   Ventral tegmental area  

摘要：

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  Modified Compound 511 (M511) significantly blocks nicotine-induced conditioned place preference (CPP) and counteracts the associated synaptic plasticity impairment.
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  By integrating network pharmacology, transcriptomics, and behavioral-molecular-morphological strategies, this study systematically elucidated the component-target-mechanism network of M511 for the first time.
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  This study pioneers the identification of the PKA-CREB-GluN2B-CaMKII signaling axis as the core molecular pathway through which M511 intervenes in nicotine addiction.