Objective: Cardiovascular diseases (CVDs), particularly coronary artery disease (CAD) and heart failure (HF), are leading causes of global mortality. Small-molecule metabolites serve as promising biomarkers for CAD and HF management, yet their low abundance in complex biological matrices poses significant detection challenges. Laser desorption/ionization mass spectrometry (LDI-MS) is a powerful analytical tool, but conventional organic matrices suffer from strong background interference and poor reproducibility. This review systematically summarizes recent advances in metal-based nanomaterials as alternative LDI-MS matrices for small-molecule biomarker detection in CAD and HF, focusing on composition and structural design strategies.

Methods: The authors reviewed and classified metal-based nanomaterials by composition (single-component systems including noble metals and metal oxides; multi-component systems including noble metal-based, metal oxide-based, and MOF-based composites) and structural design (size/morphology control, porous, core-shell, and other structures). Enhancement mechanisms and analytical performance were analyzed, and clinical applications in CAD (stable CAD, acute coronary syndrome, and myocardial infarction) and HF were reviewed.

Results: Compositional engineering enables synergistic effects including localized surface plasmon resonance, enhanced photothermal conversion, efficient charge transfer, and selective analyte enrichment. Structural design optimizes electromagnetic field distribution and provides abundant active sites. In clinical applications, nanomaterial-assisted LDI-MS combined with machine learning achieves excellent diagnostic performance for CAD and HF, including stable CAD screening, ACS subtyping, MI classification, and HF differentiation.

Conclusions: Metal-based nanomaterials significantly enhance LDI-MS performance for metabolite detection through rational design. The technology shows promise for cardiovascular metabolic profiling, but challenges remain regarding fundamental mechanisms, complex synthesis, and clinical translation. Standardized protocols, multicenter validation, and interdisciplinary collaboration are needed to advance clinical implementation.

A novel interfacial engineering strategy for 3D-printed metal-cermet composites is provided, effectively suppressing sintering-induced cracking, and opens a promising pathway for manufacturing robust components for extreme environments.

Researchers from Donghua University and Yanshan University have developed an enhanced neural network called EF-YOLO, which significantly improves the automated detection of colorectal polyps—a key precursor to colorectal cancer. By integrating advanced modules such as transformer, deformable convolution, coordinate attention, and a newly designed multi-scale aggregation mechanism, the model achieves a mean average precision (mAP) of 96.60% on standard medical datasets. This represents a major step forward in reducing missed detections during colonoscopy and supporting early clinical intervention.

Researchers from Donghua University, in collaboration with ANTA Sports Products Ltd., have developed a one-step ultraviolet (UV) irradiation technology to significantly improve the thermal stability and hydrophilicity of medium molecular weight polyethylene (PE) fibers. By integrating crosslinking and grafting modifications using a cost-effective photoinitiator system and acrylic acid (AA) as a grafting monomer, the modified fibers exhibit excellent morphological integrity and mechanical performance at elevated temperatures (130–150 °C), while the water contact angle dramatically decreases from 105.0° (hydrophobic) to 48.4° (hydrophilic). This innovation offers a practical and scalable solution for expanding the application of PE fibers in high-temperature and dyeable textile production.

Triggering the anionic redox reactions at high voltage is an effective approach to boost the capacity of Li-rich layered oxides. However, the irreversible lattice oxygen release at high voltage and sluggish ion kinetics remain conundrums. Herein, a surface modifying coupling defect engineering strategy is proposed to improve the reversibility of anionic redox reactions and ion diffusion efficiency in Li-rich layered oxides. A LiNbO3 surface modification acts as an effective physical barrier to suppresses lattice oxygen release, thereby improving cycling stability of Li-rich layered oxide. Further, the oxygen vacancies in the LiNbO3 coating enhances the ion transport kinetics, strengthening rate capability. After 500 cycles, a high capacity retention of 83.3% can be achieved for the obtained cathode materials (CV-LLO) at 5 C, much higher than that of the pristine materials (LLO, 52.3%). Moreover, CV-LLO delivers a capacity of 169.9 mAh g-1 at 5 C, which was 65.1% of the capacity at 0.2 C, much higher than that of the pristine LLO (85.6 mAh g-1, 33.7%). This study provides insights into the construction of Li-rich layered oxide cathode with highly reversible anionic redox reaction and highly cycling stability for Lithium storage.