Di Huang

The development of PVA hydrogels for cartilage repair is limited by the challenge of simultaneously combining high mechanical strength with high water content. To address this, a “Dual‐Stage Temperature‐Controlled Crystallization Quenching Method” is proposed. The approach precisely regulates crystallization kinetics, enabling meticulous control over the gel network topology. The obtained hydrogel achieves a water content of 83.41% ± 0.51%, a tensile strength of 2.68 ± 0.14 MPa, and a compressive modulus of 0.53 ± 0.02 MPa, exceeding machine learning‐predicted thresholds for each property by over 300%. This performance is attributed to a uniform, isotropic network of refined crystallites, as revealed by multiscale analysis, which facilitates homogeneous stress distribution and efficient energy dissipation. Furthermore, the hydrogel possesses a low friction coefficient, biomimetic porosity, and excellent chondrocyte compatibility. This work provides an advanced cartilage repair material and establishes a novel thermodynamic paradigm for polymer gel design through crystallization kinetics regulation.

Osteochondral repair remains a critical challenge owing to conventional scaffolds’ inadequate dynamic mechanical adaptability, poor interfacial integration, inefficient cell recruitment, and lack of spatiotemporal regulation of bioactive cues. Inspired by native tissue hierarchical gradients and endogenous healing mechanisms, we developed an electric field‐driven continuous gradient hydrogel (GHZF4) via spatiotemporal programming. Integrating nanofiber‐reinforced self‐adaptive matrix, electric field‐induced nanofiber alignment, and ZIF‐8 nanocarrier‐mediated bioactive release, GHZF4 constructs compositional/structural/mechanical gradients. Its bone‐mimetic zone achieves burst release of PDGF‐BB and sustained release of BMP‐2 for vascularized osteogenesis, while the cartilage‐mimetic zone sustains TGF‐β3 release for chondrogenesis. In vitro, GHZF4 enhances macrophage M2 polarization, autologous stem cell recruitment, angiogenesis, and osteochondral differentiation. In rat/rabbit defect models, it enables seamless integration and functional repair, validated by micro‐CT, nanoindentation and histology. Transcriptomic analysis reveals the potential upregulation of signaling pathways associated with immunomodulation, angiogenesis, and osteochondral differentiation, which shows strong consistency with our in vitro functional outcomes and in vivo regenerative phenotypes. This nanofunctionalized gradient scaffold spatiotemporally couples key repair processes, providing a promising proof‐of‐concept strategy for cell‐free functional osteochondral repair.

Reliable in vitro liver models are indispensable for researching liver diseases and developing medications. Present 2D/3D cell cultures and animal models inadequately replicate the intricacy of living systems and in vivo conditions, resulting in impaired cellular functions. They also fail to emulate tissue‐like architectures, which undermines their precision. Meanwhile, animal models present species differences, making real‐time observation of dynamic results inconvenient and raising serious ethical concerns. Therefore, there is an urgent need to develop alternative tissue models with biomimetic human pathophysiology to bridge the gap between clinical trials and traditional human and animal models. Liver‐on‐a‐chip (LOC) technology, based on microfluidics, is an innovative in vitro modeling device that can replicate the microstructures and tissue‐tissue interfaces of specific liver functional units, simulating organ and tissue‐level physiological activities. This review summarizes recent strategies and breakthroughs in LOC technologies, from biomimetic tissues and extracellular matrix construction in liver microphysiological systems to diverse LOC development approaches. Furthermore, we highlight key advances in functional LOC platforms, including 3D bioprinting, vascularization strategies, and the incorporation of liver buds and organoids to enhance physiological relevance. The integration of deep learning and sensor technologies for intelligent, real‐time monitoring is also discussed. Finally, we examine LOC applications in drug screening and disease modeling, assess challenges in clinical translation, and offer perspectives on future directions in biomedical research and personalized medicine.