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Multimodal Mechano-adaptive Artificial Synovial Fluid Drives In-Situ Engineering of Anti-Pyroptotic Extracellular Vesicles to Arrest Preclinical Osteoarthritis

GSE314982 Mus musculus Expression profiling by high throughput sequencing 6 samples Submitted 2026/08/04 Platform GPL24247
Summary
Effective early interventions for knee protection in exercise enthusiasts and pre-clinical symptomatic knee osteoarthritis (OA) patients are lacking. Abnormal mechanical loading initiates a dual pyroptotic loop between chondrocytes and macrophages, converting healthy cartilage to pathology. Herein, we engineered a multifunctional artificial synovial fluid, pPBA@MN UM6@Co (PMUC), to deliver graded protection and repair of early pathogenetic cartilage. Intra articular PMUC builds a persistent hydration layer via water bonding, mimicking native synovial fluid, markedly enhancing lubrication and dissipating mechanical stress. When abnormal stress provokes ultra early cartilage lesions, the ensuing ROS (·OH) surge cleaves boronate esters and glycosidic bonds in PMUC, releasing mannose (Man) and UM6@Co (UC) nanocomplexes. Activation of the hexosamine biosynthetic pathway (HBP) suppresses Caspase-3–GSDME-mediated pyroptosis in chondrocytes while promoting in situ formation and engineering of extracellular vesicle (EV) derived from resident and synovial macrophages. These EVs, functioning as intercellular messengers within the articular cavity, collectively disrupt the chondrocyte-macrophage pyroptosis loop and facilitate matrix regeneration. In high-load exercise and early OA rat models, PMUC prevented further erosion and healed existing defects, achieving full cartilage regeneration and restored locomotor performance within eight weeks. By coupling adaptive lubrication with stress triggered immune-metabolic modulation, PMUC offers the first stage specific strategy that simultaneously protects healthy joints and repairs silent OA, filling a critical clinical gap for exercise enthusiasts and early-stage patients.
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Also filed as BioProject PRJNA1394182 and SRA study SRP658109. Searching any of these in the dataset finder brings you back here.

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