Septic arthritis is a severe disease that damages articular cartilage and triggers a strong inflammatory response. Current treatments mainly depend on systemic antibiotics and lack effective intra-articular therapies, as well as standardized animal models, and precise detection methods. In this study, we present a drug delivery system responsive to the bacterial microenvironment for targeted inflammation control, along with an effective method for monitoring changes in septic arthritis in SD rats. This system consists a core with pH-sensitive metal-organic frameworks ZIF-8 loading anti-inflammatory drugs indomethacin and a shell with hybrid cell membranes from macrophages (MM) and platelets (PM), refer as MP@ZIF-8@IN. This system, which diverges from traditional treatments, enhances drug utilization, prolongs local retention, and allows for spontaneous release at the treatment site, thereby enabling the exclusive intra-articular treatment of septic arthritis. The drug delivery system inhibits the NF-κB pathway, reduces oxidative stress, and regulates macrophage polarization, preventing cartilage destruction. Additionally, in this standardized animal model utilizing the knee joints of SD rats, we have developed musculoskeletal ultrasound and magnetic resonance imaging for time-based monitoring, thus overcoming the limitation of conventional methods, which are unsuitable for soft tissue analysis. Our findings advance therapeutic strategies for septic arthritis and encourage further application of visualization techniques in related fields. STATEMENT OF SIGNIFICANCE: This study presents significant advancements in the treatment and understanding of septic arthritis. Our customized drug delivery system targets bacteria and macrophages, ensuring long-time drug retention and enhanced inflammation control, all while reducing reliance on antibiotics-an important step toward addressing antibiotic resistance. Additionally, we have refined septic arthritis animal models to establish clearer guidelines for intervention timing, grounded in clinical symptoms and imaging data. This addresses a critical gap in current research and offers a practical framework for future therapeutic approaches.
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