文献类型：期刊文献

英文题名：Machine learning-guided design of cooperative multi-size hydrogel microspheres for osteoarthritis therapy

作者：Chen, Xinye[1,3];Yu, Yuanman[1,2];He, Zirui[3];Pan, Lina[2];Wang, Jing[1,3];Liu, Changsheng[2,3]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Ultrafine Mat, Minist Educ, Shanghai 200237, Peoples R China;[3]East China Univ Sci & Technol, Frontiers Sci Ctr Materiobiol & Dynam Chem, Shanghai 200237, Peoples R China

年份：2027

卷号：336

外文期刊名：BIOMATERIALS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001821308000001)】；

基金：This study was supported by the Key Program of the National Natural Science Foundation of China (No. 32230059), the Excellence Research Group Program of National Natural Science Foundation of China (No. T2288102), the National Natural Science Foundation of China (No. 32471406, No. 82472161, and No. 32101086), the Foundation of Frontiers Science Center for Materiobiology and Dynamic Chemistry (No. JKVD1211002), and Key Research and Development Plan of Shandong Province (2023CXPT103), and the Wego Project of Chinese Academy of Sciences (No. (2020) 005), the Foundation of National Center for Translational Medicine (Shanghai) SHU Branch (No. SUITM-202401, No. SUITM-202502).

语种：英文

外文关键词：Osteoarthritis; Hydrogel microsphere; Machine learning

摘要：Osteoarthritis (OA) is a multifactorial joint disease propelled by interrelated pathological processes including synovial inflammation, failure of joint lubrication, and impaired cartilage regeneration. Hydrogel microspheres have demonstrated potential in the treatment of OA. However, previous studies primarily concentrated on the functionalization of hydrogel microspheres, while overlooking the influence of size effects on OA repair. Considering the intricate multicellular characteristic of the joint microenvironment, the regulatory function of particle size on biological responses differs, thus making a quantitative design strategy necessary. Here, we present a size-engineered and machine learning (ML)-guided strategy for OA therapy based on cooperatively engineered multi-size HA hydrogel microspheres. We further elucidate the relationships between microsphere size and their corresponding biological functions. In vitro and in vivo results revealed clear functional specialization: small microspheres enhanced interfacial lubrication, medium-sized microspheres exhibited optimal immunomodulatory activity, and large microspheres preferentially supported chondrocyte proliferation and extracellular matrix (ECM) production. To quantitatively optimize their cooperative effects, a deep kernel learning Gaussian process (DKL-GP) model was employed for Bayesian optimization of microsphere composition. The ML-optimized formulation significantly outperformed uniform-ratio mixtures and single-size controls in vivo, promoting cartilage protection and favorable immune microenvironment remodeling. Collectively, this work establishes a size-engineered hydrogel microsphere platform for OA therapy and introduces a generalizable paradigm for designing injectable biomaterials tailored to multiscale degenerative diseases.