Li Mengmeng, Zhao Peizhang, Wang Jingwen, Zhang Xincai, Li Jun
Orthopedic Research Institute, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China.
Trauma Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China.
Mater Horiz. 2025 Jan 2;12(1):20-36. doi: 10.1039/d4mh01124d.
Infection is the most prevalent complication of fractures, particularly in open fractures, and often leads to severe consequences. The emergence of bacterial resistance has significantly exacerbated the burden of infection in clinical practice, making infection control a significant treatment challenge for infectious bone defects. The implantation of a structural stent is necessary to treat large bone defects despite the increased risk of infection. Therefore, there is a need for the development of novel antibacterial therapies. The advancement in antibacterial biomaterials and new antimicrobial drugs offers fresh perspectives on antibacterial treatment. Although antimicrobial 3D scaffolds are currently under intense research focus, relying solely on material properties or antibiotic action remains insufficient. Antimicrobial peptides (AMPs) are one of the most promising new antibacterial therapy approaches. This review discusses the underlying mechanisms behind infectious bone defects and presents research findings on antimicrobial peptides, specifically emphasizing their mechanisms and optimization strategies. We also explore the potential prospects of utilizing antimicrobial peptides in treating infectious bone defects. Furthermore, we propose that artificial intelligence (AI) algorithms can be utilized for predicting the pharmacokinetic properties of AMPs, including absorption, distribution, metabolism, and excretion, and by combining information from genomics, proteomics, metabolomics, and clinical studies with computational models driven by machine learning algorithms, scientists can gain a comprehensive understanding of AMPs' mechanisms of action, therapeutic potential, and optimizing treatment strategies tailored to individual patients, and through interdisciplinary collaborations between computer scientists, biologists, and clinicians, the full potential of AI in accelerating the discovery and development of novel AMPs will be realized. Besides, with the continuous advancements in 3D/4D/5D/6D technology and its integration into bone scaffold materials, we anticipate remarkable progress in the field of regenerative medicine. This review summarizes relevant research on the optimal future for the treatment of infectious bone defects, provides guidance for future novel treatment strategies combining multi-dimensional printing with new antimicrobial agents, and provides a novel and effective solution to the current challenges in the field of bone regeneration.
感染是骨折最常见的并发症，尤其是开放性骨折，且常常会导致严重后果。细菌耐药性的出现显著加重了临床实践中感染的负担，使得感染控制成为感染性骨缺损治疗面临的重大挑战。尽管感染风险增加，但植入结构性支架对于治疗大的骨缺损是必要的。因此，需要开发新的抗菌疗法。抗菌生物材料和新型抗菌药物的进展为抗菌治疗提供了新的视角。虽然抗菌3D支架目前是研究的热点，但仅依靠材料特性或抗生素作用仍然不够。抗菌肽是最有前景的新型抗菌治疗方法之一。本综述讨论了感染性骨缺损背后的潜在机制，并介绍了抗菌肽的研究结果，特别强调了它们的作用机制和优化策略。我们还探讨了利用抗菌肽治疗感染性骨缺损的潜在前景。此外，我们提出人工智能（AI）算法可用于预测抗菌肽的药代动力学特性，包括吸收、分布、代谢和排泄，通过将基因组学、蛋白质组学、代谢组学和临床研究的信息与机器学习算法驱动的计算模型相结合，科学家可以全面了解抗菌肽的作用机制、治疗潜力，并优化针对个体患者的治疗策略，通过计算机科学家、生物学家和临床医生之间的跨学科合作，将实现人工智能在加速新型抗菌肽发现和开发方面的全部潜力。此外，随着3D/4D/5D/6D技术的不断进步及其与骨支架材料的整合，我们预计再生医学领域将取得显著进展。本综述总结了关于感染性骨缺损治疗最佳未来的相关研究，为未来将多维打印与新型抗菌剂相结合的新型治疗策略提供指导，并为当前骨再生领域的挑战提供新颖有效的解决方案。
