Use of degradable magnesium (Mg)-based metal implants in orthopaedic surgeries can avoid drawbacks associated with subsequent removal of the non-degradable metallic implants, reducing cost and trauma of patients. Although Mg has been applied in the clinic for orthopaedic treatment, the use of Mg-based metal implants is largely in the research phase. But its application is potentially beneficial in this context as it has been shown that Mg can promote osteogenesis and inhibit osteoclast activity. A systematic literature search about “degradable magnesium (Mg)-based metal implants” was performed in PubMed and Web of Science. Meanwhile, relevant findings have been reviewed and quoted. In this review, we summarize the latest developments in Mg-based metal implants and their role in bone regeneration. We also review the various molecular mechanisms by which Mg ions regulate bone metabolic processes, including osteogenesis, osteoclast activity, angiogenesis, immunity, and neurology. Finally, we discuss the remaining research challenges and opportunities for Mg-based implants and their applications. Currently, establishment of the in vitro and in vivo biological evaluation systems and phenotypic modification improvement of Mg-based implants are still needed. Clarifying the functions of Mg-based metal implants in promoting bone metabolism is beneficial for their clinical application. All current reviews on Mg-based implants are mainly concerned with the improvement of Mg alloy properties or the progress of applications. However, there are few reviews that provides a systematic narrative on the effect of Mg on bone metabolism. This review summarized the latest developments in Mg-based metal implants and various molecular mechanisms of Mg ions regulating bone metabolism, which is beneficial to further promote the translation of Mg based implants in the clinic and is able to provide a strong basis for the clinical application of Mg based implants.

Evidence has shown that effects from inflammation and mitochondrial dysfunction lead to pyroptosis and apoptosis of nucleus pulposus (NP) cells. Damaged mitochondria release dangerous molecules such as reactive oxygen species (ROS), activating the NLRP3 inflammasome. SS-31 is a mitochondria-targeting peptide that has been used in the treatment of many diseases by scavenging ROS and ameliorating mitochondrial function. This study found that SS-31 ameliorated lipopolysaccharide (LPS)-induced loss of cell viability, ROS production, and apoptosis in NP cells. Moreover, mitochondrial dynamics and ATP synthesis were restored on pretreatment with SS-31 compared with the LPS group. For the molecular mechanism research, SS-31 stabilized mitochondrial morphology and inhibited the activation of the NF-κB pathway and the activation of the NLRP3 inflammasome. To evaluate whether the inhibition of NLRP3 inflammasome activation by SS-31 is dependent on the clearance of mitochondrial ROS, we comparatively analyzed the activation of NLRP3 inflammasome in NP cells pretreated with SS-31 and the ROS scavenger N-acetyl-L-cysteine (NAC). The results indicate that SS-31 could inhibit NLRP3 inflammasome activation by limiting the production of mitochondrial ROS. To sum up, our results revealed that SS-31 inhibits LPS-induced apoptosis, pyroptosis, and inflammation in NP cells via scavenging ROS and maintaining the stability of mitochondrial dynamics, which could be considered a promising therapeutic intervention for disk degeneration.

Study Design: Narrative review. Objectives: This review aims to present current applications of machine learning (ML) in spine domain to clinicians. Methods: We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2020 using terms (spine, spinal, lumbar, cervical, thoracic, machine learning) to examine ML in spine. Then exclude research of other domain, case report, review or meta-analysis, and which without available abstract or full text. Results: Total 1738 articles were retrieved from database, and 292 studies were finally included. Key findings of current applications were compiled and summarized in this review. Main clinical applications of those techniques including image processing, diagnosis, decision supporting, operative assistance, rehabilitation, surgery outcomes, complications, hospitalization and cost. Conclusions: ML had achieved excellent performance and hold immense potential in spine. ML could help clinical staff to improve medical level, enhance work efficiency, and reduce adverse events. However more randomized controlled trials and improvement of interpretability are essential to clinicians accepting models’ assistance in real work.