Bone-tissue defects affect millions of people worldwide. Despite being common treatment approaches, autologous and allogeneic bone grafting have not achieved the ideal therapeutic effect. This has prompted researchers to explore novel bone-regeneration methods. In recent decades, the development of bone tissue engineering (BTE) scaffolds has been leading the forefront of this field. As researchers have provided deep insights into bone physiology and the bone-healing mechanism, various biomimicking and bioinspired BTE scaffolds have been reported. Now it is necessary to review the progress of natural bone physiology and bone healing mechanism, which will provide more valuable enlightenments for researchers in this field. This work details the physiological microenvironment of the natural bone tissue, bone-healing process, and various biomolecules involved therein. Next, according to the bone physiological microenvironment and the delivery of bioactive factors based on the bone-healing mechanism, it elaborates the biomimetic design of a scaffold, highlighting the designing of BTE scaffolds according to bone biology and providing the rationale for designing next-generation BTE scaffolds that conform to natural bone healing and regeneration.

Regenerating periodontal bone tissues in the aggravated inflammatory periodontal microenvironment under diabetic conditions is a great challenge. Here, a polydopamine-mediated graphene oxide (PGO) and hydroxyapatite nanoparticle (PHA)-incorporated conductive alginate/gelatin (AG) scaffold is developed to accelerate periodontal bone regeneration by modulating the diabetic inflammatory microenvironment. PHA confers the scaffold with osteoinductivity and PGO provides a conductive pathway for the scaffold. The conductive scaffold promotes bone regeneration by transferring endogenous electrical signals to cells and activating Ca²⁺ channels. Moreover, the scaffold with polydopamine-mediated nanomaterials has a reactive oxygen species (ROS)-scavenging ability and anti-inflammatory activity. It also exhibits an immunomodulatory ability that suppresses M1 macrophage polarization and activates M2 macrophages to secrete osteogenesis-related cytokines by mediating glycolytic and RhoA/ROCK pathways in macrophages. The scaffold induces excellent bone regeneration in periodontal bone defects of diabetic rats because of the synergistic effects of good conductive, ROS-scavenging, anti-inflammatory, and immunomodulatory abilities. This study provides fundamental insights into the synergistical effects of conductivity, osteoinductivity, and immunomodulatory abilities on bone regeneration and offers a novel strategy to design immunomodulatory biomaterials for treatment of immune-related diseases and tissue regeneration.

In this study, multilayer perceptron artificial neural networks are used to predict orthodontic treatment plans, including the determination of extraction-nonextraction, extraction patterns, and anchorage patterns. The neural network can output the feasibilities of several applicable treatment plans, offering orthodontists flexibility in making decisions. The neural network models show an accuracy of 94.0% for extraction-nonextraction prediction, with an area under the curve (AUC) of 0.982, a sensitivity of 94.6%, and a specificity of 93.8%. The accuracies of the extraction patterns and anchorage patterns are 84.2% and 92.8%, respectively. The most important features for prediction of the neural networks are “crowding, upper arch” “ANB” and “curve of Spee”. For handling discrete input features with missing data, the average value method has a better complement performance than thek-nearest neighbors (k-NN) method; for handling continuous features with missing data,k-NN performs better than the other methods most of the time. These results indicate that the proposed method based on artificial neural networks can provide good guidance for orthodontic treatment planning for less-experienced orthodontists.