Current functional assessment of biomaterial‐induced stem cell lineage fate in vitro mainly relies on biomarker‐dependent methods with limited accuracy and efficiency. Here a “Mesenchymal stem cell Differentiation Prediction (MeD‐P)” framework for biomaterial‐induced cell lineage fate prediction is reported. MeD‐P contains a cell‐type‐specific gene expression profile as a reference by integrating public RNA‐seq data related to tri‐lineage differentiation (osteogenesis, chondrogenesis, and adipogenesis) of human mesenchymal stem cells (hMSCs) and a predictive model for classifying hMSCs differentiation lineages using the k‐nearest neighbors (kNN) strategy. It is shown that MeD‐P exhibits an overall accuracy of 90.63% on testing datasets, which is significantly higher than the model constructed based on canonical marker genes (80.21%). Moreover, evaluations of multiple biomaterials show that MeD‐P provides accurate prediction of lineage fate on different types of biomaterials as early as the first week of hMSCs culture. In summary, it is demonstrated that MeD‐P is an efficient and accurate strategy for stem cell lineage fate prediction and preliminary biomaterial functional evaluation.

Stem Cell Lineage Fate Highly accurate, efficient, and convenient evaluation for biomaterial‐induced stem cell lineage fate is pivotal for regenerative biomaterials research. In article number 2210637, Binbin Lai, Xuehui Zhang, Xuliang Deng, and co‐workers report MeD‐P, a machine‐learning‐supported intelligent evaluation model, for predicting human mesenchymal stem cell–biomaterial interaction based on RNA‐seq data. This framework shows the potential of artificial intelligence in facilitating biological performance optimization of biomaterials in stem cell lineage fate regulation.

Insufficient alveolar bone height is a major problem in implant restoration surgery. Here, the therapeutic strategy of restoring the electrical microenvironment to enhance alveolar bone augmentation was investigated in a standardized large-size beagle dog pre-clinical model. A biomimetic charged nano-BaTiO3/poly(vinylidene fluoridetrifluoroethylene) (nano-BTO/P(VDF-TrFE)) composite membrane was used to restore the endogenous electrical microenvironment of alveolar bone. The charged membrane exhibited excellent electrical stability. Upon implantation with bone grafts and covering with the charged membrane in alveolar bone defect sites for three months, there were significant improvements in the bone height, bone mineral density (BMD) and bone volume, as assessed by micro-CT analysis. Histological analysis further confirmed that restoration of the electrical microenvironment significantly promoted alveolar bone regeneration and maturation. These findings thus provide an innovative strategy for restoring the electrical microenvironment to enhance alveolar bone augmentation, which could further advance prosthodontics implant technology.