Tissue engineering (TE) is critical in oral and craniofacial reconstruction. One of the most popular topics on the biomaterial-based tissue regeneration process may be the interaction between cells and scaffolds. An increasing number of studies have identified the variables affecting cell-scaffold interaction. The creation and investigation of new scaffolds for TE and regenerative medicine based on specific interactions have become possible owing to these findings. This review discusses the effects of various types of scaffold materials on cells in TE. Because the intrinsic properties of scaffolds are essential, the influence of the physical, chemical, mechanical, and biological characteristics of scaffold materials on cell-scaffold interaction that has been discovered in recent research is elaborated in this review. The components carried by scaffolds, the degradation process, and the role of degraded products in cell-scaffold interactions are examined. Further, the roles of cells, including cell types, functions, and adhesion mechanisms, and extracellular matrix are discussed. Finally, the latest research progress on cell-scaffold interactions among various engineered tissues or organs in the oral and craniofacial region is summarized. A deeper understanding of cell-scaffold interactions is anticipated to benefit the development of TE and regenerative medicine.

Apical periodontitis (AP) is one of the most prevalent disorders in dentistry. However, it can be underdiagnosed in asymptomatic patients. In addition, the perioperative evaluation of 3-dimensional (3D) lesion volume is of great clinical relevance, but the required slice-by-slice manual delineation method is time- and labor-intensive. Here, for quickly and accurately detecting and segmenting periapical lesions (PALs) associated with AP on cone beam computed tomography (CBCT) images, we proposed and geographically validated a novel 3D deep convolutional neural network algorithm, named PAL-Net. On the internal 5-fold cross-validation set, our PAL-Net achieved an area under the receiver operating characteristic curve (AUC) of 0.98. The algorithm also improved the diagnostic performance of dentists with varying levels of experience, as evidenced by their enhanced average AUC values (junior dentists: 0.89–0.94; senior dentists: 0.91–0.93), and significantly reduced the diagnostic time (junior dentists: 69.3 min faster; senior dentists: 32.4 min faster). Moreover, our PAL-Net achieved an average Dice similarity coefficient over 0.87 (0.85–0.88), which is superior or comparable to that of other existing state-of-the-art PAL segmentation algorithms. Furthermore, we validated the generalizability of the PAL-Net system using multiple external data sets from Central, East, and North China, showing that our PAL-Net has strong robustness. Our PAL-Net can help improve the diagnostic performance and speed of dentists working from CBCT images, provide clinically relevant volume information to dentists, and can potentially be applied in dental clinics, especially without expert-level dentists or radiologists.

Odontoblasts, terminally differentiated dentin-forming cells with their processes that penetrate into dentin, have been considered potential sensory cells. Current research suggests that odontoblasts sense external stimuli and transmit pain signals. PIEZO1, as a specific mechanically activated ion channel, may play an important role in mechanical transduction in odontoblasts. In this study, we devoted to investigating the functions and underlying molecular mechanisms of PIEZO1 ion channels in odontoblast mechanotransduction. Human dental pulp stem cells were cultured in vitro and induced to differentiate into odontoblast-like cells (OLCs). The expression of PIEZO1 protein in pulp, dental pulp stem cells, and OLCs was detected by immunohistochemistry or immunofluorescence. The mechanical sensitivity of OLCs was detected by a constructed fluid shear stress model and examined by calcium fluorescence intensity. A single-cell mechanical stimulation model was used to detect the PIEZO1 electrophysiological properties of OLCs. Yoda1 (a PIEZO1-specific agonist), GsMTx4 (a PIEZO1 antagonist), and non-calcium ion extracellular solution were utilized to confirm PIEZO1 mechanotransduction in OLCs in both fluid shear stress and single-cell mechanical stimulation assays. The amount of ATP released by OLCs was measured under stimulation with Yoda1 and GsMTx4. Rat trigeminal ganglion neurons were cultured in vitro and detected by whole-cell patch-clamp recording under ATP stimulation. PIEZO1 ion channels were positively expressed in OLCs and odontoblastic bodies and processes but weakly expressed in dental pulp cells. After the treatment of OLCs with shearing stress or Yoda1, the fluorescence intensity of intracellular calcium ions increased rapidly but did not noticeably change after treatment with GsMTx4 or the non-calcium ion extracellular solution. When single-cell mechanical stimuli were applied to OLCs, the evoked inward currents were recorded by patch-clamp electrophysiology. The inward currents increased and current inactivation became slower after Yoda1 treatment, but these currents almost completely disappeared after the addition of GsMTx4. The amount of ATP released by OLCs increased significantly after Yoda1 stimulation, while GsMTx4 reversed the release of ATP. Whole-cell patch-clamp detection showed that ATP evoked slow inward currents and increased the frequency of action potentials of trigeminal ganglion neurons. Taken together, these findings indicated that odontoblasts evoked a fast inward current via PIEZO1 ion channels after the application of external mechanical stimuli and released ATP to transmit signals to adjacent cells. Thus, PIEZO1 ion channels in odontoblasts mediate mechanotransduction under various pathophysiological conditions in dentin.