Amorphous Calcium Phosphate (ACP) is an essential mineral phase formed in mineralized tissues and the first commercial product as artificial hydroxyapatite. ACP is unique among all forms of calcium phosphates in that it lacks long-range, periodic atomic scale order of crystalline calcium phosphates. The X-ray diffraction pattern is broad and diffuse with a maximum at 25 degree 2 theta, and no other different features compared with well-crystallized hydroxyapatite. Under electron microscopy, its morphological form is shown as small spheroidal particles in the scale of tenths nanometer. In aqueous media, ACP is easily transformed into crystalline phases such as octacalcium phosphate and apatite due to the growing of microcrystalline. It has been demonstrated that ACP has better osteoconductivity and biodegradability than tricalcium phosphate and hydroxyapatite in vivo. Moreover, it can increase alkaline phosphatase activities of mesoblasts, enhance cell proliferation and promote cell adhesion. The unique role of ACP during the formation of mineralized tissues makes it a promising candidate material for tissue repair and regeneration. ACP may also be a potential remineralizing agent in dental applications. Recently developed ACP-filled bioactive composites are believed to be effective anti-demineralizing/remineralizing agents for the preservation and repair of tooth structures. This review provides an overview of the development, structure, chemical composition, morphological characterization, phase transformation and biomedical application of ACP in dentistry.

Routine dental visit is the most common approach to detect the gingivitis. However, such diagnosis can sometimes be unavailable due to the limited medical resources in certain areas and costly for low-income populations. This study proposes to screen the existence of gingivitis and its irritants, i.e., dental calculus and soft deposits, from oral photos with a novel Multi-Task Learning convolutional neural network (CNN) model. The study can be meaningful for promoting the public dental health, since it sheds light on a cost-effective and ubiquitous solution for the early detection of dental issues. With 625 patients included in this study, the classification Area Under the Curve (AUC) for detecting gingivitis, dental calculus and soft deposits were 87.11%, 80.11%, and 78.57%, respectively; Meanwhile, according to our experiments, the model can also localize the three types of findings on oral photos with moderate accuracy, which enables the model to explain the screen results. By comparing to general-purpose CNNs, we showed our model significantly outperformed on both classification and localization tasks, which indicates the effectiveness of Multi-Task Learning on dental disease detection. In all, the study shows the potential of deep learning for enabling the screening of dental diseases among large populations.

BACKGROUND: Demineralization can be arrested or reversed when remineralization agents are applied to incipient carious or non-cavitated carious lesions. A large number of therapeutic agents including non-fluoridated products have been developed to pr

Periodontitis is a major cause for tooth loss, which affects about 15% of the adult population. Cementum regeneration has been the crux of constructing the periodontal complex. Cementum protein 1 (CEMP1) is a cementum-specific protein that can induce cementogenic differentiation. In this study, poly(ethylene glycol) (PEG)-stabilized amorphous calcium phosphate (ACP) nanoparticles were prepared by wet-chemical method and then loaded with recombinant human CEMP1 (rhCEMP1) for controlled release. An electrospun multiphasic scaffold constituted of poly(ε-caprolactone) (PCL), type I collagen (COL), and rhCEMP1/ACP was fabricated. The effects of rhCEMP1/ACP/PCL/COL scaffold on the attachment proliferation, osteogenic, and cementogenic differentiations of human periodontal ligament cells, (PDLCs) were systematically investigated. A critical size defect rat model was introduced to evaluate the effect of tissue regeneration of the scaffolds in vivo. The results showed that PEG-stabilized ACP nanoparticles formed a core-shell structure with sustained release of rhCEMP1 for up to 4 weeks. rhCEMP1/ACP/PCL/COL scaffold could suppress PDLCs proliferation behavior and upregulate the expression of cementoblastic markers including CEMP1 and cementum attachment protein while downregulating osteoblastic markers including osteocalcin and osteopontin when it was cocultured with PDLCs in vitro for 7 days. Histology analysis of cementum after being implanted with the scaffold in rats for 8 weeks showed that there was cementum-like tissue formation but little bone formation. These results indicated the potential of using electrospun multiphasic scaffolds for controlled release of rhCEMP1 for promoting cementum regeneration in reconstruction of the periodontal complex.