Occlusal rehabilitation is an effective means of treating tooth wear, edentulous jaws and other oral diseases. Among them, full-mouth fixed occlusal reconstruction can effectively restore aesthetics and function, but the complexity of the clinical process, the high sensitivity of the technique, and the high incidence of various complications have always drawn much attention. With the application and development of digital technology in occlusal rehabilitation, the treatment outcome has been improved compared with traditional treatment. However, there are many kinds of digital technology with different efficacy, how to build an efficiently standardized digital clinical technical solution is a current difficulty. Therefore, combined with the long-term work of the department of prosthodontics in our hospital, in this paper, the minimum (occlusal perception of thickness) and maximum (centric relation) geometric quantities which should be paid attention to during reconstruction are put forward. We systematically organized the clinical procedure of digital full-mouth fixed occlusal rehabilitation used in our department for a long time. In conclusion, a 5-stage 19-step or n-step solution (5-19N for short) characterized by "from large to small" restorative space splitting logic is proposed. It has a certain reference value for the future use of digital technology to deal with complex occlusal rehabilitation cases.
Humans ; Dental Occlusion ; Computer-Aided Design ; Mouth, Edentulous/rehabilitation*

Objective:Exploring the relationship between diabetes mellitus targets and ACE2 of the receptor of novel coronavirus(2019-nCoV) through a protein interaction network to provide new perspectives for clinical use.Methods:Diabetes mellitus targets were obtained from the GeneCards and OMIM databases. Targets with a relevance score exceeding 10 were included, and ACE2 protein was manually added. The initial protein interaction network was obtained through String and then imported into Cytoscape 3.7.1. We selected the protein targets directly related to ACE2 as the target of the final analysis and imported them into String again in order to obtain the protein interaction network. Module identification, GO analysis and KEGG pathway analysis were performed respectively. The impact of ACE2 on the entire network was analyzed by scoring the module where it located.Results:19 ACE2-related proteins were finally selected from diabetes mellitus targets. Three functional modules were found through the cluster analysis. These modules involved G protein-coupled receptor binding, antioxidant activity, and insulin-like growth factor receptor binding. The main signal pathways involved were the renin angiotensin system signal pathway, the type 2 diabetes mellitus signal pathway, and the FOXA2 signal pathway. The scoring results showed that REN, AGT, INS, NOS3, IL6, and CRP scored the highest.Conclusions:ACE2 is widely associated with diabetes mellitus key proteins. COVID-19 may impact RAS of diabetes mellitus patients then induce serious complications. Clinical use of RAS inhibitors may reduce the impact of COVID-19 infection on diabetes mellitus patients.