In the field of dental aesthetics,digital aesthetic design plays a crucial role in helping dentists to predict treatment outcomes vis-ually,as well as in enhancing the consistency of knowledge and understanding of aesthetic goals between dentists and patients.It serves as the foundation for achieving ideal aesthetic effects.However,there is no clear standard for this digital process currently in China and abroad.Many dentists lack of systematic understanding of how to carry out digital aesthetic design for treatment.To establish standardized processes for dental aesthetic design and to improve the homogeneity of treatment outcomes,Chinese Society of Digital Dental Industry(CSD-DI)convened domestic experts in related field to compile this consensus.This article elaborates on the key aspects of digital aesthetic data collection,integration steps,and the digital aesthetic design process.It also formulates a decision tree for dental aesthetics at macro level and outlines corresponding workflows for various clinical scenarios,serving as a reference for clinicians.

Objective:To investigate the correlation between the evidence-based practice competence of undergraduate nursing interns and hospital evidence-based culture, and to provide a reference for the design of evidence-based practice activities in the internship program for undergraduate nursing interns in the future.Methods:From December 2021 to February 2022, the nursing interns in Hunan province of China were selected as subjects, and the evidence-based practice competence scale for nursing interns and the hospital evidence-based practice culture scale were used to investigate the evidence-based practice ability of nursing interns and hospital evidence-based practice culture. SPSS 26.0 was used for statistical analysis and inference.Results:The total score of evidence-based practice competence was 84.67±27.17 among the nursing interns, and the total score of hospital evidence-based practice culture was 79.65±15.92. Evidence-based practice competence was positively correlated with the total score of hospital evidence-based practice culture and the scores of each dimension ( r=0.635-0.813, P<0.01). Conclusions:The evidence-based practice competence of undergraduate nursing interns needs to be improved, which is positively correlated with hospital evidence-based practice culture. Schools should cooperate with teaching hospitals to create a good hospital evidence-based practice culture, systematically optimize the clinical practice arrangements of nursing interns, and promote the development of the evidence-based practice competence of nursing interns.

Objective The progressive loading process of implants was simulated,and the influence of progressive loading method on peri-implant bone reconstruction was evaluated.Methods Using finite element analysis combined with the ANSYS parametric design language(APDL),the average bone density of the peri-implant regions was observed using conventional loading(control group)and progressive loading(experimental group)within six months of implant placement.The stress distributions of bone tissues in a 1 mm3 region of interest(ROI)around the implant and variations in bone density were observed.Results Within six months after implantation,the cortical bone density of the control group decreased by 0.19 g/cm3,whereas that of the experimental group decreased by 0.15 g/cm3.The trabecular bone density of each area in the experimental group increased by 0.4 g/cm3 compared with that in the control group.The bone density in the experimental group was lower than that in the control group.The increase in cancellous bone in the experimental group was higher than that in the control group.The finite element analysis revealed that the equivalent stress distribution range and maximum value of the experimental group(8.9 MPa)were significantly higher than those of the control group(6.68 MPa).Conclusions The use of the progressive loading method within six months after implantation was conducive to the distribution of stress on the bone tissues around the implant.This reduced the variation in bone density at the edge of the implant.The peri-implant bone density increased more under progressive loading than under conventional loading.The effect is superior to that of the conventional loading method.

Objective The progressive loading process of implants was simulated,and the influence of progressive loading method on peri-implant bone reconstruction was evaluated.Methods Using finite element analysis combined with the ANSYS parametric design language(APDL),the average bone density of the peri-implant regions was observed using conventional loading(control group)and progressive loading(experimental group)within six months of implant placement.The stress distributions of bone tissues in a 1 mm3 region of interest(ROI)around the implant and variations in bone density were observed.Results Within six months after implantation,the cortical bone density of the control group decreased by 0.19 g/cm3,whereas that of the experimental group decreased by 0.15 g/cm3.The trabecular bone density of each area in the experimental group increased by 0.4 g/cm3 compared with that in the control group.The bone density in the experimental group was lower than that in the control group.The increase in cancellous bone in the experimental group was higher than that in the control group.The finite element analysis revealed that the equivalent stress distribution range and maximum value of the experimental group(8.9 MPa)were significantly higher than those of the control group(6.68 MPa).Conclusions The use of the progressive loading method within six months after implantation was conducive to the distribution of stress on the bone tissues around the implant.This reduced the variation in bone density at the edge of the implant.The peri-implant bone density increased more under progressive loading than under conventional loading.The effect is superior to that of the conventional loading method.

Humans ; Dermatitis, Atopic/drug therapy* ; Resorcinols/therapeutic use* ; Stilbenes/therapeutic use* ; Double-Blind Method ; Treatment Outcome ; Severity of Illness Index