Stephansenhart5029

Purpose To evaluate the effect of different cleaning methods on the shear bond strength (SBS) of a 10-methacryloyloxydecyl dihydrogen phosphate (MDP)-containing self-adhesive resin cement to zirconia after saliva contamination.Methods Sixty zirconia specimens were randomly divided into four groups (n=15) according to treatment surface. Except for the control group, all samples were contaminated with saliva and were then rinsed with water-spray and air-dried. Subsequently, the specimens were either treated with a cleaning paste (CP), with argon plasma (AP), or did not undergo an additional cleaning process (WS). An MDP-containing self-adhesive resin cement was applied onto the ceramic surfaces. Specimens were stored in water (24 hours) followed by thermocycling (5°C to 55°C for 10.000 cycles). SBS tests were performed in a universal testing machine, and the results (MPa ± SD) were statistically analyzed using ANOVA and Bonferroni post-hoc test. Fractured surfaces were examined to identify the failure types using a stereomicroscopy and SEM.Results The surface cleaning treatment (p less then 0.05) significantly affected the results. The highest SBS values were observed in the control group (12.16 ± 1.22 MPa) and were statistically comparable to values for the CP group (11.38 ± 1.65 MPa). The AP group (9.17 ± 1.06 MPa) showed significantly higher bond strength than the WS group (6.95 ± 1.20 MPa), but it showed significantly lower strength than the control and CP groups.Conclusions The CP application was the most effective method in removing saliva contamination. The AP treatment could not restore the SBS to the same level as uncontaminated specimens.

The purpose of this study was to comprehensively review the literature regarding the application of artificial intelligence (AI) in the dental field, focusing on the evaluation criteria and architecture types.

Electronic databases (PubMed, Cochrane Library, Scopus) were searched. this website Full-text articles describing the clinical application of AI for the detection, diagnosis, and treatment of lesions and the AI method/architecture were included.

The primary search presented 422 studies from 1996 to 2019, and 58 studies were finally selected. Regarding the year of publication, the oldest study, which was reported in 1996, focused on "oral and maxillofacial surgery." Machine-learning architectures were employed in the selected studies, while approximately half of them (29/58) employed neural networks. Regarding the evaluation criteria, eight studies compared the results obtained by AI with the diagnoses formulated by dentists, while several studies compared two or more architectures in terms of performance. The following parameters were employed for evaluating the AI performance accuracy, sensitivity, specificity, mean absolute error, root mean squared error, and area under the receiver operating characteristic curve.

Application of AI in the dental field has progressed; however, the criteria for evaluating the efficacy of AI have not been clarified. It is necessary to obtain better quality data for machine learning to achieve the effective diagnosis of lesions and suitable treatment planning.

Application of AI in the dental field has progressed; however, the criteria for evaluating the efficacy of AI have not been clarified. It is necessary to obtain better quality data for machine learning to achieve the effective diagnosis of lesions and suitable treatment planning.Purpose In recent years, the chewing frequency, i.e., the number of chewing cycles, has decreased owing to changes in dietary habits. Although these changes may be related to complete body health, there is no evidence-based tool to measure the dietary habits. We developed a small ear-hung wearable device for monitoring mastication behavior. The device, worn on the ear pinna, allows the counting of the number of chewing cycles, and data are collected on a smartphone via Bluetooth. In this study, the reliability of the novel device was verified.Methods A total of 22 healthy volunteers participated in the study. During measurement, the subjects wore the novel wearable device on their right ear pinna and were asked to chew gum, gummy jellies, and rice balls. The number of chewing cycles was counted by the device. A mandibular kinesiograph (MKG) was also recorded, and the chewing activity was recorded as a video. The accuracy, precision, and recall of the ear-hung device were calculated by comparing the data obtained from the MKG and the video recording. Additionally, the factors affecting reliability were examined.Results The accuracy, precision, and recall of the novel device were 101.6 ± 13.6%, 85.3 ± 11.0%, and 84.5 ± 9.5%, respectively. Although the accuracy was not affected by any factor, precision and recall of the novel device for women were significantly worse than that for men, and were greatest when the subjects were chewing gum.Conclusions Our findings suggest that the newly developed ear-hung wearable device for counting the number of chewing cycles was sufficiently reliable.Intermittent fasting, which can effectively reduce obesity and improve the related metabolic syndrome has become an exciting research area in recent years. Adipose tissue is pivotal in regulating the metabolism and determining the occurrence of obesity. In the current study, we aimed to investigate the effects of acute fasting (AF) on fat tissue. Mice were subjected to AF for 36 h, receiving normal chow (low-fat diet [LFD]) or a high-fat diet (HFD), with free ad libitum access to drinking water, and those fed on free-diet counterparts without fasting serveding as controls. We found that AF obviously reshaped the morphology of fat tissue (WAT) and promoted the beiging of white adipose tissue in both LFD- and HFD-fed mice. AF principally improved the lipid metabolism, and increased the M2- polarization of macrophages in WAT white fat tissue of HFD-fed mice. Interestingly, we found that AF dramatically upregulated Sirt5 expression levels and fat tissue succinylation, suggesting that AF-induced beneficial effects on fat might occur via the regulation of Sirt5 levels and altered succinylation in fatty tissues. Our study clearly showed the remodeling function of adipose tissue during AF; in terms of mechanism, the regulation of succinylation levels by AF might provide new insights into the mechanism(s) underlying the improvement in fat metabolism by energy restriction.