These results can be used by orthodontists as representative of the soft tissue profile changes during the developmental period.

Objective:The aim of this study was to develop an artificial intelligence (AI) algorithm to automatically and accurately determine the stage of cervical vertebra maturation (CVM) with the main purpose being to eliminate the human error factor. Setting and Sample Population:Archives of the cephalometric images were reviewed and the data of 1501 subjects with fully visible cervical vertebras were included in this retrospective study. Materials and Methods:Lateral cephalometric (LC) that met the inclusion criteria were used in the training process, labeling was carried out using a computer vision annotation tool (CVAT), tracing was done by an experienced orthodontist as a gold standard and, in order to limit the effect of the uneven distribution of the training data set, maturation stage was classified with a modified Bachetti method by the operator who labelled them. The labelled data were split randomly into a training set (80%), a testing set (10%) and an validation set (10%), to measure intra-observer, inter-observer reliability, intraclass correlation coefficient (ICC) and weighted Cohen's kappa test was carried out. Results:The ICC was valued at 0.973, weighted Cohen's kappa standard error was 0.870 ± 0.027 which shows high reliability of the observers and excellent level of agreement between them, the segmentation network achieved a global accuracy of 0.99 and the average dice score overall images was 0.93. The classification network achieved an accuracy of 0.802, class sensitivity of (pre-pubertal 0.78; pubertal 0.45; post-pubertal 0.98), respectively, per class specificity of (pre-pubertal 0.94; pubertal 0.94; post-pubertal 0.75), respectively. Conclusion:The developed algorithm showed the ability to determine the cervical vertebrae maturation stage which might aid in a faster diagnosis process by eliminating human intervention, which might lead to wrong decision-making procedures that might affect the outcome of the treatment plan. The developed algorithm proved reliable in determining the pre-pubertal and post-pubertal growth stages with high accuracy.

This is the first population-based study to focus solely on Turkish Cypriots' craniofacial anatomy and orthodontic characteristics. The present findings will produce 3D cephalometric normative data for the Cypriot population and will be valuable for oral and maxillofacial surgeons and orthodontists in Cyprus, the UK, Australia, Turkey, and other European countries who treat a large number of Turkish Cypriot patients.

One common negative side effect of orthodontic treatment with fixed appliances is the development of white spot lesions (WSLs) around brackets. This study is aimed at comparing the efficacy of various oral hygiene practices in preventing enamel demineralization around orthodontic brackets under similar in vitro conditions. The study included 90 extracted bovine incisors, which were randomized into six groups: fluoride toothpaste (FT), nonfluoride toothpaste (NFT), fluoride varnish plus fluoride toothpaste (FV+FT), CPP-ACP varnish plus fluoride toothpaste (CPP-ACP+FT), medical minerals gel plus nonfluoride toothpaste (MMG+NFT), and no intervention (control). All groups were subjected to demineralization and remineralization cycles. Visual appraisals were used to evaluate the changes in the enamel surface appearance at the beginning and end of the experiment. The changes in the demineralization degree were evaluated by measuring the Ca+2 concentration in the demineralization solution at different time points. The majority of teeth in the CPP-ACP+FT group exhibited no shift in appearance, whereas in the other groups, a slight change in enamel translucency was observed. At all the time points, the Ca+2 concentration in the demineralization solution in the CPP-ACP+FT group was the least among all other groups. At day 5, MMG+NFT’s preventive efficacy was significantly higher than FV+FT’s, but at days 10, 15, and 19, their efficacy was similar. However, at all the time points, MMG+NFT’s efficacy was significantly higher than that of control, whereas FV+FT’s efficacy was decreased at days 10, 15, and 19 and was close to the efficacy of control. To fight WSLs, early diagnosis was of great importance and examination of the tooth surface after air-drying for 5 s was recommended.

Objective The aims of this study were (a) to evaluate the displacement and stress distribution in the maxillary dentition associated with the use of two different unilateral distalization appliances—unilateral zygoma gear (UZG) appliance and asymmetric headgear (AHG)—in non‐growing patients; and (b) to assess the effects of fully erupted maxillary third molars on the distalization of the first molar with both appliances by using three‐dimensional finite element analysis. Settings and sample population Two 3D models of the maxilla were created: one with third molars and one without. Next, two distalizing appliances (UZG and AHG) were added to each model to create four models. Materials and methods Distalization forces were applied, and the resultant displacements were recorded at the mesiobuccal and distolingual cusps and palatal root apex of each molar and the incisal edge root apex of the central incisors. The resulting von Mises stress distributions were evaluated. Results With the UZG, the first molar showed greater root distalization than the crown in the model with the third molar, whereas the model without the third molar showed distalization and distal tipping of the first molar. With the AHG, the first molar showed a large amount of distal tipping in the model without a third molar. However, this tipping was less than that in the model with third molars. Conclusion The presence of completely erupted third molars decreased the amount of uncontrolled distal tipping in both appliances. UZG can be considered as an effective option for maxillary molar distalization.