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Molar-Incisor Hypomineralization (MIH) is a qualitative defect of enamel of unknown etiology, affecting one or more permanent molars and may include incisors. This condition is a clinical challenge and its prevalence is still uncertain given the recent increase in research. Thus, we aimed to comprehensively estimate the overall prevalence of MIH and associated characteristics. This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). We searched articles using PubMed, MEDLINE, CENTRAL, Web of Science, SciELO, LILACS and TRIP databases, until July 2021. Heterogeneity and publication bias were computed via I 2 test statistics and Egger’s significance test, respectively. Random-effects meta-analysis of prevalence were processed. We used the Strength of Recommendation Taxonomy [SORT] to grading the strength of evidence. Overall, 116 observational studies were included, with one study with moderate methodological quality and the remaining of high methodological quality. Subgroup analysis confirmed an influence of not using the 2003 MIH case definition (p = 0.0066). The pooled prevalence of MIH was 13.5% (95% CI 12.0–15.1, I 2  = 98.0%). Affected incisors were seen in 36.6% (95% CI 30.0–43.7, I 2  = 92.5%) of the cases. Lastly, the prevalence of hypomineralization of the second primary molars was observed in 3.6% of the MIH cases (95% CI 1.9–6.8, I 2  = 96.3%). America was the continent with highest prevalence (15.3, 95% CI 12.8–18.3, p < 0.001, I 2  = 96.3%) and Asia had the lowest prevalence (10.7, 95% CI 8.5–13.5, p < 0.001, I 2  = 98.7%), however no continental differences were found. Sample size and year of publication were slight contributing factors to the heterogeneity in the analysis. Overall, these results were classified with a SORT A recommendation.

Diabetes mellitus is an established risk factor for periodontitis, and periodontitis can adversely affect glycemic control. This Review discusses the complex relationship between these two conditions and the implications of this association for patients and health-care professionals. Diabetes mellitus (a group of metabolic disorders characterized by hyperglycemia) and periodontitis (a microbially induced inflammatory disorder that affects the supporting structures of teeth) are both common, chronic conditions. Multiple studies have demonstrated that diabetes mellitus (type 1 and type 2) is an established risk factor for periodontitis. Findings from mechanistic studies indicate that diabetes mellitus leads to a hyperinflammatory response to the periodontal microbiota and also impairs resolution of inflammation and repair, which leads to accelerated periodontal destruction. The cell surface receptor for advanced glycation end products and its ligands are expressed in the periodontium of individuals with diabetes mellitus and seem to mediate these processes. The association between the two diseases is bidirectional, as periodontitis has been reported to adversely affect glycemic control in patients with diabetes mellitus and to contribute to the development of diabetic complications. In addition, meta-analyses conclude that periodontal therapy in individuals with diabetes mellitus can result in a modest improvement of glycemic control. The effect of periodontal infections on diabetes mellitus is potentially explained by the resulting increase in levels of systemic proinflammatory mediators, which exacerbates insulin resistance. As our understanding of the relationship between diabetes mellitus and periodontitis deepens, increased patient awareness of the link between diabetes mellitus and oral health and collaboration among medical and dental professionals for the management of affected individuals become increasingly important. Key Points Diabetes mellitus is an established risk factor for periodontitis, a chronic microbially induced inflammatory disorder that affects the supporting structures of teeth Diabetes mellitus leads to a hyperinflammatory response to the bacterial challenge in periodontitis and impairs repair; these effects are at least partly mediated by the receptor for advanced glycation end products and its ligands Periodontitis can adversely affect glycemic control in patients with diabetes mellitus and contribute to the development of its complications Periodontal therapy seems to result in a modest improvement of glycemic control in patients with diabetes mellitus The adverse effect of periodontal infections on diabetes mellitus is potentially explained by the resulting increase in systemic inflammation, which contributes to insulin resistance Increased patient awareness of the link between diabetes mellitus and periodontitis and collaboration among medical and dental professionals for the management of affected individuals are essential

Oral lichen planus is a chronic inflammatory disease of unknown etiology or pathogenesis with varied disease severity that waxes and wanes over a long period of time. Although a common oral mucosal disease, accurate diagnosis is often challenging due to the overlapping clinical and histopathological features of oral lichen planus and other mucosal diseases. Other immune-mediated mucocutaneous diseases can exhibit lichenoid features including mucous membrane pemphigoid, chronic graft- versus -host disease, and discoid lupus erythematosus. Reactive changes to dental materials or to systemic medications can mimic oral lichen planus both clinically and histologically. In these situations the clinical presentation can be useful, as oral lichen planus presents as a multifocal process and is usually symmetrical and bilateral. Dysplasia of the oral cavity can exhibit a lichenoid histology, which may mask the potentially premalignant features. Proliferative verrucous leukoplakia, an unusual clinical disease, can often mimic oral lichen planus clinically, requiring careful correlation of the clinical and pathologic features.

The goal of this study was to develop a deep learning-based algorithm to predict temporomandibular joint (TMJ) disc perforation based on the findings of magnetic resonance imaging (MRI) and to validate its performance through comparison with previously reported results. The study objects were obtained by reviewing medical records from January 2005 to June 2018. 299 joints from 289 patients were divided into perforated and non-perforated groups based on the existence of disc perforation confirmed during surgery. Experienced observers interpreted the TMJ MRI images to extract features. Data containing those features were applied to build and validate prediction models using random forest and multilayer perceptron (MLP) techniques, the latter using the Keras framework, a recent deep learning architecture. The area under the receiver operating characteristic (ROC) curve (AUC) was used to compare the performances of the models. MLP produced the best performance (AUC 0.940), followed by random forest (AUC 0.918) and disc shape alone (AUC 0.791). The MLP and random forest were also superior to previously reported results using MRI (AUC 0.808) and MRI-based nomogram (AUC 0.889). Implementing deep learning showed superior performance in predicting disc perforation in TMJ compared to conventional methods and previous reports.

The present study investigated to what extent a systematic evaluation of electronic condylar motion recordings leads to reproducible results in different examiners. The study was based on the anonymized condylar motion recordings of 20 patients (Cadiax compact II system). These were recruited consecutively from the examinations in a center specializing in diagnosing and managing temporomandibular disorders (TMD). Four trained practitioners independently evaluated the identical movement recordings of all patients after calibration. The evaluation was based on the previously published evaluation system. The results were recorded digitally in a database. The findings were then compared, and the matching values were determined (Fleiss' Kappa). The evaluation, according to Fleiss' Kappa, showed that the consistency of the assessment of the findings among the examiners is excellent (mean value 0.88, p < 0.00001). The study shows that calibrated dentists achieved reproducible results using this evaluation system and computer-assisted reporting. Good reproducibility confirms the reliability of systematic evaluation of clinical motion analysis. The ambiguities uncovered and eliminated in the study should avoid misunderstandings in the future. Both factors establish the prerequisites for applying condylar motion analysis in clinical practice.

Gingival inflammation grade serves as a well-established index in periodontitis. The aim of this study was to develop a deep learning network utilizing a novel feature extraction method for the automatic assessment of gingival inflammation. T-distributed Stochastic Neighbor Embedding (t-SNE) was utilized for dimensionality reduction. A convolutional neural network (CNN) model based on DenseNet was developed for the identification and evaluation of gingival inflammation. To enhance the performance of the deep learning (DL) model, a novel teeth removal algorithm was implemented. Additionally, a Grad-CAM +  + encoder was applied to generate heatmaps for computer visual attention analysis. The mean Intersection over Union (MIoU) for the identification of gingivitis was 0.727 ± 0.117. The accuracy rates for the five inflammatory degrees were 77.09%, 77.25%, 74.38%, 73.68% and 79.22%. The Area Under the Receiver Operating Characteristic (AUROC) values were 0.83, 0.80, 0.81, 0.81 and 0.84, respectively. The attention ratio towards gingival tissue increased from 37.73% to 62.20%, and within 8 mm of the gingival margin, it rose from 21.11% to 38.23%. On the gingiva, the overall attention ratio increased from 51.82% to 78.21%. The proposed DL model with novel feature extraction method provides high accuracy and sensitivity for identifying and grading gingival inflammation.

Thickened fluids are commonly used in the medical management of individuals who suffer swallowing difficulty (known as dysphagia). Previous studies have shown that the rheological properties of a liquid affect the flow behavior of the bolus in swallowing, such as pharyngeal transit time. While there is no doubt that shear rheology is a highly important factor for bolus flow, it is suspected that extensional properties of a liquid bolus also plays an important role in swallowing, due to elongation of the bolus as it flows through the oropharynx. Our aim in this work was to observe the effect of extensional viscosity on pharyngeal transit time and elongation of the bolus during swallowing. Eight samples of thickened liquid barium that were shear-controlled, but varied in extensional viscosity and two samples that were extensional-controlled, but varied in shear viscosity were swallowed by eight healthy individuals. Data were collected under lateral view of videofluoroscopy swallow study (VFSS); measures of pharyngeal transit time and the ratio of the length to the width of the bolus on the frame of Upper Esophageal Sphincter (UES) opening were taken from the VFSS recordings. It was observed that the pharyngeal transit time generally increases when the fluids are thickened to higher IDDSI consistency. Additionally, higher extensional viscosity fluids reduced the elongation of the bolus during swallowing, thus potentially reducing the risk of post-swallow residue due to bolus breakage. This study confirmed the relevance of the extensional viscosity of the bolus in swallowing.

Tooth extraction is a risk factor for the development of osteonecrosis of the jaw following treatment with antiresorptive drugs (ARDs), but not all extraction sites develop this pathology. Therefore, we aimed to identify local radiographic predictors of Medication-Related Osteonecrosis of the Jaw (MRONJ) in panoramic images of oncologic patients undergoing tooth extraction. Based on a retrospective longitudinal cohort study design, patients were included if undergoing one or more tooth extraction, with at least one administration of ARDs, and presence of pre- and post-operative panoramic radiographs. After data collection, blinded and independent observations were performed. Eleven distinct imaging-related parameters were assessed preoperatively and five postoperatively, at each extraction site. A case–control and subgroup analysis assessing MRONJ development was performed. Significance level is set to 0.05 (5%). A total of 77 oncologic patients were selected, undergoing 218 tooth extractions, from which 63 teeth (29%) in 39 patients (51%) developed MRONJ. Results showed that patients developed significantly more MRONJ with longer ARD treatment ( p  = 0.057), teeth with absent and incomplete endodontic fillings with caries, widened periodontal ligament space and/or periapical lesions ( p  = 0.005), and sclerotic and heterogenous bone patterns ( p  = 0.005). In conclusion, tooth extraction sites presenting with infections and bone sclerosis are at higher risk to develop MRONJ.

The complexity of oral ulcerations poses considerable diagnostic and therapeutic challenges to oral specialists. The expert consensus was conducted to summarize the diagnostic work-up for difficult and complicated oral ulcers, based on factors such as detailed clinical medical history inquiry, histopathological examination, and ulceration-related systemic diseases screening. Not only it can provide a standardized procedure of oral ulceration, but also it can improve the diagnostic efficiency, in order to avoid misdiagnosis and missed diagnosis.

Human enamel is composed mainly of apatite. This mineral of sorption properties is susceptible to chemical changes, which in turn affect its resistance to dissolution. This study aimed to investigate whether metal leakage from orthodontic appliances chemically alters the enamel surface during an in vitro simulated orthodontic treatment. Totally 107 human enamel samples were subjected to the simulation involving metal appliances and cyclic pH fluctuations over a period of 12 months in four complimentary experiments. The average concentrations and distribution of Fe, Cr, Ni, Ti and Cu within the enamel before and after the experiments were examined using ICP‒MS and LA‒ICP‒MS techniques. The samples exposed to the interaction with metal appliances exhibited a significant increase in average Fe, Cr and Ni (Kruskal–Wallis, p < 0.002) content in comparison to the control group. The outer layer, narrow fissures and points of contact with the metal components showed increased concentrations of Fe, Ti, Ni and Cr after simulated treatment, conversely to the enamel sealed with an adhesive system. It has been concluded that metal leakage from orthodontic appliances chemically alters enamel surface and microlesions during experimental in vitro simulated treatment.