Increased surface roughness and discoloration of the direct restorative materials used in pediatric patients affect the longevity of restorations and impair children’s oral health. Many factors can alter these properties. One of these factors is the intake of dietary supplements. It is crucial to predict the properties of restorative materials when exposed to dietary supplements to maintain the dental care of children. Thus, this study aimed to investigate the effect of various syrup-formed dietary supplements on the average surface roughness and color stability of current restorative materials used in pediatric dentistry. Seven different restorative materials (conventional glass ionomer [Fuji IX GP], resin-modified glass ionomer, [Fuji II LC], zirconia-reinforced glass ionomer [Zirconomer Improved], polyacid-modified composite resin [Dyract^®XTRA], bulk-fill glass hybrid restorative [Equia Forte HT Fill], conventional resin composite [Charisma Smart], and resin composite with reactive glass fillers [Cention N]) were tested. The specimens prepared from each type of restorative material were divided into five subgroups according to dietary supplements (Sambucol Kids, Resverol, Imunol, Umca, and Microfer). These specimens were immersed daily in supplement solution over a period of 28 days. Surface roughness and color difference measurements were performed at baseline and at the 7th and 28th days. The color difference and Ra values showed that there was an interaction among the type of restorative material, type of dietary supplement, and immersion time factors (p < 0.05). Whereas lower Ra values were found in the composite resin group, the highest Ra values were found in the conventional glass ionomer group. All supplements caused increasing color difference values, and Resverol and Umca showed higher discoloration values above the clinically acceptable threshold. The intake of dietary supplement type, the immersion time of the dietary supplement, and the restorative material type affected the surface roughness and color stability of the tested direct restorative materials. All of the experimental groups showed higher Ra values than clinically acceptable surface roughness values (0.2 µm). The color difference values also increased with the immersion time.

Amaç: Diş çürüğü özellikle gelişmekte olan ülkelerde ciddi bir sağlık problemi olarak karşımıza çıkmaya devam etmektedir. Tedavi edilmemiş diş çürüklerinin yol açtığı apse, ülserasyon ve fistül gibi komplikasyonların prevalansını araştıran sınırlı sayıda araştırma bulunmaktadır. Bu çalışmanın amacı, bir grup çocukta tedavi edilmemiş diş çürüklerinin klinik sonuçlarının prevalansının araştırılmasıdır. Gereç ve Yöntem: Çalışma 1-31 Mart 2012 tarihleri arasında Gazi Üniversitesi Diş Hekimliği Fakültesi Pedodonti Anabilim Dalı Kliniğinde yaşları 5-12 arası olan 1200 çocuk üzerinde yürütüldü. Daimi ve süt dişlerinde diş çürükleri DMFT/dmft ve PUFA/pufa indeksleri ile skorlandı (D/d: çürük, M/m: kayıp, F/f: dolgulu diş, P/p: pulpayı içeren çürük lezyonu, U/u: kök parçalarından dolayı mukozanın ülserasyonu, F/f: fistül, A/a: apse). Bulgular: Çocuklarda DMFT indeksi 2.34 ± 1.37 ve dmft indeksi 4.25 ± 3.46 olarak bulundu. Daimi ve süt dişleri için PUFA/pufa prevalansı sırasıyla %2.30 ve %22.25 olarak belirlendi. Hem süt hem daimi dişlerde en yüksek skoru pulpayı içeren diş çürüğü oluşturdu (süt dişlerinde %11.24 ve daimi dişlerde %1.67). Bunu apse ve fistülizasyon izledi. Sonuç: Seçilen popülasyonda tedavi edilmemiş süt dişi çürüklerinin ve yumuşak dokudaki klinik sonuçlarının prevalansı yüksek bulundu. PUFA/pufa indeksi diş çürüklerini değerlendirmek amacıyla var olan çürük indekslerini tamamlayıcı bir epidemiyolojik araç olarak görülmektedir.

The application of artificial intelligence (AI) technologies in pediatric dentistry has expanded rapidly and is assuming an increasingly important role in the assessment of oral health and diagnostic processes in children. In particular, image-based analyses and data-driven predictive models offer significant potential to enhance diagnostic accuracy and reduce observer-dependent variability. This review addresses AI applications in pediatric dentistry within a structured framework, summarizing the methodological foundations of machine learning and deep learning approaches while critically evaluating the current body of evidence. It further identifies key limitations in the existing literature and outlines future research priorities, aiming to provide a perspective for the safe and sustainable clinical integration of AI in pediatric dentistry.

Background: Dental anxiety is a prevalent condition in pediatric oral healthcare and linked with multiple etiologic factors. Although sociodemographic factors are frequently examined, the influence of internal psychological constructs such as self-esteem remains underexplored in children. This cross-sectional study aims to evaluate the association between dental anxiety and self-esteem among school-age Turkish children. Methods: The study was conducted with 204 participants aged 7–12 years. Dental anxiety and self-esteem were assessed using Corah’s Dental Anxiety Scale and the Rosenberg Self-Esteem Scale, respectively. Group comparisons were performed with the Mann–Whitney U and Kruskal–Wallis tests, and their association was examined with Spearman’s rank correlation. Independent predictors of dental anxiety were further identified through a stepwise multiple linear regression. Results: Dental anxiety was prevalent in 24.5% of participants. No significant differences in anxiety or self-esteem were found by gender, age, or socioeconomic status (p > 0.05). A moderate negative correlation (r = −0.301, p < 0.001) was observed between self-esteem and dental anxiety. Regression analysis confirmed self-esteem as the only significant independent predictor of dental anxiety (Adjusted R² = 0.080, p < 0.001) in this model. Conclusions: Findings indicate that self-esteem is independently associated with pediatric dental anxiety, although the explained variance was modest. Whether incorporating children’s psychological profile into behavioral management improves clinical outcomes remains to be investigated.