Effect of electromagnetic fields and antioxidants on the trace element content of rat teeth Mehmet Sinan Dogan,1 Mehmet Cihan Yavas,2 Yasemin Yavuz,3 Sait Erdogan,4 Ä°smail Yener,4 Ä°brahim Simsek,1 Zeki Akkus,5 Veysel Eratilla,6 Abdulsamet Tanik,7 Mehmet Zulkuf Akdag2 1Department of Pediatric Dentistry, Faculty of Dentistry, Harran University, Å?anliurfa, 2Department of Biophysics, Faculty of Medicine, 3Department of Restorative Dentistry, Faculty of Dentistry, 4Department of Chemistry, Faculty of Science, 5Department of Biostatistics, Faculty of Medicine, 6Department of Prosthodontics, 7Department of Periodontology, Faculty of Dentistry, Dicle University, Diyarbakir, Turkey The purpose of this study was to examine the possible effect of extremely low-frequency electromagnetic fields (ELF-EMFs), from a high-voltage source, on rat teeth in terms of changes in trace elements (TEs) and the effect of antioxidants (melatonin [MLT] and Ganoderma lucidum [GL]) in counteracting these effects. We used adult male Wistar albino rats with a mean weight of 250–300 g and divided the rats into eight groups. The groups were subjected to an ELF-EMF that was applied with a high-voltage line for 8 hours/day for 26 days (Groups I, II, and III) or 52 days (Groups V, VI, and VII). Groups IV and VIII were the 26- and 52-day control/sham groups, respectively. Groups II and VI were treated with GL, and Groups III and VII were treated with MLT. MLT and GL were administered daily based on the weight of the animals and appropriate standards. At the end of the study, the rats were euthanized, and their anterior teeth were extracted. The teeth were preserved in pure water before evaluating the major TEs. At the end of the study, TE concentrations (in mg/kg) were assessed in the control and test groups. Compared with Group V, statistically significant differences in the concentrations of zinc (Zn) and strontium (Sr) were found for Group VII (ELF-EMF + MLT) (P<0.05). Therefore, ELF-EMF exposure can change the content of certain TEs in teeth and, after administering MLT and GL, the values of some of the TEs return to normal. Keywords: ELF-EMF, tooth, trace element, melatonin, Ganoderma lucidum

This study aims to evaluate the ability of an artificial intelligence (AI) model developed for use in the field of orthodontics to accurately and reliably classify skeletal maturation stages of individuals using hand–wrist radiographs. A total of 809 grayscale hand–wrist radiographs (250 × 250 px; pre-peak n = 400, peak n = 100, post-peak n = 309) were analyzed using four complementary image-based feature extraction methods: Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG), Zernike Moments (ZM), and Intensity Histogram (IH). These methods generated 2355 features per image, of which 2099 were retained after variance thresholding. The most informative 1250 features were selected using the ANOVA F-test and classified with a stacking-based machine learning (ML) architecture composed of Light Gradient Boosting Machine (LightGBM) and Logistic Regression (LR) as base learners, and Random Forest (RF) as the meta-learner. Across all evaluation folds, the average performance of the model was Accuracy = 83.42%, Precision = 84.48%, Recall = 83.42%, and F1 = 83.50%. The proposed model achieved 87.5% accuracy, 87.8% precision, 87.5% recall, and an F1-score of 87.6% in 10-fold cross-validation, with a macro-average area under the ROC curve (AUC) of 0.96. The pre-peak stage, corresponding to the period of maximum growth velocity, was identified with 92.5% accuracy. These findings indicate that integrating handcrafted radiographic features with ensemble learning can enhance diagnostic precision, reduce observer variability, and accelerate evaluation. The model provides an interpretable and clinically applicable AI-based decision-support tool for skeletal maturity assessment in orthodontic practice.

The aim of this study was to investigate the effect of deposition temperature on the structural, optical, morphological, and dielectric properties of yttria-stabilised zirconia (YSZ) films prepared by sol-gel spin-coating method. X-ray diffraction (XRD) measurements of YSZ films showed that the peaks of the cubic phase were prominent and the peak intensities increased with deposition temperature. The crystallite size, dislocation density, and microstrain of the thin films were identified by XRD. It was observed that the crystal size of the YSZ thin films increased from 16 nm to 22 nm with the deposition temperature. The surface roughness of the thin films was found to have changed as revealed by Atomic Force Microscopy (AFM) measurements. The roughness increased from 7.72 nm to 11.92 nm with increasing temperature. The optical transmittance of the YSZ thin films was investigated in the wavelength range 200-900 nm and was found to increase slightly with increasing deposition temperature. Metal-Oxide-Semiconductor (MOS) devices were fabricated from these YSZ materials for dielectric characterization. The dielectric properties of the Ag/YSZ/n-Si MOS structure were investigated. It was found that the capacitance, conductivity and other dielectric parameters of these structures are strongly frequency dependent.

Background: One of the aims of endodontic treatment is to control preoperative and postoperative pain. The present study evaluated the effects of local and systemic ibuprofen on postoperative pain. It aimed to determine the most effective method for relieving postoperative pain due to chemomechanical preparation. Material/Methods: Ninety patients with symptomatic apical periodontitis were randomly assigned to local ibuprofen, systemic ibuprofen, and control groups (n=30 each). Chemomechanical preparations were performed using a ProTaper Universal Ni-Ti rotary file under 2.5% sodium hypochlorite and 17% ethylenediaminetetraacetic acid irrigation. After the root canals were dried with sterile paper points, while Odontocide paste was applied into the root canals of the patients in the local ibuprofen group, calcium hydroxide paste was applied into the root canals of the patients in the systemic ibuprofen and control groups. Following completion of the endodontic treat-ment procedure, 200 mg ibuprofen was prescribed to patients in the systemic ibuprofen group. Friedman and Wilcoxon tests were used for statistical analysis. Results: Posttreatment pain scores were recorded at 6, 12, 24, and 48 h using a visual analogue scale. Although there were no significant differences between the local ibuprofen group (Odontocide) and the control group (Ultracal) (P > 0.05), pain scores in the systemic group (Ultracal+200 mg ibuprofen) were significantly lower than those in the other 2 groups (P < 0.05). Conclusions: These results indicate that systemic administration of ibuprofen is effective for postoperative pain relief.

Background: The aim of this study was to develop an artificial intelligence (AI)-based decision support model for evaluating the extraction indication of permanent first molars in pediatric patients using panoramic radiographs, and to investigate the potential contribution of this model to the clinical decision-making process. Methods: This retrospective observational study analyzed 1000 panoramic radiographs obtained from children aged 8–10 years who attended the Clinics of Batman University Faculty of Dentistry for routine dental examination. Among the radiographs meeting the inclusion criteria, a total of 176 panoramic images were selected based on dental maturation assessment using the Demirjian tooth development staging system. Cases in which the permanent second molar was classified as Demirjian stages E–F were labeled as “extraction indication present”, while the remaining stages were labeled as “extraction indication absent”. A balanced dataset was created, consisting of 88 cases in each group. Image features were extracted using Gabor filters and Histogram of Oriented Gradients (HOG). The selected features were analyzed using a Support Vector Machine (SVM) classifier with a radial basis function (RBF) kernel. Model performance was evaluated using accuracy, sensitivity, specificity, F1-score, and area under the receiver operating characteristic curve (ROC–AUC). Results: The proposed Gabor–HOG–SVM-based AI model achieved an overall classification accuracy of 77.78% with an AUC value of 0.77 in distinguishing between “extraction indication present” and “extraction indication absent” cases. For the extraction-indicated group, the sensitivity was 0.81 and the F1-score was 0.79, whereas for the non-indicated group, the sensitivity and F1-score were 0.74 and 0.77, respectively. No statistically significant differences were observed between the groups in terms of age or sex distribution (p > 0.05). Conclusions: This study demonstrates that artificial intelligence-based analysis of panoramic radiographic images can provide an objective and reproducible decision support approach for evaluating extraction indications of permanent first molars in pediatric patients. The proposed model should be considered as an adjunctive tool to reduce observer-dependent variability rather than a replacement for clinical judgment, and its clinical applicability should be further validated through multicenter and multi-parametric studies.

Introduction: Bifid mandibular canal (BMC) is often detected incidentally on radiological examination and can be observed in unilateral or bilateral forms. The correct localization of the BMC plays an important role in the prevention of complications such as paresthesia, anesthesia, bleeding, traumatic neuroma, which may occur during or after surgical operations on the mandible such as sagittal split ramus osteotomy, impacted third molar tooth extraction, and dental implant surgery. Objective: This study aims to retrospectively evaluate the prevalence of bifid mandibular canal (BMC) in the Southeastern Anatolian population via Conical Beam Computed Tomography (CBCT). Material and Method: In this retrospective study, CBCT images of 615 patients, who applied to the Department of Oral and Maxillofacial Surgery in the Faculty of Dentistry at Dicle University, Turkey, for various reasons from 2015 to 2020, is evaluated and cases with bifid mandibular canals are examined. The prevalence evaluation is conducted by statistical analyses in terms of sex and laterality. Results: According to the analyses, the BMC prevalence did not constitute a significant difference in terms of the age variable (p>0.05). The incidence of unilateral BMC was higher than bilateral BMC (p<0.05; p=0.016). Additionally, the prevalence of BMC was higher in males compared to females (p<0.05; p=0.008). Conclusion: BMC, which can be detected more easily and frequently via CBCT technology, is an anatomical formation that should be taken into account during oral and maxillofacial practices.