This systematic review aimed to investigate the relation between orthodontic treatment (OT) and the incidence of the gingival black triangle (GBT) after completing treatment with a fixed orthodontic appliance, as well as the associated risk factors and the level of alveolar bone. Electronic and hand searches were conducted in three electronic databases for relevant articles published up to March 2022. Retrieved articles went through a two-step screening procedure, and the risk of bias (RoB) was assessed by the Joanna Briggs Institute checklists. The incidence of GBT after OT was set as the primary outcome, while the secondary outcomes were the risk factors associated with GBT and alveolar bone loss following OT. Out of 421 papers, 5 were selected for the final analysis. The RoBs of three studies were moderate and the remaining two were low. The incidence of GBT following OT ranged from 38% to 58%. In addition, three studies reported that alveolar bone loss was reduced significantly following OT and associated with GBT, while one study found the opposite. Regarding the risk factors associated with GBT, the reported results attributed GBT to several factors including age, tooth-related factors, treatment duration, and soft tissue factors. The analysis indicates an increased incidence of GBT following OT; however, a firm conclusion cannot be drawn. Additionally, it was not possible to reach a consensus on risk factors associated with GBT due to the heterogeneity of the data. Therefore, further randomized clinical trials are highly recommended to draw a firm conclusion.

Malocclusion is a prevalent oral health concern worldwide, ranking third after dental caries and periodontal disease. Early identification and intervention in childhood can prevent its progression into adulthood. The Index of Orthodontic Treatment Need (IOTN) is widely used to assess malocclusion severity. However, global studies using the IOTN have reported varying malocclusion prevalence rates, which are influenced by socioeconomic and ethnic factors. This study aimed to examine the orthodontic treatment needs among Iraqi children aged 10–12. A total of 384 children (173 boys and 211 girls) were randomly selected from four distinct regions in Sulaimani, Iraq. Eligibility criteria included Iraqi children aged 10–12 years with no history of orthodontic treatment, non-nutritive sucking habits, or craniofacial anomalies. Evaluations took place in school environments, using criteria from the American Board of Orthodontics to assess overjet, reverse overjet, overbite, anterior openbite, and buccal crossbite. Malocclusion severity was categorized using the Dental Health Component of the IOTN. Data analysis included chi-square testing, and 95% confidence intervals to interpret findings. Most children had mild treatment needs (Grade 2: 36.2%), followed by no treatment required (Grade 1: 31.3%) and moderate needs (Grade 3: 24.5%). More severe cases were less common, with Grade 4 (4.7%) and Grade 5 (3.4%). Overbite was the most prevalent malocclusion requiring treatment, while overjet had the lowest demand. No significant gender differences were found (p > 0.05). Mild to moderate malocclusion was prevalent, with overbite and crossbite being the most frequent conditions requiring treatment. Overjet exhibited the lowest treatment demand, and gender differences were not significant, suggesting equal applicability of orthodontic programs to both boys and girls. Not applicable.

Additive manufacturing has introduced directly printed orthodontic aligners as an alternative to thermoforming. However, comparative data regarding thickness-dependent biomechanical accuracy remain limited. Therefore, this study aimed to evaluate the influence of fabrication method (thermoforming vs. direct 3D printing) and material thickness (0.76 mm vs. 1.0 mm) on the accuracy of rotational, tipping, and torque movements of different teeth under standardized in vitro conditions. Thirty-six standardized typodonts underwent digital staging (30° rotation, 10° mesial tipping, 10° positive torque). Aligners were fabricated via thermoforming (Zendura A) or direct 3D printing (Tera Harz TC-85). Movement was simulated using thermal activation (56 °C, 90 s). Pre- and post-movement scans were superimposed (Geomagic Control X), and accuracy was calculated as the percentage of achieved to programmed movement. Analyses were performed at both typodont and tooth levels. Statistical analysis was conducted using Jamovi (version 2.6.44), applying two-way ANOVA and Mann-Whitney U tests (p < 0.05). Aligner thickness significantly improved accuracy across all movement types (p < 0.001). In contrast, fabrication method showed inconsistent effects, with only isolated significant differences. Mesial tipping demonstrated the highest predictability (up to 92.67%), whereas torque showed the lowest (maximum 71.67%). Accuracy was generally higher in anterior teeth, with greater variability in posterior segments. No significant arch differences were observed. Aligner thickness is the primary determinant of biomechanical accuracy, with thicker aligners providing more predictable tooth movement. Fabrication method showed a secondary and variable influence, indicating that material thickness plays a more critical role in optimizing aligner biomechanics.

Purpose: To estimate the prevalence of three-rooted mandibular deciduous second molars (3RME) and three-rooted mandibular permanent first molars (3RM6) in Iraqi children and to evaluate their association using cone-beam computed tomography (CBCT). Methods: This retrospective cross-sectional study analyzed CBCT scans of Iraqi children aged 7– 12 years (N = 196). Root morphology was assessed in axial, coronal, and sagittal planes. Prevalence was calculated at the patient level (presence of ≥ 1 affected tooth). Associations between 3RME and 3RM6 were tested using the chi-square test, and age/sex were explored as predictors using logistic regression. Intra- and inter-examiner reliability were assessed with Cohen’s kappa. Results: Three-rooted morphology was identified in 3/196 children for 3RME (1.53%; 95% CI 0.52– 4.40) and 10/196 children for 3RM6 (5.10%; 95% CI 2.80– 9.14). A significant association was observed between 3RME and 3RM6 (χ²(4, N = 196) = 96.48, p < 0.001; Cramér’s V = 0.50). Age and sex were not significant predictors (p > 0.05). Conclusion: Three-rooted mandibular molars were uncommon in this Iraqi pediatric sample; however, 3RME co-occurred significantly with 3RM6, indicating a strong association that may be clinically useful for anticipatory diagnosis and treatment planning.

Artificial intelligence (AI) is rapidly transforming orthodontic practice by enhancing diagnostic accuracy, treatment planning, clinical decision-making, and patient management. This article reviews the current applications of AI in orthodontics, including automated cephalometric analysis, three-dimensional imaging interpretation, treatment outcome prediction, aligner therapy optimization, and digital workflow integration. AI-driven technologies have the potential to improve efficiency, reduce treatment time, and support personalized orthodontic care through data-driven insights and predictive analytics. Despite these advancements, challenges remain regarding data quality, algorithm transparency, ethical considerations, patient privacy, and the need for clinical validation. The article explores both the innovations and limitations associated with AI adoption in orthodontics and discusses future prospects for integrating machine learning and advanced computational tools into routine clinical practice. Continued collaboration between clinicians, researchers, and technology developers will be essential to maximize the benefits of AI while ensuring safe, effective, and patient-centered orthodontic care.