Predicting the Risk of Maxillary Canine Impaction Based on Maxillary Measurements Using Supervised Machine Learning.

OBJECTIVES: To predict palatally impacted maxillary canines based on maxilla measurements through supervised machine learning techniques. MATERIALS AND METHODS: The maxilla images from 138 patients were analysed to investigate intermolar width, interpremolar width, interpterygoid width, maxillary length, maxillary width, nasal cavity width and nostril width, obtained through cone beam computed tomography scans. The predictive models were built using the following machine learning algorithms: Adaboost Classifier, Decision Tree, Gradient Boosting Classifier, K-Nearest Neighbours (KNN), Logistic Regression, Multilayer Perceptron Classifier (MLP), Random Forest Classifier and Support Vector Machine (SVM). A 5-fold cross-validation approach was employed to validate each model. Metrics such as area under the curve (AUC), accuracy, recall, precision and F1 Score were calculated for each model, and ROC curves were constructed. RESULTS: The predictive model included four variables (two dental and two skeletal measurements). The interpterygoid width and nostril width showed the largest effect sizes. The Gradient Boosting Classifier algorithm exhibited the best metrics, with AUC values ranging from 0.91 [CI95% = 0.74-0.98] for test data to 0.89 [CI95% = 0.86-0.94] for crossvalidation. The nostril width variable demonstrated the highest importance across all tested algorithms. CONCLUSION: The use of maxillary measurements, through supervised machine learning techniques, is a promising method for predicting palatally impacted maxillary canines. Among the models evaluated, both the Gradient Boosting Classifier and the Random Forest Classifier demonstrated the best performance metrics, with accuracy and AUC values exceeding 0.8, indicating strong predictive capability.

Lateral cephalometric parameters among Arab skeletal classes II and III patients and applying machine learning models.

BACKGROUND: The World Health Organization considers malocclusion one of the most essential oral health problems. This disease influences various aspects of patients' health and well-being. Therefore, making it easier and more accurate to understand and diagnose patients with skeletal malocclusions is necessary. OBJECTIVES: The main aim of this research was the establishment of machine learning models to correctly classify individual Arab patients, being citizens of Israel, as skeletal class II or III. Secondary outcomes of the study included comparing cephalometric parameters between patients with skeletal class II and III and between age and gender-specific subgroups, an analysis of the correlation of various cephalometric variables, and principal component analysis in skeletal class diagnosis. METHODS: This quantitative, observational study is based on data from the Orthodontic Center, Jatt, Israel. The experimental data consisted of the coded records of 502 Arab patients diagnosed as Class II or III according to the Calculated_ANB. This parameter was defined as the difference between the measured ANB angle and the individualized ANB of Panagiotidis and Witt. In this observational study, we focused on the primary aim, i.e., the establishment of machine learning models for the correct classification of skeletal class II and III in a group of Arab orthodontic patients. For this purpose, various ML models and input data was tested after identifying the most relevant parameters by conducting a principal component analysis. As secondary outcomes this study compared the cephalometric parameters and analyzed their correlations between skeletal class II and III as well as between gender and age specific subgroups. RESULTS: Comparison of the two groups demonstrated significant differences between skeletal class II and class III patients. This was shown for the parameters NL-NSL angle, PFH/AFH ratio, SNA angle, SNB angle, SN-Ba angle. SN-Pg angle, and ML-NSL angle in skeletal class III patients, and for S-N (mm) in skeletal class II patients. In skeletal class II and skeletal class III patients, the results showed that the Calculated_ANB correlated well with many other cephalometric parameters. With the help of the Principal Component Analysis (PCA), it was possible to explain about 71% of the variation between the first two PCs. Finally, applying the stepwise forward Machine Learning models, it could be demonstrated that the model works only with the parameters Wits appraisal and SNB angle was able to predict the allocation of patients to either skeletal class II or III with an accuracy of 0.95, compared to a value of 0.99 when all parameters were used ("general model"). CONCLUSION: There is a significant relationship between many cephalometric parameters within the different groups of gender and age. This study highlights the high accuracy and power of Wits appraisal and the SNB angle in evaluating the classification of orthodontic malocclusion.

PAINe - An Artificial Intelligence Based Virtual Assistant to Aid in the Differentiation of Pain of Odontogenic versus Temporomandibular Origin.

INTRODUCTION: Pain associated with temporomandibular dysfunction (TMD) is often confused with odontogenic pain, which is a challenge in endodontic diagnosis. Validated screening questionnaires can aid the identification and differentiation of the source of pain. Therefore, this study aimed to develop a virtual assistant based on artificial intelligence, using natural language processing techniques to automate the initial screening of patients with tooth pain. METHODS: The PAINe chatbot was developed in Python language, using the PyCharm environment and the 'openai' library to integrate the ChatGPT 4 API, and the 'streamlit' library for interface construction. The validated TMD Pain Screener questionnaire and one question about the current pain intensity was integrated into the chatbot to perform the differential diagnosis of TMD in patients with tooth pain. The responses' accuracy was evaluated in 50 random scenarios to compare the chatbot with the validated questionnaire. The Kappa coefficient was calculated to assess the agreement level between the chatbot responses and the validated questionnaire. RESULTS: The chatbot achieved an accuracy rate of 86% and a substantial level of agreement (Kappa = 0.70). Most responses were clear and provided adequate information about the diagnosis. CONCLUSIONS: The implementation of a virtual assistant using natural language processing, based on large language models, for initial differential diagnosis screening of patients with tooth pain, demonstrated substantial agreement between validated questionnaires and the chatbot. This approach emerges as a practical and efficient option for screening these patients.

Influence of circadian rhythm on effects induced by mechanical strain in periodontal ligament cells.

PURPOSE: The aim of this study was to investigate the influence of mechanical strain on clock gene function in periodontal ligament (PDL) cells. Furthermore, we wanted to analyze whether effects induced by mechanical stress vary in relation to the circadian rhythm. METHODS: Human PDL fibroblasts were synchronized in their circadian rhythm with dexamethasone and stretched over 24 h. Unstretched cells served as controls. Gene expression of the core clock genes were analyzed at 4 h intervals by quantitative real-time polymerase chain reaction (qRT-PCR). Time points 0 h (group SI1) and 12 h (group SI2) after synchronization served as starting points of a 4 h force application period. Collagen-1α (COL-1α/Col-1α), interleukin-1ß (IL1-ß), and runt-related transcription factor 2 (RUNX2/Runx2) were assessed by qRT-PCR and enzyme-linked immunosorbent assay (ELISA) after 2 and 4 h. Statistical analysis comprised one-way analysis of variance (ANOVA) and post hoc tests. RESULTS: After synchronization, the typical pattern for clock genes was visible in control cells over the 24 h period. This pattern was significantly altered by mechanical strain. Under tensile stress, ARNTL gene expression was reduced, while Per1 and 2 gene expression were upregulated. In addition, mechanical stress had a differential effect on the expression of Col-1α and IL1­ß depending on its initiation within the circadian rhythm (group SI1 vs group SI2). For RUNX2, no significant differences in the two groups were observed. CONCLUSION: Our results suggest that mechanical stress affects the molecular peripheral oscillator of PDL cells. Vice versa, the circadian rhythm also seems to partially influence the effects that mechanical stress exerts on PDL cells.

Sex determination through maxillary dental arch and skeletal base measurements using machine learning.

BACKGROUND: Cranial, facial, nasal, and maxillary widths have been shown to be significantly affected by the individual's sex. The present study aims to use measurements of dental arch and maxillary skeletal base to determine sex, employing supervised machine learning. MATERIALS AND METHODS: Maxillary and mandibular tomographic examinations from 100 patients were analyzed to investigate the inter-premolar width, inter-molar width, maxillary width, inter-pterygoid width, nasal cavity width, nostril width, and maxillary length, obtained through Cone Beam Computed Tomography scans. The following machine learning algorithms were used to build the predictive models: Logistic Regression, Gradient Boosting Classifier, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Multi-Layer Perceptron Classifier (MLP), Decision Tree, and Random Forest Classifier. A 10-fold cross-validation approach was adopted to validate each model. Metrics such as area under the curve (AUC), accuracy, recall, precision, and F1 Score were calculated for each model, and Receiver Operating Characteristic (ROC) curves were constructed. RESULTS: Univariate analysis showed statistical significance (p < 0.10) for all skeletal and dental variables. Nostril width showed greater importance in two models, while Inter-molar width stood out among dental measurements. The models achieved accuracy values ranging from 0.75 to 0.85 on the test data. Logistic Regression, Random Forest, Decision Tree, and SVM models had the highest AUC values, with SVM showing the smallest disparity between cross-validation and test data for accuracy metrics. CONCLUSION: Transverse dental arch and maxillary skeletal base measurements exhibited strong predictive capability, achieving high accuracy with machine learning methods. Among the evaluated models, the SVM algorithm exhibited the best performance. This indicates potential usefulness in forensic sex determination.

Do SOD2 and SOD3 gene polymorphisms impact the oral health-related quality of life in Para athletes?

The aim of this study was to evaluate whether polymorphisms in SOD2 and SOD3 genes modulate the oral health-related quality of life (OHRQoL) of Para athletes with dental caries experience. The cross-sectional study included 264 Para athletes (143 in athletics, 61 in weightlifting and 60 in swimming). A trained and calibrated team recorded the decayed, missing and filled teeth index (DMFT). The Brazilian version of the Oral Health Impact Profile (OHIP-14) was used to measure OHRQoL. Genomic DNA was extracted from the athletes' saliva, and genetic polymorphisms in the SOD2 (rs5746136 and rs10370) and SOD3 (rs2855262 and rs13306703) genes were analyzed by real-time polymerase chain reaction. Univariate and multivariate analyses were performed. A multivariate General Linear Model analysis, adjusted for sex, revealed that the SOD3 gene polymorphism (rs2855262) had a significant effect on the psychological disability domain [codominant (p = 0.045) and recessive (p=0.038) models]. The SOD2 gene polymorphism (rs5746136) had a significant effect on the total OHIP-14 score [dominant model (p = 0.038)] and the psychological discomfort [dominant model (p = 0.034)] and physical disability [codominant model (p=0.037)] domains. Presence of the SOD2 rs10370 polymorphism led to statistical differences in the total score [codominant (p = 0.026) and dominant (p = 0.023) models] and the handicap domain scores [codominant (p = 0.027) and dominant (p = 0.032) models]. Polymorphisms of the SOD2 and SOD3 genes may be important biomarkers of OHRQoL in Para athletes with dental caries experience.

Genetic polymorphisms associated with developmental defects of enamel: A systematic review.

BACKGROUND: Polymorphisms in genes related to enamel formation and mineralization may increase the risk of developmental defects of enamel (DDE). AIM: To evaluate the existing literature on genetic polymorphisms associated with DDE. DESIGN: This systematic review was registered in the PROSPERO (CRD42018115270). The literature search was performed in PubMed, Scopus, Web of Science, LILACS, BBO, Cochrane Library, and in the gray literature. Observational studies assessing the association between DDE and genetic polymorphism were included. The Newcastle-Ottawa Scale was used to assess the risk of bias. RESULTS: One thousand one hundred and forty-six articles were identified, and 28 met the inclusion criteria. Five studies presented a low risk of bias. Ninety-two genes related to enamel development, craniofacial patterning morphogenesis, immune response, and hormone transcription/reception were included. Molar-incisor hypomineralization (MIH) and/or hypomineralization of primary second molars (HPSM) were associated with 80 polymorphisms of genes responsible for enamel development, immune response, morphogenesis, and xenobiotic detoxication. A significant association was found between the different clinical manifestations of dental fluorosis (DF) with nine polymorphisms of genes responsible for enamel development, craniofacial development, hormonal transcription/reception, and oxidative stress. Hypoplasia was associated with polymorphisms located in intronic regions. CONCLUSION: MIH, HPSM, DF, and hypoplasia reported as having a complex etiology are significantly associated with genetic polymorphisms of several genes.

Demirjian's and Cameriere's Methods for the Assessment of Dental Age Estimation in Children from a Southern Brazilian City.

The chronological age estimation of living individuals is a crucial part of forensic practice and clinical practice, such as in orthodontic treatment. It is well-known that methods for age estimation in living children should be tested on different populations. Ethnic affiliations in Brazil are divided into several major groups depending on the region, with the south of Brazil being known for its German immigration. (1) Background: This study aimed to evaluate the correlation between chronological age and dental age using Demirjian's method and Cameriere's method in a group of children from Joinville, South Brazil to investigate if both methods can be used to estimate dental age in this population. (2) Methods: The sample consisted of 229 panoramic radiographs (119 were males and were 110 females) from Brazilian children (ages ranging from 6 to 12 years). The chronological age at the time of the panoramic radiographic exam was calculated for each child. The dental age was estimated according to Demirjian's method and Cameriere's method. All continuous data were tested for normality by using the Shapiro-Wilk test. The Pearson correlation coefficient test was applied. An alpha of 5% (p < 0.05) was used for all analyses. (3) Results: The mean chronological age was 8.75 years. According to Demirjian's method, the mean dental age was 9.3 years, while according to Cameriere's method, the mean dental age was 8.66 years. A strong correlation between chronological age and dental age according to Demirjian (r = 0.776 and p < 0.0001) and Cameriere (r = 0.735 and p < 0.0001) was observed for both genders. (4) Conclusions: Both methods presented a good correlation with chronological age in the studied population and could be used to assess dental age in this population.

Correction: The investigation of WNT6 and WNT10A single nucleotide polymorphisms as potential biomarkers for dental pulp calcification in orthodontic patients.

[This corrects the article DOI: 10.1371/journal.pone.0288782.].

Frequency and variability of nonmetric dental crown traits of primary and permanent molars in a group of orthodontic patients.

BACKGROUND: The present study aimed to assess the frequency and variation of 13 nonmetric dental crown traits (NDCT) in permanent and primary molars in German orthodontic patients. METHODS: Dental records from orthodontic patients were screened and evaluated. First and second permanent and primary upper and lower molars (from left and right sides) were assessed. Teeth with cavitated dental caries, occlusal wear, restorations and obvious dental deformities were not evaluated. The NDCT for permanent molars were identified and scored according to the odontoscopic system developed by Arizona State University Dental Anthropology System (ASUDAS). The NDCT for primary molars were identified and scored according to ASUDAS, Hanihara's method and Sciulli's method. The χ2 test was used to investigate side preference and sexual dimorphism at a significance level of p ≤ 0.050. RESULTS: A total of 163 orthodontic patients (82 males and 81 females) aged 8-14 years were included. A sexual dimorphism was observed for the hypocone in first upper permanent molar (p = 0.041). The protostylid was observed in lower permanent molars (range 2.1-10%). Males presented more hypoconulid than females (p = 0.019). Only females presented the distal trigonid crest in lower first permanent molars (p = 0.002). The most common groove pattern in primary molars was Y; male presented more Y grade than females in the lower second primary molar (p = 0.039). Asymmetry was observed in some traits, ranging from 0 to 100%. CONCLUSION: The present study showed the frequency of NDCT of molars in German orthodontic patients and demonstrated that some traits present sexual dimorphism.

Association of defects of enamel with polymorphisms in the vitamin D receptor and parathyroid hormone genes.

This cross-sectional study aimed to investigate the association between developmental defects of enamel (DDE) and single nucleotide polymorphisms (SNPs) in the genes encoding the vitamin D receptor (VDR) and parathyroid hormone (PTH). Orthodontic patients receiving treatment at a dental school were selected through convenience sampling. Intra-oral photographs were used to assess DDE, which were classified according to the criteria proposed by Ghanim et al. (2015) by a single calibrated examiner (Kappa>0.80). Enamel hypoplasia, molar-incisor hypomineralization (MIH), hypomimineralized second primary molar (HSPM), and non-MIH/HSPM demarcated opacities were considered for the analysis. Genomic DNA was extracted from buccal cells. The SNPs in VDR (rs7975232) and PHT (rs694, rs6256, and rs307247) were genotyped using real-time polymerase chain reactions (PCR). Statistical analyses were performed using the PLINK software (version 1.03, designed by Shaun Purcell, EUA). Chi-square or Fisher's exact tests were performed at a significance level of 5%. Ninety-one (n=91) patients (49 females and 42 males) (mean age of 14.1±5.8 years) were included. The frequency of DDE was 38.5% (35 patients). Genotype distributions were in Hardy-Weinberg equilibrium. No significant statistical association was found between DDE and the SNPs evaluated. A borderline association (p=0.09) was observed between DDE and the CC haplotype for SNP rs7975232 in VDR. In conclusion, the selected SNPs in VDR and PTH genes were not associated with DDE in the studied samples.

Is There Variation in the Morphology of the Frontal Sinus in Individuals with Different Craniofacial Patterns? A Systematic Review with Meta-Analysis.

To evaluate differences in the morphology of the frontal sinus in adolescents and adults with different craniofacial patterns, searches up to April 2024 were conducted in six databases and other information sources to identify observational studies. Study selection, data extraction, and quality assessment using the NOS scale were performed independently by two reviewers. Random effects meta-analyses were conducted to estimate the difference in frontal sinus measurements between different craniofacial skeletal patterns (α = 0.05). The certainty of the evidence was evaluated according to GRADE. Fourteen studies were included in the review. All studies had methodological limitations that affected their quality. The syntheses showed that skeletal Class II subjects presented a significantly smaller width of the frontal sinus than skeletal Class I subjects (MD = 0.56; 95% CI: 0.38, 0.74; p < 0.0001; I2 = 3%). Skeletal Class III subjects showed a frontal sinus width (MD = -0.91; 95% CI: -1.35, -0.47; p < 0.0001; I2 = 36%) and area (MD = -28.13; 95% CI: -49.03, -7.23; p = 0.0084; I2 = 66%) significantly larger than those of the skeletal Class I subjects. The available evidence suggests a positive relationship between mandibular and frontal sinus size. There is limited evidence to make reliable estimates of the association of other craniofacial patterns and frontal sinus characteristics. These reported results are not conclusive and should be evaluated carefully due to the very low certainty of the evidence. The current evidence is scarce and consists of studies with methodological limitations; the results of the studies are often inconsistent, and the pooled estimates are imprecise. New high-quality research is still necessary.

Single Nucleotide Polymorphisms in RUNX2 and BMP2 contributes to different vertical facial profile.

The vertical facial profile is a crucial factor for facial harmony with significant implications for both aesthetic satisfaction and orthodontic treatment planning. However, the role of single nucleotide polymorphisms (SNPs) in the development of vertical facial proportions is still poorly understood. This study aimed to investigate the potential impact of some SNPs in genes associated with craniofacial bone development on the establishment of different vertical facial profiles. Vertical facial profiles were assessed by two senior orthodontists through pre-treatment digital lateral cephalograms. The vertical facial profile type was determined by recommended measurement according to the American Board of Orthodontics. Healthy orthodontic patients were divided into the following groups: "Normodivergent" (control group), "Hyperdivergent" and "Hypodivergent". Patients with a history of orthodontic or facial surgical intervention were excluded. Genomic DNA extracted from saliva samples was used for the genotyping of 7 SNPs in RUNX2, BMP2, BMP4 and SMAD6 genes using real-time polymerase chain reactions (PCR). The genotype distribution between groups was evaluated by uni- and multivariate analysis adjusted by age (alpha = 5%). A total of 272 patients were included, 158 (58.1%) were "Normodivergent", 68 (25.0%) were "Hyperdivergent", and 46 (16.9%) were "Hypodivergent". The SNPs rs1200425 (RUNX2) and rs1005464 (BMP2) were associated with a hyperdivergent vertical profile in uni- and multivariate analysis (p-value < 0.05). Synergistic effect was observed when evaluating both SNPs rs1200425- rs1005464 simultaneously (Prevalence Ratio = 4.0; 95% Confidence Interval = 1.2-13.4; p-value = 0.022). In conclusion, this study supports a link between genetic factors and the establishment of vertical facial profiles. SNPs in RUNX2 and BMP2 genes were identified as potential contributors to hyperdivergent facial profiles.

Mandibular and dental measurements for sex determination using machine learning.

The present study tested the combination of mandibular and dental dimensions for sex determination using machine learning. Lateral cephalograms and dental casts were used to obtain mandibular and mesio-distal permanent teeth dimensions, respectively. Univariate statistics was used for variables selection for the supervised machine learning model (alpha = 0.05). The following algorithms were trained: logistic regression, gradient boosting classifier, k-nearest neighbors, support vector machine, multilayer perceptron classifier, decision tree, and random forest classifier. A threefold cross-validation approach was adopted to validate each model. The areas under the curve (AUC) were computed, and ROC curves were constructed. Three mandibular-related measurements and eight dental size-related dimensions were used to train the machine learning models using data from 108 individuals. The mandibular ramus height and the lower first molar mesio-distal size exhibited the greatest predictive capability in most of the evaluated models. The accuracy of the models varied from 0.64 to 0.74 in the cross-validation stage, and from 0.58 to 0.79 when testing the data. The logistic regression model exhibited the highest performance (AUC = 0.84). Despite the limitations of this study, the results seem to show that the integration of mandibular and dental dimensions for sex prediction would be a promising approach, emphasizing the potential of machine learning techniques as valuable tools for this purpose.

Influence of preventive remineralizing techniques on surface roughness and volume loss of dentin submitted to erosive and/or abrasive challenges.

Background: The objective this study was to evaluate the influence of preventive remineralizing techniques on surface roughness and volume loss of dentin submitted to erosive and/or abrasive challenges. Material and Methods: One hundred and eighty specimens of bovine root dentin were made; half of each was isolated (without treatment - WT) and half was subjected to the following remineralizing techniques: fluoride varnish (FV); Regenerate Boosting Serum® (RBS); Er,Cr:YSGG laser (L); fluoride varnish+laser (FV+L); Regenerate Boosting Serum®+laser (RBS+L). The specimens were submitted to erosive, abrasive and erosive followed by abrasive challenge. Erosion was carried out for 5 minutes, twice a day for 10 days. Abrasion was performed with an electric toothbrush and slurry solution for 60 seconds. The evaluation was performed by confocal laser scanning microscopy. Analysis of variance and Tukey tests were used for surface roughness; volume loss comparison was performed using the Kruskal-Wallis test and Dunn's post-hoc (p<0.05). Results: There was no statistically significant difference in the surface roughness of the reference area in relation to the areas submitted to different types of treatment and challenges (p>0.05). Regarding volume loss, the untreated group submitted to erosive/abrasive challenges showed greater percentage of volume loss compared to the other groups (p<0.05). Conclusions: It is concluded that preventive remineralizing techniques are effective in maintaining dentin volume after erosive/abrasive challenges. Key words:YSGG lasers, Dentin, Erosion, Tooth Abrasion.

Calcification patterns and morphology of Sella turcica are related to anteroposterior skeletal malocclusions: A cross-sectional study.

BACKGROUND: The sphenoid bone is an irregular, unpaired, symmetrical bone located in the middle of the anterior skull and is involved in craniofacial growth and development. Since the morphology of Sella turcica (ST) is associated with different craniofacial patterns, this study aimed to investigate if there is a correlation between ST morphology on the one hand and sagittal craniofacial patterns on the other hand. METHODS: This study was conducted with a convenience sample that included Brazilian individuals undergoing orthodontic treatment. Lateral cephalograms were used to evaluate the calcification pattern and morphology of ST, as well as skeletal class by analyzing the ANB angle. Pearson's chi-square test with Bonferroni post-hoc test was performed to evaluate the association between ST calcification pattern and morphology, and anteroposterior skeletal malocclusion. The established significance level was 0.05. RESULTS: The study collective was comprised of 305 orthodontic patients (178 (58.4 %) female, 127 (41.6 %) male), who had a mean age of 23.2 (±10.6) years. 131 participants (42.9 %) presented skeletal class I, 142 (46.6%) skeletal Class II, and 32 (10.5%) had a skeletal class III. The degree of prognathism of the mandible showed a homogenous distribution within the study collective (91 (29.9 %) orthognathic, 100 (32.9 %) retrognathic, 113 (37.2 %) prognathic mandible). Concerning the maxilla, 92 (30.2%) individuals presented an orthognathic upper jaw, whereas 60 (19.7%) showed maxillary retrognathism and 153 (50.2%) maxillary prognathism. Compared to patients with skeletal class I, skeletal class III individuals presented significantly more hypertrophic posterior clinoid process (p<0.007) and pyramidal shape of the dorsum of the ST (p<0.038). CONCLUSIONS: Our results suggest that the hypertrophic posterior clinoid process and pyramidal shape of the ST dorsum are more prevalent in individuals with skeletal class III malocclusion.

Exploring the sex-associated differences in molars fused roots.

BACKGROUND: Human sexual dimorphism is associated with many biological characteristics, including dental variables. OBJECTIVES: To investigate if molars fused roots present sex-associated differences. METHODS: Panoramic radiographs were used to investigate the frequency and distribution of permanent molars fused roots. Only patients with all first and second permanent molars were included. Third molars were not investigated. Any molar with roots fused apical to the usual furcal position were considered molar fused roots. Comparisons between males and females were performed using chi-square or Fisher's and Mann-Whitney tests and the established alpha was 5% (p<0.05). Sex-differential liability models were also proposed. RESULTS: A total of 84 males and 86 females were included and 1360 molars were analyzed. Among them, 46 (26.06%) present at least one molar with fused root. Second maxillary molars were the most affected teeth. There was an association between sex and molars with fused roots. Females had a 3.4 higher chance to present fused roots than males (OR=3.4, CI 95% 1.6-6.8; p=0.0008). The female: male ratio of molars with fused roots was 2.5:1. The number of molars with fused roots ranged from 1 to 6 per patient, and the mean number of Females presented more molars with fused roots (mean = 1.01; standard deviation = 1.52) than males (mean = 0.31; standard deviation = 0.85) (p<0.05). CONCLUSIONS: Molar fused root of permanent teeth presents sex-associated differences, in which females are more affected than males. Our results support sex-differential liability models for molars fused roots.

BMP2 rs1005464 is associated with mandibular condyle size variation.

This study aimed to evaluate the association between single nucleotide polymorphisms (SNPs) in endochondral development-related genes and mandibular condyle shape, size, volume, and symmetry traits. Cone-beam Computed Tomographies and genomic DNA from 118 individuals were evaluated (age range: 15-66 years). Data from twelve 3D landmarks on mandibular condyles were submitted to morphometric analyses including Procrustes fit, principal component analysis, and estimation of centroid sizes and fluctuating asymmetry scores. Condylar volumes were additionally measured. Seven SNPs across BMP2, BMP4, RUNX2 and SMAD6 were genotyped. Linear models were fit to evaluate the effect of the SNPs on the mandibular condyles' quantitative traits. Only the association between BMP2 rs1005464 and centroid size remained significant after adjusting to account for the false discovery rate due to multiple testing. Individuals carrying at least one A allele for this SNP showed larger condylar size than common homozygotes GG (ß = 0.043; 95% CI: 0.014-0.071; P value = 0.028). The model including BMP2 rs1005464, age and sex of the participants explained 17% of the variation in condylar size. Shape, volume, and symmetry were not associated with the evaluated SNPs. These results suggest that BMP2 rs1005464 might be associated with variation in the mandibular condyles size.