Combined uranium-series and electron spin resonance dating from the Pliocene fossil sites of Aves and Milo's palaeocaves, Bolt's Farm, Cradle of Humankind, South Africa.

Bolt's Farm is the name given to a series of non-hominin bearing fossil sites that have often been suggested to be some of the oldest Pliocene sites in the Cradle of Humankind, South Africa. This article reports the results of the first combined Uranium-Series and Electron Spin Resonance (US-ESR) dating of bovid teeth at Milo's Cave and Aves Cave at Bolt's Farm. Both tooth enamel fragments and tooth enamel powder ages were presented for comparison. US-ESR, EU and LU models are calculated. Overall, the powder ages are consistent with previous uranium-lead and palaeomagnetic age estimates for the Aves Cave deposit, which suggest an age between ~3.15 and 2.61 Ma and provide the first ages for Milo's Cave dates to between ~3.1 and 2.7 Ma. The final ages were not overly dependent on the models used (US-ESR, LU or EU), which all overlap within error. These ages are all consistent with the biochronological age estimate (<3.4->2.6 Ma) based on the occurrence of Stage I Metridiochoerus andrewsi. Preliminary palaeomagnetic analysis from Milo's Cave indicates a reversal takes place at the site with predominantly intermediate directions, suggesting the deposit may date to the period between ~3.03 and 3.11 Ma within error of the ESR ages. This further suggests that there are no definitive examples of palaeocave deposits at Bolt's Farm older than 3.2 Ma. This research indicates that US-ESR dating has the potential to date fossil sites in the Cradle of Humankind to over 3 Ma. However, bulk sample analysis for US-ESR dating is recommended for sites over 3 Ma.

The effect of birth weight on tooth development by Demirjian's method.

OBJECTIVES: The aim of this study was to investigate the impact of birth weight on tooth development in children aged 7-8 years. MATERIALS AND METHODS: This retrospective cohort study comprised 75 children born at Bint Al-Huda Hospital, Bojnurd, in 2013-2014. The children were categorized into three groups based on their birth weight: Normal Birth Weight (NBW), Low Birth Weight (LBW), and Very Low Birth Weight (VLBW). Panoramic radiographs were taken for orthodontic examination, and Demirjian's 8-teeth method was employed to determine dental age. The study compared dental and chronological age within each group. Data analysis utilized SPSS software version 26, employing One-way ANOVA and chi-square tests. Statistical significance was set at P ≤ 0.05. RESULTS: The mean difference in dental and chronological age for Very Low Birth Weight (VLBW) children was 0.22 ± 0.44 years, for Low Birth Weight (LBW) children it was 0.19 ± 0.45 years, and for Normal Birth Weight (NBW) children, it was 0.08 ± 0.46 years. Although the mean difference decreased with increasing birth weight, this trend did not achieve statistical significance (P = 0.55). Furthermore, no significant differences were observed between the weight groups (P = 0.529) or genders (P = 0.191).

Knowledge, attitudes, and practices among patients with combined dentition defect and non-functional impacted teeth toward tooth autotransplantation.

BACKGROUND: Tooth autotransplantation (TAT) is a surgical procedure involving the extraction of a tooth from one location and its subsequent transplantation into another alveolar socket within the same individual. This innovative treatment approach holds significant promise. Nonetheless, the potential recipients exhibit a limited level of awareness and understanding of this procedure. This study investigated the knowledge, attitudes, and practices (KAP) among patients with combined dentition defects and non-functional impacted teeth toward TAT. METHODS: This web-based cross-sectional study was conducted between December 2022 and February 2023 at one hospital. A self-designed questionnaire was developed to collect demographic information of the patients and assess their knowledge, attitudes, and practices toward TAT. RESULTS: A total of 533 valid questionnaires were collected. The mean knowledge, attitude, and practice scores were 5.55 ± 2.38 (possible range: 0-10), 26.82 ± 2.46 (possible range, 8-40), and 27.45 ± 7.40 (possible range, 9-45), respectively. CONCLUSION: The participants had insufficient knowledge, negative attitudes, and passive practices toward TAT. Targeted interventions should be implemented to improve the understanding and practice of TAT among patients with dentition defects.

Python tooth-inspired fixation device for enhanced rotator cuff repair.

Rotator cuff repair surgeries fail frequently, with 20 to 94% of the 600,000 repairs performed annually in the United States resulting in retearing of the rotator cuff. The most common cause of failure is sutures tearing through tendons at grasping points. To address this issue, we drew inspiration from the specialized teeth of snakes of the Pythonoidea superfamily, which grasp soft tissues without tearing. To apply this nondamaging gripping approach to the surgical repair of tendon, we developed and optimized a python tooth-inspired device as an adjunct to current rotator cuff suture repair and found that it nearly doubled repair strength. Integrated simulations, 3D printing, and ex vivo experiments revealed a relationship between tooth shape and grasping mechanics, enabling optimization of the clinically relevant device that substantially enhances rotator cuff repair by distributing stresses over the attachment footprint. This approach suggests an alternative to traditional suturing paradigms and may reduce the risk of tendon retearing after rotator cuff repair.

Roles of the histone methyltransferase SET domain bifurcated 1 in epithelial cells during tooth development.

OBJECTIVE: This study aimed to reveal the effects of SET domain bifurcated 1 (SETDB1) on epithelial cells during tooth development. DESIGN: We generated conditional knockout mice (Setdb1fl/fl,Keratin14-Cre+ mice), in which Setdb1 was deleted only in epithelial cells. At embryonic day 14.5 (E14.5), immunofluorescence staining was performed to confirm the absence of SETDB1 within the epithelium of tooth embryos from Setdb1fl/fl,Keratin14-Cre+ mice. Mouse embryos were harvested after reaching embryonic day 13.5 (E13.5), and sections were prepared for histological analysis. To observe tooth morphology in detail, electron microscopy and micro-CT analysis were performed at postnatal months 1 (P1M) and 6 (P6M). Tooth embryos were harvested from postnatal day 7 (P7) mice, and the epithelial components of the tooth embryos were isolated and examined using quantitative RT-PCR for the expression of genes involved in tooth development. RESULTS: Setdb1fl/fl,Keratin14-Cre+ mice exhibited enamel hypoplasia, brittle and fragile dentition, and significant abrasion. Coronal sections displayed abnormal ameloblast development, including immature polarization, and a thin enamel layer that detached from the dentinoenamel junction at P7. Electron microscopic analysis revealed characteristic findings such as an uneven surface and the absence of an enamel prism. The expression of Msx2, Amelogenin (Amelx), Ameloblastin (Ambn), and Enamelin (Enam) was significantly downregulated in the epithelial components of tooth germs in Setdb1fl/fl,Keratin14-Cre+ mice. CONCLUSIONS: These results indicate that SETDB1 in epithelial cells is important for tooth development and clarify the relationship between the epigenetic regulation of SETDB1 and amelogenesis imperfecta for the first time.

Dental Age Estimation in Northern Chinese Han Children and Adolescents Using Demirjian's Method Combined with Machine Learning Algorithms.

OBJECTIVES: To investigate the application value of combining the Demirjian's method with machine learning algorithms for dental age estimation in northern Chinese Han children and adolescents. METHODS: Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected. The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian's method. Various machine learning algorithms, including support vector regression (SVR), gradient boosting regression (GBR), linear regression (LR), random forest regression (RFR), and decision tree regression (DTR) were employed. Age estimation models were constructed based on total, female, and male samples respectively using these algorithms. The fitting performance of different machine learning algorithms in these three groups was evaluated. RESULTS: SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples, while GBR showed the best performance in male samples. The mean absolute error (MAE) of the optimal age estimation model was 1.246 3, 1.281 8 and 1.153 8 years in the total, female and male samples, respectively. The optimal age estimation model exhibited varying levels of accuracy across different age ranges, which provided relatively accurate age estimations in individuals under 18 years old. CONCLUSIONS: The machine learning model developed in this study exhibits good age estimation efficiency in northern Chinese Han children and adolescents. However, its performance is not ideal when applied to adult population. To improve the accuracy in age estimation, the other variables can be considered.

Adolescents and Children Age Estimation Using Machine Learning Based on Pulp and Tooth Volumes on CBCT Images.

OBJECTIVES: To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography (CBCT) images, and to compare and analyze the estimation results. METHODS: A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected. The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated. Three machine learning algorithms (K-nearest neighbor, ridge regression, and decision tree) and stepwise regression were used to establish four age estimation models. The coefficient of determination, mean error, root mean square error, mean square error and mean absolute error were computed and compared. A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed. RESULTS: The K-nearest neighbor model (R2=0.779) and the ridge regression model (R2=0.729) outperformed stepwise regression (R2=0.617), while the decision tree model (R2=0.494) showed poor fitting. The correlation heatmap demonstrated a monotonically negative correlation between age and the parameters including pulp volume, the ratio of pulp volume to hard tissue volume, and the ratio of pulp volume to tooth volume. CONCLUSIONS: Pulp volume and pulp volume proportion are closely related to age. The application of CBCT-based machine learning methods can provide more accurate age estimation results, which lays a foundation for further CBCT-based deep learning dental age estimation research.

[Teeth autotransplantation as an alternative to dental implantation]. / Autotransplantatsiya zuba kak al'ternativa dental'noi implantatsii.

The stages of preoperative planning and surgical treatment of compromised teeth by the method of autotransplantation of a tooth are presented on the example of two clinical cases. The autotransplantation method can be considered an alternative to dental implantation when strictly adhering to the surgical protocol and careful selection of patients.

Fine structural human phantom in dentistry and instance tooth segmentation.

In this study, we present the development of a fine structural human phantom designed specifically for applications in dentistry. This research focused on assessing the viability of applying medical computer vision techniques to the task of segmenting individual teeth within a phantom. Using a virtual cone-beam computed tomography (CBCT) system, we generated over 170,000 training datasets. These datasets were produced by varying the elemental densities and tooth sizes within the human phantom, as well as varying the X-ray spectrum, noise intensity, and projection cutoff intensity in the virtual CBCT system. The deep-learning (DL) based tooth segmentation model was trained using the generated datasets. The results demonstrate an agreement with manual contouring when applied to clinical CBCT data. Specifically, the Dice similarity coefficient exceeded 0.87, indicating the robust performance of the developed segmentation model even when virtual imaging was used. The present results show the practical utility of virtual imaging techniques in dentistry and highlight the potential of medical computer vision for enhancing precision and efficiency in dental imaging processes.

Shape variation in cranium, mandible and teeth in selected mouse strains.

There are different strains of laboratory mouse used in many different fields. These strains differ anatomically. In order to determine these anatomical differences, shape analysis was conducted according to species. CD-1, C57bl/6 and Balb-c strains were preferred to study these differences. Forty-eight adult mouse strains belonging to these strains were utilized. The bones were photographed and geometric morphometry was applied to these photographs. Principal Component Analysis was applied to determine shape variations. In Principal component 1 for cranium, CD-1 and C57bl/6 strain groups showed different shape variations, while Balb-c strain group showed similar shape variations to the other strain groups. Principal Component 1 for the mandible separated the CD-1 and C57bl/6 strain groups in terms of shape variation. Principal Component 2 explained most of the variation between the C57bl/6 and CD-1 lineage groups. In PC1 for molars, the CD-1 group showed a different shape variation from the other groups. Mahalanobis distances and Procrustes distances were measured using Canonical variance analysis to explain the differences between the lineage groups. These measurements were statistically significant. For cranium, in canonical variate 1, CD-1 group of mouse and Balb-c group of mouse were separated from each other. In canonical variate 2, C57bl/6 group of mouse were separated from the other groups. For mandible, Balb-c group of mouse in canonical variate 1 and CD-1 group of mouse in canonical variate 2 were separated from the other groups. For molars, CD-1 group of mouse in canonical variate 1 and Balb-c group of mouse in canonical variate 2 were separated from the other groups. It was thought that these anatomical differences could be caused by genotypic factors as well as dietary differences and many different habits that would affect the way their muscles work.

Research Progress on Dental Age Estimation Based on MRI Technology.

Dental age estimation is a crucial aspect and one of the ways to accomplish forensic age estimation, and imaging technology is an important technique for dental age estimation. In recent years, some studies have preliminarily confirmed the feasibility of magnetic resonance imaging (MRI) in evaluating dental development, providing a new perspective and possibility for the evaluation of dental development, suggesting that MRI is expected to be a safer and more accurate tool for dental age estimation. However, further research is essential to verify its accuracy and feasibility. This article reviews the current state, challenges and limitations of MRI in dental development and age estimation, offering reference for the research of dental age assessment based on MRI technology.

Bioinformatics for Dentistry: A secondary database for the genetics of tooth development.

Genes strictly regulate the development of teeth and their surrounding oral structures. Alteration of gene regulation leads to tooth disorders and developmental anomalies in tooth, oral, and facial regions. With the advancement of gene sequencing technology, genomic data is rapidly increasing. However, the large sets of genomic and proteomic data related to tooth development and dental disorders are currently dispersed in many primary databases and literature, making it difficult for users to navigate, extract, study, or analyze. We have curated the scattered genetic data on tooth development and created a knowledgebase called 'Bioinformatics for Dentistry' (https://dentalbioinformatics.com/). This database compiles genomic and proteomic data on human tooth development and developmental anomalies and organizes them according to their roles in different stages of tooth development. The database is built by systemically curating relevant data from the National Library of Medicine (NCBI) GenBank, OMIM: Online Mendelian Inheritance in Man, AlphaFold Protein Structure Database, Reactome pathway knowledgebase, Wiki Pathways, and PubMed. The accuracy of the included data was verified from supporting primary literature. Upon data curation and validation, a simple, easy-to-navigate browser interface was created on WordPress version 6.3.2, with PHP version 8.0. The website is hosted in a cloud hosting service to provide fast and reliable data transfer rate. Plugins are used to ensure the browser's compatibility across different devices. Bioinformatics for Dentistry contains four embedded filters for complex and specific searches and free-text search options for quick and simple searching through the datasets. Bioinformatics for Dentistry is made freely available worldwide, with the hope that this knowledgebase will improve our understanding of the complex genetic regulation of tooth development and will open doors to research initiatives and discoveries. This database will be expanded in the future by incorporating resources and built-in sequence analysis tools, and it will be maintained and updated annually.

How teeth can be used to estimate sexual dimorphism? A scoping review.

INTRODUCTION: Teeth are biological structures with a high degree of hardness, density, calcification, and capacity to adapt to extrinsic factors at physical, biological, and physiological levels. Subsequently, they resist for a longer period in deteriorating environmental conditions. With dental analysis, it is possible to acquire biographical data about a person. The aim of this scoping review was to identify publications using human teeth tissues to estimate sexual dimorphism. METHODS: The scoping review was carried out in the following databases: Jstor, Scielo, Science Direct, PubMed, and Scopus, using ten search strategies in English and guaranteeing completeness and reproducibility of the phases stipulated in the PRISMA guide. RESULTS: 143 studies on sexual dimorphism based on dental tissue traits were included, of which 40.6% (n = 58) were done in Asia and 27.2% (n = 39) in America. 80% of the studies (equivalent to 114 articles) focused their observations and measurements on the dental crown; 4.2% in enamel, dentin, and pulp together; 3.5% in dental pulp; 2.1% in the entire tooth; 2.8% in enamel, root, and the enamel-cementum junction, and only 0.7% in dentin and pulp. In addition, 92.3% of the studies used metric methods, while only 4.9% and 2.8% used biochemical and non-metric method respectively. CONCLUSION: For sexual dimorphism establishment, enamel has been the most analyzed dental tissue in permanent canines and molars mainly. Likewise, the most widely and accurately used methods for this purpose are the metrics, with the odontometry as the most implemented (intraoral or by using dental plaster models, digital scanning or software) with prediction percentages ranging from 51% to 95.9%. In contrast to biochemical methods, that can achieve the highest precision (up to 100%), the non-metric methods, to a less extent, reported prediction percentages of 58%.

Increasing control over biomineralization in conodont evolution.

Vertebrates use the phosphate mineral apatite in their skeletons, which allowed them to develop tissues such as enamel, characterized by an outstanding combination of hardness and elasticity. It has been hypothesized that the evolution of the earliest vertebrate skeletal tissues, found in the teeth of the extinct group of conodonts, was driven by adaptation to dental function. We test this hypothesis quantitatively and demonstrate that the crystallographic order increased throughout the early evolution of conodont teeth in parallel with morphological adaptation to food processing. With the c-axes of apatite crystals oriented perpendicular to the functional feeding surfaces, the strongest resistance to uniaxial compressional stress is conferred along the long axes of denticles. Our results support increasing control over biomineralization in the first skeletonized vertebrates and allow us to test models of functional morphology and material properties across conodont dental diversity.

Haliskia peterseni, a new anhanguerian pterosaur from the late Early Cretaceous of Australia.

Pterosaur remains have been reported from every continent; however, pterosaur skeletons remain rare. A new pterosaur is presented here, Haliskia peterseni gen. et sp. nov., constituting the most complete specimen from Australia from the upper Albian Toolebuc Formation of the Eromanga Basin (Queensland, Australia). A combination of features, including the presence of a premaxillary crest and curved teeth, and the morphology of the scapulocoracoid, support its referral to Anhangueria. Haliskia can be distinguished from all other anhanguerian pterosaurs based on two dental characters: the 4th and 5th tooth pairs are smaller than the 3rd and 6th, and the 2nd and 5th alveoli are smaller than 3-4 and 6-8. Moreover, the hyoid is 70% the total length of the mandible. The phylogenetic analyses presented here place Haliskia within Anhangueria. In one analysis, Haliskia and Ferrodraco are resolved as sister taxa, with Tropeognathus mesembrinus sister to that clade. The other resolves Haliskia, Mythunga and Ferrodraco in a polytomy within Tropeognathinae. The new Australian pterosaur attests to the success of Anhangueria during the latest Early Cretaceous and suggests that the Australian forms were more taxonomically diverse and palaeobiogeographically complex than previously recognized.

Myosin II mediates Shh signals to shape dental epithelia via control of cell adhesion and movement.

The development of ectodermal organs begins with the formation of a stratified epithelial placode that progressively invaginates into the underlying mesenchyme as the organ takes its shape. Signaling by secreted molecules is critical for epithelial morphogenesis, but how that information leads to cell rearrangement and tissue shape changes remains an open question. Using the mouse dentition as a model, we first establish that non-muscle myosin II is essential for dental epithelial invagination and show that it functions by promoting cell-cell adhesion and persistent convergent cell movements in the suprabasal layer. Shh signaling controls these processes by inducing myosin II activation via AKT. Pharmacological induction of AKT and myosin II can also rescue defects caused by the inhibition of Shh. Together, our results support a model in which the Shh signal is transmitted through myosin II to power effective cellular rearrangement for proper dental epithelial invagination.

[Research on intelligent tooth segmentation method combining multiple seed region growth and boundary extension].

The segmentation of dental models is a crucial step in computer-aided diagnosis and treatment systems for oral healthcare. To address the issues of poor universality and under-segmentation in tooth segmentation techniques, an intelligent tooth segmentation method combining multiple seed region growth and boundary extension is proposed. This method utilized the distribution characteristics of negative curvature meshes in teeth to obtain new seed points and effectively adapted to the structural differences between the top and sides of teeth through differential region growth. Additionally, the boundaries of the initial segmentation were extended based on geometric features, which was effectively compensated for under-segmentation issues in region growth. Ablation experiments and comparative experiments with current state-of-the-art algorithms demonstrated that the proposed method achieved better segmentation of crowded dental models and exhibited strong algorithm universality, thus possessing the capability to meet the practical segmentation needs in oral healthcare.

Study on the Association between anterior tooth Colour Preference based on the FAHP and individual factors.

BACKGROUND: The relationship between tooth colour and individual satisfaction in oral aesthetics has long been a topic of interest. In this study, we utilized the fuzzy analytic hierarchy process (FAHP) to investigate the impacts of sex and age on tooth colour preference. The findings of this study should provide a scientific basis for oral aesthetic practice. METHODS: In the current study, a random selection method was employed, and a survey was completed by 120 patients. To obtain tooth colour data, standard tooth colour charts were used. Smile photos were taken as template images using a single-lens reflex camera. The FAHP was utilized to conduct a weight analysis of tooth colour preferences among patients of different sexes and age groups. RESULTS: There were significant differences in tooth colour preference based on sex and age. Men tend to prefer the B1 colour, while women may prioritize the aesthetic effects of other colours. Additionally, as patients age, their preferences for tooth colour become more diverse. These findings offer valuable insights for oral aesthetics practitioners, enabling them to better address the aesthetic needs of patients across different sexes and ages. This knowledge can aid in the development of more personalized treatment plans that align with patients' expectations. CONCLUSION: In this study, we utilized scientific analysis methods to quantify the popularity of different tooth colours among various groups of people. By doing so, we established a scientific foundation for clinical practice. The findings of this study offer valuable insights for oral aesthetic research, enhancing our understanding of tooth colour. Additionally, these findings have practical applications in the field of oral medicine, potentially improving patients' quality of life and overall oral health.

Evaluating tooth segmentation accuracy and time efficiency in CBCT images using artificial intelligence: A systematic review and Meta-analysis.

OBJECTIVES: This systematic review and meta-analysis aimed to assess the current performance of artificial intelligence (AI)-based methods for tooth segmentation in three-dimensional cone-beam computed tomography (CBCT) images, with a focus on their accuracy and efficiency compared to those of manual segmentation techniques. DATA: The data analyzed in this review consisted of a wide range of research studies utilizing AI algorithms for tooth segmentation in CBCT images. Meta-analysis was performed, focusing on the evaluation of the segmentation results using the dice similarity coefficient (DSC). SOURCES: PubMed, Embase, Scopus, Web of Science, and IEEE Explore were comprehensively searched to identify relevant studies. The initial search yielded 5642 entries, and subsequent screening and selection processes led to the inclusion of 35 studies in the systematic review. Among the various segmentation methods employed, convolutional neural networks, particularly the U-net model, are the most commonly utilized. The pooled effect of the DSC score for tooth segmentation was 0.95 (95 %CI 0.94 to 0.96). Furthermore, seven papers provided insights into the time required for segmentation, which ranged from 1.5 s to 3.4 min when utilizing AI techniques. CONCLUSIONS: AI models demonstrated favorable accuracy in automatically segmenting teeth from CBCT images while reducing the time required for the process. Nevertheless, correction methods for metal artifacts and tooth structure segmentation using different imaging modalities should be addressed in future studies. CLINICAL SIGNIFICANCE: AI algorithms have great potential for precise tooth measurements, orthodontic treatment planning, dental implant placement, and other dental procedures that require accurate tooth delineation. These advances have contributed to improved clinical outcomes and patient care in dental practice.

Microhardness Measurements on Tooth and Alveolar Bone in Rodent Oral Disease Models.

The mechanical property, microhardness, is evaluated in dental enamel, dentin, and bone in oral disease models, including dental fluorosis and periodontitis. Micro-CT (µCT) provides 3D imaging information (volume and mineral density) and scanning electron microscopy (SEM) produces microstructure images (enamel prism and bone lacuna-canalicular). Complementarily to structural analysis by µCT and SEM, microhardness is one of the informative parameters to evaluate how structural changes alter mechanical properties. Despite being a useful parameter, studies on microhardness of alveolar bone in oral diseases are limited. To date, divergent microhardness measurement methods have been reported. Since microhardness values vary depending on the sample preparation (polishing and flat surface) and indentation sites, diverse protocols can cause discrepancies among studies. Standardization of the microhardness protocol is essential for consistent and accurate evaluation in oral disease models. In the present study, we demonstrate a standardized protocol for microhardness analysis in tooth and alveolar bone. Specimens used are as follows: for the dental fluorosis model, incisors were collected from mice treated with/without fluoride-containing water for 6 weeks; for ligature-induced periodontal bone resorption (L-PBR) model, alveolar bones with periodontal bone resorption were collected from mice ligated on the maxillary 2nd molar. At 2 weeks after the ligation, the maxilla was collected. Vickers hardness was analyzed in these specimens according to the standardized protocol. The protocol provides detailed materials and methods for resin embedding, serial polishing, and indentation sites for incisors and alveolar. To the best of our knowledge, this is the first standardized microhardness protocol to evaluate the mechanical properties of tooth and alveolar bone in rodent oral disease models.