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.

Radiological Evaluation of the Accuracy of Demirjian, Nolla, and Willems Methods for Dental Age Estimation in 3-17-Year-Old Iranian Children.

Background: The stage of tooth formation is one of the most reliable indicators for predicting a patient's developmental age by radiographs. This study compared the accuracy of three distinct dental age estimation methods (Demirjian, Nolla, and Willems) in children aged 3-17 in the northern Iranian population. Methods: This cross-sectional study examined panoramic radiographs of 434 children aged 3-17 from Mazandaran Province, Iran, who had teeth 31-37 present on the left mandible. This study employed the Demirjian, Nolla, and Willems methods to estimate the dental age of the sample and compare it with the chronological age. The data were analyzed using SPSS v16. A paired t-test was used to compare chronological and dental ages. The Pearson correlation was used to correlate the chronological and dental ages. The errors of different methods were compared using the Wilcoxon test. P values < 0.05 were considered significant for all tests except Wilcoxon. For Wilcoxon, a P value < 0.017 was considered significant. Results: The three methods presented differing mean estimated ages. The Demirjian method delivered the highest mean, and all three methods differed significantly when compared in pairs. The results showed that the Demirjian method overestimated chronological age by 0.25 years (P < 0.001) in girls and 0.09 years (P = 0.28) in boys. The Willems method underestimated chronological age by 0.05 years (P = 0.47) in girls and 0.12 years (P = 0.13) in boys. The Nolla method underestimated chronological age by 0.41 years (P < 0.001) in girls and 0.40 years (P < 0.001) in boys. The accuracy of each method varied with the patient's age. Conclusion: According to the findings, the Willems method outperformed the Demirjian method, and the Demirjian method exceeded the Nolla method for estimating dental age in Iranian children aged 3-17. Overall, the Demirjian method overestimated the age of the study population, whereas the other two underestimated it.

YOLO-V5 based deep learning approach for tooth detection and segmentation on pediatric panoramic radiographs in mixed dentition.

OBJECTIVES: In the interpretation of panoramic radiographs (PRs), the identification and numbering of teeth is an important part of the correct diagnosis. This study evaluates the effectiveness of YOLO-v5 in the automatic detection, segmentation, and numbering of deciduous and permanent teeth in mixed dentition pediatric patients based on PRs. METHODS: A total of 3854 mixed pediatric patients PRs were labelled for deciduous and permanent teeth using the CranioCatch labeling program. The dataset was divided into three subsets: training (n = 3093, 80% of the total), validation (n = 387, 10% of the total) and test (n = 385, 10% of the total). An artificial intelligence (AI) algorithm using YOLO-v5 models were developed. RESULTS: The sensitivity, precision, F-1 score, and mean average precision-0.5 (mAP-0.5) values were 0.99, 0.99, 0.99, and 0.98 respectively, to teeth detection. The sensitivity, precision, F-1 score, and mAP-0.5 values were 0.98, 0.98, 0.98, and 0.98, respectively, to teeth segmentation. CONCLUSIONS: YOLO-v5 based models can have the potential to detect and enable the accurate segmentation of deciduous and permanent teeth using PRs of pediatric patients with mixed dentition.

Bone or Tooth dentin: The TGF-ß signaling is the key.

To investigate the cell linkage between tooth dentin and bones, we studied TGF-ß roles during postnatal dentin development using TGF-ß receptor 2 (Tgfßr2) cKO models and cell lineage tracing approaches. Micro-CT showed that the early Tgfßr2 cKO exhibit short roots and thin root dentin (n = 4; p<0.01), a switch from multilayer pre-odontoblasts/odontoblasts to a single-layer of bone-like cells with a significant loss of ~85% of dentinal tubules (n = 4; p<0.01), and a matrix shift from dentin to bone. Mechanistic studies revealed a statistically significant decrease in odontogenic markers, and a sharp increase in bone markers. The late Tgfßr2 cKO teeth displayed losses of odontoblast polarity, a significant reduction in crown dentin volume, and the onset of massive bone-like structures in the crown pulp with high expression levels of bone markers and low levels of dentin markers. We thus concluded that bones and tooth dentin are in the same evolutionary linkage in which TGF-ß signaling defines the odontogenic fate of dental mesenchymal cells and odontoblasts. This finding also raises the possibility of switching the pulp odontogenic to the osteogenic feature of pulp cells via a local manipulation of gene programs in future treatment of tooth fractures.

Convolutional neural network for automated tooth segmentation on intraoral scans.

BACKGROUND: Tooth segmentation on intraoral scanned (IOS) data is a prerequisite for clinical applications in digital workflows. Current state-of-the-art methods lack the robustness to handle variability in dental conditions. This study aims to propose and evaluate the performance of a convolutional neural network (CNN) model for automatic tooth segmentation on IOS images. METHODS: A dataset of 761 IOS images (380 upper jaws, 381 lower jaws) was acquired using an intraoral scanner. The inclusion criteria included a full set of permanent teeth, teeth with orthodontic brackets, and partially edentulous dentition. A multi-step 3D U-Net pipeline was designed for automated tooth segmentation on IOS images. The model's performance was assessed in terms of time and accuracy. Additionally, the model was deployed on an online cloud-based platform, where a separate subsample of 18 IOS images was used to test the clinical applicability of the model by comparing three modes of segmentation: automated artificial intelligence-driven (A-AI), refined (R-AI), and semi-automatic (SA) segmentation. RESULTS: The average time for automated segmentation was 31.7 ± 8.1 s per jaw. The CNN model achieved an Intersection over Union (IoU) score of 91%, with the full set of teeth achieving the highest performance and the partially edentulous group scoring the lowest. In terms of clinical applicability, SA took an average of 860.4 s per case, whereas R-AI showed a 2.6-fold decrease in time (328.5 s). Furthermore, R-AI offered higher performance and reliability compared to SA, regardless of the dentition group. CONCLUSIONS: The 3D U-Net pipeline was accurate, efficient, and consistent for automatic tooth segmentation on IOS images. The online cloud-based platform could serve as a viable alternative for IOS segmentation.

[Tooth segmentation and identification on cone-beam computed tomography with convolutional neural network based on spatial embedding information].

OBJECTIVE: To propose a novel neural network to achieve tooth instance segmentation and recognition based on cone-beam computed tomography (CBCT) voxel data. METHODS: The proposed methods included three different convolutional neural network models. The architecture was based on the Resnet module and built according to the structure of "Encoder-Decoder" and U-Net. The CBCT image was de-sampled and a fixed-size region of interest (ROI) containing all the teeth was determined. ROI would first through a two-branch "encoder and decoder" structure of the network, the network could predict each voxel in the input data of the spatial embedding. The post-processing algorithm would cluster the prediction results of the relevant spatial location information according to the two-branch network to realize the tooth instance segmentation. The tooth position identification was realized by another U-Net model based on the multi-classification segmentation task. According to the predicted results of the network, the post-processing algorithm would classify the tooth position according to the voting results of each tooth instance segmentation. At the original spatial resolution, a U-Net network model for the fine-tooth segmentation was trained using the region corresponding to each tooth as the input. According to the results of instance segmentation and tooth position identification, the model would process the correspon-ding positions on the high-resolution CBCT images to obtain the high-resolution tooth segmentation results. In this study, CBCT data of 59 cases with simple crown prostheses and implants were collected for manual labeling as the database, and statistical indicators were evaluated for the prediction results of the algorithm. To assess the performance of tooth segmentation and classification, instance Dice similarity coefficient (IDSC) and the average Dice similarity coefficient (ADSC) were calculated. RESULTS: The experimental results showed that the IDSC was 89.35%, and the ADSC was 84. 74%. After eliminating the data with prostheses artifacts, the database of 43 samples was generated, and the performance of the training network was better, with 90.34% for IDSC and 87.88% for ADSC. The framework achieved excellent performance on tooth segmentation and identification. Voxels near intercuspation surfaces and fuzzy boundaries could be separated into correct instances by this framework. CONCLUSIONS: The results show that this method can not only successfully achieve 3D tooth instance segmentation but also identify all teeth notation numbers accurately, which has clinical practicability.

Giant stem tetrapod was apex predator in Gondwanan late Palaeozoic ice age.

Current hypotheses of early tetrapod evolution posit close ecological and biogeographic ties to the extensive coal-producing wetlands of the Carboniferous palaeoequator with rapid replacement of archaic tetrapod groups by relatives of modern amniotes and lissamphibians in the late Carboniferous (about 307 million years ago). These hypotheses draw on a tetrapod fossil record that is almost entirely restricted to palaeoequatorial Pangea (Laurussia)1,2. Here we describe a new giant stem tetrapod, Gaiasia jennyae, from high-palaeolatitude (about 55° S) early Permian-aged (about 280 million years ago) deposits in Namibia that challenges this scenario. Gaiasia is represented by several large, semi-articulated skeletons characterized by a weakly ossified skull with a loosely articulated palate dominated by a broad diamond-shaped parasphenoid, a posteriorly projecting occiput, and enlarged, interlocking dentary and coronoid fangs. Phylogenetic analysis resolves Gaiasia within the tetrapod stem group as the sister taxon of the Carboniferous Colosteidae from Euramerica. Gaiasia is larger than all previously described digited stem tetrapods and provides evidence that continental tetrapods were well established in the cold-temperate latitudes of Gondwana during the final phases of the Carboniferous-Permian deglaciation. This points to a more global distribution of continental tetrapods during the Carboniferous-Permian transition and indicates that previous hypotheses of global tetrapod faunal turnover and dispersal at this time2,3 must be reconsidered.

[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.

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.

[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.

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.

Reading children's teeth to reconstruct life history and the evolution of human cooperation and cognition: The role of dental enamel microstructure and chemistry.

Studying infants in the past is crucial for understanding the evolution of human life history and the evolution of cooperation, cognition, and communication. An infant's growth, health, and mortality can provide information about the dynamics and structure of a population, their cultural practices, and the adaptive capacity of a community. Skeletal remains provide one way of accessing this information for humans recovered prior to the historical periods. Teeth in particular, are retrospective archives of information that can be accessed through morphological, micromorphological, and biogeochemical methods. This review discusses how the microanatomy and formation of teeth, and particularly enamel, serve as archives of somatic growth, stress, and the environment. Examining their role in the broader context of human evolution, we discuss dental biogeochemistry and emphasize how the incremental growth of tooth microstructure facilitates the reconstruction of temporal data related to health, diet, mobility, and stress in past societies. The review concludes by considering tooth microstructure as a biomarker and the potential clinical applications.

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.

DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation.

OBJECTIVES: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evaluate a novel open source tool called DentalSegmentator for fully automatic segmentation of five anatomical structures on DMF CT and CBCT scans: maxilla/upper skull, mandible, upper teeth, lower teeth, and the mandibular canal. METHODS: A retrospective sample of 470 CT and CBCT scans was used as a training/validation set. The performance and generalizability of the tool was evaluated by comparing segmentations provided by experts and automatic segmentations in two hold-out test datasets: an internal dataset of 133 CT and CBCT scans acquired before orthognathic surgery and an external dataset of 123 CBCT scans randomly sampled from routine examinations in 5 institutions. RESULTS: The mean overall results in the internal test dataset (n = 133) were a Dice similarity coefficient (DSC) of 92.2 ± 6.3 % and a normalised surface distance (NSD) of 98.2 ± 2.2 %. The mean overall results on the external test dataset (n = 123) were a DSC of 94.2 ± 7.4 % and a NSD of 98.4 ± 3.6 %. CONCLUSIONS: The results obtained from this highly diverse dataset demonstrate that this tool can provide fully automatic and robust multiclass segmentation for DMF CT and CBCT scans. To encourage the clinical deployment of DentalSegmentator, the pre-trained nnU-Net model has been made publicly available along with an extension for the 3D Slicer software. CLINICAL SIGNIFICANCE: DentalSegmentator open source 3D Slicer extension provides a free, robust, and easy-to-use approach to obtaining patient-specific three-dimensional models from CT and CBCT scans. These models serve various purposes in a digital dentistry workflow, such as visualization, treatment planning, intervention, and follow-up.

Old World Fruit Bats (Pteropodidae, Chiroptera) from the Pleistocene of Vietnam.

Isolated teeth of a lesser short-nosed fruit bat Cynopterus brachyotis (Müller, 1838), a fulvous fruit bat Rousettus leschenaultii (Desmarest, 1820), and a dawn bat Eonycteris spelaea (Dobson, 1871) are described from the Middle Pleistocene Tham Hai cave locality in northern Vietnam (Lang Son Province). These are the first fossil findings of the Old World fruit bats in Vietnam. The Middle Pleistocene association of Pteropodidae from the Tham Hai locality may largely reflect the composition of species that roosted in local caves.