BackgroundThis model-specific biomechanical study investigated the effects of attachment-force configuration on the three-dimensional displacement, rotational behavior, and root surface stress of a horizontally impacted maxillary central incisor with approximately 90° of distal crown rotation.MethodsThree finite element models with varying crown rotation (90°, 95°, 100°) were constructed from a single patient's cone-beam computed tomography dataset. Models B and C were parametric variants of Model A. Traction forces of 100 g were applied virtually via a button bonded on either the mesial or distal surface, with force directions tipped distally (0°, 5°, 10°, 20°) or mesially (0°, 10°, 20°, 30°). Displacement of specific landmarks, total tooth movement, rotation angles, and root surface stress were analyzed.ResultsThe impacted incisor primarily exhibited inferior displacement, which generally decreased as the initial crown rotation increased or as the force tipping angle increased. Compared to mesial-button traction protocols, distal-button traction protocols produced greater total displacement and more pronounced crown rotation. In this specific model, initial coronal rotation gradually shifted from clockwise to counterclockwise (a favorable rotational tendency) within the tested tipping ranges. For distal-button traction protocols, coronal rotation shifted from clockwise to counterclockwise at approximately 10°-20° of distal tipping in Model A and 5°-10° in Models B and C. For mesial-button traction protocols, the transition occurred at approximately 20°-30° of mesial tipping in Models A and B and 10°-20° in Model C. Root surface stress was concentrated in the superior cervical region. Stress values were higher in the distal attachment-force configuration (0.60–0.64 MPa) relative to the mesial attachment-force configuration (0.44–0.52 MPa).ConclusionsAmong the tested protocols, the distal-button traction system showed a more favorable initial counterclockwise rotational tendency. The transition from clockwise to counterclockwise rotation was model-dependent: approximately 10°-20° in Model A and 5°-10° in Models B and C for distal-button traction configuration, and approximately 20°-30° in Models A and B and 10°-20° in Model C for mesial-button traction configuration. These are model-specific biomechanical observations and clinical applicability requires further validation.
IntroductionThree-dimensional (3D) facial imaging is increasingly used in orthodontics and digital dentistry, but quantitative morphometric information does not automatically translate into reproducible and clinically interpretable decision support. A standardized pathway integrating image acquisition, landmark annotation, morphometric interpretation, visualization, patient communication, and quality monitoring is therefore needed.MethodsWe developed a Lean-M.A.S.T.E.R. clinical decision-support framework using morphometric evidence derived from three previously published studies based on 3D photogrammetry and landmark-based facial analysis in female reference cohorts. No new individual-level data were collected or reanalyzed. The evidence was translated into a six-phase framework comprising Mapping & Contextualization, Analysis & Diagnosis, Strategic Design, Testing & Adaptive Execution, Embedding & Sustainability, and Resilience & Renewal. Lean tools, Standard Work, process mapping, performance indicators, governance mechanisms, and a prospective validation pathway were incorporated into the model.ResultsThe conceptual and operational outputs of framework development comprised an implementation-oriented architecture linking 3D facial acquisition to morphometric interpretation, clinician-facing decision support, patient communication, performance monitoring, and continuous renewal. These framework outputs included a SIPOC process map, a structured morphometric evidence layer, alternative design configurations, predefined evaluation indicators, and an integrated governance and sustainability matrix. Four prospective hypotheses were defined concerning inter-operator reproducibility, workflow efficiency, clinical decision support, and patient comprehension. A prospective evaluation pathway based on single-center pilot testing, PDSA refinement, and subsequent multicenter validation was also specified. These outputs represent proposed framework components and have not yet been prospectively evaluated.ConclusionsThe Lean-M.A.S.T.E.R. framework provides a structured and testable bridge between 3D facial morphometry and clinical decision support in digital dentistry and orthodontics. Morphometric descriptors are treated as population- and context-specific information rather than universal aesthetic standards or prescriptive treatment targets. Prospective validation is required to determine the framework's feasibility, reproducibility, robustness, transferability, and sustainability while preserving clinician oversight and patient-centered decision-making.
IntroductionPolysomnography (PSG) is the gold standard for pediatric obstructive sleep apnea (OSA) diagnosis but is limited for large-scale screening and telemedicine by high costs and specialized requirements. Given the close correlation between craniofacial features and OSA, this study developed a non-invasive risk stratification model (non-OSA, mild OSA, and moderate-to-severe OSA) using two-dimensional multi-view facial photographs based on a Multi-View Convolutional Neural Network (MVCNN).Materials and methodsThis multicenter retrospective study included 212 children with frontal and lateral facial photographs linked to polysomnography. Models were evaluated at the patient level after aggregating each participant's available image records. The MVCNN was internally evaluated in 149 patients and externally evaluated in 63 patients. Patient-level discrimination and classification metrics were estimated with bootstrap confidence intervals, and paired bootstrap analysis compared models evaluated on common patients.ResultsIn the internal patient-level evaluation, MVCNN achieved a macro-AUC of 0.898 (95% CI, 0.863-0.930), macro-F1 of 0.839, balanced accuracy of 0.840, and overall accuracy of 0.846. Its macro-AUC exceeded those of ResNet-50 by 0.061 (95% CI, 0.022-0.106; P = 0.004) and VGG-16 by 0.104 (95% CI, 0.057-0.164; P < 0.001). In the external cohort, MVCNN achieved a macro-AUC of 0.876 (95% CI, 0.827-0.919), macro-F1 of 0.833, balanced accuracy of 0.826, and overall accuracy of 0.841.ConclusionsPatient-level analyses support the discriminatory performance of multi-view facial photography for pediatric OSA risk stratification in the studied dental cohorts. Prospective validation, direct view-ablation studies, and calibration in broader clinical populations are required before clinical deployment.
ObjectiveThis study aims to compare and evaluate the effects of two functional appliances—Twin Block and Forsus Fatigue Resistant Device (FRD)—on changes in airway dimensions in patients with skeletal Class II malocclusion.MethodsA search was conducted in four electronic databases (PubMed, Web of Science, Scopus, and Cochrane Library) for articles published up to November 2025. Six clinical studies (five retrospective and one prospective) that evaluated airway changes following treatment with Twin Block and Forsus FRD were included. Data extracted included study design, sample characteristics, intervention details, cephalometric airway measurements and dimensions, and pre- and post-treatment outcomes. Risk of bias was assessed using ROBINS-I, and the certainty of evidence was evaluated using GRADE.ResultsBoth Forsus FRD and Twin Block appliance therapies were associated with improvements in selected airway parameters, including increases in the upper, middle, and lower pharyngeal airway widths, anterior repositioning of the hyoid bone, and changes in nasopharyngeal and oropharyngeal sagittal dimensions. Some studies reported more pronounced airway changes and greater skeletal advancement with the Twin Block appliance, particularly in the oropharyngeal region, whereas other studies found similar airway effects with no statistically significant intergroup differences. Twin Block was associated with greater skeletal mandibular advancement in some studies, whereas Forsus FRD tended to produce more pronounced dentoalveolar effects, particularly mandibular incisor proclination. Overall, airway changes were modest and variable, with differences in age, growth stage, appliance protocol, treatment duration, and measurement techniques contributing to heterogeneity.ConclusionBoth Twin Block and Forsus FRD therapies may be associated with modest improvements in selected pharyngeal airway dimensions in patients with skeletal Class II malocclusion. Although Twin Block was associated with greater skeletal mandibular advancement in some studies and Forsus FRD tended to produce more pronounced dentoalveolar effects, particularly mandibular incisor proclination, these comparative patterns were not consistent across all studies. Consistency of statistically significant differences between the appliances in airway outcomes was not demonstrated. More high-quality prospective comparative studies are required to clarify the comparative skeletal, dentoalveolar, and airway effects of Twin Block and Forsus FRD and their clinical significance.Systematic Review Registrationidentifier: CRD420251207653.
Glutamate (Glu) occupies an unusual position in skeletal biology, functioning as both a local signaling molecule and a central intermediate of cellular metabolism. Although these roles are often discussed separately, they converge on processes that determine bone and cartilage homeostasis. This review integrates glutamatergic signaling with the intracellular glutamine (Gln)-Glu-α-ketoglutarate (α-KG)-glutathione (GSH) pathway and examines how Glu availability is translated into cell-specific responses. Across osteoblasts (OBs), osteoclasts (OCLs), bone marrow mesenchymal stem cells (BMSCs), and chondrocytes, Glu receptors and transporters modulate Ca2⁺, cyclic adenosine monophosphate (cAMP), and kinase signaling, whereas Gln-derived Glu supports tricarboxylic acid (TCA)-cycle metabolism, biosynthesis, epigenetic regulation, and antioxidant defense. The balance between these signaling and metabolic functions varies with cell type, differentiation stage, nutrient supply, mechanical loading, and inflammation. This context dependence may explain why Glu-associated pathways can support bone formation in one setting but favor resorption or cartilage damage in another. Evidence from osteoporosis, osteoarthritis, intervertebral disc degeneration, and multiple myeloma-associated bone disease highlights how disturbed nutrient availability and local Glu handling can impair tissue homeostasis. However, most mechanistic evidence remains preclinical, and Glu-related concentrations, spatial gradients, and metabolic fluxes in human skeletal tissues are poorly defined. Stable-isotope tracing, spatial metabolomics, cell-specific genetic models, and targeted delivery strategies will be essential for translating this Glu-centered network into skeletal therapies.
