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Microfluidic pulp platform with vascular integration to evaluate biofunctional material

2026-06-09T06:14:46Z

Title: Microfluidic pulp platform with vascular integration to evaluate biofunctional material Authors: Lee, Min-Yong; Mangal, Utkarsh; Yoon, Hi-Won; Im, Hyungsoon; Choi, Sung-Hwan; Kwon, Jae Sung; Shin, Su-Jung Abstract: Biofunctional materials are increasingly used to preserve tooth vitality by promoting dental pulp-mediated hard tissue formation. However, existing evaluation platforms, such as conventional in vitro assays or microfluidic systems, fail to replicate the complex histological and physiological characteristics of dental pulp. This study introduces a 4D biofunctional material-to-pulp (4D BFP) platform that recapitulates pulp physiology, integrating three key features of native pulp tissue: layered histoarchitecture, microcirculatory dynamics, and threedimensional multicellular organization. This platform further incorporates a temporal dimension by simulating age-dependent vascular transitions, thereby enabling the age-specific modelling of pulp responses, and defining the system as a 4D microfluidic pulp model. Computational fluid dynamics confirmed physiologically relevant flow profiles, while the compartmentalized design supported the spatially organized co-culture of endothelial cell (EC) and human dental pulp stem cell (hDPSC) spheroids. Functional responses to biofunctional material were assessed in both young and mature 4D pulp models. Transcriptomic profiling revealed distinct age-and material-specific signatures related to cellular growth arrest, angiogenesis, and developmental pathways. Collectively, the 4D BFP platform provides a physiological and temporal biomimetic model to study biomaterial-dental pulp interactions, supporting its application as a primary screening tool for candidate biofunctional materials.

Outcomes of Root Canal Treatment in Patients With Autoimmune Disease: A Retrospective Case-Control Study

2026-06-10T05:55:37Z

Title: Outcomes of Root Canal Treatment in Patients With Autoimmune Disease: A Retrospective Case-Control Study Authors: Lee, Seoyeon; Kim, Euiseong; Jung, Hoiin; Kim, Hyejin; Kim, Sunil Abstract: Aim The purpose of this study was to compare the outcome of nonsurgical root canal treatment (RCT) in patients with autoimmune diseases (AD) with the outcome in patients without AD. The null hypothesis was: there is no difference in the outcomes of RCT regardless of the patient group. Results were also compared among AD subgroups: inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and psoriasis (Ps).Methodology Data were obtained from a database using codes corresponding to the National Health Insurance Dental Fee Schedule. Patients diagnosed with AD who received primary RCT at the Veterans Health Service Medical Center from 2010 to 2022 formed the study group. Controls were matched using propensity score matching for age, sex, arch type, and tooth type. Preoperative periapical lesions, canal filling quality, and RCT outcomes were assessed through radiographs, including panoramic, periapical, and cone-beam computed tomography images. Outcomes were evaluated at approximately 1 year and at maximum follow-up. Chi-square tests and logistic regression were used to evaluate associations between AD and RCT success.Results The study included 203 ad patients (317 teeth) and 203 controls (312 teeth). At 1 year, success rates were 69.4% in AD patients and 73.7% in controls (p = 0.268). Within the AD group, success rates were 64.6% for IBD, 75.3% for RA, and 73.2% for Ps. Patients with IBD showed only statistical significance (p = 0.025). The mean observation duration for the maximum follow-up was approximately 50 months. Long-term success rates were 61.5% for AD and 66.0% for controls (p = 0.207). Multivariate logistic regression analysis indicated that arch type, tooth type, and the presence of preoperative apical lesions were significant factors influencing the outcome of RCT. Comparing the 1-year and long-term outcomes, IBD, RA, and Ps showed a similar trend of decreased success rates, although the differences were not statistically significant.Conclusions RCT success rates in patients with AD were comparable to those of controls. Multivariable analysis revealed that clinical factors were the primary predictors of success, rather than the presence of AD. Therefore, high-quality clinical procedures are the critical factor for favorable outcomes in AD patients.

Mamba-Based Deep Learning Model for Automated Periapical Index Classification Using Periapical Radiographs and Clinical Metadata

2026-06-10T05:55:42Z

Title: Mamba-Based Deep Learning Model for Automated Periapical Index Classification Using Periapical Radiographs and Clinical Metadata Authors: Lee, Jiyun; Park, Yudam; Kim, Sunil; Jang, Ikbeom Abstract: Aim Apical periodontitis (AP) diagnosis primarily relies on periapical radiographs (PRs) and the Periapical Index (PAI) scoring system. However, existing automated approaches often simplify PAI into binary categories or ignore essential clinical metadata, limiting diagnostic performance and applicability. Such limitations hinder timely and accurate diagnosis of AP, which may complicate treatment planning by creating uncertainty about the appropriate timing and type of intervention, and ultimately challenge clinicians' ability to make consistent and informed decisions. This study aimed to develop and validate a novel Mamba-based classification model that integrates PR with structured clinical metadata to predict detailed PAI scores across the full 5-class.Methodology In this retrospective diagnostic accuracy study, PRs and corresponding metadata-including patient age, tooth location, tooth number and arch type-were collected from a single institution. Two expert endodontists independently assigned PAI scores (1-5) based on & Oslash;rstavik's criteria, with the final reference standard set by consensus. The proposed artificial intelligence (AI) model utilized a Mamba-based state-space architecture to capture spatial dependencies and incorporate structured clinical metadata features. Training and evaluation were conducted using stratified 5-fold cross-validation.Results The model achieved 54.72% accuracy and a quadratic-weighted kappa (QWK) of 0.713 in 5-class classification, outperforming the latest models based on convolutional neural networks (CNNs) and object detection networks. Ablation analysis further supported the value of integrating patient information, showing that age was the largest impact on model performance. Gradient-weighted Class Activation Mapping (Grad-CAM) analysis for model explainability demonstrated that the model's highlighted areas were aligned with clinically meaningful periapical regions.Conclusions The proposed model addresses limitations of prior methods by leveraging the full range of the PAI scores and incorporating structured clinical information. It has the potential to support more consistent radiographic interpretation, reduce inter-examiner variability and serve as an interpretable tool in educational and clinical decision-support.

Evaluation of Micro-Shear Bond Strength of Self-Adhesive FlowablP Giomer To Bovine Tooth

2026-05-14T07:58:32Z

Title: Evaluation of Micro-Shear Bond Strength of Self-Adhesive FlowablP Giomer To Bovine Tooth Authors: Kim, Eunjin; Shin, Yooseok; Kim, Dohyun; Kim, Jeong-hee; Kim, Ran-ah; Park, Jeong-won Abstract: Purpose: Self-adhesive flowable giomer (SAG) has been used in dental practice recently to simplify clinical procedures and shorten chair times. However, there are only few studies evaluating its bond strength to enamel and dentin, resulting in a lack of evidence. The purpose of this study was to compare the micro-shear bond strength with and without adhesive in enamel and dentin to evaluate the self-adhesive ability of SAG. Methods and Materials: Sound bovine teeth were used as the tooth substrates. For & micro;-SBS tests, enamel and dentin specimens were prepared for SAG (Beautifil Kids SA-BK), a self-adhesive flowable composite (Vertise Flow-VF), and a nanohybrid flowable giomer (Beautifil Flow Plus F03-BF). Two adhesive modes were tested for BK and VF (with self-etching adhesive and no adhesive), and one for BF (with self-etching adhesive). The & micro;-SBS test was conducted after 24 h and after thermocycling for 10,000 cycles using a universal testing machine. Results: For all materials, when self-etching adhesive was used, the & micro;-SBS was significantly higherthan that of the no-adhesive group (P < 0.05). No statistically significant difference was found between the restorative materials under any condition. Thermocycling had no significant effect on the & micro;-SBS of BK. In the self-etching adhesive group, mixed failure was predominant for all materials. However, in no-adhesive group, adhesive failure and mixed failure were observed at similar levels for all materials. Conclusion: The self-adhesive resin without adhesive showed lower bonding strength in both enamel and dentin compared to the one with adhesive. Clinical relevance: Although there were no significant differences in bond strength stability between materials, SAG still offers a simplified bonding process without compromising bond strength, making it a viable option for clinical use.