DSpace Community:

Microfluidic pulp platform with vascular integration to evaluate biofunctional material

Sun, 01 Nov 2026 00:00:00 GMT

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.

Deep learning-based segmentation of enamel, cementum, alveolar bone, and gingiva in periodontal ultrasound images

Wed, 01 Jul 2026 00:00:00 GMT

Title: Deep learning-based segmentation of enamel, cementum, alveolar bone, and gingiva in periodontal ultrasound images Authors: Piao, Jiong-Zhen; Hu, Kyung-Seok; Jung, Han-Sung; Kim, Hee-Jin Abstract: Objectives: To develop a deep learning-based multi-class segmentation model for the simultaneous segmentation of key periodontal structures, including enamel, cementum, alveolar bone, and gingiva, in ultrasound images, and to enable precise localization of the cementoenamel junction (CEJ), alveolar bone crest (ABC), and gingival margin (GM). Methods: A novel dual-stream deep learning architecture featuring stochastic block shuffling was proposed. The model was trained for simultaneous four-class segmentation on an internal dataset of 752 images and validated on an external test set of 111 images. The resulting segmentation masks were subsequently used to identify three anatomical landmarks: the CEJ, ABC, and GM. Results: The model demonstrated strong segmentation performance, with median Dice similarity coefficient, intersection over union, precision, sensitivity, 95% Hausdorff distance, and average symmetric surface distance values of 0.891, 0.805, 0.887, 0.909, 0.083 mm, and 0.028 mm, respectively, for the internal set, and 0.841, 0.728, 0.781, 0.921, 0.089 mm, and 0.032 mm, respectively, for the external set. In the assessment of landmark localization accuracy, the model achieved median distance errors of 0.06 mm, 0.08 mm, and 0.06 mm for the CEJ, ABC, and GM, respectively. Conclusion: The proposed deep learning model enabled accurate automated multi-class segmentation of periodontal structures in ultrasound images and facilitated highly precise localization of anatomical landmarks derived from the segmentation masks. Clinical significance: The proposed automatic multi-class segmentation model may assist dental clinicians in visualizing and interpreting periodontal ultrasound images. This approach shows promise for supporting broader clinical adoption of ultrasonography for the evaluation of periodontal conditions and preoperative digital planning, including periodontal disease management, restorative treatment, and orthodontic care.

A premixed calcium hydroxylapatite/ carboxymethylcellulose-hyaluronic acid hybrid filler for skin quality

Wed, 01 Jul 2026 00:00:00 GMT

Title: A premixed calcium hydroxylapatite/ carboxymethylcellulose-hyaluronic acid hybrid filler for skin quality Authors: Lazzarotto, Andrea; Guida, Stefania; Kadouch, Jonathan; Fakih-Gomez, Nabil; Zerbinati, Nicola; Colombo, Luigi; Vitale, Massimo; Correa, Mariana Cesar; Yi, Kyu-Ho; 이규호 Abstract: Background: Hybrid injectable approaches combining calcium hydroxylapatite/carboxymethylcellulose with hyaluronic acid gels may improve both facial contour and skin quality. Methods: We retrospectively reviewed 12 women treated with a premixed hybrid filler injected in the subdermal plane across the mid-and lower-face. Outcomes were assessed at baseline and 4 months using the Merz Aesthetic Scales for mid-and lower-face aging severity, the Lemperle Wrinkle Severity Scale (cheek wrinkles), and a 5-point Global Aesthetic Improvement Scale for patient-reported "skin glow." Results: All Merz domains and cheek wrinkle severity improved at 4 months (cheek wrinkles, p < 0.001). Seven of 12 participants rated their skin glow as "much improved" or "very much improved," and all 12 reported at least "improved." No serious adverse events occurred; bruising resolved spontaneously within 1-2 weeks. Conclusions: In this retrospective case series, the premixed hybrid filler was well tolerated and was associated with improvement in mid-and lower-face aging severity and patient-perceived skin glow at 4 months. Level of evidence: IV. (c) 2026 The Authors. Published by Elsevier Ltd on behalf of British Association of Plastic, Reconstructive and Aesthetic Surgeons. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Establishment of standardized intraoral implant model in the rabbit edentulous diastema

Mon, 01 Jun 2026 00:00:00 GMT

Title: Establishment of standardized intraoral implant model in the rabbit edentulous diastema Authors: Dai, Xinning; Huang, Xiaoqiong; Deng, Xinwen; Ye, Zhiqian; Liu, Zixiang; Li, Weiran; Li, Yan; Wu, Shuyi; Li, Shujin Abstract: Rabbits have been valued for decades as a model for osseointegration research and biomaterial evaluation, owing to the practical handling, ethical acceptance, and cost-effectiveness. The rabbit model provides an optimal compromise between clinical translatability and practical experimental viability when compared to both large-animal and rodent alternatives. However, rabbit models face inconsistencies across implant site selection criteria, implant geometric configurations, and operative techniques, underscoring the urgent need for standardized experimental frameworks to improve cross-study comparability. The edentulous diastema in rabbit mandible-an anatomical edentulous zone between incisors and premolars-is recognized as a promising intraoral site for implant placement due to its enhanced trabecular bone density and superior volumetric capacity. In contrast to commonly used extragnathic sites (e.g., tibia, femur), which lack a relevant oral microenvironment, the mandibular diastema offers both close anatomical analogy to the human jaw and straightforward surgical access. Herein, we identified an anatomically optimal implant site in rabbit mandibular edentulous diastema utilizing micro-CT-based quantitative analyses and designed a customized implant according to the measured value. Subsequently, we developed a standardized operative workflow for implant placement, and evaluated the osseointegration following 4 weeks and 12 weeks of implantation. Furthermore, we confirmed the applicability of the standardized rabbit intraoral implant model for peri-implantitis modeling. Collectively, we established a workflow for standardizing an intraoral implant model in the edentulous diastema of rabbits which provide highly reproducible, economical, and effective platform for fundamental inquiries into osseointegration, the evaluation of novel implant surface coatings, and the initial screening of biomaterials.