Yonsei Dentistry "Symbiotic Biocompatible 3D Print Material Project" Obtained 4 Million Dollars of National Grant
Professor Sung-Hwan Choi, along with his research team at Yonsei University College of Dentistry and College of Medicine, is spearheading a national research project titled "Symbiotic biocompatible medical device material and productization technology development for patient-customized direct printed biliary stent-orthodontic appliance."
The project aims to develop productization technology for a 3D printing-based symbiotic biocompatible medical device that minimizes dysbiosis and enhances symbiotic performance. The project has secured substantial funding from Korea Evaluation Institute Of Industrial Technology(KEIT). For five years, the project will receive a generous amount of 4 million USD, enabling the team to pursue their goals.
Professor Choi stated that he will do his best to contribute to enhancing public health by developing medical device materials that not only facilitate rapid treatment and recovery in dentistry but also have potential applications in internal surgeries.
2 Million Dollars of National Fund Granted to Yonsei Dentistry "Development of CAD/CAM Hybrid Block and Anti-Carious Bioactive Material Project"
Professor Sung-Hwan Choi, from the Department of Orthodontics at Yonsei University College of Dentistry, is leading a significant research project that has grabbed the attention of the Korea Medical Device Development Fund (KMDF). The KMDF has selected Professor Choi's project as a 'National Project' and has allocated a substantial budget of 2 million USD to support its development.
The primary focus of the project is the research, development, and eventual production of a dental biomaterial that inhibits the formation of biofilms. To achieve this goal, Professor Choi has partnered with Hass Co., a company known for its expertise in lithium disilicate, glass ceramics.
Professor Choi's research team and Hass Co. aim to contribute to the fields of health and medicine by commercializing dental biomaterials and reducing dependence on foreign-made medical appliances.
Overall, the selection of Professor Choi's research project as a 'National Project' by the KMDF, coupled with the substantial funding support, signifies the recognition of its potential impact in advancing dental biomaterials research and their practical application.
1.6 Million Dollars Fund Raised in the Night of Gratitude and Progress, Envisioning YUCD's World Academic Platform
Yonsei University College of Dentistry hosted the “Night of Gratitude and Progress” on May 30, 2023. This event served as a celebration of the generosity of our donors and the unwavering dedication of our esteemed professors. We were also thrilled to announce that we have achieved an impressive QS World University Rankings for dentistry of 1st in Korea and 28th in the world.
The event brought together donors and professors who were invited to join us in celebrating our accomplishments and sharing our visions for the future. The evening was divided into two segments: the Night of Gratitude and the Night of Progress. During the Night of Gratitude, we revealed the total amount of donations received and expressed our gratitude for the support received. In total, 1.6 million dollars fund was raised in the event.
In the second part, the Night of Progress, we presented our institution's future development plan, outlining our strategic goals and aspirations. Throughout the Night of Gratitude, we showcased congratulatory video messages from collaborating foreign institutions, further emphasizing the importance of collaboration.
The "Night of Gratitude and Progress" was a memorable event that we extend our sincere appreciation to our donors, professors, and all those who have contributed to our journey towards excellence in dental education and research.
11th Yonsei International Mini-residency for Advanced Orthodontics Attracted 136 Participants from 24 Countries
The 11th Yonsei International Mini-residency for Advanced Orthodontics took place from June 19 to 27, 2023, attracting 136 orthodontists from 24 countries around the world. This renowned event was organized by the Department of Orthodontics, Institute of Craniofacial Deformity, Yonsei University College of Dentistry, focusing on essential biomechanics and up-to-date clinical protocols based on evidence. The program was featured by most of digital in-office technologies including application of intraoral scanner, facial scanner and related tools for diagnosis and appliance fabrication.
Yonsei Dentistry Forms International Partnerships
Yonsei University College of Dentistry has recently established three significant collaborative partnerships with promising international dental education institutes.
On March 27, 2023, we finalized a Dual Degree Program Agreement with Graduate School of Dental Science, National University Corporation Kyushu University in Japan. This agreement allows graduate students to obtain degrees from both universities, providing an excellent opportunity for talented students to broaden their academic horizons.
On May 26, 2023, we held a signing ceremony for the Memorandum of Understanding with Mahidol University Faculty of Dentistry in Thailand. This marked the second extension of our collaboration since the initial MoU was established in 2010. The extension underscores the strong bond and milestones achieved by both universities over the years.
On June 16, 2023, we signed a Memorandum of Agreement with Faculty of Dental Medicine, Universitas Airlangga in Indonesia. As this marks the first interaction between our institutions, we eagerly anticipate engaging in active and practical collaborations in the future.
These collaborations represent important milestones for Yonsei University College of Dentistry, fostering international relationships and promoting academic exchange among dental education institutes. We are excited about the prospects of these partnerships and the potential benefits they will bring to our students and faculties alike.
1. MAST4 controls cell cycle in spermatogonial stem cells
The spermatogenesis is a complex process that continuously maintains sperm production through self-renewal and differentiation of spermatogonial stem cells. Professor Han-Sung Jung’s research team found that MAST4, which is known to be expressed in testicular Sertoli cells, regulates self-renewal by maintaining the cell cycle in spermatogonial stem cells. This suggests that MAST4 regulates the interaction of CDK2-PLZF protein, which is involved in the cell cycle in spermatogonial stem cells, and a mechanism for restoring it through in vitro culture of testicular tissue from Mast4 knockout mice was also revealed. This study was published in the international journal ‘Cell Proliferation (Impact factor 8.755)’ in April 2023.
Division in Anatomy and Developmental Biology, Department of Oral Biology, Taste Research Center, Oral Science Research Center, BK21 FOUR Project, Yonsei University College of Dentistry
Abstract
Spermatogonial stem cell (SSC) self-renewal is regulated by reciprocal interactions between Sertoli cells and SSCs in the testis. In a previous study, microtubule-associated serine/threonine kinase 4 (MAST4) has been studied in Sertoli cells as a regulator of SSC self-renewal. The present study focused on the mechanism by which MAST4 in Sertoli cells transmits the signal and regulates SSCs, especially cell cycle regulation. The expression of PLZF, CDK2 and PLZF target genes was examined in WT and Mast4 KO testes by Immunohistochemistry, RT-qPCR and western blot. In addition, IdU and BrdU were injected into WT and Mast4 KO mice and cell cycle of SSCs was analysed. Finally, the testis tissues were cultured in vitro to examine the regulation of cell cycle by MAST4 pathway. Mast4 KO mice showed infertility with Sertoli cell-only syndrome and reduced sperm count. Furthermore, Mast4 deletion led to decreased PLZF expression and cell cycle progression in the testes. MAST4 also induced cyclin-dependent kinase 2 (CDK2) to phosphorylate PLZF and activated PLZF suppressed the transcriptional levels of genes related to cell cycle arrest, leading SSCs to remain stem cell state. MAST4 is essential for maintaining cell cycle in SSCs via the CDK2-PLZF interaction. These results demonstrate the pivotal role of MAST4 regulating cell cycle of SSCs and the significance of spermatogenesis.
2. Sonoanatomy and an ultrasound scanning protocol of the intramuscular innervation pattern of the infraspinatus muscle
Botulinum neurotoxin injection is a valuable treatment method for patients with myofascial pain syndrome in the infraspinatus muscle. However, there is no botulinum neurotoxin injection guideline, and the most appropriate injection site based on topographical anatomic information for this injection to effectively treat myofascial pain syndrome in the infraspinatus muscle is unclear. The purpose of this study was to evaluate the intramuscular nerve terminal of the infraspinatus muscle and to suggest the most efficient botulinum neurotoxin injection sites.
This study used 5 formalin-embalmed and 10 fresh frozen cadavers with a mean age of 78.9 years. Sihler’s staining was applied to evaluate the intramuscular nerve terminal of the infraspinatus muscle. The ultrasound scanning of the infraspinatus muscle was performed based on the surface landmarks and internal structures near the scapular region.
The intramuscular nerve terminal was mostly observed in the medial third area of the infraspinatus muscle. The deltoid tubercle, inferior angle, and acromion of the scapula are useful as surface landmarks to scan the infraspinatus muscle.
The proposed injection sites based on the intramuscular nerve terminal and surface landmarks can be regarded as accurate locations to reach the cluster area of the intramuscular nerve terminal and each compartment of the infraspinatus muscle to manage the myofascial pain syndrome in the infraspinatus muscle. This study was published in the international scientific journal 'Regional Anesthesia & Pain Medicine (impact factor 5.564)' in April 2023.
Hyung-Jin Lee: Catholic Institute for Applied Anatomy, Department of Anatomy, College of Medicine, The Catholic University of Korea, Seoul, Korea
Ji-Hyun Lee: Department of Anatomy and Acupoint, College of Korean Medicine, Gachon University, Seongnam, 13120 South Korea
Kyu-Ho Yi, Hee-Jin Kim: Division of Physiology, Division in Anatomy and Developmental Biology, Department of Oral Biology, Human Identification Research Institute, BK21 FOUR Project, Yonsei University College of Dentistry, Seoul, Korea
3. Prediction of Fishman’s skeletal maturity indicators using artificial intelligence
Skeletal maturity is particularly important in orthodontics for the determination of treatment timing and method. Fishman’s skeletal maturity indicators (SMI) are widely used for this purpose, as they are less time‑consuming and practical in clinical use compared to other methods. The research team led by Professor Sung‑Hwan Choi developed an automated skeletal maturation assessment system for SMI using a deep convolutional neural network and evaluated its performance. The system achieved a prediction accuracy of 0.772 and mean absolute error of 0.27, indicating a clinically reliable performance. This study was published in the international scientific journal 'Scientific Reports’ in April 2023.
Department of Orthodontics, Yonsei University College of Dentistry
Abstract
The present study aimed to evaluate the performance of automated skeletal maturation assessment system for Fishman's skeletal maturity indicators (SMI) for the use in dental fields. Skeletal maturity is particularly important in orthodontics for the determination of treatment timing and method. SMI is widely used for this purpose, as it is less time-consuming and practical in clinical use compared to other methods. Thus, the existing automated skeletal age assessment system based on Greulich and Pyle and Tanner-Whitehouse3 methods was further developed to include SMI using artificial intelligence. This hybrid SMI-modified system consists of three major steps: (1) automated detection of region of interest; (2) automated evaluation of skeletal maturity of each region; and (3) SMI stage mapping. The primary validation was carried out using a dataset of 2593 hand-wrist radiographs, and the SMI mapping algorithm was adjusted accordingly. The performance of the final system was evaluated on a test dataset of 711 hand-wrist radiographs from a different institution. The system achieved a prediction accuracy of 0.772 and mean absolute error and root mean square error of 0.27 and 0.604, respectively, indicating a clinically reliable performance. Thus, it can be used to improve clinical efficiency and reproducibility of SMI prediction.
4. Deep learning synthesis of cone-beam computed tomography from zero echo time magnetic resonance imaging
It has been about 20 years since cone-beam CT (CBCT), three-dimensional imaging, was introduced in the field of dentistry. In the meantime, the use of CBCT has been increased and it became an essential diagnostic tool in dental treatment planning. A research team of professor Sang-Sun Han paid attention to MRI, another innovative tool for the field of 3D-based dental diagnosis. The research team, together with Pohang University of Science and Technology and Korea Institute of Industrial Science and Technology, developed a deep learning-based image synthesis model that generates MRI, which is unfamiliar in the clinical field of dentistry, with a contrast similar to CBCT. The synthesized image was confirmed that it reached to the clinically applicable level. The impact of this study will be of practical help to patients who undergo MRI and CBCT together. The results of this research were published in April 2023 in the multidisciplinary international journal ‘Scientific Reports (impact factor 4.997)’.
Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry
Abstract
Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in small voxel size, but the process is associated with radiation exposure and poor soft tissue imaging. Thus, we synthesized a CBCT image from the magnetic resonance imaging (MRI), using deep learning and to assess its clinical accuracy. We collected patients who underwent both CBCT and MRI simultaneously in our institution (Seoul). MRI data were registered with CBCT data, and both data were prepared into 512 slices of axial, sagittal, and coronal sections. A deep learning-based synthesis model was trained and the output data were evaluated by comparing the original and synthetic CBCT (syCBCT). According to expert evaluation, syCBCT images showed better performance in terms of artifacts and noise criteria but had poor resolution compared to the original CBCT images. In syCBCT, hard tissue showed better clarity with significantly different MAE and SSIM. This study result would be a basis for replacing CBCT with non-radiation imaging that would be helpful for patients planning to undergo both MRI and CBCT.
5. Automated deep learning for classification of dental implant radiographs using a large multi-center dataset
This study aimed to evaluate the accuracy of automated deep learning (DL) algorithm for identifying and classifying various types of dental implant systems (DIS) using a large-scale multicenter dataset.
Dental implant radiographs of pos-implant surgery were collected from five college dental hospitals and 10 private dental clinics, and validated by the National Information Society Agency and the Korean Academy of Oral and Maxillofacial Implantology. The dataset contained a total of 156,965 panoramic and periapical radiographic images and comprised 10 manufacturers and 27 different types of DIS. The accuracy, precision, recall, F1 score, and confusion matrix were calculated to evaluate the classification performance of the automated DL algorithm. The performance metrics of the automated DL based on accuracy, precision, recall, and F1 score for 116,756 panoramic and 40,209 periapical radiographic images were 88.53%, 85.70%, 82.30%, and 84.00%, respectively. Using only panoramic images, the DL algorithm achieved 87.89% accuracy, 85.20% precision, 81.10% recall, and 83.10% F1 score, whereas the corresponding values using only periapical images achieved 86.87% accuracy, 84.40% precision, 81.70% recall, and 83.00% F1 score, respectively. Within the study limitations, automated DL shows a reliable classification accuracy based on large-scale and comprehensive datasets. Moreover, we observed no statistically significant difference in accuracy performance between the panoramic and periapical images. The clinical feasibility of the automated DL algorithm requires further confirmation using additional clinical datasets.
Korean Academy of Oral and Maxillofacial Implantology (KAOMI) Implant Research Institute, Seoul, Korea.
Wonse Park: Department of Advanced General Dentistry, Yonsei University College of Dentistry, Seoul, Korea.
Jong Ki Huh: Department of Oral and Maxillofacial Surgery, Gangnam Severance Hospital, Yonsei University College of Dentistry, 211 Eonju ro, Gangnam gu, Seoul 06273, Korea.
Jae Hong Lee: Department of Periodontology, College of Dentistry and Institute of Oral Bioscience, Jeonbuk National University, 567 Baekje daero, Deokjin gu, Jeonju 54896, Korea.
6. Effect of bacterial resistant zwitterionic derivative incorporation on the physical properties of resin-modified glass ionomer luting cement
Resin-modified glass ionomer cement (RMGIC) is a suitable option for bonding various restorations due to its ability to release fluoride ions, facilitate easy mechanical bonding with enamel and dentin, and provide superior aesthetics when compared to other types of glass-ionomer cement. However, microleakage at the restoration interface can easily lead to biofilm accumulation, resulting in treatment failure and a compromised final prosthesis. To address this issue, Prof. Sung-Hwan Choi (Department of Orthodontics) and Jae-Sung Kwon (Department and Research Institute of Dental Biomaterials and Bioengineering) utilized zwitterions, such as 2-methacryloyloxyethyl phosphorylcholine (MPC) and sulfobetaine methacrylate (SBMA), which possess surface hydration formation ability, in RMGIC. By incorporating 1 wt.% zwitterion, the adhesion to Streptococcus mutans (S. mutans) was reduced by a minimum of 30% compared to the control group, while mechanical properties such as flexural strength and bonding strength did not show significant differences. The optimal concentration of zwitterions that possess biofilm inhibition ability without compromising mechanical strength has been determined, which serves as a fundamental basis for the future advancement of zwitterionic-based RMGIC. This study was published in ‘Scientific Reports (IF 4.997)’ in March 2023.
Jae-Sung Kwon: Department and Research Institute of Dental Biomaterials and Bioengineering, Yonsei University College of Dentistry
Sung-Hwan Choi: Department of Orthodontics and Institute of Craniofacial Deformity, Yonsei University College of Dentistry
Abstract
Biofilms induce microbial-mediated surface roughening and deterioration of cement. In this study, zwitterionic derivatives (ZD) of sulfobetaine methacrylate (SBMA) and 2-methacryloyloxyethyl phosphorylcholine, were added in concentrations of 0, 1, and 3% to three different types of commercially available resin-modified glass ionomer cement (RMGIC) (RMC-I: RelyX Luting 2, RMC-II: Nexus RMGI, and RMC-III: GC FujiCEM 2). The unmodified RMGICs served as the control group for comparison. The resistance of Streptococcus mutans to ZD-modified RMGIC was evaluated with a monoculture biofilm assay. The following physical properties of the ZD-modified RMGIC were assessed: wettability, film thickness, flexural strength, elastic modulus, shear bond strength, and failure mode. The ZD-modified RMGIC significantly inhibited biofilm formation, with at least a 30% reduction compared to the control group. The addition of ZD improved the wettability of RMGIC; however, only 3% of the SBMA group was statistically different (P < 0.05). The film thickness increased in proportion to the increasing ZD concentrations; there was no statistical difference within the RMC-I (P > 0.05). The experimental groups' flexural strength, elastic modulus, and shear bond strength showed an insignificant decrease from the control group; there was no statistical difference within the RMC-I (P > 0.05). The mode of failure differed slightly in each group, but all groups showed dominance in the adhesive and mixed failure. Thus, the addition of 1 wt.% ZD in RMGIC favorably enhanced the resistance to Streptococcus mutans without any tangible loss in flexural and shear bond strength.