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배수용,박정철,신현승,이용근,최성호,정의원 대한치주과학회 2014 Journal of Periodontal & Implant Science Vol.44 No.5
Purpose: The preferred material for bone augmentation beyond the envelope of skeletalbone is the bone block graft, due to its dimensional stability. We evaluated the necessity ofrigid fixation for the bone block graft, and compared the bone regeneration and volumemaintenance associated with grafting using a synthetic hydroxyapatite block (HAB) and anautogenous bone block (ABB) without rigid fixation on rabbit calvaria over two differentperiods. Methods: Cylinder-shaped synthetic HAB and ABB were positioned without fixation on therabbit calvarium (n=16). The animals were sacrificed at 4 or 8 weeks postoperatively, andthe grafted materials were analyzed at each healing period using microcomputed tomographyand histologic evaluation. Results: Integration of the graft and the recipient bed was observed in all specimens, althoughminor dislocation of the graft materials from the original position was evident insome specimens (six ABB and ten HAB samples). A tendency toward progressive bone resorptionwas observed in the grafted ABB but not in the grafted HAB, which maintained anintact appearance. In the HAB group, the area of new bone increased between 4 and 8weeks postoperatively, but the difference was not statistically significant. Conclusions: The nonfixed HAB was successfully integrated into the recipient bed afterboth healing periods in the rabbit calvaria. In spite of limited bone formation activity incomparison to ABB, HAB may be a favorable substitute osteoconductive bone material.
전산화 단층 촬영을 이용한 상악 전치부 자연치의 순측과 구개측 골의 두께 계측
배수용(Soo-Yong Bae),박정철(Jung-Chul Park,),손주연(Joo-Yeon Sohn),엄유정(Yoo-Jung Um),정의원(Ui-Won Jung),김창성(Chang-Sung Kim),조규성(Kyoo-Sung Cho),채중규(Jung-Kiu Chai),김종관(Chong-Kwan Kim),최성호(Seong-Ho Choi) 대한치과의사협회 2009 대한치과의사협회지 Vol.47 No.10
Purpose : Anterior region is crucial area for esthetic implant restoration. However, the alveolar process undergoes atrophy after removal of teeth and creates unfavorable situation for implant installation. The knowledge of the thickness of alveolar bone is required to estimate and expect the bone resorption after extraction. The aim of this study is to measure facial, palatal and faciopalatal bone thickness on maxillary anterior teeth. Methods : Facial, palatal, and faciopalatal bone thickness were measured on the computed tomography (CT) images from 57 patients, using an image analyzer program (Ondemand 3D<SUP>®</SUP>, Cybermed, Seoul, Korea). Results: The thickness of facial bone in incisors, lateral incisors and canines were less than 1 mm. The thickness of facial bone increased from anterior to posterior region and the thickness of palatal bone increased from posterior to anterior region. Conclusion ; The measurement can be used for planning implant surgery before extraction. CT has are clinically useful in the evaluation of thickness of alveolar bone.
다구찌 기법을 적용한 자동변속기 Calibration에 관한 연구
배수용(Suyong Bae) 한국자동차공학회 2018 한국자동차공학회 학술대회 및 전시회 Vol.2018 No.11
In this paper, we have developed a method to prepare for the production error by applying the Daguchi"s Method, which is a type of experiment design (D.O.E, Design of experiment). Especially, in the development of shift-quality of the automatic transmission, we proposed a method of optimizing the matching that can improve shift-quality by introducing the S / N ratio quality loss function.
Prediction of toxicity of chemicals in DPM based on ToxCast-CTD data
Su-Yong Bae(배수용),Jinhee Choi(최진희) 환경독성보건학회 2021 한국독성학회 심포지움 및 학술발표회 Vol.2021 No.5
Diesel Particulate Matter (DPM) refers to all particulates except exhaust gas among by-products generated during the combustion process of fuel in a diesel type internal combustion engine. According to research, DPM cause human respiratory health effects, neuroinflammation and impaired the reproductive functions. The characteristic of DPM is that the composition of DPM changes according to the process of generation, temperature, and composition ratio of fuel, and for this reason, toxicity evaluation for regulation is not smooth. In this study, to support evaluation and regulation of DPM, toxicity prediction machine learning model was trained by using ToxCast data. The data was curated and prepared in several steps for greater model performance. Six algorithms (Gradient Boosting Tree, Random Forest, Multi-layered Perceptron Network, k-Nearest Neighborhood, Logistic Regression, Naive Bayes) were used when training the model, and molecular fingerprints of each chemical were calculated to be used as training data. Model performance was evaluated by using F1 score. Among the trained models, models with sufficient performance were used to predict the activity of individual chemical substances in DPM. After that, using the results, pathways and diseases that may be related to the chemical were analyzed through the Comparative Toxicogenomic Database(CTD). As a result, two diseases (cancer and urogenital diseases) and two pathways (exogenous substance metabolism and arachidonic acid metabolism) showed the highest correlation with DPM. To validate this result, in vitro assay was performed in several endpoints. This study shows the possibility of predicting the category of potential toxicity of chemical, and it is expected to be helpful in evaluating chemicals efficiently.