1.Efficacy of Bone Regeneration Cell Therapy Using Mesenchymal Stem Cells Originating from Embryonic Stem Cells in Animal Models; Bone Defects and Osteomyelitis
Jin-Ho PARK ; Han-Sol BAE ; Ingeun KIM ; Jiwoon JUNG ; Yoonho ROH ; Dongbin LEE ; Tae Sung HWANG ; Hee-Chun LEE ; June-Ho BYUN
Tissue Engineering and Regenerative Medicine 2025;22(1):145-157
BACKGROUND:
Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture.
METHODS:
This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts.
RESULTS:
Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring.
CONCLUSION
Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.
2.Efficacy of Bone Regeneration Cell Therapy Using Mesenchymal Stem Cells Originating from Embryonic Stem Cells in Animal Models; Bone Defects and Osteomyelitis
Jin-Ho PARK ; Han-Sol BAE ; Ingeun KIM ; Jiwoon JUNG ; Yoonho ROH ; Dongbin LEE ; Tae Sung HWANG ; Hee-Chun LEE ; June-Ho BYUN
Tissue Engineering and Regenerative Medicine 2025;22(1):145-157
BACKGROUND:
Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture.
METHODS:
This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts.
RESULTS:
Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring.
CONCLUSION
Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.
3.Efficacy of Bone Regeneration Cell Therapy Using Mesenchymal Stem Cells Originating from Embryonic Stem Cells in Animal Models; Bone Defects and Osteomyelitis
Jin-Ho PARK ; Han-Sol BAE ; Ingeun KIM ; Jiwoon JUNG ; Yoonho ROH ; Dongbin LEE ; Tae Sung HWANG ; Hee-Chun LEE ; June-Ho BYUN
Tissue Engineering and Regenerative Medicine 2025;22(1):145-157
BACKGROUND:
Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture.
METHODS:
This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts.
RESULTS:
Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring.
CONCLUSION
Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.
4.Efficacy of Bone Regeneration Cell Therapy Using Mesenchymal Stem Cells Originating from Embryonic Stem Cells in Animal Models; Bone Defects and Osteomyelitis
Jin-Ho PARK ; Han-Sol BAE ; Ingeun KIM ; Jiwoon JUNG ; Yoonho ROH ; Dongbin LEE ; Tae Sung HWANG ; Hee-Chun LEE ; June-Ho BYUN
Tissue Engineering and Regenerative Medicine 2025;22(1):145-157
BACKGROUND:
Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture.
METHODS:
This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts.
RESULTS:
Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring.
CONCLUSION
Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.
5.Efficacy of Bone Regeneration Cell Therapy Using Mesenchymal Stem Cells Originating from Embryonic Stem Cells in Animal Models; Bone Defects and Osteomyelitis
Jin-Ho PARK ; Han-Sol BAE ; Ingeun KIM ; Jiwoon JUNG ; Yoonho ROH ; Dongbin LEE ; Tae Sung HWANG ; Hee-Chun LEE ; June-Ho BYUN
Tissue Engineering and Regenerative Medicine 2025;22(1):145-157
BACKGROUND:
Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture.
METHODS:
This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts.
RESULTS:
Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring.
CONCLUSION
Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.
6.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
7.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
8.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
9.Association Between IQ and Brain Susceptibility in Children With Autism Spectrum Disorder: Quantitative Susceptibility Mapping Study
Minsun KOO ; Siyun JUNG ; Jung-Hee LEE ; Min-Hyeon PARK ; Yoonho NAM ; Hyun Gi KIM
Investigative Magnetic Resonance Imaging 2024;28(2):68-75
Purpose:
Although previous studies have found an association between brain iron levels and brain function, few have explored this relationship in children with autism spectrum disorder (ASD). Thus, we aimed to determine the association between quantitative susceptibility mapping (QSM)-derived magnetic susceptibility values (MSVs) and brain function in children with ASD.
Materials and Methods:
The study included children with ASD who underwent both a brain magnetic resonance imaging with QSM and the Wechsler intelligence scale for children intelligence quotient (IQ) test. Select subcortical brain regions (caudate, putamen, globus pallidus, and thalamus; both right and left) were automatically segmented, and the MSVs were extracted from the QSM. The IQ score parameters (verbal comprehension, working memory, perceptual organization, and processing speed indices, and full-scale IQ) were measured. Correlation analysis was used to assess the association between age and IQ test parameters and between age and MSV. Linear regression analysis was performed to measure the relationship between the MSV and IQ test parameters.
Results:
A total of 23 children with ASD (median age [interquartile range]: 10 [8–14] years; 12 males) were included. Age was not correlated with any of the IQ test parameters (p > 0.05). There was a significant correlation between age and right-thalamus MSV (r = 0.443, p = 0.03); however, no such correlation was found with the MSVs of other regions (p > 0.05). Among the IQ test parameters, the verbal comprehension index significantly correlated with the left-caudate MSV (r = 0.420, p = 0.046) and the perceptual organization index significantly correlated with the right-globus-pallidus MSV (r = 0.414, p = 0.049).
Conclusion
Select subcortical MSVs were associated with IQ test parameters in children with ASD, suggesting that QSM is a potential neurodevelopmental marker.
10.Label-Preserving Data Augmentation for Robust Segmentation of Thin Structure in MRI
Wooseung KIM ; Yeonah KANG ; Seokhwan LEE ; Ho-Joon LEE ; Yoonho NAM
Investigative Magnetic Resonance Imaging 2024;28(3):107-113
Purpose:
This study aims to enhance the performance of deep learning models for segmenting thin anatomical structures in medical images by introducing a label-preserving data-augmentation strategy.
Materials and Methods:
We developed a data-augmentation technique that applies geometric transformations and their inverses sequentially to input images while preserving the corresponding labels. This method was evaluated on inner ear magnetic resonance images for the automatic segmentation of semicircular canals characterized by thin and circular structures. The dataset included both internal and external samples. For the internal dataset, 70 subjects were used for model training and eight subjects for internal validation. Images were acquired using a 3 tesla magnetic resonance imaging scanner with a three-dimensional high-resolution T2 sequence, and ground-truth segmentations were manually annotated by an experienced radiologist. For external validation, four subjects from a public dataset (Vestibular-Schwannoma-SEG dataset, part of The Cancer Imaging Archive) with high-resolution T2 images for inner ear analysis were used. We performed quantitative evaluations using metrics such as Dice, intersection over union (IoU), 95% Hausdorff distance (HD), and average surface distance (ASD). A qualitative visual assessment was also performed.
Results:
The proposed model exhibited improved performance in semicircular canal segmentation in both quantitative and qualitative evaluations. Metrics such as Dice, IoU, 95% HD, and ASD indicated better performance than conventional methods.
Conclusion
The proposed label-preserving data augmentation method improves the segmentation of thin anatomical structures in medical images and offers a robust and efficient solution for enhancing deep learning models in medical imaging.

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