1.Fine particulate matter induces osteoclast-mediated bone loss in mice
Hye Young MUN ; Septika PRISMASARI ; Jeong Hee HONG ; Hana LEE ; Doyong KIM ; Han Sung KIM ; Dong Min SHIN ; Jung Yun KANG
The Korean Journal of Physiology and Pharmacology 2025;29(1):9-19
Fine particulate matter (FPM) is a major component of air pollution and has emerged as a significant global health concern owing to its adverse health effects. Previous studies have investigated the correlation between bone health and FPM through cohort or review studies. However, the effects of FPM exposure on bone health are poorly understood. This study aimed to investigate the effects of FPM on bone health and elucidate these effects in vitro and in vivo using mice. Micro-CT analysis in vivo revealed FPM exposure decreased bone mineral density, trabecular bone volume/total volume ratio, and trabecular number in the femurs of mice, while increasing trabecular separation. Histological analysis showed that the FPM-treated group had a reduced trabecular area and an increased number of osteoclasts in the bone tissue. Moreover, in vitro studies revealed that low concentrations of FPM significantly enhanced osteoclast differentiation. These findings further support the notion that short-term FPM exposure negatively impacts bone health, providing a foundation for further research on this topic.
2.Fine particulate matter induces osteoclast-mediated bone loss in mice
Hye Young MUN ; Septika PRISMASARI ; Jeong Hee HONG ; Hana LEE ; Doyong KIM ; Han Sung KIM ; Dong Min SHIN ; Jung Yun KANG
The Korean Journal of Physiology and Pharmacology 2025;29(1):9-19
Fine particulate matter (FPM) is a major component of air pollution and has emerged as a significant global health concern owing to its adverse health effects. Previous studies have investigated the correlation between bone health and FPM through cohort or review studies. However, the effects of FPM exposure on bone health are poorly understood. This study aimed to investigate the effects of FPM on bone health and elucidate these effects in vitro and in vivo using mice. Micro-CT analysis in vivo revealed FPM exposure decreased bone mineral density, trabecular bone volume/total volume ratio, and trabecular number in the femurs of mice, while increasing trabecular separation. Histological analysis showed that the FPM-treated group had a reduced trabecular area and an increased number of osteoclasts in the bone tissue. Moreover, in vitro studies revealed that low concentrations of FPM significantly enhanced osteoclast differentiation. These findings further support the notion that short-term FPM exposure negatively impacts bone health, providing a foundation for further research on this topic.
3.Fine particulate matter induces osteoclast-mediated bone loss in mice
Hye Young MUN ; Septika PRISMASARI ; Jeong Hee HONG ; Hana LEE ; Doyong KIM ; Han Sung KIM ; Dong Min SHIN ; Jung Yun KANG
The Korean Journal of Physiology and Pharmacology 2025;29(1):9-19
Fine particulate matter (FPM) is a major component of air pollution and has emerged as a significant global health concern owing to its adverse health effects. Previous studies have investigated the correlation between bone health and FPM through cohort or review studies. However, the effects of FPM exposure on bone health are poorly understood. This study aimed to investigate the effects of FPM on bone health and elucidate these effects in vitro and in vivo using mice. Micro-CT analysis in vivo revealed FPM exposure decreased bone mineral density, trabecular bone volume/total volume ratio, and trabecular number in the femurs of mice, while increasing trabecular separation. Histological analysis showed that the FPM-treated group had a reduced trabecular area and an increased number of osteoclasts in the bone tissue. Moreover, in vitro studies revealed that low concentrations of FPM significantly enhanced osteoclast differentiation. These findings further support the notion that short-term FPM exposure negatively impacts bone health, providing a foundation for further research on this topic.
4.Fine particulate matter induces osteoclast-mediated bone loss in mice
Hye Young MUN ; Septika PRISMASARI ; Jeong Hee HONG ; Hana LEE ; Doyong KIM ; Han Sung KIM ; Dong Min SHIN ; Jung Yun KANG
The Korean Journal of Physiology and Pharmacology 2025;29(1):9-19
Fine particulate matter (FPM) is a major component of air pollution and has emerged as a significant global health concern owing to its adverse health effects. Previous studies have investigated the correlation between bone health and FPM through cohort or review studies. However, the effects of FPM exposure on bone health are poorly understood. This study aimed to investigate the effects of FPM on bone health and elucidate these effects in vitro and in vivo using mice. Micro-CT analysis in vivo revealed FPM exposure decreased bone mineral density, trabecular bone volume/total volume ratio, and trabecular number in the femurs of mice, while increasing trabecular separation. Histological analysis showed that the FPM-treated group had a reduced trabecular area and an increased number of osteoclasts in the bone tissue. Moreover, in vitro studies revealed that low concentrations of FPM significantly enhanced osteoclast differentiation. These findings further support the notion that short-term FPM exposure negatively impacts bone health, providing a foundation for further research on this topic.
5.Fine particulate matter induces osteoclast-mediated bone loss in mice
Hye Young MUN ; Septika PRISMASARI ; Jeong Hee HONG ; Hana LEE ; Doyong KIM ; Han Sung KIM ; Dong Min SHIN ; Jung Yun KANG
The Korean Journal of Physiology and Pharmacology 2025;29(1):9-19
Fine particulate matter (FPM) is a major component of air pollution and has emerged as a significant global health concern owing to its adverse health effects. Previous studies have investigated the correlation between bone health and FPM through cohort or review studies. However, the effects of FPM exposure on bone health are poorly understood. This study aimed to investigate the effects of FPM on bone health and elucidate these effects in vitro and in vivo using mice. Micro-CT analysis in vivo revealed FPM exposure decreased bone mineral density, trabecular bone volume/total volume ratio, and trabecular number in the femurs of mice, while increasing trabecular separation. Histological analysis showed that the FPM-treated group had a reduced trabecular area and an increased number of osteoclasts in the bone tissue. Moreover, in vitro studies revealed that low concentrations of FPM significantly enhanced osteoclast differentiation. These findings further support the notion that short-term FPM exposure negatively impacts bone health, providing a foundation for further research on this topic.
6.A Proposal for a Predictive Model for the Number of Patients with Periodontitis Exposed to Particulate Matter and Atmospheric Factors Using Deep Learning
Septika PRISMASARI ; Kyuseok KIM ; Hye Young MUN ; Jung Yun KANG
Journal of Dental Hygiene Science 2024;24(1):22-28
Background:
Particulate matter (PM) has been extensively observed due to its negative association with human health. Previousresearch revealed the possible negative effect of air pollutant exposure on oral health. However, the predictive model between air pollutant exposure and the prevalence of periodontitis has not been observed yet. Therefore, this study aims to propose a predictive model for the number of patients with periodontitis exposed to PM and atmospheric factors in South Korea using deep learning.
Methods:
This study is a retrospective cohort study utilizing secondary data from the Korean Statistical Information Service andthe Health Insurance Review and Assessment database for air pollution and the number of patients with periodontitis, respectively. Data from 2015 to 2022 were collected and consolidated every month, organized by region. Following data matching and management, the deep neural networks (DNN) model was applied, and the mean absolute percentage error (MAPE) value was calculated to ensure the accuracy of the model.
Results:
As we evaluated the DNN model with MAPE, the multivariate model of air pollution including exposure to PM2.5, PM10, and other atmospheric factors predict approximately 85% of the number of patients with periodontitis. The MAPE value ranged from 12.85 to 17.10 (mean±standard deviation=14.12±1.30), indicating a commendable level of accuracy.
Conclusion
In this study, the predictive model for the number of patients with periodontitis is developed based on air pollution,including exposure to PM2.5, PM10, and other atmospheric factors. Additionally, various relevant factors are incorporated into the developed predictive model to elucidate specific causal relationships. It is anticipated that future research will lead to the development of a more accurate model for predicting the number of patients with periodontitis.

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