Background: Dental caries is a prevalent public health problem among adolescents that significantly affects their quality of life. The Caries Management by Risk Assessment (CAMBRA) model provides a structured, risk-based approach for caries prevention and management. This study evaluated the effectiveness of the CAMBRA-students mobile application, integrated with an information and communication technology (ICT) based intervention, in modifying caries risk factors in middle school students. Methods: A non-equivalent control group pretest-posttest design was used. A total of 131 middle school students aged 13∼14 years participated. The experimental group (n=68) received a risk-based intervention using the CAMBRA-student mobile application for 1 year, while the control group (n=63) received only standard oral health education and underwent pre- and post-tests. Data on caries risk factors; protective factors; disease indicators; and decayed, missing, and filled teeth rates were collected. Paired and independent t-tests were conducted to analyze changes within and between groups. Results: The rate of change in the caries risk classification before and after the intervention differed between the groups. In the control group, 50% of the low-risk participants were at a high-risk after 12 months. In the intervention group, 90% of the low-risk participants shifted to the high-risk category, and those classified as extremely high-risk moved to the high-risk category. When comparing changes in the caries risk assessment before and after the intervention, both groups demonstrated a significant increase in protective factors (p＜0.001). However, disease indicators increased significantly in the control, whereas no significant change was noted in the intervention group. Conclusion This study evaluated the effectiveness of an ICT-based caries management program for middle school students and confirmed changes in protective factors and specific oral health behaviors through personalized interventions. Future studies should investigate the long-term sustainability of such interventions across diverse populations to further establish their effectiveness.

Background: Dental caries is a prevalent public health problem among adolescents that significantly affects their quality of life. The Caries Management by Risk Assessment (CAMBRA) model provides a structured, risk-based approach for caries prevention and management. This study evaluated the effectiveness of the CAMBRA-students mobile application, integrated with an information and communication technology (ICT) based intervention, in modifying caries risk factors in middle school students. Methods: A non-equivalent control group pretest-posttest design was used. A total of 131 middle school students aged 13∼14 years participated. The experimental group (n=68) received a risk-based intervention using the CAMBRA-student mobile application for 1 year, while the control group (n=63) received only standard oral health education and underwent pre- and post-tests. Data on caries risk factors; protective factors; disease indicators; and decayed, missing, and filled teeth rates were collected. Paired and independent t-tests were conducted to analyze changes within and between groups. Results: The rate of change in the caries risk classification before and after the intervention differed between the groups. In the control group, 50% of the low-risk participants were at a high-risk after 12 months. In the intervention group, 90% of the low-risk participants shifted to the high-risk category, and those classified as extremely high-risk moved to the high-risk category. When comparing changes in the caries risk assessment before and after the intervention, both groups demonstrated a significant increase in protective factors (p＜0.001). However, disease indicators increased significantly in the control, whereas no significant change was noted in the intervention group. Conclusion This study evaluated the effectiveness of an ICT-based caries management program for middle school students and confirmed changes in protective factors and specific oral health behaviors through personalized interventions. Future studies should investigate the long-term sustainability of such interventions across diverse populations to further establish their effectiveness.

Background: Dental caries is a prevalent public health problem among adolescents that significantly affects their quality of life. The Caries Management by Risk Assessment (CAMBRA) model provides a structured, risk-based approach for caries prevention and management. This study evaluated the effectiveness of the CAMBRA-students mobile application, integrated with an information and communication technology (ICT) based intervention, in modifying caries risk factors in middle school students. Methods: A non-equivalent control group pretest-posttest design was used. A total of 131 middle school students aged 13∼14 years participated. The experimental group (n=68) received a risk-based intervention using the CAMBRA-student mobile application for 1 year, while the control group (n=63) received only standard oral health education and underwent pre- and post-tests. Data on caries risk factors; protective factors; disease indicators; and decayed, missing, and filled teeth rates were collected. Paired and independent t-tests were conducted to analyze changes within and between groups. Results: The rate of change in the caries risk classification before and after the intervention differed between the groups. In the control group, 50% of the low-risk participants were at a high-risk after 12 months. In the intervention group, 90% of the low-risk participants shifted to the high-risk category, and those classified as extremely high-risk moved to the high-risk category. When comparing changes in the caries risk assessment before and after the intervention, both groups demonstrated a significant increase in protective factors (p＜0.001). However, disease indicators increased significantly in the control, whereas no significant change was noted in the intervention group. Conclusion This study evaluated the effectiveness of an ICT-based caries management program for middle school students and confirmed changes in protective factors and specific oral health behaviors through personalized interventions. Future studies should investigate the long-term sustainability of such interventions across diverse populations to further establish their effectiveness.

Peripheral neurodegenerative diseases induced by irreversible peripheral nerve degeneration (PND), such as diabetic peripheral neuropathy, have a high prevalence worldwide and reduce the quality of life. However, there is no agent effective against the irreversible PND. After peripheral nerve injury, Schwann cells play an important role in regulating PND. However, because PND involves multiple biochemical events in Schwann cells, a one-drug-single-target therapeutic strategy is not feasible for PND. Here, we suggested that fascaplysin (Fas), a compound with multiple targets (CDK4/6), could overcome these problems. Fas exerted a significant inhibitory effect on axonal degradation, demyelination, and Schwann cell proliferation and dedifferentiation during in vitro and ex vivo PND. To discover the most likely novel target for PND, a chemo-bioinformatics analysis predicted the other on-targets of Fas and identified androgen receptor (AR) which were involved in Schwann cell differentiation and proliferation.AR interacted with Fas, and nuclear import of the AR/Fas complex was inhibited in Schwann cells, altering the expression patterns of transcription factors during PND. Therefore, Fas may have therapeutic potential for irreversible peripheral neurodegenerative diseases.

Peripheral neurodegenerative diseases induced by irreversible peripheral nerve degeneration (PND), such as diabetic peripheral neuropathy, have a high prevalence worldwide and reduce the quality of life. However, there is no agent effective against the irreversible PND. After peripheral nerve injury, Schwann cells play an important role in regulating PND. However, because PND involves multiple biochemical events in Schwann cells, a one-drug-single-target therapeutic strategy is not feasible for PND. Here, we suggested that fascaplysin (Fas), a compound with multiple targets (CDK4/6), could overcome these problems. Fas exerted a significant inhibitory effect on axonal degradation, demyelination, and Schwann cell proliferation and dedifferentiation during in vitro and ex vivo PND. To discover the most likely novel target for PND, a chemo-bioinformatics analysis predicted the other on-targets of Fas and identified androgen receptor (AR) which were involved in Schwann cell differentiation and proliferation.AR interacted with Fas, and nuclear import of the AR/Fas complex was inhibited in Schwann cells, altering the expression patterns of transcription factors during PND. Therefore, Fas may have therapeutic potential for irreversible peripheral neurodegenerative diseases.

Peripheral neurodegenerative diseases induced by irreversible peripheral nerve degeneration (PND), such as diabetic peripheral neuropathy, have a high prevalence worldwide and reduce the quality of life. However, there is no agent effective against the irreversible PND. After peripheral nerve injury, Schwann cells play an important role in regulating PND. However, because PND involves multiple biochemical events in Schwann cells, a one-drug-single-target therapeutic strategy is not feasible for PND. Here, we suggested that fascaplysin (Fas), a compound with multiple targets (CDK4/6), could overcome these problems. Fas exerted a significant inhibitory effect on axonal degradation, demyelination, and Schwann cell proliferation and dedifferentiation during in vitro and ex vivo PND. To discover the most likely novel target for PND, a chemo-bioinformatics analysis predicted the other on-targets of Fas and identified androgen receptor (AR) which were involved in Schwann cell differentiation and proliferation.AR interacted with Fas, and nuclear import of the AR/Fas complex was inhibited in Schwann cells, altering the expression patterns of transcription factors during PND. Therefore, Fas may have therapeutic potential for irreversible peripheral neurodegenerative diseases.

Peripheral neurodegenerative diseases induced by irreversible peripheral nerve degeneration (PND), such as diabetic peripheral neuropathy, have a high prevalence worldwide and reduce the quality of life. However, there is no agent effective against the irreversible PND. After peripheral nerve injury, Schwann cells play an important role in regulating PND. However, because PND involves multiple biochemical events in Schwann cells, a one-drug-single-target therapeutic strategy is not feasible for PND. Here, we suggested that fascaplysin (Fas), a compound with multiple targets (CDK4/6), could overcome these problems. Fas exerted a significant inhibitory effect on axonal degradation, demyelination, and Schwann cell proliferation and dedifferentiation during in vitro and ex vivo PND. To discover the most likely novel target for PND, a chemo-bioinformatics analysis predicted the other on-targets of Fas and identified androgen receptor (AR) which were involved in Schwann cell differentiation and proliferation.AR interacted with Fas, and nuclear import of the AR/Fas complex was inhibited in Schwann cells, altering the expression patterns of transcription factors during PND. Therefore, Fas may have therapeutic potential for irreversible peripheral neurodegenerative diseases.

Objectives: In the Fourth Industrial Revolution, there is a focus on managing diverse medical data to improve healthcare and prevent disease. The challenges include tracking detailed medical records across multiple institutions and the necessity of linking domestic public medical entities for efficient data sharing. This study explores MyHealthWay, a Korean healthcare platform designed to facilitate the integration and transfer of medical data from various sources, examining its development, importance, and legal implications. Methods: To evaluate the management status and utilization of MyHealthWay, we analyzed data types, security, legal issues, domestic versus international issues, and infrastructure. Additionally, we discussed challenges such as resource and infrastructure constraints, regulatory hurdles, and future considerations for data management. Results: The secure sharing of medical information via MyHealthWay can reduce the distance between patients and healthcare facilities, fostering personalized care and self-management of health. However, this approach faces legal challenges, particularly relating to data standardization and access to personal health information. Legal challenges in data standardization and access, particularly for secondary uses such as research, necessitate improved regulations. There is a crucial need for detailed governmental guidelines and clear data ownership standards at institutional levels. Conclusions This report highlights the role of Korea's MyHealthWay, which was launched in 2023, in transforming healthcare through systematic data integration. Challenges include data privacy and legal complexities, and there is a need for data standardization and individual empowerment in health data management within a systematic medical big data framework.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.