Alzheimer’s disease (AD) is characterized by progressive cognitive deterioration and significant depression. However, the mechanisms linking depression to AD pathology remain unclear. Here, we investigated whether Notch2 signaling mediates depressionlike behaviors in presenilin-2 (PS2) N141I mutant mice, an early-onset AD model. PS2 wild-type (WT) and mutant (MT) mice aged 12-15 months were subjected to unpredictable chronic mild stress (UCMS) for 4 weeks, followed by sucrose preference, tail-hanging, and forced swimming tests. Behavioral assessments showed that UCMS exacerbated anhedonia and immobility only in PS2 MT mice. Molecular analysis revealed concomitant increases in plasma corticosterone, hippocampal γ-secretase activity, and Notch2 expression, and elevated total and phosphorylated glucocorticoid receptor levels in PS2 MT-UCMS mice. Gene expression profiling of human hippocampal datasets confirmed upregulation of NOTCH2 in Alzheimer’s disease and depression.Pharmacological inhibition of γ-secretase and Notch signaling with DAPT normalizes depressive behavior, reduces corticosterone release, attenuates GR phosphorylation, and inhibits Notch2 signaling in PS2 MT mice. These findings identify Notch2 as a pivotal mediator linking chronic stress to molecular changes associated with depression and AD, and suggest that targeting Notch2 signaling may provide therapeutic benefits for comorbid mood and neurodegenerative disorders.

Purpose: Biliary atresia (BA) is a rare but progressive cholangiopathy and the leading cause of pediatric liver transplantation worldwide. The Korean Association of Pediatric Surgeons (KAPS) has conducted three national surveys (2001, 2011, and 2023) to assess long-term trends in the diagnosis, treatment, and outcomes of BA. This study provides a comparative analysis of the 2nd and 3rd national surveys, with reference to selected findings from the 1st survey. Methods: This study included 453 patients from the 3rd national survey (2011–2021) and 435 patients from the 2nd survey (2001–2010), all of whom underwent Kasai portoenterostomy. Data were collected via electronic case report forms from pediatric surgical centers nationwide. Comparisons were made regarding demographics, clinical features, diagnostic patterns, operative details, follow-up outcomes, and survival. Kaplan–Meier analysis was used to evaluate long-term survival. Results: The mean number of BA patients per year remained stable between surveys (43.5 in the 2nd, 41.18 in the 3rd), though centralization of care increased, with 61.5% of cases managed by two major institutions in the 3rd survey. The median age at surgery decreased, and the use of preoperative imaging (especially magnetic resonance cholangiopancreatography) increased. The 10-year native liver survival rate declined from 59.8% to 53.7%, while overall 10-year survival improved slightly (92.9% to 93.2%). Postoperative complications, such as cholangitis and liver failure, persisted but were better categorized. The 3rd survey also reported improved mortality (4.9%) and reduced follow-up loss (11.5%) compared to the 2nd survey. Conclusion While overall survival after Kasai operation has remained high and even improved, native liver survival has slightly declined. The findings reflect earlier diagnosis, more consistent diagnostic imaging, and increasing centralization of care. These trends underscore the importance of long-term nationwide data collection in guiding future strategies for BA management in Korea.

Purpose: This study aims to investigate and compare the incidence, demographic characteristics, clinical manifestations, preoperative diagnostic methods, anatomical classifications, associated anomalies, operative treatments, and postoperative outcomes of patients with intestinal atresia treated by the members of the Korean Association of Pediatric Surgeons (KAPS) through three nationwide surveys. Methods: KAPS conducted 3 national surveys in 1998, 2010, and 2024 to examine the patients diagnosed with intestinal atresia. In preparation for the survey, we developed a customized case registration form to obtain data on patient sex, birth weight, gestational age, clinical manifestations, preoperative diagnostic methods, anatomical types, associated anomalies, operative treatments, and postoperative outcomes. Authorized KAPS members completed the case registration form. Results: The first, second, and third national surveys included 218, 222, and 236 individuals diagnosed with intestinal atresia, respectively. The male-to-female ratios were 1.5:1, 1.1:1, and 1.1:1, respectively. The first, second, and third national surveys revealed that 34.3%, 43.3%, and 53.4% of patients were born before 37 weeks of gestation, respectively. Additionally, 28.7%, 32.0%, and 40.7% of patients had a birth weight under 2,500 g. In the third national survey, duodenoduodenostomy was the most common procedure, performed in 70 out of 82 patients diagnosed with duodenal atresia. Resection and anastomosis were the main surgical procedures conducted in 47 out of 54 cases of jejunal atresia and 74 out of 92 cases of ileal atresia. The mortality rates in the first, second, and third national surveys were 13.8%, 3.6%, and 1.3% respectively, with the lowest rate observed in the third national survey. Conclusion These national surveys offer valuable insights into the current state of intestinal atresia, including specific surgical interventions and postoperative outcomes in South Korea. For pediatric surgeons aiming to enhance their understanding of intestinal atresia and its treatment options, these surveys could be an indispensable resource and guide.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics—compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)—from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. Results: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. Conclusion The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics—compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)—from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. Results: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. Conclusion The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.

Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics—compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)—from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. Results: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. Conclusion The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.