Background: Patients with diabetes are known to be at high risk for end-stage kidney disease (ESKD), but the accurate annual risk data for new-onset ESKD is still limited. In South Korea, the prevalence and incidence of ESKD are increasing more rapidly compared to the global average. This study aimed to determine the incidence rate (IR) of ESKD by diabetes status from 2012 to 2022. Methods: Using data from the Korean National Health Insurance Service, we calculated the IR and hazard ratio (HR) for newonset ESKD in the general population. Individuals were categorized based on diabetes status into nondiabetes, impaired fasting glucose (IFG), diabetes duration <5 and ≥5 years. Results: Among the participants, 67.6% were nondiabetic, 22.3% had IFG, and 10% had diabetes. In Korea, the IRs of ESKD were 139 per million population (pmp) for nondiabetes, 188 pmp for IFG, 632 pmp for diabetes <5 years, and 3,403 pmp for diabetes ≥5 years. An advanced estimated glomerular filtration rate (eGFR) category was the strongest risk factor for ESKD development. However, even in patients with normal renal function, those with long-standing diabetes had a 14-fold higher risk of ESKD compared to nondiabetic individuals. The risk of ESKD associated with diabetes increased exponentially with declining renal function. Notably, IFG showed an increasing tendency for ESKD in younger patients (<65 years) with early-stage chronic kidney disease (CKD; eGFR ≥60 mL/min/1.73 m²). Conclusion Longer diabetes duration amplifies ESKD risk, particularly as renal function declines. Even in patients with normal renal function, long-standing diabetes significantly increases ESKD risk, while IFG is associated with elevated risk only in younger individuals with early-stage CKD.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Background: Patients with diabetes are known to be at high risk for end-stage kidney disease (ESKD), but the accurate annual risk data for new-onset ESKD is still limited. In South Korea, the prevalence and incidence of ESKD are increasing more rapidly compared to the global average. This study aimed to determine the incidence rate (IR) of ESKD by diabetes status from 2012 to 2022. Methods: Using data from the Korean National Health Insurance Service, we calculated the IR and hazard ratio (HR) for newonset ESKD in the general population. Individuals were categorized based on diabetes status into nondiabetes, impaired fasting glucose (IFG), diabetes duration <5 and ≥5 years. Results: Among the participants, 67.6% were nondiabetic, 22.3% had IFG, and 10% had diabetes. In Korea, the IRs of ESKD were 139 per million population (pmp) for nondiabetes, 188 pmp for IFG, 632 pmp for diabetes <5 years, and 3,403 pmp for diabetes ≥5 years. An advanced estimated glomerular filtration rate (eGFR) category was the strongest risk factor for ESKD development. However, even in patients with normal renal function, those with long-standing diabetes had a 14-fold higher risk of ESKD compared to nondiabetic individuals. The risk of ESKD associated with diabetes increased exponentially with declining renal function. Notably, IFG showed an increasing tendency for ESKD in younger patients (<65 years) with early-stage chronic kidney disease (CKD; eGFR ≥60 mL/min/1.73 m²). Conclusion Longer diabetes duration amplifies ESKD risk, particularly as renal function declines. Even in patients with normal renal function, long-standing diabetes significantly increases ESKD risk, while IFG is associated with elevated risk only in younger individuals with early-stage CKD.

Background: Patients with diabetes are known to be at high risk for end-stage kidney disease (ESKD), but the accurate annual risk data for new-onset ESKD is still limited. In South Korea, the prevalence and incidence of ESKD are increasing more rapidly compared to the global average. This study aimed to determine the incidence rate (IR) of ESKD by diabetes status from 2012 to 2022. Methods: Using data from the Korean National Health Insurance Service, we calculated the IR and hazard ratio (HR) for newonset ESKD in the general population. Individuals were categorized based on diabetes status into nondiabetes, impaired fasting glucose (IFG), diabetes duration <5 and ≥5 years. Results: Among the participants, 67.6% were nondiabetic, 22.3% had IFG, and 10% had diabetes. In Korea, the IRs of ESKD were 139 per million population (pmp) for nondiabetes, 188 pmp for IFG, 632 pmp for diabetes <5 years, and 3,403 pmp for diabetes ≥5 years. An advanced estimated glomerular filtration rate (eGFR) category was the strongest risk factor for ESKD development. However, even in patients with normal renal function, those with long-standing diabetes had a 14-fold higher risk of ESKD compared to nondiabetic individuals. The risk of ESKD associated with diabetes increased exponentially with declining renal function. Notably, IFG showed an increasing tendency for ESKD in younger patients (<65 years) with early-stage chronic kidney disease (CKD; eGFR ≥60 mL/min/1.73 m²). Conclusion Longer diabetes duration amplifies ESKD risk, particularly as renal function declines. Even in patients with normal renal function, long-standing diabetes significantly increases ESKD risk, while IFG is associated with elevated risk only in younger individuals with early-stage CKD.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Background: Patients with diabetes are known to be at high risk for end-stage kidney disease (ESKD), but the accurate annual risk data for new-onset ESKD is still limited. In South Korea, the prevalence and incidence of ESKD are increasing more rapidly compared to the global average. This study aimed to determine the incidence rate (IR) of ESKD by diabetes status from 2012 to 2022. Methods: Using data from the Korean National Health Insurance Service, we calculated the IR and hazard ratio (HR) for newonset ESKD in the general population. Individuals were categorized based on diabetes status into nondiabetes, impaired fasting glucose (IFG), diabetes duration <5 and ≥5 years. Results: Among the participants, 67.6% were nondiabetic, 22.3% had IFG, and 10% had diabetes. In Korea, the IRs of ESKD were 139 per million population (pmp) for nondiabetes, 188 pmp for IFG, 632 pmp for diabetes <5 years, and 3,403 pmp for diabetes ≥5 years. An advanced estimated glomerular filtration rate (eGFR) category was the strongest risk factor for ESKD development. However, even in patients with normal renal function, those with long-standing diabetes had a 14-fold higher risk of ESKD compared to nondiabetic individuals. The risk of ESKD associated with diabetes increased exponentially with declining renal function. Notably, IFG showed an increasing tendency for ESKD in younger patients (<65 years) with early-stage chronic kidney disease (CKD; eGFR ≥60 mL/min/1.73 m²). Conclusion Longer diabetes duration amplifies ESKD risk, particularly as renal function declines. Even in patients with normal renal function, long-standing diabetes significantly increases ESKD risk, while IFG is associated with elevated risk only in younger individuals with early-stage CKD.

Mycophenolate mofetil (MMF) is usually prescribed with a reduced fixed dose in Asian kidney transplant recipients (KTRs). However, the clinical efficacy and safety of the fixed dose have not yet been investigated via therapeutic drug monitoring. We evaluated whether reduced fixed-dose MMF is an optimal dosing strategy to achieve the therapeutic target of mycophenolic acid (MPA) exposure in Korean KTRs. Methods: This open-label, prospective study enrolled 50 de novo KTRs prescribed with tacrolimus, corticosteroid, and fixed-dose MMF (1.0–1.5 g/day). The trough level (C0) and area under the curve (AUC0–12 hr) of MPA were measured at 1 and 24 weeks after kidney transplantation (KT). The relationship of body weight (BW)-adjusted MMF dose with MPA C0 and MPA AUC0–12 hr was assessed using linear regression analysis. Results: The initial fixed dose of MMF of 1.44 ± 0.16 g/day was adjusted in 24 patients (48.0%) and then reduced to a mean dose of 1.19 ± 0.31 g/day at 24 weeks after KT. Most patients (≥84.0%) attained the minimum required MPA C0 of 1.0 μg/mL and MPA AUC0–12 hr of 30 μg × hr/mL at 1 and 24 weeks. The BW-adjusted MMF dose demonstrated significant positive correlations with MPA C0 and MPA AUC0– 12 hr at 1 and 24 weeks after KT. Moreover, 14 patients (28.0%) reported MPA-related adverse events that were predictable based on MPA AUC0–12 hr (cutoff level, 46.4 μg × hr/mL). Conclusion: The current reduced fixed-dose MMF strategy can help achieve the therapeutic target of MPA exposure in tacrolimus- treated Korean KTRs during the early posttransplant period.

Purpose: Breast cancer is known to be influenced by genetic and environmental factors, and several susceptibility genes have been discovered. Still, the majority of genetic contributors remain unknown. We aimed to analyze the plasma proteome of breast cancer patients in comparison to healthy individuals to identify differences in protein expression profiles and discover novel biomarkers. Methods: This pilot study was conducted using bioresources from Seoul National University Bundang Hospital’s Human Bioresource Center. Serum samples from 10 breast cancer patients and 10 healthy controls were obtained. Liquid chromatography-mass spectrometry analysis was performed to identify differentially expressed proteins. Results: We identified 891 proteins; 805 were expressed in the breast cancer group and 882 in the control group. Gene set enrichment and differential expression analysis identified 30 upregulated and 100 downregulated proteins in breast cancer. Among these, 10 proteins were selected as potential biomarkers. Three proteins were upregulated in breast cancer patients, including cluster of differentiation 44, eukaryotic translation initiation factor 2-α kinase 3, and fibronectin 1. Seven proteins downregulated in breast cancer patients were also selected: glyceraldehyde-3-phosphate dehydrogenase, α-enolase, heat shock protein member 8, integrin‑linked kinase, tissue inhibitor of metalloproteinases-1, vasodilatorstimulated phosphoprotein, and 14-3-3 protein gamma. All proteins had been previously reported to be related to tumor development and progression. Conclusion The findings suggest that plasma proteome profiling can reveal potential diagnostic biomarkers for breast cancer and may contribute to early detection and personalized treatment strategies. A further validation study with a larger sample cohort of breast cancer patients is planned.

Purpose: The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs. Materials and Methods: A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset. Results: Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%. Conclusion This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.