Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

OBJECTIVES: We estimated the population prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including unreported infections, through a Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) in 258 communities throughout Korea. METHODS: In August 2022, a survey was conducted among 10,000 household members aged 5 years and older, in households selected through two stage probability random sampling. During face-to-face household interviews, participants self-reported their health status, COVID-19 diagnosis and vaccination history, and general characteristics. Subsequently, participants visited a community health center or medical clinic for blood sampling. Blood samples were analyzed for the presence of antibodies to spike proteins (anti-S) and antibodies to nucleocapsid proteins (anti-N) SARS-CoV-2 proteins using an electrochemiluminescence immunoassay. To estimate the population prevalence, the PROC SURVEYMEANS statistical procedure was employed, with weighting to reflect demographic data from July 2022. RESULTS: In total, 9,945 individuals from 5,041 households were surveyed across 258 communities, representing all basic local governments in Korea. The overall population-adjusted prevalence rates of anti-S and anti-N were 97.6% and 57.1%, respectively. Since the Korea Disease Control and Prevention Agency has reported a cumulative incidence of confirmed cases of 37.8% through July 31, 2022, the proportion of unreported infections among all COVID-19 infection was suggested to be 33.9%. CONCLUSIONS The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19, confirming that most individuals possess antibodies to SARS-CoV-2 and that a significant number of unreported cases existed. Furthermore, this study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.

Background/Aims: The incidence and prognosis of gastric cancer (GC) shows sex difference.This study aimed to evaluate the effect of body mass index (BMI) on GC survival depending on sex. Methods: The sex, age, location, histology, TNM stages, BMI, and survival were analyzed in GC patients from May 2003 to February 2020 at the Seoul National University Bundang Hospital. Results: Among 14,688 patients, there were twice as many males (66.6%) as females (33.4%).However, under age 40 years, females (8.6%) were more prevalent than males (3.1%). Cardia GC in males showed a U-shaped distribution for underweight (9.6%), normal (6.4%), overweight (6.1%), obesity (5.6%), and severe obesity (9.3%) but not in females (p=0.003). Females showed decreased proportion of diffuse-type GC regarding BMI (underweight [59.9%], normal [56.8%], overweight [49.5%], obesity [44.8%], and severe obesity [41.7%]), but males did not (p<0.001). Both sexes had the worst prognosis in the underweight group (p<0.001), and the higher BMI, the better prognosis in males, but not females. Sex differences in prognosis according to BMI tended to be more prominent in males than in females in subgroup analysis of TNM stages I, II, and III and the operative treatment group. Conclusions GC-specific survival was affected by BMI in a sex-dependent manner. These differences may be related to genetic, and environmental, hormonal factors; body composition; and muscle mass (Trial registration number: NCT04973631).

The natural flavonoid macakurzin C (1) exhibited adiponectin biosynthesis-inducing activity during adipogenesis in human bone marrow mesenchymal stem cells and its molecular mechanism was directly associated with a pan-peroxisome proliferator-activated receptor (PPAR) modulator affecting all three PPAR subtypes α, γ, and δ. In this study, increases in adiponectin biosynthesisinducing activity by macakurzin C derivatives (2–7) were studied. The most potent adiponectin biosynthesis-inducing compound 6, macakurzin C 3,5-dimethylether, was elucidated as a dual PPARα/γ modulator. Compound 6 may exhibit the most potent activity because of the antagonistic relationship between PPARδ and PPARγ. Docking studies revealed that the O-methylation of macakurzin C to generate compound 6 significantly disrupted PPARδ binding. Compound 6 has therapeutic potential in hypoadiponectinemia-related metabolic diseases.

Background: In this study, we aimed to investigate the interaction effects of individual socioeconomic status and regional deprivation on the onset of diabetes complications and diabetes-related hospitalization among type 2 diabetes patients. Methods: Korean National Health Insurance Service National Sample Cohort data from 2002 to 2013 were used. A total of 50,954 patients newly diagnosed with type 2 diabetes from 2004 to 2012 and aged 30 years or above were included. We classified patients into six groups according to individual income level and neighborhood deprivation: ‘high in advantaged,’ ‘high in disadvantaged,’ ‘middle in advantaged,’ ‘middle in disadvantaged,’ ‘low in advantaged,’ and ‘low in disadvantaged.’ We calculated hazard ratios (HR) of onset of diabetes complication and diabetes-related hospitalization using the Cox proportional hazard model, with the reference group as diabetes patients with high income in advantaged regions. Results: In terms of the interaction effects of individual income level and regional socioeconomic level, even with the same low individual income level, the group with a high regional socioeconomic level (low in advantaged) showed low HRs for the onset of diabetes complication (HR, 1.04; 95% confidence interval [CI], 1.00–1.08) compared to the ‘low in disadvantaged’ group (HR, 1.10;95% CI, 1.05–1.16). In addition, the ‘high in advantaged’ group showed slightly higher HRs for the onset of diabetes complication (HR, 1.06; 95% CI, 1.00–1.11) compared to the ‘low in advantaged’ and it appeared to be associated with slight mitigation of the risk of diabetes complication. For the low-income level, the patients in disadvantaged regions showed the highest HRs for diabetes-related hospitalization (HR, 1.29; 95% CI, 1.19–1.41) compared to the other groups. Conclusion Although we need to perform further investigations to reveal the mechanisms that led to our results, interaction effects individual socioeconomic status and regional deprivation might be associated with on onset of diabetes complications and diabetes-related hospitalization among type 2 diabetes patients.

Background: In this study, we aimed to investigate the interaction effects of individual socioeconomic status and regional deprivation on the onset of diabetes complications and diabetes-related hospitalization among type 2 diabetes patients. Methods: Korean National Health Insurance Service National Sample Cohort data from 2002 to 2013 were used. A total of 50,954 patients newly diagnosed with type 2 diabetes from 2004 to 2012 and aged 30 years or above were included. We classified patients into six groups according to individual income level and neighborhood deprivation: ‘high in advantaged,’ ‘high in disadvantaged,’ ‘middle in advantaged,’ ‘middle in disadvantaged,’ ‘low in advantaged,’ and ‘low in disadvantaged.’ We calculated hazard ratios (HR) of onset of diabetes complication and diabetes-related hospitalization using the Cox proportional hazard model, with the reference group as diabetes patients with high income in advantaged regions. Results: In terms of the interaction effects of individual income level and regional socioeconomic level, even with the same low individual income level, the group with a high regional socioeconomic level (low in advantaged) showed low HRs for the onset of diabetes complication (HR, 1.04; 95% confidence interval [CI], 1.00–1.08) compared to the ‘low in disadvantaged’ group (HR, 1.10;95% CI, 1.05–1.16). In addition, the ‘high in advantaged’ group showed slightly higher HRs for the onset of diabetes complication (HR, 1.06; 95% CI, 1.00–1.11) compared to the ‘low in advantaged’ and it appeared to be associated with slight mitigation of the risk of diabetes complication. For the low-income level, the patients in disadvantaged regions showed the highest HRs for diabetes-related hospitalization (HR, 1.29; 95% CI, 1.19–1.41) compared to the other groups. Conclusion Although we need to perform further investigations to reveal the mechanisms that led to our results, interaction effects individual socioeconomic status and regional deprivation might be associated with on onset of diabetes complications and diabetes-related hospitalization among type 2 diabetes patients.

The Pfizer-BioNTech COVID-19 vaccine has shown excellent clinical effectiveness; however, adverse events of the vaccine remain a concern in Korea. We surveyed adverse events in 2498 healthcare workers vaccinated with the Pfizer-BioNTech COVID-19 vaccine at a university hospital. The survey was conducted using a diary card for 7 days following each injection. The questionnaire response rate was 75.1% (1876/2498) for the first dose and 73.8% (1840/2493) for the second dose. Among local reactions, pain was the most commonly reported (84.9% after the first dose and 90.4% after the second dose). After the second dose, two people visited the emergency room due to severe local pain, but no hospitalization or skin necrosis occurred. Among systemic reactions, fatigue was most frequently reported (52.8% after the first dose and 77.0% after the second dose), followed by myalgia (49.0% and 76.1%), headache (28.7% and 59.2%), chills (16.7% and 54.0%), and arthralgia (11.4% and 39.2%). One or more critical adverse events occurred in 0.2% and 0.7% of the vaccinees. Except for urticaria, more adverse events were reported after the second dose than after the first dose. In the future, adverse events should be investigated in older adults, and a future study with a longer observation period should be conducted.