Purpose: 11C-Methionine PET/CT is a promising method for detecting parathyroid lesions in patients with primary hyperparathyroidism (PHPT). We aimed to determine the diagnostic ability and correlation of digital 11C-Methionine PET/CT for parathyroid lesions in patients with PHPT, particularly in cases where standard imaging methods yielded inconclusive results. Methods: This retrospective analysis was conducted on patients diagnosed with PHPT who underwent digital 11C-Methionine PET/CT imaging because of ambiguous results on standard imaging work-up ( 99m Tc-MIBI parathyroid scan and/or neck ultrasonography). Quantitative 11C-Methionine PET/CT parameters, including maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), parathyroid methionine volume (PMV), and whole methionine uptake(WMU: PMV multiplied by SUVmean) were calculated with various thresholds, and their correlations with biochemical andpathologic parameters were investigated. Results: This study included 22 consecutive patients (10 men and 12 women) with a median age of 64.0 years. The lesion detection rate and sensitivity of digital 11C-Methionine PET/CT were 81.8% (18/22) and 100.0% (18/18), respectively.Quantitative analysis revealed that serum PTH (r = 0.490, P = 0.039) and serum calcium (r = 0.583, P = 0.011) were signifi-cantly correlated with PMV50%. Conclusion Digital 11C-Methionine PET/CT offers good performance in the detection of parathyroid lesions in PHPT patients with inconclusive standard imaging work-up. The volume parameter of PMV50% significantly correlated biochemi-cal parameters and can serve as a complementary diagnostic tool.

BACKGROUND/OBJECTIVES: Isoflavones are estrogen-like compounds found in plants and their health effects remain equivocal. We investigated dietary isoflavone intake and its associated factors in Korean breast cancer survivors, with a comparison to cancer-free women. SUBJECTS/METHODS: The usual dietary intake of breast cancer survivors (n = 981, mean age 52 yrs) in 9 hospitals between 2012 and 2019 was assessed using 3-day food records or food frequency questionnaires (FFQs). They were age-matched to 2,943 cancer-free women who completed FFQs as part of a nationwide study conducted between 2012 and 2016. We used the flavonoid database of common Korean foods and the Phenol-Explorer database to estimate isoflavone intake. The contribution of each food or food group to the total isoflavone intake was calculated. The adjusted least-squares means of dietary isoflavone intake according to lifestyle and clinical factors were calculated using generalized linear models. RESULTS: Breast cancer survivors had a higher mean dietary isoflavone intake (23.59 mg/day) than cancer-free women (17.81 mg/day). Major food sources, including tofu, soybeans, and doenjang, contributed to over 70% of the isoflavone intake in both groups. When we estimated dietary isoflavone intake according to lifestyle characteristics, isoflavone intake increased with higher scores of adherence to the American Cancer Society dietary guidelines but decreased with increasing body mass index in both groups. Among cancer-free women, dietary isoflavone intake was higher among those who had never smoked and among dietary supplement users. Among breast cancer survivors, dietary isoflavone intakes did not vary with clinical characteristics, including time since surgery and estrogen receptor status. CONCLUSION Breast cancer survivors were more likely to consume isoflavones than agematched cancer-free women. Dietary isoflavone intake was associated with healthy lifestyle characteristics in women both with and without breast cancer. Further research is needed to understand the role of the higher isoflavone intake among breast cancer survivors compared to cancer-free women on their prognosis.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

To ensure high-quality bioresources and standardize biobanks, there is an urgent need to develop and disseminate educational training programs in accordance with ISO 20387, which was developed in 2018. The standardization of biobank education programs is also required to train biobank experts. The subdivision of categories and levels of education is necessary for jobs such as operations manager (bank president), quality manager, practitioner, and administrator. Essential training includes programs tailored for beginner, intermediate, and advanced practitioners, along with customized training for operations managers. We reviewed and studied ways to develop an appropriate range of education and training opportunities for standard biobanking education and the training of experts based on KS J ISO 20387. We propose more systematic and professional biobanking training programs in accordance with ISO 20387, in addition to the certification programs of the National Biobank and the Korean Laboratory Accreditation System. We suggest various training programs appropriate to a student’s affiliation or work, such as university biobanking specialized education, short-term job training at unit biobanks, biobank research institute symposiums by the Korean Society of Pathologists, and education programs for biobankers and researchers. Through these various education programs, we expect that Korean biobanks will satisfy global standards, meet the needs of users and researchers, and contribute to the advancement of science.

Oxidative stress due to hyperglycemia damages the functions of retinal pigment epithelial (RPE) cells and is a major risk factor for diabetic retinopathy (DR). Paeoniflorin is a monoterpenoid glycoside found in the roots of Paeonia lactiflora Pall and has been reported to have a variety of health benefits. However, the mechanisms underlying its therapeutic effects on high glucose (HG)-induced oxidative damage in RPE cells are not fully understood. In this study, we investigated the protective effect of paeoniflorin against HG-induced oxidative damage in cultured human RPE ARPE-19 cells, an in vitro model of hyperglycemia. Pretreatment with paeoniflorin markedly reduced HG-induced cytotoxicity and DNA damage. Paeoniflorin inhibited HG-induced apoptosis by suppressing activation of the caspase cascade, and this suppression was associated with the blockade of cytochrome c release to cytoplasm by maintaining mitochondrial membrane stability. In addition, paeoniflorin suppressed the HG-induced production of reactive oxygen species (ROS), increased the phosphorylation of nuclear factor erythroid 2-related factor 2 (Nrf2), a key redox regulator, and the expression of its downstream factor heme oxygenase-1 (HO-1). On the other hand, zinc protoporphyrin (ZnPP), an inhibitor of HO-1, abolished the protective effect of paeoniflorin against ROS production in HG-treated cells. Furthermore, ZnPP reversed the protective effects of paeoniflorin against HG-induced cellular damage and induced mitochondrial damage, DNA injury, and apoptosis in paeoniflorin-treated cells. These results suggest that paeoniflorin protects RPE cells from HG-mediated oxidative stress-induced cytotoxicity by activating Nrf2/HO-1 signaling and highlight the potential therapeutic use of paeoniflorin to improve the symptoms of DR.

Purpose: 11C-Methionine PET/CT is a promising method for detecting parathyroid lesions in patients with primary hyperparathyroidism (PHPT). We aimed to determine the diagnostic ability and correlation of digital 11C-Methionine PET/CT for parathyroid lesions in patients with PHPT, particularly in cases where standard imaging methods yielded inconclusive results. Methods: This retrospective analysis was conducted on patients diagnosed with PHPT who underwent digital 11C-Methionine PET/CT imaging because of ambiguous results on standard imaging work-up ( 99m Tc-MIBI parathyroid scan and/or neck ultrasonography). Quantitative 11C-Methionine PET/CT parameters, including maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), parathyroid methionine volume (PMV), and whole methionine uptake(WMU: PMV multiplied by SUVmean) were calculated with various thresholds, and their correlations with biochemical andpathologic parameters were investigated. Results: This study included 22 consecutive patients (10 men and 12 women) with a median age of 64.0 years. The lesion detection rate and sensitivity of digital 11C-Methionine PET/CT were 81.8% (18/22) and 100.0% (18/18), respectively.Quantitative analysis revealed that serum PTH (r = 0.490, P = 0.039) and serum calcium (r = 0.583, P = 0.011) were signifi-cantly correlated with PMV50%. Conclusion Digital 11C-Methionine PET/CT offers good performance in the detection of parathyroid lesions in PHPT patients with inconclusive standard imaging work-up. The volume parameter of PMV50% significantly correlated biochemi-cal parameters and can serve as a complementary diagnostic tool.

BACKGROUND/OBJECTIVES: Isoflavones are estrogen-like compounds found in plants and their health effects remain equivocal. We investigated dietary isoflavone intake and its associated factors in Korean breast cancer survivors, with a comparison to cancer-free women. SUBJECTS/METHODS: The usual dietary intake of breast cancer survivors (n = 981, mean age 52 yrs) in 9 hospitals between 2012 and 2019 was assessed using 3-day food records or food frequency questionnaires (FFQs). They were age-matched to 2,943 cancer-free women who completed FFQs as part of a nationwide study conducted between 2012 and 2016. We used the flavonoid database of common Korean foods and the Phenol-Explorer database to estimate isoflavone intake. The contribution of each food or food group to the total isoflavone intake was calculated. The adjusted least-squares means of dietary isoflavone intake according to lifestyle and clinical factors were calculated using generalized linear models. RESULTS: Breast cancer survivors had a higher mean dietary isoflavone intake (23.59 mg/day) than cancer-free women (17.81 mg/day). Major food sources, including tofu, soybeans, and doenjang, contributed to over 70% of the isoflavone intake in both groups. When we estimated dietary isoflavone intake according to lifestyle characteristics, isoflavone intake increased with higher scores of adherence to the American Cancer Society dietary guidelines but decreased with increasing body mass index in both groups. Among cancer-free women, dietary isoflavone intake was higher among those who had never smoked and among dietary supplement users. Among breast cancer survivors, dietary isoflavone intakes did not vary with clinical characteristics, including time since surgery and estrogen receptor status. CONCLUSION Breast cancer survivors were more likely to consume isoflavones than agematched cancer-free women. Dietary isoflavone intake was associated with healthy lifestyle characteristics in women both with and without breast cancer. Further research is needed to understand the role of the higher isoflavone intake among breast cancer survivors compared to cancer-free women on their prognosis.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.