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.

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.

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.

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.

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.

BACKGROUND: Data on drug-coated balloon (DCB) treatment in elderly patients are limited. This study was to evaluate the efficacy of DCB treatment in percutaneous coronary intervention (PCI) among elderly patients. METHODS: A retrospective analysis included 232 patients aged 75 years or older with coronary artery disease who underwent successful PCI using either DCB alone or in combination with drug-eluting stent (DES) based on pre-dilation results (DCB-based PCI). These patients were compared with 1818 elderly patients who underwent second-generation DES implantation (DES-only PCI). The endpoint was major adverse cardiovascular events (MACE) at 2-year follow-up. RESULTS: In the DCB-based PCI, 61.2% of patients received DCB-only treatment. Compared to DES-only PCI, the DCB-based PCI group had fewer stents (0.5 ± 0.7 and 1.7 ± 0.8, P < 0.001), shorter stent lengths (13.3 ± 20.9 mm and 37.4 ± 23.0 mm, P < 0.001), and lower usage of small stents with a diameter of 2.5 mm or less (15.6% and 28.7%, P = 0.010). The DCB-based PCI group exhibited lower rate of MACE (5.5% and 13.1%, P = 0.003), target vessel revascularization (1.1% and 5.6%, P = 0.017) and major bleeding (0.7% and 5.1%, P = 0.009) at 2-year follow-up. The reduced risk in 2-year MACE was consistently observed across various matching procedures, with the most significant reduction noted in target vessel revascularization and major bleeding. CONCLUSION The DCB-based PCI reduced stent burden, particularly in the usage of small diameter stents, and was associated with lower risks of MACE, target vessel revascularization, and major bleeding compared to DES-only PCI in elderly patients.

Therapeutic efficacy of mesenchymal stem cells (MSCs) is determined by biodistribution and engraftment in vivo.Compared to intravenous infusion, biodistribution of locally transplanted MSCs are partially understood. Here, we performed a pharmacokinetics (PK) study of MSCs after local transplantation. We grafted human MSCs into the brains of immune-compromised nude mice. Then we extracted genomic DNA from brains, lungs, and livers after transplantation over a month. Using quantitative polymerase chain reaction with human Alu-specific primers, we analyzed biodistribution of the transplanted cells. To evaluate the role of residual immune response in the brain, MSCs expressing a cytosine deaminase (MSCs/CD) were used to ablate resident immune cells at the injection site. The majority of the Alu signals mostly remained at the injection site and decreased over a week, finally becoming undetectable after one month. Negligible signals were transiently detected in the lung and liver during the first week. Suppression of Iba1-positive microglia in the vicinity of the injection site using MSCs/CD prolonged the presence of the Alu signals.After local transplantation in xenograft animal models, human MSCs remain predominantly near the injection site for limited time without disseminating to other organs. Transplantation of human MSCs can locally elicit an immune response in immune compromised animals, and suppressing resident immune cells can prolong the presence of transplanted cells. Our study provides valuable insights into the in vivo fate of locally transplanted stem cells and a local delivery is effective to achieve desired dosages for neurological diseases.

Background: and Purpose This study aimed to evaluate whether extracellular-vesicle-incorporated microRNAs (miRNAs) are potential biomarkers for cancer-related stroke. Methods: This cohort study compared patients with active cancer who had embolic stroke of unknown sources (cancer-stroke group) with patients with only cancer, patients with only stroke, and healthy individuals (control groups). The expression profiles of miRNAs encapsulated in plasma exosomes and microvesicles were evaluated using microarray and validated using quantitative real-time polymerase chain reaction. The XENO-QTM miRNA assay technology was used to determine the absolute copy numbers of individual miRNAs in an external validation cohort. Results: This study recruited 220 patients, of which 45 had cancer-stroke, 76 were healthy controls, 39 were cancer controls, and 60 were stroke controls. Three miRNAs (miR-205-5p, miR-645, and miR-646) were specifically incorporated into microvesicles in patients with cancer-related stroke, cancer controls, and stroke controls. The area under the receiver operating characteristic curves of these three miRNAs were 0.7692–0.8510 for the differentiation of patients with cancer-stroke from cancer-controls and 0.8077–0.8846 for the differentiation of patients with cancer-stroke from stroke controls. The levels of several miRNAs were elevated in the plasma exosomes of patients with cancer, but were lower than those in plasma microvesicles. An in vivo study showed that systemic injection of miR-205-5p promoted the development of arterial thrombosis and elevation of D-dimer levels. Conclusion Stroke due to cancer-related coagulopathy was associated with deregulated expression of miRNAs, particularly microvesicle-incorporated miR-205-5p, miR-645, and miR-646. Further prospective studies of extracellular-vesicle-incorporated miRNAs are required to confirm the diagnostic role of miRNAs in patients with stroke and to screen the roles of miRNAs in patients with cancer.

Objectives: This study aimed to assess hand grip strength and femoral neck bone mineral density levels among Korean fishery workers and investigate their association. Methods: Hand grip strength and femoral neck bone mineral density were measured in a survey and health examination conducted in 2021 among fishery workers in a southern region of South Korea. Covariates including gender, age, education level, income level, smoking behavior, drinking behavior, family history of hip fractures, use of calcium and vitamin D supplements, hypertension, diabetes, regular exercise, and body mass index were investigated. Multiple regression analysis was employed to assess the association between hand grip strength and femoral neck bone mineral density. Results: Among 147 fishery workers, 8.16% exhibited low hand grip strength levels indicative of possible sarcopenia, and a significant association was found between low hand grip strength and decreased femoral neck bone mineral density (β = -89.14, 95% CI = -160.50, -17.78). Additionally, factors such as women gender, advanced age, family history of hip fractures, and a body mass index below 25 kg/m 2 were associated with decreased femoral neck bone mineral density. In the subgroup analysis by gender, a correlation between low hand grip strength and decreased femoral neck bone mineral density was observed only in men. Conclusions Further research is needed to explore various determinants and intervention strategies to prevent musculoskeletal disorders among fishery workers, ultimately enhancing their quality of life and well-being.

Objective: This study aimed to provide basic data for preventing and managing sarcopenia by identifying the relationship between sarcopenia, malnutrition, and psychosocial factors among the elderly in the community. Methods: The study included 1,019 subjects aged 60 and over. “Possible sarcopenia” was defined by low handgrip strength with or without reduced physical performance. Nutrition was evaluated according to the mini nutrition assessment (MNA), and the psychosocial factors examined were self-efficacy, social isolation, fear of falling, and social capital (trust and participation). A logistic regression analysis was also performed on the relationship between risk of malnutrition, psychosocial factors, and sarcopenia. Results: MNA was significantly associated with social participation (OR = 1.747, p <0.001), fear of falling (OR = 2.905, p <0.001), and self-efficacy (high/low, OR = 0.654, p = 0.011). In model 3, which included both MNA and psychosocial factors, sarcopenia was significantly associated with MNA (OR = 2.529, p <0.001) and fear of falling (OR = 1.544, p = 0.045). Compared with the low self-efficacy group, the high group (OR = 0.589, p = 0.009) was significant. The factors related to possible sarcopenia include risk of malnutrition, fear of falls, and low self-efficacy. Conclusion It will be necessary to improve self-efficacy so that individuals feel they can do activities of daily living themselves and to reduce their fear of falling through muscle strength and balance exercises.Finally, it is also necessary to increase regular participation in community social activities.