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.

This study was carried out to investigate an enhancing effect of black ginseng extract (BGE) on exercise capacity in an endurance exercising animal model. Fifty Sprague-Dawley rats were assigned to 5 experimental groups including non-training control, training control, and 3 treated groups (BGE at doses of 75, 150 and 300 mg/kg). The animals were treated with BGE for 6 weeks and their exercise ability in the maximal running distance test was determined using a treadmill every week. The blood lactic acid (LA) level and the activity of citrate synthase (CS) in the muscle were also measured after the exercise. The levels of glucose and glucose-6-phosphate (G-6-P) in the liver and muscle were determined using commercial assay kits. BGE treatments at the doses of 150 and 300 mg/kg significantly increased the exercise capacity compared with the non-training control or training control groups (P<0.05). The level of blood LA was decreased but the activity of CS was increased by the treatment of BGE at the dose of 300 mg/kg compared with the training control group. The level of G-6-P in the liver was elevated by the treatment of BGE at the dose of 300 mg/kg, compared to the training group. As compared with non-training control group, the treatments of BGE increased the levels of glucose and G-6-P in the liver and soleus muscle of rats. These results indicate that BGE have a potential for promoting exercise capacity by increasing CS activity in the muscle and decreasing LA in the serum of rats. These results also suggested that BGE can be used as a candidate supplement of health food products for promoting endurance exercise capacity in human athletes.
Animals ; Athletes ; Citrate (si)-Synthase ; Exercise ; Glucose ; Glucose-6-Phosphate ; Food, Organic ; Humans ; Lactic Acid ; Liver ; Models, Animal ; Muscle, Skeletal ; Muscles ; Panax ; Rats ; Rats, Sprague-Dawley ; Running

This study was carried out to investigate an enhancing effect of black ginseng extract (BGE) on exercise capacity in an endurance exercising animal model. Fifty Sprague-Dawley rats were assigned to 5 experimental groups including non-training control, training control, and 3 treated groups (BGE at doses of 75, 150 and 300 mg/kg). The animals were treated with BGE for 6 weeks and their exercise ability in the maximal running distance test was determined using a treadmill every week. The blood lactic acid (LA) level and the activity of citrate synthase (CS) in the muscle were also measured after the exercise. The levels of glucose and glucose-6-phosphate (G-6-P) in the liver and muscle were determined using commercial assay kits. BGE treatments at the doses of 150 and 300 mg/kg significantly increased the exercise capacity compared with the non-training control or training control groups (P<0.05). The level of blood LA was decreased but the activity of CS was increased by the treatment of BGE at the dose of 300 mg/kg compared with the training control group. The level of G-6-P in the liver was elevated by the treatment of BGE at the dose of 300 mg/kg, compared to the training group. As compared with non-training control group, the treatments of BGE increased the levels of glucose and G-6-P in the liver and soleus muscle of rats. These results indicate that BGE have a potential for promoting exercise capacity by increasing CS activity in the muscle and decreasing LA in the serum of rats. These results also suggested that BGE can be used as a candidate supplement of health food products for promoting endurance exercise capacity in human athletes.
Animals ; Athletes ; Citrate (si)-Synthase ; Exercise ; Glucose ; Glucose-6-Phosphate ; Food, Organic ; Humans ; Lactic Acid ; Liver ; Models, Animal ; Muscle, Skeletal ; Muscles ; Panax ; Rats ; Rats, Sprague-Dawley ; Running