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.

Purpose: Postoperative adhesions following thyroid surgery can lead to multiple complications that significantly impact quality of life. The use of an acellular dermal matrix (ADM) adhesion barrier device has been proposed as a potential solution to reduce the risk of such adhesions. This study aimed to evaluate the safety and anti-adhesive effect of an ADM in patients undergoing thyroid surgery. Methods: In this multicenter randomized controlled trial, patients undergoing thyroid surgery were randomly assigned to receive either ADM (n = 42) or no ADM (n = 39) during surgery. The primary outcome was the Swallowing Impairment Score (SIS-6), measured 6 weeks after surgery and compared between groups. Secondary outcomes included intergroup comparisons of the SIS-6, the Voice Handicap Index (VHI)-10, and the Glasgow-Edinburgh Throat Scale (GETS) at baseline, and 2, 6, and 18 weeks after surgery. Results: At week 6, the mean SIS-6 scores were 4.0 ± 4.1 and 3.3 ± 4.2 in the ADM and control groups, respectively, which was not significantly different. Both groups showed similar postoperative improvements in SIS-6, VHI-10, and GETS scores over time, without significant differences between groups at any time point, indicating that the ADM did not reduce the incidence of postoperative adhesions or alter the course of recovery compared to the control group. Conclusion Although application of the ADM is safe for use in patients undergoing thyroid surgery, it did not produce a clinically significant advantage in preventing postoperative adhesions. Future research should focus on identifying specific patient populations or surgical scenarios where the use of the ADM may be beneficial.

Purpose: Postoperative adhesions following thyroid surgery can lead to multiple complications that significantly impact quality of life. The use of an acellular dermal matrix (ADM) adhesion barrier device has been proposed as a potential solution to reduce the risk of such adhesions. This study aimed to evaluate the safety and anti-adhesive effect of an ADM in patients undergoing thyroid surgery. Methods: In this multicenter randomized controlled trial, patients undergoing thyroid surgery were randomly assigned to receive either ADM (n = 42) or no ADM (n = 39) during surgery. The primary outcome was the Swallowing Impairment Score (SIS-6), measured 6 weeks after surgery and compared between groups. Secondary outcomes included intergroup comparisons of the SIS-6, the Voice Handicap Index (VHI)-10, and the Glasgow-Edinburgh Throat Scale (GETS) at baseline, and 2, 6, and 18 weeks after surgery. Results: At week 6, the mean SIS-6 scores were 4.0 ± 4.1 and 3.3 ± 4.2 in the ADM and control groups, respectively, which was not significantly different. Both groups showed similar postoperative improvements in SIS-6, VHI-10, and GETS scores over time, without significant differences between groups at any time point, indicating that the ADM did not reduce the incidence of postoperative adhesions or alter the course of recovery compared to the control group. Conclusion Although application of the ADM is safe for use in patients undergoing thyroid surgery, it did not produce a clinically significant advantage in preventing postoperative adhesions. Future research should focus on identifying specific patient populations or surgical scenarios where the use of the ADM may be beneficial.

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.

Purpose: Postoperative adhesions following thyroid surgery can lead to multiple complications that significantly impact quality of life. The use of an acellular dermal matrix (ADM) adhesion barrier device has been proposed as a potential solution to reduce the risk of such adhesions. This study aimed to evaluate the safety and anti-adhesive effect of an ADM in patients undergoing thyroid surgery. Methods: In this multicenter randomized controlled trial, patients undergoing thyroid surgery were randomly assigned to receive either ADM (n = 42) or no ADM (n = 39) during surgery. The primary outcome was the Swallowing Impairment Score (SIS-6), measured 6 weeks after surgery and compared between groups. Secondary outcomes included intergroup comparisons of the SIS-6, the Voice Handicap Index (VHI)-10, and the Glasgow-Edinburgh Throat Scale (GETS) at baseline, and 2, 6, and 18 weeks after surgery. Results: At week 6, the mean SIS-6 scores were 4.0 ± 4.1 and 3.3 ± 4.2 in the ADM and control groups, respectively, which was not significantly different. Both groups showed similar postoperative improvements in SIS-6, VHI-10, and GETS scores over time, without significant differences between groups at any time point, indicating that the ADM did not reduce the incidence of postoperative adhesions or alter the course of recovery compared to the control group. Conclusion Although application of the ADM is safe for use in patients undergoing thyroid surgery, it did not produce a clinically significant advantage in preventing postoperative adhesions. Future research should focus on identifying specific patient populations or surgical scenarios where the use of the ADM may be beneficial.

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.

Aim To investigate the effects of Radix Angelica Sinensis and Radix Hedysari ultrafiltration(RAS-RH)on oxidative stress and inflammatory injury of human umbilical vein endothelial cells(HUVECs)induced by ionizing radiation.Methods The model of HUVECs damage induced by 6 Gy X-rays was estab-lished.HUVECs were treated with different concentra-tions of RAS-RH(100,200,400 μg·L-1).The proliferative activity of HUVECs was detected by CCK-8 method,the structural changes of mitochondria were observed by transmission electron microscope,the level of ROS was detected by DCFH-DA probe,the change of intracellular mitochondrial membrane potential was detected by JC-1 kit,and the apoptosis and cycle were detected by flow cytometry.The contents of IL-6 and TNF-α in cells were detected by ELISA.The activities of MDA,CAT,SOD and GSH-PX were detected by biochemical kit.The gene expression levels of Nrf2,HO-1,NF-κB,eNOS and IL-6 were detected by qRT-PCR,and the expression levels of Nrf2,HO-1,eNOS,NF-κB,p-NF-κB and IL-6 protein were detected by Western blot.Results Compared with the model group,RAS-RH could increase the activity of HUVECs induced by ionizing radiation,decrease the rate of ap-optosis,decrease the level of intracellular ROS,re-duce the injury of intracellular mitochondria,increase the level of mitochondrial membrane potential,promote the expression of Nrf2,HO-1 and eNOS,and inhibit the expression of NF-κB and IL-6.Conclusions RAS-RH has anti-radiation,antioxidant and anti-in-flammatory effects,which may reduce the oxidative stress and inflammatory damage of HUVECs induced by ionizing radiation by activating the activity of Nrf2/HO-1 signal pathway,thus promoting the activity of cell proliferation.

Objective:To investigate the role of serotonin reuptake transporter(SERT)and P2X3 receptor of dorsal root ganglion(DRG)in regulating visceral hypersensitivity of rats with irritable bowel syndrome(IBS)by electroacupuncture(EA). Methods:Male Sprague-Dawley and SERT-/-rats were subjected to preparing IBS visceral hypersensitivity models with 2,4,6-trinitrobenzene sulfonic acid(TNBS)enema.Three weeks post-modeling,interventions including EA,intrathecal injection,and EA plus intrathecal injection were applied,respectively.Hematoxylin-eosin staining and abdominal withdrawal reflex(AWR)score were used to confirm the successful establishment of the IBS model.AWR score,whole-cell patch clamp technique,and Western blotting assay were used to evaluate the changes in visceral pain sensitivity,electrophysiological properties of DRG neurons,and the expression of DRG P2X3 receptor and SERT in IBS rats. Results:Compared to the model group,the AWR score in the EA group decreased significantly(P<0.05),the resting membrane potential(P<0.05)and the number of action potentials(P<0.05)of DRG neurons reduced,and the baseline intensity increased(P<0.05);additionally,the expression of P2X3 receptor in DRG decreased(P<0.01),and the SERT expression increased(P<0.05).Compared to the P2X3 receptor agonist group,the SERT protein expression in DRG was higher in the EA group.In SERT-/-rats,the P2X3 receptor expression in DRG increased in the EA group compared to the model group(P<0.01). Conclusion:EA modulates the electrophysiological characteristics of intestinal primary sensory neurons by regulating the expression of SERT and P2X3 receptor in DRG of IBS rats.This modulation may contribute to the mechanism by which EA alleviates peripheral sensitization of visceral pain in IBS rats.