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.

Objective To analyze the predictive value of microRNA-34a-5p(miR-34a-5p)expression in pancreatic cancer tissue on postoperative poor prognosis.Methods The surgically resected pancreatic cancer tissues and normal tissues adjacent to cancer from 123 patients with pancreatic cancer were collected to detect the expression of miR-34a-5p.The expression of miR-34a-5p in pancreatic cancer tissues for patients with different clinicopathological characteristics were compared.The patients were divided into the poor prognosis group and the good prognosis group according to their prognosis,and the clinical data of patients between the two groups was compared.The risk factors of poor prognosis for patients with pancreatic cancer were analyzed by Cox regression model,and the predictive value of miR-34a-5p expression in pancreatic cancer tissues on poor prognosis of patients was analyzed by receiver operating characteristic(ROC)curve.Results The expression of miR-34a-5p in pancreatic cancer tissues was lower than that in normal tissues adjacent to cancer(P<0.05).There were statistically significant differences in the expression of miR-34a-5p in pancreatic cancer tissues of patients with different differentiation degrees,TNM stages,and lymph node metastasis(P<0.05).The proportions of low differentiation,TNM stage for stage Ⅲ,lymph node metastasis and incisal margin of R1,and levels of carbohydrate antigen 199(CA199),neutrophils/lymphocytes ratio(NLR)and platelet/lymphocyte ratio(PLR)for patients in the poor prognosis group were higher than those in the good prognosis group(P<0.05),while miR-34a-5p expression was lower than that in the good prognosis group(P<0.05).Cox regression analysis showed that low differentiation,TNM stage for stage Ⅲ,lymph node metastasis,incisal margin of R1,decreased expression of miR-34a-5p and increased levels of CA199,NLR and PLR were risk factors of poor prognosis for patients with pancreatic cancer(P<0.05).ROC curve analysis showed that the optimal cut-off value of miR-34a-5p expression in pancreatic cancer tissue for predicting poor prognosis of patients was 0.48,the sensitivity was 78.82%,the specificity was 89.47%and the area under the curve was 0.855,with good predictive value.Conclusion The expression of miR-34a-5p in pancreatic cancer tissue is lower than that in normal tissue adjacent to cancer,and its expression is related to the differentiation degree,TNM stage and lymph node metastasis,which is also a risk factor and predictor of poor prognosis for patients with pancreatic cancer.

With the widespread application of nuclear technology,the prevention and treatment of radiation damage have become significant issues in the fields of public health and medicine.This article reviews the adverse drug reactions and their monitoring for radioprotective drugs,and discusses their post-marketing re-evaluation in terms of safety,efficacy,economics,and quality standards.Research indicates that while there is a wide variety of radioprotective drugs,safety concerns are prevalent.Future efforts should focus on strengthening the monitoring and management of adverse drug reactions,optimizing drug safety,and exploring the potential of combined drug applications through multidisciplinary collaboration to enhance anti-radiation efficacy.

Radiation prevention and treatment drugs are a rapidly developing field.Radiation prevention and treatment drugs can be roughly divided into four categories:chemical synthetic drugs,biological products,natural plant extracts and traditional Chinese medicine compounds,which are widely used in medical,scientific research and other fields.This paper reviews the classification of radiation prevention and treatment drugs,which can be roughly divided into four categories:chemical synthetic drugs,biological products,natural plant extracts and traditional Chinese medicine compounds.At the same time,its mechanism of action and clinical application are elaborated in detail,and the risk assessment is carried out from the aspects of effectiveness,safety and drug interaction.Finally,the risk reduction strategies are summarized from the aspects of clinical medication specification and monitoring,continuous drug safety research,improvement of emergency reserve and support capacity and construction of full-cycle regulatory system,so as to provide reference for the rational application and further research of radiation prevention and treatment drugs.

Objective:To investigate the related factors of cognitive impairment in middle-aged and old-aged patients with type 2 diabetes mellitus(T2DM).Methods:A total of 970 patients with T2DM(585 middle-aged group and 385 old-aged group)were selected from residents of a large community in Beijing from September to December 2018.The Mini-Mental State Examination(MMSE)was used to assess the cognitive func-tion.Multivariate logistic regression was used to analyze the related factors.Results:The detection rates of cognitive impairment were 12.0％and 13.5％in middle-aged and old-aged patients with T2DM,respectively.Among mid-dle-aged patients with T2DM,work(OR=0.22,95％CI:0.03-0.77)and education at the junior college or un-dergraduate level and above(OR=0.18,95％CI:0.04-0.55)were protective factors for cognitive impair-ment.Myocardial infarction(OR=4.13,95％CI:1.26-13.63)was a risk factor for cognitive impairment.Among old-aged patients with T2DM,drinking tea 1-2 times a week(OR=0.11,95％CI:0.01-0.58)and education at the junior college or undergraduate level and above(OR=0.19,95％CI:0.05-0.54)were protective factors for cognitive impairment.Stroke(OR=3.64,95％CI:1.55-8.39)and good sleep self-assessment(OR=2.75,95％CI:1.13-7.35)were risk factors for cognitive impairment.Conclusion:Cognitive impairment in middle-aged pa-tients with T2DM is related to work,education level and myocardial infarction,and cognitive impairment in old-aged patients with T2DM is related to lifestyle,education level and stroke.

To analyze the relationship between serum non-HDL-C levels and cardiovascular disease (CVD) mortality in community populations. A retrospective cohort study was conducted using the Yuecheng District Health Information Platform in Shaoxing City, Zhejiang Province. The study cohort included individuals aged 40 years or older with no prior history of CVD who underwent physical examinations at Yuecheng District healthcare institutions between January and December 2019. A total of 39 038 participants were included, including 19 085 males (48.9%) and 19 953 females (51.1%), with a mean age of (73.64±9.10) years. The mean follow-up duration was 52.3 months. During follow-up, 1 227 CVD death events occurred. The results indicated a significant overall association between non-HDL-C levels and the risk of CVD mortality, including coronary heart disease (CHD) and stroke. Cox models indicated that, using the ideal level of non-HDL-C as the reference, the hazard ratios (HRs) for risk of CVD death in the suitable level, borderline elevated level and elevated level groups were 1.24 (95% CI: 1.08-1.42), 1.57 (95% CI: 1.34-1.85) and 2.31 (95% CI: 1.87-2.86), respectively. The corresponding HRs for CHD death were 1.39 (95% CI: 1.10-1.76), 1.69 (95% CI: 1.28-2.12) and 2.53 (95% CI: 1.76-3.64), respectively. Subgroup analysis revealed significant interaction effects between non-HDL-C and sex, smoking, alcohol consumption, and diabetes (all P interaction<0.05). Sensitivity analyses confirmed that results were consistent with the primary findings regarding the association between non-HDL-C and CVD mortality risk. In conclusion, increasing non-HDL-C levels are associated with higher risks of death from cardiovascular diseases, including stroke and CHD. The risk of CVD death associated with elevated non-HDL-C is greater among males, individuals with a history of diabetes, smokers or drinkers. In the future, attention should be paid to the monitoring of non-HDL-C in community health management, and the intensive and personalized management of blood lipids in high-risk population should be strengthened.

Objective The aim of this study was to analyze the incidence and mortality of esophageal cancer and its trend in Lianyungang city from 2008 to 2019.Methods The data of esophageal cancer in all cancer registry areas in Lianyungang city were col-lected and sorted out,and the quality control reached the standards.The incidence,mortality,age-standardized rate of Chinese population(ASRC),age-standardized rate of World population(ASRW),cumulative rate at 0-74 years old,truncation rate of 35-64 years old,and composition ranking were calculated.The Joinpoint4.7.0.0software was used to analyze the average annual percentage change(AAPC)of the age-standardized incidence and mortality of esophageal cancer by the standard population(ASIRC and ASMRC).Results From 2008 to 2019,the incidence of esophageal cancer in Lianyungang city was 25.90/100,000,ASIRC was 17.95/100,000,ASIRW was 17.91/100,000,ranking the third in the incidence spectrum of malignant tumors.The mortality was 20.55/100,000,ASMRC was 13.86/100,000,and ASMRW was 13.71/100,000,ranking the third in the malignant tumor mortality spectrum.The incidence,mortali-ty,ASIRC and ASMRC of esophageal cancer were higher in men than those in women,and higher in rural areas than those in urban are-as.From 2008 to 2019,the change trend of incidence and mortality of esophageal cancer in Lianyungang city was the same,showing a downward trend.The AAPC of the ASIRC was-6.19%(95%CI:-7.08%-5.30%,P<0.001),and the AAPC of the ASMRC was-4.03%(95%CI:-5.81%-2.22%,P<0.001).Among them,the ASIRC and ASMRC of esophageal cancer in urban and rural areas showed a downward trend(P<0.05).Among them,the ASIRC and ASMRC of esophageal cancer in urban women decreased the most,with an average annual decline of-7.99%(95%CI:-10.86%-5.03%,P<0.001)and-9.19%(95%CI:-12.35%-5.93%,P<0.001).Conclusion The incidence and mortality of esophageal cancer in Lianyungang city have shown a downward trend,a rural areas and male populations are the key prevention and control populations for esophageal cancer.

Objective:To investigate the related factors of cognitive impairment in middle-aged and old-aged patients with type 2 diabetes mellitus(T2DM).Methods:A total of 970 patients with T2DM(585 middle-aged group and 385 old-aged group)were selected from residents of a large community in Beijing from September to December 2018.The Mini-Mental State Examination(MMSE)was used to assess the cognitive func-tion.Multivariate logistic regression was used to analyze the related factors.Results:The detection rates of cognitive impairment were 12.0％and 13.5％in middle-aged and old-aged patients with T2DM,respectively.Among mid-dle-aged patients with T2DM,work(OR=0.22,95％CI:0.03-0.77)and education at the junior college or un-dergraduate level and above(OR=0.18,95％CI:0.04-0.55)were protective factors for cognitive impair-ment.Myocardial infarction(OR=4.13,95％CI:1.26-13.63)was a risk factor for cognitive impairment.Among old-aged patients with T2DM,drinking tea 1-2 times a week(OR=0.11,95％CI:0.01-0.58)and education at the junior college or undergraduate level and above(OR=0.19,95％CI:0.05-0.54)were protective factors for cognitive impairment.Stroke(OR=3.64,95％CI:1.55-8.39)and good sleep self-assessment(OR=2.75,95％CI:1.13-7.35)were risk factors for cognitive impairment.Conclusion:Cognitive impairment in middle-aged pa-tients with T2DM is related to work,education level and myocardial infarction,and cognitive impairment in old-aged patients with T2DM is related to lifestyle,education level and stroke.

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.

Objective To predict the radiation impact of discharging wastewater containing uranium within the specified limit generated during the normal operation of a new production line at a nuclear fuel plant on the receiving water body and its downstream, and to provide a reference for the management of radioactive liquid effluent discharge from nuclear facilities. Methods Based on the technical guidelines for environmental impact assessment, literature on radiation environmental impact assessment, and data collected from on-site investigations, appropriate hydrological parameters and prediction models were selected to analyze and predict the variation pattern of radioactive nuclide uranium along the receiving water body and the radiation exposure of nearby residents. Results The maximum increase in uranium concentration in the receiving water body and its downstream caused by the discharge of uranium-containing wastewater was 1.14 μg/L. The maximum predicted concentration was 2.75 μg/L after adding the background data of the water body. The resulting maximum individual annual effective dose for the public was 1.49 × 10⁻⁴ mSv/a. Conclusion The maximum predicted uranium concentration in the receiving water body and its downstream is lower than the uranium concentration limit of 30 μg/L specified in the Standards for Drinking Water Quality (GB 5749-2022). The maximum individual annual effective dose for the public is much lower than the control value of 0.2 mSv/a specified in the Radiation Protection Regulations for Uranium Processing and Fuel and Fuel Manufacturing Facilities (EJ 1056-2018). The radiation impact is acceptable.