Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objectives:To describe the use of antihypertensive, antidiabetic and lipid-lowering drugs, and evaluate the effects on blood pressure, blood glucose and blood lipids controls required by Chinese Guideline on the Primary Prevention of Cardiovascular Diseases (the guideline) in a community-based cohort of individuals at high risk for cardiovascular disease. To analyze the association of the uses of antihypertensive, antidiabetic and lipid-lowering drugs, and the comprehensive control of blood pressure, blood glucose and blood lipids with cardiovascular disease. Methods:From the CHinese Electronic health Records Research in Yinzhou (CHERRY), those who were at high risk for cardiovascular disease and aged 40-75 years as of January 1, 2013 in in Yinzhou District of Ningbo, Zhejiang Province were selected as study subjects. The information about their antihypertensive, antidiabetic, and lipid-lowering drug uses between 2013 and 2015 was collected, and blood pressure, blood glucose, and blood lipid measurements were conducted during the follow-up. The study constructed two kinds of comprehensive scores: the comprehensive medication score based on the guideline requirement for the treatment of hypertension, diabetes and hyperlipidemia, dividing the study participants into the compliancy group and non-compliancy group; and the comprehensive control score based on the guideline requirement for blood pressure, blood glucose, and blood lipids control, dividing the study participants into better control group, moderate control group, and poor control group. Cox proportional hazards regression model was used to analyze the association of the comprehensive medication score and comprehensive control score with cardiovascular disease. The incidence data of cardiovascular disease were collected from January 1, 2015 (baseline time) to August 31, 2020 (follow up end time).Results:A total of 79 734 participants at high risk for cardiovascular disease were included in the study, in whom 68.4%, 27.4%, and 4.2% had 1, 2, or 3 cardiometabolic conditions (hypertension, diabetes, or hyperlipidemia), respectively. In the participants with hypertension, diabetes, and hyperlipidemia from 2013 to 2015, the proportions of those who had two years of medication compliancy records were 66.0%, 67.4%, and 13.9%, respectively. In the hypertension patients, 59.2% had better blood pressure control, in the diabetes patients, 28.7% had better blood glucose control, and in the patients with hyperlipidemia, 27.4% had better blood lipid control. After a median follow-up of 5.66 years, 4 088 cardiovascular disease cases or deaths occurred. After multivariate adjustment, compared with the non-compliancy group, the compliancy group had lower risk for cardiovascular disease ( HR=0.91, 95% CI: 0.85-0.96). Compared with the better control group, the poor control group had an increased risk for cardiovascular disease ( HR=1.67, 95% CI: 1.53-1.81). In the moderate control group, the risk increased significantly in the diabetes patients ( HR=1.29, 95% CI: 1.07-1.56), while no additional risk for cardiovascular disease was observed in non-diabetes patients ( HR=1.06, 95% CI: 0.97-1.16). Conclusions:Compliancy to the medication required by the guideline is associated with lower risk for cardiovascular disease. However, it is still necessary to improve the medication compliancy in people at high risk in primary prevention, especially in the patients with hyperlipidemia, due to their low taking rate of lipid-lowering drugs. Additionally, as the requirement of the guideline becomes more stringent, the management of disease has met more challenges. Notably, diabetes patients who have not met the guideline requirement are at high risk for cardiovascular disease, to whom the disease management should be strengthened.

With the widespread application of ionizing radiation in many industries and the construction of nuclear power plants, the potentials for nuclear accidents is also increasing. In the event of a nuclear accident, rapid classification of a large population is generally involved, so accurate estimation of the radiation dose to the exposed population is the primary task of nuclear emergency response. Based on this need, World Health Organization and International Atomic Energy Agency have each established a worldwide network of biological dosimetry laboratories. In addition, regional networks of biological dosimetry laboratories have been established in the European Union, North America, Latin America and Asia. Based on the long-term organization of national training and assessment of biological dose estimation technology, China will also establish its own network of biological dosimetry laboratories in the future to cope with the emergency disposal needs of potential nuclear accidents. In this paper, the international biodosimetry network and related work will be reviewed, and the idea of establishing biodosimetry laboratory network in China will be elaborated.

Objective:To investigate the changes in the expression levels of long non-coding ribonucleic acids (lncRNAs) in human lymphocytes induced by low-dose ionizing radiation (LDIR) and the potential of lncRNAs as radiation biomarkers.Methods:Human immortalized lymphocytes (AHH-1) were irradiated with 0, 0.05, and 0.1 Gy of γ-rays at 24 h to extract RNAs for whole transcriptome sequencing. The sequencing was performed based on the 0, 0.05, and 0.1 Gy groups. The differentially expressed lncRNAs induced by LDIR were identified. The molecular functions, biological processes, and signaling pathway enrichment of differentially expressed genes were analyzed through the Gene Ontology (GO) analysis. Candidate lncRNAs were preliminarily validated using the qRT-PCR method. AHH-1 cells were irradiated with 0, 0.02, 0.05, 0.075, 0.1, and 0.2 Gy to extract the total RNAs at 4, 24, 48, 72, 96, and 120 h. The dose-response relationship of candidate lncRNAs was detected and analyzed. Peripheral blood sampled from eight healthy persons was irradiated with 0, 0.02, 0.05, 0.075, 0.1, and 0.2 Gy in vitro, followed by culturing for 24 h and 48 h to further verify the changes in the expression levels of radiation-responsive lncRNAs at the cellular level. Results:A total of 44 lncRNAs that were significantly up- or down-regulated after 0.05 and 0.1 Gy irradiation were initially identified through transcriptome sequencing. Among them, lncRNAs with over two-fold differential expression included SNHG1, SNHG15, NEAT1, and PRC1-AS1. At the cellular level, compared to 0 Gy, the relative expression level of PRC1-AS1 after 4 h to 48 h of γ-ray irradiation, was significantly elevated at 0.05, 0.075, and 0.1 Gy( t= -3.11 to 1.23, P < 0.05). In contrast, the relative expression level of NEAT1 was significantly up-regulated in a dose range of 0.02 to 0.1 Gy ( t=-2.47 to 2.10, P < 0.05). At the level of human peripheral blood, the relative expression levels of PRC1-AS1 and NEAT1 were significantly increased at 24 h after 0 to 0.2 Gy irradiation ( t=-3.79 to -1.96, P < 0.05). Conclusion:The PRC1-AS1 and NEAT1 with significant changes in expression levels serve as potential LDIR biomarkers.

Objective To explore the mechanism by which Liqi Huoxue Dripping Pill(LQHXDP)inhibits cardiomyocyte apoptosis in rats with myocardial ischemia-reperfusion injury(MIRI).Methods Male Sprague-Dawley(n=96)rats were randomly assigned to a normal,sham-operated,model,LQHXDP,adenovirus negative control(Ad-shNC),adenovirus-mediated HIF-1α knockdown(Ad-shHIF-1α),LQHXDP+Ad-shNC,or LQHXDP+Ad-shHIF-1α group using a random number table.LQHXDP was administered daily via oral gavage at 175.0 mg/(kg·d)for 10 consecutive days.On day 7,recombinant adenovirus was injected into the left ventricular wall of rats in the corresponding groups at multiple points.On day 10,the MIRI model was established by ligating the left anterior descending coronary artery.The sham-operated group underwent thoracotomy and suture placement without coronary ligation.Samples were collected after reperfusion was completed.Serum creatine kinase isoenzymes(CK-MB),cardiac troponin I(cTnI),and heart-type fatty acid binding protein(H-FABP)levels were measured using enzyme-linked immunosorbent assay.2,3,5-Triphenyltetrazolium chloride staining was used to measure the volume ratio of myocardial infarction.HE staining was performed to observe the morphology of myocardial tissue.Terminal transferase uridyl nick end labeling assay was conducted to analyze the apoptosis rate of cardiomyocytes,and Western blotting was used to detect the expression of key proteins in the apoptosis(B-cell lymphoma-2[Bcl-2],Bcl-2 associated X protein[Bax],and cleaved cysteinyl aspartate specific proteinase 3[Cleaved-Caspase-3]and HIF-1α/Bcl-2-adenovirus E1B 19 kDa interacting protein 3(BNIP3)signaling pathway(HIF-1α,heme oxygenase-1[HO-1],and BNIP3).Results LQHXDP pretreatment significantly reduced serum CK-MB,cTnI,and H-FABP levels,as well as the myocardial infarction volume ratio in rats with MIRI.LQHXDP also improved myocardial tissue morphology,decreased cardiomyocyte apoptosis,upregulated Bcl-2 protein expression,and downregulated Bax,Cleaved-Caspase-3,HIF-1α,HO-1,and BNIP3 protein expressions(P<0.05).However,adenovirus-mediated shRNA HIF-1α impaired the effects of LQHXDP pretreatment in attenuating myocardial injury and inhibiting apoptosis in MIRI rats(P<0.05).Conclusion LQHXDP reduces cardiomyocyte apoptosis and protects rat myocardium from MIRI by regulating the HIF-1α/BNIP3 signaling pathway.

Objective:To investigate the association between the triglyceride-glucose(TyG)index and the incidence and mortality of cardiovascular disease(CVD)in a large population-based cohort.Methods:Participants aged 40-79 years without a history of CVD at baseline were drawn from the CHi-nese Electronic health Records Research in Yinzhou(CHERRY)study between January 1,2010,and May 31,2020.The TyG index was calculated using baseline triglyceride and fasting blood glucose.Cox proportional hazards models were used to assess the association between the TyG index and the composite outcome of CVD(incidence and mortality),adjusting for age,gender,education,region,smoking sta-tus,body mass index,systolic blood pressure,and total cholesterol.Hazard ratios(HR)and 95％confi-dence intervals(CI)were calculated.Nonlinear associations between the TyG index and CVD were fur-ther evaluated using restricted cubic splines,and subgroup analyses by gender and age were conducted to explore potential differences.Results:A total of 226 406 individuals were included,with a mean age of(55.0±9.7)years at baseline,46.8％of whom were men,and a median TyG index of 8.68.Over a median follow-up of 7.99 years,9 815(4.34％)participants experienced CVD incidence or mortality.After adjusting for age,gender,education,region,smoking status,body mass index,systolic blood pressure and total cholesterol,the risk of CVD increased with higher TyG index levels(P＜0.001).The risk in the highest TyG quartile(TyG＞9.10)was 42％higher than in the lowest quartile(TyG ≤8.32)(HR=1.42,95％CI:1.34-1.51).Individuals under 60 years had a higher HR for CVD compared with those aged 60 years and above(HR:1.71 vs.1.27,P＜0.05).Restricted cubic spline analysis revealed a reverse L-shaped association between the TyG index and CVD risk in the overall population(P＜0.001 for nonlinear trend),with risk increasing after the TyG index exceeded 8.67.However,the threshold varied by gender,with a lower threshold in women(8.51)than in men(8.67).Conclusion:A significant nonlinear relationship was revealed between the TyG index and CVD risk,with a threshold effect.The risk of CVD increased once the TyG index surpassed a certain threshold,with a lower threshold in women than in men.These findings suggest that cardiovascular risk prediction and interven-tions based on the TyG index should be gender-stratified,and early intervention for individuals under 60 years old might have important public health implications.

Objective To evaluate the effectiveness and feasibility of a remote medication treatment management model for elderly patients with chronic disease at home based on mobile technology.Methods A convenient and elderly-friendly mo-bile application(hereinafter referred to as Yaoshiyi APP)was developed,and a remote medication treatment management team consisting of clinical pharmacists from tertiary hospitals,community pharmacists,and community physicians was formed.Patients from communities were selected for practical research,led by pharmacists.Based on the Yaoshiyi APP,patients were subjected to 6 months of medication treatment management practice,and the effectiveness and feasibility of the practice were evaluated.Re-sults The Yaoshiyi APP can be integrated with a variety of medical-grade wearable devices to realize the functions of automati-cally uploading monitoring data,abnormal value reminding,medication reminding,medication consultation,and medication sci-ence popularization.A total of 302 elderly patients with chronic disease at home completed the study.The results showed that phar-macists have identified and intervened in 695 cases of medication-related problems.According to the classification of medication-related problems,the top three were 247 cases(35.5％)of additional treatment,97 cases(14.0％)of unnecessary drug treat-ment,and 93 cases(13.4％)of medication compliance problems.The patient's medication adherence score(Morisky medication adherence scale-8,MMAS-8)increased from(5.85±1.57)at enrollment to(6.74±1.23)6 months after enrollment(P＜0.01).After 6 months of enrollment,the patient's satisfaction with the pharmacist's work reached a score of(4.99±0.08)out of 5.The average reduction in drug costs for patients caused by pharmacists intervening in irrational medication is(20.9±18.0)％.At the end of follow-up,93.4％of patients were proficient in using the Yaoshiyi APP.Conclusion The remote medication treatment management model for elderly patients with chronic disease at home based on mobile technology constructed in this study can ef-fectively improve patient compliance with disease monitoring and medication,ensure rational drug use,reduce medical resource waste,and receive high patient acceptance.

Objectives:To describe the use of antihypertensive, antidiabetic and lipid-lowering drugs, and evaluate the effects on blood pressure, blood glucose and blood lipids controls required by Chinese Guideline on the Primary Prevention of Cardiovascular Diseases (the guideline) in a community-based cohort of individuals at high risk for cardiovascular disease. To analyze the association of the uses of antihypertensive, antidiabetic and lipid-lowering drugs, and the comprehensive control of blood pressure, blood glucose and blood lipids with cardiovascular disease. Methods:From the CHinese Electronic health Records Research in Yinzhou (CHERRY), those who were at high risk for cardiovascular disease and aged 40-75 years as of January 1, 2013 in in Yinzhou District of Ningbo, Zhejiang Province were selected as study subjects. The information about their antihypertensive, antidiabetic, and lipid-lowering drug uses between 2013 and 2015 was collected, and blood pressure, blood glucose, and blood lipid measurements were conducted during the follow-up. The study constructed two kinds of comprehensive scores: the comprehensive medication score based on the guideline requirement for the treatment of hypertension, diabetes and hyperlipidemia, dividing the study participants into the compliancy group and non-compliancy group; and the comprehensive control score based on the guideline requirement for blood pressure, blood glucose, and blood lipids control, dividing the study participants into better control group, moderate control group, and poor control group. Cox proportional hazards regression model was used to analyze the association of the comprehensive medication score and comprehensive control score with cardiovascular disease. The incidence data of cardiovascular disease were collected from January 1, 2015 (baseline time) to August 31, 2020 (follow up end time).Results:A total of 79 734 participants at high risk for cardiovascular disease were included in the study, in whom 68.4%, 27.4%, and 4.2% had 1, 2, or 3 cardiometabolic conditions (hypertension, diabetes, or hyperlipidemia), respectively. In the participants with hypertension, diabetes, and hyperlipidemia from 2013 to 2015, the proportions of those who had two years of medication compliancy records were 66.0%, 67.4%, and 13.9%, respectively. In the hypertension patients, 59.2% had better blood pressure control, in the diabetes patients, 28.7% had better blood glucose control, and in the patients with hyperlipidemia, 27.4% had better blood lipid control. After a median follow-up of 5.66 years, 4 088 cardiovascular disease cases or deaths occurred. After multivariate adjustment, compared with the non-compliancy group, the compliancy group had lower risk for cardiovascular disease ( HR=0.91, 95% CI: 0.85-0.96). Compared with the better control group, the poor control group had an increased risk for cardiovascular disease ( HR=1.67, 95% CI: 1.53-1.81). In the moderate control group, the risk increased significantly in the diabetes patients ( HR=1.29, 95% CI: 1.07-1.56), while no additional risk for cardiovascular disease was observed in non-diabetes patients ( HR=1.06, 95% CI: 0.97-1.16). Conclusions:Compliancy to the medication required by the guideline is associated with lower risk for cardiovascular disease. However, it is still necessary to improve the medication compliancy in people at high risk in primary prevention, especially in the patients with hyperlipidemia, due to their low taking rate of lipid-lowering drugs. Additionally, as the requirement of the guideline becomes more stringent, the management of disease has met more challenges. Notably, diabetes patients who have not met the guideline requirement are at high risk for cardiovascular disease, to whom the disease management should be strengthened.