This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

BACKGROUND: The association between uric acid-albumin ratio (UAR) with different diseases has been evaluated before. However, the association between UAR with spontaneous reperfusion (SR) in patients with ST-segment elevation myocardial infarction (STEMI) has not been explored. METHODS: STEMI patients admitted to our department and underwent primary coronary angiography between 1^st November 2018 and 31^st December 2020 were retrospectively enrolled. The patients were divided into the SR group and the non-SR group according to the index coronary angiography results. The association between UAR and SR was evaluated by uni-variable and multi-variable logistic analysis. Receiver operating characteristic curve analysis was used to determine the optimum cut-off level of UAR in predicting SR. RESULTS: Three hundred and fifty-seven patients were finally enrolled in our study, 55 patients were divided into the SR group and 302 patients were divided into the non-SR group. In uni-variable analysis, patients with SR were older (P = 0.032), with higher red blood cell distribution width (P < 0.001) and red blood cell distribution width-to-platelet ratio (P < 0.001), higher level of C-reactive protein (P = 0.046), higher level of uric acid (P < 0.001) compared with patients without SR. Patients with SR had a lower level of platelets (P = 0.008), lower level of on-admission B-type natriuretic peptide (P < 0.001). As for the level of UAR, STEMI patients with SR had significantly higher levels of UAR compared with STEMI patients without SR [11.1 (8.9-13.4) vs. 8.3 (6.6-10.0), P < 0.001]. Further multi-variable logistic analysis reveals that UAR was the independent risk factor of SR in different models after adjusting different variables. Receiver operating characteristic analysis showed that UAR had good predictive value in SR (AUC = 0.75, 95% CI: 0.702-0.794, P < 0.01). CONCLUSIONS Our study shows that UAR is an independent risk factor for predicting SR in STEMI patients.

Objective To investigate the dosimetric effects of different calculation grid size(CGS)in helical tomotherapy(HT)planning system on stereotactic body radiation therapy(SBRT)for non-small cell lung cancer(NSCLC).Methods Nine NSCLC patients receiving radiation therapy for the first time at some hospital from March 2019 to December 2022 were selected as the subjects.SBRT planning was carried out through the HT system with three different CGS plans(Fine,Normal,and Coarse)and the same pitch,modulation factor(MF)and optimization conditions,and the target area indexes of the three CGS plans were compared including conformity index(CI),homogeneity index(HI),dosimetric parameters of the organ at risk(OAR),point dose verification pass rate,treatment time,number of monitor units and Sinograms.SPSS 22.0 was used for statistical analysis.Results For target area HI,there weres significant differences between CGS Fine plan and Coarse plan and between CGS Normal plan and Coarse plan(P＜0.05),while no statistical differences were found between CGS Fine plan and Normal plan(P＞0.05).For target area CI,there were significant differences between CGS Fine plan and Coarse plan(P＜0.05),while no statistical differences were found between CGS Fine plan and Normal plan and between CGS Normal plan and Coarse plan(P＞0.05).For OAR dosimetric parameters,CGS Fine plan and Coarse plan had significant differences in heart Dmax and Dmean,esophageal Dmax and Dmean,V5,V20,V30 and Dmean of the whole lung and affected lung,V5 and Dmax of the affected lung and heart V10 and V30(P＜0.05),CGS Normal plan and Coarse plan had obvious differences in esophageal Dmax(P＜0.05),and the remained dosimetric parameters were not statistically significant(P＞0.05).Fine,Normal and Coarse plans had the point dose verifica-tion pass rates being 0.96％,1.50％and 1.77％,respectively.In terms of treatment time and number of monitor units,there were significant differences between Fine plan and Coarse plan(P＜0.05)while no statistical differences were found between Fine and Normal plans and between Normal and Coarse plans(P＞0.05).Sinograms analyses showed Fine plan had evenly distributed segment color gradient,Coarse plan had areas of very dark and very light color gradients and Normal plan was somewhere in between.Conclusion Low CGS has to be used as much as possible to obtain accurate dose distribution during SBRT planning for NSCLC patients,which contributes to the execution of the radiation therapy plan and the prevention of ad-verse effects.[Chinese Medical Equipment Journal,2024,45(2):52-57]

Objective To investigate the radiotherapy dose impacts of different jaw widths on stereotactic body radiotherapy(SBRT)for hepatocellular carcinoma(HCC)with the hilical tomotherapy(HT)planning system.Methods Totally 16 HCC patients who received radiotherapy at some hospital from March 2021 to August 2023 were selected,and the planning was carried out with the same pitch,modulation factors and optimization conditions and the jaw widths being 1.0,2.5 and 5.0 cm.The dosimetric differences due to the jaw widths in planned targets and organs at risk(OAR)were compared,and the planned treatment time,monitor unit,gantry rotations and gantry period were evaluated.SPSS 22.0 was used for statistical analysis.Results Better dosimetric parameters and lower doses to OARs could be got with lower jaw widths.The widened jaw widths resulted in reduced planned treatment time,decreased monitor units and gantry rotations,shortened gantry period while enhanced treatment efficiency.Conclusion A 2.5 cm jaw width for HT planning contributes to improving treatment efficiency during HCC SBRT under the premise of ensured target dose distribution and satisfactory dose to OAR for clinical require-ments.[Chinese Medical Equipment Journal,2024,45(7):51-55]

OBJECTIVE: To explore the association between the use of metformin and the risk of ischemic stroke in patients with type 2 diabetes. METHODS: A prospective cohort study was designed from the Fangshan family cohort in Beijing. According to metformin use at baseline, 2 625 patients with type 2 diabetes in Fangshan, Beijing were divided into metformin group or non-metformin group and the incidence of ischemic stroke between the different groups during follow-up was estimated and compared by Cox proportional hazard regression model. The participants with metformin were first compared with all the parti-cipants who did not use metformin, and then were further compared with those who did not use hypoglycemic agents and those who used other hypoglycemic agents. RESULTS: The patients with type 2 diabetes were with an average age of (59.5±8.7) years, and 41.9% of them were male. The median follow-up time was 4.5 years. A total of 84 patients developed ischemic stroke during follow-up, with a crude incidence of 6.4 (95%CI: 5.0-7.7) per 1 000 person-years. Among all the participants, 1 149 (43.8%) took metformin, 1 476 (56.2%) were metformin non-users, including 593 (22.6%) used other hypoglycemic agents, and 883 (33.6%) did not use any hypoglycemic agents. Compared with metformin non-users, the Hazard ratio (HR) for ischemic stroke in metformin users was 0.58 (95%CI: 0.36-0.93; P = 0.024). Compared with other hypoglycemic agents, HR was 0.48 (95%CI: 0.28-0.84; P < 0.01); Compared with the group without hypoglycemic agents, HR was 0.65 (95%CI: 0.37-1.13; P=0.13). The association between metformin and ischemic stroke was statistically significant in the patients ≥ 60 years old compared with all the metformin non-users and those who used other hypoglycemic agents (HR: 0.48, 95%CI: 0.25-0.92; P < 0.05). Metformin use was associated with a lower incidence of ischemic stroke in the patients with good glycemic control (0.32, 95%CI: 0.13-0.77; P < 0.05). In the patients with poor glycemic control, and the association was not statistically significant (HR: 0.97, 95%CI: 0.53-1.79; P>0.05). There was an interaction between glycemic control and metformin use on incidence of ischemic stroke (P_interaction < 0.05). The results of the sensitivity analysis were consistent with the results in the main analysis. CONCLUSION Among patients with type 2 diabetic in rural areas of northern China, metformin use was associated with lower incidence of ischemic stroke, especially in patients older than 60 years. There was an interaction between glycemic control and metformin use in the incidence of ischemic stroke.
Humans ; Male ; Middle Aged ; Aged ; Female ; Metformin/adverse effects* ; Diabetes Mellitus, Type 2/drug therapy* ; Cohort Studies ; Ischemic Stroke/complications* ; Prospective Studies ; Hypoglycemic Agents/adverse effects* ; Stroke/prevention & control* ; Retrospective Studies

Objective: To forecast mortality, age-standardized mortality, and probability of premature mortality from diabetes, and to simulate the impact of controlling risk factors by 2030 in China. Methods: We simulated the burden of disease from diabetes in six scenarios according to the development goals of risk factors control by the WHO and Chinese government. Based on the theory of comparative risk assessment and the estimates of the burden of disease for China from the Global Burden of Disease Study 2015, we used the proportional change model to project the number of deaths, age-standardized mortality, and probability of premature mortality from diabetes under different scenarios of risk factors control in 2030. Results: If the trends in exposures to risk factors from 1990 to 2015 continued. Mortality, age-standardized mortality, and probability of premature mortality from diabetes would increase to 32.57/100 000, 17.32/100 000, and 0.84% by 2030, respectively. During that time, mortality, age-standardized mortality and probability of premature mortality for males would all be higher than for females. If the goals of controlling risk factors were all achieved, the number of deaths from diabetes in 2030 would decrease by 62.10% compared to the predicted numbers based on the historical trends in exposure to risk factors, and the probability of premature mortality would drop to 0.29%. If only the exposure to a single risk factor were achieved by 2030, high fasting plasma glucose control would have the greatest impact on diabetes, resulting in a 56.00% reduction in deaths compared to the predicted numbers based on the historical trends, followed by high BMI (4.92%), smoking (0.65%), and low physical activity (0.53%). Conclusions: Risk factors control plays an important role in reducing the number of deaths, age-standardized mortality rate, and probability of premature mortality from diabetes. We suggest taking comprehensive measures to control relevant risk factors for certain populations and regions, to achieve the goal of reducing the burden of disease from diabetes as expected.
Male ; Female ; Humans ; Risk Factors ; Diabetes Mellitus/epidemiology* ; Mortality, Premature ; Smoking ; Cost of Illness ; China/epidemiology* ; Global Burden of Disease

Objective: Predictive models were used to evaluate the impact of common risk factors on the number of cardio-cerebrovascular deaths and the probability of premature death. Methods: Using the data for China estimated by the Global Burden of Disease study 2015 (GBD 2015), we calculated the population attribution fraction (PAF) of risk factors. The proportional change model was used to estimate the number of unattributable deaths by 2030, and to predict the number of deaths, mortality, standardized mortality and probability of premature death by 2030. Results: According to the natural change trend of risk factors from 1990 to 2015, the number of deaths and mortality would reach 6.12 million and 428.53/100 000 by 2030, with an increase of 59.92% and 52.87%. By 2030, the probability of premature death from cardio-cerebrovascular diseases among Chinese aged 30-70 years old would continue to decline, from 11.43% to 11.28% for men, and from 5.79% to 4.43% for women. If the goals of all included risk factors were reached by 2030, 2 289 200 cardio-cerebrovascular deaths would be avoided. If only the exposure to a single risk factor was achieved by 2030, blood pressure, total cholesterol, and fine particulate matter exposure were the three most important factors affecting cardio-cerebrovascular deaths, which would reduce 1 332 800, 609 100 and 306 800 deaths, respectively. Among the involved risk factors, the control of blood pressure would mostly decrease the number of deaths due to ischemic heart disease and hemorrhagic stroke, about 677 300 and 391 100 deaths, accordingly. Conclusion: The control of risk factors is of great significance in reducing deaths and probability of premature death due to cardio-cerebrovascular diseases. If the control targets of all risk factors could be achieved by 2030, the burden of cardio-cerebrovascular diseases would be reduced greatly.
Adult ; Aged ; Blood Pressure ; Cerebrovascular Disorders/epidemiology* ; China/epidemiology* ; Female ; Humans ; Male ; Middle Aged ; Mortality, Premature ; Risk Factors

Objective: To predict the number of deaths, standardized mortality and probability of premature mortality caused by malignant cancer in the context of risk factor control at different levels in China in 2030, and assess the possibility of achieving the target of reducing the probability of premature mortality of malignant cancer. Methods: According to the risk factor control standard for malignant cancer used both at home and abroad, the results of China from Global Burden of Disease Study 2015 were used to calculate the population attributable fraction of the risk factors. Based on the comparative risk assessment theory, the deaths of malignant cancer were classified as attributable deaths and un-attributable deaths. Proportional change model was used to predict risk factor exposure and un-attributable deaths of malignant cancer in the future, then the number of deaths, standardized mortality rate and probability of premature mortality of malignant cancer in 2030 was estimated. Data analyses were performed by using software R 3.6.1. Results: If the risk factor exposure level during 1990-2015 remains, the number of deaths, standardized mortality rate, and probability of premature mortality of malignant cancer would increase to 3.62 million, 153.96/100 000 and 8.92% by 2030, respectively. If the risk factor exposure control level meets the requirement, the probability of premature mortality from cancer in people aged 30-70 years would drop to 7.57% by 2030. Conclusions: The control of risk factor exposure will play an important role in reducing deaths, standardized mortality rate and probability of premature mortality of malignant cancer. But more efforts are needed to achieve the goals of Health China Action.
Adult ; Aged ; China/epidemiology* ; Cost of Illness ; Humans ; Middle Aged ; Mortality, Premature ; Neoplasms/epidemiology* ; Risk Factors

Objective: To forecast the burden of chronic obstructive pulmonary disease (COPD) in China by 2030 and evaluate the effectiveness of controlling risk factors based on the predictive model. Methods: Based on the relationship between the death of COPD and exposure to risk factors and the theory of comparative risk assessment, we used the estimates of the Global Burden of Disease Study 2015 (GBD2015) for China, targets for controlling risk factors, and proportion change model to project the number of deaths, standardized mortality rate, and probability of premature mortality from chronic respiratory diseases by 2030 in different scenarios and to evaluate the impact of controlling the included risk factors to the disease burden of COPD in 2030. Results: If the trends in exposure to risk factors from 1990 to 2015 continued, the number of deaths and the mortality for COPD would be 1.06 million and 73.85 per 100 000 population in China by 2030, respectively, with an increase of 15.81% and 10.69% compared to those in 2015. Compared to 2015, the age-standardized mortality rate would decrease by 38.88%, and the premature mortality would reduce by 52.73% by 2030. If the smoking rate and fine particulate matter (PM_2.5) concentration separately achieve their control targets by 2030, there would be 0.34 and 0.27 million deaths that could be avoided compared to the predicted numbers based on the natural trends in exposure to risk factors and the probability of premature death would reduce to 0.59% and 0.52%, respectively. If the control targets of all included risk factors were achieved by 2030, a total of 0.53 million deaths would be averted, and the probability of premature death would decrease to 0.44%. Conclusions: If the exposures to risk factors continued as showed from 1990 to 2015, the number of deaths and mortality for COPD would increase by 2030 compared to 2015, and the standardized mortality and the probability of premature death would decrease significantly, which would achieve the targets of preventing and controlling COPD. If the exposure to the included risk factors all achieved the targets by 2030, the burden of COPD would be reduced, suggesting that the control of tobacco use and air pollution should be enhanced to prevent and control COPD.
Air Pollutants/analysis* ; Air Pollution/prevention & control* ; China/epidemiology* ; Cost of Illness ; Environmental Exposure ; Humans ; Particulate Matter/analysis* ; Pulmonary Disease, Chronic Obstructive/prevention & control* ; Risk Factors

OBJECTIVE: To explore the relationship between sleep habits (sleep duration, sleep efficiency, sleep onset timing) and ischemic stroke, and whether there is an interaction between sleep habits and ischemic stroke susceptibility gene loci. METHODS: A questionnaire survey, physical examination, blood biochemical testing and genotyping were conducted among rural residents in Beijing, and the gene loci of ischemic stroke suggested by previous genome-wide association studies (GWAS) were screened. Multivariable generalized linear model was used to analyze the correlation between sleep habits, sleep-gene interaction and ischemic stroke. RESULTS: A total of 4 648 subjects with an average age of (58.5±8.7) years were enrolled, including 1 316 patients with ischemic stroke. Compared with non-stroke patients, stroke patients with sleep duration ≥9 hours, sleep efficiency < 80%, and sleep onset timing earlier than 22:00 accounted for a higher proportion (P < 0.05). There was no significant association between sleep duration and risk of ischemic stroke (OR=1.04, 95%CI: 0.99-1.10, P=0.085). Sleep efficiency was inversely associated with the risk of ischemic stroke (OR=0.18, 95%CI: 0.06-0.53, P=0.002). The risk of ischemic stroke in the subjects with sleep efficiency < 80% was 1.47-fold (95%CI: 1.03-2.10, P=0.033) of that in the subjects with sleep efficiency ≥80%. Falling asleep earlier than 22:00 was associated with 1.26 times greater risk of stroke than falling asleep between 22:00 and 22:59 (95%CI: 1.04-1.52, P=0.017). Multifactorial adjustment model showed that rs579459 on ABO gene had an interaction with sleep time (P for interaction =0.040). When there were two T alleles for rs579459 on the ABO gene, those who fell asleep before 22:00 had 1.56 times (95%CI: 1.20-2.04, P=0.001) the risk of stroke compared with those who fell asleep between 22:00 and 22:59, and there was no significant difference when the number of pathogenic alleles was 0 or 1. In the model adjusted only for gender, age and family structure, sleep duration and the number of T allele rs2634074 on PITX2 gene had an interaction with ischemic stroke (P for interaction=0.033). CONCLUSION Decreased sleep efficiency is associated with increased risk of ischemic stroke, and falling asleep earlier than 22:00 is associated with higher risk of ischemic stroke. Sleep onset timing interacted with rs579459 in ABO gene and the risk of ischemic stroke. Sleep duration and PITX2 rs2634074 may have a potential interaction with ischemic stroke risk.
Aged ; Genome-Wide Association Study ; Humans ; Ischemic Stroke ; Middle Aged ; Sleep/genetics* ; Stroke/genetics* ; Surveys and Questionnaires