Objective:To study the improving effect of curcumin on cardiac function and its influence on myocardial collagen concentration in rats with myocardial infarction (MI).Methods:A total of 60 healthy adult male SD rats were randomly divided into sham operation group (n=10,survived rats n=9)and operation group [n=50,left an-terior descending artery was ligated,they were randomly divided into following four groups,on 28 d the treatment and survived rats in every group were:myocardial infarction (MI)group (n=9),control group (received intraper-itoneal injection of mixed solution,n= 10)and curcumin group (received intraperitoneal injection of curcumin, 100mg·kg-1 · d-1 n= 12)].After four weeks,M-mode echocardiography was used to measure left ventricular shortening fraction (LVFS),left ventricular ejection fraction (LVEF)and heart rate (HR).Masson staining was used to detect the myocardial fibrosis alteration after MI.Immunohistochemistry was used to measure expressions of myocardial collagen type Ⅰ and Ⅲ,and ratio of collagen Ⅰ/Ⅲ.Results:Compared with MI group and control group,after four weeks,there were significant rise in LVFS [(17.23±1.97)%,(19.34±0.83)% vs.(26.70± 1.15)%]and LVEF [(42.08±5.50)%,(41.63± 1.81)% vs.(56.76±2.49)%],significant reductions in HR [(433.16±20.05)beats/min,(433.04±24.17)beats/min vs.(403.96±7.08)beats/min],concentrations of myo-cardial collagen Ⅰ and Ⅲ,and ratio of collagen Ⅰ/Ⅲ [(13.5±0.9),(13.9±1.0)vs.(10.3±1.6)]in curcumin group,P <0.01 all.Masson staining indicated that acute myocardial infarction can cause significant left ventricular interstitial fibrosis.Conclusion:Curcumin could significantly improve cardiac function and inhibit myocardial fibro-sis level in rats with acute myocardial infarction.

Objective: To explore independent risk factors of coronary artery calcification (CAC) and analyze correlation among risk factors of CAC and serum osteopontin (OPN) level. Methods: According to results of 64-slice spiral computed tomography (MSCT) coronary angiography, a total of 65 patients were continuously enrolled and divided into CAC group (n=37) and non-CAC control group (n=28). Enzyme linked immunosorbent assay (ELISA) was used to measure serum level of OPN. Single factor and multiple factor Logistic regression analysis’s were used to analyze risk factors of CAC. Spearman’s straight line analysis was used to analyze correlation between risk factors of CAC and serum OPN. Results: 1、 The age, hypertension, diabetes, poor eating habits，lack of exercise, overweight, etc., which were independent risk factors of CAC （OR=3.47～12.96, P=0.018～0.003）by single factor Logistic regression analysis, were inducted to multiple factor Logistic regression analysis, its result showed that age, overweight, poor sleep quality, poor eating habits were independent risk factors of CAC, OR=35.31～5.17, P＜0.01～0.05; 2、Serum level of OPN in CAC group was significant higher than that of non-CAC control group ［(39.919±11.879) μg /L vs. (24.000±6.000) μg /L，P<0.01］; 3、The Spearman straight line correlation analysis indicated that serum level of OPN was correlated with risk factors of CAC : positively correlated with LDL-C, overweight, age, TC（r=0.487～0.286,P＜0.001～＜0.05）, and positively correlated with poor sleep quality, diabetes, poor eating habits, lack of exercise（r=4.10～2.24， P<0.01～0.05）; negatively correlated with HDL-C（r=-0.250,P＜0.05）. Conclusion: Correlation analysis indicates that age, overweight, poor sleep quality, poor eating habits etc. are independent risk factors of CAC；Serum OPN level is correlated with LDL-C, overweight，age, diabetes, lack of exercise etc., so these indicate that must decrease OPN level and risk factors of CAC to relieve CAC and slow down its development.

Objective To investigate the clinical application value of predicting the severity of acute pancreatitis(AP)based on MRI-T2WI radiomics nomogram.Methods A total of 375 patients with AP were analyzed retrospectively,who were divided into 281 cases in the training group and 94 cases in the validation group according to the ratio of 3∶1.Based on MRI-T2WI image,man-ual segmentation was performed for the pancreatic parenchyma.The radiomics feature were selected by feature extraction and dimen-sionality reduction,the support vector machine(SVM)classifier were used to construct the radiomics model.Logistic regression analysis was used to screen out independent risk factors,and an radiomics nomogram model was constructed in combined with the Radiomics score(Radscore),and the predictive performances of the models were evaluated.Results Receiver operating characteristic(ROC)curve analysis showed that the predictive efficacy of radiomics nomogram model[training group,area under the curve(AUC)=0.893;val-idation group,AUC=0.889]was higher than that of clinical model(training group,AUC=0.799;validation group,AUC=0.809)and radiomics model(training group,AUC=0.814;validation group,AUC=0.823).Conclusion The radiomics nomogram based on MRI-T2WI radiomics features and independent risk factors has high clinical application value for the prediction of AP severity.