Objective:Heart failure(HF),a worldwide health condition,is the result of many cardiovascular diseases.The traditional Chinese medicine(TCM)Xiaoyu Jiangzhi capsule(XYC)has long been in use in China to treat hyperlipidemia and inhibit platelet aggregation.This study explores the effects of XYC on heart failure(HF)and its detailed mechanisms.Methods:Isoproterenol(ISO,30 mg/kg)was injected intraperitoneally for 7 days to copy a HF model of 10-12 weeks old,20-30 g male mice.We then compared the CON(control)group,ISO(HF model)group,MET(metoprolol)group,and XYC group.Cardiac systolic function and left wall thickness were evaluated by echocardiograph.Using western blot analysis,we detected the proteins of calmodulin dependent protein kinase Ⅱ(CaMKII)and sarco/endoplasmic reticulum Ca2+-ATPase(Serca).Further-more,tsA201 cells were cultured and the human CaV1.2 calcium channel current(hCaV1.2)were detected by patch clamp experiments.Results:XYC reduced HF,inhibiting the protein expression of CaMKII,but Serca did not change signifi-cantly.Moreover,XYC inhibited the peak amplitude of the hCaV1.2 current,depolarizing shifted the activation curve 27.6 mV,and shifted the inactivation curve toward a positive potential 17.6 mV.The fraction recovered from inaction was reduced in XYC group compared with that in CON group.Conclusion:XYC could inhibit ISO-induced HF by reducing the Ca2+/CaMKII signaling pathway in mice.

Objective To construct a radiomics model for predicting hematoma enlargement in early hypertensive intracerebral hemorrhage and explore its predictive value.Methods A retrospective collection of 212 patients with hypertensive intracerebral hemorrhage within 6 h of onset,admitted to our hospital from February 2010 to August 2018,was performed.CT examination was performed within half an hour of admission.CT re-examination was performed 24 h after admission to determine whether there was hematoma enlargement.The regions of interest were delineated on the first CT,and 431 image indicators were extracted from the Matlab software.The LASSO regression model was used to screen out the most predictive imaging features,and the selected features and support vector machine classifier (SVM) were used to build the prediction model.Receiver operating characteristic (ROC) curve was used to evaluate the predicted effect of the model.Results After 24 h of admission,the incidence of hematoma enlargement was 18.9％ (40/212).Eighteen imaging ensemble features (including 4 first-order statistics features:standard deviation,kurtosis,uniformity,and variance;one shape-and size-based feature:surface to volume ratio;7 textual features:long run low grey level emphasis,inertia,correlation-angle 90,short run emphasis,correlation-all direction,long run emphasis,and inverse difference moment;6 wavelet features:autocorrelation-3,informational measure of correlation2-3,long run high gray level emphasis-4,short run high gray level emphasis-4,short run low gray level emphasis-7,and sum variance-3) were combined with SVM to establish a prediction model by LASSO regression model.The area under ROC curve was 0.928,enjoying sensitivity and specificity of 92.5％ and 83.5％,respectively.Conclusion The constructed radiomics model is helpful in predicting the expansion of hypertensive cerebral hemorrhage.