Application of thrombolysis in myocardial infarction risk index in the prediction of long-term outcomes for patients with ST-elevation myocardial infarction and multiple vessel disease: A single-center prospective observational cohort study.

The thrombolysis in myocardial infarction (TIMI) risk index has been indicated to be a simple and useful tool for risk stratification of patients with ST-elevation myocardial infarction (STEMI). However, the predictive value of the TIMI risk index regarding the long-term outcome for patients with STEMI with multiple vessel disease has remained to be determined. In the present study, a total of 369 patients diagnosed with STEMI who received emergency percutaneous coronary intervention treatment were analyzed. A five-year follow-up was performed to record the primary endpoint of all-cause mortality, as well as the secondary endpoints of myocardial infarction, stroke, emergent revascularization and admission due to heart failure. A receiver operating characteristic (ROC) curve was used to determine the cut-off value of the TIMI risk index for predicting all-cause death, based on which the patients were divided into a high TIMI group and a low TIMI group. Kaplan-Meier survival curves were used to compare the long-term survival of the two groups and multivariate Cox regression analysis was used to evaluate the predictive value of the risk factors regarding primary and secondary endpoints. The ROC curve indicated that the TIMI risk index was associated with three-year all-cause death with a cut-off value of 30.35 (area under curve, 0.705; P=0.001). The high TIMI group (>30.35) and low TIMI group (<30.35) exhibited a significant difference in all-cause death (P=0.009) but not in any of the secondary endpoints (P=0.527). Multivariate Cox regression analysis demonstrated that a high TIMI risk index was an independent risk factor for all-cause death in patients with STEMI and multiple-vessel disease (hazard ratio=3.709, 95% CI: 1.521-9.046, P=0.004). In conclusion, the TIMI risk index was associated with long-term outcomes for patients with STEMI and multiple-vessel disease and may be of value for risk prediction.

U0126 attenuates ischemia/reperfusion-induced apoptosis and autophagy in myocardium through MEK/ERK/EGR-1 pathway.

Myocardial ischemia is one of the main causes of sudden cardiac death worldwide. Depending on the cell type and stimulus, ERK activity mediates different anti-proliferative events, such as apoptosis, autophagy, and senescence. The aim of this study was to determine the protective effect of 1,4-diamino-2,3-dicyano-1,4-bis[2-aminophenylthio] butadiene (U0126), an ERK kinase inhibitor, on myocardial ischemia/reperfusion (I/R) injury and the mechanisms involved. An I/R model was established in vivo in C57BL/6 mice and in vitro using mouse cardiomyocytes, respectively. To evaluate the protective effects of U0126 on I/R injury, we measured the myocardial infarct area, apoptosis, and autophagy. Our data indicated that pretreatment with U0126 significantly reduced the infarct area caused by I/R. Moreover, U0126 reduced the caspase-3 activity and the number of TUNEL-positive cardiomyocytes, which together indicate decreased apoptosis. Additionally, U0126 remarkable reduced the level of Beclin-1 and LC3 and increased p62 expression, which indicates that U0126 suppressed H/R-induced autophagy. Furthermore, the relationship between U0126 and MEK/ERK pathway activation in H/R-induced cardiomyocytes was also investigated. U0126 ameliorated H/R injury through inhibition of the MEK/ERK pathway and by suppressing in the downstream EGR-1 expression. Together, our research suggests that U0126 may protect against H/R injury by preventing H/R-induced myocardium apoptosis and autophagy via the MEK/ERK/EGR-1 pathway, and may be a potential therapeutic approach for attenuating myocardial I/R injury.

Classification of weld defect based on information fusion technology for radiographic testing system.

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.