Personalized Analysis by Validation of Monte Carlo for Application of Pathways in Cardioembolic Stroke.

BACKGROUND Cardioembolic stroke (CES), which causes 20% cause of all ischemic strokes, is associated with high mortality. Previous studies suggest that pathways play a critical role in the identification and pathogenesis of diseases. We aimed to develop an integrated approach that is able to construct individual networks of pathway cross-talk to quantify differences between patients with CES and controls. MATERIAL AND METHODS One biological data set E-GEOD-58294 was used, including 23 normal controls and 59 CES samples. We used individualized pathway aberrance score (iPAS) to assess pathway statistics of 589 Ingenuity Pathways Analysis (IPA) pathways. Random Forest (RF) classification was implemented to calculate the AUC of every network. These procedures were tested by Monte Carlo Cross-Validation for 50 bootstraps. RESULTS A total of 28 networks with AUC >0.9 were found between CES and controls. Among them, 3 networks with AUC=1.0 had the best performance for classification in 50 bootstraps. The 3 pathway networks were able to significantly identify CES versus controls, which showed as biomarkers in the regulation and development of CES. CONCLUSIONS This novel approach could identify 3 networks able to accurately classify CES and normal samples in individuals. This integrated application needs to be validated in other diseases.

[Effects of metoprolol on electrophysiology of ischemic and anoxic myocardium in diabetic rats].

OBJECTIVE: To investigate the effects of metoprolol on electrophysiology of ischemic and anoxic myocardium in diabetic rats. METHODS: Forty Sprague-Dawley (SD) rats were divided into 4 groups: diabetes group; diabetes and ablation of left sympathetic nerve group; diabetes and metoprolol group and sham group. The diabetes model was induced by intraperitoneal injection of streptozotocin (STZ, 60 mg/kg). The ventricular diastolic effective threshold (DET), effective refractive period (ERP), and Ventricular fibrillation threshold (VFT) were measured. The serum concentration of nerve growth factor (NGF) was measured. RESULTS: Metoprolol increased DET of ischemic and anoxic myocardium in diabetic rats. The ablation of the left sympathetic nerve increased VFT of diabetic rats. VFT in metoprolo group was significantly increased compared to diabetes group after ischemia. The concentrations of NGF in diabetic group and metoprolol group were higher than those in sham group. There were no difference in NGF levels between ablation of left sympathetic nerve group and sham group. CONCLUSION: The remodeling of sympathetic nerve affects the electrophysiology of ischemic myocardium of diabetic rats. Metoprolol can increase the VFT and decrease the excitation threshold of the ischemic myocardium in diabetic rats.

Prognostic value of von Willebrand factor in patients with atrial fibrillation: A meta-analysis.

BACKGROUND: Studies on the prognostic role of von Willebrand factor (vWF) in patients with atrial fibrillation (AF) are conflicting. This meta-analysis aimed to evaluate the association of elevated circulating vWF level with adverse outcomes in patients with AF. METHODS: PubMed and Embase were used to search literature through August 2017. Prospective observational studies that evaluated the association of elevated vWF level with major adverse cardiac events (MACEs) and all-cause mortality in patients with AF were deemed eligible. The MACEs included death, stroke/transient ischemic attack, heart failure, myocardial infarction, and systemic/peripheral embolism. RESULTS: A total of 6 studies were included this meta-analysis. Patients with AF with the highest vWF level were independently associated with greater risk of MACEs (risk ratio [RR] 2.20; 95% confidence intervals [CI] 1.61-3.01) and all-cause mortality (RR 1.63; 95% CI 1.39-1.91). Subgroup analysis showed that the prognostic role of higher vWF level was consistently observed in each defined subgroups. CONCLUSION: Patients with AF with elevated vWF level are independently associated with a higher risk of MACEs and all-cause mortality. However, more well-designed prospective studies are needed to confirm these findings.

Characterizing Dysregulated Networks in Individual Patients with Ischemic Stroke Based on Monte Carlo Cross-Validation.

The purpose of this study was to introduce a new method to elucidating the molecular mechanisms in ischemic stroke. Genes from microarray data were performed enrichment to biological pathways. Dysregulated pathways and dysregulated pathway pairs were identified and constructed into networks. After Random Forest classification was performed, area under the curve (AUC) value of main network was calculated. After 50 bootstraps of Monte Carlo Cross-Validation, six pairs of pathways were found for >40 times. The best main network with AUC value = 0.735 was identified, including 14 pairs of pathways. Compared with the traditional method (gene set enrichment analysis), although a small part of pathways were shared, most of the pathways were closely related with ischemic stroke. The best network may give new insights into the underlying molecular mechanisms in ischemic stroke. It may play pivotal roles in the progression of ischemic stroke and particular attention should be focused on them for further research.