Effects of Bivalirudin and Unfractionated Heparin on Liver and Renal Function in Chinese Patients with Coronary Artery Disease Undergoing Coronary Angiography with/without Percutaneous Coronary Intervention.

BACKGROUND AND AIMS: Unfractionated heparin (UFH) and bivalirudin are widely used as anticoagulants in cardiovascular medicine, including for thrombosis prevention during coronary angiography (CAG) and percutaneous coronary intervention (PCI). Little is known of the effects of UFH and bivalirudin on liver and kidney function in patients subjected to these procedures. This study compared the effects of bivalirudin and UFH on liver/renal function in patients with coronary artery disease who underwent CAG, with or without PCI. METHODS: The study comprised 134 consecutive patients (40-89 years-old), who underwent CAG (or CAG and PCI); among them, 66 and 68 patients were subject to, respectively, bivalirudin or UFH. The following indicators of liver/renal function were measured before and after the procedures: plasma alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen, estimated glomerular filtration rate (eGFR), creatinine clearance, and serum creatinine. Patients were further stratified by severity of chronic kidney disease (CKD), based on original eGFR. RESULTS: Relative to baseline, in the bivalirudin group, ALT and AST were higher after CAG (p=0.005, 0.025), while blood urea nitrogen and serum creatinine were lower (p=0.049, <0.001). In the UFH group, ALT, AST, eGFR, and creatinine clearance were lower after CAG (p≤0.001, all). Patients given bivalirudin with moderate or severe CKD, but not those with mild CKD, gained significant improvement in kidney function. CONCLUSIONS: Relative to UFH, bivalirudin may better safeguard the renal function of patients with coronary artery disease who undergo CAG, especially patients with moderate-to-severe renal insufficiency. UFH may cause less liver damage than bivalirudin.

Characteristics of circular RNAs expression of peripheral blood mononuclear cells in humans with coronary artery disease.

Circular RNAs (circRNAs) function as promising biomarkers and therapeutic targets for coronary artery disease due to their high stability, covalently closed structure, and potential gene regulation. We aimed to identify the expression profile and role of circular RNAs (circRNAs) in coronary artery disease (CAD). We performed RNA sequence analysis of circRNAs in peripheral blood mononuclear cells of five patients with CAD and five controls. Bioinformatics analyses were adopted to explore biological functions of differentially expressed circRNAs. The miRanda and TargetScan tools were used to predict the microRNA (miRNA)-targeting interactions and to construct a triple network of differentially expressed gene-circRNA-miRNA-mRNA. In total, 13,160 downregulated and 12,905 upregulated circRNAs were identified in CAD. A gene ontology annotation analysis showed that genes in the network were involved in organelle organization, cell cycle, mitotic cycle, and cellular metabolic process. Parental genes of the 10 dysregulated circRNAs were involved in metabolism and protein modification, and these circRNAs might regulate gene expression associated with CAD via miRNA sponges. As potential competing endogenous RNAs (ceRNAs), dysregulated circRNAs may be involved in the pathogenesis of CAD, which provides new insights into the diagnosis and prognosis of coronary artery disease.

LncRNA Landscape of Coronary Atherosclerosis Reveals Differentially Expressed LncRNAs in Proliferation and Migration of Coronary Artery Smooth Muscle Cells.

We aimed to investigate differentially expressed long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in atherosclerosis and validate the expression of lncRNAs and co-expressed target genes in proliferation and migration models of human coronary artery smooth muscle cells (HCASMCs). Ten coronary artery specimens from a subject who died from a heart attack were employed. The pathological analysis was analyzed by hematoxylin and eosin (H&E) staining, and the lncRNAs and mRNAs were identified by RNA sequencing. Bioinformatic analyses were performed to predict possible mechanisms. The proliferation and migration of HCASMCs were induced with oxidized low-density lipoprotein (ox-LDL). Differentially expressed lncRNAs and mRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). In this study, 68 lncRNAs and 222 mRNAs were identified differentially expressed in atherosclerosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the Fanconi anemia pathway may be involved in atherosclerosis. GON4L was found to be the co-localized target gene of LNC_000439, and 14 genes had high correlations with the expression of seven lncRNAs. In addition, nine lncRNA-miRNA-mRNA networks were constructed, and 53 co-expressed gene modules were detected with weighted gene co-expression network analysis (WGCNA). LNC_000684, LNC_001046, LNC_001333, LNC_001538, and LNC_002115 were downregulated, while LNC_002936 was upregulated in proliferation and migration models of HCASMCs. In total, six co-expressed mRNAs were upregulated in HCASMCs. This study suggests that the differentially expressed lncRNAs identified by RNA sequencing and validated in smooth muscle cells may be a target for regulating HCASMC proliferation and migration in atherosclerosis, which will provide a new diagnostic basis and therapeutic target for the treatment of cardiovascular diseases.

Construction of monitoring model and algorithm design on passenger security during shipping based on improved Bayesian network.

A large number of data is needed by the computation of the objective Bayesian network, but the data is hard to get in actual computation. The calculation method of Bayesian network was improved in this paper, and the fuzzy-precise Bayesian network was obtained. Then, the fuzzy-precise Bayesian network was used to reason Bayesian network model when the data is limited. The security of passengers during shipping is affected by various factors, and it is hard to predict and control. The index system that has the impact on the passenger safety during shipping was established on basis of the multifield coupling theory in this paper. Meanwhile, the fuzzy-precise Bayesian network was applied to monitor the security of passengers in the shipping process. The model was applied to monitor the passenger safety during shipping of a shipping company in Hainan, and the effectiveness of this model was examined. This research work provides guidance for guaranteeing security of passengers during shipping.