Objective To analyze the relationship of serum S100 calcium binding protein A4(S100A4)and pentraxin-3(PTX3)levels with left atrial appendage thrombosis in patients with NVAF.Methods A total of 120 elderly NVAF patients treated in our hospital from March 2020 to March 2023 were enrolled in this study.According to their echocardiograms,they were divided into a left atrial appendage thrombosis group(40 cases)and a non-thrombosis group(80 cases).Serum S100A4 and PTX3 levels were detected.Spearman correlation analysis was applied to ana-lyze the relationship between serum S100A4 and PTX3 levels and left atrial appendage thrombo-sis.Logistic regression analysis was conducted to analyze the factors affecting left atrial appendage thrombosis.Results The serum levels of S100A4 and PTX3 were higher in the thrombosis group than the non-thrombosis group(P＜0.01).The serum levels of S100A4 and PTX3 were positively correlated with left atrial appendage thrombosis(r=0.497,P=0.000;r=0.555,P=0.000).Heart failure,CHA2DS2-VASc score,B-type natriuretic peptide,uric acid,S100A4 and PTX3 were risk factors for left atrial appendage thrombosis in NVAF patients(P＜0.05,P＜0.01).Combination of serum S100A4 and PTX3 in predicting left atrial appendage thrombosis formation in NVAF patients had an AUC value of of 0.949(95％CI:0.893-0.981).Conclusion Serum S100A4 and PTX3 levels are increased in NVAF patients,they are related to left atrial appendage thrombosis,and their serum levels have certain predictive value for left atrial appendage thrombosis.

Single-cell transcriptome sequencing (scRNA-seq) can resolve the expression characteristics of cells in tissues with single-cell precision, enabling researchers to quantify cellular heterogeneity within populations with higher resolution, revealing potentially heterogeneous cell populations and the dynamics of complex tissues. However, the presence of a large number of technical zeros in scRNA-seq data will have an impact on downstream analysis of cell clustering, differential genes, cell annotation, and pseudotime, hindering the discovery of meaningful biological signals. The main idea to solve this problem is to make use of the potential correlation between cells and genes, and to impute the technical zeros through the observed data. Based on this, this paper reviewed the basic methods of imputing technical zeros in the scRNA-seq data and discussed the advantages and disadvantages of the existing methods. Finally, recommendations and perspectives on the use and development of the method were provided.
Cluster Analysis ; Transcriptome