We aimed to explore the potential genes or pathways related to venous thromboembolism (VTE) and expected our findings could contribute to the development of new target drugs for VTE. The gene expression profile of GSE19151 was downloaded from Gene Expression Omnibus (GEO) database. The bioinformatics methods were applied to screen the feature genes and pathways related with VTE. A total of 115 DEGs were identified, including 25 downregulated genes and 90 upregulated genes. Function enrichment analysis showed that upregulated genes of VTE were mainly enriched in ribosome and translation-related pathways, while downregulated genes were mainly enriched in cytoskeletal protein binding and non-membrane-bounded organelle-related pathways. MCL1, TP53, and RERE were three outstanding genes involved in the interaction network. The most significant pathways enriched by module genes were ribosome and oxidative phosphorylation. Moreover, all the products of the 18 genes enriched in ribosome (hsa03010) were ribosomal proteins. Ribosome, translation, actin binding, and non-membrane-bounded organelle pathways were closely related to the development of VTE. Moreover, MCL1, TP53, and RERE might play key roles in the process of VTE.

BackgroundBreast cancer is a malignancy and lethal tumor in women. Metastasis of breast cancer is one of the causes of poor prognosis. Increasing evidences have suggested that the competing endogenous RNAs (ceRNAs) were associated with the metastasis of breast cancer. Nonetheless, potential roles of ceRNAs in regulating the metastasis of breast cancer remain unclear.MethodsThe RNA expression (3 levels) and follow-up data of breast cancer and noncancerous tissue samples were downloaded from the Cancer Genome Atlas (TCGA). Differentially expressed and metastasis associated RNAs were identified for functional analysis and constructing the metastasis associated ceRNA network by comprehensively bioinformatic analysis. The Kaplan-Meier (K-M) survival curve was utilized to screen the prognostic RNAs in metastasis associated ceRNA network. Moreover, we further identified the metastasis associated biomarkers with operating characteristic (ROC) curve. Ultimately, the data of Cancer Cell Line Encyclopedia (CCLE, https://portals.broadinstitute.org/ccle) website were selected to obtained the reliable metastasis associated biomarkers.Results1005 mRNAs, 22 miRNAs and 164 lncRNAs were screened as differentially expressed and metastasis associated RNAs. The results of GO function and KEGG pathway enrichment analysis showed that these RNAs are mainly associated with the metabolic processes and stress responses. Next, a metastasis associated ceRNA (including 104 mRNAs, 19 miRNAs, and 16 lncRNAs) network was established, and 12 RNAs were found to be related to the overall survival (OS) of patients. In addition, 3 RNAs (hsa-miR-105-5p, BCAR1, and PANX2) were identified to serve as reliable metastasis associated biomarkers. Eventually, the results of mechanism analysis suggested that BCAR1 might promote the metastasis of breast cancer by facilitating Rap 1 signaling pathway.ConclusionIn the present research, we identified 3 RNAs (hsa-miR-105-5p, BCAR1 and PANX2) might associated with prognosis and metastasis of breast cancer, which might be provide a new perspective for metastasis of breast cancer and contributed to the treatment of breast cancer.

Objective: This study aimed to establish a model to distinguish Kawasaki disease (KD) from other fever illness using the prognostic nutritional index (PNI) and immunological factors. Method: We enrolled a total of 692 patients (including 198 with KD and 494 children with febrile diseases). Of those, 415 patients were selected to be the training group and 277 patients to be the validation group. Laboratory data, including the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), the prognostic nutritional index (PNI), and immunological factors, were retrospectively collected for an analysis after admission. We used univariate and multivariate logistic regressions and nomograms for the analysis. Result: Patients with KD showed significantly higher C3 and a lower PNI. After a multivariate logistic regression, the total leukocyte count, PNI, C3, and NLR showed a significance (p < 0.05) and then performed well with the nomogram model. The areas under the ROC in the training group and the validation group were 0.858 and 0.825, respectively. The calibration curves of the two groups for the probability of KD showed a near agreement to the actual probability. Conclusions: Compared with children with febrile diseases, patients with KD showed increased C3 and a decreased nutritional index of the PNI. The nomogram established with these factors could effectively identify KD from febrile illness in children.

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ObjectivesTo study the impact of antibiotics used in Kawasaki disease (KD) with coronary artery lesions (CAL) and identify independent risk factors.MethodologyThis study reviewed the records of 287 KD patients between the years 2016 and 2020. Patients were grouped by their outcome, the CAL group, and a no-coronary artery lesions (NCAL) group, and stratified by the use of antibiotics. We collected clinical and laboratory data before the intravenous immunoglobulin (IVIG) treatment.ResultsThe two groups of KD patients with and without CAL were compared. The results showed that there are significant differences between groups which were erythrocyte count (p = 0.045) and hemoglobin (p = 0.005), red blood cell-specific volume (p = 0.001), immature granular cells percentage (p = 0.006), total protein (p = 0.045), albumin (p = 0.041), alkaline phosphatase (p = 0.023), and chlorine (p = 0.006). After multivariate logistic regression, neutrophil granulocyte percentage (odds ratio [OR] = 1.200, 95% confidence interval [CI]: 1.008-1.428, p = 0.040), lymphocyte percentage (p = 0.028, OR = 1.243, 95% CI: 1.024-1.508, p = 0.028) and total protein (OR = 4.414, 95% CI: 1.092-17.846, p = 0.037) were found to be independent risk factors for CAL. After analyzing the cases with a history of antibiotic use, multivariate analysis showed no indicators were considered independent risk factors for CAL.ConclusionNeutrophil granulocyte percentage, Lymphocyte percentage and total protein were independent risks for CAL in KD without antibiotics use history. The use of antibiotics affected physiological indicators of KD patients.