ObjectiveTo identify the core genes involved in the great saphenous varicose veins (GSVVs) through bioinformatics methods. MethodsThe transcriptional data of GSVVs tissues and normal great saphenous vein tissues (control tissues) were downloaded from the gene expression omnibus (GEO) database. The single sample gene set enrichment analysis (ssGSEA) was used to calculate Hallmark score. The Weighted Gene Co-expression Network Analysis (WGCNA) combined with machine learning algorithms was used to screen the key genes relevant GSVVs. The protein-protein interaction (PPI) analysis was performed using the String database, and the receiver operating characteristic (ROC) curve was used to reflect the discrimination ability of the target genes for GSVVs. ResultsCompared with the control tissues, there were 548 up-regulated genes and 706 down-regulated genes in the GSVVs tissues, the Hallmark points of KRAS signaling and apical junction were down-regulated, while which of peroxisomes, coagulation, reactive oxygen species pathways, etc. were up-regulated in the GSVVs tissues. A total of 639 differentially expressed genes related to GSVVs were obtained and 165 interaction relation between proteins encoded by 372 genes, and the top 10 genes with the highest betweenness values, ADAM10, APP, NCBP2, SP1, ASB6, ADCY4, HP, UBE2C, QSOX1, and CXCL1, were located at the center of the interaction relation. And the core genes were mainly related to copper ion homeostasis, neutrophil degranulation G protein coupled receptor signaling, response to oxidative stress, and regulation of amide metabolism processes. The SP1 and QSOX1 are both Hub genes. The expressions of the SP1 and QSOX1 in the GSVVs tissues were significantly up-regulated as compared with the control tissues. The area under the ROC curve of SP1 and QSOX1 in distinguishing GSVVs tissues from normal tissues was 0.972 and 1.000, respectively. ConclusionsSP1 and QSOX1 are core genes in the occurrence and development of GSVVs. Regulation of SP1 and QSOX1 genes is expected to achieve precise treatment of GSVVs.
Objective To observe and describe anatomical types of the pulmonary arteries to keep safety of lung resection. Methods Between November 25, 2005 and January 22, 2013, 194 patients who underwent right upper lobectomy/sleeve lobectomy or combined lung resection including right upper lobectomy were included in Peking University Cancer Hospital. There were 128 males with a median age of 59 (37-86) years and 66 females with a median age of 60 (42-77) years. We separated the pulmonary arteries and recorded the number and positions of them. Some patients were recorded photographically. Results There were 10 types of right upper lobe pulmonary artery branches in this study. Type 1: 1 apicoanterior segmental artery, 1 ascending segmental artery, 96 patients (49.5%); Type 2: 1 apicoanterior segmental artery, 2 ascending segmental arteries, 48 patients (24.7%); Type 3: 2 apicoanterior segmental arteries, 1 ascending segmental artery, 28 patients (14.4%); Type 4: 2 apicoanterior segmental arteries, 2 ascending segmental arteries, 9 patients (4.6%); Type 5: 1 apicoanterior segmental artery only, 6 patients (3.1%); Type 6: 1 apicoanterior segmental artery, 3 ascending segmental arteries, 3 patients (1.5%); Type 7: 4 apicoanterior segmental arteries, 1 ascending segmental artery, 1 patient (0.5%); Type 8: 3 apicoanterior segmental arteries, 1 ascending segmental artery, 1 patient (0.5%); Type 9: 2 apicoanterior segmental arteries, 1 patient (0.5%); Type 10: 3 apicoanterior segmental arteries, 2 ascending segmental arteries, 1 patient (0.5%). Conclusion The types of pulmonary artery branches are predictable in some way. It would be helpful to reduce the risk of pulmonary artery injury and improve the operation safety by following the rules. Variations of pulmonary artery should be noticed to avoid the major bleeding due to the pulmonary artery injury.
Objective To investigate the feasibility of diagnosis of potential chronic obstructive pulmonary disease (COPD) patients who cannot finish the pulmonary function test via biphasic CT scan. Methods Sixty-seven male individuals aged 43 to 74 (57.0±5.9) years were divided into a COPD group (n=26) and a control group (n=41). All individuals underwent biphasic quantitative CT scan for calculating the proportion of emphysema, functional small airway disease, and normal component of the whole lung and each lobe. Results Based on principle component analysis, two principal components “imaging feature function 1 and imaging feature function 2” were calculated and analyzed by logistic regression, which found that imaging feature function 1 was an independent risk factor of COPD (odds ratio=8.749, P<0.001), and imaging features function 1 could be used to assist the diagnosis of COPD (area under receiver operating characteristic curve=0.843, P<0.001). Conclusion Imaging features function 1 is an independent risk factor for COPD and can assist the diagnosis of COPD.