Objective To discuss the clinical application value of 256-slice helical CT 3D-imaging in guiding interventional occlusion therapy for patent ductus arteriosus (PDA).Methods A total of 40 patients with sonography-proved PDA were randomly divided into group A (angiography group) and group B (CT-guided group) with 20 patients in each group.For the patients of group A,occlusion of PDA was performed based on the intraoperative angiography findings;and for the patients of group B,occlusion of PDA was carried out according to CT examination results.Intraoperative cardiac ultrasound monitoring was adopted and the curative effect was evaluated.Results The morphology of PDA demonstrated on CT 3Dimaging in group B was highly consistent with the configuration of PDA displayed on intraoperative angiography in group A.The most narrow diameters of PDA in group B and group A were (3.88±1.59) mm and (3.63±1.41) mm respectively,and the lengths of PDA in group B and group A were (6.1±1.06) mm and (6.82±0.74) mm respectively;the differences between the two groups were not statistically significant (P＞0.05).The time spent for surgery in group B and group A was (34.3±9.11) min and (17.33±5.81) min respectively,and the intraoperative X-ray radiation doses in group B and group A were (33.93±11.0) mGy and (66.48±9.77) mGy respectively;the differences between the two groups were statistically significant (P＜0.001).In group B,the preoperative X-ray radiation dose from CT examination was (119.79±29.45) mGy,when it was added to the intraoperative X-ray radiation dose the total cumulative radiation dose of group B was strikingly higher than that of group A.Conclusion Contrast-enhanced 256-slice helical CT scan and 3D-imaging technique can replace intraoperative angiography to get accurate anatomical imaging information of PDA,which are very helpful for the performance of interventional occlusion of PDA,meanwhile,it can effectively reduce the damage to the punctured artery and shorten the operation time.However,the radiation dose is a factor that should be taken into consideration.(J Intervent Radiol,2017,26:206-209)

Objective: To understand the current situation of college students emotional regulation and its correlation with perceived social support, so as to provide a reference for improving emotional regulation ability among college students. Methods: From September 15 to October 15, 2022, a total of 15 560 students from 27 colleges and universities in Guangdong, Jiangsu, Shandong, Shanghai, Anhui, Hebei, Yunnan, Shanxi and Gansu were enrolled by stratified random sampling method. The Perceived Social Support Scale (PSSS) and the Emotion Regulation Questionnaire (ERQ) were used to investigate, and multiple stepwise regression was used to explore the relationship between perceived social support and emotion regulation of college students. Results: The scores of emotion regulation, cognitive reappraisal and expression inhibition were 44(40, 50), 24(20, 28) and 20(19, 24) respectively. There were significant differences in the scores of emotion regulation, cognitive reappraisal and expression inhibition by age, grade, household registration, only child status,cost of living, and sleep ( H/Z =77.72, 49.73, -5.10, -9.77, 7.68, 168.27 ; 204.55, 317.32, -5.96, -7.60, 131.20, 968.08; 82.18, 148.04, -2.30, -8.03, 64.82, 188.08, P <0.05). In addition, the multiple stepwise regression found that family support, friend support, and other support in perceived social support all had a positive impact on the emotional regulation state of college students ( β =0.137,0.207,0.090), and family support and friend support had a significant positive effect on expression inhibition( β =0.079,0.053) and cognitive reappraisal( β =0.153,0.296)( P <0.01). Conclusion The perceived social support can directly affect the emotional regulation of college students, and improving the emotional regulation ability has a positive significance to promote the mental health level among college students.

OBJECTIVETo investigate the differences in the gene expression profiles of the peripheral blood immune cells between liver and kidney transplantation recipients.

METHODSA dataset containing the gene expression profiles of 27 liver transplantation recipients and 25 kidney transplantation recipients (from GSE22229 and GSE28842, respectively) was downloaded from the GEO database. By combining gene set enrichment analysis (GSEA) and biological network analysis of the differentially expressed genes using Cytoscape software, we analyzed the core genes closely related to liver or kidney transplantations.

RESULTSGSEA identified 20 highly overlapping genes for liver transplantation and another 20 for kidney transplantation using leading edge analysis. Fourteen hub nodes (gene) for liver transplantation and 13 for kidney transplantation were identified by cytoscape software using interaction network analysis. Five core genes related to liver transplantation and 5 to kidney transplantation were obtained by integrating GSEA and biological network analysis.

CONCLUSIONControlling the transcription and translation of the genes of the peripheral blood immune cells is the main immune regulation mechanism in liver transplantation recipients, but in the recipients of kidney transplantation, the protein interaction network plays a more prominent role. Energy metabolism and functional regulation of the immune cells are closely related. The core genes in peripheral blood immune cells related to liver or kidney transplantation may play key roles in regulating immune functions.

Gene Regulatory Networks ; Humans ; Kidney Transplantation ; Liver Transplantation ; Oligonucleotide Array Sequence Analysis ; Transcriptome

Objective:To explore a new method of diagnosing and identifying renal transplantation clinical almost tolerance through a diagnostic model using plasma proteomics.Methods:From November 2011 to November 2012, plasma samples from 43 subjects were collected and divided into the groups of clinical almost tolerance(18 cases), rejection(12 cases)and healthy control(13 cases). Protemic analysis of plasma samples was performed by surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). Differential mass spectrometry peaks were screened and diagnostic model was established by Biomarker Wizard and Biomarker Pattern software. Identification of mass spectrometric peaks of nodes in the diagnostic model was carried out by searching the databases of SWISS-PROT and TrEMBL using ExPASy's TagIdent tool.Results:A total of 21 differential proteins peaks were obtained( P<0.05). Diagnostic model was composed of five mass spectrum peaks of 2 565.15, 1 966.28, 6 674.78, 1 103.27, 1 716.69 and 1 966.28.The sensitivity, specificity and area under the ROC curve of model were 83.3%, 92.0% and 0.951 respectively for diagnosing clinical almost tolerance.Bioinformatic identification results of mass spectrometric peaks of nodes in model were proteins of ANFB, MCH, TFF1, PDYN and PSME3. Conclusions:Establishing a diagnostic mode by plasma proteomics may be effectively employed for diagnosing clinical almost tolerance in kidney transplant.