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Combined detections of interleukin 27, interferon-γ, and adenosine deaminase in pleural effusion for diagnosis of tuberculous pleurisy 被引量:42
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作者 WU Yan-bin YE Zhi-jian +3 位作者 QIN Sou-ming WU Cong CHEN Yi-qiang SHI Huan-zhong 《Chinese Medical Journal》 SCIE CAS CSCD 2013年第17期3215-3221,共7页
Background Previous studies reported interleukin-27 (IL-27), interferon-y (IFN-γ), or adenosine deaminase (ADA) alone plays a helpful role in diagnosing tuberculous pleural effusion (TPE). The present study a... Background Previous studies reported interleukin-27 (IL-27), interferon-y (IFN-γ), or adenosine deaminase (ADA) alone plays a helpful role in diagnosing tuberculous pleural effusion (TPE). The present study aims at comparing the diagnostic accuracy of pleural IL-27, IFN-γ, and ADA, and investigate the diagnostic accuracy of the combination of IL-27, IFN-γ, or/ and ADA for differentiating TPE from pleural effusions with the other etiologies. Methods The concentrations of IL-27, IFN-γ and ADA were simultaneously determined in pleural fluids and sera from 40 patients with TPE; 26 with malignant pleural effusion, seven with infectious pleural effusion, and eight with transudative pleural effusion by enzyme linked immunosorbent assay and colorimetric method. The corresponding biochemical indexs were also simultaneously determined. Results The concentrations of pleural IL-27 and IFN-γ in the tuberculous group were significantly higher than those in the malignant, infectious, and transudative groups. The concentrations of ADA in TPE were significantly higher than those in MPE or transudative effusions, while much lower than those in infectious effusions. Among these three biomarkers, IL- 27 was the most effective for TPE diagnosis, with the cut off value of 900.8 ng/L. IL-27 had a high sensitivity of 95% and specificity of 97.6% for differential diagnosis of TPE from non-TPEs. Combinations of IL-27, IFN-γ and ADA measurements further increased the sensitivity or specificity up to 100%. Conclusions Compared to non-TPEs, IL-27, IFN-γ and ADA all simultaneously increased in TPE; and among these three rapid detection methods, IL-27 appeared to be the best for distinguishing tuberculous from non-TPEs, especially from MPE. Combinations of the three markers (IL-27, IFN-γ and ADA) yielded the highest sensitivity and specificity. These findings suggest that the applications of a new biomarker, IL-27, alone or with IFN-γ and ADA, may contribute to more efficient diagnosis strategies in the management of tuberculous pleurisy. 展开更多
关键词 adenosine deaminase INTERFERON-Γ interleukin 27 tuberculous pleurisy
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Bioinformatic exploration of MTAl-regulated gene networks in colon cancer 被引量:4
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作者 Chunxiao Li Haijuan Wang +4 位作者 Feng Lin Hui Li Tao Wen Haili Qian Qimin Zhan 《Frontiers of Medicine》 SCIE CAS CSCD 2016年第2期178-182,共5页
Metastasis-associated gene 1 (MTA1) controls a series of biological processes in tumor progression. Tumor progression is a complex process regulated by a gene network. The global cancer gene regulatory network must ... Metastasis-associated gene 1 (MTA1) controls a series of biological processes in tumor progression. Tumor progression is a complex process regulated by a gene network. The global cancer gene regulatory network must be analyzed to determine the position of MTA1 in the molecular network and its cooperative genes by further exploring the biological functions of this gene. We used TCGA data sets and GeneCards database to screen MTA1- related genes. GO and KEGG pathway analyses were conducted with DAVID and gene network analysis via STRING and Cytoscape. Results showed that in the development of colon cancer, MTA1 is linked to certain signal pathways, such as Wnt/Notch/nucleotide excision repair pathways. The findings also suggested that MTA1 demonstrates the closest relationship in a coregulation process with the key molecules AKT1, EP300, CREBBP, SMARCA4, RHOA, and CAD. These results lead MTAI exploration to an in-depth investigation in different directions, such as Wnt, Notch, and DNA repair. 展开更多
关键词 metastasis-associated gene 1 colon cancer BIOINFORMATICS
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