A Meta-Analysis of the Accuracy of Prostate Cancer Studies Which Use Magnetic Resonance Spectroscopy as a Diagnostic Tool

Peng Wang,You-min Guo,Min Liu,Yong-qian Qiang,Xiao-juan Guo,Yi-li Zhang,Xiao-Yi Duan,Qiu-Juan Zhang,Weifeng Liang 대한영상의학회 2008 Korean Journal of Radiology Vol.9 No.5

Objective: We aimed to do a meta-analysis of the existing literature to assess the accuracy of prostate cancer studies which use magnetic resonance spectroscopy (MRS) as a diagnostic tool. Materials and Methods: Prospectively, independent, blind studies were selected from the Cochrane library, Pubmed, and other network databases. The criteria for inclusion and exclusion in this study referenced the criteria of diagnostic research published by the Cochrane center. The statistical analysis was adopted by using Meta-Test version 6.0. Using the homogeneity test, a statistical effect model was chosen to calculate different pooled weighted values of sensitivity, specificity, and the corresponding 95% confidence intervals (95% CI). The summary receiver operating characteristic (SROC) curves method was used to assess the results. Results: We chose two cut-off values (0.75 and 0.86) as the diagnostic criteria for discriminating between benign and malignant. In the first diagnostic criterion, the pooled weighted sensitivity, specificity, and corresponding 95% CI (expressed as area under curve [AUC]) were 0.82 (0.73, 0.89), 0.68 (0.58, 0.76), and 83.4% (74.97, 91.83). In the second criterion, the pooled weighted sensitivity, specificity, and corresponding 95% CI were 0.64 (0.55, 0.72), 0.86 (0.79, 0.91) and 82.7% (68.73, 96.68). Conclusion: As a new method in the diagnostic of prostate cancer, MRS has a better applied value compared to other common modalities. Ultimately, large scale RCT randomized controlled trial studies are necessary to assess its clinical value. Objective: We aimed to do a meta-analysis of the existing literature to assess the accuracy of prostate cancer studies which use magnetic resonance spectroscopy (MRS) as a diagnostic tool. Materials and Methods: Prospectively, independent, blind studies were selected from the Cochrane library, Pubmed, and other network databases. The criteria for inclusion and exclusion in this study referenced the criteria of diagnostic research published by the Cochrane center. The statistical analysis was adopted by using Meta-Test version 6.0. Using the homogeneity test, a statistical effect model was chosen to calculate different pooled weighted values of sensitivity, specificity, and the corresponding 95% confidence intervals (95% CI). The summary receiver operating characteristic (SROC) curves method was used to assess the results. Results: We chose two cut-off values (0.75 and 0.86) as the diagnostic criteria for discriminating between benign and malignant. In the first diagnostic criterion, the pooled weighted sensitivity, specificity, and corresponding 95% CI (expressed as area under curve [AUC]) were 0.82 (0.73, 0.89), 0.68 (0.58, 0.76), and 83.4% (74.97, 91.83). In the second criterion, the pooled weighted sensitivity, specificity, and corresponding 95% CI were 0.64 (0.55, 0.72), 0.86 (0.79, 0.91) and 82.7% (68.73, 96.68). Conclusion: As a new method in the diagnostic of prostate cancer, MRS has a better applied value compared to other common modalities. Ultimately, large scale RCT randomized controlled trial studies are necessary to assess its clinical value.

Network Analyses of Gene Expression following Fascin Knockdown in Esophageal Squamous Cell Carcinoma Cells

Du, Ze-Peng,Wu, Bing-Li,Xie, Jian-Jun,Lin, Xuan-Hao,Qiu, Xiao-Yang,Zhan, Xiao-Fen,Wang, Shao-Hong,Shen, Jin-Hui,Li, En-Min,Xu, Li-Yan Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.13

Fascin-1 (FSCN1) is an actin-bundling protein that induces cell membrane protrusions, increases cell motility, and is overexpressed in various human epithelial cancers, including esophageal squamous cell carcinoma (ESCC). We analyzed various protein-protein interactions (PPI) of differentially-expressed genes (DEGs), in fascin knockdown ESCC cells, to explore the role of fascin overexpression. The node-degree distributions indicated these PPI sub-networks to be characterized as scale-free. Subcellular localization analysis revealed DEGs to interact with other proteins directly or indirectly, distributed in multiple layers of extracellular membrane-cytoskeleton/ cytoplasm-nucleus. The functional annotation map revealed hundreds of significant gene ontology (GO) terms, especially those associated with cytoskeleton organization of FSCN1. The Random Walk with Restart algorithm was applied to identify the prioritizations of these DEGs when considering their relationship with FSCN1. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile following fascin knockdown to future examine the roles and mechanisms of fascin action.

Shortest Path Analyses in the Protein-Protein Interaction Network of NGAL (Neutrophil Gelatinase-associated Lipocalin) Overexpression in Esophageal Squamous Cell Carcinoma

Du, Ze-Peng,Wu, Bing-Li,Wang, Shao-Hong,Shen, Jin-Hui,Lin, Xuan-Hao,Zheng, Chun-Peng,Wu, Zhi-Yong,Qiu, Xiao-Yang,Zhan, Xiao-Fen,Xu, Li-Yan,Li, En-Min Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.16

NGAL (neutrophil gelatinase-associated lipocalin) is a novel cancer-related protein involves multiple functions in many cancers and other diseases. We previously overexpressed NGAL to analyze its role in esophageal squamous cell carcinoma (ESCC). In this study, a protein-protein interaction (PPI) was constructed and the shortest paths from NGAL to transcription factors in the network were analyzed. We found 28 shortest paths from NGAL to RELA, most of them obeying the principle of extracellular to cytoplasm, then nucleus. These shortest paths were also prioritized according to their normalized intensity from the microarray by the order of interaction cascades. A systems approach was developed in this study by linking differentially expressed genes with publicly available PPI data, Gene Ontology and subcellular localizaton for the integrated analyses. These shortest paths from NGAL to DEG transcription factors or other transcription factors in the PPI network provide important clues for future experimental identification of new pathways.

OsHSF7 gene in rice, Oryza sativa L., encodes a transcription factor that functions as a high temperature receptive and responsive factor

( Jin Ge Liu ),( Qiu Lin Qin ),( Zhen Zhang ),( Ri He Peng ),( Ai Sheng Xiong ),( Jian Min Chen ),( Quan Hong Yao ) 생화학분자생물학회 2009 BMB Reports Vol.42 No.1

Increased Cognition Connectivity Network in Major Depression Disorder: A fMRI Study

Ting Shen,Cao Li,Biao Wang,Wei-min Yang,Chen Zhang,Zhiguo Wu,Mei-hui Qiu,Jun Liu,Yi-feng Xu,Dai-hui Peng 대한신경정신의학회 2015 PSYCHIATRY INVESTIGATION Vol.12 No.2

ObjectiveaaEvidence of the brain network involved in cognitive dysfunction has been inconsistent for major depressive disorder (MDD), especially during early stage of MDD. This study seeks to examine abnormal cognition connectivity network (CCN) in MDD within the whole brain. MethodsaaSixteen patients with MDD and 16 health controls were scanned during resting-state using 3.0 T functional magnetic resonance imaging (fMRI). All patients were first episode without any history of antidepressant treatment. Both the left and right dorsolateral prefrontal cortex (DLPFC) were used as individual seeds to identify CCN by the seed-target correlation analysis. Two sample t test was used to calculate between-group differences in CCN using fisher z-transformed correlation maps. ResultsaaThe CCN was constructed by bilateral seed DLPFC in two groups separately. Depressed subjects exhibited significantly increased functional connectivity (FC) by left DLPFC in one cluster, overlapping middle frontal gyrus, BA7, BA43, precuneus, BA6, BA40, superior temporal gyrus, BA22, inferior parietal lobule, precentral gyrus, BA4 and cingulate gyrus in left cerebrum. Health controls did not show any cluster with significantly greater FC compared to depressed subjects in left DLPFC network. There was no significant difference of FC in right DLPFC network between depressed subjects and the health controls. ConclusionaaThere are differences in CCN during early stage of MDD, as identified by increased FCs among part of frontal gyrus, parietal cortex, cingulate cortex, and BA43, BA22, BA4 with left DLPFC. These brain areas might be involved in the underlying mechanisms of cognitive dysfunction in MDD.

Extramedullary Plasmacytoma Involving the Bilateral Adrenal Glands on MR Imaging

Yuan Li,Ying-kun Guo,Zhi-gang Yang,En-sen Ma,Peng-qiu Min 대한영상의학회 2007 Korean Journal of Radiology Vol.8 No.3

We report here on a 64-year-old woman with extramedullary plasmacytoma involving the bilateral adrenal glands. Primary adrenal extramedullary plasmacytoma is extremely rare and only three cases of extramedullary plasmacytoma in the unilateral adrenal gland have currently been reported on. This case is of interest in that the bilateral adrenals were involved. In this article, we present the MRI findings and we briefly review the relevant literature.

A multi-layer approach to DN 50 electric valve fault diagnosis using shallow-deep intelligent models

Liu, Yong-kuo,Zhou, Wen,Ayodeji, Abiodun,Zhou, Xin-qiu,Peng, Min-jun,Chao, Nan Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.1

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.