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Huang T.,Xian Medical College | Chen Z.,Xian Medical College | Fang L.,JinLing Hospital of Nanjing
Oncology Reports

Epithelial-mesenchymal transition (EMT) is considered a critical event in cancer cell invasion and metastasis. Emerging evidence has shown that curcumin may prevent or delay the progression of cancer, an effect that may be partially due to its ability to disrupt EMT, yet this has not yet been demonstrated. In this study, we used lipopolysaccharide (LPS) to trigger EMT in MCF-7 and MDA-MB-231 breast cancer cell lines and showed that curcumin inhibited LPS-induced morphological changes, decreased the expression of LPS-induced markers of EMT such as vimentin, and increased the expression of E-cadherin, resulting in the inhibition of in vitro cell motility and invasiveness. We discovered that these actions were mediated through the inactivation of NF-?B-Snail signaling pathways. Our results indicate that curcumin plays an important role in the inhibition of LPS-induced EMT in breast cancer cells through the downregulation of NF-?B-Snail activity. These data provide a new perspective of the anti-invasive mechanism of curcumin, indicating that the effect is partly due to its ability to attack the EMT process. Source

Wang Q.,Peoples Hospital of Jiangsu Province | Li Y.,The No. 455 Hospital of PLA | Zhang Z.,Peoples Hospital of Jiangsu Province | Fang Y.,Peoples Hospital of Jiangsu Province | And 5 more authors.
Acta histochemica

This study aimed to explore the underlying molecular mechanisms of osteoarthritis (OA) by bioinformatics analysis. Synovial tissue samples from five OA and five normal donors (ND) were used to identify the differentially expressed genes (DEGs) by paired t-test. Pathway enrichment analysis of DEGs was performed, followed by construction of a protein-protein interaction (PPI) network. A functional enrichment analysis of the modules identified from the PPI network was performed, and the module with the highest enrichment scores was selected for pathway enrichment analysis. A total of 184 DEGs, including 95 up-regulated and 89 down-regulated DEGs, were identified. Up-regulated DEGs were enriched in 6 pathways, such as MAPK signaling and Wnt signaling pathway, while down-regulated DEGs were mainly enriched in glycolysis/gluconeogenesis. In the PPI network, PTTG1 with the highest connectivity degree of 18 was significantly related to nuclear division, mitosis and the cell cycle. Genes in Module A with the highest functional enrichment scores of 9.27 were mainly enriched in the pathways of oocyte meiosis, cell cycle, ubiquitin mediated proteolysis and progesterone-mediated oocyte maturation. The MAPK signaling and Wnt signaling pathways were closely associated with OA. The DEGs, such as PTTG1, MAP2K6, PPP3CC and CSNK1E, may be the potential targets for OA diagnosis and treatment. Copyright © 2014 Elsevier GmbH. All rights reserved. Source

Zhang J.,Fudan University | Cheng W.,Zhejiang Normal University | Wang Z.,JinLing Hospital of Nanjing | Zhang Z.,JinLing Hospital of Nanjing | And 4 more authors.

The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance. Despite the progress to chart the differences between the healthy controls and patients at the group level, the pattern classification of functional brain networks across individuals is still less developed. In this paper we identify two novel neuroimaging measures that prove to be strongly predictive neuroimaging markers in pattern classification between healthy controls and general epileptic patients. These measures characterize two important aspects of the functional brain network in a quantitative manner: (i) coordinated operation among spatially distributed brain regions, and (ii) the asymmetry of bilaterally homologous brain regions, in terms of their global patterns of functional connectivity. This second measure offers a unique understanding of brain asymmetry at the network level, and, to the best of our knowledge, has not been previously used in pattern classification of functional brain networks. Using modern pattern-recognition approaches like sparse regression and support vector machine, we have achieved a cross-validated classification accuracy of 83.9% (specificity: 82.5%; sensitivity: 85%) across individuals from a large dataset consisting of 180 healthy controls and epileptic patients. We identified significantly changed functional pathways and subnetworks in epileptic patients that underlie the pathophysiological mechanism of the impaired cognitive functions. Specifically, we find that the asymmetry of brain operation for epileptic patients is markedly enhanced in temporal lobe and limbic system, in comparison with healthy individuals. The present study indicates that with specifically designed informative neuroimaging markers, resting-state fMRI can serve as a most promising tool for clinical diagnosis, and also shed light onto the physiology behind complex neuropsychiatric disorders. The systematic approaches we present here are expected to have wider applications in general neuropsychiatric disorders. © 2012 Zhang et al. Source

Lu W.,JinLing Hospital of Nanjing | Lu W.,Fudan University | Zheng R.,Fudan University | Chen T.,Fudan University
Neural Networks

In this paper, we discuss outer-synchronization of the asymmetrically connected recurrent time-varying neural networks. By using both centralized and decentralized discretization data sampling principles, we derive several sufficient conditions based on three vector norms to guarantee that the difference of any two trajectories starting from different initial values of the neural network converges to zero. The lower bounds of the common time intervals between data samples in centralized and decentralized principles are proved to be positive, which guarantees exclusion of Zeno behavior. A numerical example is provided to illustrate the efficiency of the theoretical results. © 2015 Elsevier Ltd. Source

Ge Y.-R.,JinLing Hospital of Nanjing | Tian N.,JinLing Hospital of Nanjing | Lu Y.,JinLing Hospital of Nanjing | Wu Y.,JinLing Hospital of Nanjing | And 2 more authors.
Asian Pacific Journal of Cancer Prevention

Background: Many observational studies have assessed the possible association between occupational cooking and uveal melanoma risk, but reported results are controversial. Our goal was to evaluate the association between occupational cooking and uveal melanoma risk by conducting a meta-analysis of observational studies. Methods: PubMed, EMBASE, and Web of Science were searched through June 2012 to identify all eligible studies. The pooled odds ratio (OR) with its 95% confidence interval (95%CI) was used to evaluate this association. Either a fixed- or a random-effects model were used to calculate pooled ORs. Results: Five case-control studies involving a total of 1,199 cases and 6,927 controls were included in the meta-analysis. Overall, occupational cooking was associated with an increased risk of uveal melanoma (OR: 1.81,95%CI 1.33-2.46, P < 0.001). Subgroup analysis by gender suggested occupational cooking was associated with increasedrisk of uveal melanoma in both men (OR: 2.16, 95%CI 1.06-4.40, P = 0.034) and women (OR: 1.92, 95%CI 1.19-3.10, P = 0.008). Conclusion: This meta-analysis suggests that occupational cooking is associated with an increased risk of uveal melanoma in both men and women. Source

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