MM H2O2 (C) for the indicated intervals, pretreated with 1 mM NAC, 100 M GSH, or 10 M SP600125 (D), or transiently transfected with pcDNA, ASK1DN, JNK1DN, or JNK2DN for 6 h (E). Cells were then treated with vehicle or 20 M denbinobin for 2 h. Following treatment, RNA was collected to assess bim expression by semiquantitative RT-PCR as described in “Materials and methods”. Samples were normalized for -actin intensities. Typical traces are representative of three experiments with similar results.Page 13 of(page number not for citation purposes)Journal of Biomedical Science 2009, 16:http://www.jbiomedsci.com/content/16/1/species; SDS: sodium dodecylsulfate; siRNA: short interfering RNA; SOD: superoxide dismutase.Competing interestsThe order LY294002 authors declare that they have no competing interests.Authors’ contributionsCTK participated in the design of the study, performed major experiments and the data interpretation. BCC designed the experiments and interpreted the data. CCY and CMW participated in part of the experiments. MJH participated in the design of the study and interpreted the data. CCC participated in the design of the study and provided the experimental materials. MCC constructed the plasmids. CMT and SLP participated in the design of the study and data interpretation. MYB and CHS participated in data interpretation and manuscript improvement. CHL conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.AcknowledgementsThis work was supported by a research grant (NSC95-2314-B-038-014MY2) from the National Science Council of Taiwan.Figure 8 denbinobin-induced of the apoptotic pathway involved in Schematic summary A549 cell apoptosis Schematic summary of the apoptotic pathway involved in denbinobin-induced A549 cell apoptosis. Denbinobin caused Akt inactivation, leading to Bad dephosphorylation, mitochondrial dysfunction, and subsequent cell apoptosis. Denbinobin also activated ASK1 through ROS generation to cause JNK/AP-1 activation, which in turn induced Bim expression, ultimately resulting in A549 cell apoptosis.
Soh et al. BMC Bioinformatics 2011, 12(Suppl 13):S15 http://www.biomedcentral.com/1471-2105/12/S13/SPROCEEDINGSOpen AccessFinding consistent disease subnetworks across microarray datasetsDonny Soh1,2,3*, Difeng Dong1, Yike Guo2, Limsoon Wong1 From Asia Pacific Bioinformatics Network (APBioNet) Tenth International Conference on Bioinformatics ?First ISCB Asia Joint Conference 2011 (InCoB2011/ISCB-Asia 2011) Kuala Lumpur, Malaysia. 30 November – 2 DecemberAbstractBackground: While PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/26226583 contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet). SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as “subnetworks”. Results: We tested SNet on independent datasets of several diseases, including childhood ALL, DMD and lung cancer. For each of these diseases, we obtained two independent microarray datasets produced by distinct labs on distinct platforms. In each case, our technique consistently produced almost the same list of significant nontrivial subnetworks from two independent sets of microarray data. The gen.