Paclitaxel (Taxol) is an antineoplastic agent that specifically targets microtubules and arrests cells at the G2/M phase of the cell cycle. In addition to mitotic arrest, the activation of c-Jun N-terminal kinase (JNK) signaling pathway has been demonstrated to be involved in the process leading to apoptosis. In an attempt to explore what genes are transcriptionally regulated by the activated JNK signaling pathway upon paclitaxel treatment, we used cDNA microarrays to analyse the changes of gene expression in human ovarian cancer cells that were treated with paclitaxel and/or the JNK inhibitor SP600125. Among 20 genes that were specifically regulated by the paclitaxel-activated JNK pathway, interleukin (IL)-6 was shown to elicit function through the JAK-STAT signaling pathway in an autocrine and/or paracrine fashion. Subsequently, we identified that 87.5% of eight tested ovarian cancer lines secreted detectable levels of IL-6, which could be further upregulated 2-3.2 fold by 1 lM paclitaxel. Dissection on regulatory pathways for IL-6 indicated that (i) when ovarian cancer cells were treated with paclitaxel at low but clinically achievable concentrations (exemplified by 1 lM in this study), the JNK signaling pathway was the major stimulator of IL-6 gene regulation and (ii) at suprapharmacologically high concentrations (exemplified by 50 lM), paclitaxel exerted lipopolysaccharide-like effects, most likely through the Toll-like receptor 4 signaling pathway. Collectively, these results suggest that paclitaxel upregulates functional IL-6 expression in human ovarian cancer cells through multiple signaling pathways.

No abstract

Generally, the biggest difficulty when designing a neural network controller that will be capable of rapidly and efficiently controlling complex and nonlinear systems is selection of the most appropriate initial values for the parameter vector. Overcoming the coupling effects of each degree-of-freedom is also difficult in multi-variable system control. In this study, an intelligent adaptive controller is proposed to handle these behaviors. First of all, an uncertain and nonlinear plant, for the tracking of a reference trajectory, is well approximated via radial basis function networks. Next, the adjustable parameters of the intelligent system are initialized using a genetic algorithm. Then, novel online parameter tuning algorithms are developed, based on the Lyapunov stability theory. A boundary-layer function is introduced into these updating laws to cover parameter and modeling errors, and to guarantee that the state errors converge to within a specified error bound. The non-square multi-variable system can be decoupled into several reduced-order isolated square multi-variable subsystems using a singular perturbation scheme for different types of time-scale stability analysis. Following this, a decoupled adaptive neural network controller is derived simultaneously to stabilize and control the system. Finally, an example, in the form of a numerical simulation, is provided to demonstrate the effectiveness of the control methodology, which is shown to rapidly and efficiently control nonlinear multi-variable systems.

Nervous necrosis virus (NNV), a piscine nodavirus, has caused serious viral nervous necrosis and viral encephalopathy and retinopathy in hatchery-reared larvae and juveniles of a wide range of marine teleost species worldwide in the last two decades. Although the mortality of NNV-infected larvae is nearly 100%, there are still some larvae that survive this catastrophe. To comprehensively understand the variations of these survivors at the molecular level, we collected orange-spotted grouper larvae that survived an NNV outbreak in an indoor hatchery in southern Taiwan to study differential gene expression. Healthy larvae with high, medium and low levels of detected NNV were compared with morbid larvae using a 9600-clone-containing grouper larva cDNA microarray, and differential gene expression was further confirmed by a quantitative real-time polymerase chain reaction. Significant variation exists in healthy larvae. The following genes were upregulated: adenylate kinase 1-2, myosin binding protein H-like, myosin light chain 2, myosin light chain 3, tropomyosin, fast/white muscle troponin T embryonic isoform, and parvalbumin 1 and 2 genes. The following genes were downregulated: apolipoprotein A-I, trypsinogen, pyruvate kinase and astacin-like metalloprotease. Moreover, immunoglobulin M heavy chain gene transcription was significantly higher in healthy larvae that had high virus levels, indicating that humoral immunity might protect organisms from viral infection. These results suggest that some non-immune-related genes may have played important roles in survival during the larval metamorphosis stage, after betanodavirus infection.