152 resultados para parameter alpha
Resumo:
Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL/Apo-2L) has emerged as a promising anticancer agent. However, resistance to TRAIL is likely to be a major problem, and sensitization of cancer cells to TRAIL may therefore be an important anticancer strategy. In this study, we examined the effect of the epidermal growth factor receptor (EGFR)tyrosine kinase inhibitor (TKI) gefitinib and a human epidermal receptor 2 (HER2)-TKI (M578440) on the sensitivity of human colorectal cancer (CRC) cell lines to recombinant human TRAIL (rhTRAIL). A synergistic interaction between rhTRAIL and gefitinib and rhTRAIL and M578440 was observed in both rhTRAIL-sensitive and resistant CRC cells. This synergy correlated with an increase in EGFR and HER2 activation after rhTRAIL treatment. Furthermore, treatment of CRC cells with rhTRAIL resulted in activation of the Src family kinases (SFK). Importantly, we found that rhTRAIL treatment induced shedding of transforming growth factor-alpha (TGF-alpha) that was dependent on SFK activity and the protease ADAM-17. Moreover, this shedding of TGF-alpha was critical for rhTRAIL-induced activation of EGFR. In support of this, SFK inhibitors and small interfering RNAs targeting ADAM-17 and TGF-alpha also sensitized CRC cells to rhTRAIL-mediated apoptosis. Taken together, our findings indicate that both rhTRAIL-sensitive and resistant CRC cells respond to rhTRAIL treatment by activating an EGFR/HER2-mediated survival response and that these cells can be sensitized to rhTRAIL using EGFR/HER2-targeted therapies. Furthermore, this acute response to rhTRAIL is regulated by SFK-mediated and ADAM-17-mediated shedding of TGF-alpha, such that targeting SFKs or inhibiting ADAM-17, in combination with rhTRAIL, may enhance the response of CRC tumors to rhTRAIL. [Cancer Res 2008;68(20):8312-21]
Resumo:
We report on the synthesis and biological evaluation of a focussed library of N-alpha mercaptoamide containing dipeptides as inhibitors of the zinc metallopeptidase Pseudomonas aeruginosa elastase (LasB, EC 3.4.24.26). The aim of the study was to derive an inhibitor profile for LasB with regard to mapping the S´1 binding site of the enzyme. Consequently, a focussed library of 160 members has been synthesised, using standard Fmoc-solid phase methods (on a Rink-amide resin), in which a subset of amino acids including examples of those with basic (Lys, Arg), aromatic (Phe, Trp), large aliphatic (Val, Leu) and acidic (Asp, Glu) side-chains populated the P´2 position of the inhibitor sequence and all 20 natural amino acids were incorporated, in turn, at the P´1 position. The study has revealed a preference for aromatic and/or large aliphatic amino acids at P´1 and a distinct bias against acidic residues at P´2. Ten inhibitor sequences were discovered that exhibited sub to low micromolar Ki values.
Resumo:
Maintenance of oxygen homeostasis is a key requirement to ensure normal mammalian cell growth and differentiation. Hypoxia arises when oxygen demand exceeds supply, and is a feature of multiple human diseases including stroke, cancer and renal fibrosis. We have investigated the effect of hypoxia on kidney cells, and observed that insulin-induced cell viability is increased in hypoxia. We have characterized the role of protein kinase B (PKB/ Akt) in these cells as a potential mediator of this effect. PKB/Akt activity was increased by low oxygen concentrations in kidney cells, and insulin-stimulated activation of PKB/Akt was stronger, more rapid and more sustained in hypoxia. Reduction of HIF1 alpha levels using antimycin-A or siRNA targeting HlF1 alpha did not affect PKB/Akt activation in hypoxia. Pharmacologic stabilization of HIF1 alpha independent of hypoxia did not increase insulin-stimulated PKB/Akt activation. Although increased insulin-stimulated cell viability was observed in hypoxia, no differences in the degree of insulin-stimulated glucose uptake were observed in L6 muscle cells in hypoxia compared to normoxia. Thus, PKB/Akt may regulate specific cellular responses to growth factors such as insulin under adverse conditions such as hypoxia. alpha 2007 Elsevier GmbH. All rights reserved.
Resumo:
The eng-genes concept involves the use of fundamental known system functions as activation functions in a neural model to create a 'grey-box' neural network. One of the main issues in eng-genes modelling is to produce a parsimonious model given a model construction criterion. The challenges are that (1) the eng-genes model in most cases is a heterogenous network consisting of more than one type of nonlinear basis functions, and each basis function may have different set of parameters to be optimised; (2) the number of hidden nodes has to be chosen based on a model selection criterion. This is a mixed integer hard problem and this paper investigates the use of a forward selection algorithm to optimise both the network structure and the parameters of the system-derived activation functions. Results are included from case studies performed on a simulated continuously stirred tank reactor process, and using actual data from a pH neutralisation plant. The resulting eng-genes networks demonstrate superior simulation performance and transparency over a range of network sizes when compared to conventional neural models. (c) 2007 Elsevier B.V. All rights reserved.