29 research outputs found
Modulation Instability of Ultrashort Pulses in Quadratic Nonlinear Media beyond the Slowly Varying Envelope Approximation
We report a modulational instability (MI) analysis of a mathematical model
appropriate for ultrashort pulses in cascaded quadratic-cubic nonlinear media
beyond the so-called slowly varying envelope approximation. Theoretically
predicted MI properties are found to be in good agreement with numerical
simulation. The study shows the possibility of controlling the generation of MI
and formation of solitons in a cascaded quadratic-cubic media in the few cycle
regimes. We also find that stable propagation of soliton-like few-cycle pulses
in the medium is subject to the fulfilment of the modulation instability
criteria
Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
The purpose of this study was to classify selective oestrogen receptor modulators based on gene expression profiles produced in breast cancer cells expressing either wtERα or mutant351ERα. In total, 54 microarray experiments were carried out by using a commercially available Atlas cDNA Expression Arrays (Clontech), containing 588 cancer-related genes. Nine sets of data were generated for each cell line following 24 h of treatment: expression data were obtained for cells treated with vehicle EtOH (Control); with 10−9 or 10−8 M oestradiol; with 10−6 M 4-hydroxytamoxifen; with 10−6 M raloxifene; with 10−6 M idoxifene, with 10−6 M EM 652, with 10−6 M GW 7604; with 5×10−5 M resveratrol and with 10−6 M ICI 182,780. We developed a new algorithm ‘Expression Signatures’ to classify compounds on the basis of differential gene expression profiles. We created dendrograms for each cell line, in which branches represent relationships between compounds. Additionally, clustering analysis was performed using different subsets of genes to assess the robustness of the analysis. In general, only small differences between gene expression profiles treated with compounds were observed with correlation coefficients ranged from 0.83 to 0.98. This observation may be explained by the use of the same cell context for treatments with compounds that essentially belong to the same class of drugs with oestrogen receptors related mechanisms. The most surprising observation was that ICI 182,780 clustered together with oestrodiol and raloxifene for cells expressing wtERα and clustered together with EM 652 for cells expressing mutant351ERα. These data provide a rationale for a more precise and elaborate study in which custom made oligonucleotide arrays can be used with comprehensive sets of genes known to have consensus and putative oestrogen response elements in their promoter regions