Passively harmonically mode-locked vertical-external-cavity surface-emitting laser emitting 1.1 ps pulses at 147 GHz repetition rate

Coupled-cavity passive harmonic mode-locking of a quantum well based vertical-external-cavity surface-emitting laser has been demonstrated, yielding an output pulse train of 1.5 ps pulses at a repetition rate of 80 GHz and with an average power of 80 mW. Harmonic mode-locking results from coupling between the main laser cavity and a cavity formed within the substrate of the saturable absorber structure. Mode-locking on the second harmonic of the substrate cavity allows a train of 1.1 ps pulses to be generated at a repetition rate of 147 GHz with 40 mW average power. © 2010 American Institute of Physics.

Independent component analysis of microarray data in the study of endometrial cancer.

Gene microarray technology is highly effective in screening for differential gene expression and has hence become a popular tool in the molecular investigation of cancer. When applied to tumours, molecular characteristics may be correlated with clinical features such as response to chemotherapy. Exploitation of the huge amount of data generated by microarrays is difficult, however, and constitutes a major challenge in the advancement of this methodology. Independent component analysis (ICA), a modern statistical method, allows us to better understand data in such complex and noisy measurement environments. The technique has the potential to significantly increase the quality of the resulting data and improve the biological validity of subsequent analysis. We performed microarray experiments on 31 postmenopausal endometrial biopsies, comprising 11 benign and 20 malignant samples. We compared ICA to the established methods of principal component analysis (PCA), Cyber-T, and SAM. We show that ICA generated patterns that clearly characterized the malignant samples studied, in contrast to PCA. Moreover, ICA improved the biological validity of the genes identified as differentially expressed in endometrial carcinoma, compared to those found by Cyber-T and SAM. In particular, several genes involved in lipid metabolism that are differentially expressed in endometrial carcinoma were only found using this method. This report highlights the potential of ICA in the analysis of microarray data.