The natural product embelin has been demonstrated to possess a wide range of therapeutic properties, however, the mechanisms by which it exerts anticancer effects are not yet clear. By monitoring the molecular changes associated during early apoptotic phase, we have identified the crucial role of oxidative stress induced MAP kinase signalling as a predominant mechanism for its anticancer effects. Treatment of A549 lung cancer cells with embelin resulted in the enhancement of phospho-p38 and phospho-JNK levels as early as 4h. Pretreatment of cells with specific inhibitors of p38 (PD169316) and JNK (SP600125) abrogated embelin-induced caspase-3 activation. Studies employing embelin in the presence or absence of specific MAP kinase inhibitors indicated that the observed changes in phosphorylation levels of p38, JNK and ERK 1/2 are solely due to embelin and not because of cross-talk between MAP kinases. Reactive oxygen species (ROS) play a crucial role in embelin induced alterations in MAP kinase phosphorylation and apoptosis as pretreatment of cells with FeTMPyP mitigated this effect. The observed changes are not due to the inhibitory effect of embelin on XIAP as cells treated with SMAC-N7-Ant peptide, a specific inhibitor of XIAP’s BIR3 domain did not mimic embelin induced apoptotic effects. The findings of the present study clearly indicate the crucial role of p38 and JNK pathways in embelin induced apoptosis and provide us with new clues for improving its therapeutic efficacy.

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Face Recognition is important Biometric credentials for identification or verification of a person. In this paper, we propose a novel technique of generating compressed unique features of face images which helps in improving matching speed of recognition. The training face database samples are applied to 2D-DWT to obtain LL band features. The LL band features are subjected to normalization to scale the magnitude values in the range 0 to 1. The output of normalization is further convolved with the original face sample to obtain unique features. The convolved output is subjected to Gaussian filter to obtain smoothened image features. Further, The feature vector of several image samples of single person are compressed to convert into single vector to database feature vectors are created by compressing feature vectors of single person face samples in to single column unique vectors which helps in scaling down of feature vectors and improve matching speed. The test samples are subjected to same process to generate unique compressed test feature vectors and are compared with database vectors using Euclidean distance. The results are tabulated for different set of face databases and also compared with existing techniques to validate the performance of proposed method.