Comparative proteomic analysis to study molecular events during gonad development in mice

Sex determination represents a critical bifurcation in the road of embryonic development. It is based on a finely regulated network of gene activity, as well as protein-protein interactions and activation or silencing of signaling pathways. Despite the identification of a number of critical genes, many aspects of the molecular cascade that drives the differentiation of the embryonic gonad into either a testis or an ovary remain poorly understood. To identify new proteins involved in this cascade, we employed two-dimensional gel electrophoresis and mass spectrometry to compare the protein expression profiles of fetal mouse testes and ovaries. Three proteins, hnRPA1, TRA1, and HSC71, were found to be expressed in a male-specific manner and this expression was confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR) and in situ hybridization. Moreover, HSC71 was found to be hyperphosphorylated in male compared to female gonads, emphasizing the advantage of the proteomic approach in allowing the detection of posttranslational modifications.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.