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The preimplantation period of mammalian development is characterized by cleavage of a one-cell embryo to a blastocyst stage embryo. During preimplantation development, 15%-50% of the embryos die as a result of factors that are largely unknown. Two parameters of preimplantation development, a fast rate of development and a low degree of fragmentation, are indicative of good embryo quality. There is mounting evidence that genes control both rate of development and degree of fragmentation. We have discovered a gene, Ped (preimplantation embryo development), which controls the rate of preimplantation embryonic cleavage. The Ped gene is encoded by two similar genes, Q7 and Q9, in the Q region of the mouse major histocompatibility complex (MHC). The Ped gene product is an MHC class Ib protein, the Qa-2 antigen. The mechanisms by which the Ped gene controls rate of embryonic cleavage division are being explored. In order to understand genetic mechanisms underlying the second criterion of embryo quality, degree of fragmentation, we have begun to assess expression of the genes that could potentially regulate apoptosis in preimplantation embryos. We have shown that staurosporine can induce apoptosis in mouse blastocysts. By using RT-PCR, we have shown that genes encoding protein in the two major gene families that regulate apoptosis, the Bcl-2 and caspase gene families, are present in preimplantation embryos. We hypothesize that there is a homeostatic mechanism by which genes that regulate cell survival and those that regulate cell death determine the overall viability of preimplantation embryos.

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Train operation control is of great importance in reducing train operation energy consumption and improving railway operation efficiency. This paper investigates the design of optimal control inputs for multiple trains on a single railway line with several stations. Firstly, a distributed optimal control problem for multiple train operation is formulated to reduce the energy consumption and improve the punctuality of trains. Then, we propose an efficient algorithm based on the framework of the symmetric alternating direction method of multipliers to solve this optimization problem. Finally, numerical simulations show that the method can obtain the optimal train control sequence in fewer iterative steps compared to the alternating direction multiplier method, thus illustrating the effectiveness of the algorithm.