| Fully grown Xenopus oocytes can remain in their immature state essentially indefinitely, or, in response to the steroid hormone progesterone, can be induced to develop into fertilizable eggs. This process is termed oocyte maturation.Oocyte maturation involves the activation of various signal trans-duction pathways that converge to activate maturation - promoting factor ( MPF) ; this is a key activity that catalyses entry into M - phase of meiosis I and meiosis II.An important feature of meiotic maturation is an extensive network of feedback signalling ( mostly downstream of MPF activation) , which is responsible for the generation of an all - or - none response ensuring that the oocyte completes meiotic progression. These feedback mechanisms often make it difficult to determine the order of e-vents in a signalling cascade, since a small level of MPF activity is sufficient to activate most of the pathways involved in oocyte maturation.In this sense, a model is extremely helpful even the model is far from complete and absolutely correct, the model provides a clear working field, based which more meaningful questions may be asked and tried to solved, further works may be done to correct and expand the model till we have a relatively complete view of early oocyte maturation.Constructing quantitative model with ordinary differential equationsFor the cell - cycle control system, it is appropriate to use ordinary differential equations ( ODEs ) , because molecular diffusion, transcription, translation and membrane transport seem to be fast ( a matter of seconds) compared with the duration of the cell cycle ( hours). Spatial localization of reactions can be handled by compart-mental modelling, in the spirit of pharmacokinetics. The differential equations used simply capture, in mathematical terms, our intuitive i-deas about protein synthesis and degradation, phosphorylation and de-phosphorylation. They allow us to test a hypothesis by computing how the concentration of each protein will rise and fall, and then comparing the simulated behaviour of the model with the observed behaviour of the cell.We applied different rate laws to different reactions and got such ODES1. For changes of cyclinB concentration , law of mass action was recruitedd[cyclinB ]/dt = k1 [ AA ] - k2 [ cyclinB ] - k3 [ cyclinB ] * [cdc2]2. Michaelis - Menten rate equations were used in reactions regulated by enzymes for example, for cdc25c;We construct the model with the software Gepasi( general pathway simulator)ResultsXenopus oocyte maturation process and model simulationG2 arrest: let PKA - > iPKA rate = 0, total cyclin rises andstays high without causing MPF activation.free cyclin level is low for they quickly bind with cdc2, the total cyclin mainly exist in MPRTY (Pre - MPF)Ml to M2 process; all the elements are set to G2 arrest concentration , then we set PKA - > iPKA rate = 0.1 to simulate progesterone effect, (it has been reported that progesterone can decrease the cAMP level, thus causes PKA inactivation) MPF activity rise at Ml, falls at the inter phase between Ml and M2, and then remains high at M2 arrest.The model may be used not only to simulate the process, but also to provide explanations why the process is so; here we give an explanation of such a process.We showed that PKA increased the threshold 0Our model might be used to simulate and explain the normal oo-cyte maturation process, and next, we simulated several experiments and compare results observed in our simulation with those observed in experiments. Quantitative models could be well used to simulate kinase activity changes in xenopus oocyte maturation. However, one weakness of quantitative simulation is the difficulties of determining parameters with existing experimental results; and the dynamical behavior of the system will change with different parameter sets. Thus it is necessary to construct qualitative models to complement the quantitative models. We constructed the qualitative model with GNA ( genetic networ...
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