Building a model of the Hypothalamic-Pituitary-Gonadal (HPG) axis

促性腺激素释放激素(GnRH)由下丘脑神经元分泌，控制垂体前叶的促性腺激素LH和FSH的分泌，从而调节生殖的中枢控制。它以脉冲形式分泌，其效果取决于脉冲特性(特别是脉冲频率)。生殖领域最重要的最新发现之一是KNDy系统。这是一种多肽能神经元振荡器，驱动GnRH的搏动性分泌。它还调节性腺类固醇激素的反馈效应，这些激素对关键的生殖过程是必不可少的，例如青春期和季节性繁殖的时间(即在农场动物中)，以及在整个卵巢周期中促性腺激素分泌的微调。所有这些组件(下丘脑脉冲发生器/垂体脉冲解码器/性腺)对人类生殖是绝对必要的，所以这三个组件都是治疗干预的场所也许并不令人惊讶，就像它们中的任何一个的扰动都会导致疾病状态下的不孕一样。我们相信，需要数学和统计方法来充分理解这样一个复杂的系统。为此，我们已经生成了一个复杂的神经振荡器数学模型，我们已经在湿法实验室中进行了训练。数据，现在正在用来探索性腺类固醇调节的可能机制。同样，我们开发了一个数学模型，用于解码垂体促性腺激素对脉冲动力学的影响，并利用该模型来探索GnRH反应中的细胞-细胞变异性及其对信息传递的影响。我们现在计划采用类似的方法来模拟促性腺激素对性腺功能的影响，我们将不得不引入种群动力学作为附加特征(即排卵前颗粒细胞的生长和之后黄体细胞的形成)。然后我们计划简化这些子系统模型，以便这些组件可以组装成整个下丘脑-垂体-性腺系统的有意义的模型。在这个项目中，学生将学习：下丘脑脉冲发生器的数学建模，垂体脉冲解码器，以及黄体生成素和卵泡刺激素对性腺细胞的影响。通过结合现有的实验数据集进行参数拟合和灵敏度分析，以进行数值优化，以对模型组件进行参数设置和验证。简化子系统模型(根据灵敏度分析)，并再次培训系统湿实验室数据。允许生成关于生殖系统及其组件的可测试模型预测的计算方法。

Gonadotropin-releasing hormone (GnRH) is secreted from hypothalamic neurones to control secretion of the gonadotropin hormones LH and FSH form the anterior pituitary, and thereby mediates central control of reproduction. It secretes in pulses and its effects are dependent on pulse characteristics (particularly pulse frequency). One of the most important recent discoveries in the field of reproduction is that of the KNDy system. This is a peptidergic neuronal oscillator that drives pulsatile GnRH secretion. It also mediates feedback effects of gonadal steroid hormones that are essential for key reproductive processes such as the timing of puberty and seasonal breeding (i.e. in farm animals) and the fine-tuning of gonadotropin secretion across the ovarian cycle. All of these components (hypothalamic pulse generator/pituitary pulse decoder/gonads) are absolutely essential for human reproduction so it is perhaps not surprising that all three are sites for therapeutic intervention, just as perturbation of any of them can cause infertility in disease states.We are convinced that mathematical and statistical approaches are required to fully understand such a complex system. To this end we have already generated a sophisticated mathematical model of the neuronal oscillator that we have trained on wetlab. data and are now using to explore possible mechanisms for modulation by gonadal steroids. Similarly, we have developed a mathematical model for the decoding of pulse dynamics by pituitary gonadotropes and have used this to explore cell-cell variability in responses to GnRH and its impact on information transfer. We now plan to take a similar approach to modelling effects of gonadotropin hormones on gonadal function, where we will have to introduce population dynamics as an additional feature (i.e. growth of granulosa cells before ovulation and formation of luteal cells thereafter). We then plan to simplify these sub-system models so that the components can be assembled into a meaningful model of the entire hypothalamo-pituitary-gonadal system.In this project the student will learn:Mathematical modelling of the hypothalamic pulse generator, the pituitary pulse decoder and the effects of LH and FSH on gonadal cells.Numerical optimisation by performing parameter fitting and sensitivity analysis using combination of available experimental data sets to parametrise and validate model components.Simplification of the sub-system models (as informed by sensitivity analysis) and again, training on system wet-lab data.Computational methods that allow the generation of testable model predictions regarding the reproductive system and its components across the lifespan.