卵巢衰老与绝经时间模型研究。

IF 2.2 4区 数学 Q2 BIOLOGY
Sean D Lawley, Nanette Santoro, Joshua Johnson
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引用次数: 0

摘要

卵巢衰老和更年期时间的数学建模有着悠久的历史,可以追溯到半个世纪前诺贝尔奖得主罗伯特·g·爱德华兹的模型。最近,这些模型已被用于调查妇女的临床干预,这强调了在模型开发和分析中科学严谨性的重要性。在本文中,我们分析了最近在生物物理学文献中发表的一个模型。我们首先纠正了一个错误,该错误使不同人群关于更年期年龄的说法无效。然后,我们使用随机分析来显示该模型如何是先验模型的重新参数化,并将其置于几个先验模型的框架中,从而能够应用极值理论。我们证明了一些一般的极值理论结果,并使用它们来获得该模型中绝经年龄的详细估计。特别是,我们得出了一个新的预期更年期年龄公式,这是数量级比以前的启发式估计更准确。我们进一步获得严格的分析估计完全绝经年龄分布和它的所有时刻。我们最后用这些数学结果来阐明更年期年龄变异的生理来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Modeling Ovarian Aging and Menopause Timing.

Mathematical modeling of ovarian aging and menopause timing has a long history, dating back a half-century to the models of Nobel Prize winner Robert G. Edwards. More recently, such models have been used to investigate clinical interventions for women, which underscores the importance of scientific rigor in model development and analysis. In this paper, we analyze a recent model published in the biophysics literature. We first correct an error which invalidates claims about menopause age in different populations. We then use stochastic analysis to show how this model is a reparameterization of a prior model and put it in the framework of several prior models, which enables the application of extreme value theory. We prove some general extreme value theory results and use them to obtain detailed estimates of menopause age in this model. In particular, we derive a new expected menopause age formula which is orders of magnitude more accurate than the previous heuristic estimate. We further obtain rigorous analytical estimates of the full menopause age distribution and all its moments. We conclude by using these mathematical results to elucidate the physiological sources of menopause age variability.

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来源期刊
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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