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Biomathematical Modeling of Pulsatile Hormone Secretion: A Historical Perspective

机译:搏动性激素分泌的生物数学模型:历史的观点。

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摘要

Shortly after the recognition of the profound physiological significance of the pulsatile nature of hormone secretion, computer-based modeling techniques were introduced for the identification and characterization of such pulses. Whereas these earlier approaches defined perturbations in hormone concentration-time series, deconvolution procedures were subsequently employed to separate such pulses into their secretion event and clearance components. Stochastic differential equation modeling was also used to define basal and pulsatile hormone secretion. To assess the regulation of individual components within a hormone network, a method that quantitated approximate entropy within hormone concentration-times series was described. To define relationships within coupled hormone systems, methods including cross-correlation and cross-approximate entropy were utilized. To address some of the inherent limitations of these methods, modeling techniques with which to appraise the strength of feedback signaling between and among hormone-secreting components of a network have been developed. Techniques such as dynamic modeling have been utilized to reconstruct dose–response interactions between hormones within coupled systems. A logical extension of these advances will require the development of mathematical methods with which to approximate endocrine networks exhibiting multiple feedback interactions and subsequently reconstruct their parameters based on experimental data for the purpose of testing regulatory hypotheses and estimating alterations in hormone release control mechanisms.
机译:在认识到激素分泌的搏动性的深刻生理意义后不久,就引入了基于计算机的建模技术来识别和表征此类脉冲。这些较早的方法定义了激素浓度-时间序列中的扰动,随后采用解卷积程序将此类脉冲分离为它们的分泌事件和清除成分。随机微分方程模型也用于定义基础和搏动性激素的分泌。为了评估激素网络中各个成分的调节,描述了一种在激素浓度-时间序列内量化近似熵的方法。为了定义激素耦合系统之间的关系,利用了包括互相关和互近似熵的方法。为了解决这些方法的一些固有局限性,已经开发了用于评估网络的激素分泌成分之间和之中的反馈信号强度的建模技术。动态建模等技术已被用于重建耦合系统内激素之间的剂量反应相互作用。这些进展的逻辑扩展将需要开发数学方法,以近似表现出多种反馈相互作用的内分泌网络,然后基于实验数据重建其参数,以测试调节性假设并估算激素释放控制机制的变化。

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