Evidence for a Coupled Oscillator Model of Endocrine Ultradian Rhythms.
Evidence for a Coupled Oscillator Model of Endocrine Ultradian Rhythms.
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DOI：
10.1177/0748730418791423
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发表时间：
2018-10
影响因子：
3.5
通讯作者：
Kriegsfeld LJ
中科院分区：
文献类型：
--
作者：
Grant AD;Wilsterman K;Smarr BL;Kriegsfeld LJ
尽管内分泌动态的长周期时间结构已得到充分研究，但以小时为单位的内分泌节律相对尚未被探索。对这些超电节律（UR）的研究仍处于起步阶段，部分原因是尚未建立统一跨系统超电节律模式的理论框架。本概述提出了 UR 的概念耦合振荡器网络模型，其中振荡激素输出或节点通过代表节点间耦合强度的边连接。我们提出，经典荷尔蒙轴内部和跨荷尔蒙轴之间都存在可变强度耦合。由于耦合振荡器是同步的，因此这种模型意味着可以通过调查网络中的可访问节点来推断荷尔蒙系统的变化。这一含义将立即简化 UR 的研究，并为探索影响耦合的条件开辟新的途径。为了支持这个提出的框架，我们回顾了哺乳动物的证据：（1）肠-脑轴和下丘脑-垂体-甲状腺、肾上腺和性腺轴的UR，（2）这些轴内和跨这些轴的UR耦合，以及（3）这些UR与体温的关系。这些系统中的 UR 表现出与耦合振荡器网络大致一致的行为，从而保持一致的 UR 以及轴内和轴间的耦合。该模型可能有助于在高时间分辨率下探索哺乳动物生理学，并提高对个体内分泌系统动力学的理解。
Whereas long-period temporal structures in endocrine dynamics have been well studied, endocrine rhythms on the scale of hours are relatively unexplored. The study of these ultradian rhythms (URs) has remained nascent, in part, because a theoretical framework unifying ultradian patterns across systems has not been established. The present overview proposes a conceptual coupled oscillator network model of URs in which oscillating hormonal outputs, or nodes, are connected by edges representing the strength of node-node coupling. We propose that variable-strength coupling exists both within and across classic hormonal axes. Because coupled oscillators synchronize, such a model implies that changes across hormonal systems could be inferred by surveying accessible nodes in the network. This implication would at once simplify the study of URs and open new avenues of exploration into conditions affecting coupling. In support of this proposed framework, we review mammalian evidence for (1) URs of the gut-brain axis and the hypothalamo-pituitary-thyroid, -adrenal, and -gonadal axes, (2) UR coupling within and across these axes, and (3) the relation of these URs to body temperature. URs across these systems exhibit behavior broadly consistent with a coupled oscillator network, maintaining both consistent URs and coupling within and across axes. This model may aid the exploration of mammalian physiology at high temporal resolution and improve the understanding of endocrine system dynamics within individuals.
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通讯作者：
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