Composite model of time-varying appearance and disappearance of neurohormone pulse signals in blood
Composite model of time-varying appearance and disappearance of neurohormone pulse signals in blood
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DOI：
10.1016/j.jtbi.2005.03.008
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发表时间：
2005-10-07
影响因子：
2
通讯作者：
Veldhuis, JD
中科院分区：
文献类型：
--
作者：
Keenan, DM;Chattopadhyay, S;Veldhuis, JD
血液传播的神经激素信号反映了神经元、腺体和靶组织中肽和类固醇的间歇性爆发式释放。激素控制基本的生理过程，如生长、新陈代谢、生殖和与压力有关的适应。分泌的分子经历扩散、平流和从循环中不可逆消除的组合。量化这些相互依赖的过程，体现离散的事件时间，连续的分泌和消除率，随机变化的结构相关的模型构成了一个巨大的挑战。在实验环境中，只观察激素浓度，其包括随时间变化的分泌和消除的复合物。未观察到潜在爆发（脉冲）的数量、形状和位置以及伴随的分泌和动力学参数。从观察到的数据估计这些过程的属性的能力是了解调节激素动力学的基础。本发明的制剂允许在存在随机变异性的情况下客观地同时评价神经腺活性的离散（脉冲时间）和连续（分泌/消除）性质。概率分布构造的结构参数（分泌/消除，脉冲），并开发了一种算法，通过该算法，可以根据观察到的激素浓度数据，使概率报表的基本结构：脉冲频率每天，总的基础（组成）和脉动分泌每天，和半衰期的消除。该算法由以下步骤组成：首先，对给定的神经激素浓度时间序列显式构造一族顺序递减的假定脉冲-时间集，然后，在以下两者之间进行递归迭代：（a）对于给定的脉冲-时间集，从未知的潜在激素分泌和消除速率的概率分布生成样本;以及（B）确定从一个脉冲-时间组到另一个脉冲-时间组的基于概率的转换是否值得（即，添加/移除脉冲时间或保持不变）。我们应用此程序说明联合估计脉冲时间，分泌率和消除动力学的选择垂体激素（促肾上腺皮质激素，LH和GH）。(c)2005爱思唯尔有限公司保留所有权利。
Blood-borne neurohormonal signals reflect the intermittent burst-like release of peptides and steroids from neurons, glands and target tissues. Hormones control basic physiological processes, such as growth, metabolism, reproduction and stress-related adaptations. Secreted molecules undergo combined diffusion, advection and irreversible elimination from the circulation. Quantification of these interdependent processes by a structurally relevant model embodying discrete event times, continuous rates of secretion and elimination, and stochastic variations poses a formidable challenge. In an experimental setting, one observes only the hormone concentrations, which comprise a time-varying composite of secretion and elimination. The number, shape and location of underlying bursts (pulses) and attendant secretion and kinetic parameters are unobserved. The ability to estimate the properties of these processes from the observed data is fundamental to an understanding of regulated hormonal dynamics. The present formulation allows objective simultaneous appraisal of discrete (pulse times) and continuous (secretion/elimination) properties of neuroglandular activity in the presence of random variability. A probability distribution is constructed for the structural parameters (secretion/elimination, pulsing), and an algorithm is developed by which one can, based upon observed hormone concentration data, make probabilistic statements about the underlying structure: pulse frequency per day, total basal (constitutive) and pulsatile secretion per day, and half-lives of elimination. The algorithm consists of the following steps: first, explicit construction of a family of sequentially decreasing putative pulse-time sets for a given neurohormone concentration time series; and then, recursive iteration between the following two: (a) for a given pulse-time set, generate a sample from the probability distribution of unknown underlying hormone secretion and elimination rates; and (b) determine whether or not a probability-based transition from one pulse-time set to another is merited (i.e., add/remove a pulse-time or stay the same). We apply this procedure illustratively to joint estimation of pulse times, secretion rates and elimination kinetics of selected pituitary hormones (ACTH, LH and GH). (c) 2005 Elsevier Ltd. All rights reserved.