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大鼠肾脏髓质内数学模型中的最大尿液浓缩能力。

Maximum urine concentrating capability in a mathematical model of the inner medulla of the rat kidney.

机构信息

Department of Computer Science, University of Puerto Rico, Río Piedras, 00936-8377, USA.

出版信息

Bull Math Biol. 2010 Feb;72(2):314-39. doi: 10.1007/s11538-009-9448-0.

Abstract

In a mathematical model of the urine concentrating mechanism of the inner medulla of the rat kidney, a nonlinear optimization technique was used to estimate parameter sets that maximize the urine-to-plasma osmolality ratio (U/P) while maintaining the urine flow rate within a plausible physiologic range. The model, which used a central core formulation, represented loops of Henle turning at all levels of the inner medulla and a composite collecting duct (CD). The parameters varied were: water flow and urea concentration in tubular fluid entering the descending thin limbs and the composite CD at the outer-inner medullary boundary; scaling factors for the number of loops of Henle and CDs as a function of medullary depth; location and increase rate of the urea permeability profile along the CD; and a scaling factor for the maximum rate of NaCl transport from the CD. The optimization algorithm sought to maximize a quantity E that equaled U/P minus a penalty function for insufficient urine flow. Maxima of E were sought by changing parameter values in the direction in parameter space in which E increased. The algorithm attained a maximum E that increased urine osmolality and inner medullary concentrating capability by 37.5% and 80.2%, respectively, above base-case values; the corresponding urine flow rate and the concentrations of NaCl and urea were all within or near reported experimental ranges. Our results predict that urine osmolality is particularly sensitive to three parameters: the urea concentration in tubular fluid entering the CD at the outer-inner medullary boundary, the location and increase rate of the urea permeability profile along the CD, and the rate of decrease of the CD population (and thus of CD surface area) along the cortico-medullary axis.

摘要

在大鼠肾脏髓质尿液浓缩机制的数学模型中,使用非线性最优化技术来估计参数集,这些参数集在保持尿液流速在合理生理范围内的同时,使尿液与血浆渗透压比值(U/P)最大化。该模型使用中央核心公式,代表了在整个髓质中各层的 Henle 环和复合收集管(CD)的转动。变化的参数包括:进入降支细段和复合 CD 的管状液中的水流量和尿素浓度;Henle 环和 CD 的数量与髓质深度的比例缩放因子;CD 中尿素通透性分布的位置和增加率;以及从 CD 中最大的 NaCl 转运速率的比例缩放因子。最优化算法旨在最大化一个等于 U/P 的量减去尿液流速不足的惩罚函数。通过在参数空间中使 E 增加的方向改变参数值来寻求 E 的最大值。该算法达到了一个最大值 E,使尿液渗透压和髓质浓缩能力分别比基础值增加了 37.5%和 80.2%;相应的尿液流速以及 NaCl 和尿素的浓度都在报告的实验范围内或接近实验范围。我们的结果表明,尿液渗透压对三个参数特别敏感:进入 CD 的管状液中的尿素浓度、CD 中尿素通透性分布的位置和增加率,以及 CD 数量(因此 CD 表面积)沿皮质-髓质轴的减少率。

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