Interacting information streams on the nephron arterial network.

Frontiers in network physiology Pub Date : 2023-10-19 eCollection Date: 2023-01-01 DOI:10.3389/fnetp.2023.1254964
Donald J Marsh, Anthony S Wexler, Niels-Henrik Holstein-Rathlou
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Abstract

Blood flow and glomerular filtration in the kidney are regulated by two mechanisms acting on the afferent arteriole of each nephron. The two mechanisms operate as limit cycle oscillators, each responding to a different signal. The myogenic mechanism is sensitive to a transmural pressure difference across the wall of the arteriole, and tubuloglomerular feedback (TGF) responds to the NaCl concentration in tubular fluid flowing into the nephron’s distal tubule,. The two mechanisms interact with each other, synchronize, cause oscillations in tubular flow and pressure, and form a bimodal electrical signal that propagates into the arterial network. The electrical signal enables nephrons adjacent to each other in the arterial network to synchronize, but non-adjacent nephrons do not synchronize. The arteries supplying the nephrons have the morphologic characteristics of a rooted tree network, with 3 motifs characterizing nephron distribution. We developed a model of 10 nephrons and their afferent arterioles in an arterial network that reproduced these structural characteristics, with half of its components on the renal surface, where experimental data suitable for model validation is available, and the other half below the surface, from which no experimental data has been reported. The model simulated several interactions: TGF-myogenic in each nephron with TGF modulating amplitude and frequency of the myogenic oscillation; adjacent nephron-nephron with strong coupling; non-adjacent nephron-nephron, with weak coupling because of electrical signal transmission through electrically conductive arterial walls; and coupling involving arterial nodal pressure at the ends of each arterial segment, and between arterial nodes and the afferent arterioles originating at the nodes. The model predicted full synchronization between adjacent nephrons pairs and partial synchronization among weakly coupled nephrons, reproducing experimental findings. The model also predicted aperiodic fluctuations of tubular and arterial pressures lasting longer than TGF oscillations in nephrons, again confirming experimental observations. The model did not predict complete synchronization of all nephrons.

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肾单位动脉网络上相互作用的信息流。
肾中的血流量和肾小球滤过由作用于每个肾单位的传入小动脉的两种机制调节。这两种机制作为极限循环振荡器工作,每种机制都对不同的信号作出响应。肌源性机制对小动脉壁上的透壁压差敏感,而肾小管-肾小球反馈(TGF)对流入肾单位远端小管的管液中的NaCl浓度作出反应,。这两种机制相互作用,同步,引起管状流量和压力的振荡,并形成传播到动脉网络中的双峰电信号。电信号使动脉网络中彼此相邻的肾单位能够同步,但非相邻肾单位不同步。供应肾单位的动脉具有根状树状网络的形态学特征,有3个基序表征肾单位的分布。我们开发了一个由动脉网络中的10个肾单位及其传入小动脉组成的模型,该模型再现了这些结构特征,其中一半的成分在肾表面,那里有适合模型验证的实验数据,另一半在表面以下,没有实验数据报告。该模型模拟了几种相互作用:每个肾单位的TGF肌源性,TGF调节肌源性振荡的幅度和频率;相邻肾单位强耦合肾单位;不相邻的肾单位-肾单位,由于电信号通过导电动脉壁传输而具有弱耦合;以及涉及在每个动脉段的末端处以及在动脉节点和起源于节点处的传入小动脉之间的动脉节点压力的耦合。该模型预测了相邻肾单位对之间的完全同步和弱耦合肾单位之间的部分同步,再现了实验结果。该模型还预测了肾单位中肾小管和动脉压的非周期性波动,其持续时间比TGF振荡更长,再次证实了实验观察结果。该模型不能预测所有肾单位的完全同步。
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