Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network

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Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network. / Postnov, Dmitry D; Marsh, Donald J; Postnov, Dmitry E; Braunstein, Thomas Hartig; von Holstein-Rathlou, Niels-Henrik; Martens, Erik A; Sosnovtseva, Olga.

I: PLoS Computational Biology, Bind 12, Nr. 7, e1004922, 07.2016.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Postnov, DD, Marsh, DJ, Postnov, DE, Braunstein, TH, von Holstein-Rathlou, N-H, Martens, EA & Sosnovtseva, O 2016, 'Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network', PLoS Computational Biology, bind 12, nr. 7, e1004922. https://doi.org/10.1371/journal.pcbi.1004922

APA

Postnov, D. D., Marsh, D. J., Postnov, D. E., Braunstein, T. H., von Holstein-Rathlou, N-H., Martens, E. A., & Sosnovtseva, O. (2016). Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network. PLoS Computational Biology, 12(7), [e1004922]. https://doi.org/10.1371/journal.pcbi.1004922

Vancouver

Postnov DD, Marsh DJ, Postnov DE, Braunstein TH, von Holstein-Rathlou N-H, Martens EA o.a. Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network. PLoS Computational Biology. 2016 jul.;12(7). e1004922. https://doi.org/10.1371/journal.pcbi.1004922

Author

Postnov, Dmitry D ; Marsh, Donald J ; Postnov, Dmitry E ; Braunstein, Thomas Hartig ; von Holstein-Rathlou, Niels-Henrik ; Martens, Erik A ; Sosnovtseva, Olga. / Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network. I: PLoS Computational Biology. 2016 ; Bind 12, Nr. 7.

Bibtex

@article{a97087ee0b124d309bbd1dd66229ffa6,
title = "Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network",
abstract = "Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (μCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.",
author = "Postnov, {Dmitry D} and Marsh, {Donald J} and Postnov, {Dmitry E} and Braunstein, {Thomas Hartig} and {von Holstein-Rathlou}, Niels-Henrik and Martens, {Erik A} and Olga Sosnovtseva",
year = "2016",
month = jul,
doi = "10.1371/journal.pcbi.1004922",
language = "English",
volume = "12",
journal = "P L o S Computational Biology (Online)",
issn = "1553-734X",
publisher = "Public Library of Science",
number = "7",

}

RIS

TY - JOUR

T1 - Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network

AU - Postnov, Dmitry D

AU - Marsh, Donald J

AU - Postnov, Dmitry E

AU - Braunstein, Thomas Hartig

AU - von Holstein-Rathlou, Niels-Henrik

AU - Martens, Erik A

AU - Sosnovtseva, Olga

PY - 2016/7

Y1 - 2016/7

N2 - Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (μCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.

AB - Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (μCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.

U2 - 10.1371/journal.pcbi.1004922

DO - 10.1371/journal.pcbi.1004922

M3 - Journal article

C2 - 27447287

VL - 12

JO - P L o S Computational Biology (Online)

JF - P L o S Computational Biology (Online)

SN - 1553-734X

IS - 7

M1 - e1004922

ER -

ID: 164154732