Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions

Research output: Contribution to journal › Conference abstract in journal › Research › peer-review

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Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions. / Postnov, Dmitry; von Holstein-Rathlou, Niels-Henrik; Sosnovtseva, Olga; Postnov, Dmitry; Wexler, Anthony; Rowland, Douglas; Marsh, Donald.

In: F A S E B Journal, Vol. 29, No. 1 Supplement, 808.10, 04.2015.

Research output: Contribution to journal › Conference abstract in journal › Research › peer-review

Harvard

Postnov, D, von Holstein-Rathlou, N-H, Sosnovtseva, O, Postnov, D, Wexler, A, Rowland, D & Marsh, D 2015, 'Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions', F A S E B Journal, vol. 29, no. 1 Supplement, 808.10. <http://www.fasebj.org/content/29/1_Supplement/808.10.abstract>

APA

Postnov, D., von Holstein-Rathlou, N-H., Sosnovtseva, O., Postnov, D., Wexler, A., Rowland, D., & Marsh, D. (2015). Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions. F A S E B Journal, 29(1 Supplement), [808.10]. http://www.fasebj.org/content/29/1_Supplement/808.10.abstract

Vancouver

Postnov D, von Holstein-Rathlou N-H, Sosnovtseva O, Postnov D, Wexler A, Rowland D et al. Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions. F A S E B Journal. 2015 Apr;29(1 Supplement). 808.10.

Author

Postnov, Dmitry ; von Holstein-Rathlou, Niels-Henrik ; Sosnovtseva, Olga ; Postnov, Dmitry ; Wexler, Anthony ; Rowland, Douglas ; Marsh, Donald. / Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions. In: F A S E B Journal. 2015 ; Vol. 29, No. 1 Supplement.

Bibtex

@article{56e35efa71854f0a9e8cc2e4e3f79362,
title = "Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions",
abstract = "Our goal is to predict interactions that develop among nephrons and between nephrons and the arterial network that supports them. We have developed a computationally simple but physiologically-based mathematical model of the kidney vascular tree to study renal autoregulation in ensembles of interacting nephrons not directly available for experimentation. The study combines computed tomography (CT) of a renal vascular cast at 2 micrometer resolution with simulation. The CT scan showed a bifurcating branching structure with as many as 7 bifurcations between arcuate arteries and the renal surface, with afferent arterioles originating from all arterial structures, including arcuate arteries. The modeling component has 2 novel features: a probability based vascular tree based on the data from the CT images, and a network of arteries supplying several simple whole nephron models coupled electrotonically. The network model predicts dynamical aspects of vascular pressure drops and nephron self-sustained cooperative dynamics. ",
author = "Dmitry Postnov and {von Holstein-Rathlou}, Niels-Henrik and Olga Sosnovtseva and Dmitry Postnov and Anthony Wexler and Douglas Rowland and Donald Marsh",
year = "2015",
month = apr,
language = "English",
volume = "29",
journal = "F A S E B Journal",
issn = "0892-6638",
publisher = "Federation of American Societies for Experimental Biology",
number = "1 Supplement",

}

RIS

TY - ABST

T1 - Renal Arterial Network Structure by Computed Tomography, and Nephron-Arterial Interactions

AU - Postnov, Dmitry

AU - von Holstein-Rathlou, Niels-Henrik

AU - Sosnovtseva, Olga

AU - Postnov, Dmitry

AU - Wexler, Anthony

AU - Rowland, Douglas

AU - Marsh, Donald

PY - 2015/4

Y1 - 2015/4

N2 - Our goal is to predict interactions that develop among nephrons and between nephrons and the arterial network that supports them. We have developed a computationally simple but physiologically-based mathematical model of the kidney vascular tree to study renal autoregulation in ensembles of interacting nephrons not directly available for experimentation. The study combines computed tomography (CT) of a renal vascular cast at 2 micrometer resolution with simulation. The CT scan showed a bifurcating branching structure with as many as 7 bifurcations between arcuate arteries and the renal surface, with afferent arterioles originating from all arterial structures, including arcuate arteries. The modeling component has 2 novel features: a probability based vascular tree based on the data from the CT images, and a network of arteries supplying several simple whole nephron models coupled electrotonically. The network model predicts dynamical aspects of vascular pressure drops and nephron self-sustained cooperative dynamics.

AB - Our goal is to predict interactions that develop among nephrons and between nephrons and the arterial network that supports them. We have developed a computationally simple but physiologically-based mathematical model of the kidney vascular tree to study renal autoregulation in ensembles of interacting nephrons not directly available for experimentation. The study combines computed tomography (CT) of a renal vascular cast at 2 micrometer resolution with simulation. The CT scan showed a bifurcating branching structure with as many as 7 bifurcations between arcuate arteries and the renal surface, with afferent arterioles originating from all arterial structures, including arcuate arteries. The modeling component has 2 novel features: a probability based vascular tree based on the data from the CT images, and a network of arteries supplying several simple whole nephron models coupled electrotonically. The network model predicts dynamical aspects of vascular pressure drops and nephron self-sustained cooperative dynamics.

M3 - Conference abstract in journal

VL - 29

JO - F A S E B Journal

JF - F A S E B Journal

SN - 0892-6638

IS - 1 Supplement

M1 - 808.10

ER -

ID: 162217765