Literature DB >> 16204416

Multistability in tubuloglomerular feedback and spectral complexity in spontaneously hypertensive rats.

Anita T Layton1, Leon C Moore, Harold E Layton.   

Abstract

Single-nephron proximal tubule pressure in spontaneously hypertensive rats (SHR) can exhibit highly irregular oscillations similar to deterministic chaos. We used a mathematical model of tubuloglomerular feedback (TGF) to investigate potential sources of the irregular oscillations and the corresponding complex power spectra in SHR. A bifurcation analysis of the TGF model equations, for nonzero thick ascending limb (TAL) NaCl permeability, was performed by finding roots of the characteristic equation, and numerical simulations of model solutions were conducted to assist in the interpretation of the analysis. These techniques revealed four parameter regions, consistent with TGF gain and delays in SHR, where multiple stable model solutions are possible: 1) a region having one stable, time-independent steady-state solution; 2) a region having one stable oscillatory solution only, of frequency f1; 3) a region having one stable oscillatory solution only, of frequency f2, which is approximately equal to 2f1; and 4) a region having two possible stable oscillatory solutions, of frequencies f1 and f2. In addition, we conducted simulations in which TAL volume was assumed to vary as a function of time and simulations in which two or three nephrons were assumed to have coupled TGF systems. Four potential sources of spectral complexity in SHR were identified: 1) bifurcations that permit switching between different stable oscillatory modes, leading to multiple spectral peaks and their respective harmonic peaks; 2) sustained lability in delay parameters, leading to broadening of peaks and of their harmonics; 3) episodic, but abrupt, lability in delay parameters, leading to multiple peaks and their harmonics; and 4) coupling of small numbers of nephrons, leading to multiple peaks and their harmonics. We conclude that the TGF system in SHR may exhibit multistability and that the complex power spectra of the irregular TGF fluctuations in this strain may be explained by switching between multiple dynamic modes, temporal variation in TGF parameters, and nephron coupling.

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Year:  2005        PMID: 16204416     DOI: 10.1152/ajprenal.00048.2005

Source DB:  PubMed          Journal:  Am J Physiol Renal Physiol        ISSN: 1522-1466


  16 in total

1.  Signal transduction in a compliant thick ascending limb.

Authors:  Anita T Layton; Leon C Moore; Harold E Layton
Journal:  Am J Physiol Renal Physiol       Date:  2012-01-18

Review 2.  Modeling transport in the kidney: investigating function and dysfunction.

Authors:  Aurélie Edwards
Journal:  Am J Physiol Renal Physiol       Date:  2009-11-04

3.  Coupling-induced complexity in nephron models of renal blood flow regulation.

Authors:  Jakob L Laugesen; Olga V Sosnovtseva; Erik Mosekilde; Niels-Henrik Holstein-Rathlou; Donald J Marsh
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2010-02-10       Impact factor: 3.619

4.  Conduction of feedback-mediated signal in a computational model of coupled nephrons.

Authors:  Ioannis Sgouralis; Anita T Layton
Journal:  Math Med Biol       Date:  2015-03-19       Impact factor: 1.854

5.  Bifurcation study of blood flow control in the kidney.

Authors:  Ashlee N Ford Versypt; Elizabeth Makrides; Julia C Arciero; Laura Ellwein; Anita T Layton
Journal:  Math Biosci       Date:  2015-03-05       Impact factor: 2.144

6.  Mathematical modeling of renal hemodynamics in physiology and pathophysiology.

Authors:  Ioannis Sgouralis; Anita T Layton
Journal:  Math Biosci       Date:  2015-03-09       Impact factor: 2.144

Review 7.  Theoretical models for regulation of blood flow.

Authors:  Timothy W Secomb
Journal:  Microcirculation       Date:  2008-11       Impact factor: 2.628

8.  Tubular fluid flow and distal NaCl delivery mediated by tubuloglomerular feedback in the rat kidney.

Authors:  Hwayeon Ryu; Anita T Layton
Journal:  J Math Biol       Date:  2013-03-26       Impact factor: 2.259

9.  Modeling the effects of positive and negative feedback in kidney blood flow control.

Authors:  Runjing Liu; Anita T Layton
Journal:  Math Biosci       Date:  2016-03-10       Impact factor: 2.144

10.  Analysis of nonstationarity in renal autoregulation mechanisms using time-varying transfer and coherence functions.

Authors:  Ki H Chon; Yuru Zhong; Leon C Moore; Niels H Holstein-Rathlou; William A Cupples
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2008-05-21       Impact factor: 3.619

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