Literature DB >> 19205808

Multistable dynamics mediated by tubuloglomerular feedback in a model of coupled nephrons.

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

Abstract

To help elucidate the causes of irregular tubular flow oscillations found in the nephrons of spontaneously hypertensive rats (SHR), we have conducted a bifurcation analysis of a mathematical model of two nephrons that are coupled through their tubuloglomerular feedback (TGF) systems. This analysis was motivated by a previous modeling study which predicts that NaCl backleak from a nephron's thick ascending limb permits multiple stable oscillatory states that are mediated by TGF (Layton et al. in Am. J. Physiol. Renal Physiol. 291:F79-F97, 2006); that prediction served as the basis for a comprehensive, multifaceted hypothesis for the emergence of irregular flow oscillations in SHR. However, in that study, we used a characteristic equation obtained via linearization from a single-nephron model, in conjunction with numerical solutions of the full, nonlinear model equations for two and three coupled nephrons. In the present study, we have derived a characteristic equation for a model of any finite number of mutually coupled nephrons having NaCl backleak. Analysis of that characteristic equation for the case of two coupled nephrons has revealed a number of parameter regions having the potential for differing stable dynamic states. Numerical solutions of the full equations for two model nephrons exhibit a variety of behaviors in these regions. Some behaviors exhibit a degree of complexity that is consistent with our hypothesis for the emergence of irregular oscillations in SHR.

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Year:  2009        PMID: 19205808     DOI: 10.1007/s11538-008-9370-x

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  14 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.  Understanding sex differences in long-term blood pressure regulation: insights from experimental studies and computational modeling.

Authors:  Sameed Ahmed; Rui Hu; Jessica Leete; Anita T Layton
Journal:  Am J Physiol Heart Circ Physiol       Date:  2019-03-15       Impact factor: 4.733

6.  Architecture of the rat nephron-arterial network: analysis with micro-computed tomography.

Authors:  Donald J Marsh; Dmitry D Postnov; Douglas J Rowland; Anthony S Wexler; Olga V Sosnovtseva; Niels-Henrik Holstein-Rathlou
Journal:  Am J Physiol Renal Physiol       Date:  2017-04-19

7.  Functional implications of sexual dimorphism of transporter patterns along the rat proximal tubule: modeling and analysis.

Authors:  Qianyi Li; Alicia A McDonough; Harold E Layton; Anita T Layton
Journal:  Am J Physiol Renal Physiol       Date:  2018-05-30

8.  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

Review 9.  Mathematical modeling of kidney transport.

Authors:  Anita T Layton
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-07-12

10.  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

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