Literature DB >> 8468079

On the efficacy of linear system analysis of renal autoregulation in rats.

K H Chon1, Y M Chen, N H Holstein-Rathlou, D J Marsh, V Z Marmarelis.   

Abstract

In order to assess the linearity of the mechanisms subserving renal blood flow autoregulation, broad-band arterial pressure fluctuations at three different power levels were induced experimentally and the resulting renal blood flow responses were recorded. Linear system analysis methods were applied in both the time and frequency domain. In the frequency domain, spectral estimates employing FFT, autoregressive moving average (ARMA) and moving average (MA) methods were used; only the MA model showed two vascular control mechanisms active at 0.02-0.05 Hz and 0.1-0.18 Hz consistent with previous experimental findings [Holstein-Rathlou et al., Amer. J. Physiol., vol. 258, 1990.]. In the time domain, impulse response functions obtained from the MA model indicated likewise the presence of these two vascular control mechanisms, but the ARMA model failed to show any vascular control mechanism at 0.02-0.05 Hz. The residuals (i.e., model prediction errors) of the MA model were smaller than the ARMA model for all levels of arterial pressure forcings. The observed low coherence values and the significant model residuals in the 0.02-0.05 Hz frequency range suggest that the tubuloglomerular feedback (TGF) active in this frequency range is a nonlinear vascular control mechanism. In addition, experimental results suggest that the operation of the TGF mechanism is more evident at low/moderate pressure fluctuations and becomes overwhelmed when the arterial pressure forcing is too high.

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Year:  1993        PMID: 8468079     DOI: 10.1109/10.204766

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Renal blood flow and dynamic autoregulation in conscious mice.

Authors:  Radu Iliescu; Radu Cazan; Gerald R McLemore; Marcia Venegas-Pont; Michael J Ryan
Journal:  Am J Physiol Renal Physiol       Date:  2008-06-25

2.  Nonlinear analysis of renal autoregulation under broadband forcing conditions.

Authors:  V Z Marmarelis; K H Chon; Y M Chen; D J Marsh; N H Holstein-Rathlou
Journal:  Ann Biomed Eng       Date:  1993 Nov-Dec       Impact factor: 3.934

Review 3.  Renal autoregulation: new perspectives regarding the protective and regulatory roles of the underlying mechanisms.

Authors:  Rodger Loutzenhiser; Karen Griffin; Geoffrey Williamson; Anil Bidani
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2006-05       Impact factor: 3.619

4.  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

5.  Synchronization in renal microcirculation unveiled with high-resolution blood flow imaging.

Authors:  Dmitry Postnov; Donald J Marsh; Will A Cupples; Niels-Henrik Holstein-Rathlou; Olga Sosnovtseva
Journal:  Elife       Date:  2022-05-06       Impact factor: 8.713

Review 6.  Molecular mechanisms of renal blood flow autoregulation.

Authors:  Marilyn Burke; Mallikarjuna R Pabbidi; Jerry Farley; Richard J Roman
Journal:  Curr Vasc Pharmacol       Date:  2014       Impact factor: 2.719

  6 in total

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