2008
DOI: 10.1152/ajpregu.00582.2007
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Analysis of nonstationarity in renal autoregulation mechanisms using time-varying transfer and coherence functions

Abstract: Chon KH, Zhong Y, Moore LC, Holstein-Rathlou NH, Cupples WA. Analysis of nonstationarity in renal autoregulation mechanisms using time-varying transfer and coherence functions. Am J Physiol Regul Integr Comp Physiol 295: R821-R828, 2008. First published May 21, 2008 doi:10.1152/ajpregu.00582.2007.-The extent to which renal blood flow dynamics vary in time and whether such variation contributes substantively to dynamic complexity have emerged as important questions. Data from Sprague-Dawley rats (SDR) and spo… Show more

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Cited by 19 publications
(12 citation statements)
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“…There is precedent for time-varying renal autoregulatory mechanisms being detected at the whole kidney level and for these properties to differ between hypertensive and normotensive rat strains (4,31). It is possible that our findings of increased TGF variability are the result of this and that we caught different nephrons at different phases of their cycle.…”
Section: Stn and Diminished Net Tgf Responsementioning
confidence: 82%
“…There is precedent for time-varying renal autoregulatory mechanisms being detected at the whole kidney level and for these properties to differ between hypertensive and normotensive rat strains (4,31). It is possible that our findings of increased TGF variability are the result of this and that we caught different nephrons at different phases of their cycle.…”
Section: Stn and Diminished Net Tgf Responsementioning
confidence: 82%
“…6, row B. It has previously been shown that the renal autoregulation dynamics are highly time varying [23], and the time variance for the two signals can be visualized in the time-frequency representations, generated by Variable Frequency Complex Demodulation [26], in Fig. 7(c) and (d).…”
Section: Identified Clustersmentioning
confidence: 89%
“…15 Hz. It might be expected that signals sharing the same frequency are synchronized, but this is not guaranteed since renal autoregulation dynamics are highly time varying and instantaneous phase changes may be uncorrelated between the two signals [23], [24]. For this reason, we estimate the PC by evaluating the temporal variations in the phase difference between the two signals using PC and compare to a significance test.…”
Section: Identification Of Synchronized Clustersmentioning
confidence: 99%
“…There is also the question of how multiple lobules achieve TGF synchronization since juxtamedullary nephrons have lower TGF frequencies (20) that could desynchronize neighboring lobules. Given that the frequency of TGF is labile (12,53) (Fig. 1), that transit time through the loop of Henle can vary (43,45), and that synchronization is clearly plastic, it is possible that there is m:n synchronization of TGF between juxtamedullary nephrons and the short-looped nephrons in several m:n (e.g., 2:3) frequency ratios.…”
Section: Discussionmentioning
confidence: 99%