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Symposium Report |
1 Departments of Internal Medicine and Physiology & Biophysics, University of Iowa College of Medicine and, Veterans Administration Medical Center, Iowa City, IA 52242, USA
Abstract
Methods of dynamic analysis are used to provide additional understanding of the renal sympathetic neural control of renal function. The concept of functionally specific subgroups of renal sympathetic nerve fibres conveying information encoded in the frequency domain is presented. Analog pulse modulation and pseudorandom binary sequence stimulation patterns are used for the determination of renal vascular frequency response. Transfer function analysis is used to determine the effects of non-renal vasoconstrictor and vasoconstrictor intensities of renal sympathetic nerve activity on dynamic autoregulation of renal blood flow.
(Received 30 September 2004;
accepted after revision 19 November 2004; first published online 16 December 2004)
Corresponding author G. F. DiBona: Department of Internal Medicine, University of Iowa College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, USA. Email: gerald-dibona{at}uiowa.edu
A wealth of information concerning the important role of renal sympathetic nerve activity (RSNA) in the regulation of renal function has been obtained by a variety of steady-state measurements made in the time domain. However, RSNA, as well as important parameters with which it interacts, arterial pressure (AP) and renal blood flow (RBF), are oscillatory signals with components spanning the frequency range from near 0 to approximately 15–20 Hz. Study of these oscillatory components requires methods of dynamic analysis. It is the purpose of this communication to illustrate how methods of dynamic analysis can be utilized for a greater understanding of the renal sympathetic neural control of renal function.
Graded increases in RSNA regulate the three main renal neuroeffectors, the renin-containing juxtaglomerular granular cells (JGGCs), the tubule and the arterial resistance vasculature (DiBona & Kopp, 1997; Fig. 1). At lower intensities of RSNA, the JGGCs are stimulated to release renin in the absence of changes in tubular transport or renal haemodynamics (glomerular filtration rate, GFR or RBF). At slightly higher intensities, there is a further increase in renin release together with increased tubular sodium reabsorption while GFR and RBF remain unaltered. At even higher intensities, renin release is near maximum, tubular sodium reabsorption is further increased and renal vasoconstriction occurs with decreases in RBF and GFR.
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Regarding the renal sympathetic neural innervation of the three renal neuroeffectors, there is anatomical support for the view that there are separate fibres, each innervating one of the three renal neuroeffectors but not the other two (DiBona, 2000; Fig. 2). This suggests that each nerve fibre carries information that is specific for that renal neuroeffector and its function, i.e. functionally specific groups of renal sympathetic nerve fibres. This view is supported by evidence that the renal sympathetic nerve fibre population is not homogeneous (DiBona et al. 1996). There is a bimodal distribution of fibre diameter, the strength–duration curves for tubular and vascular responses are different and there is a unique subpopulation of fibres which, while silent at rest, are activated by peripheral thermal receptor stimulation but not by conventional baroreceptor or chemoreceptor stimulation.
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On comparing the power spectrum of RSNA with that of RBF, it is evident that there is less power in the RBF spectrum than in the RSNA spectrum. The renal vasculature has been considered to function as a low-pass filter, allowing oscillations at lower frequencies to pass while restricting or filtering out oscillations at higher frequencies. Using a renal nerve stimulation pattern based on analog pulse modulation in which an information-bearing message signal is superimposed on (i.e. multiplied by) a carrier signal for transmission, the ability of the renal vasculature to respond to a range of message signal frequencies (i.e. the renal vascular frequency response) was evaluated (DiBona & Sawin, 2002). When the carrier signal frequency was of non-renal vasoconstrictor intensity (1 Hz), there were no renal blood flow oscillations coherent with the message signal frequency (0.02–0.6 Hz) indicating that the renal vasculature was unresponsive. Thus, the presence of low-frequency oscillations in the RBF power spectrum does not necessarily indicate the presence of renal vasoconstriction, i.e. a decrease in volumetric RBF. However, when the carrier signal frequency was of renal vasoconstrictor intensity (5 Hz), there were renal blood flow oscillations coherent with the message signal frequencies indicating that the renal vasculature was responsive (Fig. 3). As the message signal frequency was progressively increased, it was observed that the amplitude of the oscillations in RBF was progressively attenuated by the low-pass filter function of the renal vasculature up to a frequency of 0.4 Hz beyond which oscillations were not discernible. While it was previously postulated that these low-frequency oscillations (
0.4 Hz) in the RBF signal contributed to an increase in the responsiveness of the renal vasculature to stimuli, this was not found to be the case as the renal vasoconstrictor responses to both noradrenaline (norepinephrine) and angiotensin II were unaffected.
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Autoregulation of renal blood flow
Dynamic analysis methods have provided further insight into the effects of alterations in RSNA on autoregulation of RBF. Traditionally, autoregulation has been examined using steady-state methods wherein renal artery pressure has been altered in fixed steps and the resultant steady-state values of RBF taken. Using the steady-state stepwise approach, it has been shown that non-renal vasoconstrictor intensities of renal nerve stimulation have no effect on autoregulation of RBF. When renal vasoconstrictor intensities of renal nerve stimulation are used, RBF autoregulation is impaired as seen by an upward shift of the lowest autoregulatory pressure threshold. Dynamic autoregulation of RBF examines the transfer function from the input AP signal into the RBF signal in the frequency domain. The transfer function gain describes the extent to which oscillations in the AP signal appear (‘transferred into’) in the RBF signal. A well-autoregulating kidney will attenuate the extent to which oscillations in the AP signal appear in the RBF signal and have a gain value < 1 while a poorly autoregulating kidney will have a gain value of 1 (no attenuation) or greater (amplification). The dynamic analysis of RBF autoregulation discloses the two major mechanisms involved – the slower tubuloglomerular feedback mechanism operating at 0.03–0.06 Hz (cycle length, 16–33 s) and the faster myogenic mechanism operating at 0.1–0.2 Hz (cycle length, 5–10 s). The effect of RSNA on dynamic autoregulation of RBF was studied by making measurements before and after renal denervation (DiBona & Sawin, 2004a). Studies were made in control and Wistar-Kyoto (WKY) rats where renal denervation did not affect RBF (non-renal vasoconstrictor RSNA) and in CHF rats and spontaneously hypertensive rats (SHRs) where renal denervation increased RBF (renal vasoconstrictor RSNA). Renal denervation had no effect on dynamic autoregulation of RBF in control or WKY rats. In both CHF rats and SHRs, dynamic autoregulation of RBF was improved following renal denervation. In CHF rats, improvement was noted in the tubuloglomerular feedback component while in SHRs, improvement was noted in both the tubuloglomerular feedback and myogenic components. It is important to note that identifying specific effects of renal denervation on the two individual components of RBF autoregulation, while not possible with the traditional steady-state stepwise method, is facilitated using the methods of dynamic analysis.
References
DiBona
GF (2000). Neural control of the kidney: functionally specific renal sympathetic nerve fibers. Am J Physiol Regul Integr Comp Physiol
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DiBona
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&
Kopp
UC (1997). Neural control of renal function. Physiol Rev
77, 75–197.
DiBona GF & Sawin LL (1999). Renal hemodynamic effects of activation of renal sympathetic nerve fiber groups. Am J Physiol 276, R539–R549.
DiBona
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&
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LL (2002). Effect of renal nerve stimulation on responsiveness of the rat renal vasculature. Am J Physiol Renal Physiol
283, F1056–F1065.
DiBona
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LL (2003a). Frequency response of the renal vasculature in congestive heart failure. Circulation
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DiBona
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LL (2003b). Losartan corrects abnormal frequency response of renal vasculature in congestive heart failure. Am J Physiol Heart Circ Physiol
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DiBona
GF
&
Sawin
LL (2004a). Effect of renal denervation on dynamic autoregulation of renal blood flow. Am J Physiol Renal Physiol
286, F1209–F1218.
DiBona
GF
&
Sawin
LL (2004b). Effect of endogenous angiotensin II on the frequency response of the renal vasculature. Am J Physiol Renal Physiol
287, F1171–F1178.
DiBona GF, Sawin LL & Jones SY (1996). Differentiated sympathetic neural control of the kidney. Am J Physiol 271, R84–R90.
Acknowledgements
This work was supported by National Institutes of Health grants DK-15843 and HL-55006, by a Department of Veterans Affairs Merit Review Award and by grants from the Wenner-Gren Foundations, Stockholm, Sweden and the Adlerbertska forskningsstiftelsen, The Royal Society of Arts and Sciences in Göteborg, Sweden.
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