Title :
Nonlinear system analysis of renal autoregulation in normotensive and hypertensive rats
Author :
Chon, Ki H. ; Chen, Yu-Ming ; Holstein-Rathlou, N.-H. ; Marmarelis, Vasilis Z.
Author_Institution :
Harvard-MIT Div. of Health Sci. & Technol., Cambridge, MA, USA
fDate :
3/1/1998 12:00:00 AM
Abstract :
The authors compared the dynamic characteristics in renal autoregulation of blood flow of normotensive Sprague-Dawley rats (SDR) and spontaneously hypertensive rats (SHR), using both linear and nonlinear systems analysis. Linear analysis yielded only limited information about the differences in dynamics between SDR and SHR. The predictive ability, as determined by normalized mean-square errors (NMSE), of a third-order Volterra model is better than for a linear model. This decrease in NMSE with a third-order model from that of a linear model is especially evident at frequencies below 0.2 Hz. Furthermore, NMSE are significantly higher in SHR than SDR, suggesting a more complex nonlinear system in SHR. The contribution of the third-order kernel in describing the dynamics of renal autoregulation in arterial blood pressure and blood flow was found to be important. Moreover, the authors have identified the presence of nonlinear interactions between the oscillatory components of the myogenic mechanism and tubuloglomerular feedback (TGF) at the level of whole kidney blood flow in SDR. An interaction between these two mechanisms had previously been revealed for SDR only at the single nephron level. However, nonlinear interactions between the myogenic and TGF mechanisms are not detected for SHR.
Keywords :
biocontrol; flow control; haemodynamics; kidney; nonlinear control systems; physiological models; 0.2 Hz; arterial blood pressure; hypertensive rats; linear systems analysis; myogenic mechanism; nonlinear interactions; nonlinear system analysis; nonlinear systems analysis; normalized mean-square errors; normotensive rats; renal blood flow autoregulation; single nephron level; third-order Volterra model; tubuloglomerular feedback; Arterial blood pressure; Blood flow; Frequency; Hypertension; Information analysis; Kernel; Nonlinear dynamical systems; Nonlinear systems; Predictive models; Rats; Animals; Blood Pressure; Homeostasis; Hypertension; Linear Models; Male; Models, Biological; Nonlinear Dynamics; Rats; Rats, Inbred SHR; Rats, Sprague-Dawley; Reference Values; Renal Circulation;
Journal_Title :
Biomedical Engineering, IEEE Transactions on