Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis.
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Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis. / Chon, K H; Chen, Y M; Marmarelis, V Z; Marsh, D J; Holstein-Rathlou, N H.
In: American Journal of Physiology (Consolidated), Vol. 267, No. 1 Pt 2, 1994, p. F160-73.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis.
AU - Chon, K H
AU - Chen, Y M
AU - Marmarelis, V Z
AU - Marsh, D J
AU - Holstein-Rathlou, N H
N1 - Keywords: Animals; Blood Pressure; Feedback; Hypertension; Kidney Glomerulus; Kidney Tubules; Male; Muscle, Smooth, Vascular; Nonlinear Dynamics; Rats; Rats, Inbred SHR; Rats, Sprague-Dawley; Reference Values; Renal Circulation
PY - 1994
Y1 - 1994
N2 - Previous studies using linear techniques have provided valuable insights into the dynamic characteristics of whole kidney autoregulation and have led to the general conclusion that the myogenic mechanism and tubuloglomerular feedback (TGF) are highly nonlinear control mechanisms. To explore further the dynamic nature of these nonlinear autoregulatory mechanisms, we introduce the technique of nonlinear modeling using Volterra-Wiener kernels. In the past several years, use of Volterra-Wiener kernels for nonlinear approximation has been most notably applied to neurophysiology. Recent advances in algorithms for computation of the kernels have made this technique more attractive for the study of the dynamics of nonlinear physiological systems, such as the system mediating renal autoregulation. In this study, the general theory and requirements for using this technique are discussed. The feasibility of using the technique on whole kidney pressure and flow data is examined, and a basis for using the Volterra-Wiener kernels to detect interactions between physiological control mechanisms is established. As a result of this method, we have identified the presence of interactions between the oscillating components of the myogenic and the TGF mechanisms at the level of the whole kidney blood flow in normotensive rats. An interaction between these oscillatory components had previously been demonstrated only at the single-nephron level.
AB - Previous studies using linear techniques have provided valuable insights into the dynamic characteristics of whole kidney autoregulation and have led to the general conclusion that the myogenic mechanism and tubuloglomerular feedback (TGF) are highly nonlinear control mechanisms. To explore further the dynamic nature of these nonlinear autoregulatory mechanisms, we introduce the technique of nonlinear modeling using Volterra-Wiener kernels. In the past several years, use of Volterra-Wiener kernels for nonlinear approximation has been most notably applied to neurophysiology. Recent advances in algorithms for computation of the kernels have made this technique more attractive for the study of the dynamics of nonlinear physiological systems, such as the system mediating renal autoregulation. In this study, the general theory and requirements for using this technique are discussed. The feasibility of using the technique on whole kidney pressure and flow data is examined, and a basis for using the Volterra-Wiener kernels to detect interactions between physiological control mechanisms is established. As a result of this method, we have identified the presence of interactions between the oscillating components of the myogenic and the TGF mechanisms at the level of the whole kidney blood flow in normotensive rats. An interaction between these oscillatory components had previously been demonstrated only at the single-nephron level.
M3 - Journal article
C2 - 8048557
VL - 267
SP - F160-73
JO - American Journal of Physiology - Cell Physiology
JF - American Journal of Physiology - Cell Physiology
SN - 0363-6143
IS - 1 Pt 2
ER -
ID: 8439752