A dynamic model of renal blood flow autoregulation

Bull Math Biol. 1994 May;56(3):411-29. doi: 10.1007/BF02460465.

Abstract

To test whether a mathematical model combining dynamic models of the tubuloglomerular feedback (TGF) mechanism and the myogenic mechanism was sufficient to explain dynamic autoregulation of renal blood flow, we compared model simulations with experimental data. To assess the dynamic characteristics of renal autoregulation, a broad band perturbation of the arterial pressure was employed in both the simulations and the experiments. Renal blood flow and tubular pressure were used as response variables in the comparison. To better approximate the situation in vivo where a large number of individual nephrons act in parallel, each simulation was performed with 125 parallel versions of the model. The key parameters of the 125 versions of the model were chosen randomly within the physiological range. None of the constituent models, i.e., the TGF and the myogenic, could alone reproduce the experimental observations. However, in combination they reproduced most of hte features of the various transfer functions calculated from the experimental data. The major discrepancy was the presence of a bimodal distribution of the admittance phase in the simulations. This is not consistent with most of the experimental data, which shows a unimodal curve for the admittance phase. The ability of the model to reproduce the experimental data supports the hypothesis that dynamic autoregulation of renal blood flow is due to the combined action of TGF and the myogenic response.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Animals
  • Arterioles / physiology
  • Blood Pressure
  • Computer Simulation
  • Feedback
  • Kidney Glomerulus / physiology
  • Kidney Tubules / physiology
  • Models, Biological*
  • Muscle, Smooth, Vascular / physiology
  • Rats
  • Renal Circulation*
  • Vascular Resistance
  • Vasomotor System / physiology