Renal autoregulation is the, process that minimizes the effect of blood pressure variations on renal blood flow fluctuations. Two separate but interacting control mechanisms autoregulate renal blood flow: the myogenic mechanism and tubuloglomerular feedback (TGF). TGF is an intrarenal control system found in each nepbron, and the myogenic response is a mechanism intrinsic to the vascular wall of the blood vessel. Highly regular blood pressure fluctuations in the kidney tubules in normotensive rats are replaced by highly irregular pressure fluctuations in hypertensive rats. The pressure fluctuation differences between the two strains of rats may be an indication of different autoregulatory dynamics. The primary goal of the proposed work is to unravel the underlying reasons for the changes in autoregulatory mechanics. The chief complication we must overcome, however, is the coupling between the autoregulatory mechanisms themselves.
Specific Aim (1) of the project is to test the hypothesis that the dynamic characteristics of interactions between TGF and the myogenic mechanism are modulated by blood pressure and that chronic high blood pressure further affects the interaction. IN addition to these intra-nephron interactions between TOP and the myogenic mechanism, nephrons derived from the same radial cortical artery interact through the arteriolar wall. Oscillations in vascularly-connected nepbrons are entrained in normotensive rats, but the entrainment is less complete in hypertensive rats. The static connection strength is stronger in hypertension, and the reduced entrainment is probably due to loss of signal coherence caused by the bifurcation to chaos. These observations suggest that these nephron-nephron interactions are affected by hypertension. Thus, in Specific Aim (2) we propose to measure the pressure dependence of the intra- and inter-nephron interactions, and use mathematical simulation to test the importance of these interactions to the dynamics of renal blood flow regulation.
In Specific Aim (3) we propose to evaluate possible time-varying characteristics of autoregulation of single and whole kidney blood flow. With valuable information gathered from the first three specific aims, in Specific Aim (4) we propose to develop and test a block-structured mathematical model that will be able to emulate the observed functional behavior of the renal autoregulatory mechanisms under both normotensive and hypertensive conditions. By exercising this model, as described under Specific Aim (5), we plan to begin understanding the underlying reasons for the changes observed in autoregulation under pathological conditions.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL069629-03
Application #
6666913
Study Section
Cardiovascular and Renal Study Section (CVB)
Program Officer
Barouch, Winifred
Project Start
2001-08-21
Project End
2006-07-31
Budget Start
2003-08-01
Budget End
2004-07-31
Support Year
3
Fiscal Year
2003
Total Cost
$231,073
Indirect Cost
Name
State University New York Stony Brook
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
804878247
City
Stony Brook
State
NY
Country
United States
Zip Code
11794
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Feng, Lei; Ju, Kihwan; Chon, Ki H (2005) A method for segmentation of switching dynamic modes in time series. IEEE Trans Syst Man Cybern B Cybern 35:1058-64

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