1,721,008 research outputs found
Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis
No full text Pages F160-F173: K. H. Chon, Y.-M. Chen, V. Z. Marmarelis, D. J. Marsh, and N.-H. Holstein-Rathlou. “Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis.” Pages F168-F169: The original Figs. 8-11 do not give sufficient detail of the contour plots. New, higher resolution images are reproduced here with the original legends. </jats:p
Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis
No full text Pages F160–F173: K. H. Chon, Y.-M. Chen, V. Z. Marmarelis, D. J. Marsh, and N.-H. Holstein-Rathlou. “Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis.” Pages F168–F169: The original Figs. 8–11 do not give sufficient detail of the contour plots. New, higher resolution images are reproduced here with the original legends. </jats:p
Rapid redistribution and inhibition of renal sodium transporters during acute pressure natriuresis
No full text Pages F1004–F1014: Y. Zhang, A. K. Mircheff, C. B. Hensley, C. E. Magyar, D. G. Warnock, R. Chambrey, K.-P. Yip, D. J. Marsh, N.-H. Holstein-Rathlou, and A. A. McDonough. “Rapid redistribution and inhibition of renal sodium transporters during acute pressure natriuresis.” The immunoblot panels in Figures 2 and 5–7 were inadvertently printed from low-resolution copies of the original artwork; in addition, the panels in Fig. 6 were incorrectly labeled. The correct figures are reproduced on the following pages. (See PDF) </jats:p
Rapid redistribution and inhibition of renal sodium transporters during acute pressure natriuresis
No full text Pages F1004'F1014: Y. Zhang, A. K. Mircheff, C. B. Hensley, C. E. Magyar, D. G. Warnock, R. Chambrey, K.-P. Yip, D. J. Marsh, N.-H. Holstein-Rathlou, and A. A. McDonough. “Rapid redistribution and inhibition of renal sodium transporters during acute pressure natriuresis.” The immunoblot panels in Figures 2 and 5–7 were inadvertently printed from low-resolution copies of the original artwork; in addition, the panels in Fig. 6 were incorrectly labeled. The correct figures are reproduced on the following pages. (See PDF) </jats:p
A closed-loop analysis of the tubuloglomerular feedback mechanism
No full text The tubuloglomerular feedback (TGF) mechanism is of importance in the regulation of glomerular filtration rate (GFR). A second mechanism of potential importance is the change in proximal pressure caused by a change, for example, in the rate of proximal fluid reabsorption. The quantitative contributions of these two mechanisms to the regulation of GFR and the late proximal flow rate are not known. To determine the regulatory efficiency of these two mechanisms, the late proximal flow rate was perturbed by microperfusion with artificial tubular fluid in halothane-anesthetized Sprague-Dawley rats. The resulting changes in late proximal flow rate were measured by pulse injection of rhodamine dextran. Fluorescence was excited by means of a He-Ne laser. Bolus velocity was measured by videomicroscopy. Tubular pressure was measured by the servonulling method. The microperfusion rate was varied from -15 to 20 nl/min in steps of 5 nl/min. The open-loop gain (OLG) was 3.1 (range 1.5-9.9, n = 13) at the unperturbed tubular flow rate, and decreased as the tubular flow rate was either increased or decreased. The proximal pressure increased by 0.21 +/- 0.03 mmHg per unit increase in late proximal flow rate (nl/min). By use of a mathematical model of the glomerulus, it is estimated that under the present experimental conditions the pressure increase contributes 8% (range 3-15%) of the OLG. It is concluded that, for small perturbations around the operating point, TGF accounts for most of the regulation of GFR and the late proximal flow rate, with changes in the proximal pressure of lesser importance. Furthermore, under closed-loop conditions the operating point for the TGF mechanism is at or close to the point of maximal sensitivity. </jats:p
Oscillations of tubular pressure, flow, and distal chloride concentration in rats
No full text Previous experiments have shown oscillations in proximal tubular pressure in halothane-anesthetized rats. Such oscillations should be due to oscillations in flow rate and should cause periodic oscillations in both distal tubular chloride concentration and distal tubular pressure. The purpose of the study was to test these predictions. In halothane-anesthetized Sprague-Dawley rats, distal tubular chloride activity was measured with Cl- -sensitive electrodes, and late proximal flow rate was measured by pulse injection of boluses of solutions containing rhodamine dextran. Bolus velocity was detected by videomicroscopy. The time resolution was 2 s. All four variables oscillated with the same frequency, approximately 35 mHz. The amplitude of the flow and the chloride oscillations were 28 and 10%, respectively, of the mean values. Proximal fluid velocity led proximal pressure by 1.5 +/- 0.4 s, whereas distal chloride activity lagged proximal pressure by 8.9 +/- 0.8 s. The distal pressure lagged the proximal pressure by 1.05 +/- 0.38 s. It is concluded that there is a significant variation in distal chloride activity, the magnitude of which appears to be sufficient to account for the observed flow variations through the operation of the tubuloglomerular feedback mechanism. </jats:p
Oscillations in the proximal intratubular pressure: a mathematical model
No full text This study presents a dynamic continuous time model of the regulation of the renal proximal intratubular pressure in the rat. The model integrates a functional model of the glomerulus, a tubular model, a feedback model, and an afferent arteriolar model. The model has one equilibrium solution for the dependent variables (equilibrium point) for each set of independent variables. An equilibrium point, chosen to be in accordance with experimental data from Sprague-Dawley rats, was used as the initial value for the dependent variables. The model is shown to have parameter ranges in which sustained stable oscillations in proximal pressure are present. For sustained oscillations to appear, it is necessary for the system's operating point to be located on a sufficiently steep portion of the tubuloglomerular feedback curve. The model analyses are compared with various experimental recordings of the proximal intratubular pressure. The model simulations show both spontaneous and induced oscillations in the proximal pressure in close agreement with the experimental results; but the steady-state mean pressure regulation is found to be less efficient in the model than that apparent from the experimental recordings, suggesting the involvement of additional pressure-regulating mechanisms other than those included in the present model. It is concluded that the dynamic systems approach used in the present study yields new insight into the mechanisms underlying the proximal intratubular pressure oscillations and that it can be of further value for the study of the factors regulating the proximal intratubular pressure. </jats:p
Renal blood flow regulation and arterial pressure fluctuations: a case study in nonlinear dynamics
No full text The arterial blood pressure, a physiological variable on which all renal excretory processes depend, fluctuates over a wide range of amplitudes and frequencies. Much of this variation originates in nonrenal vascular beds to support nonrenal tasks, and the fluctuations provide a noisy environment in which the kidney is obliged to operate. Were it not for renal blood flow autoregulation, it would be difficult to regulate renal excretory processes so as to maintain whole body variables within narrow bounds. Autoregulation is the noise filter on which other renal processes depend for maintaining a relatively noise-free environment in which to work. Because of the time-varying nature of the blood pressure, we have concentrated in this review on the now substantial body of work on the dynamics of renal blood flow regulation and the underlying mechanisms. Renal vascular control mechanisms are not simply reactive but have their own spontaneous dynamics. Both TGF and the myogenic mechanism oscillate autonomously. The TGF oscillation is the better understood of the two. There is an oscillation of tubular pressure, proximal tubular flow, early distal Cl- concentration, and efferent arteriolar blood flow at approximately 35 mHz; all these variables are synchronized when the measurements are made in a single tubule. The autonomous nature of the oscillation is supported by simulations of the nephron and its vasculature, which show that for a reasonable representation of the dynamics of these structures and of the parameters that govern their behavior, the solutions of the equation set are periodic at the frequency of the observed oscillation, and with the same phase relationships among its variables. The simulations also show that the critical variables for the development of the oscillation are the open-loop gain of the feedback system, and the various delays in the system of which convective transport in the axis of the thick ascending limb and signal transmission between the macula densa and the afferent arteriole are the most important. The oscillation in TGF is an example of nonlinear dynamical behavior and is yet another in a long list of oscillations and related dynamics arising in the inherently nonlinear properties of living systems. Some nonlinear systems can bifurcate to states known collectively as deterministic chaos, and TGF is a clear example of such a system. Rats with two different and unrelated forms of experimental hypertension provide tubular pressure records that pass statistical tests for ordered structure and sensitive dependence on initial conditions in the reconstructed state space, two of the hallmarks of deterministic chaos. These records also pass recent more stringent tests for chaos. The significance of deterministic chaos in the context of renal blood flow regulation is that the system regulating blood flow undergoes a physical change to a different dynamical state, and because the change is deterministic, there is every expectation that the critical change will yield itself to experimental discovery.(ABSTRACT TRUNCATED AT 400 WORDS) </jats:p
A dynamic model of the tubuloglomerular feedback mechanism
No full text We have reported oscillations in proximal tubular pressure and flow and in distal tubular pressure and chloride concentration in halothane-anesthetized Sprague-Dawley rats. These variables oscillated at the same frequency in each animal, approximately 35 mHz, but were out of phase with each other. We suggested that the oscillation arises within the tubuloglomerular feedback (TGF) system. As a test of this hypothesis, we have now developed a dynamic model to determine whether it can simulate the measured frequency and phase relationships with a realistic set of parameters. The model includes a detailed representation of pressure and flow in the tubules based on a reduced version of the Navier-Stokes equations. The NaCl concentration at the macula densa was used as the signal to the TGF mechanism. The tubular NaCl concentration was modeled by a partial differential equation based on conservation of mass. For a realistic set of parameter values the model accurately predicted oscillations with the same frequency and phase relationships among the oscillating variables as was found experimentally. Moreover, tubular NaCl handling significantly influenced the dynamic properties of the TGF system. Thus the model predicted a substantial phase shift of the NaCl concentration relative to the flow oscillation at the macula densa. The results are consistent with the hypothesis that the oscillations are caused by the TGF mechanism. The results further support the notion that the delays and damping caused by the tubule are responsible for the limited high-frequency response of renal autoregulation. </jats:p
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