A visualization-based analysis method for multiparameter models of capillary tissue-exchange

A theoretical model of nitric oxide transport in arterioles: frequency- vs. amplitude-dependent control of cGMP formation

Nitric oxide (NO) plays many important physiological roles, including the regulation of vascular smooth muscle tone. In response to hemodynamic or agonist stimuli, endothelial cells produce NO, which can diffuse to smooth muscle where it activates soluble guanylate cyclase (sGC), leading to cGMP formation and smooth muscle relaxation. The close proximity of red blood cells suggests, however, that a significant amount of NO released will be scavenged by blood, and thus the issue of bioavailability of endothelium-derived NO to smooth muscle has been investigated experimentally and theoretically. We formulated a mathematical model for NO transport in an arteriole to test the hypothesis that transient, burst-like NO production can facilitate efficient NO delivery to smooth muscle and reduce NO scavenging by blood. The model simulations predict that 1) the endothelium can maintain a physiologically significant amount of NO in smooth muscle despite the presence of NO scavengers such as hemoglobin and myoglobin; 2) under certain conditions, transient NO release presents a more efficient way for activating sGC and it can increase cGMP formation severalfold; and 3) frequency-rather than amplitude-dependent control of cGMP formation is possible. This suggests that it is the frequency of NO bursts and perhaps the frequency of Ca(2+) oscillations in endothelial cells that may limit cGMP formation and regulate vascular tone. The proposed hypothesis suggests a new functional role for Ca(2+) oscillations in endothelial cells. Further experimentation is needed to test whether and under what conditions in silico predictions occur in vivo.

Transient transcapillary exchange of water driven by osmotic forces in the heart

Osmotic transient responses in organ weight after changes in perfusate osmolarity have implied steric hindrance to small-molecule transcapillary exchange, but tracer methods do not. We obtained osmotic weight transient data in isolated, Ringer-perfused rabbit hearts with NaCl, urea, glucose, sucrose, raffinose, inulin, and albumin and analyzed the data with a new anatomically and physicochemically based model accounting for 1) transendothelial water flux, 2) two sizes of porous passages across the capillary wall, 3) axial intracapillary concentration gradients, and 4) water fluxes between myocytes and interstitium. During steady-state conditions approximately 28% of the transcapillary water flux going to form lymph was through the endothelial cell membranes [capillary hydraulic conductivity (Lp) = 1.8 +/- 0.6 x 10-8 cm. s-1. mmHg-1], presumably mainly through aquaporin channels. The interendothelial clefts (with Lp = 4.4 +/- 1.3 x 10-8 cm. s-1. mmHg-1) account for 67% of the water flux; clefts are so wide (equivalent pore radius was 7 +/- 0.2 nm, covering approximately 0.02% of the capillary surface area) that there is no apparent hindrance for molecules as large as raffinose. Infrequent large pores account for the remaining 5% of the flux. During osmotic transients due to 30 mM increases in concentrations of small solutes, the transendothelial water flux was in the opposite direction and almost 800 times as large and was entirely transendothelial because no solute gradient forms across the pores. During albumin transients, gradients persisted for long times because albumin does not permeate small pores; the water fluxes per milliosmolar osmolarity change were 200 times larger than steady-state water flux. The analysis completely reconciles data from osmotic transient, tracer dilution, and lymph sampling techniques.

Visualization-based analysis of multiparameter models using environment for N-dimensional model analysis

We present a methodology, based on N-dimensional computer visualization, for analyzing multiparameter models. This approach originally consisted of three steps: behavior analysis, sensitivity analysis, identifiability analysis. We have now developed a new way of calculating sensitivity based on the statistical measure of the coefficient of variation. Furthermore, we extended the methodology through the addition of an extra step, visual regression. Visual regression allows the user to visualize the process of actual parameter identification and presents a combined, empirical view of the first three steps in a single image. Next we applied this methodology to pulmonary capillary-transport models. Finally, we implemented the model analysis process as a stand-alone program. EN-DIMAN, the resulting software, allows researchers to carry out model analysis in a graphical user interface (GUI)-based environment.