Resistance to blood flow in peripheral vascular beds strongly influences cardiovascular function and the status of perfused tissues. The primary determinants of flow resistance are vascular networ structure, vessel diameters, and flow properties of blood. It is proposed to develop quantitative theoretical models for structural adaptation of microvascular networks and for blood flow in microvessels. ? ? Structural adaptation (vascular remodeling) allows long-term adjustment of flow resistance to ensure adequate and efficient distribution of flow, and to respond to changing demands, as during growth or following injury. Abnormal structural adaptation occurs in hypertension and other diseases. Theoretical models have been developed to predict steady-state distributions of vessel internal diameters in microvascular networks, resulting from structural adaptation in response to hemodynamic and metabolic stimuli. These models will be extended to include consideration of (i) the time-course of diameter changes; (ii) changes in wall thickness and their relation to diameter changes; (iii) loss or gain of segments in vascular networks (Specific Aim 1). Model predictions will be compared with observations in several tissues, including rat mesentery, mouse and rat skeletal muscle, and mouse subcutaneous tissue (Specific Aim 2). ? ? Microvessel walls are lined by a relatively thick glycocalyx or endothelial surface layer (ESL). Previous theoretical models have shown how the ESL can substantially increase flow resistance in capillaries. Models will be developed to predict resistance to blood flow in microvessels larger than capillaries, including effects of the endothelial surface layer (Specific Aim 3). ? ? In all these studies, emphasis will be placed on comparing the results with experimental findings, and on examining their physiological implications in normal and abnormal states including hypertension. This will be facilitated by well-established and active collaborations with experimental physiologists.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL034555-20
Application #
6746897
Study Section
Cardiovascular and Renal Study Section (CVB)
Program Officer
Goldman, Stephen
Project Start
1985-07-01
Project End
2006-06-30
Budget Start
2004-07-01
Budget End
2005-06-30
Support Year
20
Fiscal Year
2004
Total Cost
$151,500
Indirect Cost
Name
University of Arizona
Department
Physiology
Type
Schools of Medicine
DUNS #
806345617
City
Tucson
State
AZ
Country
United States
Zip Code
85721
Rasmussen, Peter M; Secomb, Timothy W; Pries, Axel R (2018) Modeling the hematocrit distribution in microcirculatory networks: A quantitative evaluation of a phase separation model. Microcirculation 25:e12445
Rasmussen, Peter M; Smith, Amy F; Sakadži?, Sava et al. (2017) Model-based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach. Microcirculation 24:
Dewhirst, Mark W; Secomb, Timothy W (2017) Transport of drugs from blood vessels to tumour tissue. Nat Rev Cancer 17:738-750
Reglin, Bettina; Secomb, Timothy W; Pries, Axel R (2017) Structural Control of Microvessel Diameters: Origins of Metabolic Signals. Front Physiol 8:813
Smith, Amy F; Nitzsche, Bianca; Maibier, Martin et al. (2016) Microvascular hemodynamics in the chick chorioallantoic membrane. Microcirculation 23:512-522
Secomb, Timothy W (2016) Hemodynamics. Compr Physiol 6:975-1003
Secomb, Timothy W; Pries, Axel R (2016) Microvascular Plasticity: Angiogenesis in Health and Disease--Preface. Microcirculation 23:93-4
Secomb, Timothy W (2016) A Green's function method for simulation of time-dependent solute transport and reaction in realistic microvascular geometries. Math Med Biol 33:475-494
Hariprasad, Daniel S; Secomb, Timothy W (2015) Prediction of noninertial focusing of red blood cells in Poiseuille flow. Phys Rev E Stat Nonlin Soft Matter Phys 92:033008
Pries, Axel R; Secomb, Timothy W (2014) Making microvascular networks work: angiogenesis, remodeling, and pruning. Physiology (Bethesda) 29:446-55

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