Literature DB >> 2589694

A dynamic nonlinear lumped parameter model for skeletal muscle circulation.

R Braakman1, P Sipkema, N Westerhof.   

Abstract

A dynamic nonlinear lumped parameter model of the circulation of skeletal muscle for constant vasoactive state is presented. This model consists of four compartments that represent the large arteries, the arterioles, the capillaries and venules, and the veins, respectively. The first compartment consists of a linear compliance (C1) and resistance (R1). The third compartment possesses no compliance and is represented by a linear resistance (R3). The second and fourth compartments each consist of a nonlinear pressure-volume relation, resulting in a pressure dependent compliance (C2, C4, respectively) and nonlinear resistance (R2, R4, respectively). The eleven model parameters were collected in a complementary way: they were partly obtained from a priori knowledge including information at the microscopic level, and partly determined by means of an estimation algorithm. Estimated values of the compliances (in cm3.kPa-1.100 g-1, 1 kPa = 7.5 mmHg) and resistances (in kPa.s.cm-3.100 g) at an (arterial) inflow pressure of 10 kPa and a (venous) outflow pressure of 0 kPa were: C1: 0.014; R1: 6.6; C2: 0.565; R2: 84.6; R3: 37.9; C4: 1.044; R4: 24.5. The model (with the nonlinear pressure-volume relations) is able to predict the static and dynamic instantaneous (i.e., for constant vasomotor tone) pressure-flow relation and the instantaneous zero flow pressure intercept. These phenomena are therefore not necessarily the result of the rheological properties of blood. The secondary or delayed dilatation upon a positive inflow pressure step (or negative step in venous pressure) is predicted by the model implying that delayed dilatation is not necessarily related to changes in vasomotor tone. Venous outflow delay, upon a positive inflow pressure step (starting from zero flow), is also predicted by the model.

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Year:  1989        PMID: 2589694     DOI: 10.1007/bf02367465

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  38 in total

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Journal:  Ann Biomed Eng       Date:  1989       Impact factor: 3.934

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  7 in total

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Journal:  Ann Biomed Eng       Date:  1992       Impact factor: 3.934

2.  Understanding the vascular environment of myofascial trigger points using ultrasonic imaging and computational modeling.

Authors:  Siddhartha Sikdar; Robin Ortiz; Tadesse Gebreab; Lynn H Gerber; Jay P Shah
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5.  Human cerebral venous outflow pathway depends on posture and central venous pressure.

Authors:  J Gisolf; J J van Lieshout; K van Heusden; F Pott; W J Stok; J M Karemaker
Journal:  J Physiol       Date:  2004-07-29       Impact factor: 5.182

6.  Modelling physiology of haemodynamic adaptation in short-term microgravity exposure and orthostatic stress on Earth.

Authors:  Parvin Mohammadyari; Giacomo Gadda; Angelo Taibi
Journal:  Sci Rep       Date:  2021-02-25       Impact factor: 4.379

7.  Distributed and Lumped Parameter Models for the Characterization of High Throughput Bioreactors.

Authors:  Laura Iannetti; Giovanna D'Urso; Gioacchino Conoscenti; Elena Cutrì; Rocky S Tuan; Manuela T Raimondi; Riccardo Gottardi; Paolo Zunino
Journal:  PLoS One       Date:  2016-09-26       Impact factor: 3.240

  7 in total

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