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Pairing computational and scaled physical models to determine permeability as a measure of cellular communication in micro- and nano-scale pericellular spaces

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Abstract

Cells, the living components of tissues, bathe in fluid. The pericellular fluid environment is a challenge to study due to the remoteness and complexity of its nanoscale fluid pathways. The degree to which the pericellular fluid environment modulates the transport of mechanical and molecular signals between cells and across tissues is unknown. As a consequence, experimental and computational studies have been limited and/or highly idealized. In this study we apply a fundamental fluid dynamics technique to measure pericellular permeability through scaled-up physical models obtained from high resolution microscopy. We assess permeability of physiologic tissue by tying together data from parallel experimental and computational models that account for specific structures of the flow cavities and cellular structures therein (cell body, cell process, pericellular matrix). A healthy cellular network devoid of cellular structure is shown to exhibit permeability on the order of 2.8 × 10−16 m2; inclusion of cellular structures reduces permeability to the order of 10−17 to 10−18 m2. These permeability studies provide not only unprecedented quantitative experimental measures of the pericellular fluid environment but also provide a novel measure of “infrastructural integrity” that likely influences the efficiency of the cellular communication network across the tissue.

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Abbreviations

μ :

viscosity of fluid

ρ :

density of fluid

k :

intrinsic permeability of specimen

κ :

hydraulic conductivity

Q :

volume flow rate

L :

length of specimen

t :

permeation/diffusion time

g :

gravitational constant

h :

height above specimen surface

V :

velocity

P :

inlet pressure

p :

fluid pressure

ε:

characteristic pore/channel dimension

Re :

Reynolds number

\( \dot{m} \) :

mass flow rate

A :

cross-sectional area of specimen

u :

axial pipe velocity

R :

radius of pericellular channel

z :

axial pipe coordinate

r :

radial pipe coordinate

C :

concentration

D :

diffusion coefficient

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Acknowledgements

This study has been funded in part by National Institutes of Health (AR 049351-01) and The Whitaker Foundation (RG-02-0527). The authors would like to acknowledge and thank Dr. Malcolm Cooke for his support in creating the rapid prototype experimental models, and Dr. Joseph Prahl for his comments and suggestions. This investigation was conducted in a facility constructed with support from Research Facilities Improvement Program Grant Number C06 RR12463-01 from the National Center for Research Resources, National Institutes of Health.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA

    Eric J. Anderson, Steven M. Kreuzer & Melissa L. Knothe Tate

  2. Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Olin 219, Cleveland, OH, 44106, USA

    Oliver Small & Melissa L. Knothe Tate

Authors
  1. Eric J. Anderson
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  2. Steven M. Kreuzer
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  3. Oliver Small
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  4. Melissa L. Knothe Tate
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Corresponding author

Correspondence to Melissa L. Knothe Tate.

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Funding: National Institutes of Health, The Whitaker Foundation.

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Anderson, E.J., Kreuzer, S.M., Small, O. et al. Pairing computational and scaled physical models to determine permeability as a measure of cellular communication in micro- and nano-scale pericellular spaces . Microfluid Nanofluid 4, 193–204 (2008). https://doi.org/10.1007/s10404-007-0156-5

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  • DOI: https://doi.org/10.1007/s10404-007-0156-5

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