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A MORPHOMETRIC STUDY ON THE THICKNESS OF THE PULMONARY AIR-BLOOD BARRIER

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Weibel, Ewald R., Knight, Bruce W.·1964·The Journal of Cell Biology

Abstract

A reliable knowledge of the thickness of the alveolo-capillary "membrane" or air-blood barrier is of physiologic interest since it is intimately related to a quantitative estimation of such functional events as gas diffusion or tissue metabolism in the lung. The characteristic thickness of the air-blood barrier with respect to gas diffusion is its harmonic mean thickness, while the arithmetic mean thickness is related to the mass of tissue building the barrier and consuming oxygen in the lung. Two morphometric methods are proposed by which these two dimensions can be estimated from random measurements in the electron microscope in a reliable, simple, and efficient manner. By applying these methods to three rat lungs the arithmetic mean thickness of the barrier was found to measure 1.25 µ, the harmonic mean thickness, 0.57 µ. On the basis of these measurements a geometric model of the barrier in the form of a corrugated membrane was derived. Its dimensions showed close similarity to those of the natural barrier. This analysis suggested furthermore that the gas conductance of the barrier is nearly optimal if one considers the mass of tissue and the minimal barrier thickness as fixed properties which are determined by other functional requirements on the alveolo-capillary membrane.

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Metadata

Authors
Weibel, E. R., & Knight, B. W.
Venue
The Journal of Cell Biology
Published
1964-06-01
Volume
21
Issue
3
Pages
367-384
ISSN
  • 0021-9525 (ISSN-L)
  • 1540-8140
OpenAlex
W1972244777
Cited by
372
References
0
FWCI
11.77
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A MORPHOMETRIC STUDY ON THE THICKNESS OF THE PULMONARY AIR-BLOOD BARRIER. https://app.cochat.ai/papers/10.1083/jcb.21.3.367
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Weibel, E. R., & Knight, B. W. (1964). A MORPHOMETRIC STUDY ON THE THICKNESS OF THE PULMONARY AIR-BLOOD BARRIER. The Journal of Cell Biology. https://doi.org/10.1083/jcb.21.3.367

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.