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Am J Physiol Lung Cell Mol Physiol. 2010 Dec;299(6):L898-904. doi: 10.1152/ajplung.00023.2010. Epub 2010 Sep 3.

Logarithmic superposition of force response with rapid length changes in relaxed porcine airway smooth muscle.

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1
Institute of Biomedical Technologies, Auckland University of Technology, New Zealand.

Abstract

We present a systematic quantitative analysis of power-law force relaxation and investigate logarithmic superposition of force response in relaxed porcine airway smooth muscle (ASM) strips in vitro. The term logarithmic superposition describes linear superposition on a logarithmic scale, which is equivalent to multiplication on a linear scale. Additionally, we examine whether the dynamic response of contracted and relaxed muscles is dominated by cross-bridge cycling or passive dynamics. The study shows the following main findings. For relaxed ASM, the force response to length steps of varying amplitude (0.25-4% of reference length, both lengthening and shortening) are well-fitted with power-law functions over several decades of time (10⁻² to 10³ s), and the force response after consecutive length changes is more accurately fitted assuming logarithmic superposition rather than linear superposition. Furthermore, for sinusoidal length oscillations in contracted and relaxed muscles, increasing the oscillation amplitude induces greater hysteresivity and asymmetry of force-length relationships, whereas increasing the frequency dampens hysteresivity but increases asymmetry. We conclude that logarithmic superposition is an important feature of relaxed ASM, which may facilitate a more accurate prediction of force responses in the continuous dynamic environment of the respiratory system. In addition, the single power-function response to length changes shows that the dynamics of cross-bridge cycling can be ignored in relaxed muscle. The similarity in response between relaxed and contracted states implies that the investigated passive dynamics play an important role in both states and should be taken into account.

PMID:
20817779
PMCID:
PMC3284315
DOI:
10.1152/ajplung.00023.2010
[Indexed for MEDLINE]
Free PMC Article
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