In vivo evaluation of oxygen consumption by arteriolar walls in skeletal muscle

M. Shibata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

To estimate the oxygen consumption rate of arteriolar walls we measured the intra- and perivascular partial oxygen tension (PO2) of arterioles in rat cremaster muscle, both at resting and vasodilating states by phosphorescence quenching technique. Using measured intra- and perivascular PO2 values, oxygen consumption rates were determined based on Krogh-Erlang analysis. We found a significant drop in PO2 in the arterioles after branching. We found that the vascular oxygen consumption rates of functional arterioles were 100-1000 times greater than those seen in in vitro experiments. These results strongly support the hypothesis that arteriolar walls consume a significant amount of oxygen as compared with the surrounding tissue. Furthermore, the reduction of vascular tone of arteriolar walls may facilitate an efficient supply of oxygen to the surrounding tissue.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2306-2307
Number of pages2
ISBN (Print)0780387406, 9780780387409
DOIs
Publication statusPublished - 2005 Jan 1
Externally publishedYes
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 2005 Sept 12005 Sept 4

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Conference

Conference2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period05/9/105/9/4

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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