Cell dynamics of smooth muscle cells and osteoblasts for tissue engineering applications

Ali A. Salifu, Yahya A. Elsayed, Constantina Lekakou, Fatima Labeed, Paul Tomlins

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The relationship between cellular oxygen consumption and cell growth is important for modelling and simulating tissue engineering processes but there is a lack of comprehensive data for cell growth as a function of oxygen consumption in the literature for human smooth muscle cells and osteoblasts. Cell growth was monitored as a function of oxygen concentration in the culture medium for human umbilical vein smooth muscle cells (HUVSMCs) and human foetal osteoblasts (hFOBs). The yield coefficients, coefficients of oxygen consumption, oxygen consumption constants, cell growth constants and specific oxygen uptake rates were determined for the cells. Cell concentration and oxygen concentration data were fitted to models for cell growth and oxygen consumption. The Monod model for cell growth rate was fitted as a function of oxygen consumption rate and cell concentration for the HUVSMCs whereas two different models were used to best fit the oxygen consumption rate as a function of cell growth rate and cell concentration for the hFOBs. These models can be utilised to predict cell growth and oxygen consumption parameters for HUVSMC and hFOB cells which may be useful for simulating vascular and bone tissue engineering processes respectively.

Original languageEnglish
Pages (from-to)504-510
Number of pages7
JournalJournal of Biomaterials and Tissue Engineering
Volume7
Issue number6
DOIs
Publication statusPublished - Jun 2017
Externally publishedYes

Keywords

  • Cell growth
  • Modelling
  • Monod model
  • Osteoblast
  • Oxygen consumption
  • Smooth muscle cell

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Medicine (miscellaneous)
  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Cell dynamics of smooth muscle cells and osteoblasts for tissue engineering applications'. Together they form a unique fingerprint.

Cite this