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Mathematical and Computer Modelling of Dynamical Systems
Methods, Tools and Applications in Engineering and Related Sciences
Volume 21, 2015 - Issue 3
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Original Articles

Development of a macro-scale model from a meso-scale model for cell culture population dynamics

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Pages 228-250 | Received 30 Dec 2013, Accepted 24 May 2014, Published online: 23 Jun 2014

Figures & data

Figure 1. N × N grid representing the flask, each mesh referred to as ‘locus’.

Figure 1. N × N grid representing the flask, each mesh referred to as ‘locus’.

Figure 2. Approximate model of the q(t) as a function of total population p(t).

Figure 2. Approximate model of the q(t) as a function of total population p(t).

Figure 3. Meso-scale simulation results showing average toxicity ξt, its approximate lower bound ξmint and upper bound ξmaxt.

Figure 3. Meso-scale simulation results showing average toxicity ξt, its approximate lower bound ξmint and upper bound ξmaxt.

Figure 4. Energy histogram of the cells and the uniform distribution approximation.

Figure 4. Energy histogram of the cells and the uniform distribution approximation.

Figure 5. (a) Fraction of cells dΔdiv that will undergo mitotic division within the next dt for α > ε˙remt; (b) Fraction of cells dΔdie that will die within the next dt for α < ε˙remt.

Figure 5. (a) Fraction of cells dΔdiv that will undergo mitotic division within the next dt for α > ε˙remt; (b) Fraction of cells dΔdie that will die within the next dt for α < ε˙remt.

Figure 6. Time profile of (a) the population size pt, (b) the total toxicity ζt, (c) the upper boundary of energy distribution ηHt and (d) the lower boundary of energy distribution ηLt. These results are obtained for an initial population occupying 40% of the flask. (Meso-scale: ––, macro-scale approximation: –•–).

Figure 6. Time profile of (a) the population size pt, (b) the total toxicity ζt, (c) the upper boundary of energy distribution ηHt and (d) the lower boundary of energy distribution ηLt. These results are obtained for an initial population occupying 40% of the flask. (Meso-scale: ––, macro-scale approximation: –•–).

Figure 7. The performance criteria which evaluate how well the macro-scale model results (with α=1) resemble the meso-scale model results: (a) %RMS, (b) %pmax c) %td and d)%te as a function of initial occupation percentage of the flask.

Figure 7. The performance criteria which evaluate how well the macro-scale model results (with α=1) resemble the meso-scale model results: (a) %∈RMS, (b) %∈pmax c) %∈td and d)%∈te as a function of initial occupation percentage of the flask.

Figure 8. (a) Quiescent population size q versus p, (b) active population size (pq) versus p, where all are expressed as percentage of the flask. (Meso-scale: ––, macro-scale approximation: –•–).

Figure 8. (a) Quiescent population size q versus p, (b) active population size (p−q) versus p, where all are expressed as percentage of the flask. (Meso-scale: ––, macro-scale approximation: –•–).

Figure 9. Energy histograms at the (a) 1st, (b) 25th, (c) 45th, (d) 65th, (e) 85th and (f) 105th time steps for an initial population occupying 10% of the flask.

Figure 9. Energy histograms at the (a) 1st, (b) 25th, (c) 45th, (d) 65th, (e) 85th and (f) 105th time steps for an initial population occupying 10% of the flask.

Figure 10. Time profile of p(t) according to the meso-scale and macro-scale model for initial populations (a) 60% (b) 30% and (c) 6% of the flask. (Meso-scale: ––, macro-scale approximation: –•–).

Figure 10. Time profile of p(t) according to the meso-scale and macro-scale model for initial populations (a) 60% (b) 30% and (c) 6% of the flask. (Meso-scale: ––, macro-scale approximation: –•–).

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