Modelling and simulation of the chondrocyte cell growth, glucose consumption and lactate production within a porous tissue scaffold inside a perfusion bioreactor

Hossain, Shakhawath; Bergstrom, Donald J.; Chen, Daniel

doi:10.1016/j.btre.2014.12.002

Cited by 36 publications

(18 citation statements)

References 35 publications

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“…The nutrient bath surrounding the construct was assumed to be well mixed, but we did not account for the effect of nutrient profusion on cell growth as in previous models (Chung et al, 2007;Hossain et al, 2015;Nava et al, 2013;Sacco et al, 2011). The nutrient concentration profile detailed in Appendix B is also independent of cell location.…”

Section: Resultsmentioning

confidence: 99%

A Hybrid Model of Cartilage Regeneration Capturing the Interactions Between Cellular Dynamics and Porosity

Cassani

Olson

2020

Bull Math Biol

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To accelerate the development of strategies for cartilage tissue engineering, models are necessary to investigate the interactions between cellular dynamics and scaffold porosity. In experiments, cells are seeded in a porous scaffold or hydrogel where over the time course of a month, the scaffold slowly degrades while cells divide and synthesize extracellular matrix constituents. We use an off-lattice cellular automaton framework to model the individual behavior of cells within the scaffold. The movement of cells and the ability to reproduce is determined by the nutrient profile in the construct and/or the local porosity, defined as the volume fraction of fluid in the surrounding region. A phenomenological approach is used to capture a continuous profile for the degrading scaffold and accumulating matrix, which will then change the local porosity throughout the construct. We parameterize the model by first matching total cell counts in the construct to chondrocytes seeded in a polyglycolic acid scaffold (Freed et al., 1994). We investigate the total cell count and location of different cell populations within the construct for different initial scaffold porosities. Similar to experiments, we observe cell counts that level off around day 15 with higher cell counts in scaffolds of higher initial solid volume fraction (lower porosity). Cell clustering is observed and characterized in regions at the edge of the construct that are close to the nutrient-rich medium in the fluid bath. Model results show that a bias in motion due to a sensitivity to porosity allows cells to move in a smarter or more optimal arrangement. We investigate the spatiotemporal distribution of cells as the cell reproduction rate, cell movement distance, and sensitivity to porosity is varied. We observe non monotonic changes in total cell counts within different regions of the construct due to the interplay between porosity and cellular movement. We also analyze the emergent average cell speed for different initial scaffold porosities, observing higher average cell speed over the course of 30 days for the lowest initial scaffold porosity. This model provides a framework to further investigate how changes in biological parameters such as cell division and movement can change the cellular count and distribution in scaffolds of different initial porosity.

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Section: Resultsmentioning

confidence: 99%

A Hybrid Model of Cartilage Regeneration Capturing the Interactions Between Cellular Dynamics and Porosity

Cassani

Olson

2020

Bull Math Biol

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“…This relationship is taken into account in the lactate production flux, qlac, as follows (Sengers et al 2005;Hossain et al 2015):…”

Section: Nutrient Transport and Uptakementioning

confidence: 99%

“…The metabolic ratio, Rprol,met, is dominated by Monod kinetics on growth stimulation by glucose availability and inhibition by excess lactate concentrations (Hossain et al 2015).…”

Section: Cell Growthmentioning

confidence: 99%

A mathematical model of tissue-engineered cartilage development under cyclic compressive loading

Bandeiras

Completo

2016

Biomech Model Mechanobiol

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In this work a coupled model of solute transport and uptake, cell proliferation, extracellular matrix synthesis and remodeling of mechanical properties accounting for the impact of mechanical loading is presented as an advancement of a previously validated coupled model for free-swelling tissue-engineered cartilage cultures. Tissue-engineering constructs were modeled as biphasic with a linear elastic solid, and relevant intrinsic mechanical stimuli in the constructs were determined by numerical simulation for use as inputs of the coupled model. The mechanical dependent formulations were derived from a calibration and parametrization dataset and validated by comparison of normalized ratios of cell counts, total glycosaminoglycans and collagen after 24-h continuous cyclic unconfined compression from another dataset. The model successfully fit the calibration dataset and predicted the results from the validation dataset with good agreement, with average relative errors up to 3.1 and 4.3 %, respectively. Temporal and spatial patterns determined for other model outputs were consistent with reported studies. The results suggest that the model describes the interaction between the simultaneous factors involved in in vitro tissue-engineered cartilage culture under dynamic loading. This approach could also be attractive for optimization of culture protocols, namely through the application to longer culture times and other types of mechanical stimuli.

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“…Moreover, the development of engineered construct largely depends on the hydrodynamic environment and adequate supply of nutrients, including oxygen and glucose, to the cells during cell culture in vitro. (9,10) However, owing to the avascular nature of tissue-engineered cartilage, the supply of nutrients and the metabolic waste removal depend on diffusion. This creates gradients of nutrients and waste throughout the entire engineered constructs.…”

Section: Introductionmentioning

confidence: 99%

“…(15) Through the creation of an in vitro cell culture process inside a bioreactor under dynamic flow conditions, it is possible to facilitate mass transfer and control both microenvironmental parameters, such as temperature, pH, pressure, oxygen tension, metabolites, regulatory molecules, shear stress, and electrical pacing, and aseptic parameters, such as feeding, waste removal, and sampling resulting in increased production of cartilage specific matrix, proteins. (3,10,14) There are several types of bioreactors used in tissue engineering. However, only bioreactors that have been used for cartilage tissue engineering will be discussed in this review.…”

Section: Introductionmentioning

confidence: 99%

Role of Bioreactors in Regeneration of Articular Cartilage

Yasmin¹,

Xiongbiao²

2016

Sensors and Materials

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Modelling and simulation of the chondrocyte cell growth, glucose consumption and lactate production within a porous tissue scaffold inside a perfusion bioreactor

Abstract: Graphical abstract

Cited by 36 publications

References 35 publications

A Hybrid Model of Cartilage Regeneration Capturing the Interactions Between Cellular Dynamics and Porosity

A Hybrid Model of Cartilage Regeneration Capturing the Interactions Between Cellular Dynamics and Porosity

A mathematical model of tissue-engineered cartilage development under cyclic compressive loading

Role of Bioreactors in Regeneration of Articular Cartilage

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