Abstract

Adipose-derived stem cells (ASCs) are clinically important in regenerative medicine as they are relatively easy to obtain, are characterized by low morbidity, and can differentiate into myogenic progenitor cells. Although studies have elucidated the principal markers, PAX7, Desmin, MyoD, and MHC, the underlying mechanisms are not completely understood. This motivates the application of computational methods to facilitate greater understanding of such processes. In the following, we present a multi-stage kinetic model comprising a system of ordinary differential equations (ODEs). We sought to model ASC differentiation using data from a static culture, where no strain is applied, and a dynamic culture, where 10% strain is applied. The coefficients of the equations have been modulated by those experimental data points. To correctly represent the trajectories, various switches and a feedback factor based on total cell number have been introduced to better represent the biology of ASC differentiation. Furthermore, the model has then been applied to predict ASC fate for strains different from those used in the experimental conditions and for times longer than the duration of the experiment. Analysis of the results reveals unique characteristics of ASC myogenesis under dynamic conditions of the applied strain.

Highlights

  • Adipose-derived stem cells (ASCs) obtained from lipoaspirate tissue provide an accessible, abundant source for autologous cells and have a great potential to tissue engineering and cell therapies [1,2,3]

  • It has been shown that during myogenesis, ASCs express the same myogenic markers (PAX7/3, Desmin, MyoD, and MHC) and exhibit similar morphological changes as satellite cells show in vivo [8, 9]

  • We propose a nonlinear model that has first been trained by our experimental data of ASC-myogenesis [8] and implemented to predict the kinetics for different dynamic conditions

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Summary

Introduction

Adipose-derived stem cells (ASCs) obtained from lipoaspirate tissue provide an accessible, abundant source for autologous cells and have a great potential to tissue engineering and cell therapies [1,2,3].

Results
Conclusion
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