Literature DB >> 26055347

A triphasic constrained mixture model of engineered tissue formation under in vitro dynamic mechanical conditioning.

Joao S Soares1, Michael S Sacks2.   

Abstract

While it has become axiomatic that mechanical signals promote in vitro engineered tissue formation, the underlying mechanisms remain largely unknown. Moreover, efforts to date to determine parameters for optimal extracellular matrix (ECM) development have been largely empirical. In the present work, we propose a two-pronged approach involving novel theoretical developments coupled with key experimental data to develop better mechanistic understanding of growth and development of dense connective tissue under mechanical stimuli. To describe cellular proliferation and ECM synthesis that occur at rates of days to weeks, we employ mixture theory to model the construct constituents as a nutrient-cell-ECM triphasic system, their transport, and their biochemical reactions. Dynamic conditioning protocols with frequencies around 1 Hz are described with multi-scale methods to couple the dissimilar time scales. Enhancement of nutrient transport due to pore fluid advection is upscaled into the growth model, and the spatially dependent ECM distribution describes the evolving poroelastic characteristics of the scaffold-engineered tissue construct. Simulation results compared favorably to the existing experimental data, and most importantly, distinguish between static and dynamic conditioning regimes. The theoretical framework for mechanically conditioned tissue engineering (TE) permits not only the formulation of novel and better-informed mechanistic hypothesis describing the phenomena underlying TE growth and development, but also the exploration/optimization of conditioning protocols in a rational manner.

Entities:  

Keywords:  Functional tissue engineering; Growth and remodeling; Heart valve; Multi-scale modeling; Poroelasticity; Reaction-diffusion

Mesh:

Substances:

Year:  2015        PMID: 26055347      PMCID: PMC4712131          DOI: 10.1007/s10237-015-0687-8

Source DB:  PubMed          Journal:  Biomech Model Mechanobiol        ISSN: 1617-7940


  63 in total

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