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Updated: Oct 16, 2025

Tissue Triage and Freezing for Models of Skeletal Muscle Disease

Tissue Triage and Freezing for Models of Skeletal Muscle Disease

Published on: July 15, 2014

General tissue mass transfer model for cryopreservation applications.

Ross M Warner¹, Robyn Shuttleworth², James D Benson²

¹School of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, Oregon.

Biophysical Journal

|October 18, 2021

Summary

Developing advanced cryopreservation methods is crucial for medicine and science. This study introduces a new mathematical model to improve cryoprotectant delivery in tissues, overcoming toxicity challenges for better organ preservation.

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Area of Science:

Biomedical Engineering
Cryobiology
Mathematical Modeling

Background:

Cryopreservation of tissues and organs is vital for medical and scientific advancement.
Vitrification offers promise but faces challenges due to cryoprotectant (CPA) toxicity.
Existing mass transfer models, like Fick's law, are insufficient for complex tissue environments.

Purpose of the Study:

To develop a comprehensive mass transfer model for CPA transport in tissues.
To address limitations of current models by incorporating tissue-specific factors.
To enable the design of less toxic CPA equilibration protocols for complex specimens.

Main Methods:

Augmented a previously developed acellular mass transfer model.
Incorporated cellular effects, fixed charges, and tissue size changes into the model.
Validated the model using articular cartilage and pancreatic islets as distinct tissue types.

Main Results:

The proposed model accurately predicts CPA concentration changes within tissues.
The model successfully predicts tissue size variations during CPA exposure.
Demonstrated applicability across diverse tissue types with different properties.

Conclusions:

A generalizable mass transfer model for tissues has been established.
This model provides a foundation for optimizing CPA delivery and reducing toxicity.
Advances in cryopreservation of complex biological specimens are facilitated by this new modeling approach.