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Updated: May 23, 2026
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The CryoAPEX Method for Electron Microscopy Analysis of Membrane Protein Localization Within Ultrastructurally-Preserved Cells
Published on: February 27, 2020
On the application of active learning and Gaussian processes in postcryopreservation cell membrane integrity
Mindaugas Norkus1, Damien Fay, Mary J Murphy
1Electrical & Electronic Engineering, School of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland. m.norkus1@nuigalway.ie
Summary
Elevated temperatures during stem cell cryopreservation damage cell integrity. Active learning with Gaussian Process models identified optimal sampling to reveal these detrimental effects on Mesenchymal Stem Cells (MSCs).
Area of Science:
- Biotechnology
- Cell Biology
- Regenerative Medicine
Background:
- Cell cryopreservation enables long-term storage of biological specimens.
- Stem cell cryostorage is crucial for regenerative medicine applications.
- Maintaining cell integrity post-cryopreservation is vital, but challenging due to temperature fluctuations.
Purpose of the Study:
- To apply active learning with Gaussian Process (GP) models to optimize experimental sampling for studying cryopreservation.
- To investigate the impact of elevated temperatures on the post-cryopreservation membrane integrity of Mesenchymal Stem Cells (MSCs).
Main Methods:
- Developed an active learning algorithm using a Gaussian Process (GP) model to identify high-information sampling locations.
- Conducted experiments on human bone marrow-derived MSCs subjected to temperature elevations (-40 to 20 °C) for 48 hours.
- Utilized the algorithm to maximize information gain from a limited experimental dataset.
Main Results:
- The active learning algorithm successfully identified optimal sampling points, maximizing the reduction in process response estimate variance.
- The developed GP model accurately characterized the relationship between temperature elevation and cell membrane integrity.
- Severe temperature elevations significantly and detrimentally affected the membrane integrity of cryopreserved MSCs.
Conclusions:
- Active learning is an effective strategy for optimizing experimental design in cell cryopreservation studies.
- Elevated temperatures during short-term handling pose a significant risk to the integrity of cryopreserved MSCs.
- Findings highlight the need for stringent temperature control during stem cell handling to preserve viability for regenerative medicine.
