Ice recrystallization inhibitors enable efficient cryopreservation of induced pluripotent stem cells: A functional and transcriptomic analysis
Bibliographic record
Abstract
• Cryopreservation protocols development for induced pluripotent stem cells (iPSCs). • We assessed ice recrystallization inhibitors (IRIs) for iPSCs cryopreservation. • We found that 15 mM IRIs in 5 % DMSO is an efficient iPSCs cryoprotective solution. • mRNA sequencing used to identify expression changes resulting from cryopreservation. • IRIs improves the utility, effectiveness, and efficiency of iPSCs cryopreservation. The successful use of human induced pluripotent stem cells (iPSCs) for research or clinical applications requires the development of robust, efficient, and reproducible cryopreservation protocols. After cryopreservation, the survival rate of iPSCs is suboptimal and cell line-dependent. We assessed the use of ice recrystallization inhibitors (IRIs) for cryopreservation of human iPSCs. A toxicity screening study was performed to assess specific small-molecule carbohydrate-based IRIs and concentrations for further evaluation. Then, a cryopreservation study compared the cryoprotective efficiency of 15 mM IRIs in 5 % or 10 % DMSO-containing solutions and with CryoStor® CS10. Three iPSC lines were cryopreserved as single-cell suspensions in the cryopreservation solutions and post-thaw characteristics, including pluripotency and differential gene expression were assessed. We demonstrate the fitness-for-purpose of 15 mM IRI in 5 % DMSO as an efficient cryoprotective solution for iPSCs in terms of post-thaw recovery, viability, pluripotency, and transcriptomic changes. This mRNA sequencing dataset has the potential to be used for molecular mechanism analysis relating to cryopreservation. Use of IRIs can reduce DMSO concentrations and its associated toxicities, thereby improving the utility, effectiveness, and efficiency of cryopreservation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".