Improved Cryopreservation of Human Induced Pluripotent Stem Cell (iPSC) and iPSC-derived Neurons Using Ice-Recrystallization Inhibitors
Bibliographic record
Abstract
Human induced pluripotent stem cells (iPSCs) and iPSC-derived neurons (iPSC-Ns) represent a differentiated modality toward developing novel cell-based therapies for regenerative medicine. However, the successful application of iPSC-Ns in cell-replacement therapies relies on effective cryopreservation. In this study, we investigated the role of ice recrystallization inhibitors (IRIs) as novel cryoprotectants for iPSCs and terminally differentiated iPSC-Ns. We found that one class of IRIs, N-aryl-D-aldonamides (specifically 2FA), increased iPSC post-thaw viability and recovery with no adverse effect on iPSC pluripotency. While 2FA supplementation did not significantly improve iPSC-N cell post-thaw viability, we observed that 2FA cryopreserved iPSC-Ns re-established robust neuronal network activity and synaptic function much earlier compared to CS10 cryopreserved controls. The 2FA cryopreserved iPSC-Ns retained expression of key neuronal specific and terminally differentiated markers and displayed functional electrophysiological and neuropharmacological responses following treatment with neuroactive agonists and antagonists. We demonstrate how optimizing cryopreservation media formulations with IRIs represents a promising strategy to improve functional cryopreservation of iPSCs and post-mitotic iPSC-Ns, the latter of which have been challenging to achieve. Developing IRI enabling technologies to support an effective cryopreservation and an efficiently managed cryo-chain is fundamental to support the delivery of successful iPSC-derived therapies to the clinic.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".