Inhibition of ice recrystallization and cryoprotective activity of wheat proteins in liver and pancreatic cells
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Bibliographic record
Abstract
Efficient cryopreservation of cells at ultralow temperatures requires the use of substances that help maintain viability and metabolic functions post-thaw. We are developing new technology where plant proteins are used to substitute the commonly-used, but relatively toxic chemical dimethyl sulfoxide. Recombinant forms of four structurally diverse wheat proteins, TaIRI-2 (ice recrystallization inhibition), TaBAS1 (2-Cys peroxiredoxin), WCS120 (dehydrin), and TaENO (enolase) can efficiently cryopreserve hepatocytes and insulin-secreting INS832/13 cells. This study shows that TaIRI-2 and TaENO are internalized during the freeze-thaw process, while TaBAS1 and WCS120 remain at the extracellular level. Possible antifreeze activity of the four proteins was assessed. The "splat cooling" method for quantifying ice recrystallization inhibition activity (a property that characterizes antifreeze proteins) revealed that TaIRI-2 and TaENO are more potent than TaBAS1 and WCS120. Because of their ability to inhibit ice recrystallization, the wheat recombinant proteins TaIRI-2 and TaENO are promising candidates and could prove useful to improve cryopreservation protocols for hepatocytes and insulin-secreting cells, and possibly other cell types. TaENO does not have typical ice-binding domains, and the TargetFreeze tool did not predict an antifreeze capacity, suggesting the existence of nontypical antifreeze domains. The fact that TaBAS1 is an efficient cryoprotectant but does not show antifreeze activity indicates a different mechanism of action. The cryoprotective properties conferred by WCS120 depend on biochemical properties that remain to be determined. Overall, our results show that the proteins' efficiencies vary between cell types, and confirm that a combination of different protection mechanisms is needed to successfully cryopreserve mammalian cells.
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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 | 0.001 |
| 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 it