Wheat enolase demonstrates potential as a non‐toxic cryopreservation agent for liver and pancreatic cells
Bibliographic record
Abstract
Cryopreservation is essential for long-term storage of cells and tissues, which can be used for clinical applications such as drug toxicity testing, human transplantation, reproductive, regenerative and transfusion medicine. It requires use of cryoprotectants (e.g. dimethyl disulfoxide (DMSO), glycerol) that protect cells and tissues from dehydration and damage caused by formation of intracellular ice during freezing. As an alternative to these cytotoxic cryoprotectants, we are developing new technology using natural substances produced by plants that survive freezing conditions. We previously showed that soluble protein extracts such as wheat protein extract (WPE) prepared from winter wheat plants can substitute for DMSO as a cryoprotectant for certain mammalian cell types. To identify novel cryoactive proteins, WPE was separated using different chromatographic procedures and cryoactive fractions were analyzed by mass spectrometry. The analysis revealed enolase as a potential wheat protein candidate. A recombinant enolase protein was prepared and was able to successfully cryopreserve rat hepatocytes and insulin-secreting INS832/13 pancreatic cells. Post-thaw cells had high viability and levels of metabolic activities. Cryopreserved cells were plateable and had good adherence and morphological properties. These results indicate that individual plant proteins such as enolase have promising potential as new, non-toxic technology for cryopreservation protocols used for clinical applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".