Effect of supercooling and cell volume on intracellular ice formation
Bibliographic record
Abstract
Intracellular ice formation (IIF) has been linked to death of cells cryopreserved in suspension. It has been assumed that cells can be supercooled by 2 to 10°C before IIF occurs, but measurements of the degree of supercooling that cells can tolerate are often confounded by changing extracellular temperature and solutions of different osmolality (which affect the cell volume). The purpose of this study was to examine how the incidence of IIF in the absence of cryoprotectants is affected by the degree of supercooling and cell volume. Human umbilical vein endothelial cells were suspended in isotonic (300 mOsm) and hypertonic (∼600 to 700 mOsm) solutions and exposed to supercooling ranging from 2 to 10°C before extracellular ice was nucleated. The number of cells undergoing IIF was examined in a cryostage (based on the darkening of cells upon intracellular freezing ("flashing")) as a function of the degree of supercooling, and cell survival post-thaw was assessed using a membrane integrity assay. We found that while the incidence of IIF increased with supercooling in both isotonic and hypertonic solutions, it was higher in the isotonic solution at any given degree of supercooling. Since cells in hypertonic solution were shrunken due to water efflux, we hypothesized that the difference in IIF behavior could be attributed to the decreased volume of cells in the hypertonic solution. Our results confirm that cells with a smaller diameter before extracellular ice nucleation have a decreased probability of IIF and suggest that cell volume could play a more significant role in the incidence of IIF than the extracellular ice nucleation temperature.
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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 | 0.001 |
| 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".