Defining the optimal cryoprotectant and concentration for cryopreservation of limbal stem cells
Bibliographic record
Abstract
Limbal stem cell (LSC) deficiency causes progressive loss of vision but may be treated by transplant of autologous LSCs. Cryopreservation has the potential to indefinitely extend the lifespan of LSCs allowing re-transplant in case of graft failure. In this study, we aimed to identify the optimal cryoprotectant and cryoprotectant concentration for LSC cultures. Suspension cultures derived from cadaveric corneoscleral rims were cooled to 4 °C with Me2SO, propylene glycol or ethylene glycol at a concentration of 5%, 10% or 15%. Cell tolerance was measured in terms of membrane integrity, colony-forming efficiency and alamarBlue® reduction. Increasing cryoprotectant concentration above 5% reduced membrane integrity, metabolism and colony-forming efficiency. Cryoprotectant choice did not significantly influence these characteristics. Cells demonstrating Side Population were maintained after cryopreservation with 5% propylene glycol in vapour phase liquid nitrogen for 1 week, indicating that cryopreservation of LSCs with relatively low cryoprotectant concentration (5%) has promise in low-temperature eye banking.
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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 | 0.001 |
| 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 | 0.001 | 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".