Freezing of Living Cells and Organs: A great challenge for thermal science and technology
Bibliographic record
Abstract
Low temperature has been utilized to keep living cells and organs dormant but potential alive (i.e. cryopreservation) for tremendous scientific and biomedical applications, including biobanking, cellular/gene therapy, tissue engineering, regenerative medicine, stem-cell/organ transplantation, artificial organs, new drug development, and conservation of endangered species. However, there is a critical contradiction between the purpose of cryopreservation and the experimental findings that the living cells can be killed by the cryopreservation process itself. Contrary to popular belief, the challenge to cells during the cryopreservation is not their ability to endure storage at cryogenic temperatures (below -180 ); rather it is "the lethality" of heat-mass transfer process coupled with phase transitions within an intermediate zone of low temperature (-15 to -130 ) that a cell must traverse twice, once during cooling and once during warming. The central theme of this presentation is to report the speaker's research work on: (1) fundamental mechanisms of cryoinjury and cryoprotection, (2) micro-heatmass transfer and its great impact on cell survival during the cryopreservation processes; and (3) development of optimal and novel technology for the cryopreservation to prevent the cryoinjury and to ensure the survival of living cells and organs.
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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".