Trehalose-Based Polyethers for Cryopreservation and Three-Dimensional Cell Scaffolds
Bibliographic record
Abstract
The capability to slow ice growth and recrystallization is compulsory in the cryopreservation of cells and tissues to avoid injuries associated with the physical and chemical responses of freezing and thawing. Cryoprotective agents (CPAs) have been used to restrain cryoinjury and improve cell survival, but some of these compounds pose greater risks for the clinical application of cryopreserved cells due to their inherent toxicity. Trehalose is known for its unique physicochemical properties and its interaction with the phospholipids of the plasma membrane, which can reduce cell osmotic stress and stabilized the cryopreserved cells. Nonetheless, there has been a shortage of relevant studies on the synthesis of trehalose-based CPAs. We hereby report the synthesis and evaluation of a trehalose-based polymer and hydrogel and its use as a cryoprotectant and three-dimensional (3D) cell scaffold for cell encapsulation and organoid production. In vitro cytotoxicity studies with the trehalose-based polymers (poly(Tre-ECH)) demonstrated biocompatibility up to 100 mg/mL. High post-thaw cell membrane integrity and post-thaw cell plating efficiencies were achieved after 24 h of incubation with skin fibroblast, HeLa (cervical), and PC3 (prostate) cancer cell lines under both controlled-rate and ultrarapid freezing protocols. Differential scanning calorimetry and a splat cooling assay for the determination of ice recrystallization inhibition activity corroborated the unique properties of these trehalose-based polyethers as cryoprotectants. Furthermore, the ability to form hydrogels as 3D cell scaffolds encourages the use of these novel polymers in the development of cell organoids and cryopreservation platforms.
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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".